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Physically-based Visualization Of Residential Building Damage Process In Hurricane

This research provides realistic techniques to visualize the process of damage to residential building caused by hurricane force winds. Three methods are implemented to make the visualization useful for educating the public about mitigation measures for their homes. First, the underline physics uses Quick Collision Response Calculation. This is an iterative method, which can tune the accuracy and the performance to calculate collision response between building components. Secondly, the damage process is designed as a Time-scalable Process. By attaching a damage time tag for each building component, the visualization process is treated as a geometry animation allowing users to navigate in the visualization. The detached building components move in response to the wind force that is calculated using qualitative rather than quantitative techniques. The results are acceptable for instructional systems but not for engineering analysis. Quick Damage Prediction is achieved by using a database query instead of using a Monte-Carlo simulation. The database is based on HAZUSĀ® engineering analysis data which gives it validity. A reasoning mechanism based on the definition of the overall building damage in HAZUSĀ® is used to determine the damage state of selected building components including roof cover, roof sheathing, wall, openings and roof-wall connections. Exposure settings of environmental aspects of the simulated environment, such as ocean, trees, cloud and rain are integrated into a scene-graph based graphics engine. Based on the graphics engine and the physics engine, a procedural modeling method is used to efficiently render residential buildings. The resulting program, Hurricane!, is an instructional program for public education useful in schools and museum exhibits.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4241
Date01 January 2007
CreatorsLiao, Dezhi
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceElectronic Theses and Dissertations

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