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Using Artificial Neural Networks to Predict the Restraint in Concrete Culverts at Early Age
Estimation of restraint is very important for accurate prediction of the risk of concrete cracking at early age. This study predicts the restraint in 324 walls and 972 roofs of concrete culverts. A parametric study included the thickness and width of the roofs, thickness and height of the walls, thickness and width of the slab and length of the structures. Each parameter increased or decreased the restraint in the walls and the roofs. The calculation of the restraint was done elastically by the finite element (FE) method. The results were used by an artificial neural network (ANN) tool, where, first, an influential percentage was investigated as input parameter on the restraint prediction. Equations were derived by the ANN model to calculate the restraint in the walls and the roofs. It was then used in a spreadsheet to calculate the restraint and compare the result with the result from the FE calculations, which showed a good agreement between the ANN model and the FE calculations
Using Artificial Neural Networks to Predict the Restraint in Concrete Culverts at Early Age
Estimation of restraint is very important for accurate prediction of the risk of concrete cracking at early age. This study predicts the restraint in 324 walls and 972 roofs of concrete culverts. A parametric study included the thickness and width of the roofs, thickness and height of the walls, thickness and width of the slab and length of the structures. Each parameter increased or decreased the restraint in the walls and the roofs. The calculation of the restraint was done elastically by the finite element (FE) method. The results were used by an artificial neural network (ANN) tool, where, first, an influential percentage was investigated as input parameter on the restraint prediction. Equations were derived by the ANN model to calculate the restraint in the walls and the roofs. It was then used in a spreadsheet to calculate the restraint and compare the result with the result from the FE calculations, which showed a good agreement between the ANN model and the FE calculations
Using Artificial Neural Networks to Predict the Restraint in Concrete Culverts at Early Age
Al-Gburi, Majid A (Autor:in) / Jonasson, Jan-Erik / Nilsson, Martin
2015
Aufsatz (Zeitschrift)
Englisch
BKL:
56.10
Ingenieurhochbau: Allgemeines
/
56.23
Brückenbau
Lokalklassifikation TIB:
645/6510/6530
Using Artificial Neural Networks to Predict the Restraint in Concrete Culverts at Early Age
British Library Online Contents | 2015
|Taylor & Francis Verlag | 2018
|Using Artificial Neural Network to Predict the Restraint in Concrete Culvert at Early Age
Online Contents | 2015
|Engineering Index Backfile | 1913
|Engineering Index Backfile | 1907
|