Review of Proposed Stress-dilatancy Relationships and Plastic Potential Functions for Uncemented and Cemented Sands

Stress-dilatancy relationship or plastic potential function are crucial components of every elastoplastic constitutive model developed for sand or cemented sand.This is because the associated flow rule usually does not produce acceptable outcomes for sand or cemented sand.Many formulas have been introduced based on the experimental observations in conventional and advanced plasticity models in order to capture ratio of plastic volumetric strain increment to plastic deviatoric strain increment(i.e.dilatancy rate).Lack of an article that gathers these formulas is clear in the literature.Thus,this paper is an attempt to summarize plastic potentials and specially stress-dilatancy relations so far proposed for constitutive modelling of cohesionless and cemented sands.Stress-dilatancy relation is usually not the same under compression and extension conditions.Furthermore,it may also be different under loading and unloading conditions.Therefore,the focus in this paper mainly places on the proposed stress-dilatancy relations for compressive monotonic loading.Moreover because plastic potential function can be calculated by integration of stress-dilatancy relationship,more weight is allocated to stress-dilatancy relationship in this research.

U-shaped Vision Transformer and Its Application in Gear Pitting Measurement

Although convolutional neural networks have become the mainstream segmentation model,the locality of convolution makes them cannot well learn global and long-range semantic information.To further improve the performance of segmentation models,we propose U-shaped vision Transformer(UsViT),a model based on Transformer and convolution.Specifically,residual Transformer blocks are designed in the encoder of UsViT,which take advantages of residual network and Transformer backbone at the same time.What is more,transpositions in each Transformer layer achieve the information interaction between spatial locations and feature channels,enhancing the capability of feature learning.In the decoder,for enhancing receptive field,different dilation rates are introduced to each convolutional layer.In addition,residual connections are applied to make the information propagation smoother when training the model.We first verify the superiority of UsViT on automatic portrait matting public dataset,which achieves 90.43%accuracy(Acc),95.56%Dice similarity coefficient,and 94.66%Intersection over Union with relatively fewer parameters.Finally,UsViT is applied to gear pitting measurement in gear contact fatigue test,and the comparative results indicate that UsViT can improve the Acc of pitting detection.

Analytical investigation of laminar flow through expanding or contracting gaps with porous walls

Laminar,isothermal,incompressible and viscous flow in a rectangular domain bounded by two moving porous walls,w hich enable the fuid to enter or exit during successive expansions or contractions is investigated analytically using optimal homotopy asymptotic method(OHAM).OHAM is a powerful method for solving nonlinear problems without depending to the small parameter.The concept of this method is briefly introduced,and it's application for this problem is studied.Then,the results are compared with numerical results and the validity of these methods is shown.After this verification,we analyze the effects of some physical applicable parameters to show the efficiency of OHAM for this type of problems.Graphical results are presented to investigate the influence of the non-dimensional wall dilation rate(a)and pemeation Reynolds number(Re)on the velocity,normal pressure distribution and wall shear stress.The present problem for slowly expanding or contracting walls with weak permeability is a simple model for the transport of biological fuids through contracting or expanding vessels.