EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 362 (2022) E3S Web Conf., 362 (2022) 03004 References
Open Access
Issue
E3S Web Conf.
Volume 362, 2022
BuildSim Nordic 2022
Article Number 03004
Number of page(s) 8
Section Users, Tools and Software
DOI https://doi.org/10.1051/e3sconf/202236203004
Published online 01 December 2022
  1. Attia, S., A. De Herde, E. Gratia, and J. L. M. Hensen (2013). Achieving informed decision-making for net zero energy buildings design using building performance simulation tools. Building Simulation 6(1), 3–21. [CrossRef] [Google Scholar]
  2. Attia, S., J. L. Hensen, L. Beltran, and A. De Herde (2012). Selection criteria for building performance simulation tools: contrasting architects’ and engineers’ needs. Journal of Building Performance Simulation 5(3), 155–169. [CrossRef] [Google Scholar]
  3. Autodesk (2022). Autodesk Revit®. https://www.autodesk.se/products/revit/ (Accessed: 2022-04-04). [Google Scholar]
  4. Batish, A. and A. Agrawal (2019). Building energy prediction for early-design-stage decision support: A review of data-driven techniques. In Proceedings of the 16th IBPSA Conference, Volume 3, pp. 1514–1521. ISSN: 2522-2708. [Google Scholar]
  5. Bengt Dahlgren AB (2021). BeDOT. http://www.bedot.tools/ (Accessed: 2022-04-13). [Google Scholar]
  6. Brearley, J. (2022). Jerboa. https://www.food4rhino.com/en/app/jerboa (Accessed: 2022-04-13). [Google Scholar]
  7. Clarke, J. A. and J. L. M. Hensen (2015). Integrated building performance simulation: Progress, prospects and requirements. Building and Environment 91, 294–306. [CrossRef] [Google Scholar]
  8. ESLab, Cornell (2020). Eddy. https://www.food4rhino.com/en/app/eddy (Accessed: 2022-04-13). [Google Scholar]
  9. Fantin Do Amaral Silva, G. and R. Bergel Gomez (2018). Energy performance modelling - Introducing the Building Early-stage Design Optimization Tool (BeDOT). Master’s thesis, Chalmers University of Technology. [Google Scholar]
  10. Gassar, A. A. A., C. Koo, T. W. Kim, and S. H. Cha (2021). Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review. Sustainability 13(17), 9815. [CrossRef] [Google Scholar]
  11. Han, T., Q. Huang, A. Zhang, and Q. Zhang (2018, October). Simulation-Based Decision Support Tools in the Early Design Stages of a Green Building—A Review. Sustainability 10(10), 3696. [CrossRef] [Google Scholar]
  12. Hensen, J. and R. Lamberts (2011, January). Building Performance Simulation for Design and Operation. Oxon: Spon Press. [Google Scholar]
  13. Hildebrand, L. and R. Bach (2018, June). A Comparative Overview of Tools for Environmental Assessment of Materials, Components and Buildings. In Sustainable and resilient building design: approaches, methods and tools, pp. 143–157. Delft: BK Books. [Google Scholar]
  14. Hollberg, A. (2016, 11). Parametric Life Cycle Assessment: Introducing a time-efficient method for environmental building design optimization. Ph. D. thesis, Bauhaus-Universitat Weimar. [Google Scholar]
  15. idbuild.dk (2022). ICEbear - Indoor Climate and Energy simulations for parametric CAD tools. http://www.idbuild.dk/icebear (Accessed: 2022-03-31). [Google Scholar]
  16. Johansson, M. and J. Messeter (2005, January). Presenting the user: constructing the persona. Digital Creativity 16(4), 231–243. [CrossRef] [Google Scholar]
  17. Ladybug Tools (2022a, October). Ladybug Tools. https://www.food4rhino.com/en/app/ladybug-tools (Accessed: 2022-03-31). [Google Scholar]
  18. Ladybug Tools (2022b). Ladybug Tools | About. https://www.ladybug.tools/about.html (Accessed: 2022-03-31). [Google Scholar]
  19. McNeel Europe (2016, May). FAQ. https://www.food4rhino.com/en/faq?lang=en (Accessed: 2022-02-11). [Google Scholar]
  20. Meex, E., A. Hollberg, E. Knapen, L. Hildebrand, and G. Verbeeck (2018). Requirements for applying LCA- based environmental impact assessment tools in the early stages of building design. Building and Environment 133, 228–236. [CrossRef] [Google Scholar]
  21. Negendahl, K. (2015). Building performance simulation in the early design stage: An introduction to integrated dynamic models. Automation in Construction 54, 39–53. [CrossRef] [Google Scholar]
  22. Nisztuk, M. and P.B. Myszkowski (2018). Usability of contemporary tools for the computational design of architectural objects: Review, features evaluation and reflection. International Journal of Architectural Computing 16(1), 58–84. [CrossRef] [Google Scholar]
  23. Robert McNeel & Associates (2022). Rhinoceros 3D. https://www.rhino3d.com/. [Google Scholar]
  24. Sadeghipour Roudsari, M. and M. Pak (2013). Ladybug: A parametric environmental plugin for grasshopper to help designers create an environmentally-conscious design. In Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association, Chambery, France, pp. 3128–3135. [Google Scholar]
  25. Sepulveda Luque, A. and F. De Luca (2022). Solar toolbox. https://www.food4rhino.com/en/app/solar-toolbox (Accessed: 2022-03-31). [Google Scholar]
  26. Solemma LLC (2022). ClimateStudio. https://www.solemma.com/climatestudio (Accessed: 2022-0331). [Google Scholar]
  27. Spitler, J. D. (2006, July). Editorial: Building Performance Simulation: The Now and the Not Yet. HVAC&R Research 12(sup1), 711–713. [CrossRef] [Google Scholar]
  28. Sustainable Building Chalmers (2022). Tool review figures. https://github.com/SB-Chalmers/life-cycle-building-performance/tree/main/figures/bps-tool-review (Accessed: 2022-04-01). [Google Scholar]
  29. Sawen, T., E. Magnusson, A. Hollberg, and A. Sasic Kala-Gasidis (2022). Reviewing parametric LCA tools applied in early-stage building design. In Proceedings of Sustainable Built Environment D-A-CH Conference 2022, Berlin (under consideration). [Google Scholar]
  30. Touloupaki, E. and T. Theodosiou (2017). Performance Simulation Integrated in Parametric 3D Modeling as a Method for Early Stage Design Optimization—A Review. Energies 10(5), 637. [CrossRef] [Google Scholar]
  31. TRANSSOLAR (2019). TRNLizard. https://www.food4rhino.com/en/app/trnlizard (Accessed: 2022-04-13). [Google Scholar]
  32. Vandkunsten (2021). Daylight. VK-01. https://github.com/vandkunsten/Daylight_VK-01 (Accessed: 2022-04-13). [Google Scholar]
  33. VITALITY (2022). Vitality. https://www.food4rhino.com/en/app/vitality (Accessed: 2022-03-31). [Google Scholar]
  34. Wang, L. (2022). Vitality. https://www.food4rhino.com/en/app/evomass (Accessed: 2022-04-13). [Google Scholar]
  35. Wastiels, L. and R. Decuypere (2019). Identification and comparison of LCA-BIM integration strategies. IOP Conference Series: Earth and Environmental Science 323(1), 012101. [CrossRef] [Google Scholar]
  36. Weisstein, E. W. and C. Stover (n.d.). Parametric Equations. https://mathworld.wolfram.com/ParametricEquations.html (Accessed: 2022-02-07). [Google Scholar]
  37. Østergård, T., R. L. Jensen, and S. E. Maagaard (2016, August). Building simulations supporting decision making in early design - A review. Renewable and Sustainable Energy Reviews 61, 187–201. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.