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_id	caadria2018_156
id	caadria2018_156
authors	Chee, Ryan Wei Shen, Tan, Wei Lin, Goh, Wei Hern, Amtsberg, Felix and Dritsas, Stylianos
year	2018
title	Locally Differentiated Concrete by Digitally Controlled Injection
doi	https://doi.org/10.52842/conf.caadria.2018.1.195
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. 195-204
summary	This paper presents a digital fabrication process for concrete which may be deployed for surface texturing, volumetric modification of material properties and 2D and 3D forming. We process concrete in its slurry state by locally injecting chemicals in solution which cause vigorous effervescent reaction to take place. By precise and controlled dispensing, using computer software and robotic hardware developed, we produce local differentiation in the finally set concrete artefacts. Our work contributes to additive and subtractive 3D manufacturing as well as functionally graded materials fabrication.
keywords	Digital Fabrication; Additive Manufacturing; Functionally Graded Materials; Architectural Robotics.
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2018_054
id	caadria2018_054
authors	Shen, Xiaofei
year	2018
title	Environmental Parametric Multi-Objective Optimization for High Performance Facade Design
doi	https://doi.org/10.52842/conf.caadria.2018.2.103
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. 103-112
summary	This paper demonstrates the applicability of a data-integrated and user-friendly Multi-Objective Optimization (MOO) method within the Grasshopper (GH) parametric design interface which supports early stage design decision making for High Performance Building (HPB) façade. With multiple environmental objectives optimized and multiple geometric parameters adjusted in the same intuitive design space, designers with limited knowledge on scripting could easily set up the nodes simultaneously when the design is carried out to achieve the efficiency in HPB design optimization. An experiment utilizing the method, with DIVA as the environmental simulator and Octopus as the MOO solver, is demonstrated for rational daylight distribution, balanced solar heat gain and reduced energy use intensity. The findings show both potentials and limitations of the proposed method.
keywords	Multi-Objective Optimization; Environmental Parametrics; Generative Design; High Performance Facade
series	CAADRIA
email
last changed	2022/06/07 07:56

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