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 ecaade2018_247
id ecaade2018_247
authors Ilunga, Guilherme and Leit?o, António
year 2018
title Derivative-free Methods for Structural Optimization
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
doi https://doi.org/10.52842/conf.ecaade.2018.1.179
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 acadia23_v1_166
id acadia23_v1_166
authors Chamorro Martin, Eduardo; Burry, Mark; Marengo, Mathilde
year 2023
title High-performance Spatial Composite 3D Printing
source ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 166-171.
summary This project explores the advantages of employing continuum material topology optimization in a 3D non-standard lattice structure through fiber additive manufacturing processes (Figure 1). Additive manufacturing (AM) has gained rapid adoption in architecture, engineering, and construction (AEC). However, existing optimization techniques often overlook the mechanical anisotropy of AM processes, resulting in suboptimal structural properties, with a focus on layer-by-layer or planar processes. Materials, processes, and techniques considering anisotropy behavior (Kwon et al. 2018) could enhance structural performance (Xie 2022). Research on 3D printing materials with high anisotropy is limited (Eichenhofer et al. 2017), but it holds potential benefits (Liu et al. 2018). Spatial lattices, such as space frames, maximize structural efficiency by enhancing flexural rigidity and load-bearing capacity using minimal material (Woods et al. 2016). From a structural design perspective, specific non-standard lattice geometries offer great potential for reducing material usage, leading to lightweight load-bearing structures (Shelton 2017). The flexibility and freedom of shape inherent to AM offers the possibility to create aggregated continuous truss-like elements with custom topologies.
series ACADIA
type project
email
last changed 2024/04/17 13:58

_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)
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
doi https://doi.org/10.52842/conf.ecaade.2019.3.017
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
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
doi https://doi.org/10.52842/conf.caadria.2018.1.205
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 sigradi2018_1631
id sigradi2018_1631
authors Godoi da Cruz, Renato; Arcipreste, Cláudia Maria; Lemieszek Pinheiro, Rafael; de Jesus Ribas, Rovadávia Aline
year 2018
title Generative design in the design development of metallic constructions
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. 211-218
summary The present article describes the construction of a system that combines parametric modeling strategies and genetic algorithms for optimization. By means of the reformulation of the Darwinian evolutionary process, it is sought to systematize a project process that allows the architect to act in the parameterization of the problems, beyond the mere formal proposition of solutions, in favor of the exploration of a greater variety of projective possibilities than would be possible using traditional design methods.
keywords Generative design; Evolutionary algorithms; Structural analysis; Environmental analysis and Metallic construction
series SIGRADI
email
last changed 2021/03/28 19:58

_id ecaade2018_434
id ecaade2018_434
authors Hünkar, Ertunç and Figueiredo, Bruno Acácio Ferreira
year 2018
title 3D Printing of High Strength and Multi-Scaled Fragmented Structures
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. 173-178
doi https://doi.org/10.52842/conf.ecaade.2018.1.173
summary Our research aims to push the limits of 3D printing towards the structural design and optimization. Additive manufacturing has an unique feature which is printing multi-faced complex geometries as easy as simple ones. Therefore additive manufacturing creates the chance of producing really small scaled complex forms. In a structural network, it can be easily understood that the more geometric variations to respond stress, the more adaptive structure will become to respond structural needs. The structural reaction is to be fictionalized by procedural operations and analysis that will be a tool to design multi-scaled fragmented structures. Those operations is to use the structural analysis and material reactions. Their iteration with the overall geometry will form the geometric generations. However the verification of the generations as outcomes of a real 3D printer is crucial. To verify, the precision of additive manufacturing should be sensitive enough that the structural element will function as it's simulated in computer with the algorithm. The sensitivity is important because, even couple of micro-sized problems can cause bigger ones in the structural element itself. The combination of all these variables can enable an initial geometry, to be able to adapt the stuructural needs in every additive generation.
keywords Additive Manufacturing(AM); Structural Optimization; Selective Laser Sintering(SLS); Structural Design; Shape Grammars; Design Computation
series eCAADe
email
last changed 2022/06/07 07:50

_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
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
doi https://doi.org/10.52842/conf.acadia.2018.328
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_067
id caadria2018_067
authors Lu, Shuai and Guo, Cong
year 2018
title Investigation on the Potential of Improving Daylight Efficiency of Office Buildings by Optimized Curved Facades
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. 113-121
doi https://doi.org/10.52842/conf.caadria.2018.2.113
summary With the rapid development of digital design methods, irregular curved shapes have been more and more widely used in buildings, which not only enriches the appearances of buildings, but also provide new possibilities of improving building performance by shape designs. However, existing researches regarding building performance and shapes mostly focus on regular shapes, while curved shapes are rarely explored. This paper aims to employ design optimization method to explore the improvement of building performance that curved shapes could contribute. Specifically, office buildings are chosen as an example and the potential of improving the daylight efficiency of them by optimized curved facades are investigated. Three major cities and two orientations are involved in the investigation. The results prove that curved facades do have significant potential to improve the daylight efficiency of office buildings, and an average improvement of 0.2032 is achieved by the optimized curved facades in the 6 cases conducted in this research in terms of the area-weighted average UDI (useful daylight illuminance) compared with the same building with plane facade.
keywords Curved Facade; Daylight; Building Performance; Design Optimization; Office Building
series CAADRIA
email
last changed 2022/06/07 07:59

_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
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
doi https://doi.org/10.52842/conf.caadria.2018.1.565
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 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
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
doi https://doi.org/10.52842/conf.acadia.2018.434
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 caadria2018_228
id caadria2018_228
authors Newton, David
year 2018
title Accommodating Change and Open-Ended Search in Design Optimization
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. 175-184
doi https://doi.org/10.52842/conf.caadria.2018.2.175
summary Many real-world architectural multi-objective problems (MOPs) are dynamic and may have objectives, decision variables, and constraints that change during the optimization process. These problems are known as dynamic MOPs (DMOPs). Dynamic multi-objective evolutionary algorithms (DMOEAs) have emerged in the fields of optimization, operations research, and computer science as one way to address the challenges posed by DMOPs. DMOEAs offer new capacities for exploration and interaction with the designer, but they have not yet been studied in the field of architecture. This research addresses these issues through the development of a unique interactive DMOEA-based design tool for the conceptual design phase. We propose a new modification to the popular nondominated sorting genetic algorithm II (NSGA-II), that we call the dynamic progressive for architecture NSGA-II (DPA-NSGA-II). We show that DPA-NSGA-II outperforms NSGA-II in finding novel solutions.
keywords algorithmic design; multi-objective optimization; evolutionary computation; parametric design; generative design
series CAADRIA
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 caadria2018_097
id caadria2018_097
authors Park, Daekwon
year 2018
title Adaptive THERM-SKIN - Tunable Cellular Materials for Adaptive Thermal Control
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
doi https://doi.org/10.52842/conf.caadria.2018.2.309
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 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
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
doi https://doi.org/10.52842/conf.ecaade.2023.2.359
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 ecaade2020_445
id ecaade2020_445
authors Spiegelhalter, Thomas, Andia, Alfredo, Levente, Juhasz and Namuduri, Srikanth
year 2020
title Part 1: The Integrated Decision Support System - Generative and synthetic biological design imaginations for the Miami bay area
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. 11-20
doi https://doi.org/10.52842/conf.ecaade.2020.2.011
summary In less than 150 years our carbon society transformed the planet. Today more than 50% of ecologies in the world are determined by unsustainable industrialization processes. The latest IPCC reports show that we are quickly arriving at points of no return in the warming of our planet. We cannot afford to continue in the same direction, we need a new imagination. As part of an E.U.-US funded $1.9 million research project we have been working on multiple projects for the future of the Miami islands since 2018:1. We developed a generative GIS-BIM based Python API for mapping and optimization of carbon-neutral design workflows. It includes genetic design combinatorics with intuitive graphical Dynamo-Python-Grasshopper programming with experimental design results. 2. We worked on a series of design research for the Miami Bay that envisions islands, living shorelines, programmable soils, and infrastructures that grow by themselves using synthetic biology.
keywords Automated Workflows, Synthetic Biology, Artificial Intelligence, Architecture, Sea-level Rise
series eCAADe
email
last changed 2022/06/07 07:56

_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
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
doi https://doi.org/10.52842/conf.caadria.2018.2.123
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 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
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
doi https://doi.org/10.52842/conf.caadria.2018.2.155
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 sigradi2018_1571
id sigradi2018_1571
authors de Mello Monteiro, Verner Max Liger; Alves Bezerra, José Rauryson; Paulino do Nascimento, Paulo Roberto; Ramalho dos Santos Júnior, Erisvaldo
year 2018
title Mathematizing Niemeyer’s architecture through parametric modeling: evaluating the parables of the Pampulha Church
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. 294-299
summary This paper describes the mathematization process behind the parables of the Pampulha Church, one of the most iconic buildings designed by Oscar Niemeyer, in order to check how applicable was the use of analytic geometry in his architecture. To reach this, we factored the second degree equations presented on the building based on the parable height and width, then using parametric modeling to translate the formula into shape. As a result, the study intended to demonstrate how equations can be integrated into architecture, identifying how conic curves are being applied to the architectural geometry.
keywords Parametric modeling; Pampulha church; Oscar Niemeyer; Analytic geometry
series SIGRADI
email
last changed 2021/03/28 19:58

_id caadria2018_343
id caadria2018_343
authors Kalantar, Negar and Borhani, Alireza
year 2018
title Informing Deformable Formworks - Parameterizing Deformation Behavior of a Non-Stretchable Membrane via Kerfing
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. 339-348
doi https://doi.org/10.52842/conf.caadria.2018.2.339
summary The process for constructing freeform buildings composed of many non-repetitive shapes and waste-free formwork systems remains relatively unexplored. This research reviews a method for fabricating complex double-curved shapes without utilizing single-use formworks. This work answers questions regarding the manufacturing of these shapes in an environmentally-friendly and economic fashion. The proposed method, called a "transformative formwork," could replace state-of-the-art CNC-milled molds and is potentially suitable for large-scale construction. The transformative formwork uses a stretchable membrane or "interpolation layer" that can be manipulated into any curved surface by using vertical bars capable of being rearranged into different heights. Here, to accurately generate most of the smooth, double-curved surfaces, laser kerfing is used for bending interpolation layer into almost any complex shape. A parametric model simplifies local or global changes to the density of the kerfing patterns, modifying the deformation behavior of the layer. Several kerfed interpolation layers produced for four transformative formworks showed that the application of this method.
keywords Transformative Formwork, Interpolation Layer, Relief-cut Patterns, Positive & Negative Gaussian Curvatures, Interlocking Archimedean Spiral-Patterns, Kerfing
series CAADRIA
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last changed 2022/06/07 07:52

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