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.

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.

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.

Mechanical and damping performances of TPMS lattice metamaterials fabricated by laser powder bed fusion

Lattice metamaterials based on three-period minimum surface(TPMS)are an effective means to achieve lightweight and high-strength materials which are widely used in various fields such as aerospace and ships.However,its vibration and noise reduction,and damping properties have not been fully studied.Therefore,in this study,the TPMS structures with parameterization were designed by the method of surface migration,and the TPMS structures with high forming quality was manufactured by laser powder bed fusion(LPBF).The mechanical properties and energy absorption characteristics of the beam and TPMS structures were studied and compared by quasi-static compression.The modal shapes of the beam lattice structures and TPMS structures were obtained by the free modal analysis,and the damping properties of two structures were obtained by modal tests.For the two structures after heat treatment with the same porosity of 70%,the yield strength of the beam lattice structure reaches 40.76 MPa,elastic modulus is 20.38 GPa,the energy absorption value is 32.23 MJ·m^(-3),the damping ratio is 0.52%.The yield strength,elastic modulus,energy absorption value,and damping ratio of the TPMS structure are 50.74 MPa,25.37 GPa,47.34 MJ·m^(-3),and 0.99%,respectively.The results show that TPMS structures exhibit more excellent mechanical properties and energy absorption,better damping performance,and obvious advantages in structural load and vibration and noise reduction compared with the beam lattice structures under the same porosity.

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.

Mechanical and Electrical Properties of Some Sn-Zn Based Lead-Free Quinary Alloys

Although there are many lead-free soldering alloys on the market, none of them have ideal qualities. The researchers are combining binary alloys with a variety of additional materials to create the soldering alloys’ features. The eutectic Sn-9Zn alloy is among them. This paper investigated the mechanical and electrical properties of Sn-9Zn-x (Ag, Cu, Sb);{x = 0.2, 0.4, and 0.6} lead-free solder alloys. The mechanical properties such as elastic modulus, ultimate tensile strength (UTS), yield strength (YS), and ductility were examined at the strain rates in a range from 4.17 10−3 s−1 to 208.5 10−3 s−1 at room temperature. It is found that increasing the content of the alloying elements and strain rate increases the elastic modulus, ultimate tensile strength, and yield strength while the ductility decreases. The electrical conductivity of the alloys is found to be a little smaller than that of the Sn-9Zn eutectic alloy.

Influence of Solvent onto Chemical Extraction of America-Type Coconut (Coco nucifera L.) Fbers: Analysis of Physicochemical, Mechanical and Morphological Properties

In this study, the natural fibers from Coconuts of the species Coco nucifera L. were Chemically extracted in different solvents such as sodium hydroxide (SH), acetone (AC) and sodium hydroxide-acetone (SHA) for their applications in the textile industries. Structural, morphological and physico-mechanical characterizations such as X-ray diffraction (XRD), Fourier transform infrared spectrometry (FTIR), scanned electron microscopy (SEM), measurements of density, Young’s modulus, water absorption rate and humidity were evaluated. The XRD and FTIR results show that Coco nucifera L. fibers contains type I cellulose. Mechanical characterizations were also carried out. These results show that by varying the different solvents used, the physico-chemical, mechanical and morphological properties of the fibers change, which implies that the solvent has an influence on the properties of these fibers. The fibers extracted by the sodium hydroxide-acetone mixture have a linear density of 1.636, the percentage of water absorption is 62.428%, the percentage of moisture absorption 9.605% compared to other values in the literature shows that this solvent mixture improves the properties of coconut fibers which contain type I cellulose. The tensile stress is 0.013 GPa, the percentage strain is 49.836% and the Young’s modulus is 0.114 GPa as well as the percentage elongation show that these fibers are elasto-plastic. The values obtained mean that these fibers are suitable for use in textiles.

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.

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.

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.

Electrochemical biosensors for point-of-care testing

Point-of-care testing(POCT)is the practice of diagnosing and monitoring diseases where the patient is located,as opposed to traditional treatment conducted solely in a medical laboratory or other clinical setting.POCT has been less common in the recent past due to a lack of portable medical devices capable of facilitating effective medical testing.However,recent growth has occurred in this field due to advances in diagnostic technologies,device miniaturization,and progress in wearable electronics.Among these developments,electrochemical sensors have attracted interest in the POCT field due to their high sensitivity,compact size,and affordability.They are used in various applications,from disease diagnosis to health status monitoring.In this paper we explore recent advancements in electrochemical sensors,the methods of fabricating them,and the various types of sensing mechanisms that can be used.Furthermore,we delve into methods for immobilizing specific biorecognition elements,including enzymes,antibodies,and aptamers,onto electrode surfaces and how these sensors are used in real-world POCT settings.

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).

Recent research progress in the mechanism and suppression of fusion welding-induced liquation cracking of nickel based superalloys

Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at high temperatures.Fusion welding serves as an effective means for joining and repairing these alloys;however,fusion welding-induced liquation cracking has been a challenging issue.This paper comprehensively reviewed recent liquation cracking,discussing the formation mechanisms,cracking criteria,and remedies.In recent investigations,regulating material composition,changing the preweld heat treatment of the base metal,optimizing the welding process parameters,and applying auxiliary control methods are effective strategies for mitigating cracks.To promote the application of nickel-based superalloys,further research on the combination impact of multiple elements on cracking prevention and specific quantitative criteria for liquation cracking is necessary.

Recent advances and innovations in the design and fabrication of wearable flexible biosensors and human health monitoring systems based on conjugated polymers

Wearable biosensors have received great interest as patient-friendly diagnostic technologies because of their high flexibility and conformability.The growing research and utilization of novel materials in designing wearable biosensors have accelerated the development of point-of-care sensing platforms and implantable biomedical devices in human health care.Among numerous potential materials,conjugated polymers(CPs)are emerging as ideal choices for constructing high-performance wearable biosensors because of their outstanding conductive and mechanical properties.Recently,CPs have been extensively incorporated into various wearable biosensors to monitor a range of target biomolecules.However,fabricating highly reliable CP-based wearable biosensors for practical applications remains a significant challenge,necessitating novel developmental strategies for enhancing the viability of such biosensors.Accordingly,this review aims to provide consolidated scientific evidence by summarizing and evaluating recent studies focused on designing and fabricating CP-based wearable biosensors,thereby facilitating future research.Emphasizing the superior properties and benefits of CPs,this review aims to clarify their potential applicability within this field.Furthermore,the fundamentals and main components of CP-based wearable biosensors and their sensing mechanisms are discussed in detail.The recent advancements in CP nanostructures and hybridizations for improved sensing performance,along with recent innovations in next-generation wearable biosensors are highlighted.CPbased wearable biosensors have been—and will continue to be—an ideal platform for developing effective and user-friendly diagnostic technologies for human health monitoring.

Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.

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.

Soft,body conformable electronics for thermoregulation enabled by kirigami

The application of thermoelectric devices(TEDs)for personalized thermoregulation is attractive for saving energy while balancing the quality of life.TEDs that directly attach to human skin remarkably minimized the energy wasted for cooling the entire environment.However,facing the extreme dynamic geometry change and strain of human skin,conventional TEDs cannot align with the contour of our bodies for the best thermoregulation effect.Hence,we designed a kirigami-based wearable TED with excellent water vapor permeability,flexibility,and conformability.Numerical analysis and experimental results reveal that our product can withstand various types of large mechanical deformation without circuit rupture.The stated outcome and proposed facile approach not only reinforce the development of wearable TEDs but also offer an innovative opportunity for different electronics that require high conformability.

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.