The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, stiffness remains, and the resulting model requires implicit methods for efficient time integration. In this paper, we outline an approach to formulating the QSSA reduction that is coupled with a strategy to generate C++ source code to evaluate the net species production rate, and the chemical Jacobian. The code-generation component employs a symbolic approach enabling a simple and effective strategy to analytically compute the chemical Jacobian. For computational tractability, the symbolic approach needs to be paired with common subexpression elimination which can negatively affect memory usage. Several solutions are outlined and successfully tested on a 3D multipulse ignition problem, thus allowing portable application across a chemical model sizes and GPU capabilities. The implementation of the proposed method is available at https://github.com/AMReX-Combustion/PelePhysics under an open-source license.

翻译：准稳态近似(QSSA)可有效缩减计算反应流求解器中实施化学机理的规模与刚性。然而在许多应用中，刚性依然存在，导致模型需要隐式方法实现高效时间积分。本文提出一种与C++源代码生成策略相结合的QSSA降阶公式化方法，用于评估净物种生成速率及化学雅可比矩阵。该代码生成组件采用符号化方法，实现了一种简单有效的化学雅可比矩阵解析计算策略。为保证计算可行性，符号方法需结合公共子表达式消除技术，但这可能对内存使用产生负面影响。本文提出了多种解决方案，并在三维多脉冲点火问题上成功验证，使得该方法可在不同化学模型规模及GPU算力间实现可移植应用。所提方法的实现代码以开源许可证形式发布于https://github.com/AMReX-Combustion/PelePhysics。