Tool life modeling for evaluating the effects of cutting speed and reinforcements on the machining of particle reinforced metal matrix composites

The wear of cutting tools in the machining of 2024Al alloy composites reinforced with Al2O3 particles using varying sizes and volume fractions of particles up to 23.3vol% was investigated by a turning process using coated carbide tools K10 and TP30 at different cut- ting speeds. Machining tests were performed with a plan of experiments based on the Taguchi method. The tool life model was developed in terms of cutting speed, size, and volume fraction of particles by multiple linear regressions. The analysis of variance （ANOVA） was also employed to carry out the effects of these parameters on the cutting tool life. The test results show that the tool life decreases with the increase of cutting speed for both cutting tools K10 and TP30, and the tool life of the K10 tool is significantly longer than that of the TP30 tool. For the tool life, cutting speed is found to be the most effective factor followed by particle content and particle size, respectively. The predicted tool life of cutting tools is found to be in very good agreement with the experimentally observed ones.

Modeling mechanism and extension of GM (1,1)

Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM （1,1）, which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM （1,1）. Finally, the paper proposes a generalization grey model GGM （1,1）, which is a extended form of GM （1,1） and also a unified form of model GM （1,1）, model GM （1,1,α）, stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed.

Forecasting investment and consumption behavior of economic agents through dynamic computable general equilibrium model

Much research has been devoted to examination of the financial easing policy of the European Central Bank(ECB).However,this study is one of the first to use a dynamic micro-founded model to investigate empirically the impact of the ECB’s Quantitative Easing(QE)policy on consumption and investment by economic agents in Italy(households,government,firms,and the rest of the world).For this purpose,we constructed a Financial Social Accounting Matrix(FSAM)for the Italian economy for the year 2009 to calibrate a dynamic computable general equilibrium model(DCGE).This model allowed us to evaluate the direct and indirect impact of money flow on the behavior of consumption and investment.The findings of the study confirmed the positive impact of the ECB’s monetary policy on the level of investment and consumption.

Stability analysis and controller design of T-S fuzzy systems with time-delay under imperfect premise matching

The issue of the stability and controller design of Takagi-Sugeno（T-S） fuzzy control systems with time-delay is investigated under imperfect premise matching when the T-S fuzzy time-delay model and fuzzy controller do not share the same membership functions.A new stability criterion which contains the information of membership functions is derived.The new stability criterion is less conservative,and enhances the design flexibility.Two numerical examples are presented to illustrate the conservativeness and effectiveness of the proposed method.

Reduced-order modeling and vibration transfer analysis of a fluid-delivering branch pipeline that consider fluid–solid interactions

The efficient dynamic modeling and vibration transfer analysis of a fluid-delivering branch pipeline(FDBP)are essential for analyzing vibration coupling effects and implementing vibration reduction optimization.Therefore,this study proposes a reduced-order dynamic modeling method suitable for FDBPs and then analyzes the vibration transfer characteristics.For the modeling method,the finite element method and absorbing transfer matrix method(ATMM)are integrated,considering the fluid–structure coupling effect and fluid disturbances.The dual-domain dynamic substructure method is developed to perform the reduced-order modeling of FDBP,and ATMM is adopted to reduce the matrix order when solving fluid disturbances.Furthermore,the modeling method is validated by experiments on an H-shaped branch pipeline.Finally,transient and steady-state vibration transfer analyses of FDBP are performed,and the effects of branch locations on natural characteristics and vibration transfer behavior are analyzed.Results show that transient vibration transfer represents the transfer and conversion of the kinematic,strain,and damping energies,while steady-state vibration transfer characteristics are related to the vibration mode.In addition,multiple-order mode exchanges are triggered when branch locations vary in frequency-shift regions,and the mode-exchange regions are also the transformation ones for vibration transfer patterns.

Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial Applications

Latent factor(LF) models are highly effective in extracting useful knowledge from High-Dimensional and Sparse(HiDS) matrices which are commonly seen in various industrial applications. An LF model usually adopts iterative optimizers,which may consume many iterations to achieve a local optima,resulting in considerable time cost. Hence, determining how to accelerate the training process for LF models has become a significant issue. To address this, this work proposes a randomized latent factor(RLF) model. It incorporates the principle of randomized learning techniques from neural networks into the LF analysis of HiDS matrices, thereby greatly alleviating computational burden. It also extends a standard learning process for randomized neural networks in context of LF analysis to make the resulting model represent an HiDS matrix correctly.Experimental results on three HiDS matrices from industrial applications demonstrate that compared with state-of-the-art LF models, RLF is able to achieve significantly higher computational efficiency and comparable prediction accuracy for missing data.I provides an important alternative approach to LF analysis of HiDS matrices, which is especially desired for industrial applications demanding highly efficient models.

An elastic-plastic analysis of short-leg shear wall structures during earthquakes

Short-leg shear wall structures are a new form of building structure that combine the merits of both frame and shear wall structures. Its architectural features, structure bearing and engineering cost are reasonable. To analyze the elastic-plastic response of a short-leg shear wall structure during an earthquake, this study modified the multiple-vertical-rod element model of the shear wall, considered the shear lag effect and proposed a multiple-vertical-rod element coupling beam model with a new local stiffness domain. Based on the principle of minimum potential energy and the variational principle, the stiffness matrixes of a short-leg shear wall and a coupling beam are derived in this study. Furthermore, the bending shear correlation for the analysis of different parameters to describe the structure, such as the beam height to span ratio, short-leg shear wall height to thickness ratio, and steel ratio are introduced. The results show that the height to span ratio directly affects the structural integrity; and the short-leg shear wall height to thickness ratio should be limited to a range of approximately 6.0 to 7.0. The design of short-leg shear walls should be in accordance with the ＂strong wall and weak beam＂ principle.

基于宏观因子的SVR-Black-Litterman资产配置模型及其实证研究

随着全球经济不稳定性的增强和我国利率市场化的深入推进,金融资产的波动性不断加剧,资产组合优化配置问题依然是金融投资理论研究和实务领域的核心问题。Black-Litterman模型因其解决了传统均值方差模型对参数敏感的问题,且允许将投资者观点融入模型中,已被广泛应用于资产配置实践中。然而投资者观点矩阵的确定一直是Black-Litterman模型理论和应用研究的难点。将宏观因子融入投资者观点矩阵,应用基于主成分分析法的支持向量回归(SVR)模型实现观点矩阵的估计,构建融入宏观因子的SVR-Black-Litterman资产配置模型。为检验模型的有效性,将该模型与经典模型进行比较。实证结果表明,所构建的模型具有较好的市场表现。

基于Kano模型的三级癫痫中心护理服务需求调查

目的 分析三级癫痫中心护理服务建设的应用需求,为优化中心建设提供参考。方法 采用便利抽样的方法选取2022年6月至2023年6月在宜春市人民医院综合癫痫中心接受治疗的100例患者为研究对象,采用基于Kano模型及德尔菲专家咨询法设计的问卷进行调查。通过Kano模型需求属性分类、Better-Worse系数分析和二维矩阵分析,确定三级癫痫中心护理服务建设的需求属性,通过需求要素筛选确定最敏感和需要改进的要素。结果 根据Kano模型需求属性分类结果,根据指标分类的20项需求中包含期望需求9项(45%)、魅力需求3项(15%)、必备需求7项(35%)、无差异需求1项(5%),其中“护士服务态度”和“远程服务快速响应”两个需求指标的敏感度最高。结论 医疗机构及三级癫痫中心管理者应重视护士服务态度提升,确保每位患者都能得到尊重和关怀,同时优化远程服务流程,提高响应速度和服务质量,以满足患者对即时性和便捷性的需求。同时,三级癫痫中心服务建设需要提高互联网端远程指导能力及信息安保能力,针对住院或居家癫痫患者及时优化调整护理策略,改善患者康复效果。

Effects of life-history components on population dynamics of the rare endangered plant <i>Davidia involucrata</i>

In order to estimate the most effect stage and process on population growth and effective conserve the rare endangered plant Davidia involucrata, we analyzed the dynamics and the contributions of life-history components on population dynamics based on Lefkovitch matrix model and sensitivity analysis. The life cycle of Davidia involucrata was divided into six stages (seed, seedling, juvenile, immature, early adult and late adult) based on the species characteristics and published literature data, the survival rates in each life-history stage were simulated using a static life table, and the fecundity of each stage was determined according to sample information. The results showed that the structure of the observed population was not ideal, and the numbers of seedlings and coppice shoots was similar. The population growth rate was influenced largely by individual growth process, and asexual reproduction made a larger contribution to population growth than sexual reproduction. However, sexual reproduction was more important than asexual reproduction, because most asexual reproducing individuals (the coppice shoots) were derived mainly from human destruction (e.g. felling trees). The most important stage was stage V (late adult), associated with seed production and germination. Therefore, conservation of Davidia involucrata populations should focus on stage V and sexual reproduction, in order to improve the seed production and germination rate, and to promote population stability and development.

THE THEORY OF STATIC DECAY IN COMPUTATIONAL MECHANICS

In this paper, a new mathematical form, matrix, continued fraction (MCF) is introduced to describe the decay of effects of an equilibrant system of forces acting on a sphere of an elastic body. By this way, the famous Saint-Venant's principle is proved often but not always valid in computational mechanics.

Precision Matrix Estimation by Inverse Principal Orthogonal Decomposition

We investigate the structure of a large precision matrix in Gaussian graphical models by decomposing it into a low rank component and a remainder part with sparse precision matrix.Based on the decomposition,we propose to estimate the large precision matrix by inverting a principal orthogonal decomposition(IPOD).The IPOD approach has appealing practical interpretations in conditional graphical models given the low rank component,and it connects to Gaussian graphical models with latent variables.Specifically,we show that the low rank component in the decomposition of the large precision matrix can be viewed as the contribution from the latent variables in a Gaussian graphical model.Compared with existing approaches for latent variable graphical models,the IPOD is conveniently feasible in practice where only inverting a low-dimensional matrix is required.To identify the number of latent variables,which is an objective of its own interest,we investigate and justify an approach by examining the ratios of adjacent eigenvalues of the sample covariance matrix?Theoretical properties,numerical examples,and a real data application demonstrate the merits of the IPOD approach in its convenience,performance,and interpretability.

Research on OD Matrix Calculation Based on Quantum Behaved Particle Swarm Optimization Algorithm

Traffic information is so far less than the number of OD variables, that it is difficult to obtain the satisfactory solution. In this paper, a method based on Quantum behaved Particle Swarm Optimization (QPSO) algorithm is developed to obtain the global optimal solution. It designs the method based on QPSO algorithm to solve the OD matrix prediction model, lists the detailed steps and points out how to choose the PSO operator. Moreover, it uses MATLAB program-ming language to carry out the simulation test. The simulation results show that the method has higher efficiency and accuracy.

清远市清城区土壤中重金属的空间分布、来源解析和健康评价:基于PCA和PMF模型的对比

本研究在中国东南部一个典型的快速转型工业城区采集了122个土壤样品。我们采用富集因子(EF)、地质累积指数法(I_(geo))、斯皮尔曼相关性分析、潜在生态风险综合指数(RI)和人体健康风险模型(HHR)多种分析方法对研究区9种重金属(As、Co、Cr、Cu、Hg、Ni、Pb、Ti和Zn)的污染特征进行评估,并结合主成分分析(PCA)、正矩阵分解(PMF)模型和地统计学法对研究区土壤进行来源解析。结果表明,土壤中As、Cu、Hg、Pb、Zn存在明显富集,但研究区整体处于清洁状态。由于PCA和PMF模型对重金属聚类分组的结果并不完全一致,故分别将9种重金属元素划分为两个来源和3个来源,以便互相验证元素划分的准确性。在潜在生态风险评价中,研究区整体处于轻微生态风险水平;值得注意的是,Hg元素带来的生态风险是所有元素中最高的。对于人体健康风险评价,在该研究区中,成人和儿童均不存在非致癌风险和致癌风险,但是我们发现儿童比成人在面对重金属带来的健康风险时表现得更敏感,应当引起重视。

基于Kano模型的中医医院微信公众号需求分析

采用Kano问卷调查方法,分析不同使用目的用户对中医医院微信公众号各功能点关注度的优先级排序,提出建议,包括明确自身定位、针对性功能开发等,从而构建特色微信公众号服务平台,促进中医医院品牌建设和微信公众号长期发展。

基于HAZOP与模糊扩展蝴蝶结模型的甲烷化装置系统风险分析

作为清洁能源的甲烷,具有很大的发展潜力。为保证甲烷化装置系统的安全稳定运行,基于危险和可操作性(HAZOP)分析与模糊扩展蝴蝶结(FEBT)模型对托普索甲烷化工艺装置系统进行了风险分析。先使用HAZOP分析和风险矩阵对该甲烷化装置系统进行了风险辨识和风险等级划分,再使用FEBT模型对该甲烷化装置系统中管道或容器内发生火灾爆炸事故的基础事件和安全屏障事件发生的可能性进行了计算。结果表明:该甲烷化装置系统中管道或容器发生火灾爆炸事故的风险管控排序最为优先;人为误操作和机械工艺方面的法兰密封失效是直接导致事故场景发生的主要促成事件。该研究结果为该甲烷化装置系统在日常安全管理中指明了关键事件,并验证了HAZOP分析和风险矩阵以及FEBT模型在化工装置系统风险分析中的有效性。

基于Bayes和SWOT的跨流域调水生态补偿受偿意愿及激励机制研究

水源区居民是水资源保护的贡献者,对水源区公众受偿意愿(WTA)的理性评估,是构建生态补偿机制的关键问题之一。通过理论探索、实地调研和模型分析,以南水北调东线水源区扬州市为例,开展跨流域调水生态补偿的WTA值及影响因素的分析研究。结果表明:在442份有效样本中,居民具有受偿意愿的比例为75.11%,采用非参数法和参数法综合评估得出WTA均值为443.29元/(人·年);基于贝叶斯网络模型分析公众WTA的影响因素,得到年龄、对当前生活用水水质的满意程度、工程给个人带来的影响对WTA影响显著;最后采用SWOT矩阵分析法从内部公众背景、外部环境政策等角度,对构建跨流域调水水源区的生态补偿机制提出激励机制。研究可以为跨流域调水生态补偿机制的构建和完善提供参考。

基于新一代几何技术规范的装配误差建模

针对由于公差设计不合理而导致的服役于复杂工况的机械装备性能下降等问题,提出一种综合考虑制造与装配误差的机械产品装配精度分析方法。该方法首先利用有限元分析机械装备零部件装配误差导致的变形,并提取发生形变的关键特征面;然后基于新一代几何技术规范(GPS)将特征面的变形转化为尺寸与形位公差数据,并与设计公差进行叠加,实现变形—误差—公差的转换;随后基于雅可比旋量理论,构建综合考虑制造与装配误差的公差分析模型支撑机械装备的公差精量化设计;最后以某型机载作动筒为工程应用对象,对比分析了是否考虑受力变形条件下装配精度分析的结果差异,结果显示该方法相较于原有方法具有更高的计算准确性,能为精密机械产品精度设计提供更加准确的指导。