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.

翻译：热力学与闪蒸平衡计算是仿真过程计算的基石。迭代方法作为一种广泛应用的非线性问题求解技术，在整个过程中依赖于直接影响解的稳定性和有效性的导数计算。本研究采用最先进的自动微分框架进行热力学计算，可在不改变算法逻辑的前提下获得精确导数。这与传统数值微分算法形成鲜明对比，显著提升了过程仿真的收敛性和计算效率。通过标准化学相平衡计算（如PT、PV和PH闪蒸）评估自动微分方法的数值稳定性和迭代次数。实验结果表明，自动微分方法具有更均匀的梯度分布，且所需收敛迭代次数更少。实验结果显示，系统展现出更均匀的梯度分布和计算收敛曲线，有效凸显了自动微分带来的改进。此外，该方法展现出更强的泛化能力，可更便捷地应用于其他各类化学仿真模块的计算中。