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	ascaad2010_279
id	ascaad2010_279
authors	Celani, G.; L. Medrano; J. Spinelli
year	2010
title	Unicamp 2030: A plan for increasing a university campus in a sustainable way and an example of integrated use of CAAD simulation and computational design strategies
source	CAAD - Cities - Sustainability [5th International Conference Proceedings of the Arab Society for Computer Aided Architectural Design (ASCAAD 2010 / ISBN 978-1-907349-02-7], Fez (Morocco), 19-21 October 2010, pp. 279-286
summary	The state university of Campinas, Unicamp, is a public university in upstate São Paulo, Brazil, ranked the second best in the country. It was founded in 1966, and its main campus started to be built in 1967, in the suburbs of Campinas, nowadays a two-million people city. The area of the campus is almost 3 million square meters (300 hectares), with a total built area of 522.000 m2 and a population of 40 thousand people - 30 thousand students, 2 thousand faculty members and almost 8 thousand staff members. The campus’ gross population density is 133 people per hectare. Less than 6% of the total campus area is presently occupied. The design of Unicamp's campus is based on concepts that were typical of the modern movement, with reminiscences of corbusian urbanism, in which preference is given to cars and buildings are spread apart on the territory, with little concern to the circulation of pedestrians. The standard building type that has been built on campus since the 1970's is based on non-recyclable materials, and has a poor thermal performance. Unicamp is expected to double its number of students by the year 2030. The campus density is thus expected to grow from 600 people per hectare to almost 1,000 people per hectare. The need to construct new buildings is seen as an opportunity to correct certain characteristics of the campus that are now seen as mistakes, according to sustainability principles. This paper describes a set of proposals targeting the increase of the campus' density in a sustainable way. The plan also aims at increasing the quality of life on campus and diminishing its impact on the environment. The main targets are: - Reducing the average temperature by 2oC; - Reducing the average displacement time by 15 minutes; - Increasing the campus' density by 100%; - Reducing the CO2 emissions by 50%. // In order to achieve these goals, the following actions have been proposed: Developing a new standard building for the university, incorporating sustainability issues, such as the use of renewable and/or recyclable materials, the installation of rainwater storage tanks, the use of natural ventilation for cooling, sitting the buildings in such a way to decrease thermal gain, and other issues that are required for sustainable buildings' international certifications. To assess the performance of the new standard building, different simulation software were used, such as CFD for checking ventilation, light simulation software to assess energy consumption, and so on. 1. Filling up under-utilized urban areas in the campus with new buildings, to make better use of unused infrastructure and decrease the distance between buildings. 2. Proposing new bicycle paths in and outside campus, and proposing changes in the existing bicycle path to improve its safety. 3. Developing a landscape design plan that aims at creating shaded pedestrian and bicycle passageways.
series	ASCAAD
type	normal paper
email
last changed	2021/07/16 10:37

_id	e9f3
authors	Greenwald-Katz, G. and Katz, Lou
year	1970
title	Capturing the Third Dimension. An Interactive Graphics Program For Computer Aided Architectural Design
source	Computer Decisions 2: 50-53
summary	Using the Adage-50 (with 16k memory) the authors created a interactive, real-time display that allowed for the graphic modeling of building shapes while at the same time giving a readout of critical design parameters. This enabled the designer, at an early stage, to create a building shape that would fit within the design requirements of square footage, building footprint and height limitations.
series	other
email
last changed	2003/03/28 09:19

_id	3eb3
authors	Maver, T.W.
year	1970
title	Appraisal in the Building Design Process
source	Emerging Methods in Environmental Design and Planning (Ed: G Moore) MIT Press, 195-202
series	other
email
last changed	2003/06/02 15:00

_id	e1a1
authors	Rodriguez, G.
year	1996
title	REAL SCALE MODEL VS. COMPUTER GENERATED MODEL
source	Full-Scale Modeling in the Age of Virtual Reality [6th EFA-Conference Proceedings]
summary	Advances in electronic design and communication are already reshaping the way architecture is done. The development of more sophisticated and user-friendly Computer Aided Design (CAD) software and of cheaper and more powerful hardware is making computers more and more accessible to architects, planners and designers. These professionals are not only using them as a drafting tool but also as a instrument for visualization. Designers are "building" digital models of their designs and producing photo-like renderings of spaces that do not exist in the dimensional world. The problem resides in how realistic these Computer Generated Models (CGM) are. Moss & Banks (1958) considered realism “the capacity to reproduce as exactly as possible the object of study without actually using it”. He considers that realism depends on: 1)The number of elements that are reproduced; 2) The quality of those elements; 3) The similarity of replication and 4) Replication of the situation. CGM respond well to these considerations, they can be very realistic. But, are they capable of reproducing the same impressions on people as a real space? Research has debated about the problems of the mode of representation and its influence on the judgement which is made. Wools (1970), Lau (1970) and Canter, Benyon & West (1973) have demonstrated that the perception of a space is influenced by the mode of presentation. CGM are two-dimensional representations of three-dimensional space. Canter (1973) considers the three-dimensionality of the stimuli as crucial for its perception. So, can a CGM afford as much as a three-dimensional model? The “Laboratorio de Experimentacion Espacial” (LEE) has been concerned with the problem of reality of the models used by architects. We have studied the degree in which models can be used as reliable and representative of real situations analyzing the Ecological Validity of several of them, specially the Real-Scale Model (Abadi & Cavallin, 1994). This kind of model has been found to be ecologically valid to represent real space. This research has two objectives: 1) to study the Ecological Validity of a Computer Generated Model; and 2) compare it with the Ecological Validity of a Real Scale Model in representing a real space.
keywords	Model Simulation, Real Environments
series	other
type	normal paper
more	http://info.tuwien.ac.at/efa/
last changed	2004/05/04 14:42

_id	cf2011_p018
id	cf2011_p018
authors	Sokmenoglu, Ahu; Cagdas Gulen, Sariyildiz Sevil
year	2011
title	A Multi-dimensional Exploration of Urban Attributes by Data Mining
source	Computer Aided Architectural Design Futures 2011 [Proceedings of the 14th International Conference on Computer Aided Architectural Design Futures / ISBN 9782874561429] Liege (Belgium) 4-8 July 2011, pp. 333-350.
summary	The paper which is proposed here will introduce an ongoing research project aiming to research data mining as a methodology of knowledge discovery in urban feature analysis. To address the increasing multi-dimensional and relational complexity of urban environments requires a multidisciplinary approach to urban analysis. This research is an attempt to establish a link between knowledge discovery methodologies and automated urban feature analysis. Therefore, in the scope of this research we apply data mining methodologies for urban analysis. Data mining is defined as to extract important patterns and trends from raw data (Witten and Frank, 2005). When applied to discover relationships between urban attributes, data mining can constitute a methodology for the analysis of multi-dimensional relational complexity of urban environments (Gil, Montenegro, Beirao and Duarte, 2009) The theoretical motivation of the research is derived by the lack of explanatory urban knowledge which is an issue since 1970‚Äôs in the area of urban research. This situation is mostly associated with deductive methods of analysis. The analysis of urban system from the perspective of few interrelated factors, without considering the multi-dimensionality of the system in a deductive fashion was not been explanatory enough. (Jacobs, 1961, Lefebvre, 1970 Harvey, 1973) To address the multi-dimensional and relational complexity of urban environments requires the consideration of diverse spatial, social, economic, cultural, morphological, environmental, political etc. features of urban entities. The main claim is that, in urban analysis, there is a need to advance from traditional one dimensional (Marshall, 2004) description and classification of urban forms (e.g. Land-use maps, Density maps) to the consideration of the simultaneous multi-dimensionality of urban systems. For this purpose, this research proposes a methodology consisting of the application of data mining as a knowledge discovery method into a GIS based conceptual urban database built out of official real data of Beyoglu. Generally, the proposed methodology is a framework for representing and analyzing urban entities represented as objects with properties (attributes). It concerns the formulation of an urban entity‚Äôs database based on both available and non-available (constructed from available data) data, and then data mining of spatial and non-spatial attributes of the urban entities. Location or position is the primary reference basis for the data that is describing urban entities. Urban entities are; building floors, buildings, building blocks, streets, geographically defined districts and neighborhoods etc. Urban attributes are district properties of locations (such as land-use, land value, slope, view and so forth) that change from one location to another. Every basic urban entity is unique in terms of its attributes. All the available qualitative and quantitative attributes that is relavant (in the mind of the analyst) and appropriate for encoding, can be coded inside the computer representation of the basic urban entity. Our methodology is applied by using the real and official, the most complex, complete and up-to-dataset of Beyoglu (a historical neighborhood of Istanbul) that is provided by the Istanbul Metropolitan Municipality (IBB). Basically, in our research, data mining in the context of urban data is introduced as a computer based, data-driven, context-specific approach for supporting analysis of urban systems without relying on any existing theories. Data mining in the context of urban data; ‚Ä¢ Can help in the design process by providing site-specific insight through deeper understanding of urban data. ‚Ä¢ Can produce results that can assist architects and urban planners at design, policy and strategy levels. ‚Ä¢ Can constitute a robust scientific base for rule definition in urban simulation applications such as urban growth prediction systems, land-use simulation models etc. In the paper, firstly we will present the framework of our research with an emphasis on its theoretical background. Afterwards we will introduce our methodology in detail and finally we will present some of important results of data mining analysis processed in Rapid Miner open-source software. Specifically, our research define a general framework for knowledge discovery in urban feature analysis and enable the usage of GIS and data mining as complementary applications in urban feature analysis. Acknowledgments I would like to thank to Nuffic, the Netherlands Organization for International Cooperation in Higher Education, for funding of this research. I would like to thank Ceyhun Burak Akgul for his support in Data Mining and to H. Serdar Kaya for his support in GIS.
keywords	urban feature analysis, data mining, urban database, urban complexity, GIS
series	CAAD Futures
email
last changed	2012/02/11 19:21

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