Invertible Design Manifolds for Heat Transfer Surfaces (INVERT)
The DIFFERENTIATE program seeks to leverage the emerging artificial intelligence (AI) revolution to help resolve the energy and environmental challenges of our time. The program aims to speed energy innovation by incorporating machine learning (ML) into the energy technology development process. A core part of AI, ML is the study of computer algorithms that improve automatically through experience. This approach is expected to facilitate a rapid transition to lower-carbon-footprint energy sources and systems. To organize the proposed efforts, the program uses a simplified engineering design process framework to conceptualize several ML tools that could help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation.
Project Innovation + Advantages:
The University of Maryland (UMD) will create inverse design tools for the development of enhanced heat transfer surfaces at reduced computational cost. Heat transfer surfaces are used to increase the efficiency of many energy conversion systems, but they are currently designed in a slow, iterative fashion. UMD will use a direct inverse design method map from given environments and performance metrics to design variables or materials. The project will make use of generative adversarial networks, statistical connections between optimization and dynamical systems, and active learning to achieve its goals. The team will test its tools on turbine blade components and heat exchangers.
DIFFERENTIATE aims to enhance the productivity of energy engineers in helping them to develop next-generation energy technologies. If successful, DIFFERENTIATE will yield the following benefits in ARPA-E mission areas:
Seek U.S. technological competitive advantage by leading the development of machine-learning enhanced engineering design tools.
Use these tools to solve our most challenging energy and environmental problems by facilitating an economically-attractive transition to lower carbon-footprint energy sources and systems
Reap the economic productivity benefits associated with the commercial adoption of the resulting higher-value energy technologies and associated products.
ARPA-E Program Director:
Dr. David TewProject Contact:
Dr. Mark Fuge
Press and General Inquiries Email:
ARPA-E-Comms@hq.doe.govProject Contact Email:
United Technologies Research Center