Applied Math and Software
Theory, Mathematics, and Algorithm and Code Development Supporting Reacting Flow Research
A comprehensive framework for predictive combustion modeling requires many simplifying assumptions for computational affordability. Often modeling choices can only be knowledgably made if the uncertainty associated with alternative formulations has been quantified. This is one of many instances in which uncertainty quantification (UQ) plays a role in research. Additionally, UQ is crucial for risk assessment related to a wide range of Sandia technologies and programs, and more broadly to systems and infrastructure worldwide. The UQ research program at the CRF has accordingly broadened over time from its original focus on needs of the reacting flow effort to a wide range of topics and applications.
Some model simplification needs, such as reducing huge chemical-kinetic mechanisms to manageable form, benefit from systematic methods specially developed for the application. Chemical-kinetic mechanism reduction and the related challenge of speeding up the computational time advancement of such mechanisms are being addressed using a mathematical technique called computational singular perturbation (CSP).
CSP methodology development and use is one of several topics being addressed within the framework of a computational reacting flow study that also focuses on algorithmic requirements resulting from the hierarchical nature of reacting flows (diverse coupled phenomena spanning a wide range of length and time scales). Expertise in numerical simulation of hierarchical systems that has been gained through reacting flow studies is being applied to other hierarchical systems. Likewise, UQ studies have led to a broader perspective on the simulation of stochastic dynamical systems generally.