How can the integration of phase change materials (PCMs) within structural elements be optimized to minimize thermal bridging in building envelopes, and what role do machine learning algorithms play in predicting and enhancing the thermal performance of these hybrid systems under varying environmental conditions?
After having participated to tests including PCMs in the building envelope, I am rather skeptical about the success of this strategy, in particular in reducing the effects of thermal bridges. Indeed, to include PCMs , the structure of the bridge is modified. It may then be easier to cut the thermal bridge.
Machine learning algorithms are based on existing knowledge that may not exist yet. It may be easier to use existing finite elements software to simulate the thermal bridge, including PCM if required.
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