Information Processing and Assessment for Improved Computational Energy Modelling

Authors

  • Zuhair A Nasar

DOI:

https://doi.org/10.31185/ejuow.Vol9.Iss1.226

Keywords:

Information Processing, Building Informational Modelling, Computational Model, Parametric Design

Abstract

This study explores how designer interacts with the computational model. This research intends to demystify how “design knowledge” is obtained, used and processed in the age of computation. The paper shows how the computational modelling tools associated with performance-based parametric design help support design decisions during the initial design phases. Building Energy Performance (BEP) is chosen as the main context to develop a set of criteria for the iterative development, testing, evaluation, and validation of a prototype model. Therefore, as a practical work, the research explores a series of new energy simulation modelling techniques based on parametric design and multi optimization-based design. Specifically, it aims to explore, develop, and test new approaches in parametric modelling that can support energy simulation, using multi optimization, where designers can easily state the design parameters and use them in energy-performance-based design. The exploratory research approach is the main theme of this research. However, during the development of the research it was found that there is a need to blend this research design with the descriptive research approach. One of the key contributions of this study will be the development of a more direct link and useful methods for the translation of information into data inputs to support computational thinking and modelling processes.

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References

Bazjanac, Vladimir. 2008. IFC BIM-based Methodology for Semi-automated Building Energy Performance Simulation. Lawrence Berkeley National Laboratory.

Bazjanac, Vladimir. 2009. Implementation of Semi-automated Energy Performance Simulation: Building Geometry. Paper read at CIB W.

Demanuele, Christine, Tamsin Tweddell, and Michael Davies. 2010. Bridging the gap between predicted and actual energy performance in schools. Paper read at World renewable energy congress XI.

Menezes, Anna Carolina, Andrew Cripps, Dino Bouchlaghem, and Richard Buswell. 2012. Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap. Applied Energy 97:355-364. DOI: https://doi.org/10.1016/j.apenergy.2011.11.075

Wang, Chensheng. 2007. On the inspiration of creative thinking for engineering students. Paper read at Information Technologies and Applications in Education, 2007. ISITAE'07. First IEEE International Symposium on. DOI: https://doi.org/10.1109/ISITAE.2007.4409321

Tseng, Ian, Jarrod Moss, Jonathan Cagan, and Kenneth Kotovsky. 2008. The role of timing and analogical similarity in the stimulation of idea generation in design. Design Studies 29 (3):203-221. DOI: https://doi.org/10.1016/j.destud.2008.01.003

Chiu, Sheng-Hsiao. 2010. Students’ knowledge Sources and Knowledge Sharing in The Design Studio—an Exploratory Study. International Journal of Technology and Design Education 20 (1):27. DOI: https://doi.org/10.1007/s10798-008-9061-9

Oxman, Rivka. 2004. Think-maps: teaching design thinking in design education. Design studies 25 (1):63-91. DOI: https://doi.org/10.1016/S0142-694X(03)00033-4

Al-Sayed, Kinda, Ruth Conroy Dalton, and Christoph Holscher. 2010. Discursive Design Thinking: The Role of Explicit Knowledge in Creative Architectural Design Reasoning. Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing 24 (2):211-230. DOI: https://doi.org/10.1017/S0890060410000065

Alhusban, Ahmad Abidrabbu. 2012. What Does the Architectural Creative Leap Look Like Through a Conceptual Design Phase in the Undergraduate Architectural Design Studio?

de Wilde, Pieter. 2014. The gap between predicted and measured energy performance of buildings: A framework for investigation. Automation in Construction 41:40-49. DOI: https://doi.org/10.1016/j.autcon.2014.02.009

Attia, Shady, Mohamed Hamdy, William O'Brien, and Salvatore Carlucci. 2013. Assessing Gaps and Needs for Integrating Building Performance Optimization Tools in Net Zero Energy Buildings Design. Energy and Buildings 60:110-124. DOI: https://doi.org/10.1016/j.enbuild.2013.01.016

Bogenstatter, Ulrich. 2000. Prediction and Optimization of Life-cycle Costs in Early Design. Building Research and Information 28 (5-6):376-386. DOI: https://doi.org/10.1080/096132100418528

Çavuşoğlu, Ömer Halil 2015. The Position of BIM Tools in Conceptual Design Phase: Parametric Design and Energy Modeling Capabilities. Ecaade 2015: Real Time - Extending the Reach of Computation, Vol 1:607-612.

Schlueter, Arno, and Frank Thesseling. 2009. Building information model based energy/exergy performance assessment in early design stages. Automation in Construction 18 (2):153-163. DOI: https://doi.org/10.1016/j.autcon.2008.07.003

Attia, Shady, Liliana Beltrán, André De Herde, and Jan Hensen. 2009. “Architect Friendly”: A Comparison of ten Different Building Performance Simulation Tools. Paper read at Proceedings of 11th International Building Performance Simulation Association Conference and Exhibition.

Asl, Mohammad Rahmani, Michael Bergin, Adam Menter, and Wei Yan. 2014. BIM-based Parametric Building Energy Performance Multi-Objective Optimization. Fusion: Data Integration at Its Best, Vol 2:455-464.

Li, Beidi. 2017. “Use of Building Energy Simulation Software in Early-Stage of Design Process.”

Asl, Mohammad Rahmani, Saied Zarrinmehr, Michael Bergin, and Wei Yan. 2015. BPOpt: A Framework for BIM-based Performance Optimization. Energy and Buildings 108:401-412. DOI: https://doi.org/10.1016/j.enbuild.2015.09.011

Basbagill, J., F. Flager, M. Lepech, and M. Fischer. 2013. Application of Life-Cycle Assessment to Early Stage Building Design for Reduced Embodied Environmental Impacts. Building and Environment 60:81-92. DOI: https://doi.org/10.1016/j.buildenv.2012.11.009

Ding, Grace KC. 2008. Sustainable construction—The role of environmental assessment tools. Journal of environmental management 86 (3):451-464. DOI: https://doi.org/10.1016/j.jenvman.2006.12.025

Wang, Weimin M., Radu Zmeureanu, and Hugues Rivard. 2005. Applying multi-objective genetic algorithms in green building design optimization. Building and Environment 40 (11):1512-1525. DOI: https://doi.org/10.1016/j.buildenv.2004.11.017

Kim, Hyoungsub, Mohammad Rahmani Asl, and Wei Yan. 2015. Parametric BIM-based Energy Simulation for Buildings with Complex Kinetic Facades. Ecaade 2015: Real Time - Extending the Reach of Computation, Vol 1:657-664.

Asl, Mohammad Rahmani, Saied Zarrinmehr, and Wei Yan. 2013. Towards Bim-Based Parametric Building Energy Performance Optimization. Acadia 2013: Adaptive Architecture:101.

Carbon Trust. 2011. Closing the gap: Lessons Learned on Realising the Potential of Low Carbon Building Design. London: Carbon Trust. https://www.carbontrust.com/media/81361/ctg047-closing-the-gap-low-carbon-building-design.pdf.

CarbonBuzz. 2020. “CarbonBuzz an CIBSE and RIBA Platform 2016.” 2019. https://www.carbonbuzz.org/casestudiestab.jsp.

Toth, Bianca, Flora Salim, Robin Drogemuller, John H Frazer, and Jane Burry. 2011. Closing the loop of design and analysis: Parametric modelling tools for early decision support. Paper read at Circuit Bending, Breaking and Mending: Proceedings of the 16th International Conference on Computer-Aided Architectural Design Research in Asia.

Zero Carbon Hub. 2014. Closing the gap between design and as-built performance. Evidence Review Report. Zero Carbon Hub, London, UK.

Becker, Edward. 2018. “Affordances and Limitations of Cognitive Bias Reduction in Introductory Digital Design Pedagogy.” Architectural Research in Finland 2 (1): 195–210.

Strobbe, Tiemen, Ronald De Meyer, and Jan Van Campenhout. 2013. A Generative Approach towards Performance-Based Design. Paper read at eCAADe 2013: Computation and Performance–Proceedings of the 31st International Conference on Education and research in Computer Aided Architectural Design in Europe, Delft, The Netherlands, September 18-20, 2013.

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Published

2021-09-22

How to Cite

A Nasar , Z. . (2021). Information Processing and Assessment for Improved Computational Energy Modelling. Wasit Journal of Engineering Sciences, 9(1), 37–49. https://doi.org/10.31185/ejuow.Vol9.Iss1.226

Issue

Section

Urban design and architecture