Matching Items (2)
Description
In geographical locations with hot-arid climates, sun control in buildings is one primary problem to solve for the building envelope design. Today's technological advances in building science bring with them the opportunity to design dynamic façade systems for sun radiation control and daylighting. Although dynamic systems can become an attractive visual element, they can be costly and challenging to maintain for building owners. Alternatively, fixed solar-shading systems can be designed to create dynamism in the façade of the building, while providing similar functionalities for sun control. The work presented in this project focuses on the use of a visual scripting editor for modeling software, Grasshopper, to develop a Solar Control Visual Script that evaluates building envelope surfaces with planar and non-uniform rational basis-spline (NURBS) forms and provides projections for fixed sun control systems. The design platform of Grasshopper allows individuals with no experience or prior computer coding education to build up programming-like capabilities; this feature permits users to discover new design possibilities within flexible frames that can contribute to the overall design being pursued, while also having an environmental response. The Solar Control Visual Script provides minimum sizing geometries that achieve shading in openings at a particular date and time of the year. The model for this method of analysis makes use of three components to derive the appropriate values for the projections of shading geometries: typical meteorological year (TMY) data, irradiation isotropic equations and shading profile angles equations for vertical and tilted surfaces. Providing an automatic visual of generated geometries uncovers the opportunity to test several model forms and reiterates the analysis when modifying control parameters. By employing building science as a set of environmental parameters, the design outcome bears a dynamic form that responds to natural force conditions. The optimized results promote an efficient environmental design solution for sun control as an integral alternative into the building envelope.
ContributorsGrijalva, Karla (Author) / Bryan, Harvey J. (Thesis advisor) / Griffiths, Jason (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The human motion is defined as an amalgamation of several physical traits such as bipedal locomotion, posture and manual dexterity, and mental expectation. In addition to the “positive” body form defined by these traits, casting light on the body produces a “negative” of the body: its shadow. We often interchangeably use with silhouettes in the place of shadow to emphasize indifference to interior features. In a manner of speaking, the shadow is an alter ego that imitates the individual.
The principal value of shadow is its non-invasive behaviour of reflecting precisely the actions of the individual it is attached to. Nonetheless we can still think of the body’s shadow not as the body but its alter ego.
Based on this premise, my thesis creates an experiential system that extracts the data related to the contour of your human shape and gives it a texture and life of its own, so as to emulate your movements and postures, and to be your extension. In technical terms, my thesis extracts abstraction from a pre-indexed database that could be generated from an offline data set or in real time to complement these actions of a user in front of a low-cost optical motion capture device like the Microsoft Kinect. This notion could be the system’s interpretation of the action which creates modularized art through the abstraction’s ‘similarity’ to the live action.
Through my research, I have developed a stable system that tackles various connotations associated with shadows and the need to determine the ideal features that contribute to the relevance of the actions performed. The implication of Factor Oracle [3] pattern interpretation is tested with a feature bin of videos. The system also is flexible towards several methods of Nearest Neighbours searches and a machine learning module to derive the same output. The overall purpose is to establish this in real time and provide a constant feedback to the user. This can be expanded to handle larger dynamic data.
In addition to estimating human actions, my thesis best tries to test various Nearest Neighbour search methods in real time depending upon the data stream. This provides a basis to understand varying parameters that complement human activity recognition and feature matching in real time.
The principal value of shadow is its non-invasive behaviour of reflecting precisely the actions of the individual it is attached to. Nonetheless we can still think of the body’s shadow not as the body but its alter ego.
Based on this premise, my thesis creates an experiential system that extracts the data related to the contour of your human shape and gives it a texture and life of its own, so as to emulate your movements and postures, and to be your extension. In technical terms, my thesis extracts abstraction from a pre-indexed database that could be generated from an offline data set or in real time to complement these actions of a user in front of a low-cost optical motion capture device like the Microsoft Kinect. This notion could be the system’s interpretation of the action which creates modularized art through the abstraction’s ‘similarity’ to the live action.
Through my research, I have developed a stable system that tackles various connotations associated with shadows and the need to determine the ideal features that contribute to the relevance of the actions performed. The implication of Factor Oracle [3] pattern interpretation is tested with a feature bin of videos. The system also is flexible towards several methods of Nearest Neighbours searches and a machine learning module to derive the same output. The overall purpose is to establish this in real time and provide a constant feedback to the user. This can be expanded to handle larger dynamic data.
In addition to estimating human actions, my thesis best tries to test various Nearest Neighbour search methods in real time depending upon the data stream. This provides a basis to understand varying parameters that complement human activity recognition and feature matching in real time.
ContributorsSeshasayee, Sudarshan Prashanth (Author) / Sha, Xin Wei (Thesis advisor) / Turaga, Pavan (Thesis advisor) / Tinapple, David A (Committee member) / Arizona State University (Publisher)
Created2016