Pub Date : 2023-07-19DOI: 10.1177/14780771231188474
Adel Gürel, Burcu Şenyapılı Ozcan
The initial phases of design, known as the conceptual design phases, are often associated with hand sketching, while parametric tools are reserved for the later, more developed stages of design. This paper examines the potentials of using parametric tools in the early design phases in comparison to widely utilized hand sketching. It is intended to find out the impacts of using parametric tools on the cognitive behaviors and the satisfaction of self-assessment levels of the designers. An experimental study was conducted with a group of graduate architecture students using Grasshopper, the findings of which are analyzed through a content-oriented coding scheme, together with protocol analyses. Significant differences are found between cognitive behaviors of the participants in using hand sketching and Grasshopper. The findings show that all of the participants consider Grasshopper as a useful conceptual design tool that may be utilized in early design phases, in contrast to its wide popularity in the late stages of design.
{"title":"Cognitive Comparison of design methods in the conceptual phase","authors":"Adel Gürel, Burcu Şenyapılı Ozcan","doi":"10.1177/14780771231188474","DOIUrl":"https://doi.org/10.1177/14780771231188474","url":null,"abstract":"The initial phases of design, known as the conceptual design phases, are often associated with hand sketching, while parametric tools are reserved for the later, more developed stages of design. This paper examines the potentials of using parametric tools in the early design phases in comparison to widely utilized hand sketching. It is intended to find out the impacts of using parametric tools on the cognitive behaviors and the satisfaction of self-assessment levels of the designers. An experimental study was conducted with a group of graduate architecture students using Grasshopper, the findings of which are analyzed through a content-oriented coding scheme, together with protocol analyses. Significant differences are found between cognitive behaviors of the participants in using hand sketching and Grasshopper. The findings show that all of the participants consider Grasshopper as a useful conceptual design tool that may be utilized in early design phases, in contrast to its wide popularity in the late stages of design.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46325414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.1177/14780771231186259
Mohammed Ayoub
Traditional vaulted roof-forms have long been utilized in hot-desert climate for better indoor environmental quality. Unprecedently, this research investigates the possible contribution of machine learning to estimate the received solar irradiances by those roofs, based on simulation-derived training and testing datasets, where two algorithms were used to reduce their higher-dimensionality. Then, four models of ordinary least-squares and artificial neural networks were developed. Their ability to accurately estimate solar irradiances was confirmed, with R 2 of 95.599–98.794% and RMSE of 12.437–23.909 Wh/m 2 . Transfer Learning was also applied to pass the stored knowledge of the best-performing model into another one for estimating the performance of new roof-forms. The results demonstrated that transferred models could provide better estimations with R 2 of 87.416–97.889% and RMSE of 79.300–13.971 Wh/m 2 , compared to un-transferred models. Machine learning shall redefine the practice of building performance, providing architects with flexibility to rapidly make informed decisions during the early design stages.
{"title":"Estimating the received solar irradiances by traditional vaulted roofs using optimized neural networks and transfer learning","authors":"Mohammed Ayoub","doi":"10.1177/14780771231186259","DOIUrl":"https://doi.org/10.1177/14780771231186259","url":null,"abstract":"Traditional vaulted roof-forms have long been utilized in hot-desert climate for better indoor environmental quality. Unprecedently, this research investigates the possible contribution of machine learning to estimate the received solar irradiances by those roofs, based on simulation-derived training and testing datasets, where two algorithms were used to reduce their higher-dimensionality. Then, four models of ordinary least-squares and artificial neural networks were developed. Their ability to accurately estimate solar irradiances was confirmed, with R 2 of 95.599–98.794% and RMSE of 12.437–23.909 Wh/m 2 . Transfer Learning was also applied to pass the stored knowledge of the best-performing model into another one for estimating the performance of new roof-forms. The results demonstrated that transferred models could provide better estimations with R 2 of 87.416–97.889% and RMSE of 79.300–13.971 Wh/m 2 , compared to un-transferred models. Machine learning shall redefine the practice of building performance, providing architects with flexibility to rapidly make informed decisions during the early design stages.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135454461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-23DOI: 10.1177/14780771231176029
Paulo Roberto da Silva Ruiz, C. Almeida, M. B. Schimalski, V. Liesenberg, E. Mitishita
Registering, documenting, updating, revitalizing, expanding, and renovating old urban buildings require proper documentation. The adoption of 3D survey techniques is essential to grant efficiency and agility to such purposes. This article discusses a multi-approach integration of Light Detection and Ranging (LiDAR) data collected by aerial and terrestrial platforms, meant for the 3D modeling of a building at Level of Detail 3. The selected building presents challenging elements for modeling, such as blocks with different heights and indented facades. It is located on the campus of the Federal University of Paraná (UFPR) in Curitiba, Brazil, on a site with irregular terrain and surrounded by trees, what made the terrestrial laser scanning process difficult. For its three-dimensional reconstruction, data from an Aerial Laser Scanning system were integrated with data from a Terrestrial Laser Scanner (TLS). Based on the 3D modeling, an as-is Building Information Modeling model of the building’s exterior was created. To validate the results, measurements of the building were obtained by means of an Electronic Distance Measurement (EDM) device and they were then compared with measurements extracted from the point cloud-based BIM model. The results demonstrate that there was a correspondence between the EDM and the LiDAR-derived measures, attaining a satisfactory statistical agreement. The article focuses on the accuracy of LiDAR models for the cadastral update of buildings, providing information for decision making in documentation projects and construction interventions. The main contribution of this work consists in a multi-approach workflow for delivering an effective and precise solution for accomplishing an as-is BIM documentation, highlighting advantages, drawbacks, and the potential of this set of methods for integrating multi-source LiDAR point clouds.
{"title":"Multi-approach integration of ALS and TLS point clouds for a 3-D building modeling at LoD3","authors":"Paulo Roberto da Silva Ruiz, C. Almeida, M. B. Schimalski, V. Liesenberg, E. Mitishita","doi":"10.1177/14780771231176029","DOIUrl":"https://doi.org/10.1177/14780771231176029","url":null,"abstract":"Registering, documenting, updating, revitalizing, expanding, and renovating old urban buildings require proper documentation. The adoption of 3D survey techniques is essential to grant efficiency and agility to such purposes. This article discusses a multi-approach integration of Light Detection and Ranging (LiDAR) data collected by aerial and terrestrial platforms, meant for the 3D modeling of a building at Level of Detail 3. The selected building presents challenging elements for modeling, such as blocks with different heights and indented facades. It is located on the campus of the Federal University of Paraná (UFPR) in Curitiba, Brazil, on a site with irregular terrain and surrounded by trees, what made the terrestrial laser scanning process difficult. For its three-dimensional reconstruction, data from an Aerial Laser Scanning system were integrated with data from a Terrestrial Laser Scanner (TLS). Based on the 3D modeling, an as-is Building Information Modeling model of the building’s exterior was created. To validate the results, measurements of the building were obtained by means of an Electronic Distance Measurement (EDM) device and they were then compared with measurements extracted from the point cloud-based BIM model. The results demonstrate that there was a correspondence between the EDM and the LiDAR-derived measures, attaining a satisfactory statistical agreement. The article focuses on the accuracy of LiDAR models for the cadastral update of buildings, providing information for decision making in documentation projects and construction interventions. The main contribution of this work consists in a multi-approach workflow for delivering an effective and precise solution for accomplishing an as-is BIM documentation, highlighting advantages, drawbacks, and the potential of this set of methods for integrating multi-source LiDAR point clouds.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44138631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-08DOI: 10.1177/14780771231181237
Selen Çiçek, G. Turhan, Aybüke Taşer
The urban built environment of contemporary cities confronts a constant risk of deterioration due to natural or artificial reasons. Especially political aggression and war conflicts have significant destructive effects on architectural and cultural heritage buildings. The post-war urbanscapes demonstrate the striking effects of the armed conflicts during the hot war encounters. However, the residues of the urbanscapes become the actual indicators of damage and loss. Since today we can make future predictions using a variety of machine learning algorithms, it is possible to represent hybrid projections of urban heterotopias. In this context, this research proposes to explore dystopian post-war projections for modern cities based on their architectural styles and demonstrate the utopian scenarios of rehabilitation possibilities for the damaged urban built environment of post-war cities by using generative adversarial network (GAN) algorithms. Two primary datasets containing the post-war and pre-war building facades have been given as the input data for the CycleGAN and pix2pix GAN models. Thus, two different image-to-image GAN models have been compared regarding their ability to produce legible building facade projections in architectural features. Besides, the machine learning process results have been discussed in terms of cities’ utopian and dystopian future predictions, demonstrating the war conflicts’ immense effects on the built environment. Moreover, the immediate consequence of the destructive aggression on tangible and intangible architectural heritage would become visible to inhabitants and policymakers when the AI-generated rehabilitation potentials have been exposed.
{"title":"Deterioration of pre-war and rehabilitation of post-war urbanscapes using generative adversarial networks","authors":"Selen Çiçek, G. Turhan, Aybüke Taşer","doi":"10.1177/14780771231181237","DOIUrl":"https://doi.org/10.1177/14780771231181237","url":null,"abstract":"The urban built environment of contemporary cities confronts a constant risk of deterioration due to natural or artificial reasons. Especially political aggression and war conflicts have significant destructive effects on architectural and cultural heritage buildings. The post-war urbanscapes demonstrate the striking effects of the armed conflicts during the hot war encounters. However, the residues of the urbanscapes become the actual indicators of damage and loss. Since today we can make future predictions using a variety of machine learning algorithms, it is possible to represent hybrid projections of urban heterotopias. In this context, this research proposes to explore dystopian post-war projections for modern cities based on their architectural styles and demonstrate the utopian scenarios of rehabilitation possibilities for the damaged urban built environment of post-war cities by using generative adversarial network (GAN) algorithms. Two primary datasets containing the post-war and pre-war building facades have been given as the input data for the CycleGAN and pix2pix GAN models. Thus, two different image-to-image GAN models have been compared regarding their ability to produce legible building facade projections in architectural features. Besides, the machine learning process results have been discussed in terms of cities’ utopian and dystopian future predictions, demonstrating the war conflicts’ immense effects on the built environment. Moreover, the immediate consequence of the destructive aggression on tangible and intangible architectural heritage would become visible to inhabitants and policymakers when the AI-generated rehabilitation potentials have been exposed.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46353094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1177/14780771231180256
Jong Bum Kim, D. Oprean, Laura B. Cole, Laura Zangori
The research investigates the design and development of a serious game to teach green building design and energy literacy in rural middle schools in the United States. The paper presents a pilot study, education mini-game development integrated with parametric BIM and energy simulations. The game scenario was built on the developed science curriculum modules in our funded research, teaching building energy technologies such as daylighting, artificial lighting, window configurations, building materials, solar panels, etc. The mini-game, Illumi’s World, presents a baseline science lab and a media library of typical public schools in the United States. The players have the opportunity to improve energy literacy in several ways: manipulating the building configurations and the energy options, reviewing energy costs and emission level changes, and monitoring the performance from the game dashboards. This paper presents background theory, curriculum design, the mini-game development framework, methods and tools for energy simulation and BIM visualization, and the findings and challenges.
{"title":"Illumi’s world: A mini-game development with parametric BIM-based simulations","authors":"Jong Bum Kim, D. Oprean, Laura B. Cole, Laura Zangori","doi":"10.1177/14780771231180256","DOIUrl":"https://doi.org/10.1177/14780771231180256","url":null,"abstract":"The research investigates the design and development of a serious game to teach green building design and energy literacy in rural middle schools in the United States. The paper presents a pilot study, education mini-game development integrated with parametric BIM and energy simulations. The game scenario was built on the developed science curriculum modules in our funded research, teaching building energy technologies such as daylighting, artificial lighting, window configurations, building materials, solar panels, etc. The mini-game, Illumi’s World, presents a baseline science lab and a media library of typical public schools in the United States. The players have the opportunity to improve energy literacy in several ways: manipulating the building configurations and the energy options, reviewing energy costs and emission level changes, and monitoring the performance from the game dashboards. This paper presents background theory, curriculum design, the mini-game development framework, methods and tools for energy simulation and BIM visualization, and the findings and challenges.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"462 - 477"},"PeriodicalIF":1.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42301319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1177/14780771231170455
Daniel Koehler
Large-scale language-image (LLI) models have the potential to open new forms of critical practice through architectural research. Their success enables designers to research within discourses that are profoundly connected to the built environment but did not previously have the resources to engage in spatial research. Although LLI models do not generate coherent building ensembles, they offer an esthetic experience of an AI infused design practice. This paper contextualizes diffusion models architecturally. Through a comparison of approaches to diffusion models in architecture, this paper outlines data-centric methods that allow architects to design critically using computation. The design of text-driven latent spaces extends the histories of typological design to synthetic environments including non-building data into an architectural space. More than synthesizing quantic ratios in various arrangements, the architect contributes by assessing new categorical differences into generated work. The architects’ creativity can elevate LLI models with a synthetic architecture, nonexistent in the data sets the models learned from.
{"title":"More than anything: Advocating for synthetic architectures within large-scale language-image models","authors":"Daniel Koehler","doi":"10.1177/14780771231170455","DOIUrl":"https://doi.org/10.1177/14780771231170455","url":null,"abstract":"Large-scale language-image (LLI) models have the potential to open new forms of critical practice through architectural research. Their success enables designers to research within discourses that are profoundly connected to the built environment but did not previously have the resources to engage in spatial research. Although LLI models do not generate coherent building ensembles, they offer an esthetic experience of an AI infused design practice. This paper contextualizes diffusion models architecturally. Through a comparison of approaches to diffusion models in architecture, this paper outlines data-centric methods that allow architects to design critically using computation. The design of text-driven latent spaces extends the histories of typological design to synthetic environments including non-building data into an architectural space. More than synthesizing quantic ratios in various arrangements, the architect contributes by assessing new categorical differences into generated work. The architects’ creativity can elevate LLI models with a synthetic architecture, nonexistent in the data sets the models learned from.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"242 - 255"},"PeriodicalIF":1.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45748049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1177/14780771231168230
K. Steinfeld
The emergence of text-to-image generative models (e.g., Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this phenomenon, this text offers a socio-technical history of text-to-image generative systems. Three moments in time, or “scenes,” are presented here: the first at the advent of AI in the middle of the last century; the second at the “reawakening” of a specific approach to machine learning at the turn of this century; the third that documents a rapid sequence of innovations, dubbed “clever little tricks,” that occurred across just 18 months. This final scene is the crux, and represents the first formal documentation of the recent history of a specific set of informal innovations. These innovations were produced by non-affiliated researchers and communities of creative contributors, and directly led to the technologies that so compellingly captured the architectural imagination in the summer of 2022. Across these scenes, we examine the technologies, application domains, infrastructures, social contexts, and practices that drive technical research and shape creative practice in this space.
{"title":"Clever little tricks: A socio-technical history of text-to-image generative models","authors":"K. Steinfeld","doi":"10.1177/14780771231168230","DOIUrl":"https://doi.org/10.1177/14780771231168230","url":null,"abstract":"The emergence of text-to-image generative models (e.g., Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this phenomenon, this text offers a socio-technical history of text-to-image generative systems. Three moments in time, or “scenes,” are presented here: the first at the advent of AI in the middle of the last century; the second at the “reawakening” of a specific approach to machine learning at the turn of this century; the third that documents a rapid sequence of innovations, dubbed “clever little tricks,” that occurred across just 18 months. This final scene is the crux, and represents the first formal documentation of the recent history of a specific set of informal innovations. These innovations were produced by non-affiliated researchers and communities of creative contributors, and directly led to the technologies that so compellingly captured the architectural imagination in the summer of 2022. Across these scenes, we examine the technologies, application domains, infrastructures, social contexts, and practices that drive technical research and shape creative practice in this space.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"211 - 241"},"PeriodicalIF":1.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49218025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-29DOI: 10.1177/14780771231180258
Hang Xu, Tsung-Hsien Wang
Urban building energy modelling (UBEM) is a prevalent research method to examine the multi-scale building to urban renovation in mitigating global energy-related carbon emissions. However, only a few studies delineate a complete workflow from generation to application using UBEM. In particular, to facilitate the designing of sustainable built environments, existing research needs to emphasize the integration of multi-scale energy performance evaluation within the design development process for architects and urban planners. The key challenges lie in the need for integrated datasets and incompatibility between software tools required for designing, modelling, and evaluation. This paper presents a comprehensive methodological framework to investigate applicable urban decarbonization strategies. A case study of Sheffield in the UK demonstrates the development of an automated and standardized computational workflow. This data-driven workflow aims to evaluate energy demand and supply scenarios at an urban scale to access the potential of decarbonizing built environments. The workflow is designed to be adaptable to various scales of urban regions, given a suitable geographic information system (GIS) dataset.
{"title":"A generative computational workflow to develop actionable renovation strategies for renewable built environments: A case study of Sheffield","authors":"Hang Xu, Tsung-Hsien Wang","doi":"10.1177/14780771231180258","DOIUrl":"https://doi.org/10.1177/14780771231180258","url":null,"abstract":"Urban building energy modelling (UBEM) is a prevalent research method to examine the multi-scale building to urban renovation in mitigating global energy-related carbon emissions. However, only a few studies delineate a complete workflow from generation to application using UBEM. In particular, to facilitate the designing of sustainable built environments, existing research needs to emphasize the integration of multi-scale energy performance evaluation within the design development process for architects and urban planners. The key challenges lie in the need for integrated datasets and incompatibility between software tools required for designing, modelling, and evaluation. This paper presents a comprehensive methodological framework to investigate applicable urban decarbonization strategies. A case study of Sheffield in the UK demonstrates the development of an automated and standardized computational workflow. This data-driven workflow aims to evaluate energy demand and supply scenarios at an urban scale to access the potential of decarbonizing built environments. The workflow is designed to be adaptable to various scales of urban regions, given a suitable geographic information system (GIS) dataset.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"516 - 535"},"PeriodicalIF":1.7,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49167078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-29DOI: 10.1177/14780771231177506
Kim Ricafort, Mohammed Makki
The superblock of Kampung Melayu in Jakarta, Indonesia, is an urban morphology amalgamated by the environmental and infrastructure challenges raised by Jakarta’s inevitable urban growth. Low-income settlements like Kampung Melayu are particularly susceptible as a result of the city’s rapid and uncontrolled urban sprawl, erratic tropical weather, increasing sea levels and unparalleled environmental stresses. The proposed research utilises a multi-objective evolutionary algorithm (MOEA) for an in-depth investigation of the many relationships within the urban fabric to address these difficulties. The experiments demonstrate an alternate urban strategy for a flood-resilient Kampung that investigates the selection techniques coupled with the use of population-based algorithms. While preserving the irregularity that has been ingrained in the history of the urban form, the results address the environmental and demographic stresses of the urban village.
{"title":"Urban flood resilience in Kampung Melayu: A multi-objective evolutionary approach","authors":"Kim Ricafort, Mohammed Makki","doi":"10.1177/14780771231177506","DOIUrl":"https://doi.org/10.1177/14780771231177506","url":null,"abstract":"The superblock of Kampung Melayu in Jakarta, Indonesia, is an urban morphology amalgamated by the environmental and infrastructure challenges raised by Jakarta’s inevitable urban growth. Low-income settlements like Kampung Melayu are particularly susceptible as a result of the city’s rapid and uncontrolled urban sprawl, erratic tropical weather, increasing sea levels and unparalleled environmental stresses. The proposed research utilises a multi-objective evolutionary algorithm (MOEA) for an in-depth investigation of the many relationships within the urban fabric to address these difficulties. The experiments demonstrate an alternate urban strategy for a flood-resilient Kampung that investigates the selection techniques coupled with the use of population-based algorithms. While preserving the irregularity that has been ingrained in the history of the urban form, the results address the environmental and demographic stresses of the urban village.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"478 - 497"},"PeriodicalIF":1.7,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43385415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-26DOI: 10.1177/14780771231177508
F. P. Ortner, J. Tay
Embedding circular economy (CE) principles in early design requires iterative evaluation across multiple lifecycle phases, with trade-offs between objectives complicating the identification of best solutions. This paper puts forward methods to automatically discover diverse, yet well-performing solution types within complex multi-objective CE design optimisation models. Working with a parametric model derived from a furniture design for CE case study, a comparison is made between weighted-sum single objective optimisation and multi-objective optimisation augmented with clustered solution types targeted by the reference point-based NSGA-II optimisation algorithm. Efficiency of optimisation, quality of results and distinctiveness of solution types presented by each method is compared in an effort to understand which will best assist designers to manage complexity in CE design. The generalisability of the presented methods to larger scale CE design problems is discussed and future areas of work on computational design for CE are extrapolated from the presented results.
{"title":"Exploring a circular economy solution space A comparative study to develop automated optimisation workflows supported by machine learning for circular design problems","authors":"F. P. Ortner, J. Tay","doi":"10.1177/14780771231177508","DOIUrl":"https://doi.org/10.1177/14780771231177508","url":null,"abstract":"Embedding circular economy (CE) principles in early design requires iterative evaluation across multiple lifecycle phases, with trade-offs between objectives complicating the identification of best solutions. This paper puts forward methods to automatically discover diverse, yet well-performing solution types within complex multi-objective CE design optimisation models. Working with a parametric model derived from a furniture design for CE case study, a comparison is made between weighted-sum single objective optimisation and multi-objective optimisation augmented with clustered solution types targeted by the reference point-based NSGA-II optimisation algorithm. Efficiency of optimisation, quality of results and distinctiveness of solution types presented by each method is compared in an effort to understand which will best assist designers to manage complexity in CE design. The generalisability of the presented methods to larger scale CE design problems is discussed and future areas of work on computational design for CE are extrapolated from the presented results.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"404 - 420"},"PeriodicalIF":1.7,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46010296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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