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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	caadria2020_431
id	caadria2020_431
authors	Kim, Jong Bum, Balakrishnan, Bimal and Aman, Jayedi
year	2020
title	Environmental Performance-based Community Development - A parametric simulation framework for Smart Growth development in the United States
doi	https://doi.org/10.52842/conf.caadria.2020.1.873
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 873-882
summary	Smart Growth is an urban design movement initiated by Environmental Protection Agency (EPA) in the United States (Smart Growth America, 2019). The regulations of Smart Growth control urban morphologies such as building height, use, position, section configurations, faÃ§ade configurations, and materials, which have an explicit association with energy performances. This research aims to analyze and visualize the impact of Smart Growth developments on environmental performances. This paper presents a parametric modeling and simulation framework for Smart Growth developments that can model the potential community development scenarios, simulate the environmental footprints of each parcel, and visualize the results of modeling and simulation. We implemented and examined the proposed framework through a case study of two Smart Growth regulations: Columbia Unified Development Code (UDC) in Missouri (City of Columbia Missouri, 2017) and Overland Park Downtown Form-based Code (FBC) in Kansas City (City of Overland Park, 2017, 2019). Last, we discuss the implementation results, the limitations of the proposed framework, and the future work. We anticipate that the proposed method can improve stakeholders' understanding of how Smart Growth developments are associated with potential environmental footprints from an expeditious and thorough exploration of what-if scenarios of the multiple development schemes.
keywords	Smart Growth; Building Information Modeling (BIM); Parametric Simulation; Solar Radiation
series	CAADRIA
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last changed	2022/06/07 07:52

_id	ecaade2023_227
id	ecaade2023_227
authors	Moorhouse, Jon and Freeman, Tim
year	2023
title	Towards a Genome for Zero Carbon Retrofit of UK Housing
doi	https://doi.org/10.52842/conf.ecaade.2023.2.197
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 197–206
summary	The United Kingdom has some of the worst insulated housing stock in Northern Europe. This is in part due to the age of housing in the UK, with over 90% being built before 1990 [McCrone 2017, Piddington 2020]. Moreover, 85% of current UK housing will still be in use in 2050 by which stage their Government are targeting Net Carbon Zero [Eyre 2019]. Domestic energy use accounts for around 25% of UK carbon emissions. The UK will need to retrofit 20 million dwellings in order to meet this target. If this delivery were evenly spread, it would equate to over 2,000 retrofit completions each day. Government-funded initiatives are stimulating the market, with upwards of 60,000 social housing retrofits planned for 2023, but it is clear that a system must be developed to enable the design and implementation of housing-stock improvement at a large scale.This paper charts the 20-year development of a digital approach to the design for low-carbon domestic retrofit by architects Constructive Thinking Studio Limited and thence documents the emergence of a collaborative approach to retrofit patterns on a National scale. The author has led the Research and Development stream of this practice, developing a Building Information Modelling methodology and integrated Energy Modelling techniques to optimise design for housing retrofit [Georgiadou 2019, Ben 2020], and then inform a growing palette of details and a database of validated solutions [Moorhouse 2013] that can grow and be used to predict options for future projects [D’Angelo 2022]. The data is augmented by monitoring energy and environmental performance, enabling a growing body of knowledge that can be aligned with existing big data to simulate the benefits of nationwide stock improvement. The paper outlines incremental case studies and collaborative methods pivotal in developing this work The proposed outcome of the work is a Retrofit Genome that is available at a national level.
keywords	Retrofit, Housing, Zero-Carbon, BIM, Big Data, Design Genome
series	eCAADe
email
last changed	2023/12/10 10:49

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