Scalable Implicit Flow Solver for Realistic Wing Simulations with Flow Control

Abstract

Massively parallel computation provides an enormous capacity to perform simulations on a timescale that can change the paradigm of how scientists, engineers, and other practitioners use simulations to address discovery and design. This work considers an active flow control application on a realistic and complex wing design that could be leveraged by a scalable, fully implicit, unstructured flow solver and access to high-performance computing resources. The article describes the active flow control application; then summarizes the main features in the implementation of a massively parallel turbulent flow solver, PHASTA; and finally demonstrates the methods strong scalability at extreme scale. Scaling studies performed with unstructured meshes of 11 and 92 billion elements on the Argonne Leadership Computing Facility's Blue Gene/Q Mira machine with up to 786,432 cores and 3,145,728 MPI processes.