Thermal Modeling of Direct Digital Melt-Deposition Processes

Additive manufacturing involves creating three-dimensional (3D) objects by depositing materials layer-by-layer. The freeform nature of the method permits the production of components with complex geometry. Deposition processes provide one more capability, which is the addition of multiple materials in a discrete manner to create “heterogeneous” objects with locally controlled composition and microstructure. The result is direct digital manufacturing (DDM) by which dissimilar materials are added voxel-by-voxel (a voxel is volumetric pixel) following a predetermined tool-path. A typical example is functionally gradient material such as a gear with a tough core and a wear-resistant surface. The inherent complexity of DDM processes is such that process modeling based on direct physics-based theory is difficult, especially due to a lack of temperature-dependent thermophysical properties and particularly when dealing with melt-deposition processes. In order to overcome this difficulty, an inverse problem approach is proposed for the development of thermal models that can represent multi-material, direct digital melt deposition. This approach is based on the construction of a numerical-algorithmic framework for modeling anisotropic diffusivity such as that which would occur during energy deposition within a heterogeneous workpiece. This framework consists of path-weighted integral formulations of heat diffusion according to spatial variations in material composition and requires consideration of parameter sensitivity issues.     

Advances in Modeling and Simulation of Grinding Processes

In the last decade the relevance of modeling and simulation of grinding processes has significantly risen which is caused by industrial needs and is indicated by the number of publications and research activities in this area. This keynote paper results from a collaborative work within the STC G and gives an overview of the current state of the art in modeling and simulation of grinding processes: Physical process models (analytical and numerical models) and empirical process models (regression analysis, artificial neural net models) as well as heuristic process models (rule based models) are taken into account, and outlined with respect to their achievements in this paper. The models are characterized by the process parameters such as grinding force, grinding temperature, etc. as well as work results including surface topography and surface integrity. Furthermore, the capabilities and the limitations of the presented model types and simulation approaches will be exemplified.     

A framework for automated analysis and simulation of 3D polycrystalline microstructures. Part 2: Synthetic structure generation

This is the second of a two-part paper intended to develop a framework for collecting data, quantifying characteristics and subsequently representing microstructural information from polycrystalline materials. The framework is motivated by the need for incorporating accurate three-dimensional grain-level morphology and crystallography in computational analysis models that are currently gaining momentum. Following the quantification of microstructural features in the first part, this paper focuses on the development of models and codes for generating statistically equivalent synthetic microstructures. With input in the form of statistical characterization data obtained from serial-sectioning of the microstructures, this module is intended to provide computational modeling efforts with a microstructure representation that is statistically similar to the actual polycrystalline material.     

Multiscale, Multiphysics Numerical Modeling of Fusion Welding with Experimental Characterization and Validation

Various physical interfacial phenomena occur during the process of welding and influence the final properties of welded structures. As the features of such interfaces depend on physics that resolve at different spatial scales, a multiscale and multiphysics numerical modeling approach is necessary. In a collaborative research project Modeling of Interface Evolution in Advanced Welding, a novel strategy of model linking is employed in a multiscale, multiphysics computational framework for fusion welding. We only directly link numerical models that are on neighboring spatial scales instead of trying to link all submodels directly together through all available spatial scales. This strategy ensures that the numerical models assist one another via smooth data transfer, avoiding the huge difficulty raised by forcing models to attempt communication over many spatial scales. Experimental activities contribute to the modeling work by providing valuable input parameters and validation data. Representative examples of the results of modeling, linking and characterization are presented.     

Mixed logical dynamical model for back bead width prediction of pulsed GTAW process with misalignment

The purpose of this paper is to propose a kind of mixed logical dynamical (MLD) model to predict the back bead width of pulsed GTAW process with misalignment. Misalignment is considered as discrete input and the nonlinear welding process is approximated using piecewise linear models. A MLD model is then established and gives a good prediction quality of the back bead width of pulsed GTAW process with misalignment. The stability and reliability of the MLD model are tested by a closed loop control experiment. This study shows that the MLD framework is a good modeling method for pulsed GTAW process. Thus, a solid foundation for penetration control of welding process is established based on the MLD model.     

Advances in multi-scale modeling of solidification and casting processes

The development of the aviation, energy and automobile industries requires an advanced integrated product/process R&D systems which could optimize the product and the process design as well. Integrated computational materials engineering (ICME) is a promising approach to fulfill this requirement and make the product and process development efficient, economic, and environmentally friendly. Advances in multi-scale modeling of solidification and casting processes, including mathematical models as well as engineering applications are presented in the paper. Dendrite morphology of magnesium and aluminum alloy of solidification process by using phase field and cellular automaton methods, mathematical models of segregation of large steel ingot, and microstructure models of unidirectionally solidified turbine blade casting are studied and discussed. In addition, some engineering case studies, including microstructure simulation of aluminum casting for automobile industry, segregation of large steel ingot for energy industry, and microstructure simulation of unidirectionally solidified turbine blade castings for aviation industry are discussed.     

Overview on constitutive modeling for hydroforming with the existence of through-thickness normal stress

The hydroforming process is used widely across many industrial fields. High applied pressure during hydroforming makes it necessary to consider the influence of the through-thickness normal stress, while traditional approaches based upon a plane-stress assumption are not appropriate in such cases. Reliable constitutive models that consider the through-thickness normal stress are summarized in this paper, which focuses on the state of the art in the following several aspects: determine the flow stress curve with proper experimental methods and choose the measurement and computational methods to minimize the error as much as possible; select the proper three-dimensional anisotropic yield criterion for the specific material; Define the forming limit model and construct corresponding experimental verification method. The review of existing work has revealed several gaps in current knowledge of the hydroforming process accounting for the through-thickness normal stress. Conclusions are drawn concerning some critical issues and potential future developments in hydroforming modeling.     

Analysis of coupled ply damage and delamination failure processes in ceramic matrix composites

Damage and failure processes in two relatively complex ceramic matrix composite sub-elements are studied using both experiments and computational modeling. The sub-elements, representative of turbine blade-to-disk attachment region, are analyzed and tested under uniaxial loading at room temperature. The computational models consider – in a coupled way – both the nonlinear behavior of plies due to intra-laminar ply damage mechanism as well as the interlaminar delamination mechanism at the ply interfaces. Analyses and experiments indicate that delamination is the dominant failure mode and ply damage processes have a little effect on delamination initiation and growth. However, the ultimate failure of the sub-elements is due to ply damage mechanism, the evolution of which is strongly affected by the delamination process. The spatial locations of major delamination cracks and ply failure regions, as predicted by the models, are in good agreement with the experiments. In addition, a reasonable quantitative agreement between analyses results and experimental data is observed.     

基于动态PLS框架的铝合金脉冲MIG焊解耦控制设计及仿真

针对铝合金脉冲MIG焊中存在的多变量强耦合、难建模等特点,利用动态PLS控制框架在解耦、建模等方面的优势,将多变量的控制转换成为多个单回路的控制,并对各控制回路单独进行PID控制器设计.介绍了动态PLS建模及基于动态PLS建模框架的控制器设计的结构与特点,并将该控制器设计方法引入到铝合金脉冲MIG焊中,并进行仿真试验.仿真验证采用动态PLS框架的控制器设计方法能获得满意的动态和稳态特性,并可应用于其它焊接过程,为基于数据驱动的动态建模控制方法在复杂焊接过程中的应用奠定了基础.     

The laser surface modification of advanced ceramics: A modeling approach

A numerical approach for predicting microstructures during the laser surface modification of ceramics has been proposed. Laser surface modification is a near-non-equilibrium or non-equilibrium process involving high cooling rates (10²–10⁸ K/s) leading to rapid solidification. As the basic governing solidification theory behind conventional processes like casting and laser processing is the same, the approach and the theory behind the conventional processes can be extended to such near-non-equilibrium processes by adequately modifying the conventional models. This study looks at various challenges in modeling the laser processing phenomena and elaborates on present efforts and future modeling goals.     

一种面向企业经营过程的工作流模型

作为支持企业经营过程重组、经营过程自动化的一种手段,工作流技术得到越来越广泛的应用。而作为工作流管理系统理论研究和实际应用基础的工作流模型,成为工作流技术的主要研究方向之一。文章针对目前工作流过程模型在描述能力、柔性以及过程重用方面的不足,提出一种基于UML2.0活动图,具有可扩展机制,以简单、直观的图形化表示方法描述企业业务流程的工作流建模方法,同时,基于J2EE平台,开发了支持该建模方法的建模工具,并使用该工具建立了威海海都食品集团的典型业务流程实例。     

Precision high temperature lead-free solder interconnections by means of high-energy droplet deposition techniques

This paper presents a number of numerical models that illustrate the experimental details of the key physical phenomena affecting the operation of novel materials deposition processes for electronics assembly. These processes include both laser and electric arc based droplet deposition processes. These are being developed in the electronics industry to allow the use of new lead-free alloys as replacements for high temperature lead based alloys, such as Sn5Pb95. The paper presents models of physical processes with respect to the desired process metrics of droplet size and deposition accuracy and reviews the potential limiting product - process interactions such as excessive thermal excursions and their effects on the target materials being joined.     

Intelligent Kano classification of product features based on customer reviews

Product features can be classified into different categories based on customer opinions. The rapid development of artificial intelligence and machine learning paves the way toward computational analysis of customer reviews for opinion mining. This paper presents an Intelligent Kano framework to extract, quantify, and classify different product features based on customer reviews. The framework is enabled by a novel integration of multiple artificial intelligence and machine learning techniques such as sentiment analysis and anomaly detection. A case study is conducted to validate the framework’s effectiveness. Over 12,000 customer reviews on two coffee machines are analyzed for the classification.     

Numerical analysis of friction stir welding process

Friction stir welding (FSW), which has several advantages over the conventional welding processes, is a solid-state welding process where no gross melting of the material being welded takes place. Despite significant advances over the last decade, the fundamental knowledge of thermomechanical processes during FSW is still not completely understood. To gain physical insight into the FSW process and the evaluation of the critical parameters, the development of models and simulation techniques is a necessity. In this article, the available literature on modeling of FSW has been reviewed followed by details of an attempt to understand the interaction between process parameters from a simulation study, performed using commercially available nonlinear finite element (FE) code DEFORM. The distributions of temperature, residual stress, strain, and strain rates were analyzed across various regions of the weld apart from material flow as a means of evaluating process efficiency and the quality of the weld. The distribution of process parameters is of importance in the prediction of the occurrence of welding defects, and to locate areas of concern for the metallurgist. The suitability of this modeling tool to simulate the FSW process has been discussed. The lack of the detailed material constitutive information and other thermal and physical properties at conditions such as very high strain rates and elevated temperatures seems to be the limiting factor while modeling the FSW process.     

Optimal temperature variable selection by grouping approach for thermal error modeling and compensation

One of the difficult issues in a thermal error compensation scheme is to select appropriate temperature variables as well as to obtain accurate thermal error component models. In this research, an optimization method is presented to overcome this difficulty. The optimization objective function is formulated by a modified model adequacy criterion based on the Mallows' C_p statistic. A new search method is developed for discrete search domains with non-directional or unknown-order variables. The search process includes correlation grouping, representative searching, group searching and variable searching. It not only ensures optimal results but also reduces computational time greatly. One modeling example is presented. The optimal model is found with a 0.982 R²-value using four temperature variables selected from 46 candidates of temperature variables. The largest error residual is reduced down to 2.2 microns from 20.0 microns. The comparison of modeling results from the proposed approach and three other modeling methods is addressed as well.     

3D FE modeling of cold rotary forging of a ring workpiece

Cold rotary forging is an advanced but much complex incremental metal forming process with multi-factors coupling interactive effects. Previous researches concentrated mainly on studying the cold rotary forging process of the cylindrical workpiece based on the analytical and experimental methods. In the current work, in order to better investigate and understand the cold rotary forging process of the ring workpiece, a 3D elastic–plastic dynamic explicit FE model of the process is developed under the ABAQUS software environment. Some key technologies of modeling methods are dealt with reasonably and some key forming conditions are also determined properly. The reliability of the proposed 3D FE model is verified experimentally. Through simulation, the distributions and histories of different field-variables such as stress, strain and force and power parameters are investigated in detail. The research results provide valuable guidelines for better understanding the deformation characteristics of cold rotary forging of the ring workpiece. Furthermore, the modeling methods presented in this paper have the general significance to study other rotary forging processes, such as the hot rotary forging process, the rotary forging process of workpiece with complex profile and so on.     

A new spectral framework for establishing localization relationships for elastic behavior of composites and their calibration to finite-element models

Localization relationships aim to connect the microscale response in a composite material to the macroscale loading conditions, while taking into account the local details of the microstructure at the location of interest. Such linkages are at the core of multi-scale modeling of materials since they provide efficient scale-bridging relationships. These structure–property linkages are expressed through fourth-rank localization tensors derived from higher-order homogenization theories. This paper builds upon a recently developed spectral framework called microstructure-sensitive design that was established to formulate localization relationships for the elastic response in composite materials. The method casts existing higher-order homogenization theory into a Fourier space to achieve substantial computational advantages over other multi-scale modeling approaches. More specifically, it is demonstrated that the spectral approach transforms the localization relationship into a simple algebraic series comprising polynomials of the microstructure coefficients. A remarkable feature of this new method is that the coefficients of the polynomial expression, termed influence coefficients, are completely independent of the morphological details in a specific microstructure. Consequently, they need to be established only once. It is demonstrated in this paper that an appropriately truncated localization relationship can be obtained by calibration of the influence coefficients to the results of finite-element models. These, and other, salient features of the proposed spectral framework are first theoretically established, and then demonstrated with a simple case study.