Use of artificial neural networks to predict 3-D elastic settlement of foundations on soils with inclined bedrock
Autor: | Vicente Brotons, Esteban Díaz Castañeda, Roberto Tomás |
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Přispěvatelé: | Universidad de Alicante. Departamento de Ingeniería Civil, Ingeniería del Terreno y sus Estructuras (InTerEs) |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
geography
Settlement geography.geographical_feature_category Finite-element modelling Settlement (structural) Bedrock Artificial neural networks (ANNs) 0211 other engineering and technologies Foundation (engineering) 02 engineering and technology Geotechnical Engineering and Engineering Geology Elasticity Ingeniería del Terreno Work (electrical) State agency Regional development Political science 021105 building & construction Regional science Christian ministry Foundation Soil/structure interaction Mecánica de Medios Continuos y Teoría de Estructuras 021101 geological & geomatics engineering Civil and Structural Engineering |
Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
Popis: | The application of the theory of elasticity for the calculation of foundation settlements has yielded equations that are well-established and consolidated in geotechnical standards and/or that are recommended for use. These equations are corrected by an influence factor in order to increase their precision and to encompass the existing complex geotechnical casuistry. The study presented herein utilizes neural networks to improve the determination of the influence factor (Iα), which considers the effect of a finite elastic half-space limited by the inclined bedrock under a foundation. The results obtained through the utilization of artificial neural networks (ANNs) demonstrate a notable improvement in the predicted values for the influence factor in comparison with those of existing analytical equations. The work was partially supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER), under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P, and by the Spanish Ministry of Education, Culture and Sport, under project PRX17/00439. |
Databáze: | OpenAIRE |
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