DYNAMIC STABILITY OF SPINDLE BLADE IN RING SPINNING Zhou Bingrong(Department of Mechanical Engineering)

It is discussed that a tangential force T induces a self-excited vibration in the motion ofspindle blades of a ring spinning frame.Depending on the relative magnitude of the tangentialforce compared with the tangential damping force the motion of blade is either stable orunstable.The chief factors causing the self-excited vibration can also be traced from the charac-ter of the experimental locus.

Spark Plasma Sintering of Mg-based Alloys:Microstructure,Mechanical Properties,Corrosion Behavior,and Tribological Performance

Within the past ten years,spark plasma sintering(SPS)has become an increasingly popular process for Mg manufacturing.In the SPS process,interparticle diffusion of compressed particles is rapidly achieved due to the concept of Joule heating.Compared to traditional and additive manufacturing(AM)techniques,SPS gives unique control of the structural and microstructural features of Mg components.By doing so,their mechanical,tribological,and corrosion properties can be tailored.Although great advancements in this field have been made,these pieces of knowledge are scattered and have not been contextualized into a single work.The motivation of this work is to address this scientific gap and to provide a groundwork for understanding the basics of SPS manufacturing for Mg.To do so,the existing body of SPS Mg literature was first surveyed,with a focus on their structural formation and degradation mechanisms.It was found that successful Mg SPS fabrication highly depended on the processing temperature,particle size,and particle crystallinity.The addition of metal and ceramic composites also affected their microstructural features due to the Zener pinning effect.In degradative environments,their performance depends on their structural features and whether they have secondary phased composites.In industrial applications,SPS'd Mg was found to have great potential in biomedical,hydrogen storage,battery,automotive,and recycling sectors.The prospects to advance the field include using Mg as a doping agent for crystallite size refinement and using bulk metallic Mg-based glass powders for amorphous SPS components.Despite these findings,the interactions of multi-composites on the processing-structure-property relationships of SPS Mg is not well understood.In total,this work will provide a useful direction in the SPS field and serve as a milestone for future Mg-based SPS manufacturing.

Predicting the Mechanical Behavior of a Bioinspired Nanocomposite through Machine Learning

The bioinspired nacre or bone structure represents a remarkable example of tough,strong,lightweight,and multifunctional structures in biological materials that can be an inspiration to design bioinspired high-performance materials.The bioinspired structure consists of hard grains and soft material interfaces.While the material interface has a very low volume percentage,its property has the ability to determine the bulk material response.Machine learning technology nowadays is widely used in material science.A machine learning model was utilized to predict the material response based on the material interface properties in a bioinspired nanocomposite.This model was trained on a comprehensive dataset of material response and interface properties,allowing it to make accurate predictions.The results of this study demonstrate the efficiency and high accuracy of the machine learning model.The successful application of machine learning into the material property prediction process has the potential to greatly enhance both the efficiency and accuracy of the material design process.

Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based SOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(SVR)were applied to estimate SOH,and root mean square error(RMSE)was used to evaluate and compare the estimation performance.The results showed that the feature selection pipeline can improve SOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and SVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on SOH estimation performance and tries to fill the gap of effective SOH estimation between theoretical study and real dynamic application.

Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.

Influence of layer thickness on formation quality,microstructure,mechanical properties,and corrosion resistance of WE43 magnesium alloy fabricated by laser powder bed fusion

Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.

Squeeze casting for metal alloys and composites:An overview of influence of process parameters on mechanical properties and microstructure

Squeeze casting is a well-established and reliable process for fabricating high-integrity metallic alloys,bimetals,and composites.The quality and high performance of squeeze cast components are dependent on optimum casting conditions.Inappropriate selection of parameter values may adversely affect the quality of the casting.The squeeze cast components are generally subjected to secondary processing such as heat treatment,extrusion,and other bulk deformation processes to improve the microstructural features and mechanical properties.Heat treatment further refines the grains and reduces porosity,consequently improving tensile strength,and hardness;however,ductility decreases.This paper provides a comprehensive review on studies concerning the influence of processing parameters on porosity,density,percentage elongation,strength,hardness,wear,and fracture of squeeze casting alloys,aiming to provide sufficient information on the squeeze casting process and the effects of processing parameters on product quality.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the ondemand necessity to perform surgery during space missions.Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing.Among all 3D printing techniques,fused deposition modelling(FDM)is a low-cost and more rapid printing technique.This article proposes the fabrication of surgical instruments,namely,forceps and hemostat using the fused deposition modeling(FDM)process.Excellent mechanical properties are the only indicator to judge the quality of the functional parts.The mechanical properties of FDM-processed parts depend on various process parameters.These parameters are layer height,infill pattern,top/bottom pattern,number of top/bottom layers,infill density,flow,number of shells,printing temperature,build plate temperature,printing speed,and fan speed.Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid(PLA)parts printed by FDM.The experiments have performed through Taguchi’s L27orthogonal array(OA).Variance analysis(ANOVA)ascertains the significance of the process parameters and their percent contributions to the evaluation indexes.Finally,as a multiobjective optimization technique,grey relational analysis(GRA)obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties.Scanning electron microscopy(SEM)examines the types of defects and strong bonding between rasters.The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength(42.6 MPa)and modulus of elasticity(3274 MPa).

Influence of tool rotational speed on mechanical and corrosion behaviour of friction stir processed AZ31/Al_(2)O_(3)nanocomposite

Nano-sized reinforcements improved the mechanical characteristics efficiently by promoting more implicit particle hardening mechanisms compared to micron-sized reinforcements.Nano-sized particles lessen the critical particle solidification velocity for swamp and thus offers better dispersal.In the present investigation,the friction stir processing(FSP)is utilized to produce AZ31/Al_(2)O_(3)nanocomposites at various tool rotation speeds(i.e.,900,1200,and 1500 rpm)with an optimized 1.5%volume alumina(Al_(2)O_(3))reinforcement ratio.The mechanical and corrosion behavior of AZ31/Al_(2)O_(3)-developed nanocomposites was investigated and compared with that of the AZ31 base alloy.The AZ31 alloy experienced a comprehensive dynamic recrystallization during FSP,causing substantial grain refinement.Grain-size strengthening is the primary factor contributed to the enhancement in the strength of the fabricated nanocomposite.Tensile strength and yield strength values were lower than those for the base metal matrix,although an upward trend in both values has been observed with an increase in tool rotation speed.An 19.72%increase in hardness along with superior corrosion resistance was achieved compared to the base alloy at a tool rotational speed of 1500 rpm.The corrosion currents(Jcorr)of all samples dropped with increase in the rotational speed,in contrast to the corrosion potentials(Ecorr),which increased.The values of Jcorr of AZ31/Al_(2)O_(3)were 42.3%,56.8%,and 65.5%lower than those of AZ31 alloy at the chosen rotating speeds of 900,1200,and 1500 rpm,respectively.The corrosion behavior of friction stir processed nanocomposites have been addressed in this manuscript which has not been given sufficient attention in the existing literature.Further,this work offers an effective choice for the quality assurance of the FSP process of AZ31/Al_(2)O_(3)nanocomposites.The obtained results are relevant to the development of lightweight automobile and aerospace structures and components.

Microstructure and mechanical properties of curved AZ31 magnesium alloy profiles produced by differential velocity sideways extrusion

Lightweight curved profiles are widely utilised in the transportation industry considering the increasing need for improving aerodynamic efficiency,aesthetics and cutting emissions.In this paper,curved AZ31 Mg alloy profiles were manufactured in one operation by a novel process,differential velocity sideways extrusion(DVSE),in which two opposed rams were used.Effects of extrusion temperature and velocity(strain rate) on curvature,microstructure,and mechanical properties of the formed profiles were examined.Profile curvature was found to be more readily controlled by the velocity ratio of the bottom ram v2to the top ram v1,whereas extrusion temperature(T=250,300,350℃)and extrusion velocity(v_(1)=0.1,1 mm/s) slightly affect curvature for a given velocity ratio.A homogeneous microstructure with equiaxed grains(~4.5 μm) resulted from dynamic recrystallisation(DRX),was observed after DVSE(v_(2)/v_(1)=1/2) at 300 ℃ and v_(1)=0.1 mm/s,where the initial billet had an average grain size of ~25 um.Increasing extrusion temperature leads to grain growth(~5 μm) at 350 ℃ and v_(1)=0.1 mm/s.DRX is incomplete at the relatively low temperature of 250℃(v_(1)=0.1 mm/s),and higher strain rate with v1=1mm/s(T=300℃),resulting in inhomogeneous bi-modal necklace pattern grains ranging in size around 1-25 μm for the former and 2-20μm for the latter.Grain refinement is attributed to DRX during the severe plastic deformation(SPD) arising in DVSE,and initiates at the prior boundaries of coarse grains in a necklace-like manner.Compared with the billet,micro-hardness and ultimate tensile strength of the profiles have been enhanced,which is compatible with grain refinement.Also,an obvious increase in tensile ductility was found.However,yield strength slightly decreases except for the complete DRXed case(300℃,v_(1)=0.1 mm/s),where a slightly higher value was found,indicating strengthening by grain refinement is greater than softening caused by texture modification.The initial billet had a strong basal texture wherein the {0002} basal plane is oriented parallel to the extrusion direction(’hard’ orientation),while DVSE results in the profiles having weak basal textures and the {0002} basal plane oriented ~5-10° to the extrusion direction(i.e.towards the orientation for easier slip).This significantly modified texture contributes to the softening of the profiles in the extrusion direction,in which tensile tests were performed,and the related elongation improvement.

Effect of deep cryogenic treatment on the microstructural,mechanical and ballistic properties of AA7075-T6 aluminum alloy

The study focused on investigating the effect of Deep Cryogenic Treatment(DCT)on the mechanical and ballistic properties of AA7075-T6 aluminum alloy.The microstructure,microhardness,tensile strength,and impact strength of the Base Material(BM)and DCT-treated 7075 samples were analyzed through metallographic analysis and mechanical tests.The microstructure of the DCT-treated 7075 samples revealed fine grains and a distribution of secondary phase particles.The tensile strength,impact strength,and microhardness of DCT-treated samples increased by 7.41%,4%,and 9.68%,respectively,compared to the BM samples.The fractography analysis of the tensile samples showed cleavage facets,microvoids,and dimples in both the samples.The ballistic behavior of the BM and DCT target plates were studied by impacting hard steel core projectiles at a velocity of 750±10 m/s.The target plates failed due to petaling and ductile hole enlargement,and the depth of penetration(DOP)of the DCT target was less than that of the BM target,indicating a higher ballistic resistance.The post-ballistic microstructure examination of the target plates showed the formation of an Adiabatic Shear Band(ASB)without any cracks.It was concluded that the DCT treatment improved the mechanical and ballistic properties of the aluminum alloy due to grain refinement and high dislocation density.

Simultaneous enhancement of mechanical properties and corrosion resistance of as-cast Mg-5Zn via microstructural modification by friction stir processing

Magnesium alloys are ideal lightweight materials;however,their applications are extremely limited due to their low strength,poor ductility,and weak corrosion resistance.In the present study,a friction stir processing(FSP)treatment was employed to optimize the mechanical properties and corrosion resistance of an as-cast Mg-5Zn alloy.The average grain size of the Mg-5Zn alloy was refined from 133.8μm to1.3μm as a result of FSP.Along different directions,FSP exhibited the enhancement effects on different mechanical properties.Furthermore,according to the potentiodynamic polarization results,the corrosion current density at the free-corrosion potential of the FSPed sample,was 4.1×10^(-6)A/cm^(2)in 3.5 wt.%Na Cl aqueous solution,which was significantly lower than that of the as-cast sample.Electrochemical impedance spectroscopy revealed that the polarization impedance,Rp,of the FSPed sample was 1534Ω/cm^(2)in 3.5 wt.%NaCl aqueous solution,which was 71.4%greater than that of the as-cast sample.The corrosion morphology of the FSPed sample in 3.5 wt.%NaCl aqueous solution exhibited largely uniform corrosion,rather than severe localized corrosion characteristics,which further reduced the corrosion depth on the basis of reducing the corrosion current density.The results presented herein indicate that FSP is a viable technique for simultaneously improving the mechanical properties and corrosion resistance of the as-cast Mg-5Zn alloy.

Implications of twinning on the microstructure development,crystallographic texture and mechanical performance of Mg alloys-a critical review

Deformation twinning is profusely activated in the Mg alloys due to lower critical resolved shear stress(CRSS) compared to the non-basal slip systems(prismatic and pyramidal ) and plays a significant role in texture reorientation, grain refinement and enhancement of mechanical performance. Twinning is a sequential process comprising twin nucleation, twin propagation and twin growth, hence several intrinsic and extrinsic parameters that facilitate or suppress the process have been critically reviewed. The dependence of twinning on the grain size, deformation temperature, favorable grain orientation and shear strain have been thoroughly discussed in the context of published literature and an attempt has been made to provide a benchmark conclusive finding based on the majority of works. Furthermore, the subsequent effect of twinning on the mechanical performance of Mg alloys, including ductility, formability and tension-compression asymmetry has been discussed in detail. Lastly, the stability of twins, including stress and thermal stability, is summarized and critical issues related to pertinent bottlenecks have been addressed.

Auxetic mechanical metamaterials: from soft to stiff

Auxetic mechanical metamaterials are artificially architected materials that possess negative Poisson’s ratio,demonstrating transversal contracting deformation under external vertical compression loading.Their physical properties are mainly determined by spatial topological configurations.Traditionally,classical auxetic mechanical metamaterials exhibit relatively lower mechanical stiffness,compared to classic stretching dominated architectures.Nevertheless,in recent years,several novel auxetic mechanical metamaterials with high stiffness have been designed and proposed for energy absorption,load-bearing,and thermal-mechanical coupling applications.In this paper,mechanical design methods for designing auxetic structures with soft and stiff mechanical behavior are summarized and classified.For soft auxetic mechanical metamaterials,classic methods,such as using soft basic material,hierarchical design,tensile braided design,and curved ribs,are proposed.In comparison,for stiff auxetic mechanical metamaterials,design schemes,such as hard base material,hierarchical design,composite design,and adding additional load-bearing ribs,are proposed.Multi-functional applications of soft and stiff auxetic mechanical metamaterials are then reviewed.We hope this study could provide some guidelines for designing programmed auxetics with specified mechanical stiffness and deformation abilities according to demand.

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection,a fundamental process that enables the transfer of mass,energy,and momentum from the solar wind into the magnetosphere.The spatial and temporal properties of the magnetopause,under varying solar and magnetospheric conditions,remain largely unknown because empirical studies using in-situ observations are challenging to interpret.Global wide field-of-view(FOV)imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and,subsequently,quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere.Two upcoming missions,ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays,an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms.High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary,the magnetopause,and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation.This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and,with this,identify the location of the magnetopause over the Sun−Earth line.To do so,we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information.Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images.Also,our proposed methodology shows that the accuracy of both three-dimensional(3-D)estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Dynamic and electrical responses of a curved sandwich beam with glass reinforced laminate layers and a pliable core in the presence of a piezoelectric layer under low-velocity impact

The dynamic responses and generated voltage in a curved sandwich beam with glass reinforced laminate(GRL)layers and a pliable core in the presence of a piezoelectric layer under low-velocity impact(LVI)are investigated.The current study aims to carry out a dynamic analysis on the sandwich beam when the impactor hits the top face sheet with an initial velocity.For the layer analysis,the high-order shear deformation theory(HSDT)and Frostig's second model for the displacement fields of the core layer are used.The classical non-adhesive elastic contact theory and Hunter's principle are used to calculate the dynamic responses in terms of time.In order to validate the analytical method,the outcomes of the current investigation are compared with those gained by the experimental tests carried out by other researchers for a rectangular composite plate subject to the LVI.Finite element(FE)simulations are conducted by means of the ABAQUS software.The effects of the parameters such as foam modulus,layer material,fiber angle,impactor mass,and its velocity on the generated voltage are reviewed.

Free vibration and buckling analysis of polymeric composite beams reinforced by functionally graded bamboo fbers

Natural fibers have been extensively researched as reinforcement materials in polymers on account of their environmental and economic advantages in comparison with synthetic fibers in the recent years.Bamboo fibers are renowned for their good mechanical properties,abundance,and short cycle growth.As beams are one of the fundamental structural components and are susceptible to mechanical loads in engineering applications,this paper performs a study on the free vibration and buckling responses of bamboo fiber reinforced composite(BFRC)beams on the elastic foundation.Three different functionally graded(FG)layouts and a uniform one are the considered distributions for unidirectional long bamboo fibers across the thickness.The elastic properties of the composite are determined with the law of mixture.Employing Hamilton’s principle,the governing equations of motion are obtained.The generalized differential quadrature method(GDQM)is then applied to the equations to obtain the results.The achieved outcomes exhibit that the natural frequency and buckling load values vary as the fiber volume fractions and distributions,elastic foundation stiffness values,and boundary conditions(BCs)and slenderness ratio of the beam change.Furthermore,a comparative study is conducted between the derived analysis outcomes for BFRC and homogenous polymer beams to examine the effectiveness of bamboo fibers as reinforcement materials,demonstrating the significant enhancements in both vibration and buckling responses,with the exception of natural frequencies for cantilever beams on the Pasternak foundation with the FG-◇fiber distribution.Eventually,the obtained analysis results of BFRC beams are also compared with those for carbon nanotube reinforced composite(CNTRC)beams found in the literature,indicating that the buckling loads and natural frequencies of BFRC beams are lower than those of CNTRC beams.

Effect of Interface Form on Creep Failure and Life of Dissimilar Metal Welds Involving Nickel-Based Weld Metal and Ferritic Base Metal

For dissimilar metal welds(DMWs)involving nickel-based weld metal(WM)and ferritic heat resistant steel base metal(BM)in power plants,there must be an interface between WM and BM,and this interface suffers mechanical and microstructure mismatches and is often the rupture location of premature failure.In this study,a new form of WM/BM interface form,namely double Y-type interface was designed for the DMWs.Creep behaviors and life of DMWs containing double Y-type interface and conventional I-type interface were compared by finite element analysis and creep tests,and creep failure mechanisms were investigated by stress-strain analysis and microstructure characterization.By applying double Y-type interface instead of conventional I-type interface,failure location of DMW could be shifted from the WM/ferritic heat-affected zone(HAZ)interface into the ferritic HAZ or even the ferritic BM,and the failure mode change improved the creep life of DMW.The interface premature failure of I-type interface DMW was related to the coupling effect of microstructure degradation,stress and strain concentrations,and oxide notch on the WM/HAZ interface.The creep failure of double Y-type interface DMW was the result of Type IV fracture due to the creep voids and micro-cracks on fine-grain boundaries in HAZ,which was a result of the matrix softening of HAZ and lack of precipitate pinning at fine-grain boundaries.The double Y-type interface form separated the stress and strain concentrations in DMW from the WM/HAZ interface,preventing the trigger effect of oxide notch on interface failure and inhibiting the interfacial microstructure cracking.It is a novel scheme to prolong creep life and enhance reliability of DMW,by means of optimizing the interface form,decoupling the damage factors from WM/HAZ interface,and then changing the failure mechanism and shifting the failure location.

Research on Cavitation Characteristics and Influencing Factors of Herringbone Gear Pump

Cavitation is a common issue in pumps,causing a decrease in pump head,a fall in volumetric efficiency,and an intensification of outlet flow pulsation.It is one of the main hazards that affect the regular operation of the pump.Research on pump cavitation mainly focuses on mixed flow pumps,jet pumps,external spur gear pumps,etc.However,there are few cavitation studies on external herringbone gear pumps.In addition,pumps with different working principles significantly differ in the flow and complexity of the internal flow field.Therefore,it is urgent to study the cavitation characteristics of external herringbone gear pumps.Compared with experimentalmethods,visual research and cavitation area identification are achieved through computation fluid dynamic(CFD),and changing the boundary conditions and shape of the gear rotor is easier.The simulation yields a head error of only 0.003%under different grid numbers,and the deviation between experimental and simulation results is less than 5%.The study revealed that cavitation causes flow pulsation at the outlet,and the cavitation serious area is mainly distributed in the meshing gap and meshing area.Cavitation can be inhibited by reducing the speed,increasing the inlet pressure,and changing the helix angle can be achieved.For example,when the inlet pressure is 5 bar,the maximumgas volume fraction in themeshing area is less than 50%.These results provide a reference for optimizing the design and finding the optimal design parameters to reduce or eliminate cavitation.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.