Phase‐Field Modeling of Microstructural Evolution by Freeze‐Casting

Freeze‐casting has attracted great attention as a potential method for manufacturing bioinspired materials with excellent flexibility in microstructure control. The solidification of ice crystals in ceramic colloidal suspensions plays an important role during the dynamic process of freeze‐casting. During solidification, the formation of a microstructure results in a dendritic pattern within the ice‐template crystals, which determines the macroscopic properties of materials. In this paper, the authors propose a phase‐field model that describes the crystallization in an ice template and the evolution of particles during anisotropic solidification. Under the assumption that ceramic particles represent mass flow, namely a concentration field, the authors derive a sharp‐interface model and then transform the model into a continuous initial boundary value problem via the phase‐field method. The adaptive finite‐element technique and generalized single‐step single‐solve (GSSSS) time‐integration method are employed to reduce computational cost and reconstruct microstructure details. The numerical results are compared with experimental results, which demonstrate good agreement. Finally, a microstructural morphology map is constructed to demonstrate the effect of different concentration fields and input cooling rates. The authors observe that at particle concentrations ranging between 25 and 30% and cooling rate lower than ?5° min^?1 generates the optimal dendrite structure in freeze casting process.

     

Complementarity framework for non‐linear dynamic analysis of skeletal structures with softening plastic hinges

In this paper, we describe an algorithm for the incremental state update of elasto‐plastic systems with softening. The algorithm uses a complementary pivoting technique and is based on casting the incremental state update as a complementarity problem. In developing the algorithm, we take advantage of the special features of solid and structural mechanics problems to achieve good computational performance, and hence the ability to compute numerical solutions to practical size problems. For example, the notion of a tangent stiffness matrix arises. Numerical examples using models of skeletal structures are presented to demonstrate the practicability of the algorithm. The numerical examples also raise some interesting questions about multiplicity of the solutions. Copyright © 2010 John Wiley & Sons, Ltd.     

Joining Between NiAl and Heat Resistant Alloys by Reactive Casting

NiAl is a low‐density and high‐strength structural material that has potential for use at temperatures higher than currently possible with conventional superalloys. However, NiAl is brittle at temperatures below 600 K, which is one of its most significant disadvantages and impedes its practical use as a structural material. A possible way to overcome this problem will be joining of it to ductile structural materials. The authors have recently developed a new technique named “reactive casting,” which enables the superheated liquid of a high‐melting‐point intermetallic compound to be produced without the need of external heating. In this study, they investigate the feasibility of joining between NiAl and heat resistant alloys such as nickel‐base and iron‐base alloys by the reactive casting method.     

Optimal Scheduling of Casting Sequence Using Genetic Algorithms

Scheduling a casting sequence involving a number of orders with different casting weights and satisfying due dates of is an important optimization problem often encountered in foundries. In this article, we attempt to solve this complex, multi-variable, and multi-constraint optimization problem by using different implementations of genetic algorithms (GAs). In comparison with a mixed-integer linear programming solver, GAs with problem-specific operators are found to provide faster (with a subquadratic computational time complexity) and more reliable solutions to very large (more than 1 million integer variables) casting sequence optimization problems. In addition to solving the particular problem, the study demonstrates how problem-specific information can be introduced in a GA for solving complex real-world problems.     

Scheduling of die casting operations including high-mix low-volume and line-type production

This article addresses the scheduling problem of a real die casting shop. The problem is of practical importance and yet complicated, especially for a modern casting environment where a variety of cast products made of different alloys are simultaneously manufactured in relatively small lot sizes. As a simple and robust scheduling methodology, a Linear Programming (LP) model is proposed so as to determine the quantity of each product in a casting shift. The solution of the LP model maximises the average efficiency of melting furnaces, i.e., the percentage use of molten alloys throughout the shifts. Our model can represent a most general casting environment to the extent that some die casting machines carry out frequent in-process die exchanges for flexible manufacturing. At the same time, we employ line-type casting as well as a combination die with multi-cavities which can cast dissimilar shapes concurrently. In the high-mix low-volume manufacturing world, the proposed LP model can assist the die casting industry to strengthen its competence by providing an optimal schedule that satisfies practical constraints on casting processes.     

Verbund‐Gießschmieden hybrider Aluminiumbauteile

In compound‐cast‐forging of hybrid aluminum parts the positive characteristics of casting and forging processes as well as the different materials are combined. This makes it possible to produce components with complex geometries and different local characteristics. Component areas with high complexity (e. g. with an undercut) are cast, areas that are exposed to high mechanical stresses, are forged. In the conducted investigations a preformed, massive formed semi‐finished part out of a wrought aluminum alloy was joined with a die‐cast aluminum alloy by casting and forming from the casting temperature in one cast‐forging process. The results of the studies show a good joining quality of cast‐forged components made of different aluminum alloys.     

A Combined Electromagnetic Levitation Melting,Counter‐Gravity Casting,and Mold Preheating Furnace for Producing TiAl Alloy

In this work, the authors describe the development of TiAl castings over a wide range of approaches. To overcome casting defects and cracks that appear in TiAl castings, a novel furnace is designed and constructed. The design combines induction skull melting, counter‐gravity casting, and mold heating, which facilitates both filling and microstructure formation via a controllable process. This aim is to improve shaping capabilities and microstructural control for TiAl castings. Melting and casting experiments on TiAl alloys with a nominal composition corresponding to Ti–48Al–2Cr–2Nb (at%) are carried out and discussed. X‐ray examinations indicate that the shaping of the TiAl components dose not contain macro casting defects, validating the advantages of this technique. The results are of interest to researchers devoted to technical innovations and modifications for TiAl casting at the industrial scale.

     

Scheduling continuous aluminium casting lines

This study considers the problem of scheduling casting lines of an aluminium casting and processing plant. In aluminium processing plants, continuous casting lines are the bottleneck resources, i.e. factory throughput is limited by the amount of aluminium that can be cast. The throughput of a casting line might be increased by minimizing total setup time between jobs. The objective is to minimize setup time on production lines for a given time period while balancing workload between production lines to accommodate potential new orders. A mathematical formulation for scheduling jobs to minimize the total setup time while achieving workload balance between the production lines is presented. Since the casting scheduling problem is an NP-hard problem, even with only one casting line, a four-step algorithm to find good solutions in a reasonable amount of time is proposed. In this process, a set of asymmetric travelling salesman problems is followed by a pairwise exchange heuristic. The proposed procedure is applied to a case study using real casting data.     

Solving a mixed integer linear program with times setup for the steel-continuous casting planning and scheduling problem

In this paper, we present a novel model that generalise the steelmaking continuous casting planning and scheduling problem. The model includes three stages: converters namely CV, refining stands namely RS and continuous castings namely CC. The obtained problem can be formulated as a mathematical program with typical constraints, namely the times setup constraints. We develop a mixed integer linear program (MILP) to schedule several sequences of charges for more than two continuous castings devices. The aim is: (i) on one hand, to schedule a list of several sequences that are already ordered for each continuous casting with times setup between two successive sequences, (ii) on the other hand, to determine the optimal order of the successive sequences. We use a benchmark and randomly generated instances to test the model and solved by mean of the commercial software solver Cplex v12.5. These problems span a variety of instances varying from small to large sized instances with different intrinsec parameters as the availability date for a converter CV or the variation intervals of the start time for the first charge at the continuous casting CC stage. We analyse the efficiency of the proposed model based on the CPU time and show the time limitations of the model for large instances. Also, we show the robustness of the model when modifying the initial (starting) state.     

Modelling the pressure die casting process using a hybrid Finite‐Boundary Element model

In this paper an efficient three‐dimensional hybrid thermal model for the pressure die casting process is described. The Finite Element Method (FEM) is used for modelling heat transfer in the casting, and the Boundary Element Method (BEM) for the die. The FEM can efficiently account for the non‐linearity introduced by the release of latent heat on solidification, whereas the BEM is ideally suited for modelling linear heat conduction in the die, as surface temperatures are of principal importance. The FE formulation for the casting is based on the modified effective capacitance method, which provides high accuracy and unconditional stability. This is essential for accurate modelling of the pressure die casting process and efficient coupling to the BEM. The BE model caters for surface phenomena such as boiling in the cooling channels, which is important, as this effectively controls the manner in which energy is extracted. The die temperature is decomposed into two components, one a steady‐state part and the other a time‐dependent perturbation. This approach enables the transient die temperatures to be calculated in an efficient way, since only die surfaces close to the die cavity are considered in the perturbation analysis. A multiplicative Schwarz method for non‐overlapping domains is used to couple the individual die blocks and casting. The method adopted makes use of the weak coupling between the domains, which is a result of the relatively high interfacial thermal resistance that is present. Numerical experiments are performed to demonstrate the computational effectiveness of the approach. Predicted die and casting temperatures are compared with thermocouple measurements and good agreement is indicated. Copyright © 1999 John Wiley & Sons, Ltd.     

A new approach to improving the macrosegregation in zirconium‐containing magnesium‐lithium alloy

In the preparation process of zirconium‐containing magnesium alloy, although zirconium is introduced into alloy by magnesium‐zirconium master alloy, the settling of zirconium particles has always been a key problem. In this study, the magnesium‐30wt.%zirconium master alloy was added into magnesium‐14wt.%lithium‐zinc alloy melt in the form of the block (about 20 mm) and the particles (about 20 μm), respectively, and then magnesium‐14wt.%lithium‐zinc with 0.5 wt.% zirconium alloy were prepared using stir‐casting process. Macrosegregation of major element (zirconium), microstructure and microhardness at different casting positions were examined to investigate the effect of zirconium addition methods on macrosegregation of magnesium‐14wt.%lithium‐zinc alloy. The results show that, for the block magnesium‐zirconium master alloy addition, there is obvious macrosegregation in alloy ingots, the zirconium contents at the top position of ingot are higher than that at the bottom by nearly 200 %. The method of particles master alloy addition can effectively improve macrosegregation, the difference in zirconium contents between the top and bottom is less than 16 %.     

Structural shape and topology optimization of cast parts using level set method

This paper presents a level set‐based shape and topology optimization method for conceptual design of cast parts. In order to be successfully manufactured by the casting process, the geometry of cast parts should satisfy certain moldability conditions, which poses additional constraints in the shape and topology optimization of cast parts. Instead of using the originally point‐wise constraint statement, we propose a casting constraint in the form of domain integration over a narrowband near the material boundaries. This constraint is expressed in terms of the gradient of the level set function defining the structural shape and topology. Its explicit and analytical form facilitates the sensitivity analysis and numerical implementation. As compared with the standard implementation of the level set method based on the steepest descent algorithm, the proposed method uses velocity field design variables and combines the level set method with the gradient‐based mathematical programming algorithm on the basis of the derived sensitivity scheme of the objective function and the constraints. This approach is able to simultaneously account for the casting constraint and the conventional material volume constraint in a convenient way. In this method, the optimization process can be started from an arbitrary initial design, without the need for an initial design satisfying the cast constraint. Numerical examples in both 2D and 3D design domain are given to demonstrate the validity and effectiveness of the proposed method. Copyright © 2017 John Wiley & Sons, Ltd.     

A hybrid SVM and supervised learning approach to fuzzy min‐max hyperbox classifiers

Abstract

In this paper, a fuzzy min‐max hyperbox classifier is designed to solve M‐class classification problems using a hybrid SVM and supervised learning approach. In order to solve a classification problem, a set of training patterns is gathered from a considered classification problem. However, the training set may include several noisy patterns. In order to delete the noisy patterns from the training set, the support vector machine is applied to find the noisy patterns so that the remaining training patterns can describe the behavior of the considered classification system well. Subsequently, a supervised learning method is proposed to generate fuzzy min‐max hyperboxes for the remaining training patterns so that the generated fuzzy min‐max hyperbox classifier has good generalization performance. Finally, the Iris data set is considered to demonstrate the good performance of the proposed approach for solving this classification problem.     

TMF criteria for Lost Foam Casting aluminum alloys

The purpose of this paper is to define a thermo‐mechanical fatigue criterion in order to predict the failure of aluminum alloys components issued with the lost foam casting process and used in particular in the automotive industry. The microstructure of the studied materials (A356–A319 aluminum alloys) is clearly affected by the lost foam casting process which can directly affect the mechanical properties, the damage mechanisms and the fatigue failure of specimens and components. The major problem in defining a predictive fatigue criterion in this case is the fact that it should be applicable for the component which is submitted to complex multiaxial thermo‐mechanical loadings. Since many years, energy‐based criteria have been used to predict fatigue failure of this class of materials. Then, different energy‐based criteria are tested in order to take into account different types of triaxiality and mean stress effects corrections. The fatigue lifetime results predicted by both of them show a good agreement with experimental results.     

Engineering Design Processes: A Comparison of Students and Expert Practitioners

In this paper we report on an in‐depth study of engineering design processes. Specifically, we extend our previous research on engineering student design processes to compare the design behavior of students and expert engineers. Nineteen experts from a variety of engineering disciplines and industries each designed a playground in a lab setting, and gave verbal reports of their thoughts during the design task. Measures of their design processes and solution quality were compared to pre‐existing data from 26 freshmen and 24 seniors. The experts spent significantly more time on the task overall and in each stage of engineering design, including significantly more time problem scoping. The experts also gathered significantly more information covering more categories. Results support the argument that problem scoping and information gathering are major differences between advanced engineers and students, and important competencies for engineering students to develop. Timeline representations of the expert designers' processes illustrate characteristic distinctions we found and may help students gain insights into their own design processes.     

Process planning for multi-axis NC machining of free surfaces

Process planning for the manufacture of free surfaces is mainly concerned with determination of machining configuration. In this paper, we investigate the machining configuration problem stated as: For a given surface model, find (1) The minimum number of control axes, (2) The minimum range of the rotational axes, and (3) The workpart setup orientation. In deriving the solution algorithm, we ensured implementability by casting the problem into an algebraic domain. Using a digitized visibility map, called the binary spherical map, the machining configuration problem can be solved in a unified fashion without falling into numerical complexity. The solution algorithms are implemented and validated via computer simulations, indicating they can be implemented on the CAD/CAM system as a process planner.     

Partial-differential-equation-constrained amplitude-based shape detection in inverse acoustic scattering

In this article we discuss a formal framework for casting the inverse problem of detecting the location and shape of an insonified scatterer embedded within a two-dimensional homogeneous acoustic host, in terms of a partial-differential-equation-constrained optimization approach. We seek to satisfy the ensuing Karush–Kuhn–Tucker first-order optimality conditions using boundary integral equations. The treatment of evolving boundary shapes, which arise naturally during the search for the true shape, resides on the use of total derivatives, borrowing from recent work by Bonnet and Guzina [1–4] in elastodynamics. We consider incomplete information collected at stations sparsely spaced at the assumed obstacle’s backscattered region. To improve on the ability of the optimizer to arrive at the global optimum we: (a) favor an amplitude-based misfit functional; and (b) iterate over both the frequency- and wave-direction spaces through a sequence of problems. We report numerical results for sound-hard objects with shapes ranging from circles, to penny- and kite-shaped, including obstacles with arbitrarily shaped non-convex boundaries. Partial support for this work was provided by the US National Science Foundation under grant award CMS-0348484.     

Spray formed and rolled aluminium‐magnesium‐scandium alloys with high scandium content

Aluminium‐magnesium‐scandium alloys offer good weldability, high corrosion resistance, high thermal stability and the potential for high strength by precipitation hardening. A problem of aluminium‐scandium alloys is the low solubility of about 0.3 mass‐% scandium when using conventional casting methods. The solution of scandium can be raised by higher cooling rates during solidification. This was realised by spray forming of Al‐4.5Mg‐0.7Sc alloys as flat deposits. Further cooling rates after solidification should also be high to prevent coarse precipitation of secondary Al₃Sc. Therefore a cooling device was designed for the spray formed flat deposits. The flat deposits were rolled at elevated temperatures to close the porosity from spray forming. Microstructures, aging behaviour and tensile properties of the rolled sheets were investigated. Strength enhancements of about 100 MPa compared to conventional Al‐Mg‐Sc alloys were achieved.     

Level‐set topology optimization with many linear buckling constraints using an efficient and robust eigensolver

Linear buckling constraints are important in structural topology optimization for obtaining designs that can support the required loads without failure. During the optimization process, the critical buckling eigenmode can change; this poses a challenge to gradient‐based optimization and can require the computation of a large number of linear buckling eigenmodes. This is potentially both computationally difficult to achieve and prohibitively expensive. In this paper, we motivate the need for a large number of linear buckling modes and show how several features of the block Jacobi conjugate gradient (BJCG) eigenvalue method, including optimal shift estimates, the reuse of eigenvectors, adaptive eigenvector tolerances and multiple shifts, can be used to efficiently and robustly compute a large number of buckling eigenmodes. This paper also introduces linear buckling constraints for level‐set topology optimization. In our approach, the velocity function is defined as a weighted sum of the shape sensitivities for the objective and constraint functions. The weights are found by solving an optimization sub‐problem to reduce the mass while maintaining feasibility of the buckling constraints. The effectiveness of this approach in combination with the BJCG method is demonstrated using a 3D optimization problem. Copyright © 2016 John Wiley & Sons, Ltd.     

The Effects of Casting Temperature on the Glass Formation of Zr‐Based Metallic Glasses

The glass1‐forming ability of two alloys, Zr_64.9Al_7.9Ni_10.7Cu_16.5 and Zr₄₇Cu_37.5Ag_7.5Al₈, prepared by arc‐melting a mixture of Zr, Cu, Al, Ni and Ag elements is studied as a function of casting temperature. Other processing parameters such as the alloy melt mass, and the vacuum and injection pressures during the copper‐mold‐casting process are kept constant so just the influence of the casting temperature is considered. The casting temperature determines the characteristics of the liquid melt and the cooling rate. The glass‐forming ability is discussed in terms of dissipation of pre‐exiting, metastable local‐ordering clusters that act as nucleation sites promoting crystallization, the cooling rate at high casting temperatures, and the presence of oxygen in the alloys, which is increased at high casting temperatures. It is found that the glass‐forming ranges of alloys shrink as the glass‐forming size approaches a critical value. The optimum temperatures are around 1450 K and 1550 K for Zr_64.9Al_7.9Ni_10.7Cu_16.5 and Zr₄₇Cu_37.5Ag_7.5Al₈ alloys respectively. The alloys were studied by XRD, TEM, oxygen‐level determination, and DSC.