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	acadia20_208
id	acadia20_208
authors	Zheng, Hao; Wang, Xinyu; Qi, Zehua; Sun, Shixuan; Akbarzadeh, Masoud
year	2020
title	Generating and Optimizing a Funicular Arch Floor Structure
doi	https://doi.org/10.52842/conf.acadia.2020.2.208
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 208-217.
summary	In this paper, we propose a geometry-based generative design method to generate and optimize a floor structure with funicular building members. This method challenges the antiquated column system, which has been used for more than a century. By inputting the floor plan with the positions of columns, designers can generate a variety of funicular supporting structures, expanding the choice of floor structure designs beyond simply columns and beams and encouraging the creation of architectural spaces with more diverse design elements. We further apply machine learning techniques (artificial neural networks) to evaluate and optimize the structural performance and constructability of the funicular structure, thus finding the optimal solutions within the almost infinite solution space. To achieve this, a machine learning model is trained and used as a fast evaluator to help the evolutionary algorithm find the optimal designs. This interdisciplinary method combines computer science and structural design, providing flexible design choices for generating floor structures.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2022_385
id	ecaade2022_385
authors	Zheng, Shuyuan, Velho, Avantika, Ross, Kate, Chen, Hongshun, Li, Ling and Zolotovsky, Katia
year	2022
title	Self-Cleaning Surface Architectures from Chitin Biomaterials - Computational and experimental methodology
doi	https://doi.org/10.52842/conf.ecaade.2022.1.091
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 91–100
summary	The current pandemic and the climate crisis urge people to rethink their relationships to the natural and urban environments. In this research we turned to nature for inspiration to find new ways to keep human environments clean and healthy. This paper presents a computational and experimental methodology to design self-cleaning architectural surfaces from chitin biomaterial modeled after butterfly wings. We fabricate surface architectures using parametric modeling, 3d printing, and molding of chitin biomaterial, and assess their performance using mechanical testing, experimental and computational simulations. The goal is to provide an alternative to hydrophobic fossil fuel-based plastics using surface morphologies of biomaterials to achieve structural rigidity and self- cleaning properties in architectural surfaces.
keywords	Material-based Design, Parametric Design, Digital Fabrication, Biomaterials, Computational Simulation, Hydrophobicity, Biomimicry
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ddss2006-pb-169
id	DDSS2006-PB-169
authors	Zhenjiang Shen, Mitsuhiko Kawakami, and Ping Chen
year	2006
title	Study on a Decision Support System for Large-Scale Shopping Centre Location Planning Using a Multi-Agent System
source	Van Leeuwen, J.P. and H.J.P. Timmermans (eds.) 2006, Progress in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven: Eindhoven University of Technology, ISBN-10: 90-386-1756-9, ISBN-13: 978-90-386-1756-5, p. 169-184
summary	Multi-agent system as a bottom-up approach has been shown powerful in better understanding processes of urban development and growth. Most of them are approaching from economic theory and social behaviours but urban planning. This paper proposes an alternative approach to urban simulation that combines urban planning with agents' behaviour in multi-agent modelling thus to make scenarios analysis more reasonable particularly for decision based on urban land use plan. This paper discusses the approach as a computer simulative solution of a new large-scale shopping centre location for most regional cities in Japan where commercial heart of inner city is facing decline. We postulate that policy decision makers can get better understanding of the policies' impact on inner city commercial environment under different scenarios through computer experimentation.
keywords	Inner city decline, Planning regulations, Planning policy, Agent
series	DDSS
last changed	2006/08/29 12:55

_id	cdrf2022_223
id	cdrf2022_223
authors	Zhiyi Dou, Waishan Qiu, Wenjing Li, Dan Luo
year	2022
title	Evaluation Process of Urban Spatial Quality and Utility Trade-Off for Post-COVID Working Preferences
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_19
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The formation of cities, and the relocation of workers to densely populated areas reflect a spatial equilibrium, in which the higher real consumption levels of urban areas are offset by lower non-monetary amenities [1]. However, as the society progress toward a post-COVID stage, the prevailing decentralized delivery systems and location-based services, the growing trend of working from home, with citizens’ shifting preference of de-appreciating densities and gathering, have not only changed the possible spatial distribution of opportunities, resources, consumption and amenities, but also transformed people’s preference regarding desirable urban spatial qualities, value of amenities, and working opportunities [2, 3]. This research presents a systematic method to evaluate the perceived trade-off between urban spatial qualities and urban utilities such as amenities, transportation, and monetary opportunities by urban residence in the post-COVID society. The outcome of the research will become a valid tool to drive and evaluate urban design strategies based on the potential self-organization of work-life patterns and social profiles in the designated neighbourhood. To evaluate the subjective perception of the urban residence, the study started with a comparative survey by asking residence to compare two randomly selected urban contexts in a data base of 398 contexts sampled across Hong Kong and state their living preference under the presumption of following scenarios: 1. working from home; 2. working in city centre offices. Core information influencing the spatial equilibrium are provided in the comparable urban context such as street views, housing price, housing space, travel time to city centre, adjacency to public transport and amenities, etc. Each context is given a preference score calculated with Microsoft TrueSkill Bayesian ranking algorithm [4] based on the comparison survey of two scenarios. The 398 contexts are further analysed via GIS and image processing, to be deconstructed into numerical values describing main features for each of the context that influence urban design strategies such as composition of spatial features, amenity allocation, adjacency to city centre and public transportations. Machine learning models are trained with the numerical values of urban features as input and two preference scores for the two working scenarios as the output. The correlation heat maps are used to identify main urban features and its p-value that influence residence’s preference under two working scenarios in post–COVID era. The same model could also be applied to inform the direction of urban design strategies to construct a sustainable community for each type of working population and validate the design strategies via predicting its competitiveness in attracting residence and developing target industries.
series	cdrf
email
last changed	2024/05/29 14:02

_id	cdrf2022_274
id	cdrf2022_274
authors	Zhiyong Dong and Jinru Lin
year	2022
title	Nolli Map: Interpretation of Urban Morphology Based on Machine Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_24
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	Nolli map is the earliest diagram tool to simplify and quantify urban form, which most intuitively reflects the spatial layout of tangible elements in the city. The urban morphology contains its inherent evolutionary laws. Exploring the inner rules of cities is helpful for people to conduct urban research and design. Unlike the traditional research methods of urban morphology, the neural network algorithm provides us with new ideas for understanding urban morphology. In this experiment, we label 136 European cities samples in the rules of Nolli map as a training set for machine learning. We use Generative Adversarial Networks (GAN) for multiple mapping experiments. The generated images present recognizable and plausible images of the urban fabric. The results show that the machine can learn the inherent laws of complex urban fabrics, which expands a new applied method for the study of urban morphology.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2014_014
id	caadria2014_014
authors	Zhong, Chen; Stefan Müller Arisona and Gerhard Schmitt
year	2014
title	A Visual Analytics Framework for Large Transportation Datasets
doi	https://doi.org/10.52842/conf.caadria.2014.223
source	Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of the 19th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2014) / Kyoto 14-16 May 2014, pp. 223–232
summary	The advancement of sensor technologies makes it possible to collect large amounts of dynamic urban data. On the other hand, how to store, process, and analyze collected urban data to make them useful becomes a new challenge. To address this issue, this paper proposes a visual analytics framework, which is applied to transportation data to manage and extract information for urban studies. More specifically, the proposed framework has three components: (1) a geographic information system (GIS) based pipeline providing basic data processing functions; (2) a spatial network analysis that is integrated into the pipeline for extracting spatial structure of urban movement; (3) interactive operations allowing the user to explore and view the output data sets at different levels of details. Taking Singapore as a case study area, we use a sample data set from the automatic smart card fare collection system as an input to our prototype tool. The result shows the feasibility of proposed framework and analysis method. To summarize, our work shows the potential of geospatial based visual analytics tools in using ‘big’ data for urban analysis.
keywords	GIS; visual analytics; transportation data; flow map; spatial network analysis
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	esaulov02_paper_eaea2007
id	esaulov02_paper_eaea2007
authors	Esaulov, G.V.
year	2008
title	Videomodeling in Architecture. Introduction into Concerned Problems
source	Proceedings of the 8th European Architectural Endoscopy Association Conference
summary	Since the very 1st year Russian Academy of Architecture and building sciences that was established in 1992 by the Presidents’ decree as the higher scientific and creative organization in the country has always paid much attention to supporting and developing fundamental investigations in architecture, town-planning, building sciences, professional education and creative practice. Study of the birth process of the architectural idea and searching for tools assisting the architect’s creative activity and opportunities for adequate transfer of architectural image to potential consumer – relate to the number of problems which constantly bother the architectural community. Before turning to the conference, let us set certain conditions that have a significant impact on the development of architectural and construction activity in modern Russia.
series	EAEA
more	http://info.tuwien.ac.at/eaea
last changed	2008/04/29 20:46

_id	caadria2024_15
id	caadria2024_15
authors	Zhong, Chuwen, Shi, Yi'an, Cheung, Lok Hang and Wang, Likai
year	2024
title	AI-Enhanced Performative Building Design Optimization and Exploration: A Design Framework Combining Computational Design Optimization and Generative AI
doi	https://doi.org/10.52842/conf.caadria.2024.1.059
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 59–68
summary	When using computational optimization for early-stage architectural design, most optimization applications often produce abstract design geometries with minimal details and information in relation to architectural design, such as design languages and styles. Meanwhile, Generative AI (GAI), including Natural Language Processing (NLP) and Computer Vision (CV), hold great potential to assist designers in efficiently exploring architectural design references, but the generated images are often blamed for having limited relevance to the context and building performance. To address the limitation in computational optimization and leverage the capability of GAI in design exploration, this study proposes a design framework that incorporates Performative/Performance-based Design Optimization (PDO) and GAI programs for early-stage architectural design. A case study is demonstrated by designing a high-rise mixed-use residential tower in Hong Kong. The result shows that the PDO-GAI approach can help designers efficiently proceed with both diverging exploration and converging development.
keywords	Building Performance, Computational Optimization, Design Exploration, Generative AI, Architectural Style, Façade Language
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2020_115
id	caadria2020_115
authors	Zhong, Jia Ding, Chao, Sara, Ming Chun and Tsou, Jin Yeu
year	2020
title	Establishing a Prediction Model for Better Decision Making Regarding Urban Green Planning in a High-density Urban Context
doi	https://doi.org/10.52842/conf.caadria.2020.1.517
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 517-526
summary	This paper presents a prototype of a prediction model. The model helps to improve decision making regarding urban green patch planning. This process is achieved by the model predicting the response of thermal comfort conditions in an urban green patch to different planning decisions. This process is demonstrated via an investigation of variations in urban density. The model features a surface temperature mapping approach, which assigns surface temperature data acquired through field-measurement to solid surfaces in CFD simulations based on the shading state. Besides, trees are simulated in a systematic way, and the model combines CFD simulations with PET values, the processes of which are also demonstrated in this paper.
keywords	Urban Green Planning; Decision Making; Thermal Comfort; CFD
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2022_153
id	ecaade2022_153
authors	Zhong, Ximing, Fricker, Pia, Yu, Fujia, Tan, Chuheng and Pan, Yuzhe
year	2022
title	A Discussion on an Urban Layout Workflow Utilizing Generative Adversarial Network (GAN) - With a focus on automatized labeling and dataset acquisition
doi	https://doi.org/10.52842/conf.ecaade.2022.2.583
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 583–592
summary	Deep Learning (DL) has recently gained widespread attention in the automation of urban layout processes. This study proposes a rule-based and Generative Adversarial Network (GAN) workflow to automatically select and label urban datasets to train customized GAN models for the generation of urban layout proposals. The developed workflow automatically collects and labels urban typology samples from open-source maps. Furthermore, it controls the results of the GAN process with labels and provides real-time urban layout suggestions based on a co-design process. The conducted case study shows that the average value of the GAN results, trained from an automatically generated dataset, meets the site's requirements. The developed co-design strategy allows the architect to control the GAN process and perform iterations on urban layouts. The research addresses the research gap in GAN applications in the field of urban design and planning. Many studies have demonstrated that training the (GAN) model by labeling enables machines to learn urban morphological features and urban layout logic. However, two research gaps remain: (1) The manual filtering of GAN urban sample datasets to fit site-specific design requirements is very time-consuming. (2) Without a suitable data labeling method, it is difficult to manage the GAN process in such a manner to facilitate the meeting of overriding design requirements.
keywords	Deep Learning, Generative Adversarial Network (GAN), Urban Layout Process, Automatic Dataset Construction, Co-design
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2023_166
id	ecaade2023_166
authors	Zhong, Ximing, Koh, Immanuel and Fricker, Pia
year	2023
title	Building-GNN: Exploring a co-design framework for generating controllable 3D building prototypes by graph and recurrent neural networks
doi	https://doi.org/10.52842/conf.ecaade.2023.2.431
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. 431–440
summary	This paper discusses a novel deep learning (DL) framework named Building-GNN, which combines the Graph Neural Network (GNN) and the Recurrent neural network (RNN) to address the challenge of generating a controllable 3D voxel building model. The aim is to enable architects and AI to jointly explore the shape and internal spatial planning of 3D building models, forming a co-design paradigm. While the 3D results of previous DL methods, such as 3DGAN, are challenging to control in detail and meet the constraints and preferences of architects' inputs, Building-GNN allows for reasoning about the complex constraint relationships between each voxel. In Building-GNN, the GNN simulates and learns the graph structure relationship between 3D voxels, and the RNN captures the complex interplaying constraint relationships between voxels. The training set consists of 4000 rule-based generated 3D voxel models labeled with different degrees of masking. The quality of the 3D results is evaluated using metrics such as IoU, Fid, and constraint satisfaction. The results demonstrate that adding RNN enhances the accuracy of 3D model shape and voxel relationship prediction. Building-GNN can perform multi-step rational reasoning to complete the 3D model layout planning in different scenarios based on the architect's precise control and incomplete input.
keywords	Deep learning, Graph Neural Networks, 3D Building Layout, Co-design Recurrent Neural Networks, Multi-step Reasoning
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2024_378
id	caadria2024_378
authors	Zhong, Ximing, Liang, Jiadong, Pia, Fricker and Liu, Shengyu
year	2024
title	A Framework for Fine-Tuning Urban Gans Using Design Decision Data Generated by Architects Through Gans Applications
doi	https://doi.org/10.52842/conf.caadria.2024.2.019
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 19–28
summary	Recent studies have utilized Generative Adversarial Networks (GANs) to learn from existing urban layouts for urban design tasks. We define these GANs as Urban-GAN. However, urban layouts generated by Urban-GAN lack specificity and often require multiple modifications by architects to meet specific design requirements, making the process inefficient and non-customizable. Inspired by the concept of fine-tuning language models, we propose a stacked GAN model framework that fine-tunes Urban-GAN using data generated by architects in solving specific design tasks, forming AD-Urban-GAN. Our results indicate that layouts produced by AD-Urban-GAN more effectively emulate architects' design morphology decisions, enhancing Urban-GAN’s adaptability and efficiency in handling design tasks. Furthermore, AD-Urban-GAN enhances the customizability of Urban-GAN models for specific urban design tasks, generating layouts that accurately understand and meet the requirements of specific tasks. AD-Urban-GAN significantly streamlines the process of generating design prototypes for specific task types, enabling precise quantitative control over urban layout results. This workflow establishes a data acquisition and training loop that strengthens the customizability of existing GANs. The design decision data generated by architects can improve the adaptability and customization of GANs models, facilitating efficient collaborative work between architects and artificial intelligence.
keywords	architect design decisions, Fine-tuning, GANs, Stack-GANs, adaptability, customizability
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	ecaade2024_199
id	ecaade2024_199
authors	Zhong, Ximing; Liang, Jiadong; Li, Yingkai
year	2024
title	Building-Agent: A 3D generation agent framework integrating large language models and graph-based 3D generation model
doi	https://doi.org/10.52842/conf.ecaade.2024.2.291
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 291–300
summary	Large language models (LLMs) possess powerful intelligence, demonstrating unprecedented potential in AI-driven architectural design. While LLMs can understand design tasks, they lack the reasoning capability from language to three-dimensional (3D) architectural models. This paper proposes a novel 3D building generative agent framework, Building-Agent, which combines LLMs' decision-making capabilities with Graph Neural Networks (GNNs) generative abilities. Experiments utilize real design briefs and site constraints to test the building agent's task-processing capabilities. The results demonstrate that the Building-Agent can accurately predict different site layout outcomes and achieve high task completion rates. Furthermore, it enables interactive 3D building layout iteration through multi-step natural language instructions. The Building-Agent's ability to comprehend and reason about 3D spatial layouts, based on the graph representations of 3D models in the modeling engine and the requirements of natural language inputs, showcases its potential to accomplish tasks with initial proficiency. Compared to previous 3D generative models that rely on human decision-making for inputting spatial constraints, the Building-Agent paves the way for AI to comprehend and complete 3D design tasks autonomously, promising a transformative impact on AI and architectural design.
keywords	Building-Agent, Large Language Model, Graph Generation Model, Language Comprehending, 3D Spatial Reasoning, 3D Cognitive Ability
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_261
id	ecaade2024_261
authors	Zhong, Yuqin; Tan, Zhi Sheng; Mavros, Panagiotis; Hölscher, Christoph; Tunçer, Bige
year	2024
title	Estimating Relative Pedestrian Crowd Distribution: A visibility-graph-based analysis workflow for malls during early design stage
doi	https://doi.org/10.52842/conf.ecaade.2024.2.433
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 433–442
summary	This paper introduces a visibility-graph-based workflow for early stages of architectural design, aimed at estimating relative pedestrian crowd distribution in shopping malls. Traditional methods like Agent-Based Modeling (ABM) and Space Syntax analysis face challenges in early design phases due to extensive data or configuration needs and lack of detail respectively. Our approach uses visibility graph as the foundation and generates visit probabilities and Chains of Activities (COAs) from empirical studies, balancing accuracy, accessibility and efficiency. The workflow's integration within designers’ familiar design interface allows for rapid prototyping and assessment of design iterations, making it a practical tool. Validation through a case study in a shopping mall in Singapore demonstrates the workflow's accuracy, with results showing strong similarity to both ABM and observed data, but with significantly less time and resource demands. This workflow offers a novel solution for early-stage design, providing a swift and accurate means to evaluate pedestrian dynamics and optimize design layouts.
keywords	Pedestrian Crowd Analysis, Mixed-use Building, Shopping Mall Design, Visibility Graph Analysis, Agent-based Modelling, Evidence-based Design
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2020_173
id	caadria2020_173
authors	Zhou, JueLun and Tong, ZiYu
year	2020
title	Spatial Characteristics Analysis of Urban Form at the Macroscale Based on Landscape Pattern Indices
doi	https://doi.org/10.52842/conf.caadria.2020.1.823
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 823-832
summary	Spatial characteristics are significant for urban form studies. Because quantifying the urban form at the macroscale is difficult, most of the relevant studies neglect or simplify the diversity of urban built areas. Local climate zone (LCZ) classification systems can transform macro urban form into a theme map composed of different LCZ classes, and such LCZ maps represent an effective urban form mapping technique, especially for built areas. However, this method still fails to provide a quantitative representation of the spatial characteristics. In this paper, the LCZ map is treated as a matrix composed of different patches and landscape pattern indices are applied to quantify the urban form. Taking 8 Chinese cities as case studies, the results show that 4 landscape scale indices and 4 class scale indices can effectively quantify the spatial characteristics of the urban form, including the area, shape, aggregation, and diversity. The quantitative spatial characteristics can provide a reference for urban design and management.
keywords	landscape pattern indices; Local Climate Zones (LCZ); urban form
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	03b7
authors	Zhou, Ming
year	2000
title	Use of Computers in Reconstruction of Ancient Buildings
doi	https://doi.org/10.52842/conf.acadia.2000.223
source	Eternity, Infinity and Virtuality in Architecture [Proceedings of the 22nd Annual Conference of the Association for Computer-Aided Design in Architecture / 1-880250-09-8] Washington D.C. 19-22 October 2000, pp. 223-225
summary	Many cities in China today are in the midst of a profound architectural transformation. Among these rapidly developing cities, most of them are many centuries old, possessing rich historical architecture of distinct local traditions. However, the ancient buildings and the neighborhood are disappearing quickly, because of the wholesale demolition for urban development or many years of neglect. In this paper, the use of computers in reconstruction of ancient buildings is briefly discussed with some case studies. The advanced computer technology provides a powerful tool for the ancient architecture preservation and reproduction. It makes the reconstruction engineering more efficient, true to the original, and low cost.
series	ACADIA
last changed	2022/06/07 07:57

_id	946b
authors	Zhou, Q., Krawczyk, R.J. and Schipporeit, G.
year	2002
title	From CAD to IAD: A Working Model of the Internet-based Engineering Consulting in Architecture
doi	https://doi.org/10.52842/conf.caadria.2002.073
source	CAADRIA 2002 [Proceedings of the 7th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 983-2473-42-X] Cyberjaya (Malaysia) 18–20 April 2002, pp. 073-80
summary	Information technology has become so powerful that what is conventionally called CAD might evolve into iAD (Internet Aided Design) in the near future (Zhou 2000). For Internet applications in the AEC industry, most of the efforts and success have been concentrated on project management and collaboration, while in the design and engineering consulting area, limited progress has been made. During the period of Internet development, the nature of the fragmentation of the AEC industry has not been changed. Based on previous research of surveys of development of Internet applications in the AEC industry (Zhou 2001), and the study of information technology both available today and in the near future, we propose a general abstracted model of an Internet-based consulting system by integrating a variety of disciplines and functions of design and construction processes. This model will cover a range of design phases, such as, information gathering, automatic remote consultation, specific problem solving, and collaboration. Finally, in future follow up research, we will apply the proposed model to steel construction in architectural design, and develop a prototype simulation by selecting one type of structural system.
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2003_a7-3
id	caadria2003_a7-3
authors	Zhou, Q.
year	2003
title	From CAD to iAD - A Prototype Simulation of the Internet-based Steel Construction Consulting for Architects
doi	https://doi.org/10.52842/conf.caadria.2003.919
source	CAADRIA 2003 [Proceedings of the 8th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 974-9584-13-9] Bangkok Thailand 18-20 October 2003, pp. 919-936
summary	Information technology has become so powerful and interactive that what is conventionally called CAD might evolve into iAD (Internet Aided Design). For Internet applications in the AEC (Architecture, Engineering and Construction) industry, most of the efforts and applications have been concentrated on project management and collaboration, while in the area of design and engineering consulting, limited progress has been made. Even with some of this success, contemporary development has not changed the nature of the fragmentation of the AEC industry. Based on previous research surveys (Zhou & Krawczyk 2001) of the development of Internet applications in the AEC industry and the proposal of a conceptual model of Internet-based engineering consulting in architecture, this research will apply these theories and concepts into a specified area of steel construction consulting for architects. The first phase of this research will define the content and scope of steel construction consulting and the potential Internet application. Second, a proposed solid working model is developed covering organizational structure, user network, services provided and technology. In the third phase (as this paper presented), a prototype simulation is used to apply the concepts and methodology in a preliminary design application to demonstrate how this Internet-based consulting model would work.
series	CAADRIA
last changed	2022/06/07 07:57

_id	90b5
authors	Zhou, Qi and Krawczyk, Robert J.
year	2001
title	From CAD to iAD: A survey of Internet application in the AEC industry
doi	https://doi.org/10.52842/conf.acadia.2001.392
source	Reinventing the Discourse - How Digital Tools Help Bridge and Transform Research, Education and Practice in Architecture [Proceedings of the Twenty First Annual Conference of the Association for Computer-Aided Design in Architecture / ISBN 1-880250-10-1] Buffalo (New York) 11-14 October 2001, pp. 392-397
summary	The internet is becoming increasingly more valuable in the field of architectural design that what we conventionally called CAD might soon be changed to iAD (internet Aided Design) (Zhou and Krawczyk 2000). In order to have a clear vision of what iAD will be or could be, we should first examine what is currently available. This research focuses on an investigation of selected web vendors, which are typical and most influential in providing internet related services for the AEC industry. Our purpose for doing this survey is: to understand the progress and development of internet application in the AEC industry, identify the technology used in this area, determine the advantages and deficiencies of current practice and develop a base for future research in proposing a evolutionary model of internet Aided Design for architecture.
keywords	Internet Aided Design, Web-Based Application, On-Line Collaboration
series	ACADIA
email
last changed	2022/06/07 07:57

_id	sigradi2007_af107
id	sigradi2007_af107
authors	Espina, Jane; Francisco Rincón
year	2007
title	Simulation as an urban planification tool: Plaza Baralt [Simulación como herramienta de planificación urbana: Plaza Baralt]
source	SIGraDi 2007 - [Proceedings of the 11th Iberoamerican Congress of Digital Graphics] México D.F. - México 23-25 October 2007, pp. 364-369
summary	Pedestrian simulation tools are usually used to evaluate pedestrians’ evacuation/security in buildings (closed environments). The paper’s objective is to develop a methodology for the application of these tools in urban planning (open spaces), where the pedestrian behavior is more complex. The area studied is Plaza Baralt, in Maracaibo Venezuela, an area enclosed by historic buildings. The proposed scenarios and pedestrian flow simulations – based in cellular automata – followed a locally adapted data recollection and site analysis. As a result the methodology allows the designer to analyze various scenarios, fast and efficiently, identifying problems of areas, flow, land use and user profiles.
keywords	Pedestrian flow simulation; land use; urban planning; scenery
series	SIGRADI
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last changed	2016/03/10 09:51

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