Finite Element Simulations on Failure Behaviors of Granular Materials with Microstructures Using a Micromechanics-Based Cosserat Elastoplastic Model

This paper presents a micromechanics-based Cosserat continuum model for microstructured granular materials.By utilizing this model,the macroscopic constitutive parameters of granular materials with different microstructures are expressed as sums of microstructural information.The microstructures under consideration can be classified into three categories:a medium-dense microstructure,a dense microstructure consisting of one-sized particles,and a dense microstructure consisting of two-sized particles.Subsequently,the Cosserat elastoplastic model,along with its finite element formulation,is derived using the extended Drucker-Prager yield criteria.To investigate failure behaviors,numerical simulations of granular materials with different microstructures are conducted using the ABAQUS User Element(UEL)interface.It demonstrates the capacity of the proposed model to simulate the phenomena of strain-softening and strain localization.The study investigates the influence of microscopic parameters,including contact stiffness parameters and characteristic length,on the failure behaviors of granularmaterials withmicrostructures.Additionally,the study examines themesh independence of the presented model and establishes its relationship with the characteristic length.A comparison is made between finite element simulations and discrete element simulations for a medium-dense microstructure,revealing a good agreement in results during the elastic stage.Somemacroscopic parameters describing plasticity are shown to be partially related to microscopic factors such as confining pressure and size of the representative volume element.

Effect of Water Absorption on the Mechanical Property and Failure Mechanism of Hollow Glass Microspheres Composite Epoxy Resin Solid Buoyancy Materials

To study the water absorption of hollow glass microspheres(HGMs)composite epoxy resin solid buoyancy materials in the marine environment and its effect on the mechanical properties,the water absorption was measured by immersing the material in distilled water for 36 days at ambient temperature and fitted to Fick’s second law.The strength of materials before and after water absorption were tested by uniaxial experiments,and the effects of the filling ratio and water absorption on the mechanical properties of the materials were analyzed and explained.Finally,the failure modes and mechanism of the hollow glass microspheres composite material were explicated from the microscopic level by scanning electron microscope(SEM).This research will help solve the problems of solid buoyancy materials in ocean engineering applications.

Failure Characteristics of Rock-like Mortar Specimens with Arc-shaped Flaws under Freezing-thaw Cycles and Uniaxial Compression

To investigate the freeze-thaw(F-T)damages and failure characteristics of rock mass with arc-shaped joints in cold regions,three types of cement mortar specimens with different central angles and prefabricated arc-shaped flaws are subjected to uniaxial compressive tests under different F-T cycles.Experimental observations show that the uniaxial compressive strength of specimens are significantly influenced by F-T cycles and their failure modes are mainly affected by the central angleαof the prefabricated flaws.Unlike the specimens with a central angle of 60°,the specimens with a central angle of 120°and 180°have greater curvature of flaws,so tensile cracks occur in the arc-top area of their prefabricated flaws.According to experimental images observed by environmental scanning electron microscope(ESEM),as the number of F-T cycles increases,the deterioration effect of the specimen becomes more obvious,which is specifically reflected in the increase of the mass loss,peak stress loss,and damage variables as a power function,and the peak strain decreases as a quadratic polynomial.According to numerical results using two-dimensional particle flow code(PFC2D),it is found that F-T cycles cause more damage to the specimen in the early stages than in the later ones.The area of the concentrated compressive stress zone in the middle is decreased due to the increased number of F-T cycles,while the area of the surrounding tensile-shear stress zone is increased.The models appear different failure modes due to the release of concentrated stress in different tensile-shear zones.

Internal failure of anode materials for lithium batteriesd——A critical review

Prevention of mechanical and finally electrochemical failures of lithium batteries is a critical aspect to be considered during their design and performance, especially for those with high specific capacities. Internal failure is observed as one of the most serious factors, including loss of electrode materials, structure deformation and dendrite growth. It usually incubates from atomic/molecular level and progressively aggravates along with lithiation. Understanding the internal failure is of great importance for developing solutions of failure prevention and advanced anode materials. In this research, different internal failure processes of anode materials for lithium batteries are discussed. The progress on observation technologies of the anode failure is further summarized in order to understand their mechanisms of internal failure. On top of them, this review aims to summarize innovative methods to investigate the anode failure mechanisms and to gain new insights to develop advanced and stable anodes for lithium batteries.

Test selection and optimization for PHM based on failure evolution mechanism model

The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.

Failure characteristics of Ag-SnO_2 contact material in AC level

The failure characteristics of the contact material Ag-SnO2 were investigated by X-ray diffraction（XRD）,scanning electron microscopy（SEM）,and X-ray energy dispersive spectroscopy（EDS）.Phase analysis showed that there were Ag,SnO2,and Sn on the contact surfaces at the time of failure under the load condition of 30 A and 220 V（AC）,which means that SnO2 decomposed in service.When the contacts were tested under airproof ambient condition,half-spherical bulges came into being on the contact surfaces,which resulted in early failure and dispersive characteristics.But half-spherical bulges were not found when the contacts were tested under open ambient condition.The temperature change of the contacts during the life testing under airproof ambient condition was different from that under open ambient condition.

New double yield surface model for coarse granular materials incorporating nonlinear unified failure criterion

A new double-yield-sarface （DYS） model was developed to characterize the strength and deformation behaviors of coarse granular materials （CGMs）. Two kinds of deformation mechanisms, including the shear and compressive plastic deformation, were taken into account in this model, These two deformation mechanisms were described by the shear and compressive yield functions, respectively. The Lode angle dependent formulations of proposed model were deduced by incorporating a 3D nonlinear unified failure criterion. Some comparisons were presented between the numerical predictions of proposed model and test data of true triaxial tests on the modeled rockfills. The model predictions are in good agreement with the test data and capture the strain hardening and plastic volumetric dilation of CGMs. These findings verify the reasonability of current DYS model, and indicate that this model is well suited to reproduce the stress-strain-volume change behavior of CGMs in general.

Decision making tools for optimal material selection:A review

The present work reviews different decision making tools(material comparing and choosing tools)used for selecting the best material considering different parameters.In this review work,the authors have tried to address the following important enquiries:1)the engineering applications addressed by the different material choosing and ranking methods;2)the predominantly used decision making tools addressing the optimal material selection for the engineering applications;3)merits and demerits of decision making tools used;4)the dominantly used criteria or objectives considered while selecting a suitable alternative material;5)overview of DEA on material selection field.The authors have surveyed literatures from different regions of the globe and considered literatures since 1988.The present review not only stresses the importance of material selection in the early design stage of the product development but also aids the design and material engineers to apply different decision making tools systematically.

ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples, the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

PROGRESSIVE FAILURE ANALYSIS OF LAMINATED COMPOSITES WITH TRANSVERSE SHEAR EFFECTS

This paper deals with the progressive failure analysis of composite laminates. Triangular elements which include the transverse shear effects are us.d for the stress analysis. A new method for the calculation of the shear correction factors is presented. Several failure criteria are used to check the first ply failure and distinguish the laminate failure modes into fiber breakage or buckling, matrix cracking and delamination. After the failure is detected, the stiffness of the failed ply is modified according to the failure modes. The ultimate strength of the laminate is obtained by an iterative way. Several examples are given in the paper for stress analysis and progressive failure analysis of composite laminates.

Concurrent Material Selection of Natural Fibre Filament for Fused Deposition Modeling Using Integration of Analytic Hierarchy Process/Analytic Network Process

The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments.Moreover,selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites.It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements.Therefore,in this study,integration of the Analytic Hierarchy Process(AHP)/Analytic Network Process(ANP)has been introduced in selecting the natural fibres based in different clusters of selection concurrently.The selection process has been performed based on the interdependency among the selection criteria.Pairwise comparison matrices are constructed based on AHP’s hierarchical model and super matrices are constructed based on the ANP’s network model.As a result,flax fibre has ranked at the top of the selection by scored 19.5%from the overall evaluation.Flax fibre has excellent material properties and been found in various natural fibre composite applications.Further investigation is needed to study the compatibility of this fibre to be reinforced with a thermoplastic polymer matrix to develop a resultant natural fibre composite filament for fused deposition modeling.

Sine Trigonometry Operational Laws for Complex Neutrosophic Sets and Their Aggregation Operators in Material Selection

In this paper,sine trigonometry operational laws(ST-OLs)have been extended to neutrosophic sets(NSs)and the operations and functionality of these laws are studied.Then,extending these ST-OLs to complex neutrosophic sets(CNSs)forms the core of thiswork.Some of themathematical properties are proved based on ST-OLs.Fundamental operations and the distance measures between complex neutrosophic numbers(CNNs)based on the ST-OLs are discussed with numerical illustrations.Further the arithmetic and geometric aggregation operators are established and their properties are verified with numerical data.The general properties of the developed sine trigonometry weighted averaging/geometric aggregation operators for CNNs(ST-WAAO-CNN&ST-WGAO-CNN)are proved.A decision making technique based on these operators has been developed with the help of unsupervised criteria weighting approach called Entropy-ST-OLs-CNDM(complex neutrosophic decision making)method.A case study for material selection has been chosen to demonstrate the ST-OLs of CNDM method.To check the validity of the proposed method,entropy based complex neutrosophic CODAS approach with ST-OLs has been executed numerically and a comparative analysis with the discussion of their outcomes has been conducted.The proposed approach proves to be salient and effective for decision making with complex information.

A Failure Sample Selection Method Based on Failure Pervasion Intensity

The complex and uncertain relationship among failures was always ignored in failure sample selection based on traditional testability demonstration experimental method. A failure pervasion model is founded based on fuzzy probability Petri net (FPPN) which can depict the propagation and pervasion relation among failures,then failure pervasion intensity is defined,the process of failure pervasion was depicted based on k-step fault pervasion algorithm and the pervasion intensity was expressed by a value. The method of sample selection based on failure pervasion intensity and failure rate is introduced into the process of sample selection. The practical application shows that the sample set selected based on failure pervasion intensity and failure rate can represent the failure set adequately.

Fully umbilical cord-derived adhesive materials enable to recruit and segregate immune cells for the reversal of acute liver failure

Inflammatory cytokine storms can trigger disease exacerbation and even death and have reached a consensus in the clinical treatment of acute organ failure.However,the existing strategies remain a great challenge to efficiently suppress inflammatory cytokine storms for promoting organ repair and regeneration.Herein,fully human umbilical cord(UC)-derived adhesive materials(UCAM)that integrate decellularized extracellular matrix(ECM)nanofiber hydrogel and homologous mesenchymal stem cells(MSCs)are demonstrated to greatly suppress inflammatory cytokine storms,demonstrating high efficacy in treating acute liver failure(ALF)in rats with 90%hepatectomy.The UC-derived adhesive materials have the capacity to secrete a significant quantity of cytokines by MSCs to recruit activated immune cells to migrate into their ECM nanofiber networks,segregating them away from the infection area and thereby greatly suppressing the inflammatory cytokine storms.As expected,the UC-derived adhesive materials can significantly promote hepatocyte proliferation to achieve functional recovery and regeneration of the liver,significantly improving the survival rate in rats.Our fully human UC-derived adhesive materials provide a new avenue in suppressing inflammatory cytokine storms for promoting organ regeneration that would be really utility in clinical organ transplantation-related treatment.

Effect of inclusion size on the high cycle fatigue strength and failure mode of a high V alloyed powder metallurgy tool steel

The fatigue strength of a high V alloyed powder metallurgy tool steel with two different inclusion size levels, tempered at different temperatures, was investigated by a series of high cycle fatigue tests. It was shown that brittle inclusions with large sizes above 30μm prompted the occurrence of subsurface crack initiation and the reduction in fatigue strength. The fracture toughness and the stress amplitude both exerted a significant influence on the fish-eye size. A larger fish-eye area would form in the sample with a higher fracture toughness subjected to a lower stress amplitude. The stress intensity factor of the inclusion was found to lie above a typical value of the threshold stress intensity factor of 4 MPa.m^1/2. The fracture toughness of the sample with a hardness above HRC 56 could be estimated by the mean value of the stress intensity factor of the fish-eye. According to fractographic evaluation, the critical inclusion size can be calculated by linear fracture mechanics.

A Deep Learning-Based Computational Algorithm for Identifying Damage Load Condition: An Artificial Intelligence Inverse Problem Solution for Failure Analysis

In this work,we have developed a novel machine(deep)learning computational framework to determine and identify damage loading parameters(conditions)for structures and materials based on the permanent or residual plastic deformation distribution or damage state of the structure.We have shown that the developed machine learning algorithm can accurately and(practically)uniquely identify both prior static as well as impact loading conditions in an inverse manner,based on the residual plastic strain and plastic deformation as forensic signatures.The paper presents the detailed machine learning algorithm,data acquisition and learning processes,and validation/verification examples.This development may have significant impacts on forensic material analysis and structure failure analysis,and it provides a powerful tool for material and structure forensic diagnosis,determination,and identification of damage loading conditions in accidental failure events,such as car crashes and infrastructure or building structure collapses.

Left ventricular assist devices as destination therapy in stage D heart failure

1 Introduction? Mechanical circulatory support (MCS) has increasingly become an important management opportunity for patients with stage D heart failure (HF) with remarkable impact on patient survival and quality of life. Early clinical trials have demonstrated improved outcomes of durable left ventricular assist device (LVAD) support compared with optimal medical management.[1] As technology advanced, continuous flow LVADs outperformed pulsatile flow devices in clinical trials and the field migrated to HeartMate (Abbott Laboratories, Abbott Park, IL) and HeartWare (Medtronic, Minneapolis, MN) devices due to their clinical superiority. Among the continuous flow devices.

Mechanical properties of crosslinks controls failure mechanism of hierarchical intermediate filament networks

Intermediate filaments are one of the key components of the cytoskeleton in eukaryotic cells, and their mechanical properties are found to be equally important for physiological function and disease. While the mechanical properties of single full length filaments have been studied, how the mechanical properties of crosslinks affect the mechanical property of the intermediate filament network is not well understood. This paper applies a mesoscopic model of the intermediate network with varied crosslink strengths to investigate its failure mechanism under the extreme mechanical loading. It finds that relatively weaker crosslinks lead to a more flaw tolerant intermediate filament network that is also 23% stronger than the one with strong crosslinks. These findings suggest that the mechanical properties of interfacial components are critical for bioinspired designs which provide intriguing mechanical properties.

Rock parameters inversion for estimating the maximum heights of two failure zones in overburden strata of a coal seam

In order to enter effective parameters of rock mass in a numerical model,the relationships between mechanical parameters of rock and rock mass were obtained by an inversion method and an orthogonal test,given our measurements of the maximum heights of two failure zones in the Longdong coal mine. Using the maximum heights of the caving zone and the water-conducting fractured zone as test indices the modulus of elasticity,the Poisson ratio,cohesion and tension strength as test factors and different values of reduction enhancement factors as test levels,an orthogonal test was designed to obtain an optimum simulation scheme.From the analysis of different values of reduction enhancement factors which affect the test indices,an optimum factor combination for modification of parameters could be inferred.By using modified parameters in our numerical simulation,the maximum heights of the caving zone and the water-conducting fractured zone in the extensive Xiyi area were determined as 15.06 m and 36.92 m.These values were almost the same as those obtained by similar material simulation（8.5 m and 37.0 m）and empirical prediction（8.4 m and 34.4 m）.These results indicate that the modification of parameters is a rational method.

Construction of Parsimonious Event Risk Scores by an Ensemble Method. An Illustration for Short-Term Predictions in Chronic Heart Failure Patients from the GISSI-HF Trial

Selecting which explanatory variables to include in a given score is a common difficulty, as a balance must be found between statistical fit and practical application. This article presents a methodology for constructing parsimonious event risk scores combining a stepwise selection of variables with ensemble scores obtained by aggregation of several scores, using several classifiers, bootstrap samples and various modalities of random selection of variables. Selection methods based on a probabilistic model can be used to achieve a stepwise selection for a given classifier such as logistic regression, but not directly for an ensemble classifier constructed by aggregation of several classifiers. Three selection methods are proposed in this framework, two involving a backward selection of the variables based on their coefficients in an ensemble score and the third involving a forward selection of the variables maximizing the AUC. The stepwise selection allows constructing a succession of scores, with the practitioner able to choose which score best fits his needs. These three methods are compared in an application to construct parsimonious short-term event risk scores in chronic HF patients, using as event the composite endpoint of death or hospitalization for worsening HF within 180 days of a visit. Focusing on the fastest method, four scores are constructed, yielding out-of-bag AUCs ranging from 0.81 (26 variables) to 0.76 (2 variables).