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Effects of Relative Rate Information on the Optimization of Detailed Kinetic Models

机译：相对率信息对详细动力学模型优化的影响

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摘要

Mathematical tools are increasingly employed to adjust rate constants in complex detailed kinetic models to make them consistent with multiple sets of experimental data. Such model optimization methods typically begin with the assignment of uncertainties in the absolute rate constants in a starting model, followed by variation of the rate constants within these uncertainty bounds in order to tune rate parameters to match model outputs to experimental observations. The present work examines the impact of including information on relative reaction rates in the optimization strategy, which is not typically done in current implementations. It is shown that where such rate constant data is available, the available parameter space changes dramatically due to the correlations inherent in such measurements. Relative rate constants are typically measured with greater relative accuracy than corresponding absolute rate constant measurements, which further reduces the available parameter space. This significantly affects the uncertainty in the model outcomes as a result of kinetic parameter uncertainties. We demonstrate this effect by considering a simple example case emulating an ignition event and show that constraints in parameter space from relative rate measurements lead to significantly smaller uncertainty in the output ignition delay time. Implications with respect to the maintenance of physically realistic kinetics in optimized models are also discussed.
机译：数学工具越来越多地用于调整复杂的详细动力学模型中的速率常数，使它们与多组实验数据一致。这种模型优化方法通常从起始模型中的绝对速率常数中的不确定性分配，然后在这些不确定性范围内的速率常数的变化，以便调谐速率参数以将模型输出匹配到实验观察。本工作介绍了包括优化策略中相对反应率的信息的影响，这通常不在当前实施中进行。结果表明，在这种速率常数数据可用的情况下，可用的参数空间由于这种测量中固有的相关性而显着地变化。相对速率常数通常以比相应的绝对速率常数测量更大的相对精度测量，这进一步降低了可用参数空间。由于动力学参数不确定性，这显着影响模型结果中的不确定性。我们通过考虑模拟点火事件的简单示例性案例来证明这种效果，并显示来自相对速率测量的参数空间中的约束导致输出点火延迟时间明显更小的不确定性。还讨论了对优化模型中物理现实动力学维护的影响。

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