首页|University of Missouri Researcher Yields New Study Findings on Machine Learning (Machine Learning for Modeling Oscillating Heat Pipes: A Review)
University of Missouri Researcher Yields New Study Findings on Machine Learning (Machine Learning for Modeling Oscillating Heat Pipes: A Review)
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New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of Missouri by NewsRx correspondents, research stated, "Oscillating heat pipes are heat transfer devices with the potential of addressing some of the most pressing current thermal management problems, from the miniaturization of microchips to the development of hypersonic vehicles." Financial supporters for this research include Office of Naval Research. The news reporters obtained a quote from the research from University of Missouri: "Since their invention in the 1990s, numerous studies have attempted to develop predictive and inverse design models for oscillating heat pipe function. However, the field still lacks robust and flexible models that can be used to prescribe design specifications based on a target performance. The fundamental difficulty lies in the fact that, despite the simplicity of their design, the mechanisms behind the operation of oscillating heat pipes are complex and only partially understood. To circumvent this limitation, over the last several years, there has been increasing interest in the application of machine learning techniques to oscillating heat pipe modeling. Our survey of the literature has revealed that machine learning techniques have successfully been used to predict different aspects of the operation of these devices. However, many fundamental questions such as which machine learning models are better suited for this task or whether their results can extrapolate to different experimental setups remain unanswered."
University of MissouriCyborgsEmerging TechnologiesMachine Learning
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