arXiv subjects

Olivier Mesnard

Publications and source records attributed to Olivier Mesnard.

3 recordsLinked to original sources

arXiv2021

[Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates

This article reports on a full replication study in computational fluid dynamics, using an immersed boundary method to obtain the flow around a pitching and rolling elliptical wing. As in the original study, the computational experiments investigate the wake topology and aerodynamic forces, looking at the effect of: Reynolds number (100--400), Strouhal number (0.4--1.2), aspect ratio, and rolling/pitching phase difference. We also include a grid-independence study (from 5 to 72 million grid cells). The trends in aerodynamic performance and the characteristics of the wake topology were replicated, despite some differences in results. We declare the replication successful, and make fully available all the digital artifacts and workflow definitions, including software build recipes and container images, as well as secondary data and post-processing code. Run times for each computational experiment were between 8.1 and 13.8 hours to complete 5 flapping cycles, using two compute nodes with dual 20-core 3.7GHz Intel Xeon Gold 6148 CPUs and two NVIDIA V100 GPU devices each.

physics.flu-dyn↗

arXiv2019

Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics

In a new effort to make our research transparent and reproducible by others, we developed a workflow to run and share computational studies on the public cloud Microsoft Azure. It uses Docker containers to create an image of the application software stack. We also adopt several tools that facilitate creating and managing virtual machines on compute nodes and submitting jobs to these nodes. The configuration files for these tools are part of an expanded "reproducibility package" that includes workflow definitions for cloud computing, in addition to input files and instructions. This facilitates re-creating the cloud environment to re-run the computations under the same conditions. Although cloud providers have improved their offerings, many researchers using high-performance computing (HPC) are still skeptical about cloud computing. Thus, we ran benchmarks for tightly coupled applications to confirm that the latest HPC nodes of Microsoft Azure are indeed a viable alternative to traditional on-site HPC clusters. We also show that cloud offerings are now adequate to complete computational fluid dynamics studies with in-house research software that uses parallel computing with GPUs. Finally, we share with the community what we have learned from nearly two years of using Azure cloud to enhance transparency and reproducibility in our computational simulations.

cs.CE↗

arXiv2016

Reproducible and replicable CFD: it's harder than you think

Completing a full replication study of our previously published findings on bluff-body aerodynamics was harder than we thought. Despite the fact that we have good reproducible-research practices, sharing our code and data openly. Here's what we learned from three years, four CFD codes and hundreds of runs.

physics.comp-ph↗