Design Automation of Heat exchangers using Deep reinforcement learning

该项目的目标是进一步开发具有AI引擎的软件，用于热设备的设计自动化。项目的这一阶段对于产品在商业上可行和具有竞争力至关重要。热交换器在去除设备中产生的不需要的热量方面发挥着至关重要的作用，因此在冷却电子设备、HVAC、数据中心和电动汽车中具有广泛的应用。热交换器设计自动化软件能够根据可用空间和操作条件等参数自动优化热交换器几何形状。使用深度强化学习的换热器设计自动化可将设计性能显著提高高达60%，并通过自动化提高工程设计团队的生产力。该项目旨在将新功能应用到现有的设计自动化软件中，以包括大批量制造工艺和可压缩流动条件。该项目的另一个目标是案例研究和制造具有工业应用的原型，以证明所设计的热交换器的可制造性。这些功能的成功实施沿着每次设计成本分析将大大提高热交换器设计自动化软件的商业可行性。它还为行业领导者提供了我们软件功能的概念验证。

The objective of this project is to further develop a software with an AI engine for design automation of thermal devices. This phase of the project is essential for the product to become commercially viable and competitive. Heat exchangers play a vital role for the removal of unwanted heat generated in a device and, as such, have wide variety of applications in cooling electronics, HVAC, data centers, and electric vehicles. Heat exchanger design automation software is capable of automatic optimization of heat exchanger geometry based on parameters such as available space and operating conditions. Design Automation of Heat exchangers using Deep reinforcement learning provides significant improvement in design performance of up to 60 percent and enhances productivity of engineering design teams through automation. This project aims to implement new features into the existing design automation software to include high volume manufacturing processes and compressible flow conditions. Another goal of this project is the case-study and manufacturing of prototypes with industrial applications to demonstrate the manufacturability of the designed heat exchangers. Successful implementation of these features along with cost per design analysis will greatly improve the commercial viability of heat exchanger design automation software. It also provides industry leaders with proof of concept of the capabilities of our software.