Computational fluid dynamics through the solution of the Navier–Stokes equations with turbulence models has become commonplace. However, simply solving these equations is not sufficient to be able to perform efficient design optimization with a flow solver in the loop. This paper discusses the recommendations for developing a flow solver that is suitable for efficient aerodynamic and multidisciplinary design optimization. One of the major recommendations is to be able to load the flow solver as a library that provides direct memory access to the relevant data. Other recommendations are to use a higher-level language for scripting and to pay special attention to solution warm starting, code efficiency, flow solver robustness, and solution failure handling. As an example of a flow solver that follows these recommendations, the open-source flow solver ADflow is presented. Results from aerodynamic optimization, aerostructural analysis, and aerostructural optimization using ADflow demonstrate the performance advantages claimed in the recommendations. The publication of these recommendations and the availability of the source code open the door for other solvers to adopt the same application programming interface. ADflow is part of a wider aerodynamic shape optimization tool suite that is also available under an open-source license.

通过带有湍流模型的Navier–Stokes方程的解来进行计算流体动力学已变得司空见惯。但是，仅求解这些方程式不足以通过循环中的流量求解器执行高效的设计优化。本文讨论了开发适用于高效空气动力学和多学科设计优化的流量求解器的建议。主要建议之一是能够将流求解器加载为库，该库提供对相关数据的直接内存访问。其他建议是使用高级语言编写脚本，并特别注意解决方案的热启动，代码效率，流求解器的鲁棒性和解决方案故障的处理。作为遵循这些建议的流量求解器的示例，介绍了开源流求解器ADflow。空气动力学优化，航空结构分析和使用ADflow进行航空结构优化的结果证明了建议中提到的性能优势。这些建议的发布以及源代码的可用性为其他求解器采用相同的应用程序编程接口打开了大门。ADflow是更广泛的空气动力学形状优化工具套件的一部分，该套件也可以通过开源许可获得。这些建议的发布以及源代码的可用性为其他求解器采用相同的应用程序编程接口打开了大门。ADflow是更广泛的空气动力学形状优化工具套件的一部分，该套件也可以通过开源许可获得。这些建议的发布以及源代码的可用性为其他求解器采用相同的应用程序编程接口打开了大门。ADflow是更广泛的空气动力学形状优化工具套件的一部分，该套件也可以通过开源许可获得。