Development of a Chemistry Dynamic Load Balancing Solver with Sparse Analytical Jacobian Approach for Rapid and Accurate Reactive Flow Simulations
Yinan Yang, Tsukasa Hori, Shinya Sawada, Fumiteru Akamatsu

TL;DR
This paper presents a rapid, accurate chemical reactive flow solver on OpenFOAM, combining sparse Jacobian, dynamic load balancing, parallel processing, and local time stepping, validated on turbulent premixed flames.
Contribution
It introduces a novel integrated acceleration strategy and a sparse analytical Jacobian approach for reactive flow simulations, improving efficiency and robustness.
Findings
Achieved over 31 times speed-up in simulations.
Validated solver on three turbulent premixed flames.
Provided optimal parameters for various turbulence models.
Abstract
In addressing the demands of industrial high-fidelity computation, the present study introduces a rapid and accurate customized solver developed on the OpenFOAM platform. To enhance computational efficiency, a novel integrated acceleration strategy is introduced. Initially, a sparse analytical Jacobian approach utilizing the SpeedCHEM chemistry library was implemented to increase the efficiency of the ODE solver. Subsequently, the Dynamic Load Balancing (DLB) code was employed to uniformly distribute the computational workload for chemistry among multiple processes. Further optimization was achieved through the introduction of the Open Multi-Processing (OpenMP) method to enhance parallel computing efficiency. Lastly, the Local Time Stepping (LTS) scheme was integrated to maximize the individual time step for each computational cell, resulting in a noteworthy minimum speed-up of over 31…
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Taxonomy
TopicsCombustion and flame dynamics · Computational Fluid Dynamics and Aerodynamics · Fluid Dynamics and Turbulent Flows
