id |
ijac201917206 |
authors |
Ackerman, Aidan; Jonathan Cave, Chien-Yu Lin and Kyle Stillwell |
year |
2019 |
title |
Computational modeling for climate change: Simulating and visualizing a resilient landscape architecture design approach |
source |
International Journal of Architectural Computing vol. 17 - no. 2, 125-147 |
summary |
Coastlines are changing, wildfires are raging, cities are getting hotter, and spatial designers are charged with the task of designing to mitigate these unknowns. This research examines computational digital workflows to understand and alleviate the impacts of climate change on urban landscapes. The methodology includes two separate simulation and visualization workflows. The first workflow uses an animated particle fluid simulator in combination with geographic information systems data, Photoshop software, and three-dimensional modeling and animation software to simulate erosion and sedimentation patterns, coastal inundation, and sea level rise. The second workflow integrates building information modeling data, computational fluid dynamics simulators, and parameters from EnergyPlus and Landsat to produce typologies and strategies for mitigating urban heat island effects. The effectiveness of these workflows is demonstrated by inserting design prototypes into modeled environments to visualize their success or failure. The result of these efforts is a suite of workflows which have the potential to vastly improve the efficacy with which architects and landscape architects use existing data to address the urgency of climate change. |
keywords |
Modeling, simulation, environment, ecosystem, landscape, climate change, sea level rise, urban heat island |
series |
journal |
email |
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full text |
file.pdf ( bytes) |
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Baerlecken D. and Riether G. (2009)
From texture to volume: an investigation in quasi-crystalline systems
, Proceedings of the 13th congress of the Ibero-American society of digital graphics (SIGraDi 2009) . Sao Paulo, 16–18 November 2009, p. 957
|
|
|
|
Brown I., Jude S., Koukoulas S. et al. (2006)
Dynamic simulation and visualisation of coastal erosion
, Comput Environ Urban; 30: 840–860
|
|
|
|
Bueno E., Quadros Gonçalves Neto A. and Mehl C. (2017)
Analysis of variations in daylight performance of the Curitiba civic center through parametric modeling and simulation
, Proceedings of the 21th conference of the Ibero-American society of digital graphics , 22–24 November 2017, pp. 486–490
|
|
|
|
Cantrell B. and Yates N.B. (2012)
Modeling the environment: techniques and tools for the 3D illustration of dynamic landscapes
, Hoboken, NJ: John Wiley
|
|
|
|
Chronis A., Dubor A., Cabay E. et al. (2017)
Integration of CFD in computational design—an evaluation of the current state of the art
, Proceedings of the 35th eCAADe conference on sharing computational knowledge! (ShoCK), volume 1, Rome, 20–22 September 2017, pp. 601–610
|
|
|
|
Doyle T.W., Chivoiu B. and Enwright N.M. (2015)
Sea-level rise modeling handbook: resource guide for coastal land man- agers, engineers, and scientists
, Professional Paper 1815. Reston, VA: US Geological Survey. DOI: 10.3133/ pp1815
|
|
|
|
Enright D., Marschner S. and Fedkiw R. (2002)
Animation and rendering of complex water surfaces
, ACM T Graphic; 21: 736–744
|
|
|
|
Feng Y. and Zhan S. (2011)
Simulation of real water in 3D animation
, Proceedings of the 2011 international conference on multimedia technology, Hangzhou, China, 26–28 July 2011. New York: IEEE
|
|
|
|
Hauer M.E., Evans J.M. and Mishra D.R. (2016)
Millions projected to be at risk from sea-level rise in the continental United States
, Nat Clim Change; 6: 691–695
|
|
|
|
Jelesnianski C.P., Chen J. and Shaffer W.A. (1992)
SLOSH: Sea, lake, and overland surges from hurricanes
, NOAA Technical Report NWS 48, April 1992. Silver Spring, MD: National Oceanic and Atmospheric Administration, US Department of Commerce
|
|
|
|
Jentsch M.F., James P.A., Bourikas L. et al. (2013)
Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates
, Renew Energ; 55: 514–524
|
|
|
|
Lee J.S., Kim J.T. and Lee M.G. (2013)
Mitigation of urban heat island effect and greenroofs
, Indoor Built Environ; 23: 62–69
|
|
|
|
Mark E. and Ultmann Z. (2016)
Environmental footprint design tool: exchanging geographical information system and computer-aided design data in real time
, Int J Archit Comput; 14: 307–321
|
|
|
|
Melsom J. and Girot C. (2015)
Directed deposition: exploring the roles of simulation and design in erosion and landslide processes
, Proceedings of the 35th annual conference of the association for computer aided design in archi- tecture (ACADIA), Cincinnati, OH, 19–25 October 2015, pp. 211–221
|
|
|
|
Moazami A., Carlucci S. and Geving S. (2017)
Critical analysis of software tools aimed at generating future weather files with a view to their use in building performance simulation
, Enrgy Proced; 132: 640–645
|
|
|
|
M’Closkey K. and VanDerSys K. (2017)
Dynamic patterns: visualizing landscapes in a digital age
, Basingstoke: Taylor & Francis
|
|
|
|
Nicholson-Cole S.A. (2005)
Representing climate change futures: a critique on the use of images for visual communication
, Comput Environ Urban; 29: 255–273
|
|
|
|
Nik V.M. and Arfvidsson J. (2017)
Using typical and extreme weather files for impact assessment of climate change on buildings
, Enrgy Proced; 132: 616–621
|
|
|
|
Salgueiro I. and Ferries B. (2015)
An “environmental BIM” approach for the architectural schematic design stage
, Int J Archit Comput; 13(3–4): 299–312
|
|
|
|
Shiffman D. (2012)
The nature of code
, La Vergne, TN: Lightning Source
|
|
|
|
last changed |
2019/08/07 14:04 |
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