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

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_id	caadria2020_258
id	caadria2020_258
authors	Beatricia, Beatricia, Indraprastha, Aswin and Koerniawan, M. Donny
year	2020
title	Revisiting Packing Algorithm - A Strategy for Optimum Net-to Gross Office Design
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. 405-414
doi	https://doi.org/10.52842/conf.caadria.2020.1.405
summary	Net-to-gross efficiency is defined as the ratio of net area to a gross area of a building. Net-to-gross efficiency will determine the quantity of leasable building area. On the other side, the effectiveness of the spatial distribution of a floor plan design must follow the value of net-to-gross efficiency. Therefore in the context of office design, there are two challenges need to be improved: 1) to get an optimum value of efficiency, architects need to assign the amount and size of the office units which can be effectively arranged, and 2) to fulfill high net-to-gross efficiency value that usually set out at minimal 85%. This paper aims to apply the packing algorithm as a strategy to achieve optimum net-to-gross efficiency and generating spatial configuration of office units that fit with the result. Our study experimented with series of models and simulations consisting of three stages that start from finding net-to-gross efficiency, defining office unit profiles based on preferable office space units, and applying the packing algorithm to get an optimum office net-to-gross efficiency. Computational processes using physics engine and optimization solvers have been utilized to generate design layouts that have minimal spatial residues, hence increasing the net-to-gross ratio.
keywords	net-to-gross efficiency; packing algorithm; modular office area; area optimization;
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2020_063
id	caadria2020_063
authors	Wang, Chunxiao and Lu, Shuai
year	2020
title	Influence of Uncertainties in Envelope and Occupant Parameters on the Reliability of Energy-Based Form Optimization of Office Buildings
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. 497-506
doi	https://doi.org/10.52842/conf.caadria.2020.1.497
summary	Building performance optimization is effective in finding optimal designs and improving building energy efficiency, but its reliability can be affected by uncertainties in input parameters. This paper conducts a reliability analysis on energy-based form optimization of office buildings under uncertainties in envelope and occupancy parameters. An optimization process involving Rhinoceros, EnergyPlus and genetic algorithms is first implemented. Then parametric studies of 644 scenarios involving 4 cities in different climates and 3 form variables are conducted. The results indicate that uncertainties in input parameters could lead to major unreliability of optimization results, including reductions up to 13% in energy saving achieved by optimization and descents up to 10% in energy efficiency compared with results before optimization. Moreover, the uncertainty in visual transmittance of windows is the most significant cause for the unreliability, followed by U-value of walls, while the uncertainty in occupant density and occupant schedule has limited influence. The results can help designers understand the uncertainty of which parameters should be controlled and to what extend optimization results can be trusted in various scenarios.
keywords	Building Performance Optimization; Form Design; Building Energy Efficiency; Uncertainty Analysis; Office Building
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	cdrf2019_217
id	cdrf2019_217
authors	Jinghua Song and Sirui Sun
year	2020
title	Research on Architectural Form Optimization Method Based on Environmental Performance-Driven Design
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_21
summary	In the context of contemporary environment and society, the architectural form optimization based on Environmental performance-driven design is a method by using environmental performance data to optimize the architectural form. Its value lies in dealing with the interaction between architecture and environment, and developing architecture with environmental sustainability. This thesis summarizes the similarities and differences between performance-driven form design and traditional bionic form design. The traditional bionic design separates the bionic object from its complex living environment, and its simple imitation tends to fall into the local rather than the global optimum. However, performancedriven design is different from bionic design. It advocates environmental factors as a driving factor rather than a confrontational factor. It is a systematic global optimal method for studying architectural form. This paper puts forward the specific architectural form optimization simulation process based on the performance-driven thought. Taking the multilayer parking building design of the riparian zone on the south bank of Chongqing as an example, the parametric design method is used to obtain architectural optimization form adapted to the environment.
series	cdrf
email
last changed	2022/09/29 07:51

_id	cdrf2019_229
id	cdrf2019_229
authors	Jingyi Li and Hong Chen
year	2020
title	Optimization and Prediction of Design Variables Driven by Building Energy Performance—A Case Study of Office Building in Wuhan
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_22
summary	This research focuses on the energy performance of office building in Wuhan. The research explored and predicted the optimal solution of design variables by Multi-Island Genetic Algorithm (MIGA) and RBF Artificial neural networks (RBF-ANNs). Research analyzed the cluster centers of design variable by K-means cluster method. In the study, the RBF-ANNs model was established by 1,000 simulation cases. The RMSE (root mean square error) of the RBF-ANNs model in different energy aspects does not exceed 15%. Comparing to the reference case (the largest energy consumption case in the optimization), the 214 elite cases in RBF-ANNs model save at least 37.5% energy. By the cluster centers of the design variables in the elite cases, the study summarized the benchmark of 14 design variables and also suggested a building energy guidance for Wuhan office building design.
series	cdrf
email
last changed	2022/09/29 07:51

_id	acadia20_154p
id	acadia20_154p
authors	Josephson, Alex; Friedman, Jonathan; Salance, Benjamin; Vasyliv, Ivan; Melnichuk, Tim
year	2020
title	Gusto: Rationalizing Computational Masonry Design
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. 154-159
summary	Gusto 501 is a multi-level Infill Building on the footprint of an old car garage. Surrounded by an overpass and former factories, the restaurant and event spaces take the form of a ‘Hyper garage’ as a nod to its urban context. The interior is punctuated with standard terracotta blocks formed to create an intricate play of shadows during the day and embedded with LEDs to provide atmospheric illumination at night. The client's vision, our narrative, and the program demanded an innovative use of the primal material: terracotta. The scale of the project required the use of 3,700 blocks. Within the array wrapped around a 50ft tall interior volume, each block needed to be formed and sequenced uniquely to maintain structural integrity and interface with building systems, and express the sculptural qualities our team had designed. Standard approaches to the masonry could not achieve the effects our team was striving for - we had to develop our ground-up process to manufacture and install mass-customized masonry. The design process involved an algorithmic approach to a series of cuts and geometric manipulations to the blocks that allowed for near-endless combinations/configurations to create a dynamic interior facade system. Partisans, partnering with a terracotta block manufacturer, a local mason, and a masonry engineer, pursued simplifying production using wire cutter systems. Digital and physical mock-ups were then used to create a robust library of parameterized design criteria that optimized corbelling, grout thickness, weight, and fabrication complexity. Working sets of drawings were automated through a fully integrated BIM model, simplifying and speeding up installation. The challenge of marrying these processes with the physical realities of installation required another level of collaboration that included the masons themselves and the electricians who would eventually combine lighting systems into the sculpted block array.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	caadria2020_273
id	caadria2020_273
authors	Shuyan, Zhu and Chenlong, Ma
year	2020
title	An Informed Method - Visualization for Multi-objective Optimization in Conceptual Design Phase
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. 425-434
doi	https://doi.org/10.52842/conf.caadria.2020.1.425
summary	The relationship of different performance objects may be very complicated that designers can't guarantee the improvement of one object don't affect the others. Multi-objective optimization algorithms provide Pareto optimal design solutions, but because of the nonlinearity introduced by the objective functions, the relationships in the objective space do not extend to the decision variable space and vice versa. Based on the design of building blocks and west facade in a practical project, the paper put forward a visualized method for optimization process of building performance, and combine the multi-objective optimization algorithm with the visualization of fitness landscape, so that architects can easily obtain the knowledge of complex relationships between building performance and building parameters. It is more conducive to obtain a design scheme which can balance the requirements of appearance and performance at the same time, and achieve the ultimate goal of improving the efficiency of design.
keywords	Visualization; Multi-objective optimization; Fitness landscape
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	sigradi2020_223
id	sigradi2020_223
authors	Silva, Diego Jami Menezes da; Martino, Jarryer Andrade de
year	2020
title	Space planning from environmental parameter
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. 223-228
summary	The environmental parameter as a constraint in the initial phase of the design process becomes essential for the promotion of the building's environment comfort. This research explores the principles of space planning and the genetic algorithm considering an environment parameter to obtain optimized-solutions automatically in the initial phase of the architectural design process. For this, a generative system was developing using space planning and a genetic algorithm from an environmental parameter to obtain better solutions automatically. Several studies happened to understand the functioning of the mechanism. The research discusses the results and failures that may have influenced the generative system.
keywords	Genetic algorithm, Generative system, Space planning, Performative design, Environmental comfort
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	acadia20_148p
id	acadia20_148p
authors	Vansice, Kyle; Attraya, Rahul; Culligan, Ryan; Johnson, Benton; Sondergaard, Asbjorn; Peters, Nate
year	2020
title	Stereoform Slab
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. 148-153
summary	Stereoform Slab is both a pavilion and a prototype - an exhibition for the 2019 Chicago Architectural Biennial. It is an experiment in how digital form-finding and robotics can be leveraged to rethink the future of concrete construction. Stereoform Slab examines the role of one of the most ubiquitous horizontal elements in the city - the concrete slab, also the most common element in contemporary construction. Using smarter forming systems - in this case, a ruled-surface-derived, robotic hotwire process - the Stereoform Slab prototype proved that the amount of material used and waste generated could be minimized without increasing construction complexity, by about 20% over a conventional system. Stereoform also extends the conventional concrete span (column spacing), specifically in Chicago, from 30’ to 45’. In developing a concrete forming system that affords added flexibility without increasing construction costs, it is possible to reduce embodied carbon significantly. The method allows reducing carbon in buildings that aren’t typically the subject of advanced architectural design or rigorous optimization – conventional buildings that compose a majority of our built environment, and its respective contributions to global carbon emissions. Stereoform is the result of a multi-objective design optimization process. Optimal materialization, according to the compressive/tensile physics present in beam design, was balanced against the fabrication constraints of a singularly ruled-surface, which enables fast form-making using robotic hotwire cutting. SOM and Autodesk collaborated to mirror the approach developed to optimize Stereoform slab as a pavilion, to the building scale, using the multi-objective optimization platform Refinery. Project Refinery allowed the team to create a hyper-responsive system design that could adapt to any number of varying programmatic conditions and loading patterns. The development of this approach is a crucial step in making optimization techniques flexible enough to balance the number of competing parameters in the design process available and accessible to a broader design audience within architecture and engineering.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	caadria2020_009
id	caadria2020_009
authors	Wang, Likai, Chen, Kian Wee, Janssen, Patrick and Ji, Guohua
year	2020
title	Algorithmic generation of architectural Massing Models for building design optimisation - Parametric Modelling Using Subtractive and Additive Form Generation Principles
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. 385-394
doi	https://doi.org/10.52842/conf.caadria.2020.1.385
summary	Using performance-based optimisation to explore unknown design solutions space has become widely acknowledged and considered an efficient approach to designing high-performing buildings. However, the lack of design diversity in the design space defined by the parametric model often confines the search of the optimisation process to a family of similar design variants. In order to overcome this weakness, this paper presents two parametric massing generation algorithms based on the additive and subtractive form generation principles. By abstracting the rule of these two principles, the algorithms can generate diverse building massing design alternatives. This allows the algorithms to be used in performance-based optimisation for exploring a wide range of design alternatives guided by various performance objectives. Two case studies of passive solar energy optimisation are presented to demonstrate the efficacy of the algorithm in helping architects achieve an explorative performance-based optimisation process.
keywords	parametric massing algorithms; performance-based optimisation; design exploration; solar irradiation
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ecaade2020_183
id	ecaade2020_183
authors	Zhao, Jiangyang, Lombardi, Davide and Agkathidis, Asterios
year	2020
title	Application of Robotic Technologies for the Fabrication Of Traditional Chinese Timber Joints
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. 351-360
doi	https://doi.org/10.52842/conf.ecaade.2020.2.351
summary	The traditional Chinese building design was influenced by the climate and the sociogeographical conditions of the different regions in China. They were usually constructed out of wood relying on timber-joint based construction systems. Amongst the wide variety of the structural elements, the Dougong (bucket arch) is one of the most common components of traditional wooden framework buildings, presenting a high level of complexity. Parametric design and robotic technology enable new possibilities regarding its fabrication and application in contemporary architecture. Our paper will explore how the Dougong components could be reinvented through the use of parametric tools and robotic fabrication methods and thus applied to contemporary architectural structures. We will analyse and compare the properties of the original Dougong with the reinvented unit by using finite element analysis and digital optimization tools. Our findings will provide an insight into the traditional construction principles of the joint and how these can inform a design and fabrication framework for its application in contemporary buildings.
keywords	Dougong joint; timber structures; parametric design; robotic fabrication; optimization algorithm
series	eCAADe
email
last changed	2022/06/07 07:57

_id	cdrf2019_134
id	cdrf2019_134
authors	Zhen Han, Wei Yan, and Gang Liu
year	2020
title	A Performance-Based Urban Block Generative Design Using Deep Reinforcement Learning and Computer Vision
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_13
summary	In recent years, generative design methods are widely used to guide urban or architectural design. Some performance-based generative design methods also combine simulation and optimization algorithms to obtain optimal solutions. In this paper, a performance-based automatic generative design method was proposed to incorporate deep reinforcement learning (DRL) and computer vision for urban planning through a case study to generate an urban block based on its direct sunlight hours, solar heat gains as well as the aesthetics of the layout. The method was tested on the redesign of an old industrial district located in Shenyang, Liaoning Province, China. A DRL agent - deep deterministic policy gradient (DDPG) agent - was trained to guide the generation of the schemes. The agent arranges one building in the site at one time in a training episode according to the observation. Rhino/Grasshopper and a computer vision algorithm, Hough Transform, were used to evaluate the performance and aesthetics, respectively. After about 150 h of training, the proposed method generated 2179 satisfactory design solutions. Episode 1936 which had the highest reward has been chosen as the final solution after manual adjustment. The test results have proven that the method is a potentially effective way for assisting urban design.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_024
id	caadria2020_024
authors	Zheng, Hao and Ren, Yue
year	2020
title	Architectural Layout Design through Simulated Annealing Algorithm
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. 275-284
doi	https://doi.org/10.52842/conf.caadria.2020.1.275
summary	Simulated Annealing is an artificial intelligence algorithm for finding the optimal solution of a proposition in an ample search space, which is based on the similarity between the physical annealing process of solid materials and the combinatorial optimization problem. In architectural layout design, although architects usually rely on their subjective design concepts to arrange buildings in a site, the judging criteria hidden in their design concepts are understandable. They can be summarized and parameterized as a combination of penalty and reward functions. By defining the functions to evaluate a design plan, then using the simulated annealing algorithm to search the optimal solution, the plan can be optimized and generated automatically. Six penalty and reward functions are proposed with different parameter weights in this article, which become a guideline for architectural layout design, especially for residential area planning. Then the results of several tests are shown, in which the parameter weights are adjusted, and the importance of each function is integrated. Lastly, a recommended weight and "temperature" setting are proposed, and a system of generating architectural layout is invented, which releases architects from building arranging work in an early stage.
keywords	Architectural Layout; Simulated Annealing; Artificial Intelligence; Computational Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2020_193
id	ecaade2020_193
authors	Alymani, Abdulrahman, Jabi, Wassim and Corcoran, Padraig
year	2020
title	Machine Learning Methods for Clustering Architectural Precedents - Classifying the relationship between building and ground
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 643-652
doi	https://doi.org/10.52842/conf.ecaade.2020.1.643
summary	Every time an object is built, it creates a relationship with the ground. Architects have a full responsibility to design the building by taking the ground into consideration. In the field of architecture, using data mining to identify any unusual patterns or emergent architectural trends is a nascent area that has yet to be fully explored. Clustering techniques are an essential tool in this process for organising large datasets. In this paper, we propose a novel proof-of-concept workflow that enables a machine learning computer system to cluster aspects of an architect's building design style with respect to how the buildings in question relate to the ground. The experimental workflow in this paper consists of two stages. In the first stage, we use a database system to collect, organise and store several significant architectural precedents. The second stage examines the most well-known unsupervised learning algorithm clustering techniques which are: K-Means, K-Modes and Gaussian Mixture Models. Our experiments demonstrated that the K-means clustering algorithm method achieves a level of accuracy that is higher than other clustering methods. This research points to the potential of AI in helping designers identify the typological and topological characteristics of architectural solutions and place them within the most relevant architectural canons
keywords	Machine Learning; Building and Ground Relationship; Clustering Algorithms; K-means cluster Algorithms
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_208p
id	acadia20_208p
authors	Bernier-Lavigne, Samuel
year	2020
title	Object-Field
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. 208-213
summary	This project aims to continue the correlative study between two fundamental entities of digital architecture: the object and the field. Following periods of experimentations on the ""field"" (materialization of flows of data through animation), the ""field of objects"" (parametricism), the ""object"" (OOO), we investigate the last possible interaction remaining: the ""object-field,"" by merging the formal characteristics of the object with the structural flow of its internal field. This investigation is achieved by exploring the high-resolution features of 3d printing in the design of autonomous architectural objects expressing materiality through topological optimization. The objects are generated by an iterative process of volumetric reduction, resulting in an ensemble of monoliths. Four of them are selected and analyzed through topological optimization in order to extract their internal fields. Next, a series of high-resolution algorithmic systems translate the structural information into 3d printed materiality. Of the four object-fields, one materializes, close to identical, the result of the optimization, giving the keystone to understanding the others. The second one expresses the structural flow through a 1mm voxel system, informed by the optimization, having the effect of stiffening the structure where it is needed and thus generating a new topography on the object. The last two explore the blur that this high-resolution can paradoxically create, with complete integration of the optimal structure in a transparent monolith. This is achieved by a vertex displacement algorithm, and the dissolution of the formal data of the monolith and the structural flows, through the mereological assembly of simple linear elements. For each object-field, a series of drawings was developed using specific algorithmic procedures derived from the peculiarities of their complex geometry. The drawings aim to catalyze coherence throughout the project, where similarities, hitherto kept apart by the multiple materialities, begin to dialogue.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2024_222
id	ecaade2024_222
authors	Bindreiter, Stefan; Sisman, Yosun; Forster, Julia
year	2024
title	Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 79–88
doi	https://doi.org/10.52842/conf.ecaade.2024.2.079
summary	To achieve Sustainable Development Goals, in addition to the switch to sustainable energy sources and energy-efficient buildings, transport offers a major lever for reducing energy consumption and greenhouse gases. The increasing demand for emission-free mobility (e.g. through electromobility) but also heat pumps has a direct impact on the electricity consumption of buildings and settlements. It is still difficult to simulate the effects and interactions of different measures as sector coupling concepts require comprehensible tools for ex ante evaluation of planning measures at the community level and the linking of domain-specific models (energy, transport). Using the municipality of Bruck an der Leitha (Austria) as an example, a digital twin based on an open data model (Bednar et al., 2020) is created for the development of methods, which can be used to simulate measures to improve the settlement structure within the municipality. Forecast models for mobility (Schmaus, 2019; Ritz, 2019) and the building stock are developed or applied and linked via the open data model to be able to run through development scenarios and variants. The forecasting and visualisation options created in the project form the basis for the ex-ante evaluation of measures and policies on the way to a Positive-Energy-District. By identifying and collecting missing data, data gaps are filled for the simulation of precise models in the specific study area. A digital, interactive 3D model is created to examine the forecast results and the different scenarios.
keywords	visualisation, decision support, sector coupling, holistic spatial energy models for municipal planning, (energy) saving potentials in settlement development
series	eCAADe
email
last changed	2024/11/17 22:05

_id	acadia20_226p
id	acadia20_226p
authors	Borhani, Alireza; Kalantar, Negar
year	2020
title	Interlocking Shell
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. 226-231
summary	With a specific focus on robotic stereotomy, two full-scale vault structures were designed to explore the potential of self-standing building structures made from interlocking components; these structures were fabricated with a track-mounted industrial-scale robot (ABB 4600). To respond to the economic affordances of robotic subtractive cutting, all uniquely shaped structural modules came from one block of material (48"" x96"" x36""). Through the discretization of curvilinear tessellated vault surfaces into a limited number of uniquely shaped modules with embedded form-fitting connectors, the project exhibited the potential for programming a robot to cut ruled surfaces to produce freeform shells of any kind. Representing nearly zero-waste construction, the developed technology can potentially be used for self-supporting emergency shelters and field medical clinics, facilitating easy shipping and speedy assembly. Without using any scaffolding, a few people can erect and dismantle an entire mortar-free structure at the construction site. The disassembled structure occupies minimal space in storage, and the structure’s pieces can be transported to the site in stacks. Robot milling is a common technique for removing material to transform a block into a sculptural shape. Unlike milling techniques that produce significant waste, we used a hotwire that sliced through a Geofoam block to create almost no waste pieces. Since the front side of every module was concurrent with the backside of the next one, such a decision allowed to operate just one cut per front side of each module. In this case, by having three cuts, two neighboring modules were fabricated. The form of the structure and its modules emerged from the constraints of the fabrication technique, aiming to establish a feedback loop between geometry, material, simulation, and tool. By cross-referencing geometric data across Grasshopper, a customized tessellation script was made to breakdown a vault into its modular ruled surface constructs.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2020_307
id	ecaade2020_307
authors	Caetano, Ines and Leitao, António
year	2020
title	When the Geometry Informs the Algorithm - A hybrid visual/textual programming framework for facade design
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. 371-380
doi	https://doi.org/10.52842/conf.ecaade.2020.2.371
summary	Facade design is becoming increasingly complex, forcing architects to more frequently resort to analysis and optimization processes. However, these processes are time-consuming and require the coordination of multiple tools. Algorithmic Design (AD) has the potential to overcome these limitations through the use of algorithms implemented in Textual Programming Languages (TPLs) or Visual Programming Languages (VPLs). VPLs are more used in architecture due to their smoother learning curve and user-friendliness, but TPLs are better suited than VPLs for handling complex AD problems. To make TPLs more appealing to architects, we incorporated VPLs' features in the textual paradigm, namely, Visual Input Mechanisms (VIMs). In this paper, we propose an extension to an existing AD framework for the design exploration, analysis, and optimization of facades to support a TPL-based approach that handles VIMs.
keywords	Algorithmic Design; Facade Design; Textual Languages; Visual Input
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_604
id	acadia20_604
authors	Craney, Ryan; Adel, Arash
year	2020
title	Engrained Performance
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. 604-613.
doi	https://doi.org/10.52842/conf.acadia.2020.1.604
summary	This project presents a novel fabrication-aware and performance-driven computational design method that facilitates the design and robotic fabrication of a wood shingle facade system. The research merges computational design, robotic fabrication, and building facade optimization into a seamless digital design-to-fabrication workflow. The research encompasses the following topics: (1) a constructive system integrating the rules, constraints, and dependencies of conventional shingle facades; (2) an integrative computational design method incorporating material, robotic fabrication, and assembly constraints; (3) an optimization method for facade sun shading; and (4) a digital design-to-fabrication workflow informing the robotic fabrication procedures. The result is an integrative computational design method for the design of a wood shingle facade. Environmental analysis and multi-objective optimization are coupled with a variable facade surface to produce several optimal design solutions that conform to the constraints of the robotic setup and constructive system. When applied to architectural design, the proposed integrative computational design method demonstrates significant improvements in facade sun-shading performance while also linking the digital design to the fabrication process.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_432
id	ecaade2020_432
authors	Fragkia, Vasiliki and Worre Foged, Isak
year	2020
title	Methods for the Prediction and Specification of Functionally Graded Multi-Grain Responsive Timber Composites
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. 585-594
doi	https://doi.org/10.52842/conf.ecaade.2020.2.585
summary	The paper presents design-integrated methods for high-resolution specification and prediction of functionally graded wood-based thermal responsive composites, using machine learning. The objective is the development of new circular design workflow, employing robotic fabrication, in order to predict fabrication files linked to material performance and design requirements, focused on application for intrinsic responsive and adaptive architectural surfaces. Through an experimental case study, the paper explores how machine learning can form a predictive design framework where low-resolution data can solve material systems at high resolution. The experimental computational and prototyping studies show that the presented image-based machine learning method can be adopted and adapted across various stages and scales of architectural design and fabrication. This in turn allows for a design-per-requirement approach that optimizes material distribution and promotes material economy.
keywords	material specification; responsive timber composites; machine learning; robotic fabrication; building envelopes
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2020_032
id	caadria2020_032
authors	Gu, Zhuoxing and Yang, Chunxia
year	2020
title	Generation of Public Space Structure Based on Digital Multi-agent System - Taking the interaction between self-consensus "Stigmergy" particles and the old city area as an example
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. 285-294
doi	https://doi.org/10.52842/conf.caadria.2020.1.285
summary	In the study, the ant colony behavior was simulated to establish a parametric multi-agent system with independent consensus "Stigmergy" for interaction with the site. In the experiment, the initial points of the particles correspond to the key historical buildings, and the target points correspond to the important public space nodes. Edit and adjust the motion characteristics, search features, generation and disappearance characteristics of the simulated particles to obtain the main consensus particle swarm distribution and the distributed consensus particle swarm distribution. This form has a compliant or conflicting relationship with the existing urban environment. Using the contours of the self-consensus spatial form, the particle swarm density, and the pointing relationship between the particles and the building can provide a basis for the transformation and renewal of the existing urban environment, thus forming a spatial transformation strategy that more closely matches the user behavior in the space.
keywords	Multi-agent system; Particle property construction; Stigmergy; Self-consensus particles; Public space structure
series	CAADRIA
email
last changed	2022/06/07 07:51

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