Papers by Author: Xiao Yong Li

Abstract: In recent years artificial neural networks (ANNs) have been applied to many geotechnical engineering problems with some degree of success. With respect to the design of Highway embankment, accurate prediction of settlement of soft clay foundation in highway is necessary to ensure appropriate structural and serviceability performance. In this paper, an ANN model is developed for predicting settlement of soft clay foundation based on the observation data of settlement. Approximately 200 data sets, obtained from the Field Tests and the published literature, are used to develop the ANN model. In addition, the paper discusses the choice of input and internal network parameters which were examined to obtain the optimum model. Finally, the paper compares the predictions obtained by the ANN with those given by a number of traditional methods. It is demonstrated that the ANN model outperforms the traditional methods and provides accurate settlement predictions for soft clay foundation in highway.

Abstract: The correlation distance is one of the important parameters for the application of random field theory to reliability analyses. Soil spatial variability is related to soil point variability with the reduction factor of variance in random field theory, and the reduction factor of variance depends on both soil auto-correlation distance and spatial area. The sampling space effect on auto-correlation distance is studied. The vertical and horizontal correlation distances of typical stratum are analyzed in statistics based on a large amount of investigation data and the representative values of correlation distance of local area are obtained. It is concluded that that the correlation distances estimated by different soil parameters are similar, and the horizontal correlation distance is much larger than the vertical one for the same soil parameter. The sampling space should be paid attention to when calculating correlation distance of soil parameter.

Abstract: The measured coefficient of consolidation can have a substantial degree of variation even in a uniform clay layer. The probability characteristic values for such parameters as consolidation coefficient and compression modulus are analyzed from local engineering data. This paper, through a probabilistic analysis, examines the variability of one-dimensional consolidation solutions. The multilayer models are evaluated. Then the Monte Carlo method is used to develop solutions for one dimensional consolidation. It identified the influence of the parameter uncertainty on the probability characteristic of the consolidation degree. The uncertainty of consolidation coefficient has a great impact on the probabilistic characteristics of the consolidation degree, but for compression modulus it is opposite true. It proposed a simplification analysis method that considers only the uncertainty of consolidation coefficient without consideration of the uncertainty of compression modulus, and its erroneous precision can meet the engineering requirements.

Abstract: There are three normal sizes of loading plate as 30 cm, 50 cm, 75 cm in roadbed compaction quality detection. The size effect rule for coefficient of foundation is obtained from the investigation on plate load test results by the experiment in lab. The laboratory test may control well the conditions by building the test section modeling the roadbed. The test section is 15 m by 5m. The diameters of loading plate used is 30cm, 35cm, 40cm, 45cm, 50cm, 55cm, 60cm, 65cm, 70cm and 75cm in the test. The regression equation between coefficients of foundation measured by different size of loading plate has been concluded. It is obtained that the ratio of coefficients of foundation between the plate of 50 cm and 30cm is 1.6 for granule filler, 1.65 for grind filler, and the one between the plate of 70 cm and 30cm is 2.17 for granule filler, 2.3 for grind filler.

Abstract: The measured coefficient of consolidation can have a substantial degree of variation even in a uniform clay layer. This paper examines the variability of one-dimensional consolidation solutions through a probabilistic analysis. The spatial probabilistic characteristics for the coefficient of vertical consolidation are studied. The influence of a spatially random coefficient of consolidation on one-dimensional consolidation has been studied using the probabilistic method. In the probabilistic analysis, the adequacy of distribution model for coefficient of consolidation is tested using experimental data. A sensitivity analysis of the degree of consolidation to uncertain parameters is presented for clay soil. It is the analysis result that probability distribution type of vertical consolidation has a considerable influence on degree of consolidation. The results are discussed in terms of confidence level.