Docs
- + diff --git a/docs/advanced-settings/module-development/index.html b/docs/advanced-settings/module-development/index.html index dcb48130..0f1cab17 100644 --- a/docs/advanced-settings/module-development/index.html +++ b/docs/advanced-settings/module-development/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/advanced-settings/overview/index.html b/docs/advanced-settings/overview/index.html index 1da793f1..76e904e4 100644 --- a/docs/advanced-settings/overview/index.html +++ b/docs/advanced-settings/overview/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/advanced-settings/partial-development/index.html b/docs/advanced-settings/partial-development/index.html index e4b6e665..a2f5e436 100644 --- a/docs/advanced-settings/partial-development/index.html +++ b/docs/advanced-settings/partial-development/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/advanced-settings/scripts/index.html b/docs/advanced-settings/scripts/index.html index 2df99995..539336c1 100644 --- a/docs/advanced-settings/scripts/index.html +++ b/docs/advanced-settings/scripts/index.html @@ -25,7 +25,7 @@ - + @@ -1255,7 +1255,7 @@Docs
- + diff --git a/docs/advanced-settings/styles/index.html b/docs/advanced-settings/styles/index.html index 8cbb33d3..b1a763e5 100644 --- a/docs/advanced-settings/styles/index.html +++ b/docs/advanced-settings/styles/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/configuration/colors/index.html b/docs/configuration/colors/index.html index 3a144619..2f772a71 100644 --- a/docs/configuration/colors/index.html +++ b/docs/configuration/colors/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/configuration/layout/index.html b/docs/configuration/layout/index.html index 4b42d8b4..130f518d 100644 --- a/docs/configuration/layout/index.html +++ b/docs/configuration/layout/index.html @@ -25,7 +25,7 @@ - + @@ -1244,7 +1244,7 @@Docs
- + diff --git a/docs/developing/index.html b/docs/developing/index.html index bfd91499..33f4bc63 100644 --- a/docs/developing/index.html +++ b/docs/developing/index.html @@ -25,7 +25,7 @@ - + @@ -1408,7 +1408,7 @@Class Interface Specifica
-
+
diff --git a/docs/getting-started/command-line/index.html b/docs/getting-started/command-line/index.html
index c75901dd..fa323b67 100644
--- a/docs/getting-started/command-line/index.html
+++ b/docs/getting-started/command-line/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/getting-started/compiling/index.html b/docs/getting-started/compiling/index.html
index 53df7956..67eedb0c 100644
--- a/docs/getting-started/compiling/index.html
+++ b/docs/getting-started/compiling/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1851,7 +1851,7 @@ Compiling
+
diff --git a/docs/getting-started/contribute/index.html b/docs/getting-started/contribute/index.html
index 30d71d5f..8e6f188f 100644
--- a/docs/getting-started/contribute/index.html
+++ b/docs/getting-started/contribute/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1906,7 +1906,7 @@ License
+
diff --git a/docs/getting-started/introduction/index.html b/docs/getting-started/introduction/index.html
index 4381428f..a55cc3e0 100644
--- a/docs/getting-started/introduction/index.html
+++ b/docs/getting-started/introduction/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1391,7 +1391,7 @@ Running OpenSees
+
diff --git a/docs/getting-started/modeling/index.html b/docs/getting-started/modeling/index.html
index 708dfb34..64f263f5 100644
--- a/docs/getting-started/modeling/index.html
+++ b/docs/getting-started/modeling/index.html
@@ -25,7 +25,7 @@
-
+
@@ -913,10 +913,44 @@ Docs
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ On this page
+
+
+
+
+
+
-Modeling in Python
+Modeling in Python
-
+
The best practice for modeling in Python is to create a model class
by calling the opensees.openseespy.Model(...) constructor (note the capital “M”).
All standard OpenSees functions, as documented
@@ -934,9 +968,9 @@
Modeling in Python import opensees.openseespy as ops
model = ops.Model(ndm=2, ndf=3)
model.node(1, 2.0, 3.0)
-Evaluate Tcl models from Python
+Evaluate Tcl models from Python
-
+
The first scripting interface to OpenSees used a programming language
called Tcl, which continues to be supported.
To execute Tcl commands from a Python script, just create an instance
@@ -978,6 +1012,13 @@
Evaluate Tcl models fro
+On this page:
+
@@ -1267,6 +1308,7 @@ Evaluate Tcl models fro
Evaluate Tcl models fro
-
+
diff --git a/docs/getting-started/python/index.html b/docs/getting-started/python/index.html
index 1eb0812e..373408f9 100644
--- a/docs/getting-started/python/index.html
+++ b/docs/getting-started/python/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/frame/index.html b/docs/library/frame/index.html
index 7f72fe7c..daf49d69 100644
--- a/docs/library/frame/index.html
+++ b/docs/library/frame/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/index.html b/docs/library/index.html
index b031e19b..1266f15e 100644
--- a/docs/library/index.html
+++ b/docs/library/index.html
@@ -25,7 +25,7 @@
-
+
@@ -749,7 +749,7 @@
-
+
diff --git a/examples/archstaticsnap/IncrementalAnalysis.ipynb b/examples/archstaticsnap/IncrementalAnalysis.ipynb
index 3f55332c..3f23dc69 100644
--- a/examples/archstaticsnap/IncrementalAnalysis.ipynb
+++ b/examples/archstaticsnap/IncrementalAnalysis.ipynb
@@ -1,26 +1,31 @@
{
"cells": [
- {
- "cell_type": "markdown",
- "id": "44f24cf9-aad0-4929-b3b7-b4103654238a",
- "metadata": {},
- "source": [
- "# Incremental Analysis of a Shallow Arch"
- ]
- },
{
"cell_type": "markdown",
"id": "b6909664-24e3-401c-b176-49ee45890e58",
"metadata": {},
"source": [
- "[](https://mybinder.org/v2/gh/claudioperez/opensees/HEAD?labpath=notebooks%2FIncrementalAnalysis%2FIncrementalAnalysis.ipynb)\n",
+ "\n",
+ "\n",
+ "In this problem, we investigate how this programmatic interface can be used to solve a highly nonlinear problem.\n",
+ "Consider the shallow arch shown below (Clarke and Hancock, 1990):\n",
"\n",
"\n",
"\n",
- "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n",
+ "This problem exhibits several critical points along the solution path,\n",
+ "and requires the use of a sophisticated algorithm to properly traverse these.\n",
+ "In this study, we will investigate how the OpenSees framework can be used to compose these algorithms.\n",
"\n",
+ "We will perform the analysis by creating an OpenSees `Model` data structure, and using\n",
+ "its *methods* to perform various tasks. A method is simply a function that\n",
+ "is linked to a particular instance of a data structure. In this case, the `Model`\n",
+ "data structure holds the geometry and state (i.e., the current values of solution variables) of our structural model. Some methods that you might see being used in this notebook include (you wont need to make any changes to the use of any of these):\n",
"\n",
- "Begin by importing the `arch_model` helper function from the file [`arch.py`](./arch.py):"
+ "- `Model.integrator(...)` This method configures the iteration strategy to be performed\n",
+ " in the next increment\n",
+ "- `Model.analyze(n)` This method applies `n` increments, and between each increment, performs Newton-Raphson iterations.\n",
+ "\n",
+ "In this notebook, the `Model` data structure is created by the `arch_model` helper function, which we load from the file [`arch.py`](./arch.py):"
]
},
{
@@ -38,7 +43,7 @@
"id": "1f478018-476b-44b4-aa2f-5deb49037670",
"metadata": {},
"source": [
- "Import some helpful third-party libraries"
+ "We'll also find the following imports convenient:"
]
},
{
@@ -53,7 +58,7 @@
"\n",
"try:\n",
" import scienceplots\n",
- " plt.style.use(\"steel\") #([\"ieee\", \"science\", \"notebook\"])\n",
+ " plt.style.use([\"steel\"]) #([\"ieee\", \"science\", \"notebook\"])\n",
"except:\n",
" pass"
]
@@ -63,7 +68,18 @@
"id": "adfeaf3b-6027-42ea-96e2-eac362168c2a",
"metadata": {},
"source": [
- "## The Framework"
+ "## Solution Strategy\n",
+ "\n",
+ "Our general strategy is implemented in the following function `solve()`.\n",
+ "This function adopts an incremental approach\n",
+ "where the load is applied in small steps of varying size. \n",
+ "The arguments to the function are:\n",
+ "\n",
+ "- `model`: an OpenSees `Model` object\n",
+ "- `node` : an integer indicating which node to collect results from.\n",
+ "\n",
+ "Both of these arguments will be supplied by the `arch_model` helper function mentioned\n",
+ "above.\n"
]
},
{
@@ -74,25 +90,29 @@
"outputs": [],
"source": [
"def analyze(model, mid, increment, steps, dx, *args):\n",
- " dof = 2\n",
+ " # Initialize some variables\n",
+ " xy = [] # Container to hold solution history (i.e., load factor and displacement at `node`)\n",
+ " status = 0 # Convergence flag; Model.analyze() will return 0 if successful.\n",
"\n",
- " xy = []\n",
- "\n",
- " status = 0\n",
- "\n",
- " increment(model, mid, dof, dx, *args)\n",
+ " # Configure the first load increment strategy; explained below\n",
+ " increment(model, dx, *args)\n",
"\n",
" for step in range(steps):\n",
- " if status != 0:\n",
- " dx /= 2\n",
- " increment(model, mid, dof, dx, *args)\n",
"\n",
+ " # 1. Perform Newton-Raphson iterations until convergence for 1 load\n",
+ " # increment\n",
" status = model.analyze(1)\n",
"\n",
- " xy.append([model.nodeDisp(mid, dof), model.getTime()])\n",
+ " # 2. Store the displacement and load factor\n",
+ " xy.append([model.nodeDisp(mid, 2), model.getTime()])\n",
"\n",
+ " # 3. If the iterations failed, try cutting\n",
+ " # the increment arc-length in half\n",
+ " if status != 0:\n",
+ " dx /= 2\n",
+ " increment(model, dx, *args)\n",
"\n",
- " return np.array(xy).T\n"
+ " return np.array(xy).T"
]
},
{
@@ -109,9 +129,9 @@
"Load incrementation strategy: Direct incrementation of the load parameter (Section 4.1.1)\n",
"\n",
"Solution 2 \n",
- "Iterative strategy: Constant vertical displacement under the load, $v_6$ (Section 3.2)\n",
+ "Iterative strategy: Constant vertical displacement under the load, $u_{\\mathrm{mid}}$ (Section 3.2)\n",
"
\n",
- "Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)\n",
+ "Load incrementation strategy: Incrementation of the displacement component $u_{\\mathrm{mid}}$ (Section 4.1.2)\n",
" \n",
"Solution 3 \n",
"Iterative strategy: Constant arc-length (Section 3.3)\n",
@@ -153,27 +173,28 @@
"metadata": {},
"outputs": [],
"source": [
- "def solution0(model, mid, dof, dx):\n",
+ "def solution0(model, dx):\n",
" model.integrator(\"LoadControl\", 400.0)\n",
"\n",
"\n",
- "def solution1(model, mid, dof, dx):\n",
+ "def solution1(model, dx):\n",
" Jd = 5\n",
" model.integrator(\"LoadControl\", dx, Jd, -800., 800.)\n",
"\n",
"\n",
- "def solution2(model, mid, dof, dx):\n",
+ "def solution2(model, dx, *args):\n",
" Jd = 5\n",
+ " mid, dof = args\n",
" model.integrator(\"DisplacementControl\", mid, dof, dx, Jd)\n",
"\n",
"\n",
- "def norm_control(model, mid, dof, dx):\n",
+ "def norm_control(model, dx, *args):\n",
" Jd = 15\n",
- " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, \"-det\")\n",
+ " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, det=True)\n",
"\n",
"\n",
- "def arc_control(model, mid, dof, dx, a):\n",
- " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.5, reference=\"point\")\n"
+ "def arc_control(model, dx, *args, a=0):\n",
+ " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.0, reference=\"point\")\n"
]
},
{
@@ -182,30 +203,9 @@
"id": "7024dd88-cf13-4c48-a73e-9cdba805dd28",
"metadata": {},
"outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 49845.5, Norm deltaX: 152.498\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 11340.8, Norm deltaX: 123.419\n",
- "ArcLength::update() - imaginary roots due to multiple instability directions - initial load increment was too large\n",
- "a: 6.20586 b: -2674.5 c: 319258 b24ac: -772128\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 3293.9, Norm deltaX: 54.5382\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- },
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -224,24 +224,25 @@
"# ax.plot(-x, y, 'x', label=\"S1\")\n",
"# print(y)\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 7, -150)\n",
+ "model, mid = arch_model()\n",
+ "x, y = analyze(model, mid, solution2, 7, -150, *(mid, 2))\n",
"ax.plot(-x, y, 'o', label=\"S2\")\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 536, -1.5)\n",
+ "x, y = analyze(*arch_model(), solution2, 536, -1.5, *(mid, 2))\n",
"ax.plot(-x, y, '-', label=\"S2\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 9500, 0.5, 0)\n",
"# ax.plot(-x, y, \"-\", label=\"arc\")\n",
"\n",
- "# Requires -det\n",
- "x, y = analyze(*arch_model(), arc_control, 110, 45, 0)\n",
+ "\n",
+ "x, y = analyze(*arch_model(), arc_control, 110, 45)\n",
"ax.plot(-x, y, \"x\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
- "ax.plot(-x, y, \"+\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
+ "# ax.plot(-x, y, \"+\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
- "ax.plot(-x, y, \"*\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
+ "# ax.plot(-x, y, \"*\", label=\"arc\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 8000, 0.8, 0)\n",
"# ax.plot(-x, y, \"x\", label=\"arc\")\n",
@@ -250,30 +251,24 @@
"# ax.plot(-x, y, \"-\", label=\"norm\")\n",
"\n",
"\n",
+ "ax.set_title(\"Displacement vs Load Factor\")\n",
+ "ax.set_ylabel(r\"Load factor $\\lambda$\")\n",
+ "ax.set_xlabel(\"Displacement $u$\")\n",
+ "\n",
"ax.set_xlim([0, 1200])\n",
"ax.set_ylim([-800, 3000])\n",
- "fig.legend()"
+ "fig.legend();"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"id": "f0b43af2-dc3c-4a40-a1fd-e11e46f23206",
"metadata": {},
"outputs": [
{
"data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -283,28 +278,11 @@
}
],
"source": [
- "plt.plot(-x, '.')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "5fa5cc7e-f3ae-4d36-95dc-b2a45074d3ec",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "ax.plot(-x, \".\")"
+ "fix, ax = plt.subplots()\n",
+ "ax.plot(-x, '.');\n",
+ "ax.set_title(\"Displacement vs Step Number\")\n",
+ "ax.set_ylabel(\"Displacement $u$\")\n",
+ "ax.set_xlabel(\"Analysis step $n$\");"
]
},
{
@@ -320,16 +298,19 @@
"id": "21bf025c-2023-4ea6-adf2-56f452f304b5",
"metadata": {},
"source": [
- ""
+ "![](\"arch.gif\")
"
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "1f5c771b-31ef-4f62-9f8b-7cc7bb392184",
+ "cell_type": "markdown",
+ "id": "732dc061-374d-41e6-935a-f82c88f758fe",
"metadata": {},
- "outputs": [],
- "source": []
+ "source": [
+ "## References\n",
+ "\n",
+ "\n",
+ "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n"
+ ]
}
],
"metadata": {
diff --git a/examples/archstaticsnap/arch.py b/examples/archstaticsnap/arch.py
index 61c7635e..176d57a4 100644
--- a/examples/archstaticsnap/arch.py
+++ b/examples/archstaticsnap/arch.py
@@ -9,11 +9,6 @@ def arch_model():
Rise = 500
Offset = 200
- # Define material parameters
- E = 200
- A = 1e4
- I = 1e8
-
# Compute radius
R = Rise/2 + (2*L)**2/(8*Rise)
th = 2*np.arcsin(L/R)
@@ -43,14 +38,19 @@ def arch_model():
# create the node
model.node(tag, x, y)
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
# Create elements
- transfTag = 1
- model.geomTransf("Corotational", transfTag)
+ transf = 1
+ model.geomTransf("Corotational", transf)
for i in range(ne):
tag = i+1
nodes = (i+1, i+2)
- model.element("ElasticBeamColumn", tag, *nodes, A, E, I, transfTag)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
model.fix( 1, 1, 1, 0)
@@ -63,12 +63,14 @@ def arch_model():
model.load(mid, 0.0, -1.0, 0.0, pattern=1)
- model.system("ProfileSPD")
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
# model.system("FullGeneral")
# model.system("BandGeneral")
- # model.system("Umfpack", det=True)
+ model.system("Umfpack", det=True)
- model.test("NormUnbalance", 1e-6, 25, 0)
+ model.test("NormUnbalance", 1e-6, 25, 9)
model.algorithm("Newton")
model.analysis("Static")
diff --git a/examples/archstaticsnap/index.html b/examples/archstaticsnap/index.html
index caeb7e41..cf61524b 100644
--- a/examples/archstaticsnap/index.html
+++ b/examples/archstaticsnap/index.html
@@ -25,7 +25,7 @@
-
+
@@ -52,7 +52,7 @@
-
+
@@ -110,7 +110,7 @@
"about": {
"@id": "https://stairlab.github.io/#/schema/organization/1"
},
- "dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
+ "dateModified": "2024-10-11T00:55:08CET","breadcrumb": {
"@id": "https://stairlab.github.io/opensees-gallery/examples/archstaticsnap/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
@@ -354,8 +354,8 @@
- 3 min read •
- 569 words
+ 6 min read •
+ 1,092 words
@@ -506,25 +506,46 @@
-
+
+
-Incremental Analysis of a Shallow Arch
-
-
-
-
-
+
+
+
+ On this page
+
+
+
+
+
+
+The files for this example are:
+
+-
+
@@ -533,21 +554,135 @@
Incremental Anal
+
+
+
+
+
+ arch.py - This file contains the function arch_model which is used construct the model
+-
+
+
-
+
+
+
+
+
+
IncrementalAnalysis.ipynb - This is the current Jupyter notebook file
+
+
+
+
+
+
+
+ import numpy as np
+import opensees.openseespy
+
+# Create the model
+def arch_model():
+
+ # Define model parameters
+ L = 5000
+ Rise = 500
+ Offset = 200
+
+ # Compute radius
+ R = Rise/2 + (2*L)**2/(8*Rise)
+ th = 2*np.arcsin(L/R)
+
+ #
+ # Build the model
+ #
+ model = opensees.openseespy.Model(ndm=2, ndf=3)
+
+ # Create nodes
+ ne = 10
+ nen = 2 # nodes per element
+ nn = ne*(nen-1)+1
+ mid = (nn+1)//2 # midpoint node
+
+ for i, angle in enumerate(np.linspace(-th/2, th/2, nn)):
+ tag = i + 1
+
+ # Compute x and add offset if midpoint
+ x = R*np.sin(angle)
+ if tag == mid:
+ x -= Offset
+
+ # Compute y
+ y = R*np.cos(angle)
+
+ # create the node
+ model.node(tag, x, y)
+
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
+
+ # Create elements
+ transf = 1
+ model.geomTransf("Corotational", transf)
+ for i in range(ne):
+ tag = i+1
+ nodes = (i+1, i+2)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
+
+
+ model.fix( 1, 1, 1, 0)
+ model.fix(nn, 1, 1, 0)
+
+ # Create a load pattern that scales linearly
+ model.pattern("Plain", 1, "Linear")
+
+ # Add a nodal load to the pattern
+ model.load(mid, 0.0, -1.0, 0.0, pattern=1)
+
+
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
+ # model.system("FullGeneral")
+ # model.system("BandGeneral")
+ model.system("Umfpack", det=True)
+
+ model.test("NormUnbalance", 1e-6, 25, 9)
+ model.algorithm("Newton")
+ model.analysis("Static")
+
+
+ return model, mid
+
+
+
+
+
+
-
-
-
-
-
+
License
+
diff --git a/docs/getting-started/introduction/index.html b/docs/getting-started/introduction/index.html
index 4381428f..a55cc3e0 100644
--- a/docs/getting-started/introduction/index.html
+++ b/docs/getting-started/introduction/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1391,7 +1391,7 @@ Running OpenSees
+
diff --git a/docs/getting-started/modeling/index.html b/docs/getting-started/modeling/index.html
index 708dfb34..64f263f5 100644
--- a/docs/getting-started/modeling/index.html
+++ b/docs/getting-started/modeling/index.html
@@ -25,7 +25,7 @@
-
+
@@ -913,10 +913,44 @@ Docs
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ On this page
+
+
+
+
+
+
-Modeling in Python
+Modeling in Python
-
+
The best practice for modeling in Python is to create a model class
by calling the opensees.openseespy.Model(...) constructor (note the capital “M”).
All standard OpenSees functions, as documented
@@ -934,9 +968,9 @@
Modeling in Python import opensees.openseespy as ops
model = ops.Model(ndm=2, ndf=3)
model.node(1, 2.0, 3.0)
-Evaluate Tcl models from Python
+Evaluate Tcl models from Python
-
+
Docs
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ On this page
+
+
+
+
+
+
-Modeling in Python
+Modeling in Python
-
+ opensees.openseespy.Model(...) constructor (note the capital “M”).
All standard OpenSees functions, as documented
@@ -934,9 +968,9 @@ import opensees.openseespy as ops
model = ops.Model(ndm=2, ndf=3)
model.node(1, 2.0, 3.0)Evaluate Tcl models from Python
+Evaluate Tcl models from Python
-
+ The first scripting interface to OpenSees used a programming language called Tcl, which continues to be supported. To execute Tcl commands from a Python script, just create an instance @@ -978,6 +1012,13 @@
Evaluate Tcl models fro
+On this page:
+
@@ -1267,6 +1308,7 @@ Evaluate Tcl models fro
Evaluate Tcl models fro
-
+
diff --git a/docs/getting-started/python/index.html b/docs/getting-started/python/index.html
index 1eb0812e..373408f9 100644
--- a/docs/getting-started/python/index.html
+++ b/docs/getting-started/python/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/frame/index.html b/docs/library/frame/index.html
index 7f72fe7c..daf49d69 100644
--- a/docs/library/frame/index.html
+++ b/docs/library/frame/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/index.html b/docs/library/index.html
index b031e19b..1266f15e 100644
--- a/docs/library/index.html
+++ b/docs/library/index.html
@@ -25,7 +25,7 @@
-
+
@@ -749,7 +749,7 @@
-
+
diff --git a/examples/archstaticsnap/IncrementalAnalysis.ipynb b/examples/archstaticsnap/IncrementalAnalysis.ipynb
index 3f55332c..3f23dc69 100644
--- a/examples/archstaticsnap/IncrementalAnalysis.ipynb
+++ b/examples/archstaticsnap/IncrementalAnalysis.ipynb
@@ -1,26 +1,31 @@
{
"cells": [
- {
- "cell_type": "markdown",
- "id": "44f24cf9-aad0-4929-b3b7-b4103654238a",
- "metadata": {},
- "source": [
- "# Incremental Analysis of a Shallow Arch"
- ]
- },
{
"cell_type": "markdown",
"id": "b6909664-24e3-401c-b176-49ee45890e58",
"metadata": {},
"source": [
- "[](https://mybinder.org/v2/gh/claudioperez/opensees/HEAD?labpath=notebooks%2FIncrementalAnalysis%2FIncrementalAnalysis.ipynb)\n",
+ "\n",
+ "\n",
+ "In this problem, we investigate how this programmatic interface can be used to solve a highly nonlinear problem.\n",
+ "Consider the shallow arch shown below (Clarke and Hancock, 1990):\n",
"\n",
"\n",
"\n",
- "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n",
+ "This problem exhibits several critical points along the solution path,\n",
+ "and requires the use of a sophisticated algorithm to properly traverse these.\n",
+ "In this study, we will investigate how the OpenSees framework can be used to compose these algorithms.\n",
"\n",
+ "We will perform the analysis by creating an OpenSees `Model` data structure, and using\n",
+ "its *methods* to perform various tasks. A method is simply a function that\n",
+ "is linked to a particular instance of a data structure. In this case, the `Model`\n",
+ "data structure holds the geometry and state (i.e., the current values of solution variables) of our structural model. Some methods that you might see being used in this notebook include (you wont need to make any changes to the use of any of these):\n",
"\n",
- "Begin by importing the `arch_model` helper function from the file [`arch.py`](./arch.py):"
+ "- `Model.integrator(...)` This method configures the iteration strategy to be performed\n",
+ " in the next increment\n",
+ "- `Model.analyze(n)` This method applies `n` increments, and between each increment, performs Newton-Raphson iterations.\n",
+ "\n",
+ "In this notebook, the `Model` data structure is created by the `arch_model` helper function, which we load from the file [`arch.py`](./arch.py):"
]
},
{
@@ -38,7 +43,7 @@
"id": "1f478018-476b-44b4-aa2f-5deb49037670",
"metadata": {},
"source": [
- "Import some helpful third-party libraries"
+ "We'll also find the following imports convenient:"
]
},
{
@@ -53,7 +58,7 @@
"\n",
"try:\n",
" import scienceplots\n",
- " plt.style.use(\"steel\") #([\"ieee\", \"science\", \"notebook\"])\n",
+ " plt.style.use([\"steel\"]) #([\"ieee\", \"science\", \"notebook\"])\n",
"except:\n",
" pass"
]
@@ -63,7 +68,18 @@
"id": "adfeaf3b-6027-42ea-96e2-eac362168c2a",
"metadata": {},
"source": [
- "## The Framework"
+ "## Solution Strategy\n",
+ "\n",
+ "Our general strategy is implemented in the following function `solve()`.\n",
+ "This function adopts an incremental approach\n",
+ "where the load is applied in small steps of varying size. \n",
+ "The arguments to the function are:\n",
+ "\n",
+ "- `model`: an OpenSees `Model` object\n",
+ "- `node` : an integer indicating which node to collect results from.\n",
+ "\n",
+ "Both of these arguments will be supplied by the `arch_model` helper function mentioned\n",
+ "above.\n"
]
},
{
@@ -74,25 +90,29 @@
"outputs": [],
"source": [
"def analyze(model, mid, increment, steps, dx, *args):\n",
- " dof = 2\n",
+ " # Initialize some variables\n",
+ " xy = [] # Container to hold solution history (i.e., load factor and displacement at `node`)\n",
+ " status = 0 # Convergence flag; Model.analyze() will return 0 if successful.\n",
"\n",
- " xy = []\n",
- "\n",
- " status = 0\n",
- "\n",
- " increment(model, mid, dof, dx, *args)\n",
+ " # Configure the first load increment strategy; explained below\n",
+ " increment(model, dx, *args)\n",
"\n",
" for step in range(steps):\n",
- " if status != 0:\n",
- " dx /= 2\n",
- " increment(model, mid, dof, dx, *args)\n",
"\n",
+ " # 1. Perform Newton-Raphson iterations until convergence for 1 load\n",
+ " # increment\n",
" status = model.analyze(1)\n",
"\n",
- " xy.append([model.nodeDisp(mid, dof), model.getTime()])\n",
+ " # 2. Store the displacement and load factor\n",
+ " xy.append([model.nodeDisp(mid, 2), model.getTime()])\n",
"\n",
+ " # 3. If the iterations failed, try cutting\n",
+ " # the increment arc-length in half\n",
+ " if status != 0:\n",
+ " dx /= 2\n",
+ " increment(model, dx, *args)\n",
"\n",
- " return np.array(xy).T\n"
+ " return np.array(xy).T"
]
},
{
@@ -109,9 +129,9 @@
"Load incrementation strategy: Direct incrementation of the load parameter (Section 4.1.1)\n",
"\n",
"Solution 2 \n",
- "Iterative strategy: Constant vertical displacement under the load, $v_6$ (Section 3.2)\n",
+ "Iterative strategy: Constant vertical displacement under the load, $u_{\\mathrm{mid}}$ (Section 3.2)\n",
"
\n",
- "Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)\n",
+ "Load incrementation strategy: Incrementation of the displacement component $u_{\\mathrm{mid}}$ (Section 4.1.2)\n",
" \n",
"Solution 3 \n",
"Iterative strategy: Constant arc-length (Section 3.3)\n",
@@ -153,27 +173,28 @@
"metadata": {},
"outputs": [],
"source": [
- "def solution0(model, mid, dof, dx):\n",
+ "def solution0(model, dx):\n",
" model.integrator(\"LoadControl\", 400.0)\n",
"\n",
"\n",
- "def solution1(model, mid, dof, dx):\n",
+ "def solution1(model, dx):\n",
" Jd = 5\n",
" model.integrator(\"LoadControl\", dx, Jd, -800., 800.)\n",
"\n",
"\n",
- "def solution2(model, mid, dof, dx):\n",
+ "def solution2(model, dx, *args):\n",
" Jd = 5\n",
+ " mid, dof = args\n",
" model.integrator(\"DisplacementControl\", mid, dof, dx, Jd)\n",
"\n",
"\n",
- "def norm_control(model, mid, dof, dx):\n",
+ "def norm_control(model, dx, *args):\n",
" Jd = 15\n",
- " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, \"-det\")\n",
+ " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, det=True)\n",
"\n",
"\n",
- "def arc_control(model, mid, dof, dx, a):\n",
- " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.5, reference=\"point\")\n"
+ "def arc_control(model, dx, *args, a=0):\n",
+ " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.0, reference=\"point\")\n"
]
},
{
@@ -182,30 +203,9 @@
"id": "7024dd88-cf13-4c48-a73e-9cdba805dd28",
"metadata": {},
"outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 49845.5, Norm deltaX: 152.498\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 11340.8, Norm deltaX: 123.419\n",
- "ArcLength::update() - imaginary roots due to multiple instability directions - initial load increment was too large\n",
- "a: 6.20586 b: -2674.5 c: 319258 b24ac: -772128\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 3293.9, Norm deltaX: 54.5382\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- },
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -224,24 +224,25 @@
"# ax.plot(-x, y, 'x', label=\"S1\")\n",
"# print(y)\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 7, -150)\n",
+ "model, mid = arch_model()\n",
+ "x, y = analyze(model, mid, solution2, 7, -150, *(mid, 2))\n",
"ax.plot(-x, y, 'o', label=\"S2\")\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 536, -1.5)\n",
+ "x, y = analyze(*arch_model(), solution2, 536, -1.5, *(mid, 2))\n",
"ax.plot(-x, y, '-', label=\"S2\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 9500, 0.5, 0)\n",
"# ax.plot(-x, y, \"-\", label=\"arc\")\n",
"\n",
- "# Requires -det\n",
- "x, y = analyze(*arch_model(), arc_control, 110, 45, 0)\n",
+ "\n",
+ "x, y = analyze(*arch_model(), arc_control, 110, 45)\n",
"ax.plot(-x, y, \"x\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
- "ax.plot(-x, y, \"+\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
+ "# ax.plot(-x, y, \"+\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
- "ax.plot(-x, y, \"*\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
+ "# ax.plot(-x, y, \"*\", label=\"arc\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 8000, 0.8, 0)\n",
"# ax.plot(-x, y, \"x\", label=\"arc\")\n",
@@ -250,30 +251,24 @@
"# ax.plot(-x, y, \"-\", label=\"norm\")\n",
"\n",
"\n",
+ "ax.set_title(\"Displacement vs Load Factor\")\n",
+ "ax.set_ylabel(r\"Load factor $\\lambda$\")\n",
+ "ax.set_xlabel(\"Displacement $u$\")\n",
+ "\n",
"ax.set_xlim([0, 1200])\n",
"ax.set_ylim([-800, 3000])\n",
- "fig.legend()"
+ "fig.legend();"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"id": "f0b43af2-dc3c-4a40-a1fd-e11e46f23206",
"metadata": {},
"outputs": [
{
"data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -283,28 +278,11 @@
}
],
"source": [
- "plt.plot(-x, '.')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "5fa5cc7e-f3ae-4d36-95dc-b2a45074d3ec",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "ax.plot(-x, \".\")"
+ "fix, ax = plt.subplots()\n",
+ "ax.plot(-x, '.');\n",
+ "ax.set_title(\"Displacement vs Step Number\")\n",
+ "ax.set_ylabel(\"Displacement $u$\")\n",
+ "ax.set_xlabel(\"Analysis step $n$\");"
]
},
{
@@ -320,16 +298,19 @@
"id": "21bf025c-2023-4ea6-adf2-56f452f304b5",
"metadata": {},
"source": [
- ""
+ ""
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "1f5c771b-31ef-4f62-9f8b-7cc7bb392184",
+ "cell_type": "markdown",
+ "id": "732dc061-374d-41e6-935a-f82c88f758fe",
"metadata": {},
- "outputs": [],
- "source": []
+ "source": [
+ "## References\n",
+ "\n",
+ "\n",
+ "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n"
+ ]
}
],
"metadata": {
diff --git a/examples/archstaticsnap/arch.py b/examples/archstaticsnap/arch.py
index 61c7635e..176d57a4 100644
--- a/examples/archstaticsnap/arch.py
+++ b/examples/archstaticsnap/arch.py
@@ -9,11 +9,6 @@ def arch_model():
Rise = 500
Offset = 200
- # Define material parameters
- E = 200
- A = 1e4
- I = 1e8
-
# Compute radius
R = Rise/2 + (2*L)**2/(8*Rise)
th = 2*np.arcsin(L/R)
@@ -43,14 +38,19 @@ def arch_model():
# create the node
model.node(tag, x, y)
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
# Create elements
- transfTag = 1
- model.geomTransf("Corotational", transfTag)
+ transf = 1
+ model.geomTransf("Corotational", transf)
for i in range(ne):
tag = i+1
nodes = (i+1, i+2)
- model.element("ElasticBeamColumn", tag, *nodes, A, E, I, transfTag)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
model.fix( 1, 1, 1, 0)
@@ -63,12 +63,14 @@ def arch_model():
model.load(mid, 0.0, -1.0, 0.0, pattern=1)
- model.system("ProfileSPD")
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
# model.system("FullGeneral")
# model.system("BandGeneral")
- # model.system("Umfpack", det=True)
+ model.system("Umfpack", det=True)
- model.test("NormUnbalance", 1e-6, 25, 0)
+ model.test("NormUnbalance", 1e-6, 25, 9)
model.algorithm("Newton")
model.analysis("Static")
diff --git a/examples/archstaticsnap/index.html b/examples/archstaticsnap/index.html
index caeb7e41..cf61524b 100644
--- a/examples/archstaticsnap/index.html
+++ b/examples/archstaticsnap/index.html
@@ -25,7 +25,7 @@
-
+
@@ -52,7 +52,7 @@
-
+
@@ -110,7 +110,7 @@
"about": {
"@id": "https://stairlab.github.io/#/schema/organization/1"
},
- "dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
+ "dateModified": "2024-10-11T00:55:08CET","breadcrumb": {
"@id": "https://stairlab.github.io/opensees-gallery/examples/archstaticsnap/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
@@ -354,8 +354,8 @@
- 3 min read •
- 569 words
+ 6 min read •
+ 1,092 words
@@ -506,25 +506,46 @@
-
+
+
-Incremental Analysis of a Shallow Arch
-
-
-
-
-
+
+
+
+ On this page
+
+
+
+
+
+
+The files for this example are:
+
+-
+
@@ -533,21 +554,135 @@
Incremental Anal
+
+
+
+
+
+ arch.py - This file contains the function arch_model which is used construct the model
+-
+
+
-
+
+
+
+
+
+
IncrementalAnalysis.ipynb - This is the current Jupyter notebook file
+
+
+
+
+
+
+
+ import numpy as np
+import opensees.openseespy
+
+# Create the model
+def arch_model():
+
+ # Define model parameters
+ L = 5000
+ Rise = 500
+ Offset = 200
+
+ # Compute radius
+ R = Rise/2 + (2*L)**2/(8*Rise)
+ th = 2*np.arcsin(L/R)
+
+ #
+ # Build the model
+ #
+ model = opensees.openseespy.Model(ndm=2, ndf=3)
+
+ # Create nodes
+ ne = 10
+ nen = 2 # nodes per element
+ nn = ne*(nen-1)+1
+ mid = (nn+1)//2 # midpoint node
+
+ for i, angle in enumerate(np.linspace(-th/2, th/2, nn)):
+ tag = i + 1
+
+ # Compute x and add offset if midpoint
+ x = R*np.sin(angle)
+ if tag == mid:
+ x -= Offset
+
+ # Compute y
+ y = R*np.cos(angle)
+
+ # create the node
+ model.node(tag, x, y)
+
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
+
+ # Create elements
+ transf = 1
+ model.geomTransf("Corotational", transf)
+ for i in range(ne):
+ tag = i+1
+ nodes = (i+1, i+2)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
+
+
+ model.fix( 1, 1, 1, 0)
+ model.fix(nn, 1, 1, 0)
+
+ # Create a load pattern that scales linearly
+ model.pattern("Plain", 1, "Linear")
+
+ # Add a nodal load to the pattern
+ model.load(mid, 0.0, -1.0, 0.0, pattern=1)
+
+
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
+ # model.system("FullGeneral")
+ # model.system("BandGeneral")
+ model.system("Umfpack", det=True)
+
+ model.test("NormUnbalance", 1e-6, 25, 9)
+ model.algorithm("Newton")
+ model.analysis("Static")
+
+
+ return model, mid
+
+
+
+
+
+
-
-
-
-
-
+Evaluate Tcl models fro
-
+
diff --git a/docs/getting-started/python/index.html b/docs/getting-started/python/index.html
index 1eb0812e..373408f9 100644
--- a/docs/getting-started/python/index.html
+++ b/docs/getting-started/python/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/frame/index.html b/docs/library/frame/index.html
index 7f72fe7c..daf49d69 100644
--- a/docs/library/frame/index.html
+++ b/docs/library/frame/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1243,7 +1243,7 @@ Docs
-
+
diff --git a/docs/library/index.html b/docs/library/index.html
index b031e19b..1266f15e 100644
--- a/docs/library/index.html
+++ b/docs/library/index.html
@@ -25,7 +25,7 @@
-
+
@@ -749,7 +749,7 @@
-
+
diff --git a/examples/archstaticsnap/IncrementalAnalysis.ipynb b/examples/archstaticsnap/IncrementalAnalysis.ipynb
index 3f55332c..3f23dc69 100644
--- a/examples/archstaticsnap/IncrementalAnalysis.ipynb
+++ b/examples/archstaticsnap/IncrementalAnalysis.ipynb
@@ -1,26 +1,31 @@
{
"cells": [
- {
- "cell_type": "markdown",
- "id": "44f24cf9-aad0-4929-b3b7-b4103654238a",
- "metadata": {},
- "source": [
- "# Incremental Analysis of a Shallow Arch"
- ]
- },
{
"cell_type": "markdown",
"id": "b6909664-24e3-401c-b176-49ee45890e58",
"metadata": {},
"source": [
- "[](https://mybinder.org/v2/gh/claudioperez/opensees/HEAD?labpath=notebooks%2FIncrementalAnalysis%2FIncrementalAnalysis.ipynb)\n",
+ "\n",
+ "\n",
+ "In this problem, we investigate how this programmatic interface can be used to solve a highly nonlinear problem.\n",
+ "Consider the shallow arch shown below (Clarke and Hancock, 1990):\n",
"\n",
"\n",
"\n",
- "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n",
+ "This problem exhibits several critical points along the solution path,\n",
+ "and requires the use of a sophisticated algorithm to properly traverse these.\n",
+ "In this study, we will investigate how the OpenSees framework can be used to compose these algorithms.\n",
"\n",
+ "We will perform the analysis by creating an OpenSees `Model` data structure, and using\n",
+ "its *methods* to perform various tasks. A method is simply a function that\n",
+ "is linked to a particular instance of a data structure. In this case, the `Model`\n",
+ "data structure holds the geometry and state (i.e., the current values of solution variables) of our structural model. Some methods that you might see being used in this notebook include (you wont need to make any changes to the use of any of these):\n",
"\n",
- "Begin by importing the `arch_model` helper function from the file [`arch.py`](./arch.py):"
+ "- `Model.integrator(...)` This method configures the iteration strategy to be performed\n",
+ " in the next increment\n",
+ "- `Model.analyze(n)` This method applies `n` increments, and between each increment, performs Newton-Raphson iterations.\n",
+ "\n",
+ "In this notebook, the `Model` data structure is created by the `arch_model` helper function, which we load from the file [`arch.py`](./arch.py):"
]
},
{
@@ -38,7 +43,7 @@
"id": "1f478018-476b-44b4-aa2f-5deb49037670",
"metadata": {},
"source": [
- "Import some helpful third-party libraries"
+ "We'll also find the following imports convenient:"
]
},
{
@@ -53,7 +58,7 @@
"\n",
"try:\n",
" import scienceplots\n",
- " plt.style.use(\"steel\") #([\"ieee\", \"science\", \"notebook\"])\n",
+ " plt.style.use([\"steel\"]) #([\"ieee\", \"science\", \"notebook\"])\n",
"except:\n",
" pass"
]
@@ -63,7 +68,18 @@
"id": "adfeaf3b-6027-42ea-96e2-eac362168c2a",
"metadata": {},
"source": [
- "## The Framework"
+ "## Solution Strategy\n",
+ "\n",
+ "Our general strategy is implemented in the following function `solve()`.\n",
+ "This function adopts an incremental approach\n",
+ "where the load is applied in small steps of varying size. \n",
+ "The arguments to the function are:\n",
+ "\n",
+ "- `model`: an OpenSees `Model` object\n",
+ "- `node` : an integer indicating which node to collect results from.\n",
+ "\n",
+ "Both of these arguments will be supplied by the `arch_model` helper function mentioned\n",
+ "above.\n"
]
},
{
@@ -74,25 +90,29 @@
"outputs": [],
"source": [
"def analyze(model, mid, increment, steps, dx, *args):\n",
- " dof = 2\n",
+ " # Initialize some variables\n",
+ " xy = [] # Container to hold solution history (i.e., load factor and displacement at `node`)\n",
+ " status = 0 # Convergence flag; Model.analyze() will return 0 if successful.\n",
"\n",
- " xy = []\n",
- "\n",
- " status = 0\n",
- "\n",
- " increment(model, mid, dof, dx, *args)\n",
+ " # Configure the first load increment strategy; explained below\n",
+ " increment(model, dx, *args)\n",
"\n",
" for step in range(steps):\n",
- " if status != 0:\n",
- " dx /= 2\n",
- " increment(model, mid, dof, dx, *args)\n",
"\n",
+ " # 1. Perform Newton-Raphson iterations until convergence for 1 load\n",
+ " # increment\n",
" status = model.analyze(1)\n",
"\n",
- " xy.append([model.nodeDisp(mid, dof), model.getTime()])\n",
+ " # 2. Store the displacement and load factor\n",
+ " xy.append([model.nodeDisp(mid, 2), model.getTime()])\n",
"\n",
+ " # 3. If the iterations failed, try cutting\n",
+ " # the increment arc-length in half\n",
+ " if status != 0:\n",
+ " dx /= 2\n",
+ " increment(model, dx, *args)\n",
"\n",
- " return np.array(xy).T\n"
+ " return np.array(xy).T"
]
},
{
@@ -109,9 +129,9 @@
"Load incrementation strategy: Direct incrementation of the load parameter (Section 4.1.1)\n",
"\n",
"Solution 2 \n",
- "Iterative strategy: Constant vertical displacement under the load, $v_6$ (Section 3.2)\n",
+ "Iterative strategy: Constant vertical displacement under the load, $u_{\\mathrm{mid}}$ (Section 3.2)\n",
"
\n",
- "Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)\n",
+ "Load incrementation strategy: Incrementation of the displacement component $u_{\\mathrm{mid}}$ (Section 4.1.2)\n",
" \n",
"Solution 3 \n",
"Iterative strategy: Constant arc-length (Section 3.3)\n",
@@ -153,27 +173,28 @@
"metadata": {},
"outputs": [],
"source": [
- "def solution0(model, mid, dof, dx):\n",
+ "def solution0(model, dx):\n",
" model.integrator(\"LoadControl\", 400.0)\n",
"\n",
"\n",
- "def solution1(model, mid, dof, dx):\n",
+ "def solution1(model, dx):\n",
" Jd = 5\n",
" model.integrator(\"LoadControl\", dx, Jd, -800., 800.)\n",
"\n",
"\n",
- "def solution2(model, mid, dof, dx):\n",
+ "def solution2(model, dx, *args):\n",
" Jd = 5\n",
+ " mid, dof = args\n",
" model.integrator(\"DisplacementControl\", mid, dof, dx, Jd)\n",
"\n",
"\n",
- "def norm_control(model, mid, dof, dx):\n",
+ "def norm_control(model, dx, *args):\n",
" Jd = 15\n",
- " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, \"-det\")\n",
+ " model.integrator(\"MinUnbalDispNorm\", dx, Jd, -10, 10, det=True)\n",
"\n",
"\n",
- "def arc_control(model, mid, dof, dx, a):\n",
- " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.5, reference=\"point\")\n"
+ "def arc_control(model, dx, *args, a=0):\n",
+ " model.integrator(\"ArcLength\", dx, a, det=True, exp=0.0, reference=\"point\")\n"
]
},
{
@@ -182,30 +203,9 @@
"id": "7024dd88-cf13-4c48-a73e-9cdba805dd28",
"metadata": {},
"outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 49845.5, Norm deltaX: 152.498\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 11340.8, Norm deltaX: 123.419\n",
- "ArcLength::update() - imaginary roots due to multiple instability directions - initial load increment was too large\n",
- "a: 6.20586 b: -2674.5 c: 319258 b24ac: -772128\n",
- "\u001b[0;31m FAILURE\u001b[0m :: Iter: 25, Norm: 3293.9, Norm deltaX: 54.5382\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- },
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -224,24 +224,25 @@
"# ax.plot(-x, y, 'x', label=\"S1\")\n",
"# print(y)\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 7, -150)\n",
+ "model, mid = arch_model()\n",
+ "x, y = analyze(model, mid, solution2, 7, -150, *(mid, 2))\n",
"ax.plot(-x, y, 'o', label=\"S2\")\n",
"\n",
- "x, y = analyze(*arch_model(), solution2, 536, -1.5)\n",
+ "x, y = analyze(*arch_model(), solution2, 536, -1.5, *(mid, 2))\n",
"ax.plot(-x, y, '-', label=\"S2\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 9500, 0.5, 0)\n",
"# ax.plot(-x, y, \"-\", label=\"arc\")\n",
"\n",
- "# Requires -det\n",
- "x, y = analyze(*arch_model(), arc_control, 110, 45, 0)\n",
+ "\n",
+ "x, y = analyze(*arch_model(), arc_control, 110, 45)\n",
"ax.plot(-x, y, \"x\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
- "ax.plot(-x, y, \"+\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 88, 0)\n",
+ "# ax.plot(-x, y, \"+\", label=\"arc\")\n",
"\n",
- "x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
- "ax.plot(-x, y, \"*\", label=\"arc\")\n",
+ "# x, y = analyze(*arch_model(), arc_control, 80, 188, 0)\n",
+ "# ax.plot(-x, y, \"*\", label=\"arc\")\n",
"\n",
"# x, y = analyze(*arch_model(), arc_control, 8000, 0.8, 0)\n",
"# ax.plot(-x, y, \"x\", label=\"arc\")\n",
@@ -250,30 +251,24 @@
"# ax.plot(-x, y, \"-\", label=\"norm\")\n",
"\n",
"\n",
+ "ax.set_title(\"Displacement vs Load Factor\")\n",
+ "ax.set_ylabel(r\"Load factor $\\lambda$\")\n",
+ "ax.set_xlabel(\"Displacement $u$\")\n",
+ "\n",
"ax.set_xlim([0, 1200])\n",
"ax.set_ylim([-800, 3000])\n",
- "fig.legend()"
+ "fig.legend();"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"id": "f0b43af2-dc3c-4a40-a1fd-e11e46f23206",
"metadata": {},
"outputs": [
{
"data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -283,28 +278,11 @@
}
],
"source": [
- "plt.plot(-x, '.')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "5fa5cc7e-f3ae-4d36-95dc-b2a45074d3ec",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "ax.plot(-x, \".\")"
+ "fix, ax = plt.subplots()\n",
+ "ax.plot(-x, '.');\n",
+ "ax.set_title(\"Displacement vs Step Number\")\n",
+ "ax.set_ylabel(\"Displacement $u$\")\n",
+ "ax.set_xlabel(\"Analysis step $n$\");"
]
},
{
@@ -320,16 +298,19 @@
"id": "21bf025c-2023-4ea6-adf2-56f452f304b5",
"metadata": {},
"source": [
- ""
+ ""
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "1f5c771b-31ef-4f62-9f8b-7cc7bb392184",
+ "cell_type": "markdown",
+ "id": "732dc061-374d-41e6-935a-f82c88f758fe",
"metadata": {},
- "outputs": [],
- "source": []
+ "source": [
+ "## References\n",
+ "\n",
+ "\n",
+ "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n"
+ ]
}
],
"metadata": {
diff --git a/examples/archstaticsnap/arch.py b/examples/archstaticsnap/arch.py
index 61c7635e..176d57a4 100644
--- a/examples/archstaticsnap/arch.py
+++ b/examples/archstaticsnap/arch.py
@@ -9,11 +9,6 @@ def arch_model():
Rise = 500
Offset = 200
- # Define material parameters
- E = 200
- A = 1e4
- I = 1e8
-
# Compute radius
R = Rise/2 + (2*L)**2/(8*Rise)
th = 2*np.arcsin(L/R)
@@ -43,14 +38,19 @@ def arch_model():
# create the node
model.node(tag, x, y)
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
# Create elements
- transfTag = 1
- model.geomTransf("Corotational", transfTag)
+ transf = 1
+ model.geomTransf("Corotational", transf)
for i in range(ne):
tag = i+1
nodes = (i+1, i+2)
- model.element("ElasticBeamColumn", tag, *nodes, A, E, I, transfTag)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
model.fix( 1, 1, 1, 0)
@@ -63,12 +63,14 @@ def arch_model():
model.load(mid, 0.0, -1.0, 0.0, pattern=1)
- model.system("ProfileSPD")
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
# model.system("FullGeneral")
# model.system("BandGeneral")
- # model.system("Umfpack", det=True)
+ model.system("Umfpack", det=True)
- model.test("NormUnbalance", 1e-6, 25, 0)
+ model.test("NormUnbalance", 1e-6, 25, 9)
model.algorithm("Newton")
model.analysis("Static")
diff --git a/examples/archstaticsnap/index.html b/examples/archstaticsnap/index.html
index caeb7e41..cf61524b 100644
--- a/examples/archstaticsnap/index.html
+++ b/examples/archstaticsnap/index.html
@@ -25,7 +25,7 @@
-
+
@@ -52,7 +52,7 @@
-
+
@@ -110,7 +110,7 @@
"about": {
"@id": "https://stairlab.github.io/#/schema/organization/1"
},
- "dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
+ "dateModified": "2024-10-11T00:55:08CET","breadcrumb": {
"@id": "https://stairlab.github.io/opensees-gallery/examples/archstaticsnap/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
@@ -354,8 +354,8 @@
- 3 min read •
- 569 words
+ 6 min read •
+ 1,092 words
@@ -506,25 +506,46 @@
-
+
+
-Incremental Analysis of a Shallow Arch
-
-
-
-
-
+
+
+
+ On this page
+
+
+
+
+
+
+The files for this example are:
+
+-
+
@@ -533,21 +554,135 @@
Incremental Anal
+
+
+
+
+
+ arch.py - This file contains the function arch_model which is used construct the model
+-
+
+
-
+
+
+
+
+
+
IncrementalAnalysis.ipynb - This is the current Jupyter notebook file
+
+
+
+
+
+
+
+ import numpy as np
+import opensees.openseespy
+
+# Create the model
+def arch_model():
+
+ # Define model parameters
+ L = 5000
+ Rise = 500
+ Offset = 200
+
+ # Compute radius
+ R = Rise/2 + (2*L)**2/(8*Rise)
+ th = 2*np.arcsin(L/R)
+
+ #
+ # Build the model
+ #
+ model = opensees.openseespy.Model(ndm=2, ndf=3)
+
+ # Create nodes
+ ne = 10
+ nen = 2 # nodes per element
+ nn = ne*(nen-1)+1
+ mid = (nn+1)//2 # midpoint node
+
+ for i, angle in enumerate(np.linspace(-th/2, th/2, nn)):
+ tag = i + 1
+
+ # Compute x and add offset if midpoint
+ x = R*np.sin(angle)
+ if tag == mid:
+ x -= Offset
+
+ # Compute y
+ y = R*np.cos(angle)
+
+ # create the node
+ model.node(tag, x, y)
+
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
+
+ # Create elements
+ transf = 1
+ model.geomTransf("Corotational", transf)
+ for i in range(ne):
+ tag = i+1
+ nodes = (i+1, i+2)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
+
+
+ model.fix( 1, 1, 1, 0)
+ model.fix(nn, 1, 1, 0)
+
+ # Create a load pattern that scales linearly
+ model.pattern("Plain", 1, "Linear")
+
+ # Add a nodal load to the pattern
+ model.load(mid, 0.0, -1.0, 0.0, pattern=1)
+
+
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
+ # model.system("FullGeneral")
+ # model.system("BandGeneral")
+ model.system("Umfpack", det=True)
+
+ model.test("NormUnbalance", 1e-6, 25, 9)
+ model.algorithm("Newton")
+ model.analysis("Static")
+
+
+ return model, mid
+
+
+
+
+
+
-
-
-
-
-
\n", - "Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)\n", + "Load incrementation strategy: Incrementation of the displacement component $u_{\\mathrm{mid}}$ (Section 4.1.2)\n", "
"
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "1f5c771b-31ef-4f62-9f8b-7cc7bb392184",
+ "cell_type": "markdown",
+ "id": "732dc061-374d-41e6-935a-f82c88f758fe",
"metadata": {},
- "outputs": [],
- "source": []
+ "source": [
+ "## References\n",
+ "\n",
+ "\n",
+ "> Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: https://doi.org/10.1002/nme.1620290702.\n"
+ ]
}
],
"metadata": {
diff --git a/examples/archstaticsnap/arch.py b/examples/archstaticsnap/arch.py
index 61c7635e..176d57a4 100644
--- a/examples/archstaticsnap/arch.py
+++ b/examples/archstaticsnap/arch.py
@@ -9,11 +9,6 @@ def arch_model():
Rise = 500
Offset = 200
- # Define material parameters
- E = 200
- A = 1e4
- I = 1e8
-
# Compute radius
R = Rise/2 + (2*L)**2/(8*Rise)
th = 2*np.arcsin(L/R)
@@ -43,14 +38,19 @@ def arch_model():
# create the node
model.node(tag, x, y)
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
# Create elements
- transfTag = 1
- model.geomTransf("Corotational", transfTag)
+ transf = 1
+ model.geomTransf("Corotational", transf)
for i in range(ne):
tag = i+1
nodes = (i+1, i+2)
- model.element("ElasticBeamColumn", tag, *nodes, A, E, I, transfTag)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
model.fix( 1, 1, 1, 0)
@@ -63,12 +63,14 @@ def arch_model():
model.load(mid, 0.0, -1.0, 0.0, pattern=1)
- model.system("ProfileSPD")
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
# model.system("FullGeneral")
# model.system("BandGeneral")
- # model.system("Umfpack", det=True)
+ model.system("Umfpack", det=True)
- model.test("NormUnbalance", 1e-6, 25, 0)
+ model.test("NormUnbalance", 1e-6, 25, 9)
model.algorithm("Newton")
model.analysis("Static")
diff --git a/examples/archstaticsnap/index.html b/examples/archstaticsnap/index.html
index caeb7e41..cf61524b 100644
--- a/examples/archstaticsnap/index.html
+++ b/examples/archstaticsnap/index.html
@@ -25,7 +25,7 @@
-
+
@@ -52,7 +52,7 @@
-
+
@@ -110,7 +110,7 @@
"about": {
"@id": "https://stairlab.github.io/#/schema/organization/1"
},
- "dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
+ "dateModified": "2024-10-11T00:55:08CET","breadcrumb": {
"@id": "https://stairlab.github.io/opensees-gallery/examples/archstaticsnap/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
@@ -354,8 +354,8 @@
- 3 min read •
- 569 words
+ 6 min read •
+ 1,092 words
@@ -506,25 +506,46 @@
-
+
+
-
+
+Incremental Analysis of a Shallow Arch - -
-- - + + + + On this page + + + +
The files for this example are:
+-
+
-
+
@@ -533,21 +554,135 @@
Incremental Anal + + + + + +
arch.py- This file contains the functionarch_modelwhich is used construct the model
+ -
+
+
-
+
+
+
+
+
+
IncrementalAnalysis.ipynb- This is the current Jupyter notebook file
+
+
-
-
-
-
-
+
+
+
+import numpy as np
+import opensees.openseespy
+
+# Create the model
+def arch_model():
+
+ # Define model parameters
+ L = 5000
+ Rise = 500
+ Offset = 200
+
+ # Compute radius
+ R = Rise/2 + (2*L)**2/(8*Rise)
+ th = 2*np.arcsin(L/R)
+
+ #
+ # Build the model
+ #
+ model = opensees.openseespy.Model(ndm=2, ndf=3)
+
+ # Create nodes
+ ne = 10
+ nen = 2 # nodes per element
+ nn = ne*(nen-1)+1
+ mid = (nn+1)//2 # midpoint node
+
+ for i, angle in enumerate(np.linspace(-th/2, th/2, nn)):
+ tag = i + 1
+
+ # Compute x and add offset if midpoint
+ x = R*np.sin(angle)
+ if tag == mid:
+ x -= Offset
+
+ # Compute y
+ y = R*np.cos(angle)
+
+ # create the node
+ model.node(tag, x, y)
+
+ # Define elastic section properties
+ E = 200
+ A = 1e4
+ I = 1e8
+ model.section("ElasticFrame", 1, A=A, E=E, I=I)
+
+ # Create elements
+ transf = 1
+ model.geomTransf("Corotational", transf)
+ for i in range(ne):
+ tag = i+1
+ nodes = (i+1, i+2)
+ model.element("PrismFrame", tag, nodes, section=1, transform=transf)
+
+
+ model.fix( 1, 1, 1, 0)
+ model.fix(nn, 1, 1, 0)
+
+ # Create a load pattern that scales linearly
+ model.pattern("Plain", 1, "Linear")
+
+ # Add a nodal load to the pattern
+ model.load(mid, 0.0, -1.0, 0.0, pattern=1)
+
+
+ # Select linear solver, and ensure determinants are
+ # computed and stored.
+ # model.system("ProfileSPD")
+ # model.system("FullGeneral")
+ # model.system("BandGeneral")
+ model.system("Umfpack", det=True)
+
+ model.test("NormUnbalance", 1e-6, 25, 9)
+ model.algorithm("Newton")
+ model.analysis("Static")
+
+
+ return model, mid
+
+
+In this problem, we investigate how this programmatic interface can be used to solve a highly nonlinear problem. +Consider the shallow arch shown below (Clarke and Hancock, 1990):
@@ -578,25 +713,19 @@Incremental Anal
height="1918"
width="2800"
alt="Shallow arch">
-
-
-
-
-
-
- Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at:
-
-
-
-
-
-
-
-https://doi.org/10.1002/nme.1620290702
-
- .
-
-
Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: - - - - - - - -https://doi.org/10.1002/nme.1620290702 - - .
-Begin by importing the arch_model helper function from the file
+
This problem exhibits several critical points along the solution path, +and requires the use of a sophisticated algorithm to properly traverse these. +In this study, we will investigate how the OpenSees framework can be used to compose these algorithms.
+We will perform the analysis by creating an OpenSees Model data structure, and using
+its methods to perform various tasks. A method is simply a function that
+is linked to a particular instance of a data structure. In this case, the Model
+data structure holds the geometry and state (i.e., the current values of solution variables) of our structural model. Some methods that you might see being used in this notebook include (you wont need to make any changes to the use of any of these):
-
+
Model.integrator(...)This method configures the iteration strategy to be performed +in the next increment
+Model.analyze(n)This method appliesnincrements, and between each increment, performs Newton-Raphson iterations.
+
In this notebook, the Model data structure is created by the arch_model helper function, which we load from the file
@@ -612,36 +741,50 @@
Incremental Anal
arch.py:
-from arch import arch_model
from arch import arch_modelImport some helpful third-party libraries
+from arch import arch_modelWe’ll also find the following imports convenient:
import numpy as np
import matplotlib.pyplot as plt
try:
import scienceplots
- plt.style.use("steel") #(["ieee", "science", "notebook"])
+ plt.style.use(["steel"]) #(["ieee", "science", "notebook"])
except:
passThe Framework
+Solution Strategy
+Our general strategy is implemented in the following function solve().
+This function adopts an incremental approach
+where the load is applied in small steps of varying size.
+The arguments to the function are:
+
+model: an OpenSees Model objectnode : an integer indicating which node to collect results from.
+Both of these arguments will be supplied by the arch_model helper function mentioned
+above.
def analyze(model, mid, increment, steps, dx, *args):
- dof = 2
+ # Initialize some variables
+ xy = [] # Container to hold solution history (i.e., load factor and displacement at `node`)
+ status = 0 # Convergence flag; Model.analyze() will return 0 if successful.
- xy = []
-
- status = 0
-
- increment(model, mid, dof, dx, *args)
+ # Configure the first load increment strategy; explained below
+ increment(model, dx, *args)
for step in range(steps):
- if status != 0:
- dx /= 2
- increment(model, mid, dof, dx, *args)
+ # 1. Perform Newton-Raphson iterations until convergence for 1 load
+ # increment
status = model.analyze(1)
- xy.append([model.nodeDisp(mid, dof), model.getTime()])
+ # 2. Store the displacement and load factor
+ xy.append([model.nodeDisp(mid, 2), model.getTime()])
+ # 3. If the iterations failed, try cutting
+ # the increment arc-length in half
+ if status != 0:
+ dx /= 2
+ increment(model, dx, *args)
return np.array(xy).T
The strategies used by Clarke and Hancock are:
@@ -651,9 +794,9 @@ The Framework
- Solution 2
-
-Iterative strategy: Constant vertical displacement under the load, $v_6$ (Section 3.2)
+Iterative strategy: Constant vertical displacement under the load, $u_{\mathrm{mid}}$ (Section 3.2)
-Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)
+Load incrementation strategy: Incrementation of the displacement component $u_{\mathrm{mid}}$ (Section 4.1.2)
- Solution 3
-
Iterative strategy: Constant arc-length (Section 3.3)
@@ -686,27 +829,28 @@
The Framework
-def solution0(model, mid, dof, dx):
+def solution0(model, dx):
model.integrator("LoadControl", 400.0)
-def solution1(model, mid, dof, dx):
+def solution1(model, dx):
Jd = 5
model.integrator("LoadControl", dx, Jd, -800., 800.)
-def solution2(model, mid, dof, dx):
+def solution2(model, dx, *args):
Jd = 5
+ mid, dof = args
model.integrator("DisplacementControl", mid, dof, dx, Jd)
-def norm_control(model, mid, dof, dx):
+def norm_control(model, dx, *args):
Jd = 15
- model.integrator("MinUnbalDispNorm", dx, Jd, -10, 10, "-det")
+ model.integrator("MinUnbalDispNorm", dx, Jd, -10, 10, det=True)
-def arc_control(model, mid, dof, dx, a):
- model.integrator("ArcLength", dx, a, det=True, exp=0.5, reference="point")
fig, ax = plt.subplots()
+def arc_control(model, dx, *args, a=0):
+ model.integrator("ArcLength", dx, a, det=True, exp=0.0, reference="point")
fig, ax = plt.subplots()
# x, y = solution0(*arch_model(), 6, 400.0)
# ax.plot(-x, y, 'x', label="S0")
@@ -715,24 +859,25 @@ The Framework
# ax.plot(-x, y, 'x', label="S1")
# print(y)
-x, y = analyze(*arch_model(), solution2, 7, -150)
+model, mid = arch_model()
+x, y = analyze(model, mid, solution2, 7, -150, *(mid, 2))
ax.plot(-x, y, 'o', label="S2")
-x, y = analyze(*arch_model(), solution2, 536, -1.5)
+x, y = analyze(*arch_model(), solution2, 536, -1.5, *(mid, 2))
ax.plot(-x, y, '-', label="S2")
# x, y = analyze(*arch_model(), arc_control, 9500, 0.5, 0)
# ax.plot(-x, y, "-", label="arc")
-# Requires -det
-x, y = analyze(*arch_model(), arc_control, 110, 45, 0)
+
+x, y = analyze(*arch_model(), arc_control, 110, 45)
ax.plot(-x, y, "x", label="arc")
-x, y = analyze(*arch_model(), arc_control, 80, 88, 0)
-ax.plot(-x, y, "+", label="arc")
+# x, y = analyze(*arch_model(), arc_control, 80, 88, 0)
+# ax.plot(-x, y, "+", label="arc")
-x, y = analyze(*arch_model(), arc_control, 80, 188, 0)
-ax.plot(-x, y, "*", label="arc")
+# x, y = analyze(*arch_model(), arc_control, 80, 188, 0)
+# ax.plot(-x, y, "*", label="arc")
# x, y = analyze(*arch_model(), arc_control, 8000, 0.8, 0)
# ax.plot(-x, y, "x", label="arc")
@@ -741,18 +886,21 @@ The Framework
# ax.plot(-x, y, "-", label="norm")
+ax.set_title("Displacement vs Load Factor")
+ax.set_ylabel(r"Load factor $\lambda$")
+ax.set_xlabel("Displacement $u$")
+
ax.set_xlim([0, 1200])
ax.set_ylim([-800, 3000])
-fig.legend()
Output:
-[0;31m FAILURE[0m :: Iter: 25, Norm: 49845.5, Norm deltaX: 152.498
-[0;31m FAILURE[0m :: Iter: 25, Norm: 11340.8, Norm deltaX: 123.419
-ArcLength::update() - imaginary roots due to multiple instability directions - initial load increment was too large
-a: 6.20586 b: -2674.5 c: 319258 b24ac: -772128
-[0;31m FAILURE[0m :: Iter: 25, Norm: 3293.9, Norm deltaX: 54.5382
<matplotlib.legend.Legend at 0x7f1ddb0b8d00>
-<Figure size 2560x1920 with 1 Axes>
plt.plot(-x, '.')
Output:
-[<matplotlib.lines.Line2D at 0x7f1dd8e8ec40>]
-<Figure size 2560x1920 with 1 Axes>
ax.plot(-x, ".")
Output:
-[<matplotlib.lines.Line2D at 0x7f1dd8cc8340>]
The following animation of the solution is created in
+
fig.legend();
Output:
+
+<Figure size 2560x1920 with 1 Axes>
fix, ax = plt.subplots()
+ax.plot(-x, '.');
+ax.set_title("Displacement vs Step Number")
+ax.set_ylabel("Displacement $u$")
+ax.set_xlabel("Analysis step $n$");
Output:
+
+<Figure size 2560x1920 with 1 Axes>
The following animation of the solution is created in
@@ -768,39 +916,32 @@
The Framework Animating.ipynb
+
+References
+
+
+
+ Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at:
+
+https://doi.org/10.1002/nme.1620290702
+
+ .
+
-
-
-
-
-
-
-
-![]()
-
-
-
@@ -835,6 +976,13 @@ The Framework On this page:
+
@@ -1124,6 +1272,7 @@ The Framework The Framework
+
diff --git a/examples/buildingmodes/index.html b/examples/buildingmodes/index.html
index a720aab5..677a085f 100644
--- a/examples/buildingmodes/index.html
+++ b/examples/buildingmodes/index.html
@@ -3,7 +3,7 @@
-
+
@@ -12,10 +12,10 @@
-
+
-
+
@@ -25,7 +25,7 @@
-
+
@@ -44,16 +44,16 @@
OpenSees - Building Modes
-
+
-
+
-
+
@@ -63,7 +63,7 @@
-
+
@@ -75,14 +75,14 @@
"@graph": [
{
"@type": "Organization",
- "@id": "https://stairlab.github.io/#/schema/organization/1",
+ "@id": "http://localhost:1313/#/schema/organization/1",
"name": "STAIRlab",
- "url": "https://stairlab.github.io/",
+ "url": "http://localhost:1313/",
"sameAs": [null,"https://github.com/claudioperez/OpenSeesRT"],
"image": {
"@type": "ImageObject",
- "@id": "https://stairlab.github.io/#/schema/image/1",
- "url": "https://stairlab.github.io/img/logo1280x640.png",
+ "@id": "http://localhost:1313/#/schema/image/1",
+ "url": "http://localhost:1313/img/logo1280x640.png",
"width": 1280 ,
"height": 640 ,
"caption": "STAIRlab"
@@ -90,48 +90,48 @@
},
{
"@type": "WebSite",
- "@id": "https://stairlab.github.io/#/schema/website/1",
- "url": "https://stairlab.github.io/",
+ "@id": "http://localhost:1313/#/schema/website/1",
+ "url": "http://localhost:1313/",
"name": "OpenSees",
"description": "OpenSees Examples.",
"publisher": {
- "@id": "https://stairlab.github.io/#/schema/organization/1"
+ "@id": "http://localhost:1313/#/schema/organization/1"
}
},
{
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/",
- "url": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/",
+ "url": "http://localhost:1313/opensees-gallery/examples/buildingmodes/",
"name": "Building Modes",
"description": "A building is modeled as a cantilever, and the first three mode shapes are plotted.",
"isPartOf": {
- "@id": "https://stairlab.github.io/#/schema/website/1"
+ "@id": "http://localhost:1313/#/schema/website/1"
},
"about": {
- "@id": "https://stairlab.github.io/#/schema/organization/1"
+ "@id": "http://localhost:1313/#/schema/organization/1"
},
"dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/image/2"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/image/2"
},
"inLanguage": "en-US",
"potentialAction": [{
- "@type": "ReadAction", "target": ["https://stairlab.github.io/opensees-gallery/examples/buildingmodes/"]
+ "@type": "ReadAction", "target": ["http://localhost:1313/opensees-gallery/examples/buildingmodes/"]
}]
},
{
"@type": "BreadcrumbList",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1",
"name": "Breadcrumbs",
"itemListElement": [{
"@type": "ListItem",
"position": 1 ,
"item": {
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/",
- "url": "https://stairlab.github.io/opensees-gallery/",
+ "@id": "http://localhost:1313/opensees-gallery/",
+ "url": "http://localhost:1313/opensees-gallery/",
"name": "Home"
}
},{
@@ -139,15 +139,15 @@
"position": 2 ,
"item": {
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/",
- "url": "https://stairlab.github.io/opensees-gallery/examples/",
+ "@id": "http://localhost:1313/opensees-gallery/examples/",
+ "url": "http://localhost:1313/opensees-gallery/examples/",
"name": "Examples"
}
},{
"@type": "ListItem",
"position": 3 ,
"item": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/"
}
}]
},
@@ -157,9 +157,9 @@
"@graph": [
{
"@type": "ImageObject",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/image/2",
- "url": "https://stairlab.github.io/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
- "contentUrl": "https://stairlab.github.io/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/image/2",
+ "url": "http://localhost:1313/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
+ "contentUrl": "http://localhost:1313/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
"caption": "Building Modes"
}
]
@@ -252,6 +252,24 @@
+ About
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/examples/cablestayed/index.html b/examples/cablestayed/index.html
index e2625817..6f8f1077 100644
--- a/examples/cablestayed/index.html
+++ b/examples/cablestayed/index.html
@@ -25,7 +25,7 @@
-
+
@@ -508,9 +508,9 @@
@@ -845,7 +845,7 @@
-
+
diff --git a/examples/cantilevertransient/index.html b/examples/cantilevertransient/index.html
index 4e41f92f..fb63a7c5 100644
--- a/examples/cantilevertransient/index.html
+++ b/examples/cantilevertransient/index.html
@@ -25,7 +25,7 @@
-
+
@@ -659,7 +659,7 @@ Create a section section = opensees.section.from_aisc("Fiber", "W24x131", # "W14x426",
sec_tag, tag=mat_tag, mesh=SecData, ndm=2, units=units)
import sees.section
sees.section.render(section);
Output:
-
+
<Figure size 350x262.5 with 1 Axes>
Printing the fiber section will display the effective
cross-sectional properties which result from quadrature over the cross section fibers:
print(section)
Output:
@@ -792,7 +792,7 @@ Displacement History
AxHndl.plot(Xp,Yp,'b')
FigHndl.savefig("drift.png")Output:
-
+
<Figure size 350x262.5 with 1 Axes>
Shear force-displacement history
@@ -806,7 +806,7 @@ Shear force-displaceme
AxHndl.plot(Xp, Yp, 'b')
plt.show()
Output:
-
+
<Figure size 350x262.5 with 1 Axes>
@@ -1168,7 +1168,7 @@ Shear force-displaceme
-
+
diff --git a/examples/chopra-10.4/index.html b/examples/chopra-10.4/index.html
index d5d92a72..ccf584b5 100644
--- a/examples/chopra-10.4/index.html
+++ b/examples/chopra-10.4/index.html
@@ -25,7 +25,7 @@
-
+
@@ -634,13 +634,13 @@ Instructions on
Python
Tcl
@@ -656,7 +656,7 @@ Instructions on
-
+
python EigenAnal_twoStoryShearFrame8.py
@@ -667,7 +667,7 @@ Instructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
solve().
+This function adopts an incremental approach
+where the load is applied in small steps of varying size.
+The arguments to the function are:model: an OpenSees Model objectnode : an integer indicating which node to collect results from.arch_model helper function mentioned
+above.def analyze(model, mid, increment, steps, dx, *args):
- dof = 2
+ # Initialize some variables
+ xy = [] # Container to hold solution history (i.e., load factor and displacement at `node`)
+ status = 0 # Convergence flag; Model.analyze() will return 0 if successful.
- xy = []
-
- status = 0
-
- increment(model, mid, dof, dx, *args)
+ # Configure the first load increment strategy; explained below
+ increment(model, dx, *args)
for step in range(steps):
- if status != 0:
- dx /= 2
- increment(model, mid, dof, dx, *args)
+ # 1. Perform Newton-Raphson iterations until convergence for 1 load
+ # increment
status = model.analyze(1)
- xy.append([model.nodeDisp(mid, dof), model.getTime()])
+ # 2. Store the displacement and load factor
+ xy.append([model.nodeDisp(mid, 2), model.getTime()])
+ # 3. If the iterations failed, try cutting
+ # the increment arc-length in half
+ if status != 0:
+ dx /= 2
+ increment(model, dx, *args)
return np.array(xy).TThe Framework
- Solution 2
-
-Iterative strategy: Constant vertical displacement under the load, $v_6$ (Section 3.2)
+Iterative strategy: Constant vertical displacement under the load, $u_{\mathrm{mid}}$ (Section 3.2)
-Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2)
+Load incrementation strategy: Incrementation of the displacement component $u_{\mathrm{mid}}$ (Section 4.1.2)
- Solution 3
-
Iterative strategy: Constant arc-length (Section 3.3)
@@ -686,27 +829,28 @@
The Framework
-Load incrementation strategy: Incrementation of the displacement component $v_6$ (Section 4.1.2) +Load incrementation strategy: Incrementation of the displacement component $u_{\mathrm{mid}}$ (Section 4.1.2)
The Framework
def solution0(model, mid, dof, dx):
+def solution0(model, dx):
model.integrator("LoadControl", 400.0)
-def solution1(model, mid, dof, dx):
+def solution1(model, dx):
Jd = 5
model.integrator("LoadControl", dx, Jd, -800., 800.)
-def solution2(model, mid, dof, dx):
+def solution2(model, dx, *args):
Jd = 5
+ mid, dof = args
model.integrator("DisplacementControl", mid, dof, dx, Jd)
-def norm_control(model, mid, dof, dx):
+def norm_control(model, dx, *args):
Jd = 15
- model.integrator("MinUnbalDispNorm", dx, Jd, -10, 10, "-det")
+ model.integrator("MinUnbalDispNorm", dx, Jd, -10, 10, det=True)
-def arc_control(model, mid, dof, dx, a):
- model.integrator("ArcLength", dx, a, det=True, exp=0.5, reference="point")
fig, ax = plt.subplots()
+def arc_control(model, dx, *args, a=0):
+ model.integrator("ArcLength", dx, a, det=True, exp=0.0, reference="point")
fig, ax = plt.subplots()
# x, y = solution0(*arch_model(), 6, 400.0)
# ax.plot(-x, y, 'x', label="S0")
@@ -715,24 +859,25 @@ The Framework
# ax.plot(-x, y, 'x', label="S1")
# print(y)
-x, y = analyze(*arch_model(), solution2, 7, -150)
+model, mid = arch_model()
+x, y = analyze(model, mid, solution2, 7, -150, *(mid, 2))
ax.plot(-x, y, 'o', label="S2")
-x, y = analyze(*arch_model(), solution2, 536, -1.5)
+x, y = analyze(*arch_model(), solution2, 536, -1.5, *(mid, 2))
ax.plot(-x, y, '-', label="S2")
# x, y = analyze(*arch_model(), arc_control, 9500, 0.5, 0)
# ax.plot(-x, y, "-", label="arc")
-# Requires -det
-x, y = analyze(*arch_model(), arc_control, 110, 45, 0)
+
+x, y = analyze(*arch_model(), arc_control, 110, 45)
ax.plot(-x, y, "x", label="arc")
-x, y = analyze(*arch_model(), arc_control, 80, 88, 0)
-ax.plot(-x, y, "+", label="arc")
+# x, y = analyze(*arch_model(), arc_control, 80, 88, 0)
+# ax.plot(-x, y, "+", label="arc")
-x, y = analyze(*arch_model(), arc_control, 80, 188, 0)
-ax.plot(-x, y, "*", label="arc")
+# x, y = analyze(*arch_model(), arc_control, 80, 188, 0)
+# ax.plot(-x, y, "*", label="arc")
# x, y = analyze(*arch_model(), arc_control, 8000, 0.8, 0)
# ax.plot(-x, y, "x", label="arc")
@@ -741,18 +886,21 @@ The Framework
# ax.plot(-x, y, "-", label="norm")
+ax.set_title("Displacement vs Load Factor")
+ax.set_ylabel(r"Load factor $\lambda$")
+ax.set_xlabel("Displacement $u$")
+
ax.set_xlim([0, 1200])
ax.set_ylim([-800, 3000])
-fig.legend()
Output:
-[0;31m FAILURE[0m :: Iter: 25, Norm: 49845.5, Norm deltaX: 152.498
-[0;31m FAILURE[0m :: Iter: 25, Norm: 11340.8, Norm deltaX: 123.419
-ArcLength::update() - imaginary roots due to multiple instability directions - initial load increment was too large
-a: 6.20586 b: -2674.5 c: 319258 b24ac: -772128
-[0;31m FAILURE[0m :: Iter: 25, Norm: 3293.9, Norm deltaX: 54.5382
<matplotlib.legend.Legend at 0x7f1ddb0b8d00>
-<Figure size 2560x1920 with 1 Axes>
plt.plot(-x, '.')
Output:
-[<matplotlib.lines.Line2D at 0x7f1dd8e8ec40>]
-<Figure size 2560x1920 with 1 Axes>
ax.plot(-x, ".")
Output:
-[<matplotlib.lines.Line2D at 0x7f1dd8cc8340>]
The following animation of the solution is created in
+
fig.legend();<Figure size 2560x1920 with 1 Axes>fix, ax = plt.subplots()
+ax.plot(-x, '.');
+ax.set_title("Displacement vs Step Number")
+ax.set_ylabel("Displacement $u$")
+ax.set_xlabel("Analysis step $n$");<Figure size 2560x1920 with 1 Axes>Animating.ipynb
+
+References + +
++- - - - - - - -Clarke, M.J. and Hancock, G.J. (1990) ‘A study of incremental‐iterative strategies for non‐linear analyses’, International Journal for Numerical Methods in Engineering, 29(7), pp. 1365–1391. Available at: + +https://doi.org/10.1002/nme.1620290702 + + .
+
@@ -835,6 +976,13 @@
@@ -1124,6 +1272,7 @@ The Framework On this page: +
The Framework The Framework
+
diff --git a/examples/buildingmodes/index.html b/examples/buildingmodes/index.html
index a720aab5..677a085f 100644
--- a/examples/buildingmodes/index.html
+++ b/examples/buildingmodes/index.html
@@ -3,7 +3,7 @@
-
+
@@ -12,10 +12,10 @@
-
+
-
+
@@ -25,7 +25,7 @@
-
+
@@ -44,16 +44,16 @@
OpenSees - Building Modes
-
+
-
+
-
+
@@ -63,7 +63,7 @@
-
+
@@ -75,14 +75,14 @@
"@graph": [
{
"@type": "Organization",
- "@id": "https://stairlab.github.io/#/schema/organization/1",
+ "@id": "http://localhost:1313/#/schema/organization/1",
"name": "STAIRlab",
- "url": "https://stairlab.github.io/",
+ "url": "http://localhost:1313/",
"sameAs": [null,"https://github.com/claudioperez/OpenSeesRT"],
"image": {
"@type": "ImageObject",
- "@id": "https://stairlab.github.io/#/schema/image/1",
- "url": "https://stairlab.github.io/img/logo1280x640.png",
+ "@id": "http://localhost:1313/#/schema/image/1",
+ "url": "http://localhost:1313/img/logo1280x640.png",
"width": 1280 ,
"height": 640 ,
"caption": "STAIRlab"
@@ -90,48 +90,48 @@
},
{
"@type": "WebSite",
- "@id": "https://stairlab.github.io/#/schema/website/1",
- "url": "https://stairlab.github.io/",
+ "@id": "http://localhost:1313/#/schema/website/1",
+ "url": "http://localhost:1313/",
"name": "OpenSees",
"description": "OpenSees Examples.",
"publisher": {
- "@id": "https://stairlab.github.io/#/schema/organization/1"
+ "@id": "http://localhost:1313/#/schema/organization/1"
}
},
{
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/",
- "url": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/",
+ "url": "http://localhost:1313/opensees-gallery/examples/buildingmodes/",
"name": "Building Modes",
"description": "A building is modeled as a cantilever, and the first three mode shapes are plotted.",
"isPartOf": {
- "@id": "https://stairlab.github.io/#/schema/website/1"
+ "@id": "http://localhost:1313/#/schema/website/1"
},
"about": {
- "@id": "https://stairlab.github.io/#/schema/organization/1"
+ "@id": "http://localhost:1313/#/schema/organization/1"
},
"dateModified": "2024-09-19T09:17:28CET","breadcrumb": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1"
},
"primaryImageOfPage": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/image/2"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/image/2"
},
"inLanguage": "en-US",
"potentialAction": [{
- "@type": "ReadAction", "target": ["https://stairlab.github.io/opensees-gallery/examples/buildingmodes/"]
+ "@type": "ReadAction", "target": ["http://localhost:1313/opensees-gallery/examples/buildingmodes/"]
}]
},
{
"@type": "BreadcrumbList",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/breadcrumb/1",
"name": "Breadcrumbs",
"itemListElement": [{
"@type": "ListItem",
"position": 1 ,
"item": {
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/",
- "url": "https://stairlab.github.io/opensees-gallery/",
+ "@id": "http://localhost:1313/opensees-gallery/",
+ "url": "http://localhost:1313/opensees-gallery/",
"name": "Home"
}
},{
@@ -139,15 +139,15 @@
"position": 2 ,
"item": {
"@type": "WebPage",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/",
- "url": "https://stairlab.github.io/opensees-gallery/examples/",
+ "@id": "http://localhost:1313/opensees-gallery/examples/",
+ "url": "http://localhost:1313/opensees-gallery/examples/",
"name": "Examples"
}
},{
"@type": "ListItem",
"position": 3 ,
"item": {
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/"
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/"
}
}]
},
@@ -157,9 +157,9 @@
"@graph": [
{
"@type": "ImageObject",
- "@id": "https://stairlab.github.io/opensees-gallery/examples/buildingmodes/#/schema/image/2",
- "url": "https://stairlab.github.io/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
- "contentUrl": "https://stairlab.github.io/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
+ "@id": "http://localhost:1313/opensees-gallery/examples/buildingmodes/#/schema/image/2",
+ "url": "http://localhost:1313/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
+ "contentUrl": "http://localhost:1313/opensees-gallery/opensees-gallery/examples/buildingmodes/img/mode_shapes-1280x640.png",
"caption": "Building Modes"
}
]
@@ -252,6 +252,24 @@
+ About
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/examples/cablestayed/index.html b/examples/cablestayed/index.html
index e2625817..6f8f1077 100644
--- a/examples/cablestayed/index.html
+++ b/examples/cablestayed/index.html
@@ -25,7 +25,7 @@
-
+
@@ -508,9 +508,9 @@
@@ -845,7 +845,7 @@
-
+
diff --git a/examples/cantilevertransient/index.html b/examples/cantilevertransient/index.html
index 4e41f92f..fb63a7c5 100644
--- a/examples/cantilevertransient/index.html
+++ b/examples/cantilevertransient/index.html
@@ -25,7 +25,7 @@
-
+
@@ -659,7 +659,7 @@ Create a section section = opensees.section.from_aisc("Fiber", "W24x131", # "W14x426",
sec_tag, tag=mat_tag, mesh=SecData, ndm=2, units=units)
import sees.section
sees.section.render(section);
Output:
-
+
<Figure size 350x262.5 with 1 Axes>
Printing the fiber section will display the effective
cross-sectional properties which result from quadrature over the cross section fibers:
print(section)
Output:
@@ -792,7 +792,7 @@ Displacement History
AxHndl.plot(Xp,Yp,'b')
FigHndl.savefig("drift.png")Output:
-
+
<Figure size 350x262.5 with 1 Axes>
Shear force-displacement history
@@ -806,7 +806,7 @@ Shear force-displaceme
AxHndl.plot(Xp, Yp, 'b')
plt.show()
Output:
-
+
<Figure size 350x262.5 with 1 Axes>
@@ -1168,7 +1168,7 @@ Shear force-displaceme
-
+
diff --git a/examples/chopra-10.4/index.html b/examples/chopra-10.4/index.html
index d5d92a72..ccf584b5 100644
--- a/examples/chopra-10.4/index.html
+++ b/examples/chopra-10.4/index.html
@@ -25,7 +25,7 @@
-
+
@@ -634,13 +634,13 @@ Instructions on
Python
Tcl
@@ -656,7 +656,7 @@ Instructions on
-
+
python EigenAnal_twoStoryShearFrame8.py
@@ -667,7 +667,7 @@ Instructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
@@ -845,7 +845,7 @@
-
+
diff --git a/examples/cantilevertransient/index.html b/examples/cantilevertransient/index.html
index 4e41f92f..fb63a7c5 100644
--- a/examples/cantilevertransient/index.html
+++ b/examples/cantilevertransient/index.html
@@ -25,7 +25,7 @@
-
+
@@ -659,7 +659,7 @@
Create a section section = opensees.section.from_aisc("Fiber", "W24x131", # "W14x426", sec_tag, tag=mat_tag, mesh=SecData, ndm=2, units=units)
import sees.section
sees.section.render(section);Output:
-
+
<Figure size 350x262.5 with 1 Axes>Printing the fiber section will display the effective cross-sectional properties which result from quadrature over the cross section fibers:
print(section)Output:
@@ -792,7 +792,7 @@Displacement History
AxHndl.plot(Xp,Yp,'b')
FigHndl.savefig("drift.png")Output:
-
+
<Figure size 350x262.5 with 1 Axes>
Shear force-displacement history
@@ -806,7 +806,7 @@ Shear force-displaceme
AxHndl.plot(Xp, Yp, 'b')
plt.show()
Output:
-
+
<Figure size 350x262.5 with 1 Axes>
@@ -1168,7 +1168,7 @@ Shear force-displaceme
-
+
diff --git a/examples/chopra-10.4/index.html b/examples/chopra-10.4/index.html
index d5d92a72..ccf584b5 100644
--- a/examples/chopra-10.4/index.html
+++ b/examples/chopra-10.4/index.html
@@ -25,7 +25,7 @@
-
+
@@ -634,13 +634,13 @@ Instructions on
Python
Tcl
@@ -656,7 +656,7 @@ Instructions on
-
+
python EigenAnal_twoStoryShearFrame8.py
@@ -667,7 +667,7 @@ Instructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
<Figure size 350x262.5 with 1 Axes>Shear force-displaceme AxHndl.plot(Xp, Yp, 'b') plt.show()
Output:
-
+
<Figure size 350x262.5 with 1 Axes>Shear force-displaceme
-
+
diff --git a/examples/chopra-10.4/index.html b/examples/chopra-10.4/index.html
index d5d92a72..ccf584b5 100644
--- a/examples/chopra-10.4/index.html
+++ b/examples/chopra-10.4/index.html
@@ -25,7 +25,7 @@
-
+
@@ -634,13 +634,13 @@ Instructions on
Python
Tcl
@@ -656,7 +656,7 @@ Instructions on
-
+
python EigenAnal_twoStoryShearFrame8.py
@@ -667,7 +667,7 @@ Instructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
Instructions on
-
+
python EigenAnal_twoStoryShearFrame8.py
@@ -667,7 +667,7 @@ Instructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
python EigenAnal_twoStoryShearFrame8.pyInstructions on
-
+
python -m opensees EigenAnal_twoStoryShearFrame8.tcl
@@ -697,13 +697,13 @@ Create the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
python -m opensees EigenAnal_twoStoryShearFrame8.tclCreate the model Python
Tcl
@@ -719,7 +719,7 @@ Create the model
+
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-
import opensees.openseespy as ops
@@ -732,7 +732,7 @@ Create the model
+
model BasicBuilder -ndm 2 -ndf 3
@@ -759,13 +759,13 @@ Create the model Python
Tcl
@@ -781,7 +781,7 @@ Create the model
+
model.node(1, 0., 0.)
model.node(2, L , 0.)
@@ -797,7 +797,7 @@ Create the model
+
node 1 0. 0. ;
node 2 $L 0. ;
@@ -826,13 +826,13 @@ Create the model Python
Tcl
@@ -848,7 +848,7 @@ Create the model
+
model.fix(1, 1, 1, 1)
model.fix(2, 1, 1, 1)
@@ -860,7 +860,7 @@ Create the model
+
fix 1 1 1 1;
fix 2 1 1 1;
@@ -887,13 +887,13 @@ Create the model Python
Tcl
@@ -909,7 +909,7 @@ Create the model
+
model.mass(3, m , 0., 0. )
model.mass(4, m , 0., 0. )
@@ -923,7 +923,7 @@ Create the model
+
mass 3 $m 0. 0. ;
mass 4 $m 0. 0. ;
@@ -954,13 +954,13 @@ Create the model Python
Tcl
@@ -976,7 +976,7 @@ Create the model
+
model.element("ElasticBeamColumn", 1, 1, 3, Ac, Ec, 2.*Ic, TransfTag)
model.element("ElasticBeamColumn", 2, 3, 5, Ac, Ec, Ic, TransfTag)
@@ -992,7 +992,7 @@ Create the model
+
element elasticBeamColumn 1 1 3 $Ac $Ec [expr 2.*$Ic] $TransfTag;
element elasticBeamColumn 2 3 5 $Ac $Ec $Ic $TransfTag;
@@ -1031,13 +1031,13 @@ Define recorders Python
Tcl
@@ -1053,7 +1053,7 @@ Define recorders
+
for k in range(numModes):
model.recorder("Node", f"eigen {k}", file=f"modes/mode{k}.out", nodeRange=[1, 6], dof=[1, 2, 3])
@@ -1065,7 +1065,7 @@ Define recorders
+
foreach k [range $numModes] {
recorder Node -file [format "modes/mode%i.out" $k] -nodeRange 1 6 -dof 1 2 3 "eigen $k"
@@ -1115,13 +1115,13 @@ Display mode shapes
@@ -1465,7 +1465,7 @@ Display mode shapes
+
diff --git a/examples/concretesurface/index.html b/examples/concretesurface/index.html
index d1b95cf8..1bcf029d 100644
--- a/examples/concretesurface/index.html
+++ b/examples/concretesurface/index.html
@@ -25,7 +25,7 @@
-
+
@@ -911,7 +911,7 @@
-
+
diff --git a/examples/example1/index.html b/examples/example1/index.html
index cbcf9819..1cf92281 100644
--- a/examples/example1/index.html
+++ b/examples/example1/index.html
@@ -25,7 +25,7 @@
-
+
@@ -1415,13 +1415,13 @@ Model
Tcl
Python(RT)
@@ -1437,7 +1437,7 @@ Model
-
+
model -ndm 2 -ndf 2
@@ -1448,7 +1448,7 @@ Model
-
+
import opensees.openseespy as ops
@@ -1485,13 +1485,13 @@ Model
Tcl
Python(RT)
@@ -1507,7 +1507,7 @@ Model
-
+
# Create nodes & add to domain
# tag X Y
@@ -1523,7 +1523,7 @@ Model
-
+
# Create nodes
# tag X Y
@@ -1551,13 +1551,13 @@ Model
Tcl
Python(RT)
@@ -1573,7 +1573,7 @@ Model
-
+
# Set the boundary conditions
# tag X Y
@@ -1588,7 +1588,7 @@ Model
-
+
# set the boundary conditions
# nodeID xRestrnt? yRestrnt?
@@ -1617,13 +1617,13 @@ Model
Tcl
Python(RT)
@@ -1639,7 +1639,7 @@ Model
-
+
# Create Elastic material prototype
uniaxialMaterial Elastic 1 3000;
@@ -1651,7 +1651,7 @@ Model
-
+
# Create Elastic material prototype
model.uniaxialMaterial("Elastic", 1, 3000)
@@ -1682,13 +1682,13 @@ Model
Tcl
Python(RT)
@@ -1704,7 +1704,7 @@ Model
-
+
element Truss 1 1 4 10.0 1;
element Truss 2 2 4 5.0 1;
@@ -1717,7 +1717,7 @@ Model
-
+
# Type tag nodes Area material
model.element("Truss", 1, (1, 4), 10.0, 1 )
@@ -1772,13 +1772,13 @@ Loads
Tcl
Python(RT)
@@ -1794,7 +1794,7 @@ Loads
-
+
set loads {4 100 -50}
@@ -1805,7 +1805,7 @@ Loads
-