A Novel Perspective Process Simulation Framework Based on Automatic
Differentiation
- URL: http://arxiv.org/abs/2311.11129v1
- Date: Sat, 18 Nov 2023 17:37:33 GMT
- Title: A Novel Perspective Process Simulation Framework Based on Automatic
Differentiation
- Authors: Shaoyi Yang
- Abstract summary: We use state-of-the-art automatic differentiation frameworks for thermodynamic calculations to obtain precise derivatives without altering the logic of the algorithm.
This contrasts with traditional numerical differentiation algorithms and significantly improves the convergence and computational efficiency of process simulations.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Thermodynamic and flash equilibrium calculations are the cornerstones of
simulation process calculations. The iterative approach, a widely used
nonlinear problem-solving technique, relies on derivative calculations
throughout the procedure that directly affect the stability and effectiveness
of the solution. In this study, we use state-of-the-art automatic
differentiation frameworks for thermodynamic calculations to obtain precise
derivatives without altering the logic of the algorithm. This contrasts with
traditional numerical differentiation algorithms and significantly improves the
convergence and computational efficiency of process simulations in contrast to
numerical differentiation algorithms. Standard chemical phase equilibrium
calculations such as PT, PV, and PH flash are used to evaluate an automated
differentiation approach with respect to numerical stability and iteration
counts. It is used to evaluate the iteration count. The results of the
experiment showed that the automatic differentiation method has a more uniform
gradient distribution and requires fewer convergence iterations. The
experimental results show that the system shows that the process is more
uniform. The gradient distribution and computational convergence curves help to
highlight the improvements provided by automatic differentiation. In addition,
this method shows greater generalizability and can be used more easily in the
calculation of various other chemical simulation modules.
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