55 lines
1.5 KiB
Python
55 lines
1.5 KiB
Python
import cantera as ct
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import numpy as np
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import time
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import gaspype as gp
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gas = ct.Solution("gri30.yaml")
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n_species = gas.n_species
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n_states = 1_000_000
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# Random temperatures and pressures
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temperatures = np.linspace(300.0, 2500.0, n_states)
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pressures = np.full(n_states, ct.one_atm)
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# Generate random compositions for H2, H2O, N2
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rng = np.random.default_rng(seed=42)
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fractions = rng.random((n_states, 3))
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fractions /= fractions.sum(axis=1)[:, None] # normalize
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# Convert to full 53-species mole fraction array
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X = np.zeros((n_states, n_species))
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X[:, gas.species_index('H2')] = fractions[:, 0]
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X[:, gas.species_index('H2O')] = fractions[:, 1]
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X[:, gas.species_index('N2')] = fractions[:, 2]
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# Build SolutionArray
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states = ct.SolutionArray(gas, n_states)
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time.sleep(0.5)
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# Vectorized assignment
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t0 = time.perf_counter()
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states.TPX = temperatures, pressures, X
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cp_values = states.cp_mole
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elapsed = time.perf_counter() - t0
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print(f"Computed {n_states} Cp values in {elapsed:.4f} seconds (vectorized cantera)")
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print("First 5 Cp values (J/mol-K):", cp_values[:5] / 1000)
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# Vectorized fluid creation
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fluid = (
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gp.fluid({'H2': 1}) * fractions[:, 0]
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+ gp.fluid({'H2O': 1}) * fractions[:, 1]
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+ gp.fluid({'N2': 1}) * fractions[:, 2]
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)
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time.sleep(0.5)
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# Benchmark: calculate Cp for all states at once
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t0 = time.perf_counter()
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cp_values = fluid.get_cp(t=temperatures)
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elapsed = time.perf_counter() - t0
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print(f"Computed {n_states} Cp values in {elapsed:.4f} seconds (vectorized Gaspype)")
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print("First 5 Cp values (J/mol·K):", cp_values[:5]) |