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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	caadria2018_241
id	caadria2018_241
authors	Molina, Kalani and Park, Hyoung-June
year	2018
title	Sparking Off Walkability - A Computational Approach of Urban Network Analysis on Walkability in TOD Neighborhoods
doi	https://doi.org/10.52842/conf.caadria.2018.2.391
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 391-400
summary	Existing and proposed Transit Oriented Development (TOD) neighborhoods of Waipahu Transit Center Station in Honolulu, Hawaii are revisited by a proposed computational approach of Urban Network Analysis (UNA). The four measures of UNA: reach, gravity, closeness, and straightness are employed for investigating walkability in these given urban neighborhoods. In each measure, 1) accessibility to transportation 2) intersections frequency, 3) residential building density, 4) commercial building density, and 5) Industrial buildings density are delineated and proposed as vital factors for improving planning and design decisions on walkability patterns around the TOD neighborhoods.
keywords	Urban Network Analysis, Walkability, Transit Oriented Develoment
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2018_181
id	caadria2018_181
authors	Chun, Junho, Lee, Juhun and Park, Daekwon
year	2018
title	TOPO-JOINT - Topology Optimization Framework for 3D-Printed Building Joints
doi	https://doi.org/10.52842/conf.caadria.2018.1.205
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 205-214
summary	Joints and connectors are often the most complex element in building assemblies and systems. To ensure the performance of the assemblies and systems, it is critical to optimize the geometry and configurations of the joints based on key functional requirements (e.g., stiffness and thermal exchange). The proposed research focuses on developing a multi-objective topology optimization framework that can be utilized to design highly customized joints and connections for building applications. The optimized joints that often resemble tree structures or bones are fabricated using additive manufacturing techniques. This framework is built upon the integration of high-fidelity topology optimization algorithms, additive manufacturing, computer simulations and parametric design. Case studies and numerical applications are presented to demonstrate the validity and effectiveness of the proposed optimization and additive manufacturing framework. Optimal joint designs from a variety of architectural and structural design considerations, such as stiffness, thermal exchange, and vibration are discussed to provide an insightful interpretation of these interrelationships and their impact on joint performance.
keywords	Topology optimization; parametric design; 3d printing
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia20_164p
id	acadia20_164p
authors	Lange, Christian; Ratoi, Lidia; Co Lim, Dominic; Hu, Jason; Baker, David M.; Yu, Vriko; Thompson, Phil
year	2020
title	Reformative Coral Habitats
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 164-169
summary	Coral reefs are some of the most diverse ecologies in the marine world. They are the habitat to tens of thousands of different marine species. However, these wildlife environments are endangered across the globe. Recent research estimates that around 75 percent of the remaining coral reefs are currently under threat. In 2018 after a devastating storm, Hong Kong lost around 80% of its existing corals. Consequently, a team consisting of marine biologists and architects at The University of Hong Kong has developed a series of performative structures that have been deployed in the city's waters in July 2020, intending to aid new coral growth over the coming years. The project was commissioned by the Agriculture, Fisheries, and Conservation Department (AFCD) and is part of an ongoing active management measure for coral restoration in Hoi Ha Wan Marine Park in Hong Kong. The following objectives were defined as part of the design and fabrication research of the project. To develop a design strategy that builds on the concept of biomimicry to allow for complex spaces to occur that would provide attributes against the detachment of the inserted coral fragment, hence could enhance a diverse marine life specific to the context of the cities water conditions. To generate an efficient printing path that accommodates the specific morphological design criteria and ensures structural integrity and the functional aspects of the design. To develop an efficient fabrication process with a DIW 3D printing methodology that considers warping, shrinkage, and cracking in the clay material. The research team developed a method that combined an algorithmic design approach for the design of different geometries with a digital additive manufacturing process utilizing robotic 3D clay printing. The overall fabrication strategy for the complex and large pieces sought to ensure structural longevity, optimize production time, and tackle the involved double-sided printing method. Overall, 128 tiles were printed, covering roughly 40sqm of the seabed.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	caadria2018_097
id	caadria2018_097
authors	Park, Daekwon
year	2018
title	Adaptive THERM-SKIN - Tunable Cellular Materials for Adaptive Thermal Control
doi	https://doi.org/10.52842/conf.caadria.2018.2.309
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 309-318
summary	This research investigates a tunable cellular material system that can alternate between a thermal insulator and a heat exchanger. The capability to morph between these two distinctive thermal functions provide opportunities to create novel material systems that can dynamically adapt to its environment. The operating principle is to strategically deform the cellular material so that the shape and size of the cavities are optimized for the intended thermal function. In the compressed state, the cavity spaces are narrow enough to suppress convection heat transfer and utilize the low thermal conductivity property of still air. The expanded state has the optimum cavity dimensions for air to move through the system and exchange heat with the material system. The first stage of the research utilizes the existing thermal optimization studies for establishing the analytical model for predicting the performance of each state as a function of the geometric features. The second stage constructs a parametric model using the predictions, and two separate material architectures were designed and fabricated based on it. The calibrated analytical model can be utilized in designing various dynamic thermal interaction systems at a wide range of conditions and parameters (e.g., climate, temperature, scale, and material).
keywords	Dynamic Thermal Insulation; Cellular Materials; Thermal Design and Optimization; Adaptive Materials
series	CAADRIA
email
last changed	2022/06/07 08:00

_id	ecaade2018_251
id	ecaade2018_251
authors	Park, Hyejin, Panya, David Stephen, Goo, Hyungmo, Kim, Teahoon and Seo, Jihyo
year	2018
title	BIM-based Virtual Reality and Human Behavior Simulation For Safety Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.823
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 823-832
summary	The constant development of Building Information Modelling and Virtual reality in architecture and construction has gone beyond visualization and marketing in architecture to enhancing workflows of architects with assets such as immersion and interaction that assists Architects to make more informed decisions from design to construction. Using virtual reality complex decisions can be simulated and analyzed to produce iterations for the optimizing design. Recently, safety design to protect users from the risk of life has become an issue. BIM and VR for Safety Design is a beneficial collaboration for the designer to experience user safety in a virtual built environment immersively. There is a need for intensive experimentation and simulation into user-centered design safety due to the complexity of this part of the design process. The most unpredictable elements of user design safety is human behavior. this paper explores Human behavior using intelligent virtual agents in emergency situations, as this is when user safety is at highest risk in a built environment. In this paper, we explore the potential of a BIM based VR and human behavior simulation in relation to emergency situations.
keywords	BIM; Virtual Reality; Safety simulation; Safety design; human behavior
series	eCAADe
email
last changed	2022/06/07 08:00

_id	cf2019_003
id	cf2019_003
authors	Steinfeld, Kyle; Katherine Park, Adam Menges and Samantha Walker
year	2019
title	Fresh Eyes A framework for the application of machine learning to generative architectural design, and a report of activities at Smartgeometry 2018
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 22
summary	This paper presents a framework for the application of Machine Learning (ML) to Generative Architectural Design (GAD), and illustrates this framework through a description of a series of projects completed at the Smart Geometry conference in May of 2018 (SG 2018) in Toronto. Proposed here is a modest modification of a 3-step process that is well-known in generative architectural design, and that proceeds as: generate, evaluate, iterate. In place of the typical approaches to the evaluation step, we propose to employ a machine learning process: a neural net trained to perform image classification. This modified process is different enough from traditional methods as to warrant an adjustment of the terms of GAD. Through the development of this framework, we seek to demonstrate that generative evaluation may be seen as a new locus of subjectivity in design.
keywords	Machine Learning, Generative Design, Design Methods
series	CAAD Futures
email
last changed	2019/07/29 14:08

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