An integrated heterogeneous computing framework for ensemble simulations of laser-induced ignition

TL;DR

This paper presents an integrated heterogeneous computing framework for ensemble simulations of laser-induced ignition, combining physics-based modeling, data management, and scalable computing on supercomputers to advance rocket engine research.

Contribution

It introduces a novel, cross-disciplinary computational framework that unifies physics, computer science, and data science for ensemble simulations on heterogeneous supercomputers.

Findings

Framework demonstrates high efficiency, scalability, and accuracy.

Successfully manages ensemble data and performs sensitivity analysis.

Framework is exascale-oriented and serves as a benchmark for future studies.

Abstract

An integrated computational framework is introduced to study complex engineering systems through physics-based ensemble simulations on heterogeneous supercomputers. The framework is primarily designed for the quantitative assessment of laser-induced ignition in rocket engines. We develop and combine an implicit programming system, a compressible reacting flow solver, and a data generation/management strategy on a robust and portable platform. We systematically present this framework using test problems on a hybrid CPU/GPU machine. Efficiency, scalability, and accuracy of the solver are comprehensively assessed with canonical unit problems. Ensemble data management and autoencoding are demonstrated using a canonical diffusion flame case. Sensitivity analysis of the ignition of a turbulent, gaseous fuel jet is performed using a simplified, three-dimensional model combustor. Our approach unifies computer science, physics and engineering, and data science to realize a cross-disciplinary workflow. The framework is exascale-oriented and can be considered a benchmark for future computational science studies of real-world systems.