An experimental methodology for the calibration of indoor building environment models using thermal point clouds and CFD simulation
This paper presents an experimental methodology employing thermal point clouds (TPCs) of indoor spaces to develop and calibrate Computational Fluid Dynamics (CFD) models for simulating indoor building environments. TPCs, captured at various time intervals, provide geometry and surface temperatures o...
| Autores: | , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Recursos: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/40926 |
| Acesso em linha: | https://doi.org/10.1080/17512549.2024.2358923 https://hdl.handle.net/10578/40926 |
| Access Level: | acceso abierto |
| Palavra-chave: | CFD indoors innovative calibration thermal point clouds thermal properties |
| Resumo: | This paper presents an experimental methodology employing thermal point clouds (TPCs) of indoor spaces to develop and calibrate Computational Fluid Dynamics (CFD) models for simulating indoor building environments. TPCs, captured at various time intervals, provide geometry and surface temperatures of the space envelope are crucial for initial and final contrast parameters in model calibration. Segments from TPCs of interior surfaces serve as ground truth for calibrating theoretical CFD models. This involves adjusting boundary conditions to approximate real surface temperature distributions on selected walls. The innovative calibration approach incorporates automatic wall segmentation processes, enabling comparison between in-situ measured and simulated values. A case study assesses the similarity between real thermal orthoimages and CFD simulations, employing qualitative and quantitative analysis with a convergence criterion. Results validate the methodology, highlighting the need for further automation of manual processes. |
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