Methodology for the Evaluation of an Energetic Model of Thermal Transmittance in a Window by Means of Horizontal Aggregation (HA) from Short-range Photogrammetry for Model Digital Twin

Abstract

One of the great challenges in the architecture, engineering, and construction (AEC) industry is data communication and its development in modelling techniques. The development of 5G techniques, with the Internet of things (IoT), artificial intelligence (AI), amongst others, is developing significant advances for staging of data integration in the so-called digital twins (DTs). Undoubtedly, the DTs intend to synchronize the real physical data with a digital world that experiences successive changes that occur throughout the life cycle of the system. In this context, this work experiments with a horizontal integration methodology to evaluate the U-value of a window frame from structure from motion (SfM) photogrammetry data, as part of a digital twin. The “in situ” evaluation of the thermal transmittance of a common aluminium window frame that is being used in existing buildings in the 1960s and that reached constructions of the 1980s is addressed. The experimental results apply simulation analysis using two-dimensional software. Thermal transmittance measurement equipment was used through a thermal flow meter plate, and the variations in thermal behaviour were analyzed according to the geometry of the frame. The results show different Uf-value data between the simulation and the in situ measurement with a dispersion variability of 1.5 W/m2K between the models. The essence and originality of the experimentation lie in the integration of horizontal aggregates (HA) as a basis in the simulation, measurement, and reverse engineering processes to an energy model of the DT system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.