Towards Scalable Parallel-in-Time Turbulent Flow Simulations

TL;DR

This paper introduces a reformulation for turbulent flow simulations that relaxes initial conditions and allows bidirectional information flow, enabling scalable parallel-in-time computations for chaotic systems.

Contribution

It presents a novel reformulation that makes turbulent flow simulations well-conditioned and suitable for parallel-in-time methods, improving scalability and efficiency.

Findings

Reformulation relaxes initial conditions for turbulent flows.

Simulations become well-conditioned boundary value problems.

Enables scalable parallel-in-time turbulent flow simulations.

Abstract

We present a reformulation of unsteady turbulent flow simulations. The initial condition is relaxed and information is allowed to propagate both forward and backward in time. Simulations of chaotic dynamical systems with this reformulation can be proven to be well-conditioned time domain boundary value problems. The reformulation can enable scalable parallel-in-time simulation of turbulent flows.