Deformation control criterion of shield tunnel under lateral relaxation of soft soil

Metro shield tunnels under the lateral relaxation of soil(LRS)are susceptible to significant lateral deformations,which jeopardizes the structural safety and waterproofing.However,deformation control standards for such situations have not been clearly defined.Therefore,based on a specific case,a model test is conducted to realize the LRS of a shield tunnel in a sandy stratum to reveal its effect on segment liners.Subsequently,a deformation control criterion is established.The LRS is simulated by linearly reducing the loads applied to the lateral sides of the segment structure.During lateral unloading,the lateral earth pressure coefficient on the segment decreases almost exponentially,and the structural deformation is characterized by horizontal expansion at the arch haunches and vertical shrinkage at the arch vault and arch bottom.Based on the mechanical pattern of the segment structure and the acoustic emission,the deformation response of a segment can be classified into three stages:elastic and quasi-elastic,damage,and rapid deformation development.For a shield tunnel with a diameter of approximately 6 m and under the lateral relaxation of sandy soil,when the ellipticity of the segment is less than 2.71%,reinforcement measures are not required.However,the segment deformation must be controlled when the ellipticity is 2.71%to 3.12%;in this regard,an ellipticity of 3%can be used as a benchmark in similar engineering projects.

Double regularization control based on level set evolution for tablet packaging image segmentation

This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to make image segmentation. Compared to methods based on level set, the proposed DRC method has some advantages for tablet packaging image segmentation. The local re- gional control term and the rectangle initialization contour are first employed in this method to quickly segment un- even grayscale images and accelerate the curve evolution rate. Gaussian filter operator and the convolution calcula- tion are then adopted to remove the effects of texture noises in image segmentation. The developed penalty energy function, as regularization term, increases the constrained conditions based on the gradient flow conditions. Since the potential function is embedded into the level set of evo- lution equations and the image contour evolutions are bi- laterally extended, the proposed method further improves the accuracy of image contours. Experimental studies show that the DRC method greatly improves the computational efficiency and numerical accuracy, and achieves better results for image contour segmentation compared to other level set methods.