morgen.ini

morgen_plots = z_plots		# Path to plot folder: **z_plots**
morgen_roms = z_roms		# Path to reduced order models folder: **z_roms**

network_dt = 60.0		# Requested solver time-step [s]: **60.0**
network_vmax = 20.0		# Maximum gas velocity [m/s]: **20.0**
network_cfl = 0.5		# Target CFL constant [1]: **0.5**

model_tuning = 1.0		# Tunable efficiency factor scaling the friction term [1]: 1.0
model_reynolds = 100000.0	# Estimated Reynolds number [1]: 100000.0
model_friction = schifrinson	# Friction factor model: hofer , nikuradse , altshul , **schifrinson** , pmt1025 , igt
model_compressibility = aga88	# Compressibility factor model: ideal , dvgw , **aga88** , papay
model_compref = steady		# Reference for compressibility: **steady** , normal
model_gravity = static		# Gravity term: none, **static**, dynamic

steady_maxiter_lin = 20	# Number of least-norm iterations to refine steady-state estimation: **20** (r >= 1)
steady_maxiter_non = 2000	# Number of time-step iterations to refine steady-state estimation: **1000** (r >= 1)
steady_maxerror = 1e-6		# Maximal error of refined steady-state: **1e-6** (=10^-6)
steady_Tc = -82.595		# Critical temperature [C]: -82.595
steady_pc =  45.988		# Critical pressure [bar]:   45.988
steady_pn =   1.01325		# Normal pressure [bar]:      1.01325

solver_relax = 1.0		# IMEX Solver relaxation: **1.0** (0 < r <= 1.0)
solver_rk2type = 11		# Number of 2nd order hyperbolic Runge-Kutta stages: 5, 6, 7, 8, 9, 10, **11**, 12
solver_rk4type = MeaR99a       # Type of 4th order hyperbolic Runge-Kutta: **MeaR99a**, MeaR99b, TseS05

T0_min =   0.0			# Minimum ambient temperature [C]: 0
T0_max =  20.0			# Maximum ambient temperature [C]: 20.0
Rs_min = 500.0			# Minimum specific gas constant [J/(kg*K)]: 500.0   (Natural gas: 518.3)
Rs_max = 600.0			# Maximum specific gas constant [J/(kg*K)]: 600.0   (Hydrogen:   4124.2)

mor_excitation = step		# Generic training input type: **step** , impulse , random-binary , white-noise
mor_max = 200			# Maximum reduced order: **200** (r > 2)
mor_parametric = true		# Parametric model order reduction: **true** , false
mor_pgrid = 1			# Sparse parameter grid level: **1** (1 <= r < 4)

eval_pnorm = 2			# Parameter norm: 1 , **2** , Inf
eval_skip = 3			# Evaluate every n-th reduced order model: **3**  (r >= 1)
eval_max = 200			# Maximum reduced order to evaluate: **200**  (r >= 2, use Inf for maximum possible)
eval_parametric = true		# Parametric reduced order model evaluation: **true**, false
eval_ptest = 5			# Number of test parameters: **5**  (r >= 1)
eval_gain = false		# Use gain correction: **true**, false