VISUALISATION OF 4D THERMAL MAPS
Abstract
Today, there are many building energy simulation systems. Most rely on theoretical thermal models and numerical simulations to improve the building design and achieve good energy-efficient living conditions. The 3D visualisation technique proposed in this paper analyses temperature distribution in a room. A room is divided into uniform grids, and the temperature field is established by calculating temperature values for each cell using an inverse distance weighted interpolation algorithm with sensor data. These cells are visualised by voxel rendering. An X3D simulation system coupled with a cost-effective set of temperature sensors can provide valuable insights into room design. A measured thermal status can lead to energy savings and improved thermal comfort with improved efficiency. The paper discusses the cost-effective and simplified process for a hardware-software prototype system that can provide real data-driven 4D thermal maps for buildings. The system can be extended to provide 4D thermal maps for more rooms and multi-storey buildings.
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References
P.X. Gao, A.R. Curtis,B. Wong,S. Keshav: It's not easy being green. ACM SIGCOMM Computer Communication Review, 42(4), 211-22, 2012
M.C. Hao, R.K. Sharma, D.A. Keim, U. Dayal, C. Patel, R. Vennelakanti: Application of Visual Analytics for Thermal State Management in Large Data Centres, Computer Graphics Forum, 29(6):1895-904, 2010
S. Yan, X. Li: Analytical expression of indoor temperature distribution in generally ventilated room with arbitrary boundary conditions, Energy and Buildings, Vol. 208, 2020
H.Edtmayer, D. Brandl, T. Mach, E. Schlager, H. Gursch, M. Lugmair, C. Hochenauer: Modelling virtual sensors for real-time indoor comfort control, Journal of Building Engineering, Vol. 67, 2023
C. Lou, H.C. Zhou: Deduction of the two-dimensional distribution of temperature in a cross section of a boiler furnace from images of flame radiation, Combust. Flame, Vol. 143 (1–2), p.p. 97-105, 2005
G.Jiang, M.Kang, Z.Cai, H.Wang, Y.Liu, W.Wang: Online reconstruction of 3D temperature field fused with POD-based reduced order approach and sparse sensor data, International Journal of Thermal Sciences, Vol. 175, 2022
B. Lange, N. Rodriguez, W. Puech, H. Rey, X. Vasques: A 3D particle visualization system for temperature management. Proceedings of SPIE - The International Society for Optical Engineering, 7868, 2011
H.Edtmayer, D.Brandl, T.Mach, E.Schlager, H.Gursch, M.Lugmair, C.Hochenauer: Modelling virtual sensors for real-time indoor comfort control, Journal of Building Engineering. 67, 2023
R. Jedermann, J. Palafox-Albarrán, P. Barreiro, L. Ruiz-García, J. Ignacio Robla, W. Lang, "Interpolation of spatial temperature profiles by sensor networks," SENSORS, 2011 IEEE, Ireland, 778-781, 2011
I. Cohen, D. Gordon: VS: a surface-based system for topological analysis, quantization and visualization of voxel data. Med Image Anal. 13(2), 245-56, 2009
J. Kruger, P. Kipfer, P. Kondratieva,RD. Westermann: A particle system for interactive visualization of 3D flows, IEEE Trans Vis Comput Graph, 11(6), 744-56, 2005
S.M. Seitz, C.R. Dyer: Photorealistic scene reconstruction by voxel coloring. Int J Comput Vision, 35(2):151-73, 1999
N.A. Taranukha, Z.A. Izabekov: A method for voxel visualization of 3D objects. Program Comput Soft+; 33(6):336-42, 2007
MatLab help.
R. Hajovsky, B. Filipova, M. Pies and S. Ozana: Using Matlab for thermal processes modeling and prediction at mining dumps, 12th International Conference on Control, Automation and Systems, p.p. 584-587, 2012
Tim VOXview (https://www.mathworks.com/matlabcentral/fileexchange/78745-voxview), MATLAB Central File Exchange. Retrieved June 1, 2023
F. Quintella, L.P. Soares, A.B. Raposo: DWeb3D: a toolkit for developing X3D applications in a simplified environment, Web3D '10: Proceedings of the 15th International Conference on Web 3D Technology, pp. 45–54, 2010
X. Shen,H. Chen, T.M. Shih, X.Qingyu, Z. Hualin: Construction of three-dimensional temperature distribution using a network of ultrasonic transducers, Scientific Reports 9, 12726, 2019
A. Schweigkofler, O. Braholli, S. Akro, D. Siegele, P. Penna, C. Marcher, L. Tagliabue, D. Matt: Digital Twin as energy management tool through IoT and BIM data integration, CLIMA 2022 conference, 2022
