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DEVELOPMENT OF NEW DRIVEN PILE TECHNOLOGY
| 题名： | DEVELOPMENT OF NEW DRIVEN PILE TECHNOLOGY |
| 作者： | Robert Y. Liang |
| 关键词： | Pile driving, Smith model. Neural Networks, Standard Penetration Testing, |
| 摘要： | A research project has been carried out to achieve three major objectives related to pile driving: (a) development of an energy based dynamic method to replace the existing Engineering News (EN) formula approach, (b) development of an in-situ testing technique to determine the site-specific Smith model parameters, (c) development of an improved wave equation based numerical simulation technique for efficient estimate of pile capacity based on HST (high strain test) data. A total of 32 dynamic pile tests and three static load tests have been carried out throughout Ohio. These test results constitute one part of the University of Akron (UA) database. In addition, data from existing literatures and FHWA database were added to the UA database to form a more comprehensive database for the development and verification of the new computational algorithms. This research has produced one new product (a new pile driving control system) and two new computational methodologies (one is the neural network based method for predicting pile capacity using the SPT soil boring information, and the other one is the SPT based methodology for estimating Smith model parameters). The major developments of the new computational algorithms, as a result of this research, are: (i) A probability based energy approach and the Bayesian updating technique for pile capacity estimate, (ii) A new semi-analytical solution cast in either forward or back calculation for CAPWAP type pile capacity estimate, (iii)A methodology for the determination of the Smith model parameters using the SPT N values, (iv) Two major neural network based computational algorithms to predict pile capacity on the basis of the measured HST data. Research findings that were recommended for implementation include: (a) adoption of the new product, the pile driving control system, for field use, (b) adoption of the neural network based algorithm to predict pile capacity based on the SPT N values, and (c) adoption of the methodology for the determination of the Smith model parameters from the SPT N values. |
| 报告类型： | 科技报告 |
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