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Details for article 43 of 65 found articles
| Title: |
Prediction of Airport Flexible Pavement Critical Responses from Non-destructive Test Data Using ANN-based Structural Models |
| Author: |
Kasthurirangan Gopalakrishnan |
| Appeared in: |
Journal of applied sciences |
| Paging: | Volume 6 (2006) nr. 7 pages 1547-1552 |
| Year: |
2006 |
| Contents: |
This study describes the development of Artificial Neural Network (ANN) based pavement response prediction models for rapid structural analysis of airport flexible pavements based on Non-destructive Test (NDT) data. A finite element based pavement structural model, which can accommodate stress-sensitive geomaterial stiffness models, was used to generate the ANN training and testing dataset. The goal was to establish ANN models for predicting critical responses (stresses and strains) from routine NDT airfield pavement structural evaluation data. The developed ANN models predicted the critical pavement responses obtained from the finite element model with good accuracy. Further research is required to achieve increased prediction accuracies and validate the ANN models using actual field data. |
| Publisher: |
Asian Network for Scientific Information (provided by DOAJ) |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 43 of 65 found articles
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