Neural Networks as Metamodel for Hygrothermal Simulations of Building Components – Reducing the Calculation Time of Probabilistic Assessments KU Leuven
Simulating the hygrothermal response of a building component often involves many uncertainties, such as the exterior and interior climate, or even the exact geometry and material properties. A deterministic assessment often does not suffice to come to a reliable design decision or conclusion, whereas a probabilistic evaluation includes these uncertainties, and thus allows assessing the hygrothermal behaviour and the related damage risks more ...