Prediction of Cross-Tension Strength of Self-Piercing Riveted Joints Using Finite Element Simulation and XGBoost Algorithm

Self-piercing riveting(SPR)has been widely used in automobile industry,and the strength prediction of SPR joints always attracts the attention of researchers.In this work,a prediction method of the cross-tension strength of SPR joints was proposed on the basis of finite element(FE)simulation and extreme gradient boosting decision tree(XGBoost)algorithm.An FE model of SPR process was established to simulate the plastic deformations of rivet and substrate materials and verified in terms of cross-sectional dimensions of SPR joints.The residual mechanical field from SPR process simulation was imported into a 2D FE model for the cross-tension testing simulation of SPR joints,and cross-tension strengths from FE simulation show a good consistence with the experiment result.Based on the verified FE model,the mechanical properties and thickness of substrate materials were varied and then used for FE simulation to obtain cross-tension strengths of a number of SPR joints,which were used to train the regression model based on the XGBoost algorithm in order to achieve prediction for cross-tension strength of SPR joints.Results show that the cross-tension strengths of SPR steel/aluminum joints could be successfully predicted by the XGBoost regression model with a respective error less than 7.6%compared to experimental values.

Investigation on Yield Behavior of 7075‑T6 Aluminum Alloy at Elevated Temperatures

Aluminum alloys have drawn considerable attention in the area of automotive lightweight.High strength aluminum alloys are usually deformed at elevated temperatures due to their poor formability at room temperature.In this work,the yield behavior of 7075 aluminum alloy in T6 temper(AA7075-T6)within the temperature ranging from 25°C to 230°C was investigated.Uniaxial and biaxial tensile tests with the aid of induction heating system were performed to determine the stress vs.strain curves and the yield loci of AA7075-T6 at elevated temperatures,respectively.Von Mises,Hill48 and Yld2000-2d yield criteria were applied to predicting yield loci which were compared with experimentally measured yield loci of the AA7075-T6.Results show that yield stress corresponding to the same equivalent plastic strain decreases with increasing temperature within the investigated temperature range and the shape of yield loci evolves nearly negligibly.The experimental yield locus expands with an increase of equivalent plastic strain at the same temperature and the work hardening rate of AA7075-T6 exhibits obvious stress-state-dependency.The nonquadratic Yld2000-2d yield criterion describes the yield surfaces of AA7075-T6 more accurately than the quadratic von Mises and Hill48 yield criteria,and an exponent of 14 in the Yld2000-2d yield function gives the optimal predictions for the AA7075-T6 at all investigated temperatures.

红原机场太阳能供暖系统的运行特性研究

为研究高寒地区太阳能供暖系统的运行特性,建立了红原机场太阳能供暖系统的TRNSYS仿真模型,并利用实测数据验证了模型的有效性。通过运行仿真模型分析了集热器的效率、蓄热水箱的温度及各模式的运行时间。研究结果表明,集热器的日平均集热效率最大值为0.40,供暖中期平均值在0.3左右;12月和1月蓄热装置温度在50oC以上的时间可达5~6个小时,供暖初期和末期最高可达13~15个小时;太阳能直接供暖、热泵单独供暖及两者联合供暖模式分别占总供暖时间的40.76%、37.03%和22.21%。研究结果为太阳能供暖系统在高海拔寒冷地区的应用提供了参考。

Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets

Objective:The aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets.Methods:Nonparametric(NOISeq)and robust rank aggregation-ranked parametric(EdgeR)methods were used to assess robust differentially expressed genes across multiple datasets.Protein-protein interaction network,GO,KEGG enrichment,and subnetwork analyses were performed to identify immune-associated hub genes in breast cancer.Immune cell infiltration was evaluated with the CIBERSORT,XCELL,and TIMER methods.The association between the hub gene-based risk signature and survival was determined through Kaplan–Meier survival analysis,multivariate Cox analysis,and a nomogram with external verification.Results:We identified 163 robust differentially expressed genes in breast cancer through applying both nonparametric and parametric methods to multiple GEO(n=2,212)and TCGA(n=1,045)datasets.Integrated bioinformatic analyses further identified 10 hub genes:CXCL10,CXCL9,CXCL11,SPP1,POSTN,MMP9,DPT,COL1A1,ADAMDEC1,and RGS1.The 10 hub-gene-based risk signature significantly correlated with the prognosis of patients with breast cancer.Moreover,these hub genes were strongly associated with the extent of infiltration of CD4+T cells,CD8+T cells,neutrophils,macrophages,and myeloid dendritic cells into breast tumors.Conclusions:Integrated analyses of multiple databases led to the discovery of 10 robust hub genes that together may serve as a risk factor characteristic of the immune microenvironment in breast cancer.

Factors That Affect the Computational Prediction of Hot Spots in Protein-Protein Complexes

Protein-protein complexes play an important role in the physiology and the pathology of cellular functions, and therefore are attractive therapeutic targets. A small subset of residues known as “hot spots”, accounts for most of the protein-protein binding free energy. Computational methods play a critical role in identifying the hotspots on the proteinprotein interface. In this paper, we use a computational alanine scanning method with all-atom force fields for predicting hotspots for 313 mutations in 16 protein complexes of known structures. We studied the effect of force fields, solvation models, and conformational sampling on the hotspot predictions. We compared the calculated change in the protein-protein interaction energies upon mutation of the residues in and near the protein-protein interface, to the experimental change in free energies. The AMBER force field (FF) predicted 86% of the hotspots among the three commonly used FF for proteins, namely, AMBER FF, Charmm27 FF, and OPLS-2005 FF. However, AMBER FF also showed a high rate of false positives, while the Charmm27 FF yielded 74% correct predictions of the hotspot residues with low false positives. Van der Waals and hydrogen bonding energy show the largest energy contribution with a high rate of prediction accuracy, while the desolvation energy was found to contribute little to improve the hot spot prediction. Using a conformational ensemble including limited backbone movement instead of one static structure leads to better predicttion of hotpsots.

A Multiscale Model of Mass-Functionally Graded Beam-Fluid System Under Bending and Vibration Responses

In this paper,a multiscale model is developed for the mass functionally graded(FG)beam-fluid system to investigate its static and dynamic responses based on 3D printed porous beam free vibration tests,which are determined by two aspects.At the microstructural level,the gradient variation is realized by arbitrary distribution of matrix pores,and the effective moduli under specific distribution are obtained using the micromechanics homogenization theory.In the meantime,at the structural level,the mechanical responses of FG porous beams subjected to mass loading are considered in a static fluid environment.Then,the explicit expressions of local finite-element(FE)expressions corresponding to the static and dynamic responses are given in the appendices.The present results are validated against numerical and experimental results from the literature and mechanical tests of 3D printed structures,with good agreement generally obtained,giving credence to the present model.On this basis,a comprehensive parametric study is carried out,with a particular focus on the effects of boundary conditions,fluid density,and slenderness ratio on the bending and vibration of FG beams with several different gradations.

Study of neutron density fluctuation and neutron-proton correlation in Au+Au collisions using PYTHIA8/Angantyr

Utilizing the PYTHIA8 Angantyr model,which incorporates the multiple-parton interaction(MPI)based color reconnection(CR)mechanism,we study the relative neutron density fluctuation and neutron-proton correlation in Au+Au collisions at√sNN=7.7,11.5,14.5,19.6,27,39,62.4,and 200 GeV.In this study,we not only delve into the dependence of these two remarkable observations on rapidity,centrality,and energy,but also analyze their interplay with the MPI and CR.Our results show that the light nuclei yield ratio of protons,deuterons,and tritons,expressed by the elegant expression N_(t)N_(p)/N^(d)^(2),remains unchanged even as the rapidity coverage and collision centrality increase.Interestingly,we also reveal that the effect of CR is entirely dependent on the presence of the MPI;CR has no impact on the yield ratio if the MPI is off.Our findings further demonstrate that the light nuclei yield ratio experiences a slight increase with increasing collision energy,as predicted by the PYTHIA8 Angantyr model;however,it cannot describe the non-monotonic trend observed by the STAR experiment.Based on the Angantyr model simulation results,it is essential not to overlook the correlation between neutron and proton fluctuations.The Angantyr model is a good baseline for studying collisions in the absence of a quark-gluon plasma system,given its lack of flow and jet quenching.

Molecular mechanism of SCARB2-mediatec attachment and uncoating of EV71

Unlike the well-established picture for the entry of enveloped viruses, the mechanism of cellular entry of non-enveloped eukaryotic viruses remains largely mysterious. Picornaviruses are representative models for such viruses, and initiate this entry process by their functional receptors. Here we present the structural and functional studies of SCARB2, a functional receptor of the important human enterovirus 71 （EV71）. SCARB2 is responsible for attachment as well as uncoating of EV71. Differences in the structures of SCARB2 under neutral and acidic conditions reveal that SCARB2 undergoes a pivotal pH-dependent conformational change which opens a lipid-transfer tunnel to mediate the expulsion of a hydrophobic pocket factor from the virion, a pre-requisite for uncoating. We have also identified the key residues essential for attachment to SCARB2, identifying the canyon region of EV71 as mediating the receptor interaction. Together these results provide a clear understanding of cellular attachment and initiation of uncoating for enteroviruses.

Effect of Atmospheric Pressure Plasma Treatment on the Lap-Shear Strength of Adhesive-Bonded Sheet Molding Compound Joints

Atmospheric pressure plasma treatment(APPT)technology was used herein to treat sheet molding compound(SMC)substrates to increase the lap-shear strength of adhesive-bondedSMCjoints.Further,the mechanisms behind the lap-shear strength improvements in APPT-treated adhesive-bonded SMC joints were explored.A maximum lap-shear strength about three times that of the as-received SMC joints was achieved when the APPT distance was set to 20 mm.The surface roughness,which exhibited little benefit to the lap-shear strength,was determined to not be the primary reason for the increase in lap-shear strength.Specifically,X-ray photoelectron spectra revealed that an increased amount of O-containing groups(i.e.,C–O–H,C–O–C,H–O–C=O or R–O–C=O)following APPT contributed to the improved lap-shear strength.In addition,the surface free energy increased significantly after APPT,which improved the lap-shear strength of the adhesive-bonded SMC joints.Compared to the change of surface morphology,the changes in both the surface chemical property and surface free energy played larger roles in increasing the lap-shear strength of APPT-treated SMC joints.

Flexural Performance of Steel-FRP Composites for Automotive Applications

The design of hybrid structure offers an attractive solution to enhance strength and structural stiffness as well as to achieve lightweight effect and cost reduction.The applications of steel-FRP(fiber-reinforced polymer)composites in trans-portation and civil engineering have been comprehensively reviewed.In order to apply hybrid structures to car body parts such as B-pillar,flexural performance of steel-FRP composites is investigated by means of three-point bending test in this study.An analytical model is deduced to calculate the initial stiffness,the bending load and the energy absorption of steel-FRP composites.Steel-CFRP(carbon fiber-reinforced polymer)and steel-AFRP(aramid fiber-reinforced polymer)composites are experimentally studied and discussed.The results demonstrate that the steel-FRP composites exhibit significantly higher load-carrying capabilities and initial stiffnesses along with larger energy absorptions in the bending process compared to the single steel sheet.

Functional annotation from the genome sequence of the giant panda

The giant panda is one of the most critically endangered species due to the fragmentation and loss of its habitat.Studying the functions of proteins in this animal,especially specific trait-related proteins,is therefore necessary to protect the species.In this work,the functions of these proteins were investigated using the genome sequence of the giant panda.Data on 21,001 proteins and their functions were stored in the Giant Panda Protein Database,in which the proteins were divided into two groups:20,179 proteins whose functions can be predicted by GeneScan formed the known-function group,whereas 822 proteins whose functions cannot be predicted by GeneScan comprised the unknown-function group.For the known-function group,we further classified the proteins by molecular function,biological process,cellular component,and tissue specificity.For the unknown-function group,we developed a strategy in which the proteins were filtered by cross-Blast to identify panda-specific proteins under the assumption that proteins related to the panda-specific traits in the unknown-function group exist.After this filtering procedure,we identified 32 proteins(2 of which are membrane proteins)specific to the giant panda genome as compared against the dog and horse genomes.Based on their amino acid sequences,these 32 proteins were further analyzed by functional classification using SVM-Prot,motif prediction using MyHits,and interacting protein prediction using the Database of Interacting Proteins.Nineteen proteins were predicted to be zinc-binding proteins,thus affecting the activities of nucleic acids.The 32 panda-specific proteins will be further investigated by structural and functional analysis.