The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).     

车载多层减振平台的主动控制及仿真

为了研究被动悬架车载主动减振平台的低成本控制策略及其减振效果,针对一种新型长宽比较大的多层减振平台,建立了车辆被动悬架与主动减振平台的一体化全系统动力学分析模型。进而,设计了"线性被动、旋转主动"的平台控制策略,并应用MATLAB及ADAMS软件,在三种典型路面激励下,进行了仿真测试。结果表明:采用垂向线性振动的多层被动减振、旋转振动的低成本主动控制策略,被动悬架车载减振平台的减振效果明显,实现了车载减振平台的高性价比设计。     

钼变形抗力的研究

在Gleeble-1500热模拟试验机上，分析钼的高温变形特征，其变形温度为1100～1400℃，变形速率为1-50s^-1，变形程度为0-0．6，并对钼板进行塑性变形抗力的研究，采用非线性回归方法建立钼板的变形抗力模型。获得了钼板的变形抗力曲线图，对不同的数学模型结构进行回归比较，提出拟合精度高的变形抗力的数学模型，该模型具有较高的精度及良好的数值稳定性。     

连铸中间包内三维湍流流动的数值模拟

连铸中间包的操作条件决定了其内流动现象的复杂性，为此，本文选择两种不同的湍流模型ｋ－ε和ＬＥＳ（Ｌａｒｇｅｅｄｄｙｓｉｍｕｌａｔｉｏｎ），建立了描述连铸中间包内三维湍流流动的数学模型，并实施了数值计算和模型验证，对单流中间包内的流动现象进行了描述，考察了有，无流动控制情况下中间包内的流动特征和湍流模型的合理性，结果表明，合理的流动控制有利于中间包内非金属夹杂的上浮和吸附，用ｋ－ε模型基本上能够描述     

方柱体镦粗的两个新力学模型

在对平板间镦粗圆柱体的研究［１，２，３］基础上，进一步对普通平板间的方柱体镦粗，进行了工程力学的分析，提出了二个新力学模型，并进行了实验验证。这为形成新的拔长理论［４，６］奠定了力学基础。     

Remanufacturability and Assessment Method

WITH the development of surface engineering andlaws on environment protect,lots of companies have toconsider reclaim of the used products.In practice,theyrealized if the products adopt design forremanufacturing,the benefit of remanufacturing wouldbe increased obviously'1'.Some researcher haveentered into remanufacturability field and built relativeevaluating methods'2'.Based on researching resultabout design for remanufacturing,some concepts,remanufacturability system and assessment method ar…     

应用人工神经网络理论建立热粘塑性材料的本构关系

本文将人工神经网络（ＡＮＮ）用于建立热粘塑性材料的本构关系，意在探索出一种描述材料变形力学行为的新方法。文中给出了应用人工神经网络建立热粘塑性材料本构关系的ＢＰ模型和学习算法过程，并应用于４５号钢在高温和高速变形条件下的流动应力计算。计算结果与实测结果比较表明，二者吻合良好。因此，应用人工神经网络建立热粘塑性材料的本构关系具有重要的工程应用价值。     

The Chick Chorioallantoic Membrane Model: A New In Vivo Tool to Evaluate Breast Cancer Stem Cell Activity

The high plasticity of cancer stem-like cells (CSCs) allows them to differentiate and proliferate, specifically when xenotransplanted subcutaneously into immunocompromised mice. CSCs are highly tumorigenic, even when inoculated in small numbers. Thus, in vivo limiting dilution assays (LDA) in mice are the current gold standard method to evaluate CSC enrichment and activity. The chick embryo chorioallantoic membrane (CAM) is a low cost, naturally immune-incompetent and reproducible model widely used to evaluate the spontaneous growth of human tumor cells. Here, we established a CAM-LDA assay able to rapidly reproduce tumor specificities—in particular, the ability of the small population of CSCs to form tumors. We used a panel of organotropic metastatic breast cancer cells, which show an enrichment in a stem cell gene signature, enhanced CD44⁺/CD24^−/low cell surface expression and increased mammosphere-forming efficiency (MFE). The size of CAM-xenografted tumors correlate with the number of inoculated cancer cells, following mice xenograft growth pattern. CAM and mice tumors are histologically comparable, displaying both breast CSC markers CD44 and CD49f. Therefore, we propose a new tool for studying CSC prevalence and function—the chick CAM-LDA—a model with easy handling, accessibility, rapid growth and the absence of ethical and regulatory constraints.     

Equivalent model of multi-type distributed generators under faults with fast-iterative calculation method based on improved PSO algorithm

There are various types of distributed generators (DGs) with diferent grid integration strategies. The transient char? acteristics of the fault currents provided by the DGs are diferent to those of conventional synchronous generators. In this paper, a distribution network with multi-type DGs is investigated, including consideration of DG low-voltage ride through (LVRT). The fault current characteristics of two typical DGs, i.e. an inverter-interfaced distributed generator (IIDG) and a doubly-fed induction generator (DFIG), are analyzed, considering the specifc operation modes. Based on analysis of the fault characteristics, an equivalent model of the multi-type DGs under symmetrical/asymmetrical fault conditions is established. A fast-iterative fault calculation method for enhancing the calculation efciency while avoid? ing local convergence is then proposed using an improved particle swarm optimization (PSO) algorithm. A simula? tion system of the distribution network with multi-type DGs is established in PSCAD/EMTDC. The simulation results validate the high accuracy and calculation efciency of the proposed calculation method of the fault components. This can assist in the settings of the protection threshold.     

Prediction of Functional Consequences of Missense Mutations in ANO4 Gene

The anoctamin (TMEM16) family of transmembrane protein consists of ten members in vertebrates, which act as Ca²⁺-dependent ion channels and/or Ca²⁺-dependent scramblases. ANO4 which is primarily expressed in the CNS and certain endocrine glands, has been associated with various neuronal disorders. Therefore, we focused our study on prioritizing missense mutations that are assumed to alter the structure and stability of ANO4 protein. We employed a wide array of evolution and structure based in silico prediction methods to identify potentially deleterious missense mutations in the ANO4 gene. Identified pathogenic mutations were then mapped to the modeled human ANO4 structure and the effects of missense mutations were studied on the atomic level using molecular dynamics simulations. Our data show that the G80A and A500T mutations significantly alter the stability of the mutant proteins, thus providing new perspective on the role of missense mutations in ANO4 gene. Results obtained in this study may help to identify disease associated mutations which affect ANO4 protein structure and function and might facilitate future functional characterization of ANO4.