Market Assessment for Deep Reinforcement Learning (DRL) based Shape Optimization for Heat Exchangers

点击翻译按钮获取中文摘要

University of Waterloo (UW) researchers Hamdullahpur (Professor, Department of Mechanical and Mechatronics Engineering) Kerameti (PhD candidate, Department of Mechanical and Mechatronics Engineering) have developed a new software-based methodology for the design of complex heat exchangers used in various industrial applications. The invention enables designers to design and build more effective heat exchanger (e.g., higher heat transfer rate, lower pressure drop) without using expensive and time consuming computational fluid dynamics or other numerical method software. Among several, the main advantage of this novel system include changing the geometry by reconfiguring the CAD file automatically toward a desired shape where other methods require conversion to CAD file for downstream tasks such as manufacturing. The combination of AI agents optimizes shapes that construct the geometry of the heat exchanger. This method is developed for the first time by the creators of the current invention. As part of this Market Assessment grant, the selected consultant will perform a thorough market analysis to identify the most suitable market opportunities along with technical challenges associated with the application of the technology in a particular market segment. A favorable market assessment result will further guide the development of a commercialization strategy and in attracting investments.