- CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality
- Edited by Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi
Semi-Automatic Workflow for Air-Conditioning System Zoning and Simulation
- Yikun Yang
- Yiqun Pan
- Georg Suter
- © 2023 Author(s) |
- CC BY-NC 4.0
- DOI: 10.36253/979-12-215-0289-3.105
Building information modeling (BIM) shows its potential in the performance driven design, where multiple design solutions are generated and selected against certain design goals. This paper proposes a workflow to generate and simulate multiple thermal zoning schemes toward a semi-automatic design process of air-conditioning (AC) system. Thermal zoning plays a pivotal role in the design thinking of engineers by synthesizing load calculation, equipment sizing, and pipe/duct layout. However, it is often done intuitively with influence on performance unknown at the initial stage. To make it quantitative, we decompose the zoning process into three levels (thermal/control/system) of space aggregation, joining both semantic and numeric characteristics. For the semantic part, space functions are considered by space labeling, accessibility, and adjacency. As to the numeric part, spaces are zoned based on their thermal response similarities, revealed by dynamic mode decomposition on simulated free-float temperature. Then, the system zoning is generated by rolling out convenient distribution network layouts, representing typical fan-coil or variable-air-volume systems. Variables at each level contribute to the "generative" zoning. Based on multiple zoning schemes, the configurations are serialized into EnergyPlus and Modelica inputs for co-simulation. Initial cost, energy consumption, and comfort level of conditioning join together for the zoning evaluation. The entire workflow is implemented in Grasshopper with self-developed plugins
- Keywords:
- BIM,
- Thermal zoning,
- Generative design,
- HVAC system,
- Performance simulation,
Tongji University, China - ORCID: 0000-0002-4702-2608
Tongji University, China - ORCID: 0000-0003-4890-4378
Design Computing Group, Austria - ORCID: 0000-0002-8329-5304
- Berquist, J., Tessier, A., O’Brien, W., & Attar, R. (2017, May). An investigation of generative design for heating, ventilation, and air-conditioning. In Proceedings of the symposium on simulation for architecture and urban design. DOI: 10.5555/3289787.3289805
- Boskic, L., Brown, C.N., & Mezić, I. (2020). Koopman mode analysis on thermal data for building energy assessment. Advances in Building Energy Research. DOI: 10.1080/17512549.2020.1842802
- Brahme, R., Mahdavi, A., Lam, K.P., Gupta, S. (2001, August). Complex building performance analysis in early stages of design: A solution based on differential modeling, homology-based mapping, and generative design agents. In Proceedings of Building Simulation Conference of IBPSA (Vol. 7, p. 661-668). DOI: 10.26868/25222708.2001.0661-668
- Bres, A., Judex, F., Suter, G. de Wilde, P. (2017, September). A method for automated generation of HVAC distribution subsystems for building performance simulation. In Proceedings of Building Simulation Conference of IBPSA (Vol. 15, p. 1548-1557). DOI: 10.26868/25222708.2017.413
- Chen, K. K., Tu, J. H., & Rowley, C. W. (2012). Variants of Dynamic Mode Decomposition: boundary condition, Koopman, and Fourier analyses. Journal of Nonlinear Science, 22, 887-915. DOI: 10.1007/s00332-012-9130-9
- Chen, Z., Guan, H., Yuan, X., Xie, T., Xu, P. (2022). Rule-based generation of HVAC duct routing. Automation in Construction. 139, 104264. DOI: 10.1016/j.autcon.2022.104264
- Fischer, M., Aalami, F., Akbas, & Akbas, R. (1998). Formalizing product model transformations: case examples and applications. In Artificial Intelligence in Structural Engineering, Information Technology for Design, Collaboration, Maintenance, and Monitoring. 113-132. DOI: 10.1007/BFb0030447
- Fu, M., Liu, R., Qi, B., & Issa, R. R. (2020). Generating straight skeleton-based navigation networks with Industry Foundation Classes for indoor way-finding. Automation in Construction, 112, 103057. DOI: 10.1016/j.autcon.2019.103057
- Georgescu, M., & Mezić, I. (2015). Building energy modeling: A systematic approach to zoning and model reduction using Koopman Mode Analysis. Energy and Buildings, 86, 794-802. DOI: 10.1016/j.enbuild.2014.10.046
- Held, S., Korte, B., Rautenbach, D., & Vygen, J. (2011). Combinatorial optimization in VLSI design. Combinatorial Optimization-Methods and Applications, 31, 33-96.
- Medjdoub, B., & Bi, G. (2018). Parametric-based distribution duct routing generation using constraint-based design approach. Automation in Construction, 90, 104-116. DOI: 10.1016/j.autcon.2018.02.006
- Mezić, I. (2005). Spectral properties of dynamical systems, model reduction and decompositions. Nonlinear Dynamics, 41, 309-325. DOI: 10.1007/s11071-005-2824-x
- Raak, F., Susuki, Y., Mezic, I., & Hikihara, T. (2016, December). On Koopman and Dynamic Mode Decompositions for application to dynamic data with low spatial dimension. In Proceedings of IEEE 55th Conference on Decision and Control (CDC) (6485-6491). DOI: 10.1109/CDC.2016.7799267
- Roudsari, M.S., & Pak, M. (2013, August). Ladybug: A parametric environmental plugin for Grasshopper to help designers create an environmentally-conscious design. In Proceedings of Building Simulation Conference of IBPSA (Vol 13. p. 3128-3125). DOI: 10.26868/25222708.2013.2499
- Rowley, C. W., Mezić, I., Bagheri, S., Schlatter, P., & Henningson, D. S. (2009). Spectral analysis of nonlinear flows. Journal of Fluid Mechanics, 641, 115-127. DOI: 10.1017/S0022112009992059
- Schmid, P. J. (2022). Dynamic Mode Decomposition and its variants. Annual Review of Fluid Mechanics, 54, 225–254. DOI: 10.1146/annurev-fluid-030121-015835
- Sugihara, K. (2013). Straight Skeleton for automatic generation of 3-D building models with general shaped roofs. In Proceedings of the 21st International Conference on Computer Graphics, Visualization and Computer Vision.
- Suter, G. (2015, July). Definition of views to generate, visualize, and evaluate multi-view space models of schematic building designs. In Proceedings of 22nd International Workshop: Intelligent Computing in Engineering, EG-ICE.
- Suter, G. (2022). Modeling multiple space views for schematic building design using space ontologies and layout transformation operations. Automation in Construction, 134, 104041. DOI: 10.1016/j.autcon.2021.104041
- Visschers, M.G. (2016). BIM based whole-building energy analysis towards and improved interoperability: A conversion from the IFC file format to a validated gbXML file format. Master thesis. Technische Universiteit Eindhoven.
- Wetter, M., Benne, K., Gautier, A., Nouidui, T.S., Ramle, A., Roth A., Tummescheit, H., Mentzer, S. & Winther C. (2020, September). Lifting the garage door on Spawn, an open-source BEM-controls engine. In Proceedings of Building Performance Modeling Conference and SimBuild (p. 518-525). https://api.semanticscholar.org/CorpusID:221857040
Chapter Information
Chapter Title
Semi-Automatic Workflow for Air-Conditioning System Zoning and Simulation
Authors
Yikun Yang, Yiqun Pan, Georg Suter
DOI
10.36253/979-12-215-0289-3.105
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Bibliographic Information
Book Title
CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality
Book Subtitle
Managing the Digital Transformation of Construction Industry
Editors
Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/979-12-215-0289-3
eISBN (pdf)
979-12-215-0289-3
eISBN (xml)
979-12-215-0257-2
Series Title
Proceedings e report
Series ISSN
2704-601X
Series E-ISSN
2704-5846