Cloud-Repro: 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 computational studies on a public cloud. 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. The present Zenodo dataset contains all secondary data required to reproduce the figures of the manuscript ("Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics") without running the CFD simulations again.为推动研究的透明化与可复现性，便于其他研究者复现相关工作，我们开发了一套可在公有云（public cloud）上执行计算类研究的工作流。该工作流借助Docker容器构建应用软件栈的镜像文件。此外，我们采用了多款工具，用于在计算节点上创建与管理虚拟机，并向这些节点提交计算任务。上述工具的配置文件属于扩充后的可复现性包（reproducibility package）的组成部分：该包除收录输入文件与操作指南外，还涵盖了云计算工作流的定义文件。这一设计可助力研究者重新搭建云环境，在完全一致的条件下复现整套计算流程。 本Zenodo数据集包含复现论文《Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics》配图所需的全部二级数据，且无需再次运行计算流体动力学（Computational Fluid Dynamics，CFD）模拟。