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	caadria2018_082
id	caadria2018_082
authors	Zhu, Li and Yang, Yang
year	2018
title	Optimization Design Study of Lightweight Temporary Building Integrated with PCMS Through CFD Simulation
doi	https://doi.org/10.52842/conf.caadria.2018.2.155
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. 155-164
summary	In fact, the phase change materials (PCMs) integrated in the building envelope structure can decrease the buildings' energy consumption by enhancing thermal energy storage capacity, which has been acknowledged and appreciated by many engineers and architects. To achieve a better practical application effect under the minimum cost principle and provide a different design method based on indoor thermal discomfort evaluation results for stakeholders, this paper numerically test the application effect of composite envelope under Tianjin climate through commercial computational fluid dynamic soft (Fluent). Further, parameter sensitivity to thermal performance of the composite envelope and indoor thermal discomfort are investigated in this paper, and two different evaluation indicators are introduced and used here. The numerical results obtained in this paper support the high potential of using PCM in lightweight temporary buildings and highlight the further optimization design work.
keywords	Optimization design; Lightweight temporary building; PCMs; CFD simulation
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2018_w02
id	ecaade2018_w02
authors	Jabi, Wassim and Aish, Robert
year	2018
title	Non-manifold Topology for Architectural and Engineering Modelling
doi	https://doi.org/10.52842/conf.ecaade.2018.1.057
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 57-60
summary	Non-manifold topology (NMT) allows the user to construct light-weight conceptual spatial architectural models which define the overall enclosure and the internal cellular division within that enclosure. The objective of this workshop is to give participants hands-on opportunities with a new software library that we have been developing under a research grant from the Leverhulme Trust. On the first day, the concepts of non-manifold topology will be introduced, including non-regular modelling operations. On the second day, we will introduce two plug-ins, which have been interfaced to our NMT tools: a) building energy simulation using OpenStudio and EnergyPlus and b) structural analysis software.
keywords	Non-manifold topology; Visual data flow programming; Building performance simulation; Computational design
series	eCAADe
email
last changed	2022/06/07 07:50

_id	ecaaderis2018_112
id	ecaaderis2018_112
authors	Kontovourkis, Odysseas and Konatzii, Panagiota
year	2018
title	Design-static analysis and environmental assessment investigation based on a kinetic formwork-driven by digital fabrication principles
source	Odysseas Kontovourkis (ed.), Sustainable Computational Workflows [6th eCAADe Regional International Workshop Proceedings / ISBN 9789491207143], Department of Architecture, University of Cyprus, Nicosia, Cyprus, 24-25 May 2018, pp. 131-140
keywords	This research focuses on design-static analysis and environmental assessment procedures that are based on the idea of a flexible kinetic formwork used as the automated mechanism for the production of bricks for porous wall structures. A key aspect of this investigation is the Life Cycle Assessment (LCA) analysis study that is applied in order to achieve, in parallel with the automated procedure, the sustainable potential of the products. For this purpose, the design and construction flexibility of the product is taken into account from the early design decision making stage by examining different sizes of bricks under fabrication including massive or porous ones in order to test their design and static performance, aiming to adapt their shape in multiple functional and environmental scenarios. In parallel, the LCA impact of the given design scenarios are taken into consideration, again from the early design phase, and include, among other objectives, material minimization, less environmental impact of building materials and less energy consumption based on the proposed digital fabrication technology. This is examined by comparing digital design and robotic automated results using three types of ecological materials.
series	eCAADe
email
last changed	2018/05/29 14:33

_id	acadia18_434
id	acadia18_434
authors	Meibodi, Mania Aghaei ; Jipa, Andrei; Giesecke, Rena; Shammas, Demetris; Bernhard, Mathias; Leschok, Matthias; Graser, Konrad; Dillenburger, Benjamin
year	2018
title	Smart Slab. Computational design and digital fabrication of a lightweight concrete slab
doi	https://doi.org/10.52842/conf.acadia.2018.434
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 434-443
summary	This paper presents a computational design approach and novel digital fabrication method for an optimized lightweight concrete slab using a 3D-printed formwork. Smart Slab is the first concrete slab fabricated with a 3D-printed formwork. It is a lightweight concrete slab, displaying three-dimensional geometric differentiation on multiple scales. The optimization of slab systems can have a large impact on buildings: more compact slabs allow for more usable space within the same building volume, refined structural concepts allow for material reduction, and integrated prefabrication can reduce complexity on the construction site. Among the main challenges is that optimized slab geometries are difficult to fabricate in a conventional way because non-standard formworks are very costly. Novel digital fabrication methods such as additive manufacturing of concrete can provide a solution, but until now the material properties and the surface quality only allow for limited applications. The fabrication approach presented here therefore combines the geometric freedom of 3D binderjet printing of formworks with the structural performance of fiber reinforced concrete. Using 3D printing to fabricate sand formwork for concrete, enables the prefabrication of custom concrete slab elements with complex geometric features with great precision. In addition, space for building systems such as sprinklers and Lighting could be integrated in a compact way. The design of the slab is based on a holistic computational model which allows fast design optimization and adaptation, the integration of the planning of the building systems, and the coordination of the multiple fabrication processes involved with an export of all fabrication data. This paper describes the context, design drivers, and digital design process behind the Smart Slab, and then discusses the digital fabrication system used to produce it, focusing on the 3D-printed formwork. It shows that 3D printing is already an attractive alternative for custom formwork solutions, especially when strategically combined with other CNC fabrication methods. Note that smart slab is under construction and images of finished elements can be integrated within couple of weeks.
keywords	full paper, digital fabrication, computation, generative design, hybrid practices
series	ACADIA
type	paper
email
last changed	2022/06/07 07:58

_id	ijac201816403
id	ijac201816403
authors	Pantazis, Evangelos and David Gerber
year	2018
title	A framework for generating and evaluating façade designs using a multi-agent system approach
source	International Journal of Architectural Computing vol. 16 - no. 4, 248-270
summary	Digital design paradigms in architecture have been rooted in representational models which are geometry centered and therefore fail to capture building complexity holistically. Due to a lack of computational design methodologies, existing digital design workflows do little in predicting design performance in the early design stage and in most cases analysis and design optimization are done after a design is fixed. This work proposes a new computational design methodology, intended for use in the area of conceptual design of building design. The proposed methodology is implemented into a multi-agent system design toolkit which facilitates the generation of design alternatives using stochastic algorithms and their evaluation using multiple environmental performance metrics. The method allows the user to probabilistically explore the solution space by modeling the design parameters’ architectural design components (i.e. façade panel) into modular programming blocks (agents) which interact in a bottom-up fashion. Different problem requirements (i.e. level of daylight inside a space, openings) described into agents’ behavior allow for the coupling of data from different engineering fields (environmental design, structural design) into the a priori formation of architectural geometry. In the presented design experiment, a façade panel is modeled into an agent-based fashion and the multi-agent system toolkit is used to generate and evolve alternative façade panel configurations based on environmental parameters (daylight, energy consumption). The designer can develop the façade panel geometry, design behaviors, and performance criteria to evaluate the design alternatives. The toolkit relies on modular and functionally specific programming modules (agents), which provide a platform for façade design exploration by combining existing three-dimensional modeling and analysis software.
keywords	Generative design, multi-agent systems, façade design, agent-based modeling, stochastic search
series	journal
email
last changed	2019/08/07 14:04

_id	sigradi2018_1867
id	sigradi2018_1867
authors	Alawadhi, Mohammad; Yan, Wei
year	2018
title	Geometry from 3D Photogrammetry for Building Energy Modeling
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 631-637
summary	Building energy modeling requires skilled labor, and there is a need to make environmental assessments of buildings more efficient and accessible for architects. A building energy model is based on collecting data from the real, physical world and representing them as a digital model. Recent digital photogrammetry tools can reconstruct real-world geometry by transforming photographs into 3D models automatically. However, there is a lack of accessible workflows that utilize this technology for building energy modeling and simulations. This paper presents a novel methodology to generate a building energy model from a photogrammetry-based 3D model using available tools and computer algorithms.
keywords	3D scanning; Building energy modeling; Building energy simulation; Digital photogrammetry; Photo-to-BEM
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	ecaadesigradi2019_249
id	ecaadesigradi2019_249
authors	Chiarella, Mauro, Gronda, Luciana and Veizaga, Martín
year	2019
title	RILAB - architectural envelopes - From spatial representation (generative algorithm) to geometric physical optimization (scientific modeling)
doi	https://doi.org/10.52842/conf.ecaade.2019.3.017
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 17-24
summary	Augmented graphical thinking operates by integrating algorithmic, heuristic, and manufacturing processes. The Representation and Ideation Laboratory (RILAB-2018) exercise begins with the application of a parametric definition developed by the team of teachers, allowing for the construction of structural systems by the means of the combination of segmental shells and bending-active. The main objetive is the construction of a scientific model of simulation for bending-active laminar structures has brought into reality trustworthy previews for architectural envelopes through the interaction of parametrized relational variables. This way we put designers in a strategic role for the building of the pre-analysis models, allowing more preciseness at the time of picking and defining materials, shapes, spaces and technologies and thus minimizing the decisions based solely in the definition of structural typological categories, local tradition or direct experience. The results verify that the strategic integration of models of geometric physical optimization and spatial representation greatly expand the capabilities in the construction of the complex system that operates in the act of projecting architecture.
keywords	architectural envelopes; augmented graphic thinking; geometric optimization; bending-active
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_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	cdrf2023_526
id	cdrf2023_526
authors	Eric Peterson, Bhavleen Kaur
year	2023
title	Printing Compound-Curved Sandwich Structures with Robotic Multi-Bias Additive Manufacturing
doi	https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_44
source	Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
summary	A research team at Florida International University Robotics and Digital Fabrication Lab has developed a novel method for 3d-printing curved open grid core sandwich structures using a thermoplastic extruder mounted on a robotic arm. This print-on-print additive manufacturing (AM) method relies on the 3d modeling software Rhinoceros and its parametric software plugin Grasshopper with Kuka-Parametric Robotic Control (Kuka-PRC) to convert NURBS surfaces into multi-bias additive manufacturing (MBAM) toolpaths. While several high-profile projects including the University of Stuttgart ICD/ITKE Research Pavilions 2014–15 and 2016–17, ETH-Digital Building Technologies project Levis Ergon Chair 2018, and 3D printed chair using Robotic Hybrid Manufacturing at Institute of Advanced Architecture of Catalonia (IAAC) 2019, have previously demonstrated the feasibility of 3d printing with either MBAM or sandwich structures, this method for printing Compound-Curved Sandwich Structures with Robotic MBAM combines these methods offering the possibility to significantly reduce the weight of spanning or cantilevered surfaces by incorporating the structural logic of open grid-core sandwiches with MBAM toolpath printing. Often built with fiber reinforced plastics (FRP), sandwich structures are a common solution for thin wall construction of compound curved surfaces that require a high strength-to-weight ratio with applications including aerospace, wind energy, marine, automotive, transportation infrastructure, architecture, furniture, and sports equipment manufacturing. Typical practices for producing sandwich structures are labor intensive, involving a multi-stage process including (1) the design and fabrication of a mould, (2) the application of a surface substrate such as FRP, (3) the manual application of a light-weight grid-core material, and (4) application of a second surface substrate to complete the sandwich. There are several shortcomings to this moulded manufacturing method that affect both the formal outcome and the manufacturing process: moulds are often costly and labor intensive to build, formal geometric freedom is limited by the minimum draft angles required for successful removal from the mould, and customization and refinement of product lines can be limited by the need for moulds. While the most common material for this construction method is FRP, our proof-of-concept experiments relied on low-cost thermoplastic using a specially configured pellet extruder. While the method proved feasible for small representative examples there remain significant challenges to the successful deployment of this manufacturing method at larger scales that can only be addressed with additional research. The digital workflow includes the following steps: (1) Create a 3D digital model of the base surface in Rhino, (2) Generate toolpaths for laminar printing in Grasshopper by converting surfaces into lists of oriented points, (3) Generate the structural grid-core using the same process, (4) Orient the robot to align in the direction of the substructure geometric planes, (5) Print the grid core using MBAM toolpaths, (6) Repeat step 1 and 2 for printing the outer surface with appropriate adjustments to the extruder orientation. During the design and printing process, we encountered several challenges including selecting geometry suitable for testing, extruder orientation, calibration of the hot end and extrusion/movement speeds, and deviation between the computer model and the physical object on the build platen. Physical models varied from their digital counterparts by several millimeters due to material deformation in the extrusion and cooling process. Real-time deviation verification studies will likely improve the workflow in future studies.
series	cdrf
email
last changed	2024/05/29 14:04

_id	acadia18_328
id	acadia18_328
authors	Kladeftira, Marirena; Shammas, Demetris; Bernhard, Mathias; Dillenburger, Benjamin
year	2018
title	Printing Whisper Dishes. Large-scale binder jetting for outdoor installations
doi	https://doi.org/10.52842/conf.acadia.2018.328
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 328-335
summary	This research explores the design opportunities of a novel fabrication process for large scale architectural installations suitable for outdoor weather conditions. High resolution, bespoke geometries are easily fabricated at no extra cost in a continuous system using Binder Jet printing technology. The material properties of sandstone are considered a design drive for producing structural paths according to a finite element analysis. Several post processing materials are tested for strengthening the final geometry and providing a water resistant solution. The process is tested in a large, 1:1 sound installation of a pair of acoustic mirrors. First, this paper describes the specific potential and challenges of Binder Jet printing for outdoor applications. It, then, outlines the design principles of the sound device, the acoustic mirror, and their integration into a digital model. Finally, the computational design strategy is described, including topology optimization to reduce the weight/material and the integration of functional details
keywords	work in progress, 3d printing, form finding, digital fabrication, building technologies
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	caadria2018_046
id	caadria2018_046
authors	Lu, Siliang and Cochran Hameen, Erica
year	2018
title	Integrated IR Vision Sensor for Online Clothing Insulation Measurement
doi	https://doi.org/10.52842/conf.caadria.2018.1.565
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. 565-573
summary	As one of the most important building systems, HVAC plays a key role in creating a comfortable thermal environment. Predicted Mean Vote (PMV), an index that predicts the mean value of the votes of a large group of persons on the thermal sensation scale, has been adopted to evaluate the built environment. Compared to environmental factors, clothing insulation can be much harder to measure in the field. The existing research on real-time clothing insulation measurement mainly focuses on expensive infrared thermography (IR) cameras. Therefore, to ensure cost-effectiveness, the paper has proposed a solution consisting of a normal camera, IR and air temperature sensors and Arduino Nanos to measure clothing insulation in real-time. Moreover, the algorithm includes the initialization from clothing classification with pre-trained neural network and optimization of the clothing insulation calculation. A total of 8 tests have been conducted with garments for spring/fall, summer and winter. The current results have shown the accuracy of T-shirt classification can reach over 90%. Moreover, compared with the results with IR cameras and reference values, the accuracies of the proposed sensing system vary with different clothing types. Research shall be further conducted and be applied into the dynamic PMV-based HVAC control system.
keywords	clothing insulation; skin temperature; clothing classification; IR temperature sensor; Optimization
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2023_10
id	ecaade2023_10
authors	Sepúlveda, Abel, Eslamirad, Nasim and De Luca, Francesco
year	2023
title	Machine Learning Approach versus Prediction Formulas to Design Healthy Dwellings in a Cold Climate
doi	https://doi.org/10.52842/conf.ecaade.2023.2.359
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. 359–368
summary	This paper presents a study about the prediction accuracy of daylight provision and overheating levels in dwellings when considering different methods (machine learning vs prediction formulas), training, and validation data sets. An existing high-rise building located in Tallinn, Estonia was considered to compare the best ML predictive method with novel prediction formulas. The quantification of daylight provision was conducted according to the European daylight standard EN 17037:2018 (based on minimum Daylight Factor (minDF)) and overheating level in terms of the degree-hour (DH) metric included in local regulations. The features included in the dataset are the minDF and DH values related to different combinations of design parameters: window-to-floor ratio, level of obstruction, g-value, and visible transmittance of the glazing system. Different training and validation data sets were obtained from a main data set of 5120 minDF values and 40960 DH values obtained through simulation with Radiance and EnergyPlus, respectively. For each combination of training and validation dataset, the accuracy of the ML model was quantified and compared with the accuracy of the prediction formulas. According to our results, the ML model could provide more accurate minDF/DH predictions than by using the prediction formulas for the same design parameters. However, the amount of room combinations needed to train the machine-learning model is larger than for the calibration of the prediction formulas. The paper discuss in detail the method to use in practice, depending on time and accuracy concerns.
keywords	Optimization, Daylight, Thermal Comfort, Overheating, Machine Learning, Predictive Model, Dwellings, Cold Climates
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaaderis2023_11
id	ecaaderis2023_11
authors	Sepúlveda, Abel, Eslamirad, Nasim, Seyed Salehi, Seyed Shahabaldin, Thalfeldt, Martin and De Luca, Francesco
year	2023
title	Machine Learning-based Optimization Design Workflow based on Obstruction Angles for Building Facades
source	De Luca, F, Lykouras, I and Wurzer, G (eds.), Proceedings of the 9th eCAADe Regional International Symposium, TalTech, 15 - 16 June 2023, pp. 15–24
summary	This paper proposes a ML-based optimization design workflow based on obstruction angles for the optimization of building facades (i.e. g-value and window width). The optimization output consists of the optimal clustering of windows in order to ensure a desired level of daylight provision according to method 2 defined in the EN17307:2018 (i.e. based on Spatial Daylight Autonomy: sDA) and to not exceed a maximum level of specific cooling capacity (SCC). The independent variables or design parameters of the parametric model are: room orientation/dimensions, window dimensions, and obstruction angle (??). The ML prediction models were trained and tested with reliable simulation results using validate softwares. The total number of room combinations is 61440 for sDA and SCC simulations. The development of reliable (90% of right predictions) ML predictive models based on decision tree technique were calibrated. The optimal clustering of windows was done first by floors and secondly by the designer’s need to homogenize the external facade with similar glazing properties and window sizes, having impact on the annual heating consumption. The proposed method help designers to make accurate and faster design decisions during early design stages and renovation plans.
keywords	optimization, daylight, thermal comfort, cooling capacity, machine-learning predictive model, office buildings, cold climates
series	eCAADe
email
last changed	2024/02/05 14:28

_id	ecaade2018_170
id	ecaade2018_170
authors	Shahsavari, Fatemeh, Koosha, Rasool, Vahid, Milad R., Yan, Wei and Clayton, Mark
year	2018
title	Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making - A Probabilistic Model and Applications
doi	https://doi.org/10.52842/conf.ecaade.2018.1.295
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 295-304
summary	To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants' behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process.
keywords	Probability-based design decision; uncertainty analysis; sensitivity analysis; building energy consumption model
series	eCAADe
email
last changed	2022/06/07 07:57

_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

_id	caadria2018_257
id	caadria2018_257
authors	Yousif, Shermeen and Yan, Wei
year	2018
title	Clustering Forms for Enhancing Architectural Design Optimization
doi	https://doi.org/10.52842/conf.caadria.2018.2.431
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. 431-440
summary	This work introduces a new system in architectural design optimization that integrates form diversity and clustering methods into the process. The first method we propose is an algorithm for rating design solutions according to their geometric correspondences, maximizing differences and enforcing diversity. In addition, we implement the K-means algorithm to cluster the resulting design forms into groups of similar forms, to substitute each group with one representative solution. The work aims to facilitate decision making and form evaluation for designers, leading to an interactive optimization process, and contributing to improving existing optimization models in architectural design research and practice. We modeled a dynamic system through prototyping, experimenting and test-case application. As a prototype development, the protocol was done through phases of: (1) parametric modeling, (2) conducting energy simulation and daylight analysis and running a generative system, and (3) developing an algorithm for form diversity and another for implementing K-means clustering. The results are illustrated and discussed in detail in the paper.
keywords	Architectural Design Optimization; Form Diversity; K-Means Clustering
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2018_247
id	ecaade2018_247
authors	Ilunga, Guilherme and Leit?o, António
year	2018
title	Derivative-free Methods for Structural Optimization
doi	https://doi.org/10.52842/conf.ecaade.2018.1.179
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 179-186
summary	The focus on efficiency has grown over recent years, and nowadays it is critical that buildings have a good performance regarding different criteria. This need prompts the usage of algorithmic approaches, analysis tools, and optimization algorithms, to find the best performing variation of a design. There are many optimization algorithms and not all of them are adequate for a specific problem. However, Genetic Algorithms are frequently the first and only option, despite being considered last resort algorithms in the mathematical field. This paper discusses methods for structural optimization and applies them on a structural problem. Our tests show that Genetic Algorithms perform poorly, while other algorithms achieve better results. However, they also show that no algorithm is consistently better than the others, which suggests that for structural optimization, several algorithms should be used, instead of simply using Genetic Algorithms.
keywords	Derivative-free Optimization; Black-box Optimization; Structural Optimization; Algorithmic Design
series	eCAADe
email
last changed	2022/06/07 07:49

_id	caadria2018_101
id	caadria2018_101
authors	Tablada, Abel, Chaplin, Ian, Huang, Huajing, Lau, Siu-Kit, Yuan, Chao and Lau, Stephen Siu-Yu
year	2018
title	Simulation Algorithm for the Integration of Solar and Farming Systems on Tropical Façades
doi	https://doi.org/10.52842/conf.caadria.2018.2.123
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. 123-132
summary	The study focuses on the creation of an algorithm in Grasshopper using Ladybug and Honeybee plugins to simulate a large number of façade design variants with the integration of photovoltaic (PV) panels as shading devices and farming systems. The algorithm aims to facilitate such simulations in a semi-automated way complying with standard practise in a relative short time. Simulation results are then extracted and assessed using an analytical optimization method.
keywords	Key words: grasshopper; ladybug; honeybee; BIPV; vertical farming; productive facades
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_405
id	ecaade2018_405
authors	Belém, Catarina and Leit?o, António
year	2018
title	From Design to Optimized Design - An algorithmic-based approach
doi	https://doi.org/10.52842/conf.ecaade.2018.2.549
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. 549-558
summary	Stringent requirements of efficiency and sustainability lead to the demand for buildings that have good performance regarding different criteria, such as cost, lighting, thermal, and structural, among others. Optimization can be used to ensure that such requirements are met. In order to optimize a design, it is necessary to generate different variations of the design, and to evaluate each variation regarding the intended criteria. Currently available design and evaluation tools often demand manual and time-consuming interventions, thus limiting design variations, and causing architects to completely avoid optimization or to postpone it to later stages of the design, when its benefits are diminished. To address these limitations, we propose Algorithmic Optimization, an algorithmic-based approach that combines an algorithmic description of building designs with automated simulation processes and with optimization processes. We test our approach on a daylighting optimization case study and we benchmark different optimization methods. Our results show that the proposed workflow allows to exclude manual interventions from the optimization process, thus enabling its automation. Moreover, the proposed workflow is able to support the architect in the choice of the optimization method, as it enables him to easily switch between different optimization methods.
keywords	Algorithmic Design; Algorithmic Analysis; Algorithmic Optimization; Lighting optimization; Black-Box optimization
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_459
id	ecaadesigradi2019_459
authors	Bourdakis, Vassilis and Tsangrassoulis, Aris
year	2019
title	Dynamic Façade Design Studio - From sketches to microcontrollers
doi	https://doi.org/10.52842/conf.ecaade.2019.2.725
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 725-730
summary	The paper presents the outcome of two semesters running a dynamic façade design studio (2014 and 2018) to 3rd and 4th year undergraduates, using computational design, simulation and visualization tools in designing environmentally activated building envelopes. The paper discusses the problems faced by the students and the teaching team throughout the design process and finally suggests ways of integrating microcontrollers as a teaching tool enabling students to comprehend the logic, complexities and overall mechanics of responsive environmental design.
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

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