Numerical modeling of friction stir welding using the tools with polygonal pins

Friction stir welding using the tools with polygonal pins is often found to improve the mechanical strength of weld joint in comparison to the tools with circular pins. However, the impacts of pin profile on the peak temperature, tool torque and traverse force, and the resultant mechanical stresses experienced by the tool have been rarely reported in a systematic manner. An estimation of the rate of heat generation for the tools with polygonal pins is challenging due to their non-axisymmetric cross-section about the tool axis. A novel methodology is presented to analytically estimate the rate of heat generation for the tools with polygonal pins. A three-dimensional heat transfer analysis of friction stir welding is carried out using finite element method. The computed temperature field from the heat transfer model is used to estimate the torque, traverse force and the mechanical stresses experienced by regular triangular, square, pentagon and hexagon pins following the principles of solid mechanics. The computed results show that the peak temperature experienced by the tool pin increases with the number of pin sides. However, the resultant maximum shear stress experienced by the pin reduces from the triangular to hexagonal pins.

Application of Artificial Neural Networks Model as Analytical Tool for Groundwater Salinity

The main source of water in Gaza Strip is the shallow coastal aquifer. It is extremely deteriorated in terms of salinity which influenced by many variables. Studying the relation between these variables and salinity is often a complex and nonlinear process, making it suitable to model by Artificial Neural Networks (ANN). Initially, it is assumed that the salinity (represented by chloride concentration, mg/l) may be affected by some variables as: recharge rate, abstraction, abstraction average rate, life time and aquifer thickness. Data were extracted from 56 municipal wells, covering the area of Gaza Strip. After a number of modeling trials, the best neural network was determined to be Multilayer Perceptron network (MLP) with four layers: an input layer of 6 neurons, first hidden layer with 10 neurons, second hidden layer with 7 neurons and the output layer with 1 neuron which gives the final chloride concentration. The ANN model generated very good results depending on the high correlation between the observed and simulated values of chloride concentration. The correlation coefficient (r) was 0.9848. The high value of (r) showed that the simulated chloride concentration values using the ANN model were in very good agreement with the observed chloride concentration which mean that ANN model is useful and applicable for groundwater salinity modeling. ANN model was successfully utilized as analytical tool to study influence of the input variables on chloride concentration. It proved that chloride concentration in groundwater is reduced by decreasing abstraction, abstraction average rate and life time. Furthermore, it is reduced by increasing recharge rate and aquifer thickness.

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.

Developing a Data Modelling Tool to Visualize the Transformation of an ER Diagram into a Relational Schema

In this paper, the authors present the development of a data modelling tool that visualizes the transformation process of an ＂Entity-Relationship＂ Diagram （ERD） into a relational database schema. The authors＇ focus is the design of a tool for educational purposes and its implementation on e-learning database course. The tool presents two stages of database design. The first stage is to draw ERD graphically and validate it. The drawing is done by a learner. Then at second stage, the system enables automatically transformation of ERD to relational database schema by using common rules. Thus, the learner could understand more easily how to apply the theoretical material. A detailed description of system functionalities and algorithm for the conversion are proposed. Finally, a user interface and usage aspects are exposed.

A MECHANICS MODEL FOR CIRCULAR FORM TOOL CUTTING

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FEATURE SOLID MODELING TOOL SYSTEM:FSMTS

In conformity with the principle of Design for Manufacture,feature-based design strate- (?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NC programs”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe- less,substantial breakthrough has not been made in the solid modeling field,except“feature at- taching”or“feature recognizing”methods have been taken on.In this paper,the theory, concepts,system architecture,and algorithm principles of solid modeling tool system have been represented.The practice of Feature Solid Modeling Tool System (FSMTS) developed at Huazhong University has proved that the tool may be a new foundation of Feature-Based Design.

Online Capacitance Modeling Tool for Conductors Represented as Simply-Connected Polygonal Geometries in 2D

We present an online tool for calculating the capacitance between two conductors represented as simply-connected polygonal geometries in 2D with Dirichlet boundaries and homogeneous dielectric. Our tool can be used to model the so-called 2.5D geometries, where the 3rd dimension can be extruded out of plane. Micro-electro-mechanical systems (MEMS) with significant facing surfaces may be approximated with 2.5D geometry. Our tool compares favorably in accuracy and speed to the finite element method (FEM). We achieve modeling accuracy by treating the corners exactly with a Schwarz-Christoffel mapping. And we achieve fast results by not needing to discretize boundaries and subdomains. As a test case, we model a MEMS torsional actuator. Our tool computes capacitance about 1000 times faster than FEM with 4.7% relative error.

Tool Temperature and Process Modeling of Friction Stir Welding

Friction stir welding (FSW) has many advantages rather than fusion welding, but details of internal phenomena during its processes have not yet been clarified. In this study, a thermo-mechanically coupled process model was developed to investigate FSW phenomena inside a tool and workpiece. As a workpiece, 6061-T6 aluminum alloy was employed. The system of FSW process model includes several thermal boundaries. Among heat flows through these boundaries, heat transfers into the exterior of the system become more sensitive to tool and workpiece temperatures than heat transfers within the system. This paper especially focused on a heat transfer coefficient at a workpiece bottom, and optimized it through experiments and finite element method (FEM) analyses. The tool temperatures during FSW were measured with a special tooling system with imbedded thermocouples within a tool. As a result, an analysis model that is able to investigate details at a wide range of traverse speeds was developed for practical high speed welding. Then, the accuracy of developed FEM model was validated with them. Finally, the temperatures and stress distribution around workpiece/tool interfaces were investigated with the developed model.

NDT-Suite: A Methodological Tool Solution in the Model-Driven Engineering Paradigm

Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a challenge for software engineering. Several causes can be stacked out, but one of them can be the lack of tool support for the efficient application of this paradigm. This paper presents a set of tools, grouped in a suite named NDT-Suite, which under the Model-Driven paradigm offer a suitable solution for software development. These tools explore different options that this paradigm can improve such as, development, quality assurance or requirement treatment. Besides, this paper analyses how they are being successfully applied in the industry.

Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool

Aiming at the problem of low machining accu- racy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA（grey relational analysis） method is introduced into the selection of tem- perature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN （artificial neural network） model is presented, and ABC（artificial bee colony） algorithm is introduced to train the link weights of ANN, a new ABC- NN（Artificial bee colony-based neural network） modeling method is proposed and used in the prediction of spindle thermal errors. In order to test the prediction performance of ABC-NN model, an experiment system is developed, the prediction results of LSR （least squares regression）, ANN and ABC-NN are compared with the measurement results of spindle thermal errors. Experiment results show that the prediction accuracy of ABC-NN model is higher than LSR and ANN, and the residual error is smaller than 3 pm, the new modeling method is feasible. The proposed research provides instruction to compensate thermal errors and improve machining accuracy of NC machine tools.

A Generic Kinematic Model for Three Main Types of Five-axis Machine Tools

Material removal is one of the most used processes in manufacturing. Five-axis CNC machines are believed to be the best tools in sculptured surface machining. In this study, a generic and unified kinematic model was developed as a viable alternative to the particular solutions that are only applicable to individual machine configurations. This versatile model is then used to verify the feasibility of the two rotational joints within the kinematic chain of three main types of a five-axis machine-tool. This versatile model is very useful applied to the design of five-axis machine tools.

A Functional Data Modeling Tool for Engineering Applications

The fact that most engineering applications are developed by engineers themselves rather than computer professionals calls for the data modeling methods to be powerful enough to represent complex engineering phenomena, but simple enough to use. A data modeling method which can help engineers to write C++ code with high quality is introduced.

FLOW STRESS MODEL FOR HARD MACHINING OF AISI H13 WORK TOOL STEEL

An approach is presented to characterize the stress response of workpiece in hard machining, accounted for the effect of the initial workpiece hardness, temperature, strain and strain rate on flow stress. AISI H13 work tool steel was chosen to verify this methodology. The proposed flow stress model demonstrates a good agreement with data collected from published experiments. Therefore, the proposed model can be used to predict the corresponding flow stress-strain response of AISI H13 work tool steel with variation of the initial workpiece hardness in hard machining.

Thermal Error Modeling Method with the Jamming of Temperature-Sensitive Points'Volatility on CNC Machine Tools

Aiming at the deficiency of the robustness of thermal error compensation models of CNC machine tools, the mechanism of improving the models＇ robustness is studied by regarding the Leaderway-V450 machining center as the object. Through the analysis of actual spindle air cutting experimental data on Leaderway-V450 machine, it is found that the temperature-sensitive points used for modeling is volatility, and this volatility directly leads to large changes on the collinear degree among modeling independent variables. Thus, the forecasting accuracy of multivariate regression model is severely affected, and the forecasting robustness becomes poor too. To overcome this effect, a modeling method of establishing thermal error models by using single temperature variable under the jamming of temperature-sensitive points＇ volatility is put forward. According to the actual data of thermal error measured in different seasons, it is proved that the single temperature variable model can reduce the loss of fore- casting accuracy resulted from the volatility of tempera- ture-sensitive points, especially for the prediction of cross quarter data, the improvement of forecasting accuracy is about 5 μm or more. The purpose that improving the robustness of the thermal error models is realized, which can provide a reference for selecting the modelingindependent variable in the application of thermal error compensation of CNC machine tools.

Evaluation of Thermal Effect of PCM Wallboards by Coupling Simplified Phase Change Model with Design Tool

A simplified PCM wallboard model is coupled to an existing design-oriented model of multi-zone buildings. Using a reference model and a basic simulation configuration, the accuracy of the resulting PCM wallboard-building thermal design tool is evaluated. A new performance indicator, called PCM utilization factor, is then proposed in order to estimate the thermal efficiency of using PCM wallboards in buildings. Using this PCM Utilization factor and a degrees-hours indicator, the ability of the PCM wallboard-building thermal design tool to evaluate the effect of PCM wallboards on heating loads and summer thermal comfort in the early design phase of a project is examined in two real case studies: a family house project and an existing office building. The user-friendliness of this design tool, and the short calculation times it leads to when performing a year-long simulation using a standard office computer, make it a well-adapted tool for sensibility studies or multi-criterion optimization for buildings that contain PCM wallboards.

A New Analysis Concept in Applying Software Reliability Growth Models and Tool Implementation: The SafeMan

In recent years, many software development organizations have been assessing and analyzing their software product’s reliability/quality and judging whether the software product is releasable by using Software Reliability Growth Models (SRGMs) at the final stage of software development. The usage of SRGMs originates in the advantage that various reliability analysis results based on the SRGMs can be acquired easily. However, it is very difficult for general software project managers to grasp the achievement level of reliability/quality based on its analysis results because some sort of professional knowledge is required in order to understand the information on the attainment progress of software product’s reliability/quality. Moreover, it is also difficult for software project managers and inspectors who do not deeply comprehend the details of their project to evaluate the degree of software reliability and quality, if they assess it without grasping the live development situation and only see the documents submitted from their staff. In this paper, we propose a new analysis concept for assessing the software product’s reliability/quality, and illustrate the output results obtained by a tool, the SafeMan.

MODULE DEFINITION MODEL FOR MODULAR DESIGN AND MANUFACTU－RING OF HEAVY DUTY MACHINE TOOLS

The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works

Bayesian zero-failure reliability modeling and assessment method for multiple numerical control(NC) machine tools

A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

基于Virtools的虚拟商场漫游系统的设计与实现

介绍了3DS Max结合Virtools开发工具的虚拟现实设计方法及整个三维虚拟商场的制作流程,采用3DS Max构建3D模型,制作3D动画,在模型构建中,采用层次细节技术和纹理贴图技术相结合的方式,在节省创作时间的基础上,提高了场景的实时渲染速度。在场景的交互设计中,本系统利用碰撞检测技术来保证系统漫游的真实感,最终实现了具有沉浸感、现实感、交互感的商场漫游系统。