For a soft rock tunnel under high stress in jointed and swell soft rock （HJS）, two construction schemes pilot-tunneling enlarging excavation and step-by-step excavation were optimized using FLAC20, and the deformati...For a soft rock tunnel under high stress in jointed and swell soft rock （HJS）, two construction schemes pilot-tunneling enlarging excavation and step-by-step excavation were optimized using FLAC20, and the deformation effects of the two construction schemes were verified by field tests. Based on engineer- ing geological investigation and mechanical analysis of large deformations, the complex deformation mechanisms of stress expansion and structural deformation of the soft rock tunnel were confirmed, and support countermeasures from the complex deformation mechanism converted to a single type were proposed, and the support parameters were optimized by field tests. These technologies were proved by engineering practice, which produced significant technical and economic benefits.展开更多
The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing paramet...The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing parameter design method, this paper proposes an optimization design scheme based on orthogonal testing and support vector machines （SVMs）. Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency. Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure, uniform applied load and the number of chambers that affect the bending response of inflatable wings. An SVM intelligent model is established and limited orthogonal test swatches are studied. Thus, the precise relationships between each parameter and product quality features, as well the signal-to-noise ratio （SNR）, can be obtained. This can guide general technological design optimization.展开更多
基金financially supported by the National Natural Science Foundation of China (Nos. 51474188, 51074140 and 51310105020)the Natural Science Foundation of Hebei Province (No. E2014203012)the Program for Taihang Scholars
文摘For a soft rock tunnel under high stress in jointed and swell soft rock （HJS）, two construction schemes pilot-tunneling enlarging excavation and step-by-step excavation were optimized using FLAC20, and the deformation effects of the two construction schemes were verified by field tests. Based on engineer- ing geological investigation and mechanical analysis of large deformations, the complex deformation mechanisms of stress expansion and structural deformation of the soft rock tunnel were confirmed, and support countermeasures from the complex deformation mechanism converted to a single type were proposed, and the support parameters were optimized by field tests. These technologies were proved by engineering practice, which produced significant technical and economic benefits.
文摘The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing parameter design method, this paper proposes an optimization design scheme based on orthogonal testing and support vector machines （SVMs）. Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency. Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure, uniform applied load and the number of chambers that affect the bending response of inflatable wings. An SVM intelligent model is established and limited orthogonal test swatches are studied. Thus, the precise relationships between each parameter and product quality features, as well the signal-to-noise ratio （SNR）, can be obtained. This can guide general technological design optimization.
