Goal-oriented sensor placement and model updating strategies applied to a real building in the Sense-City equipment under controlled winter and heat wave scenarios

Abstract A goal-oriented inverse technique is proposed for the accurate computation of quantities of interest in thermal building problems. In contrast to the standard inverse methods, only the model parameters sensitive to the chosen quantity of interest are updated. The technique is applied to a real building in the Sense-City equipment. A two-zone thermal model described by 15 parameters is used. To study the robustness of the inverse method, two controlled climate scenarios conducted in Sense-City, i.e. the Carpentras (south of France) winter and the Paris 2003 heatwave, and five different quantities of interest are considered. For all the the chosen quantities of interest, it is shown that very few model parameters need to be updated by the inverse technique leading to a better estimation of the quantity of interest. The obtained results are experimentally validated using the sensor outputs and a controlled stationary climate test in the Sense-City equipment. The goal-oriented framework is also used for optimal sensor placement. A first application shows that the number of temperature sensors can be drastically reduced to compute a quantity of interest. Last, for operational use, the proposed method is integrated in a software chain containing computer-aided design and thermal dynamic simulation tools. All sensor outputs are provided in the companion paper [25] .