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Physics-informed neural control of heat flow rate in a counter-flow heat exchanger: modeling, identification and experimental validation
The advanced operation of heat exchangers plays a critical role in the development of efficient and sustainable multivector energy systems. This paper proposes a hybrid physics-informed and data-driven framework for the analysis, identification, and regulation of transient heat transfer in counter-f
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