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Interpretation of FWD Data When Pavement Layers Are Not Intact; Final rept. Jul 95-Jun 97
| 题名： | Interpretation of FWD Data When Pavement Layers Are Not Intact; Final rept. Jul 95-Jun 97 |
| 作者： | Kim, Y. R.; Lee, Y. C.; Park, S.; Ranjithan, S. R. |
| 关键词： | Pavements; Pavement diflections; Finite element analysis; Mathematical models; Asphalt pavements; Flexible pavements; Asphaltic concrete; Dynamic analysis; Neural nets |
| 摘要： | The falling weight deflectometer (FWD) has become a popular tool worldwide for the evaluation of the structural capacity and integrity of existing pavements. Most of the deflection analysis programs used today are based on multi-layered elastic analysis which assumes static loading and continuous, homogeneous, and isotrophic layers. When FWD tests are performed on broken or cracked pavements (of which information is crucial in making rehabilitation and overlay decisions), the multi-layered elastic theory-based backcalulation programs assume that the effect of these discontinuities in a cracked layer on deflection basins would be accounted for by the reduction of the elastic modulus for that layer. However, it has been concluded and confirmed by researchers and practitioners that the backcalculation algorithms based on the multi-layered elastic theory rpoduce large variation in the algorithms based on the multi-layered elastic theory produce large variation in the 'effective' moduli of the cracked layers. Studies have also shown that significant errors in the backcalculated pavement moduli can accrue from performing a static analysis of what is inherently a dynamic test. Unfortunately, dynamic analysis usually involves complex calculations and requires significant computation time, thus making it impracticable for routine applications. This study presents a methology based on deflection basin parameters and artificial neural networks (ANNs) for processing dynamic FWD measurements to estimate layer strengths. |
| 总页数： | 160p |
| 报告类型： | 科技报告 |
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