One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study...One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study aims to apply intelligent methods to predict settlement after constructing central core rockfill dams.Attempts were made in this research to prepare models for predicting settlement of these dams using the information of 35 different central core rockfill dams all over the world and Adaptive Neuro-Fuzzy Interface System(ANFIS) and Gene Expression Programming(GEP) methods.Parameters such as height of dam(H) and compressibility index(Ci) were considered as the input parameters.Finally,a form was designed using visual basic software for predicting dam settlement.With respect to the accuracy of the results obtained from the intelligent methods,they can be recommended for predicting settlement after constructing central core rockfill dams for the future plans.展开更多
An inner seepage face phenomenon is given and a numerical simulation procedure has been developed.It may appear at the interface of two materials when an unconfined seepage flows from a porous media to a coarser porou...An inner seepage face phenomenon is given and a numerical simulation procedure has been developed.It may appear at the interface of two materials when an unconfined seepage flows from a porous media to a coarser porous media with a higher permeability.Inaccuracy and divergent problems may arise both in a saturated-only and in a variably saturated analysis while an inner seepage face is not simulated with a special procedure.The position of the seepage face is determined during the nonlinear iteration process and the flux of the inner seepage face nodes is transferred to the downstream side nodes.Validity and efficiency of the procedure are illustrated by the simulation of two dimensional steady state seepage examples of heterogeneous zoned dams which is usually used to validate algorithms.An analysis of a three-dimensional earth core rockfill dam is also presented here.The procedure can also be applied to general transient seepage problems.展开更多
The conventional quality control method of core rocldill dam construction exhibit difficulty controlling compaction parameters accurately or ensuring construction quality. This is because it is easily influenced by hu...The conventional quality control method of core rocldill dam construction exhibit difficulty controlling compaction parameters accurately or ensuring construction quality. This is because it is easily influenced by human behavior or lack of adequate management. We therefore establish the timely monitoring indexes and control criteria of compaction processes by considering the characteristics and quality requirements of high core rockffll dam construction. Based on the established indexes and criteria, integrating GPS, GPRS and PDA technologies, a real-time compaction quality monitoring method is proposed. The relevant key techniques are proposed as well, including automatic collection of information and a graphic algorithm for rolling-process visualization. By the proposed method and techniques, a real-time monitoring system is provided to realize the precise automatic online entire-process monitoring of compaction parameters, including compaction pass, rolling trajectory, nmning speed of roller, vibration status and rolled pavement thickness. The application of the Nuozhadu project shows that the proposed system can control compaction parameters effectively and ensure better construction quality. Therefore, it might become a new way towards construction quality control of high core rockfill dam.展开更多
Parameters identification of rockfill materials is a crucial issue for high rockfill dams. Because of the scale effect, random sampling and sample disturbance, it is difficult to obtain the actual mechanical propertie...Parameters identification of rockfill materials is a crucial issue for high rockfill dams. Because of the scale effect, random sampling and sample disturbance, it is difficult to obtain the actual mechanical properties of rockfill from laboratory tests. Parameters inversion based on in situ monitoring data has been proven to be an efficient method for identifying the exact parameters of the rockfill. In this paper, we propose a modified genetic algorithm to solve the high-dimension multimodal and nonlinear optimal parameters inversion problem. A novel crossover operator based on the sum of differences in gene fragments(So DX) is proposed, inspired by the cloning of superior genes in genetic engineering. The crossover points are selected according to the difference in the gene fragments, defining the adaptive length. The crossover operator increases the speed and accuracy of algorithm convergence by reducing the inbreeding and enhancing the global search capability of the genetic algorithm. This algorithm is compared with two existing crossover operators. The modified genetic algorithm is then used in combination with radial basis function neural networks(RBFNN) to perform the parameters back analysis of a high central earth core rockfill dam. The settlements simulated using the identified parameters show good agreement with the monitoring data, illustrating that the back analysis is reasonable and accurate. The proposed genetic algorithm has considerable superiority for nonlinear multimodal parameter identification problems.展开更多
文摘One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study aims to apply intelligent methods to predict settlement after constructing central core rockfill dams.Attempts were made in this research to prepare models for predicting settlement of these dams using the information of 35 different central core rockfill dams all over the world and Adaptive Neuro-Fuzzy Interface System(ANFIS) and Gene Expression Programming(GEP) methods.Parameters such as height of dam(H) and compressibility index(Ci) were considered as the input parameters.Finally,a form was designed using visual basic software for predicting dam settlement.With respect to the accuracy of the results obtained from the intelligent methods,they can be recommended for predicting settlement after constructing central core rockfill dams for the future plans.
基金supported by the National Natural Science Foundation of China (Grant No. 10932012)the China-Europe Science and Technology Cooperation Program (Grant No. 0820)European Commission(Grant No. FP7-NMP-2007-LARGE-1)
文摘An inner seepage face phenomenon is given and a numerical simulation procedure has been developed.It may appear at the interface of two materials when an unconfined seepage flows from a porous media to a coarser porous media with a higher permeability.Inaccuracy and divergent problems may arise both in a saturated-only and in a variably saturated analysis while an inner seepage face is not simulated with a special procedure.The position of the seepage face is determined during the nonlinear iteration process and the flux of the inner seepage face nodes is transferred to the downstream side nodes.Validity and efficiency of the procedure are illustrated by the simulation of two dimensional steady state seepage examples of heterogeneous zoned dams which is usually used to validate algorithms.An analysis of a three-dimensional earth core rockfill dam is also presented here.The procedure can also be applied to general transient seepage problems.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51021004, 51079096)the Program for New Century Excellent Talents in University (Grant No. NCET-08-0391)
文摘The conventional quality control method of core rocldill dam construction exhibit difficulty controlling compaction parameters accurately or ensuring construction quality. This is because it is easily influenced by human behavior or lack of adequate management. We therefore establish the timely monitoring indexes and control criteria of compaction processes by considering the characteristics and quality requirements of high core rockffll dam construction. Based on the established indexes and criteria, integrating GPS, GPRS and PDA technologies, a real-time compaction quality monitoring method is proposed. The relevant key techniques are proposed as well, including automatic collection of information and a graphic algorithm for rolling-process visualization. By the proposed method and techniques, a real-time monitoring system is provided to realize the precise automatic online entire-process monitoring of compaction parameters, including compaction pass, rolling trajectory, nmning speed of roller, vibration status and rolled pavement thickness. The application of the Nuozhadu project shows that the proposed system can control compaction parameters effectively and ensure better construction quality. Therefore, it might become a new way towards construction quality control of high core rockfill dam.
基金supported by the National Natural Science Foundation of China(Grant Nos.51379161&51509190)China Postdoctoral Science Foundation(Grant No.2015M572195)the Fundamental Research Funds for the Central Universities
文摘Parameters identification of rockfill materials is a crucial issue for high rockfill dams. Because of the scale effect, random sampling and sample disturbance, it is difficult to obtain the actual mechanical properties of rockfill from laboratory tests. Parameters inversion based on in situ monitoring data has been proven to be an efficient method for identifying the exact parameters of the rockfill. In this paper, we propose a modified genetic algorithm to solve the high-dimension multimodal and nonlinear optimal parameters inversion problem. A novel crossover operator based on the sum of differences in gene fragments(So DX) is proposed, inspired by the cloning of superior genes in genetic engineering. The crossover points are selected according to the difference in the gene fragments, defining the adaptive length. The crossover operator increases the speed and accuracy of algorithm convergence by reducing the inbreeding and enhancing the global search capability of the genetic algorithm. This algorithm is compared with two existing crossover operators. The modified genetic algorithm is then used in combination with radial basis function neural networks(RBFNN) to perform the parameters back analysis of a high central earth core rockfill dam. The settlements simulated using the identified parameters show good agreement with the monitoring data, illustrating that the back analysis is reasonable and accurate. The proposed genetic algorithm has considerable superiority for nonlinear multimodal parameter identification problems.
