Cumincad : CUMINCAD Papers : Search Results

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

PDF papers
References

Hits 1 to 4 of 4

Reformat results as: short short into frame detailed detailed into frame

_id	ecaade2020_404
id	ecaade2020_404
authors	Singh, Manav Mahan, Schneider-Marin, Patricia, Harter, Hannes, Lang, Werner and Geyer, Philipp
year	2020
title	Applying Deep Learning and Databases for Energy-efficient Architectural Design - Abstract
doi	https://doi.org/10.52842/conf.ecaade.2020.2.079
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 79-87
summary	The reduction of energy consumption of buildings requires consideration in early design phases. However, modelling and computation time required for dynamic energy simulations makes them inappropriate in the early phases. This paper presents a performance prediction approach for these phases that is embedded in a multi-level-of-development modelling approach. First, parametric pre-trained modular deep learning components are embedded in the building elements. The energy performance is predicted by composing these components. Second, embodied energy assessment is performed by extracting the information from a database. A calculation module queries the database and calculates the embodied energy. Both, embodied and operational, energy are assembled to predict lifecycle energy demand. The method has been implemented prototypically in a digital modelling environment Revit. A case study serves to demonstrate the application process, the user interaction and the information flows. It shows energy prediction in early design phases to enhance the environmental performance of the building.
keywords	BIM; Operational Energy; Embodied Energy; Life-cycle Energy Demand; Early Design Phases
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2022_16
id	ecaade2022_16
authors	Bailey, Grayson, Kammler, Olaf, Weiser, Rene, Fuchkina, Ekaterina and Schneider, Sven
year	2022
title	Performing Immersive Virtual Environment User Studies with VREVAL
doi	https://doi.org/10.52842/conf.ecaade.2022.2.437
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 437–446
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learns the relationship between building geometry, typology, and construction type with the Global Warming potential (GWP) in tons of C02 equivalent (tCO2e). The first one, a regression model, can predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly through early predictions of the structure’s material and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Pre-Occupancy Evaluation, Immersive Virtual Environment, Wayfinding, User Centered Design, Architectural Study Design
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2020_791
id	sigradi2020_791
authors	Mussi, Andréa Quadrado; Rodrigues, Daiara Iasmin; Isele, Priscila Castioni; Schneider, Alana Arena
year	2020
title	Landscaping co-design: digital fabrication as communication among designers, visually impaired people and children
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 791-798
summary	Children's playgrounds, intended for recreation and significant for the inclusion and mobility of children, through inclusive urban equipment that stimulate new experiences for cognitive development. In order to gather suggestions through a co-design with visually impaired people and children, to develop the landscaping co-design at Square Capitao Jovino. This article describes some activities carried out in the design processes, emphasizing the importance of an inclusive project based on their daily experiences. This article is a follow-up of the actions already carried out for requalification in the square (nine years ago), with the support of Higher Education Institution and Blind Association.
keywords	Design process, Digital fabrication, Co-design, Visually impaired people
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	acadia20_360
id	acadia20_360
authors	Schneider, Maxie; Fransén Waldhör, Ebba; Denz, Paul-Rouven; Vongsingha, Puttakhun; Suwannapruk, Natchai; Sauer, Christiane
year	2020
title	Adaptive Textile Facades Through the Integration of Shape Memory Alloy
doi	https://doi.org/10.52842/conf.acadia.2020.1.360
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 360-370.
summary	The R&D project ADAPTEX showcases a material-driven and computationally informed design approach to adaptive textile facades through the integration of shape memory alloy (SMA) as an actuator. The results exhibit thermally responsive and self-sufficient sun-shading solutions with innovative design potential that enhance the energy performance of the built environment. With regard to climate targets, an environmentally viable concept is proposed that reduces the energy required for climatization, is lightweight, and can function as a refurbishment system. Two concepts—ADAPTEX Wave and ADAPTEX Mesh—are being developed to be tested as full-scale demonstrators for facade deployment by an interdisciplinary team from architecture, textile design, facade engineering, and material research. The two concepts follow a material-driven, low-complexity design strategy and differ in type of kinetic movement, textile construction, integration of the SMA, reset force, and scale of permeability. In this paper, we describe the computational design process and tools to develop and design current and future prototypes and demonstrators, providing insights on the challenges and potentials of developing textiles with integrated shape memory alloys for architectural applications.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

No more hits.