Application of Distributed Computing for High Fidelity AC Machine Analysis

该研究调查了高性能计算（HPC）在应用于电机设计和计算电磁学工具时所带来的机会，包括内部部署和基于云的计算。涉及电磁学、热和结构分析的优化管道需要遍历非常大的搜索空间，这可能导致在典型的个人计算机上难以处理的求解时间。通过将解决方案计算转移到大型分布式系统，解决方案的时间急剧下降。这会在同一时间内产生更多的解决方案;增加设计迭代速率，或者它可以在同一时间内产生更高保真的解决方案;从而实现更优化的机器设计。这一概念已被广泛采用的Ansys，Autodesk等。这项研究是特别感兴趣的汽车设计有限公司，业主的Ansys汽车CAD。MotorCAD是一个参数化电机设计套件，用于端到端电机设计。目前，MotorCAD网格化管道和FEA求解器与其图形用户界面（GUI）紧密耦合。这使得将MotorCAD的FEA解决方案逻辑抽象到分布式系统非常困难，并带来了其他几个问题，包括许可和操作系统锁定，因为MotorCAD的GUI只能在基于Windows的操作系统中运行。这项研究的一部分旨在与Motor Design Ltd.合作，将解决方案逻辑与GUI分离，并构建一个强大的基于云的基础设施，以极大地提高MotorCAD用户的生产力。研究方法的新奇源于对构建专门设计用于大型分布式系统的计算电磁学工具的潜在好处的调查，不仅利用这些系统的大量CPU计数和内存分配，而且还利用缓存，监控，数据存储以及由Web服务提供商提供的大量其他工具，例如AWS，Google Cloud Platform，Azure，这种好的工具必须根据用户的要求优化成本或时间。云计算资源的定价可以与有关特定计算实例的详细信息（例如虚拟CPU计数、内存分配、地理位置等）一起使用，以优化给定时间约束的成本，或者相反地优化在指定预算内快速解决问题的时间。云系统需要网络进行通信，因此还必须考虑网络时间和实例实例化时间。此外，本研究还将研究分布式计算在增材制造（AM）电机设计工具中的应用。这为机器设计提供了进一步的机会，因为与在本地硬件上运行时的解决方案时间相比，可以在易于处理的时间范围内分析高度复杂的定子和绕组几何形状。该项目属于EPSRC“电机和驱动器/电磁学”研究领域的福尔斯。

The research investigates the opportunities presented by high performance computing (HPC), both on-premises and cloud based, when applied to electrical machine design and computational electromagnetics tools. Optimisation pipelines involving electromagnetics, thermal and structural analyses require traversal of very large search spaces, which can lead to intractable solution times on typical personal computers. By moving the solution calculations to large distributed systems solutions times fall precipitously. This results in more solutions in the same time; increasing design iteration rate, or it can result in higher fidelity solutions in the same; leading to more optimal machine designs. This concept has been widely adopted by the likes of Ansys, Autodesk, etc.This research is of particular interest to Motor Design Ltd, the proprietors of Ansys MotorCAD. MotorCAD is a parametric electrical machine design suite for use in end-to-end electrical machine design. At present, the MotorCAD meshing pipeline and FEA solver are tightly coupled to its graphical user interface (GUI). This makes abstracting MotorCAD's FEA solution logic to distributed systems very difficult and carries with it several other issues including licensing and operating system lock-in as MotorCAD's GUI runs only within Windows based operating systems. Part of this research aims to work alongside Motor Design Ltd. to separate the solution logic from the GUI and build a robust cloud-based infrastructure to greatly boost the productivity of MotorCAD users.The novelty of the research methodology stems from the investigation into the potential benefits of building computational electromagnetics tools designed specifically to be run on large distributed systems, utilising not only the large CPU counts and memory allocation of these systems, but also the caching, monitoring, data storage, and a plethora of other tools made available by web service providers such as AWS, Google Cloud Platform, Azure, etc. A good tool of this kind must optimise for either cost or time at the request of the user. Pricing for cloud compute resources can be used with detailed information about specific compute instances (such as virtual CPU count, memory allocation, geographical location, etc) to optimise for cost with a given time constraint, or conversely optimise for fast time to solution within a specified budget. Cloud systems require a network to communicate, therefore network times and instance instantiation times must also be considered. Furthermore, this research will investigate the application of distributed computing to additively manufactured (AM) electrical machine design tools. This presents further opportunities within the context of machine design as highly complex stator and winding geometries can be analysed within tractable timeframes compared with the solution times when run on local hardware.This project falls within the EPSRC "Electrical motors and drives / electromagnetics" research area.