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ChrisZYJChrisZYJ
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fix merge mistakes
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13 files changed

+91
-34
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‎examples/1D_acoustic_gauss_sigmadist/case_restart.py‎

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#!/usr/bin/env python3
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import json
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# Configuring case dictionary
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print(
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json.dumps(
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{
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# Logistics ================================================================
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"run_time_info": "T",
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# ==========================================================================
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# Computational Domain Parameters ==========================================
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"x_domain%beg": 0,
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"x_domain%end": 0.001,
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"m": 199,
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"n": 0,
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"p": 0,
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"dt": 2e-9,
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"t_step_start": 0,
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"t_step_stop": 250,
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"t_step_save": 1,
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# ==========================================================================
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# Simulation Algorithm Parameters ==========================================
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"num_patches": 1,
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"model_eqns": 2,
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"alt_soundspeed": "F",
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"num_fluids": 1,
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"mpp_lim": "F",
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"mixture_err": "F",
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"time_stepper": 3,
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"weno_order": 5,
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"weno_eps": 1.0e-16,
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"teno": "T",
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"teno_CT": 1e-8,
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"null_weights": "F",
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"mp_weno": "F",
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"riemann_solver": 2,
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"wave_speeds": 1,
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"avg_state": 2,
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"bc_x%beg": -6,
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"bc_x%end": -6,
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# ==========================================================================
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# Formatted Database Files Structure Parameters ============================
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"format": 2,
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"precision": 2,
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"prim_vars_wrt": "T",
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"rho_wrt": "T",
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"parallel_io": "T",
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# ==========================================================================
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# Patch 1 Liquid ===========================================================
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"patch_icpp(1)%geometry": 1,
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"patch_icpp(1)%x_centroid": 0.0005,
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"patch_icpp(1)%length_x": 0.001,
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"patch_icpp(1)%vel(1)": 0.0,
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"patch_icpp(1)%pres": 1e05,
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"patch_icpp(1)%alpha_rho(1)": 1100,
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"patch_icpp(1)%alpha(1)": 1.0,
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# ==========================================================================
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# Acoustic source ==========================================================
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"acoustic_source": "T",
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"num_source": 1,
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"acoustic(1)%support": 1,
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"acoustic(1)%loc(1)": 0.0001,
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"acoustic(1)%pulse": 2,
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"acoustic(1)%npulse": 1,
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"acoustic(1)%dir": 1.0,
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"acoustic(1)%mag": 1.0,
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"acoustic(1)%gauss_sigma_dist": 2e-8 * 1493,
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"acoustic(1)%delay": 1e-7,
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# ==========================================================================
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# Fluids Physical Parameters ===============================================
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"fluid_pp(1)%gamma": 1.0e00 / (4.4e00 - 1.0e00),
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"fluid_pp(1)%pi_inf": 4.4e00 * 5.57e08 / (4.4e00 - 1.0e00),
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# ==========================================================================
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}
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)
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)
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# ==============================================================================

‎examples/1D_exp_tube_phasechange/case.py‎

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# save frequency = SF + 1 (because the initial state, 0.dat, is also saved)
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SF = 200
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# making Nt divisible By SF
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# making Nt divisible by SF
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tendA = (xe - xb) / ss * 0.25
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# 1 - ensure NtA is sufficient to go a little beyond tendA

‎examples/2D_axisym_shockwatercavity/case.py‎

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# I calculating tend twice; first is an estimate, second is
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# the actual value used. This is because I am getting errors in the
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# post process part every time I approximate the actual Nt By an integer
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# post process part every time I approximate the actual Nt by an integer
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# number (think of a smarter way).
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# dimensionless time
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# Save Frequency. Note that the number of autosaves will be SF + 1, as th IC (0.dat) is also saved
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SF = 400
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## making Nt divisible By SF
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## making Nt divisible by SF
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# 1 - ensure NtA goes slightly beyond tendA
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NtA = int(tendA // dt + 1)
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‎examples/2D_laplace_pressure_jump/case.py‎

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#!/usr/bin/env python3
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# This case file demonstrates the Laplace pressure jump of a water droplet in air. The laplace pressure jump
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# in 2D is given By delta = sigma / r where delta is the pressure jump, sigma is the surface tension coefficient,
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# in 2D is given by delta = sigma / r where delta is the pressure jump, sigma is the surface tension coefficient,
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# and r is the radius of the droplet. The results of this simulation agree with theory to well within 1%
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# relative error.
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‎examples/2D_phasechange_bubble/case.py‎

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# Critical time-step
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tc = 0.915 * R0 * math.sqrt(rho0wl1 / p01)
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# making Nt divisible By SF
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# making Nt divisible by SF
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# tendA = 1.5 * tc
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tend = 1.2 * tc
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‎examples/2D_phasechange_bubble/casefile.py‎

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# Critical time-step
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tc = 0.915 * R0 * math.sqrt(rho0wl1 / p01)
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# making Nt divisible By SF
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# making Nt divisible by SF
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# tendA = 1.5 * tc
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tend = 1.2 * tc
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‎examples/2D_shocktube_phasechange/case.py‎

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# save frequency = SF + 1 (because the initial state, 0.dat, is also saved)
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SF = 40
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# making Nt divisible By SF
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# making Nt divisible by SF
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tendA = (xe - xb) / ss * 5 / 24
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# 1 - ensure NtA is sufficient to go a little beyond tendA

‎examples/3D_phasechange_bubble/case.py‎

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# Critical time-step
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tc = 0.915 * R0 * math.sqrt(rho0wl1 / p01)
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# making Nt divisible By SF
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# making Nt divisible by SF
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# tendA = 1.5 * tc
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tend = 1.2 * tc
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‎examples/3D_shockdroplet/case.py‎

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# I calculating tend twice; first is an estimate, second is
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# the actual value used. This is because I am getting errors in the
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# post process part every time I approximate the actual Nt By an integer
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# post process part every time I approximate the actual Nt by an integer
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# number (think of a smarter way).
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# dimensionless time
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# Save Frequency. Note that the number of autosaves will be SF + 1, as th IC (0.dat) is also saved
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SF = 400
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## making Nt divisible By SF
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## making Nt divisible by SF
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# 1 - ensure NtA goes slightly beyond tendA
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NtA = int(tendA // dt + 1)
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‎examples/scaling/case.py‎

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# I calculate tend twice; first is an estimate, second is
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# the actual value used. This is because I am getting errors in the
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# post process part every time I approximate the actual Nt By an integer
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# post process part every time I approximate the actual Nt by an integer
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# number (think of a smarter way).
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# dimensionless time
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# Save Frequency. Note that the number of autosaves will be SF + 1, as th IC (0.dat) is also saved
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SF = 400
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## making Nt divisible By SF
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## making Nt divisible by SF
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# 1 - ensure NtA goes slightly beyond tendA
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NtA = int(tendA // dt + 1)
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