Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro...Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro-posed to improve the efficiency for edge inference of Deep Neural Networks(DNNs),existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead,and their efficiency is bounded by the bottleneck of computation latency and memory footprint.To tackle this challenge,we present an efficient inference approach on the basis of PoT quantization and model compression.An integer-only scalar PoT quantization(IOS-PoT)is designed jointly with a distribution loss regularizer,wherein the regularizer minimizes quantization errors and training disturbances.Additionally,two-stage model compression is developed to effectively reduce memory requirement,and alleviate bandwidth usage in communications of networked heterogenous learning systems.The product look-up table(P-LUT)inference scheme is leveraged to replace bit-shifting with only indexing and addition operations for achieving low-latency computation and implementing efficient edge accelerators.Finally,comprehensive experiments on Residual Networks(ResNets)and efficient architectures with Canadian Institute for Advanced Research(CIFAR),ImageNet,and Real-world Affective Faces Database(RAF-DB)datasets,indicate that our approach achieves 2×∼10×improvement in the reduction of both weight size and computation cost in comparison to state-of-the-art methods.A P-LUT accelerator prototype is implemented on the Xilinx KV260 Field Programmable Gate Array(FPGA)platform for accelerating convolution operations,with performance results showing that P-LUT reduces memory footprint by 1.45×,achieves more than 3×power efficiency and 2×resource efficiency,compared to the conventional bit-shifting scheme.展开更多
This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performe...This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performed on saturated expansive soil specimens with varying compaction conditions and soil structures under different stress states.Experimental results demonstrate that the specimens expand during freezing and contract during thawing.All specimens converge to the same residual void ratio after seven FT cycles,irrespective of their different initial void ratio,stress state,and soil structure.The compression index of the expansive soil specimens increases with the initial void ratio,whereas their swelling index remains nearly constant.A model extending the disturbed state concept(DSC)is proposed to predict the 1D compression behaviors of FT-impacted soils.The model incorporates a parameter,b,to account for the impacts of FT cycles.Empirical equations have been developed to link the key model parameters(i.e.the normalized yield stress and parameter b)to the soil state parameter(i.e.the normalized void ratio)in order to simplify the prediction approach.The proposed model well predicts the results of the tested expansive soil.In addition,the model’s feasibility for other types of soils,including low-and high-plastic clays,and high-plastic organic soils,has been validated using published data from the literature.The proposed model is simple yet reliable for predicting the compression behaviors of soils subjected to FT cycles.展开更多
The steel plate is one of the main products in steel industries,and its surface quality directly affects the final product performance.How to detect surface defects of steel plates in real time during the production p...The steel plate is one of the main products in steel industries,and its surface quality directly affects the final product performance.How to detect surface defects of steel plates in real time during the production process is a challenging problem.The single or fixed model compression method cannot be directly applied to the detection of steel surface defects,because it is difficult to consider the diversity of production tasks,the uncertainty caused by environmental factors,such as communication networks,and the influence of process and working conditions in steel plate production.In this paper,we propose an adaptive model compression method for steel surface defect online detection based on expert knowledge and working conditions.First,we establish an expert system to give lightweight model parameters based on the correlation between defect types and manufacturing processes.Then,lightweight model parameters are adaptively adjusted according to working conditions,which improves detection accuracy while ensuring real-time performance.The experimental results show that compared with the detection method of constant lightweight parameter model,the proposed method makes the total detection time cut down by 23.1%,and the deadline satisfaction ratio increased by 36.5%,while upgrading the accuracy by 4.2%and reducing the false detection rate by 4.3%.展开更多
Automated machine learning(AutoML)pruning methods aim at searching for a pruning strategy automatically to reduce the computational complexity of deep convolutional neural networks(deep CNNs).However,some previous wor...Automated machine learning(AutoML)pruning methods aim at searching for a pruning strategy automatically to reduce the computational complexity of deep convolutional neural networks(deep CNNs).However,some previous work found that the results of many Auto-ML pruning methods cannot even surpass the results of the uniformly pruning method.In this paper,the ineffectiveness of Auto-ML pruning,which is caused by unfull and unfair training of the supernet,is shown.A deep supernet suffers from unfull training because it contains too many candidates.To overcome the unfull training,a stage-wise pruning(SWP)method is proposed,which splits a deep supernet into several stage-wise supernets to reduce the candidate number and utilize inplace distillation to supervise the stage training.Besides,a wide supernet is hit by unfair training since the sampling probability of each channel is unequal.Therefore,the fullnet and the tinynet are sampled in each training iteration to ensure that each channel can be overtrained.Remarkably,the proxy performance of the subnets trained with SWP is closer to the actual performance than that of most of the previous AutoML pruning work.Furthermore,experiments show that SWP achieves the state-of-the-art in both CIFAR-10 and ImageNet under the mobile setting.展开更多
Facial emotion recognition achieves great success with the help of large neural models but also fails to be applied in practical situations due to the large model size of neural methods.To bridge this gap,in this pape...Facial emotion recognition achieves great success with the help of large neural models but also fails to be applied in practical situations due to the large model size of neural methods.To bridge this gap,in this paper,we combine two mainstream model compression methods(pruning and quantization)together,and propose a pruningthen-quantization framework to compress the neural models for facial emotion recognition tasks.Experiments on three datasets show that our model could achieve a high model compression ratio and maintain the model’s high performance well.Besides,We analyze the layer-wise compression performance of our proposed framework to explore its effect and adaptability in fine-grained modules.展开更多
Edge Machine Learning(EdgeML)and Tiny Machine Learning(TinyML)are fast-growing fields that bring machine learning to resource-constrained devices,allowing real-time data processing and decision-making at the network’...Edge Machine Learning(EdgeML)and Tiny Machine Learning(TinyML)are fast-growing fields that bring machine learning to resource-constrained devices,allowing real-time data processing and decision-making at the network’s edge.However,the complexity of model conversion techniques,diverse inference mechanisms,and varied learning strategies make designing and deploying these models challenging.Additionally,deploying TinyML models on resource-constrained hardware with specific software frameworks has broadened EdgeML’s applications across various sectors.These factors underscore the necessity for a comprehensive literature review,as current reviews do not systematically encompass the most recent findings on these topics.Consequently,it provides a comprehensive overview of state-of-the-art techniques in model conversion,inference mechanisms,learning strategies within EdgeML,and deploying these models on resource-constrained edge devices using TinyML.It identifies 90 research articles published between 2018 and 2025,categorizing them into two main areas:(1)model conversion,inference,and learning strategies in EdgeML and(2)deploying TinyML models on resource-constrained hardware using specific software frameworks.In the first category,the synthesis of selected research articles compares and critically reviews various model conversion techniques,inference mechanisms,and learning strategies.In the second category,the synthesis identifies and elaborates on major development boards,software frameworks,sensors,and algorithms used in various applications across six major sectors.As a result,this article provides valuable insights for researchers,practitioners,and developers.It assists them in choosing suitable model conversion techniques,inference mechanisms,learning strategies,hardware development boards,software frameworks,sensors,and algorithms tailored to their specific needs and applications across various sectors.展开更多
BACKGROUND： Varying degrees of inflammatory responses occur during lumbar nerve root compression. Studies have shown that nitric oxide synthase （NOS） and calcitonin gene-related peptide （CGRP） are involved in sec...BACKGROUND： Varying degrees of inflammatory responses occur during lumbar nerve root compression. Studies have shown that nitric oxide synthase （NOS） and calcitonin gene-related peptide （CGRP） are involved in secondary disc inflammation. OBJECTIVE： To observe the effects of warm acupuncture on the ultrastructure of inflammatory mediators in a rat model of lumbar nerve root compression, including NOS and CGRP contents. DESIGN, TIME AND SETTING： Randomized, controlled study, with molecular biological analysis, was performed at the Experimental Center, Sixth People＇s Hospital Affiliated to Shanghai Jiao Tong University, between September 2006 and April 2007. MATERIALS： Acupuncture needles and refined Moxa grains were purchased from Shanghai Taicheng Technology Development Co., Ltd., China; Mobic tablets were purchased from Shanghai Boehringer Ingelheim Pharmaceuticals Co., Ltd., China; enzyme linked immunosorbent assay （ELISA） kits for NOS and CGRP were purchased from ADL Biotechnology, Inc., USA. METHODS： A total of 50, healthy, adult Sprague-Dawley rats, were randomly divided into five groups normal, model, warm acupuncture, acupuncture, and drug, with 10 rats in each group. Rats in the four groups, excluding the normal group, were used to establish models of lumbar nerve root compression. After 3 days, Jiaji points were set using reinforcing-reducing manipulation in the warm acupuncture group. Moxa grains were burned on each needle, with 2 grains each daily. The acupuncture group was the same as the warm acupuncture group, with the exception of non-moxibustion. Mobic suspension （3.75 mg/kg） was used in the oral drug group, once a day. Treatment of each group lasted for 14 consecutive days. Modeling and medication were not performed in the normal group. MAIN OUTCOME MEASURES： The ultrastructure of damaged nerve roots was observed with transmission electron microscopy; NOS and CGRP contents were measured using ELISA. RESULTS： The changes of the radicular ultramicrostructure were characterized by Wallerian degeneration; nerve fibers were clearly demyelinated; axons collapsed or degenerated; outer Schwann cell cytoplasm was swollen and its nucleus was compacted. Compared with the normal group, NOS and CGRP contents in the nerve root compression zone in the model group were significantly increased （P 〈 0.01）. Nerve root edema was improved in the drug, acupuncture and the warm acupuncture groups over the model group. NOS and CGRP expressions were also decreased with the warm acupuncture group having the lowest concentration （P 〈 0.01）. CONCLUSION： In comparison to the known effects of Mobic drug and acupuncture treatments, the warm acupuncture significantly decreased NOS and CGRP expression which helped improve the ultrastructure of the compressed nerve root.展开更多
Despite the rapid development of mobile and embedded hardware, directly executing computationexpensive and storage-intensive deep learning algorithms on these devices’ local side remains constrained for sensory data ...Despite the rapid development of mobile and embedded hardware, directly executing computationexpensive and storage-intensive deep learning algorithms on these devices’ local side remains constrained for sensory data analysis. In this paper, we first summarize the layer compression techniques for the state-of-theart deep learning model from three categories: weight factorization and pruning, convolution decomposition, and special layer architecture designing. For each category of layer compression techniques, we quantify their storage and computation tunable by layer compression techniques and discuss their practical challenges and possible improvements. Then, we implement Android projects using TensorFlow Mobile to test these 10 compression methods and compare their practical performances in terms of accuracy, parameter size, intermediate feature size,computation, processing latency, and energy consumption. To further discuss their advantages and bottlenecks,we test their performance over four standard recognition tasks on six resource-constrained Android smartphones.Finally, we survey two types of run-time Neural Network(NN) compression techniques which are orthogonal with the layer compression techniques, run-time resource management and cost optimization with special NN architecture,which are orthogonal with the layer compression techniques.展开更多
A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calcula...A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.展开更多
The Spalart-Allmaras （S-A） turbulence model, the shear-stress transport （SST） turbulence model and their compressibility corrections are revaluated for hypersonic compression comer flows by using high-order differ...The Spalart-Allmaras （S-A） turbulence model, the shear-stress transport （SST） turbulence model and their compressibility corrections are revaluated for hypersonic compression comer flows by using high-order difference schemes. The compressibility effect of density gradient, pressure dilatation and turbulent Mach number is accounted. In order to reduce confusions between model uncertainties and discretization errors, the formally fifth-order explicit weighted compact nonlinear scheme （WCNS-E-5） is adopted for convection terms, and a fourth-order staggered central difference scheme is applied for viscous terms. The 15° and 34° compression comers at Mach number 9.22 are investigated. Numerical results show that the original SST model is superior to the original S-A model in the resolution of separated regions and predictions of wall pressures and wall heat-flux rates. The capability of the S-A model can be largely improved by blending Catris＇ and Shur＇s compressibility corrections. Among the three corrections of the SST model listed in the present paper, Catris＇ modification brings the best results. However, the dissipation and pressure dilatation corrections result in much larger separated regions than that of the experiment, and are much worse than the original SST model as well as the other two corrections. The correction of turbulent Mach number makes the separated region slightly smaller than that of the original SST model. Some results of low-order schemes are also presented. When compared to the results of the high-order schemes, the separated regions are smaller, and the peak wall pressures and peak heat-flux rates are lower in the region of the reattachment points.展开更多
A numerical simulation of shock wave turbulent boundary layer interaction induced by a 24° compression corner based on Gao-Yong compressible turbulence model was presented.The convection terms and the diffusion t...A numerical simulation of shock wave turbulent boundary layer interaction induced by a 24° compression corner based on Gao-Yong compressible turbulence model was presented.The convection terms and the diffusion terms were calculated using the second-order AUSM(advection upstream splitting method) scheme and the second-order central difference scheme,respectively.The Runge-Kutta time marching method was employed to solve the governing equations for steady state solutions.Significant flow separation-region which indicates highly non-isotropic turbulence structure has been found in the present work due to intensity interaction under the 24° compression corner.Comparisons between the calculated results and experimental data have been carried out,including surface pressure distribution,boundary-layer static pressure profiles and mean velocity profiles.The numerical results agree well with the experimental values,which indicate Gao-Yong compressible turbulence model is suitable for the prediction of shock wave turbulent boundary layer interaction in two-dimensional compression corner flows.展开更多
In this article, we consider the blowup criterion for the local strong solution to the compressible fluid-particle interaction model in dimension three with vacuum. We establish a BKM type criterion for possible break...In this article, we consider the blowup criterion for the local strong solution to the compressible fluid-particle interaction model in dimension three with vacuum. We establish a BKM type criterion for possible breakdown of such solutions at critical time in terms of both the L^∞ （0, T; L^6）-norm of the density of particles and the ^L1（0, T; L^∞）-norm of the deformation tensor of velocity gradient.展开更多
Modeling of a centrifugal compressor is of great significance to surge characteristics and fluid dynamics in the Altitude Ground Test Facilities(AGTF).Real-time Modular Dynamic System Greitzer(MDSG)modeling for dynami...Modeling of a centrifugal compressor is of great significance to surge characteristics and fluid dynamics in the Altitude Ground Test Facilities(AGTF).Real-time Modular Dynamic System Greitzer(MDSG)modeling for dynamic response and simulation of the compression system is introduced.The centrifugal compressor,pipeline network,and valve are divided into pressure output type and mass flow output type for module modeling,and the two types of components alternate when the system is established.The pressure loss and thermodynamics of the system are considered.An air supply compression system of AGTF is modeled and simulated by the MDSG model.The simulation results of mass flow,pressure,and temperature are compared with the experimental results,and the error is less than 5%,which demonstrates the reliability,practicability,and universality of the MDSG model.展开更多
Isothermal compression of TC4 alloy was performed on a Thermecmaster-Z simulator at the deformation temperatures ranging from 1093 to 1243 K, the strain rates ranging from 0.001 to 10.000 s^-l and a maximum strain of ...Isothermal compression of TC4 alloy was performed on a Thermecmaster-Z simulator at the deformation temperatures ranging from 1093 to 1243 K, the strain rates ranging from 0.001 to 10.000 s^-l and a maximum strain of 0.8. The experimental results show that the flow stress increases with the decrease in the deformation temperature and the increase in the strain rate. The apparent activation energy for deformation is much lower at lower strain rates than that at higher strain rates. The flow stress model considering strain compensation was established. The average relative error between the calculated flow stress and experimental results is about 7.69%, indicating that the present model could be used to accurately predict the flow stress during high temperature in α＋β phase field of TC4 alloy.展开更多
Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of ...Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.展开更多
BACKGROUND：It has been shown that interleukin-1 （IL-1） may cause inflammatory reactions, which stimulate the nerve root of patients with lumbar intervertebral disc protrusion and leads to pain. Whether the clinical...BACKGROUND：It has been shown that interleukin-1 （IL-1） may cause inflammatory reactions, which stimulate the nerve root of patients with lumbar intervertebral disc protrusion and leads to pain. Whether the clinical curative effects of acupuncture in the treatment of lumbar and leg pain are linked to an inhibition of local IL-1 secretion is unknown. OBJECTIVE： To assess the influence of acupuncture on IL-1, this study was designed to verify the effects of acupuncture at the ＂Huatuojiaji （Extra）＂ point on the nerve root in a rat model of lumbar nerve root compression, compared with administration of meloxicam, a non-steroidal anti-inflammatory drug. DESIGN, TIME AND SETTING： Randomized, controlled, molecular biology experiment, performed at the Experimental Center, Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University between September 2005 and April 2006. MATERIALS： Forty healthy adult Sprague Dawley rats of either gender were included in this study. The rats were randomly and evenly divided into the following four groups： normal control, model, acupuncture and meloxicam groups. Lumbar nerve root compression was induced in rats in the model, acupuncture, and meloxicam groups by inserting a specially made silicon rubber slice at the juncture of the L5 nerve root and the dural sac. The acupuncture needle （pattern number N3030, 30#, 1.5 inch） was purchased from Suzhou Medical Appliance Factory, China. IL-1 enzyme linked immunosorbent assay （ELISA） kit was purchased from Santa Cruz Biotechnology, Inc., USA. METHODS： The acupuncture group was acupunctured at the ＂Huatuojiaji＂ point, which is lateral to the compressed L5-6 nerve root, with an acupuncture depth of 0.5 cm. There were two treatment courses, each of involved seven 20-minute acupuncture sessions, one session a day. The meloxicam group was administered intragastrically 3.75 mg/kg meloxicam （5 mg meloxicam /10 mL physiological saline）. Rats in the normal control group and model group received an intragastric administration of 10 mL/kg physiological saline. All administrations were performed once a day. MAIN OUTCOME MEASURES： At day 14 post-surgery, the IL-1 level in the compressed nerve root was determined by a streptavidin-peroxidase （S-P） immunohistochemical method, and IL-1β mRNA expression in the compressed nerve root was simultaneously detected by real-time reverse transcription-polymerase chain reaction. RESULTS： The expression levels of IL-1 and IL-1β mRNA in the L5 nerve root were significantly higher in the model group than in the control group （P 〈 0.01）. However, the expression levels of IL-1 and IL-1β mRNA were significantly lower in the acupuncture and meloxicam groups than in the model group （P 〈 0.05–0.01）. Expression levels of IL-1 and IL-1β mRNA were significantly higher in the acupuncture group than in the meloxicam group （P 〈 0.01）. CONCLUSION： Acupuncture at the ＂Huatuojiaji＂ point decreases the IL-1 level by inhibiting IL-1β mRNA expression to a greater extent than meloxicam administration.展开更多
With the high-quality development of urban buildings,higher requirements are come up with for lateral bearing capacity of laterally loaded piles.Consequently,a more accurate analysis to predict the lateral response of...With the high-quality development of urban buildings,higher requirements are come up with for lateral bearing capacity of laterally loaded piles.Consequently,a more accurate analysis to predict the lateral response of the pile within an allowable displacement is an important issue.However,the current p-y curve methods cannot fully take into account the pile-soil interaction,which will lead to a large calculation difference.In this paper,a new analytical p-y curve is established and a finite difference method for determining the lateral response of pile is proposed,which can consider the separation effect of pile-soil interface and the coefficient of circumferential friction resistance.In particular,an analytical expression is developed to determine the compressive soil pressure by dividing the compressive soil pressure into two parts:initial compressive soil pressure and increment of compressive soil pressure.In addition,the relationship between compressive soil pressure and horizontal displacement of the pile is established based on the reasonable assumption.The correctness of the proposed method is verified through four examples.Based on the verified method,a parametric analysis is also conducted to investigate the influences of factors on lateral response of the pile,including internal friction angle,pile length and elastic modulus of pile.展开更多
According to the damage mechanism of concrete material during the uniaxial compressive failure process,this paper further establishes the statistical damage constitutive model of concrete subjected to uniaxial compres...According to the damage mechanism of concrete material during the uniaxial compressive failure process,this paper further establishes the statistical damage constitutive model of concrete subjected to uniaxial compressive stress based on the statistical damage model under uniaxial tension. The damage evolution law in the direction subjected to pressure is confirmed by the tensile damage evolution process of lateral deformation due to the Poisson effect,and then the compressive stress-strain relationship is defined. The peak nominal stress state and the critical state occurring in the macro longitudinal distributed splitting cracks are distinguished. The whole loading process can be divided into the even damage phase and the local breakage phase. The concrete specimen is divided into the failure process zone and the resting unloading zone. The size effects during the local breakage phase under the uniaxial monotonic compressive process and the hysteretic phenomenon under the cyclic compressive loading process are analyzed. Finally,the comparison between theoretical results and experimental results preliminarily verifies the rationality and feasibility of understanding the failure mechanism of concrete through the statistical damage constitutional law.展开更多
A two phase model of rock was proposed in order to investigate the mechanism of brittle fracture due to uniaxial compression, in which rock was considered to be a composite material consisting of hard grains and collo...A two phase model of rock was proposed in order to investigate the mechanism of brittle fracture due to uniaxial compression, in which rock was considered to be a composite material consisting of hard grains and colloids. The stress state in colloid region near grains was calculated using Finite Element Method (FEM). The influence of the tensile stresses on the crack initiation and failure process of brittle rock subjected to uniaxial compression was investigated by numerical experiments. The FE results show that tensile stresses are induced easily in the neighboring area of hard grains with the maximum value near grain boundaries. The distribution of tensile stresses depends on the relative position of hard grains. The cracks initiated just near the boundary area of hard grains, which was governed by tensile stress. These results clearly reveal the micro fracture mechanism of brittle rock loaded by uniaxial compression. It can be concluded that the failure mode of brittle rock under uniaxial compression is still tensile fracture from the point view of microstructure. However, since the wide colloid region is still under compressive stress state, further propagation of boundary cracks through this region obviously needs more external load, thus causing the uniaxial compressive strength of rock much higher than its tensile strength obtained via Brazilian (splitting)展开更多
Based on the theory of fluid dynamics in porous media, a numerical model of gas flow in unsaturated zone is developed with the consideration of gas density change due to variation of air pressure. This model is charac...Based on the theory of fluid dynamics in porous media, a numerical model of gas flow in unsaturated zone is developed with the consideration of gas density change due to variation of air pressure. This model is characterized of its wider range of availability. The accuracy of this numerical model is analyzed through comparison with modeling results by previous model with presumption of little pressure variation and the validity of this numerical model is shown. Thus it provides basis for the designing and management of landfill gas control system or soil vapor extraction system in soil pollution control.展开更多
基金This work was supported by Open Fund Project of State Key Laboratory of Intelligent Vehicle Safety Technology by Grant with No.IVSTSKL-202311Key Projects of Science and Technology Research Programme of Chongqing Municipal Education Commission by Grant with No.KJZD-K202301505+1 种基金Cooperation Project between Chongqing Municipal Undergraduate Universities and Institutes Affiliated to the Chinese Academy of Sciences in 2021 by Grant with No.HZ2021015Chongqing Graduate Student Research Innovation Program by Grant with No.CYS240801.
文摘Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro-posed to improve the efficiency for edge inference of Deep Neural Networks(DNNs),existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead,and their efficiency is bounded by the bottleneck of computation latency and memory footprint.To tackle this challenge,we present an efficient inference approach on the basis of PoT quantization and model compression.An integer-only scalar PoT quantization(IOS-PoT)is designed jointly with a distribution loss regularizer,wherein the regularizer minimizes quantization errors and training disturbances.Additionally,two-stage model compression is developed to effectively reduce memory requirement,and alleviate bandwidth usage in communications of networked heterogenous learning systems.The product look-up table(P-LUT)inference scheme is leveraged to replace bit-shifting with only indexing and addition operations for achieving low-latency computation and implementing efficient edge accelerators.Finally,comprehensive experiments on Residual Networks(ResNets)and efficient architectures with Canadian Institute for Advanced Research(CIFAR),ImageNet,and Real-world Affective Faces Database(RAF-DB)datasets,indicate that our approach achieves 2×∼10×improvement in the reduction of both weight size and computation cost in comparison to state-of-the-art methods.A P-LUT accelerator prototype is implemented on the Xilinx KV260 Field Programmable Gate Array(FPGA)platform for accelerating convolution operations,with performance results showing that P-LUT reduces memory footprint by 1.45×,achieves more than 3×power efficiency and 2×resource efficiency,compared to the conventional bit-shifting scheme.
基金support from the Natural Sciences and Engineering Research Council of Canada(NSERC)through the Discovery Grant(Grant No.5808)received in 2019 for his research programsThe third author appreciates the funding from the National Natural Science Foundation of China(Grant No.52378365)Hubei Key Research&Development Program(Grant No.2023BCB112).
文摘This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performed on saturated expansive soil specimens with varying compaction conditions and soil structures under different stress states.Experimental results demonstrate that the specimens expand during freezing and contract during thawing.All specimens converge to the same residual void ratio after seven FT cycles,irrespective of their different initial void ratio,stress state,and soil structure.The compression index of the expansive soil specimens increases with the initial void ratio,whereas their swelling index remains nearly constant.A model extending the disturbed state concept(DSC)is proposed to predict the 1D compression behaviors of FT-impacted soils.The model incorporates a parameter,b,to account for the impacts of FT cycles.Empirical equations have been developed to link the key model parameters(i.e.the normalized yield stress and parameter b)to the soil state parameter(i.e.the normalized void ratio)in order to simplify the prediction approach.The proposed model well predicts the results of the tested expansive soil.In addition,the model’s feasibility for other types of soils,including low-and high-plastic clays,and high-plastic organic soils,has been validated using published data from the literature.The proposed model is simple yet reliable for predicting the compression behaviors of soils subjected to FT cycles.
基金supported by the National Key R&D Program of China(No.2018AAA0100500)the National Natural Science Foundation of China(Nos.62232004 and 61632008)+3 种基金the Jiangsu Provincial Key Laboratory of Network and Information Security(No.BM2003201)the Key Laboratory of Computer Network and Information Integration of Ministry of Education of China(No.93K-9)the Collaborative Innovation Center of Novel Software Technology and Industrializationthe Big Data Computing Center of Southeast University in China for providing the experiment environment and computing facility.
文摘The steel plate is one of the main products in steel industries,and its surface quality directly affects the final product performance.How to detect surface defects of steel plates in real time during the production process is a challenging problem.The single or fixed model compression method cannot be directly applied to the detection of steel surface defects,because it is difficult to consider the diversity of production tasks,the uncertainty caused by environmental factors,such as communication networks,and the influence of process and working conditions in steel plate production.In this paper,we propose an adaptive model compression method for steel surface defect online detection based on expert knowledge and working conditions.First,we establish an expert system to give lightweight model parameters based on the correlation between defect types and manufacturing processes.Then,lightweight model parameters are adaptively adjusted according to working conditions,which improves detection accuracy while ensuring real-time performance.The experimental results show that compared with the detection method of constant lightweight parameter model,the proposed method makes the total detection time cut down by 23.1%,and the deadline satisfaction ratio increased by 36.5%,while upgrading the accuracy by 4.2%and reducing the false detection rate by 4.3%.
基金This work was supported by Natural Science Foundation of Zhejiang Province,China(No.LY21F030018)National Key R&D Program of China(No.2018YFB 1308400).
文摘Automated machine learning(AutoML)pruning methods aim at searching for a pruning strategy automatically to reduce the computational complexity of deep convolutional neural networks(deep CNNs).However,some previous work found that the results of many Auto-ML pruning methods cannot even surpass the results of the uniformly pruning method.In this paper,the ineffectiveness of Auto-ML pruning,which is caused by unfull and unfair training of the supernet,is shown.A deep supernet suffers from unfull training because it contains too many candidates.To overcome the unfull training,a stage-wise pruning(SWP)method is proposed,which splits a deep supernet into several stage-wise supernets to reduce the candidate number and utilize inplace distillation to supervise the stage training.Besides,a wide supernet is hit by unfair training since the sampling probability of each channel is unequal.Therefore,the fullnet and the tinynet are sampled in each training iteration to ensure that each channel can be overtrained.Remarkably,the proxy performance of the subnets trained with SWP is closer to the actual performance than that of most of the previous AutoML pruning work.Furthermore,experiments show that SWP achieves the state-of-the-art in both CIFAR-10 and ImageNet under the mobile setting.
基金supported in part by the Technological Breakthrough Project of Science,Technology and Innovation Commission of Shenzhen Municipality(No.JSGG20201102162000001)InnoHK Initiative of Hong Kong SAR Government,and the Laboratory for AI-Powered Financial Technologies Ltd.
文摘Facial emotion recognition achieves great success with the help of large neural models but also fails to be applied in practical situations due to the large model size of neural methods.To bridge this gap,in this paper,we combine two mainstream model compression methods(pruning and quantization)together,and propose a pruningthen-quantization framework to compress the neural models for facial emotion recognition tasks.Experiments on three datasets show that our model could achieve a high model compression ratio and maintain the model’s high performance well.Besides,We analyze the layer-wise compression performance of our proposed framework to explore its effect and adaptability in fine-grained modules.
文摘Edge Machine Learning(EdgeML)and Tiny Machine Learning(TinyML)are fast-growing fields that bring machine learning to resource-constrained devices,allowing real-time data processing and decision-making at the network’s edge.However,the complexity of model conversion techniques,diverse inference mechanisms,and varied learning strategies make designing and deploying these models challenging.Additionally,deploying TinyML models on resource-constrained hardware with specific software frameworks has broadened EdgeML’s applications across various sectors.These factors underscore the necessity for a comprehensive literature review,as current reviews do not systematically encompass the most recent findings on these topics.Consequently,it provides a comprehensive overview of state-of-the-art techniques in model conversion,inference mechanisms,learning strategies within EdgeML,and deploying these models on resource-constrained edge devices using TinyML.It identifies 90 research articles published between 2018 and 2025,categorizing them into two main areas:(1)model conversion,inference,and learning strategies in EdgeML and(2)deploying TinyML models on resource-constrained hardware using specific software frameworks.In the first category,the synthesis of selected research articles compares and critically reviews various model conversion techniques,inference mechanisms,and learning strategies.In the second category,the synthesis identifies and elaborates on major development boards,software frameworks,sensors,and algorithms used in various applications across six major sectors.As a result,this article provides valuable insights for researchers,practitioners,and developers.It assists them in choosing suitable model conversion techniques,inference mechanisms,learning strategies,hardware development boards,software frameworks,sensors,and algorithms tailored to their specific needs and applications across various sectors.
基金Modern Projects of Traditional Chinese Medicine of Shanghai Science and Technology Commission, No.08DZ1973200Research Projects of Shanghai Bureau of Public Health,No.2006Q004L
文摘BACKGROUND： Varying degrees of inflammatory responses occur during lumbar nerve root compression. Studies have shown that nitric oxide synthase （NOS） and calcitonin gene-related peptide （CGRP） are involved in secondary disc inflammation. OBJECTIVE： To observe the effects of warm acupuncture on the ultrastructure of inflammatory mediators in a rat model of lumbar nerve root compression, including NOS and CGRP contents. DESIGN, TIME AND SETTING： Randomized, controlled study, with molecular biological analysis, was performed at the Experimental Center, Sixth People＇s Hospital Affiliated to Shanghai Jiao Tong University, between September 2006 and April 2007. MATERIALS： Acupuncture needles and refined Moxa grains were purchased from Shanghai Taicheng Technology Development Co., Ltd., China; Mobic tablets were purchased from Shanghai Boehringer Ingelheim Pharmaceuticals Co., Ltd., China; enzyme linked immunosorbent assay （ELISA） kits for NOS and CGRP were purchased from ADL Biotechnology, Inc., USA. METHODS： A total of 50, healthy, adult Sprague-Dawley rats, were randomly divided into five groups normal, model, warm acupuncture, acupuncture, and drug, with 10 rats in each group. Rats in the four groups, excluding the normal group, were used to establish models of lumbar nerve root compression. After 3 days, Jiaji points were set using reinforcing-reducing manipulation in the warm acupuncture group. Moxa grains were burned on each needle, with 2 grains each daily. The acupuncture group was the same as the warm acupuncture group, with the exception of non-moxibustion. Mobic suspension （3.75 mg/kg） was used in the oral drug group, once a day. Treatment of each group lasted for 14 consecutive days. Modeling and medication were not performed in the normal group. MAIN OUTCOME MEASURES： The ultrastructure of damaged nerve roots was observed with transmission electron microscopy; NOS and CGRP contents were measured using ELISA. RESULTS： The changes of the radicular ultramicrostructure were characterized by Wallerian degeneration; nerve fibers were clearly demyelinated; axons collapsed or degenerated; outer Schwann cell cytoplasm was swollen and its nucleus was compacted. Compared with the normal group, NOS and CGRP contents in the nerve root compression zone in the model group were significantly increased （P 〈 0.01）. Nerve root edema was improved in the drug, acupuncture and the warm acupuncture groups over the model group. NOS and CGRP expressions were also decreased with the warm acupuncture group having the lowest concentration （P 〈 0.01）. CONCLUSION： In comparison to the known effects of Mobic drug and acupuncture treatments, the warm acupuncture significantly decreased NOS and CGRP expression which helped improve the ultrastructure of the compressed nerve root.
基金supported by the National Key Research and Development Program of China (No. 2018YFB1003605)Foundations of CARCH (No. CARCH201704)+3 种基金the National Natural Science Foundation of China (No. 61472312)Foundations of Shaanxi Province and Xi’an ScienceTechnology Plan (Nos. B018230008 and BD34017020001)the Foundations of Xidian University (No. JBZ171002)
文摘Despite the rapid development of mobile and embedded hardware, directly executing computationexpensive and storage-intensive deep learning algorithms on these devices’ local side remains constrained for sensory data analysis. In this paper, we first summarize the layer compression techniques for the state-of-theart deep learning model from three categories: weight factorization and pruning, convolution decomposition, and special layer architecture designing. For each category of layer compression techniques, we quantify their storage and computation tunable by layer compression techniques and discuss their practical challenges and possible improvements. Then, we implement Android projects using TensorFlow Mobile to test these 10 compression methods and compare their practical performances in terms of accuracy, parameter size, intermediate feature size,computation, processing latency, and energy consumption. To further discuss their advantages and bottlenecks,we test their performance over four standard recognition tasks on six resource-constrained Android smartphones.Finally, we survey two types of run-time Neural Network(NN) compression techniques which are orthogonal with the layer compression techniques, run-time resource management and cost optimization with special NN architecture,which are orthogonal with the layer compression techniques.
文摘A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.
基金Foundation items： National Basic Research Program of China （2009CB723801） National Natural Science Foundation of China （11072259）
文摘The Spalart-Allmaras （S-A） turbulence model, the shear-stress transport （SST） turbulence model and their compressibility corrections are revaluated for hypersonic compression comer flows by using high-order difference schemes. The compressibility effect of density gradient, pressure dilatation and turbulent Mach number is accounted. In order to reduce confusions between model uncertainties and discretization errors, the formally fifth-order explicit weighted compact nonlinear scheme （WCNS-E-5） is adopted for convection terms, and a fourth-order staggered central difference scheme is applied for viscous terms. The 15° and 34° compression comers at Mach number 9.22 are investigated. Numerical results show that the original SST model is superior to the original S-A model in the resolution of separated regions and predictions of wall pressures and wall heat-flux rates. The capability of the S-A model can be largely improved by blending Catris＇ and Shur＇s compressibility corrections. Among the three corrections of the SST model listed in the present paper, Catris＇ modification brings the best results. However, the dissipation and pressure dilatation corrections result in much larger separated regions than that of the experiment, and are much worse than the original SST model as well as the other two corrections. The correction of turbulent Mach number makes the separated region slightly smaller than that of the original SST model. Some results of low-order schemes are also presented. When compared to the results of the high-order schemes, the separated regions are smaller, and the peak wall pressures and peak heat-flux rates are lower in the region of the reattachment points.
文摘A numerical simulation of shock wave turbulent boundary layer interaction induced by a 24° compression corner based on Gao-Yong compressible turbulence model was presented.The convection terms and the diffusion terms were calculated using the second-order AUSM(advection upstream splitting method) scheme and the second-order central difference scheme,respectively.The Runge-Kutta time marching method was employed to solve the governing equations for steady state solutions.Significant flow separation-region which indicates highly non-isotropic turbulence structure has been found in the present work due to intensity interaction under the 24° compression corner.Comparisons between the calculated results and experimental data have been carried out,including surface pressure distribution,boundary-layer static pressure profiles and mean velocity profiles.The numerical results agree well with the experimental values,which indicate Gao-Yong compressible turbulence model is suitable for the prediction of shock wave turbulent boundary layer interaction in two-dimensional compression corner flows.
基金supported by the National Basic Research Program of China(973 Program)(2011CB808002)the National Natural Science Foundation of China(11371152,11128102,11071086,and 11571117)+3 种基金the Natural Science Foundation of Guangdong Province(S2012010010408)the Foundation for Distinguished Young Talents in Higher Education of Guangdong(2015KQNCX095)the Major Foundation of Hanshan Normal University(LZ201403)the Scientific Research Foundation of Graduate School of South China Normal University(2014ssxm04)
文摘In this article, we consider the blowup criterion for the local strong solution to the compressible fluid-particle interaction model in dimension three with vacuum. We establish a BKM type criterion for possible breakdown of such solutions at critical time in terms of both the L^∞ （0, T; L^6）-norm of the density of particles and the ^L1（0, T; L^∞）-norm of the deformation tensor of velocity gradient.
基金supported in part by the Stable Support Research Project of AECC Sichuan Gas Turbine Establishment,China(No.GJCZ-0013-19)the Open Foundation of State Key Laboratory of Compressor Technology,China(Compressor Technology Laboratory of Anhui Province)(No.SKL-YSJ2020007).
文摘Modeling of a centrifugal compressor is of great significance to surge characteristics and fluid dynamics in the Altitude Ground Test Facilities(AGTF).Real-time Modular Dynamic System Greitzer(MDSG)modeling for dynamic response and simulation of the compression system is introduced.The centrifugal compressor,pipeline network,and valve are divided into pressure output type and mass flow output type for module modeling,and the two types of components alternate when the system is established.The pressure loss and thermodynamics of the system are considered.An air supply compression system of AGTF is modeled and simulated by the MDSG model.The simulation results of mass flow,pressure,and temperature are compared with the experimental results,and the error is less than 5%,which demonstrates the reliability,practicability,and universality of the MDSG model.
基金financially supported by China Postdoctoral Science Foundation (No. 2017M610649)Fundamental Research Funds for the Central Universities (No. 3102017zy001)
文摘Isothermal compression of TC4 alloy was performed on a Thermecmaster-Z simulator at the deformation temperatures ranging from 1093 to 1243 K, the strain rates ranging from 0.001 to 10.000 s^-l and a maximum strain of 0.8. The experimental results show that the flow stress increases with the decrease in the deformation temperature and the increase in the strain rate. The apparent activation energy for deformation is much lower at lower strain rates than that at higher strain rates. The flow stress model considering strain compensation was established. The average relative error between the calculated flow stress and experimental results is about 7.69%, indicating that the present model could be used to accurately predict the flow stress during high temperature in α＋β phase field of TC4 alloy.
基金financially supported by the National Natural Science Foundation of China(Nos.51275415 and50905144)the Natural Science Basic Research Plan in Shanxi Province(No.2011JQ6004)the Program of the Ministry of Education of China for Introducing Talents of Discipline to Universities(No.B08040)
文摘Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.
文摘BACKGROUND：It has been shown that interleukin-1 （IL-1） may cause inflammatory reactions, which stimulate the nerve root of patients with lumbar intervertebral disc protrusion and leads to pain. Whether the clinical curative effects of acupuncture in the treatment of lumbar and leg pain are linked to an inhibition of local IL-1 secretion is unknown. OBJECTIVE： To assess the influence of acupuncture on IL-1, this study was designed to verify the effects of acupuncture at the ＂Huatuojiaji （Extra）＂ point on the nerve root in a rat model of lumbar nerve root compression, compared with administration of meloxicam, a non-steroidal anti-inflammatory drug. DESIGN, TIME AND SETTING： Randomized, controlled, molecular biology experiment, performed at the Experimental Center, Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University between September 2005 and April 2006. MATERIALS： Forty healthy adult Sprague Dawley rats of either gender were included in this study. The rats were randomly and evenly divided into the following four groups： normal control, model, acupuncture and meloxicam groups. Lumbar nerve root compression was induced in rats in the model, acupuncture, and meloxicam groups by inserting a specially made silicon rubber slice at the juncture of the L5 nerve root and the dural sac. The acupuncture needle （pattern number N3030, 30#, 1.5 inch） was purchased from Suzhou Medical Appliance Factory, China. IL-1 enzyme linked immunosorbent assay （ELISA） kit was purchased from Santa Cruz Biotechnology, Inc., USA. METHODS： The acupuncture group was acupunctured at the ＂Huatuojiaji＂ point, which is lateral to the compressed L5-6 nerve root, with an acupuncture depth of 0.5 cm. There were two treatment courses, each of involved seven 20-minute acupuncture sessions, one session a day. The meloxicam group was administered intragastrically 3.75 mg/kg meloxicam （5 mg meloxicam /10 mL physiological saline）. Rats in the normal control group and model group received an intragastric administration of 10 mL/kg physiological saline. All administrations were performed once a day. MAIN OUTCOME MEASURES： At day 14 post-surgery, the IL-1 level in the compressed nerve root was determined by a streptavidin-peroxidase （S-P） immunohistochemical method, and IL-1β mRNA expression in the compressed nerve root was simultaneously detected by real-time reverse transcription-polymerase chain reaction. RESULTS： The expression levels of IL-1 and IL-1β mRNA in the L5 nerve root were significantly higher in the model group than in the control group （P 〈 0.01）. However, the expression levels of IL-1 and IL-1β mRNA were significantly lower in the acupuncture and meloxicam groups than in the model group （P 〈 0.05–0.01）. Expression levels of IL-1 and IL-1β mRNA were significantly higher in the acupuncture group than in the meloxicam group （P 〈 0.01）. CONCLUSION： Acupuncture at the ＂Huatuojiaji＂ point decreases the IL-1 level by inhibiting IL-1β mRNA expression to a greater extent than meloxicam administration.
基金Project(52068004)supported by the National Natural Science Foundation of ChinaProject(2018JJA160134)supported by the Natural Science Foundation of Guangxi Province,ChinaProject(AB19245018)supported by Key Research Projects of Guangxi Province,China。
文摘With the high-quality development of urban buildings,higher requirements are come up with for lateral bearing capacity of laterally loaded piles.Consequently,a more accurate analysis to predict the lateral response of the pile within an allowable displacement is an important issue.However,the current p-y curve methods cannot fully take into account the pile-soil interaction,which will lead to a large calculation difference.In this paper,a new analytical p-y curve is established and a finite difference method for determining the lateral response of pile is proposed,which can consider the separation effect of pile-soil interface and the coefficient of circumferential friction resistance.In particular,an analytical expression is developed to determine the compressive soil pressure by dividing the compressive soil pressure into two parts:initial compressive soil pressure and increment of compressive soil pressure.In addition,the relationship between compressive soil pressure and horizontal displacement of the pile is established based on the reasonable assumption.The correctness of the proposed method is verified through four examples.Based on the verified method,a parametric analysis is also conducted to investigate the influences of factors on lateral response of the pile,including internal friction angle,pile length and elastic modulus of pile.
基金Sponsored by the Program for New Century Excellent Talents in University (NCET-05-0413)the National Natural Science Foundation of China(Grant No.90510018 and 50679006)the China Postdoctoral Science Foundation(Grant No.20090461166)
文摘According to the damage mechanism of concrete material during the uniaxial compressive failure process,this paper further establishes the statistical damage constitutive model of concrete subjected to uniaxial compressive stress based on the statistical damage model under uniaxial tension. The damage evolution law in the direction subjected to pressure is confirmed by the tensile damage evolution process of lateral deformation due to the Poisson effect,and then the compressive stress-strain relationship is defined. The peak nominal stress state and the critical state occurring in the macro longitudinal distributed splitting cracks are distinguished. The whole loading process can be divided into the even damage phase and the local breakage phase. The concrete specimen is divided into the failure process zone and the resting unloading zone. The size effects during the local breakage phase under the uniaxial monotonic compressive process and the hysteretic phenomenon under the cyclic compressive loading process are analyzed. Finally,the comparison between theoretical results and experimental results preliminarily verifies the rationality and feasibility of understanding the failure mechanism of concrete through the statistical damage constitutional law.
文摘A two phase model of rock was proposed in order to investigate the mechanism of brittle fracture due to uniaxial compression, in which rock was considered to be a composite material consisting of hard grains and colloids. The stress state in colloid region near grains was calculated using Finite Element Method (FEM). The influence of the tensile stresses on the crack initiation and failure process of brittle rock subjected to uniaxial compression was investigated by numerical experiments. The FE results show that tensile stresses are induced easily in the neighboring area of hard grains with the maximum value near grain boundaries. The distribution of tensile stresses depends on the relative position of hard grains. The cracks initiated just near the boundary area of hard grains, which was governed by tensile stress. These results clearly reveal the micro fracture mechanism of brittle rock loaded by uniaxial compression. It can be concluded that the failure mode of brittle rock under uniaxial compression is still tensile fracture from the point view of microstructure. However, since the wide colloid region is still under compressive stress state, further propagation of boundary cracks through this region obviously needs more external load, thus causing the uniaxial compressive strength of rock much higher than its tensile strength obtained via Brazilian (splitting)
基金TheResearchFundfortheDoctoralProgramofHighEducation P .R .China(No 980 0 2 712 )
文摘Based on the theory of fluid dynamics in porous media, a numerical model of gas flow in unsaturated zone is developed with the consideration of gas density change due to variation of air pressure. This model is characterized of its wider range of availability. The accuracy of this numerical model is analyzed through comparison with modeling results by previous model with presumption of little pressure variation and the validity of this numerical model is shown. Thus it provides basis for the designing and management of landfill gas control system or soil vapor extraction system in soil pollution control.
