Reliability and sensitivity analysis of wedge stability in the abutments of an arch dam using artificial neural network     

Mostafaei  Hasan  Behnamfar  Farhad  Alembagheri  Mohammad 《地震工程与工程振动(英文版)》2022,21(4):1019-1033

In this study, the seismic stability of arch dam abutments is investigated within the framework of the probabilistic method. A large concrete arch dam is considered with six wedges for each abutment. The seismic safety of the dam abutments is studied with quasi-static analysis for different hazard levels. The Londe limit equilibrium method is utilized to calculate the stability of the wedges in the abutments. Since the finite element method is time-consuming, the neural network is used as an alternative for calculating the wedge safety factor. For training the neural network, 1000 random samples are generated and the dam response is calculated. The direction of applied acceleration is changed within 5-degree intervals to reveal the critical direction corresponding to the minimum safety factor. The Latin hypercube sampling (LHS) is employed for sample generation, and the safety level is determined with reliability analysis. Three sample numbers of 1000, 2000 and 4000 are used to examine the average and standard deviation of the results. The global sensitivity analysis is used to identify the effects of random variables on the abutment stability. It is shown that friction, cohesion and uplift pressure have the most significant effects on the wedge stability variance.

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Compiling and verifying 3D models of 2D induced polarization and resistivity data by geostatistical methods     

Kamran Mostafaei  Hamidreza Ramazi 《Acta Geophysica》2018,66(5):959-971

A 3D model of collected time-domain induced polarization (IP) and electrical resistivity tomography (ERT) data is compiled by geostatistical methods as well as studying spatial correlation among the database. Mesgaran copper deposit, located in Birjand eastern Iran, was chosen to compile and verify the model, leading to five parallel surveyed IP and ERT profiles with dipole–dipole arrays. The collected data were inverted, and then 2D models of IP and ER were prepared; also 3D inversion was done. Afterward, the 3D model has been built by geostatistical methods. Correspondingly, the anomalies threshold was detected by fractal methods and the estimation variance and Kriging efficiency were calculated to validate the modeling. The mineralization zones were determined according to the classified anomalies and those with the lowest error. Results indicated a high correlation between anomalies identified from the model and mineralization. The results made it possible to construct 3D models from surveyed 2D data with acceptable error level.  相似文献