Predicció de coeficients de pressió mitjançant xarxes neuronals artificials
This work presents an artificial neural network based interpolation model. Using existing information from pressure distributions over low-rise buildings databases, the model is able to predict, accurately, pressure profiles over any roof with the desired physical characteristics (over the existing...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2010 |
| País: | España |
| Institución: | Universitat Rovira i virgili (URV) |
| Repositorio: | Repositori Institucional de la Universitat Rovira i Virgili |
| OAI Identifier: | oai:urv.cat:TDX:368 |
| Acceso en línea: | https://hdl.handle.net/20.500.11797/TDX368 http://hdl.handle.net/10803/8586 |
| Access Level: | acceso abierto |
| Palabra clave: | 66 - Enginyeria, tecnologia i indústria química. Metal·lúrgia 624 - Enginyeria civil i de la construcció en general 004 - Informàtica |
| Sumario: | This work presents an artificial neural network based interpolation model. Using existing information from pressure distributions over low-rise buildings databases, the model is able to predict, accurately, pressure profiles over any roof with the desired physical characteristics (over the existing data domain). With the pressure interpolated data, wind loads over the roofs can be calculated, assisting its design process. This methodology drives to a cheaper design process since it replaces the experimentation, with scaled buildings, in wind tunnels. During the developed work methodology it has been demonstrated that the pressure field over building surfaces contains, in itself, all of the information necessary to predict the (surface) pressure fluctuations at all locations and times. |
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