Abstract: The main objective of this study is to present a more accurate method to estimate the energy performance of buildings. This purpose is meant to evaluate the feasibility and relevance of more complex statistical modeling techniques, such as the artificial neural network. The energy performance of buildings may be estimated by their capacity to ensure a healthy and comfortable environment, with low energy consumption during the whole year. The glazed areas have a decisive role in the building energy performance having in view the complex functions that they play in the system. A parametric study, based on another powerful tool - the design of experiment method, which allows us to emphasize the measure in which the geometric and energetic characteristics of glazed areas influence the energy efficiency, estimated by the yearly energy needs, to ensure a comfortable and healthy environment. An artificial neural network - ANN is a computational model inspired by the biological natural neuron.

• Publication Date: 26-Oct-2014
• DOI: 10.15224/978-1-63248-030-9-55
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Abstract: Earthquakes can cause soil deformations if there is no prevention and improvement. Failures occur as a result of intolerable deformations. Stone columns and Jet-Grouting methods are mostly used in Eskisehir, Turkey. In this study, the modeling studies of soil deformations are presented for improvement types and different earthquake effects. Models are performed by using Plaxis 2D software dynamic module and the results are compered. As a result, soil improvement techniques are needed and chosen carefully because some methods can be insufficient to prevent deformations caused by strong earthquakes.

• Publication Date: 26-Oct-2014
• DOI: 10.15224/978-1-63248-030-9-51
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• Downloads: 0