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Multi-turn wave springs have the potential to replace conventional coil springs in a variety of applications by providing the same force and deflection characteristics and using only half the space. In this paper, we study the mechanical behavior of a fiber-reinforced composite single turn wave spring as a potential to replace conventional steel based wave springs. Wave springs are more compact than coil springs and are adaptable for manufacturing using composites. The use of composites for the wave spring represents significant challenges in not only understanding the elastic response, but also the failure and fatigue characteristics. In this paper, a wave spring is studied using experimental, analytical and numerical approaches. The analytical approach proposed is based on the theory of circular beams loaded normal to the plane of curvature. The models are extended to orthotropic carbon-epoxy wave springs with arbitrary geometric parameters. Parametric numerical models enable a detailed understanding the effects of geometry on the mechanical behavior of the wave springs. Quasi-static and fatigue experiments are performed on the composite wave springs demonstrating excellent repeatability and a robust fatigue behavior. [ABSTRACT FROM AUTHOR]

[Display omitted] • The PGNN architecture is a promising approach for training a network that can predict design parameters based on design requirements. • By utilizing a parametrized unit-cells dataset, unit-cells beyond the traditional Cubic or Orthotropic unit-cells can be included, providing greater flexibility in the design process. • Our inverse design framework outperforms search and lookup table methods in terms of accuracy and computational power. This paper investigates the feasibility of data-driven methods in automating the engineering design process, specifically studying inverse design of cellular mechanical metamaterials. Traditional methods of designing cellular materials typically rely on trial and error or iterative optimization, which often leads to limited productivity and high computational costs. While data-driven approaches have been explored for the inverse design of cellular materials, many of these methods lack robustness and fail to consider the manufacturability of the generated structures. This study aims to develop an efficient inverse design methodology that accurately generates mechanical metamaterial while ensuring the manufacturability of predicted structures. To achieve this, we have created a comprehensive dataset that spans a broad range of mechanical properties by applying rotations to cubic structures synthesized from the nine cubic symmetries of cubic materials. We then employ a physics-guided neural network (PGNN) consisting of dual neural networks: a generator network, which serves as the inverse design tool, and a forward network, which acts as a physics-guided simulator. The goal is to generate desired anisotropic stiffness components with unit-cell design parameters. The results of our inverse model are examined with three distinct datasets and demonstrate high computational efficiency and prediction accuracy compared to conventional methods. [ABSTRACT FROM AUTHOR]

Abstract: Aseptic loosening is one of the main reasons for the revision of a total knee replacement (TKR). The design of the key component of a TKR, the femoral component, is particularly problematic because its failure can be the result of different causes. This makes the development of new biomaterials for use in the femoral component a challenging task. This paper focuses on the engineering design aspects in order to understand the limitations of current materials and design deficiencies. The paper describes the introduction of a new biomaterial for a femoral component and justifies the recommendation to use multi-functional materials as a possible solution to aseptic loosening. The potential advantages of applying functionally graded biomaterials (FGBMs) in prosthetic femur are explained by reducing the leading causes of failure including wear, micro-motion and stress-shielding effect. The ideas presented in this paper can be used as the basis for further research on the feasibility and advantages of applying FGBM in other superior implant designs. [Copyright &y& Elsevier]

Abstract: When selecting materials for a building, architects are guided not only by structural and functional requirements but also consider aspects relating to the sensory effect and experience. The material information and selection tools available for architects are, however, often dominated by technical material data without providing systematic knowledge on experience aspects of materials. Hence, no comprehensive material information is available to the architect. This paper aims to identify, organize, and map the different elements contributing to the material selection process for buildings, and generate a schematic of basic material selection considerations for an architectural design project. The paper discusses the findings of three studies investigating architects’ materials selection process at different stages of the design process. As a result, architects’ materials selection considerations are identified and organized according to four categories: Context, Manufacturing, Material aspects, and Experience. These considerations are discussed in relation to each other as well as in reference to material selection research in architecture and industrial design. The results confirm the importance of aspects relating to experience in an architectural material context and emphasize the need for further research and information on the topic of material experience in architecture. [Copyright &y& Elsevier]

Abstract: Glass products have applications in design engineering, and they can solve many special problems. These materials can work in situations in which plastics and metals would fail and need to be part of designer’s repertoire. In some situations, by using these materials, some difficult problems would be solved. This paper contains a number of chapters as follows: a brief about ceramics family, a short history of glass, a brief about physics and the technology of glass fabrication, recently developed glasses with special destinations, testing methods and news about glass parts processing (grinding, waterjet processing, laser cutting, nanoimprint lithography, etc.). The last chapter of this review paper contain some strategic lines of glass usage in industry and estimations about the future of glass development. [Copyright &y& Elsevier]

[Display omitted] • Highlighting the status, inherent barriers, and challenges of multi-material 4D printing. • A strategic research roadmap based on the opportunities and challenges in engineering and interdisciplinary design. • Proposal of a design for 4D printing framework. The combination of scientific advances in additive manufacturing (AM) and smart materials (SMs) has enabled the development of a new interdisciplinary research area: 4D printing. This technology offers – via stimuli-responsive materials – promising transformation capabilities to objects whether at the functional, shape, or property levels. By considering such capabilities, researchers from multiple disciplines have investigated a large spectrum of stimuli-SMs associations with proofs-of-concept built from either commercial or custom 3D printers. Despite the abundant initiatives, 4D printing requires additional developments to meet robust system applications for the industry. The paper aims to highlight the status, inherent barriers, and challenges of 4D printing to be addressed from a product-systems design perspective. It firstly reminds the fundamentals of SMs, processes, stimulus, and AM to which a synthesis of significant research works related to 4D printing highlighting the current status as well as scientific, technical, and organizational limitations is provided. Beyond this comprehensive study, the paper emphasizes opportunities and challenges from multiple perspectives and draws a research roadmap for engineering design and cross-disciplinary design. The outcome of the work tends to structure research efforts for the next decade towards the development of smart products that meet use for humans and the industry. [ABSTRACT FROM AUTHOR]

Abstract: The importance of materials selection in engineering design is well recognised. There are already plenty of formalised methods to support selection of individual materials, where the requirements on the materials are, respectively, known. Practical design problems, however, often involve materials in combination – the multiple materials jointly contribute to the performance of the system to produce optimal design metrics; and the selection of materials is often coupled with the determination or design of structural components and their configuration. To address these problems, this paper recommends a multiple-mapping strategy and an inter-level behavioural modelling strategy. The former can simultaneously consider both structural and materials solutions in supporting design decision-making at the early design stage; while the latter can provide a platform for the designer to work out the couplings among the properties of the materials and their corresponding components, thus supporting design decision-making in selecting materials when they are applied in combination, which is generally at the downstream design stage. The paper also discusses the implications and difficulties in providing optimal solutions to the addressed problems; and based on this, to propose some prospects of future work to further improve these design strategies. [Copyright &y& Elsevier]

Materials selection as a significant step in engineering design process can be effectively implemented with the aid of MADM methods. The traditional MADM approaches only focus on beneficial or non-beneficial attributes to choose the optimal material; however, the selection should be made considering target values of attributes in some cases. In spite of practical applications of the target-based decision-making specially in engineering design problems, few studies have focused on the field. In the present paper, we developed a target-based MULTIMOORA method through introducing a normalization technique for materials selection in biomedical applications. We utilized two combinations of subjective, objective, and inter-attribute correlation effect significant coefficients to give importance to attributes. The information entropy and standard deviation concepts were used to assign two objective significant coefficients. This assumption leads to two modes of solution. Each mode has three subordinate and a final rankings. The final ranks of the two modes were consolidated into an aggregate ranking. The final and aggregate rankings were obtained using the dominance theory. We discussed two real-world biomedical engineering problems including materials selection for femoral components of hip and knee joint prostheses. Our aggregate rankings for the practical cases were compared with the results of previous studies. [ABSTRACT FROM AUTHOR]

Considerable effort has been spent on the development of normalization models in multi-attribute decision-making (MADM) but despite all of these there is no definitive answer to question: which technique is the most appropriate? Therefore, after a thorough review of the literature, thirty-one methods were identified, classified and evaluated for use in materials selection problems. The objective of this paper is to examine the shortcomings of normalization methods and suggest ways of improving their use in the engineering design decision-making process. The emphasis is placed on materials selection, for problems that include target criteria, as well as cost and benefit considerations, typically seen in more challenging applications such as aerospace and biomedical engineering. It is shown that although many normalization methods may appear to be minor variants of each other, these nuances can have important consequences in engineering design decision-making. To conclude, some dimensionless methods are proposed. The result of this research investigation will help ensure engineering decision makers in general improve their current use of MADM methods but in particular aid designers in developing suitable design performance indices for materials selection. [ABSTRACT FROM AUTHOR]

Considerable effort has been spent on the development of normalization models in multi-attribute decision-making (MADM) but despite all of these there is no definitive answer to question: which technique is the most appropriate? Therefore, after a thorough review of the literature, thirty-one methods were identified, classified and evaluated for use in materials selection problems. The objective of this paper is to examine the shortcomings of normalization methods and suggest ways of improving their use in the engineering design decision-making process. The emphasis is placed on materials selection, for problems that include target criteria, as well as cost and benefit considerations, typically seen in more challenging applications such as aerospace and biomedical engineering. It is shown that although many normalization methods may appear to be minor variants of each other, these nuances can have important consequences in engineering design decision-making. To conclude, some dimensionless methods are proposed. The result of this research investigation will help ensure engineering decision makers in general improve their current use of MADM methods but in particular aid designers in developing suitable design performance indices for materials selection. [ABSTRACT FROM AUTHOR]

In engineering design, the decision to select an optimal material has become a challenging task for the designers, and the evaluation of alternative materials may be based on some multiple attribute decision making (MADM) methods. However, the current methods for material selection may induce the information losing and cannot represent the real preference of decision maker precisely. Therefore, in this paper, inspired by the idea of the intuitionistic linguistic variables, we define a new fuzzy variable called uncertain membership linguistic variable (UMLV) which composes two linguistic variables and membership degrees of elements to the linguistic variables. Meanwhile, the operational laws, score function, accuracy function and comparison rules of the UMLV are defined. Then, some aggregation operators are developed for aggregating the uncertain membership linguistic information such as the uncertain membership linguistic weighted average (UMLWA) operator, the uncertain membership linguistic weighted geometric (UMLWG) operator, the uncertain membership linguistic ordered weighted average (UMLOWA) operator and the uncertain membership linguistic ordered weighted geometric (UMLOWG) operator, and some desirable properties of these operators are discussed. Based on the proposed operators, an approach is proposed for material selection problems under uncertain membership linguistic environment. Finally, two numerical examples for material selection are given to illustrate the application of the proposed approach. [ABSTRACT FROM AUTHOR]

[Display omitted] • Deep reinforcement learning was used to find the optimal sequences of design decisions to optimize elementally discretized structures. • This work offers a gradient-free approach to solving the compliance minimization topology optimization problem. • The deep reinforcement learning agent was trained using an interactive environment built to capture compliance minimization relevant information. • The agent designed optimal topologies using a two-step progressive refinement method leading to improved efficiency and solution detail. Advances in machine learning algorithms and increased computational efficiencies give engineers new capabilities and tools to apply to engineering design. Machine learning models can approximate complex functions and, therefore, can be useful for various tasks in the engineering design workflow. This paper investigates using reinforcement learning (RL), a subset of machine learning that teaches an agent to complete a task through accumulating experiences in an interactive environment, to automate the designing of 2D discretized topologies. RL agents use past experiences to learn sequential sets of actions to best achieve some objective. In the proposed environment, an RL agent can make sequential decisions to design a topology by removing elements to best satisfy compliance minimization objectives. After each action, the agent receives feedback by evaluating how well the current topology satisfies the design objectives. After training, the agent was tasked with designing optimal topologies under various load cases. The agent's proposed designs had similar or better compliance minimization performance to those produced by traditional gradient-based topology optimization methods. These results show that a deep RL agent can learn generalized design strategies to satisfy multi-objective design tasks and, therefore, shows promise as a tool for arbitrarily complex design problems across many domains. [ABSTRACT FROM AUTHOR]

Abstract: In engineering design, the selection of material alternatives usually depends of different criteria based on the specific problem. Due to the different units of this criteria, a normalization process is needed in the selection model. A lot of normalization approach can be found in literature and at the same time many algorithms have been developed to ensure the optimal material selection for a certain industrial application. Two elements of reflection can be drawn from the analysis of these. The first is the absence of an aided support to the selection of the correct engineering criteria by whom operate the selection process. The second is the need to define a weighting method that at the same time can be user-friendly to use and representative of the project’s needs. A new selection model based on the integration between House of Quality and the Comprehensive Vikor Algorithm is presented in this paper. This approach, called Integral Aided Material Selection (IAMS), can overcome the main lack of traditional material selection model and provide a real support tool to the project team. That way the project team can optimally choose the selection criteria and assign to these the correct priority coherently with the project needs. A case study is presented to illustrate and justify the proposed method. The topic of the case study concerns the identification of the best coating for the protection of an aluminum alloy substrate (Al-7075) from the effects of abrasive wear against an alternating counterpart made by a high-strength cast iron. [Copyright &y& Elsevier]

Abstract: Foam-filled tubes have recently gained attention due to their excellent energy absorption capacity. In order to improve the crashworthiness of foam-filled tubes, the energy absorption characteristics of two kinds of functionally lateral graded foam-filled tubes (FLGFTs) are investigated in this paper. Based on the numerical results, it is found that each of the two kinds of FLGFTs has more excellent energy absorption capacity than the ordinary uniform foam-filled tube (UFT) with the same weight. In addition, it can also be found that the gradient exponential parameter m which controls the variation of foam density gives rise to significant effects on the crashworthiness of FLGFTs. Thus, in order to seek for the optimal gradient exponential parameter, the two kinds of FLGFTs are optimized by multiobjective particle swarm optimization (MOPSO) algorithm, aiming to achieve the maximum specific energy absorption (SEA) and the minimum peak crushing force (PCF). During the process of multiobjective optimization design, the 7th-order polynomial functions of SEA and PCF are established and found to be accurate enough for engineering design. The results obtained by optimizations further indicate that the optimal FLGFT performs more excellent energy absorption characteristics than ordinary UFT. The optimization design data is a good guidance for the crashworthiness design of FLGFTs. [Copyright &y& Elsevier]

Abstract: The choice of a particular material, for a certain product, to perform a certain function, is a task that is all too often jumped over, either because the choice looks obvious, or because habits of convergent thinking lead the engineering designer to persist in the most usual material for the application. Done in the early stages of product development, the choice of materials involves complex decision-making processes, balancing intricate functional, technological and economic criteria reflecting the function of the part/product, the manufacturing process and the production volumes and final cost. Development teams rely on some basic methods to decide on materials using engineering properties as benchmarks, but such methods seldom address the whole problem of material-function-shape-process-cost-environmental impacts. This paper starts with an overview of the existing methods for selecting materials and then moves onto propose a new selection procedure (Materials Selection Engine) that overcomes some of the limitations found in the former methods. It uses the materials engineering properties to accommodate their technical fitness, but also considers life cycle cost items and environmental impacts to create a decision space in which the best materials for the application are mapped and classified. According to the importance the design team wants to give to economics and environment issues and to upstream and downstream life phases more informed decisions can then be made. A case study is presented aiming at a better understanding of the procedure proposed. [Copyright &y& Elsevier]

Abstract: Ranking and selection of the optimal material is an important stage in the engineering design process. However, most of the methods proposed for ranking in materials selection have tended to focus on cost and benefit criteria, with target values receiving much less attention in spite of their importance in many practical decision-making problems such as selecting materials to best match the properties of human tissue in biomedical engineering applications. In response to this perceived gap, the development of a new normalization technique is considered in this paper that provides an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and objective weighting in materials selection. There are four example cases included to validate the accuracy of outcomes from the proposed model. It is believed that the proposed decision-making model is suitable for linking to material databases and has the potential to enhance the efficiency of computer-aided materials selection systems. [Copyright &y& Elsevier]

Abstract: The role of materials in the engineering design process has already been well recognized. Choice of an appropriate material for a particular product is one of the critical tasks for the designers. Designers need to identify materials with specific functionalities in order to find feasible design concepts and fulfill the product’s end requirements. There is a vast array of materials with diverse properties available to the designers to satisfy different design requirements. The large number of available materials together with the complex relationships between various selection criteria, often make the material selection process a difficult and time consuming task. A systematic and efficient approach towards material selection is necessary in order to select the best alternative for a given engineering application. This paper focuses on the application of four preference ranking-based multi-criteria decision-making (MCDM) methods for solving a gear material selection problem. These are extended PROMETHEE II (EXPROM2), complex proportional assessment of alternatives with gray relations (COPRAS-G), ORESTE (Organization, Rangement Et Synthese De Donnes Relationnelles) and operational competitiveness rating analysis (OCRA) methods. Using these four methods, a list of all the possible choices from the best to the worst suitable materials is obtained taking into account different material selection criteria. The ranking performance of these methods is also compared with that of the past researchers. [Copyright &y& Elsevier]

Abstract: Materials selection is an onerous but very important activity in the design process. An inappropriate choice of material(s) can adversely affect the productivity and profitability and hence reputation of a manufacturing organization. The complexity of materials selection makes multi-criteria analysis an invaluable tool in the engineering design process. However, the application of various multi-criteria decision making (MCDM) methods can yield different results, especially when alternatives lead to similar performance. Therefore, an aggregation technique is proposed in this paper for optimal decision-making. In this approach, ranking orders obtained by various MCDM methods are used as the input of the suggested procedure and the outputs are aggregation rankings, which help designers and engineers to reach a consensus on materials selection for a specific application. An illustrative example is given to demonstrate the application of this procedure and its effectiveness in obtaining optimal materials selection. [Copyright &y& Elsevier]

Abstract: This review paper evaluates the current status of the exploitation of engineering materials for design purposes with respect to developments in the respective disciplines, through a structured review of the content of Materials & Design journal over 30years of publication. This review updates strategically the two previous reviews, with an emphasis this time placed on changes occurring over the last 10years, making appropriate reference to the earlier investigations to explain noteworthy developments. The new information presented is again derived from the abundance of technical knowledge contained from within the many varied and growing number of high quality articles in the journal, supplemented by the author’s personal comments and experience of the field. [ABSTRACT FROM AUTHOR]

Abstract: In engineering design, material alternatives evaluate according to different criteria depending on the objectives of the problem. Performance ratings for different criteria are measured by different units, but in the decision matrix in order to have a valid comparison all the elements must be dimensionless. However, a lot of normalization methods have been developed for cost and benefit criteria, not only there has not been enough attention for engineering design situations in which approaching the target values are desirable but also the available methods have shortcomings. A new version of VIKOR method, which covers all types of criteria with emphasize on compromise solution, is proposed in this paper. The proposed comprehensive version of VIKOR also overcomes the main error of traditional VIKOR by a simpler approach. Suggested method can enhance exactness of material selection results in different applications, especially in biomedical application where the implant materials should possess similar properties to those of human tissues. Five examples are included to illustrate and justify the suggested method. [ABSTRACT FROM AUTHOR]

Abstract: The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method. [Copyright &y& Elsevier]

Abstract: This paper investigates optimal design of spatially varying frictional constraints in reducing the risk of failure due to wrinkling and thinning. First, this problem is formulated deterministically as a multi-objective optimization with spatially distributed frictional constraints, and pre-determined BHF. An FEM-based genetic algorithm approach (NSGA-II) is used to determine the deterministic Pareto front for multiple design alternatives, and a tradeoff strategy is used to identify an optimal design. Further, using a first order mean-value approach, a probabilistic formulation is proposed. The deterministic and probabilistic designs are compared to the conventional spatially uniform friction case. The results show that in the drawing of a Hishida oil pan part, an overall improvement of 33% in strain distribution can be obtained and a further 12% improvement can be obtained with probabilistic design. A covariance based approach is used to explore a reliable design that is robust to process uncertainties. [Copyright &y& Elsevier]

Abstract: To improve crushing energy absorption, aluminum foam has been adopted as one of new filler materials in impact engineering. Introduction of the foam material alters the crash behavior of structural component and necessitates exploration of more sophisticated design optimization methodology. In this regard, various surrogate model techniques have been extensively exploited to seek optimal crashworthiness design for thin-walled structures. This paper aimed at developing a multiobjective optimization framework for thin-walled column with aluminum foam-filler. As a typical sectional structure, squared columns were taken into account as a demonstrative example in this study. Higher order response surfaces were constructed for energy absorption and peak crushing force, which was validated by comparing against various close-form solutions published in literature. The difference between the single-objective and multiple-objective optimizations was discussed in a Pareto sense and the importance to seek for multiobjective optimization was highlighted. [Copyright &y& Elsevier]

Abstract: Magnetorheological (MR) fluid is a manageable fluid that exhibits drastic changes in rheological properties and interchangeable depending on the applied magnetic field strength. The fluid is potentially advantageous to be employed in many applications. This paper presents the design of test equipment for the performance of compression and tension tests. Finite element method magnetics (FEMM) was used to analyze the magnetic field distribution through the MR fluid. The test equipment was constructed and modified according to the operational principles, conditions and simulation results. The tests were performed in a vertical direction to the DC magnetic field generated by a coil. Experimental results showed that the compressive/tensile stresses of MR fluids increased as the applied current increased. The test equipment was utilized to investigate the performance of the MR fluid in squeeze mode. [Copyright &y& Elsevier]

Abstract: An ever increasing variety of materials is available today, with each having its own characteristics, applications, advantages, and limitations. In choosing the right material, there is not always a single definite attribute of selection and the designers and engineers have to take into account a large number of material selection attributes. This paper presents a logical procedure for material selection for a given engineering application. The procedure is based on an improved compromise ranking method considering the material selection attributes and their relative importance for the application considered. Two examples are included to illustrate the approach. [Copyright &y& Elsevier]

Abstract: In this paper, the Weibull and the normal cumulative probability are discussed and compared in relation to the analysis of the fracture toughness K IC. It is shown that, in the normal distribution, K IC can take negative or zero values, causing complications in structural design. In the Weibull distribution, this does not happen and its lower limit K ICL can be determined without problems. So, the Weibull cumulative probability represents reality in a better form. Finally, comparing experimental data with both distributions, it is found that the Weibull probability is more economics in terms of structural design. [Copyright &y& Elsevier]

Abstract: Cellular structures are generally assembled with face sheet plies in their application. It is necessary to understand the influence of assembled plies on deformation and energy absorption before using textile composite cellular structures in engineering design. In this paper, effects of ply assembly, outer ply material, outer ply thickness, and loading area on energy absorption and deformation of the applied structure including cellular structure and face sheet plies are investigated. Three-dimensional finite element analyses are carried out employing orthotropic mechanical properties of the applied materials, textile composite, wood, E-glass, aluminium alloy 2024-T3 and unidirectional fiber–epoxy composite T-300. The predicted results show that deformation and distributed strain energy density of both outer and inner surfaces of the applied structure are significantly affected by ply assembly, outer ply material, outer ply thickness, and loading area. [Copyright &y& Elsevier]

Abstract: Engineering design relates to the design of engineered artifacts formed by materials of various types. Materials play an important role during the entire design process. At the early design stage, materials may achieve some of the required functions. Hence, designers may need to identify materials with specific functionalities in order to find feasible design concepts. ‘Materials identification’ is used to refer to this materials-related design activity. At the downstream design stages, when the physical structure for a design has been determined, materials with specific properties should be selected from a set of candidates, which is commonly referred to as ‘materials selection’. In this paper, an overview of recent research in materials identification and materials selection is conducted, that provides materials support for the early and downstream stages of engineering design respectively. The purpose of this work is to provide a documentary of latest research efforts in this area, to recognize the importance of materials identification and selection for engineering design problem solving, as well as to propose prospects of future research, so that more effort can be spent on those lacking materials-related research. [Copyright &y& Elsevier]

Abstract: Today apart from CAD/CAM activities, engineering simulation tools based on the finite element method are employed regularly in the design of stamping dies for sheet metal parts in automotive industries. With the increased use of FE simulations in tooling departments, the forming analyses of sheet metals components are used more frequently in the design feasibility studies of production tooling. These computer tools allow the design engineer to investigate the process and material parameters controlling the material flow over the die surfaces. Nevertheless, the reliability of predicted formability and the accuracy of the estimated deformed geometry for a given stamping part depend on the selected computational modeling approach. In this paper, a kinematic hardening plasticity model based on an additive backstress form is described in order to improve the predicted sheet metal deformation response. The performance of the model in the forming analyses of sheet metals is investigated, and the FE analysis of Numisheet’93 U-channel benchmark is performed using implicit FE analyses based on the kinematic hardening plasticity model. A comparison of the U-channel geometry after springback, predicted with present model, indicates a significant improvement with respect to geometry computed using the isotropic hardening plasticity model. [Copyright &y& Elsevier]

Abstract: An optimizing procedure of microwave absorber is proposed based on the absorbing mechanism for one-layer microwave absorber in this paper. Amplitude–frequency characteristic of the material is obtained under optimal fitting electromagnetic parameters together by using the optimizing method. The influence of dispersion of electromagnetic parameters and the thickness on the performance of the absorbing material is analyzed. [Copyright &y& Elsevier]

Abstract: The design of rotating components demands a good understanding of the effect on materials under dynamic stress conditions. Depending on the operating conditions, the components have to possess appropriate stiffness and strength properties to ensure stresses are kept within acceptable limits, and geometrical stability is maintained to ensure correct functioning. The loads may also fluctuate throughout the rotational cycle, inducing fatigue in the component. In addition, any adverse effects of environmental impact have to be taken into consideration. The design is clearly complicated and utilising the most appropriate material or materials is challenging. This paper discusses the design decision-making involved for a rotationally dynamic component using the example of a helicopter rotor blade. The specification and outline design provide the context for evaluating and comparing metallic and composite constructions. [Copyright &y& Elsevier]

Abstract: The aim of the paper is to consider the role that surface engineering has to play in the area of environmental design and to highlight some aspects of the surface engineering technologies which need to be considered from a lifecycle viewpoint, but are rarely explicitly discussed. The benefits of surface engineering are addressed by consideration of case studies stressing different performance enhancements and consequential environmental benefits. The lifecycle aspects are largely drawn from the authors own experience, and again use case studies identifying a series of issues. Overall the authors believe in the importance of surface engineering within environmental design but stress the need for lifecycle analysis in order to justify its use. [Copyright &y& Elsevier]

Engineering design draws on tens of thousands of materials and on many hundreds of processes to shape, join and finish them. One aspect of optimized design of a product or system is that of selecting, from this vast menu, the materials and processes that best meet the needs of the design, maximizing its performance and minimizing its cost. The problem, still incompletely solved, is that of matching material and process attributes to design requirements. Some of these attributes can be expressed as numbers, like density or thermal conductivity; some are Boolean, such as the ability to be recycled; some, like resistance to corrosion, can be expressed only as a ranking (poor, adequate, good, for instance); and some can only be captured in text and images. Achieving the match with design requirements involves four basic steps. (1) A method for translating design requirements into a specification for material and process. (2) A procedure for screening out those that cannot meet the specification, leaving a subset of the original menu. (3) A scheme for ranking the surviving materials and process, identifying those that have the greatest potential. (4) A way of searching for supporting information about the top-ranked candidates, giving as much background information about their strengths, weaknesses, history of use and future potential as possible. In this paper we review the strategies that have evolved to deal with this problem, the progress that has been made and the challenges that remain. [Copyright &y& Elsevier]

Choosing the optimal material and manufacturing process combination for a given engineering component application is mostly non-trivial and involves considerable design expertise and experience. This choice is not made in isolation of a lot of other conflicting design issues, technical and non-technical, as well as the need to satisfy interface requirements with adjoining components. This paper describes, through a practical case study, a systematic approach to designing engineering components, with an emphasis on selecting appropriate materials and manufacturing processes. The approach adopted exploits commercially available technologies only, avoiding more exotic materials and processes that may satisfy the technical demands but are inherently risky and prohibitively expensive. [Copyright &y& Elsevier]

Materials selection and design for structural polymers becomes more and more important for different industrial products such as telephones, pens, computers, TV-sets, kitchenware, car parts, toys, etc. Polymers have often been considered as an inferior and weak material in many areas. However, it has mainly been due to the fact that polymers, as well as many other materials, have too often been used in uncertain or wrong applications. In this paper, the principles for materials selection are presented as a model with different steps from definition of functions to the feedback from the delivered product. Design aspects and examples of methods to fulfil demands for manufacturing, assembly, disassembly, service and recycling, etc, are also presented as well as environmental friendly solutions for product development. Examples of Integrated Product Development for plastics with design aspects are given and analysed. [Copyright &y& Elsevier]

Complex oxide thin films, such as ferroelectric thin films, are widely used in various devices. However, the chemical composition and chemical bonding of the surface layer are usually different from those in the ‘bulk’ region of the oxide thin films. The existence of the surface layer will certainly affect the properties, such as the dielectric behavior, of the films. In this paper, a model for evaluating the effect of the surface layer on the dielectric behavior of oxide films is proposed. The effective dielectric constant of the thin films is suggested as a function of the dielectric constants of expected and unexpected compounds in the surface layer, the content of unexpected compounds in the surface layer, and the volume fraction of the surface layer in the whole thin film. As an example, the dependence of the effective dielectric behavior of PbTiO3 thin films on the surface layer has been estimated using this model. The results show that a surface layer deviating from the stoichiometry of the film has a pronounced effect on the effective dielectric constant of thin films. It is obvious that in the design of oxide films and film devices the effect of the surface layer on the dielectric behavior of the films should be taken into account. [Copyright &y& Elsevier]

Possible changes in the United States product liability laws have been identified as having an increasing negative influence on the engineering design process. This paper considers a specific case of a materials failure which has recently been argued through the English courts under the 1987 Consumer Protection Act. This act, and its interpretation, is discussed with regard to its possible future impact on the design rationale. [Copyright &y& Elsevier]

Mechanistic capabilities found in nature have influenced a variety of successful functional designs in engineering. However, the unique combinations of mechanical properties found in natural materials have not been readily adapted into synthetic materials, due to a disconnect between biological principles and engineering applications. Current biomimetic material approaches tend to involve mimicking nature's microstructure geometries or mimicking nature's adaptive design process through brute force element-by-element composite optimization techniques. While the adaptive approach promotes the generation of application-specific microstructure geometries, the element-by-element optimization techniques encompass a large design space that is directly related to the number of elements in the system. In contrast, a novel methodology is proposed in this paper that merges biological pattern generation mechanisms observed in the Gray-Scott model, with an evolutionary-inspired genetic algorithm to create adaptive bio-inspired composite geometries optimized for stiffness and toughness. The results reveal that this methodology significantly reduces the optimization parameter space from tens of thousands of parameters to only four or five. In addition, the resultant composite geometries improved upon the overall combination of stiffness and toughness by a factor of 13, when compared to published brute force element-by-element techniques. Unlabelled Image • A methodology is introduced combining biological pattern generation with a genetic algorithm to design bio-inspired structures. • The bio-like structures were generated by modifying a set of rules similar to the design process implemented in nature. • The optimization parameter space was significantly reduced to only four or five parameters. • The combination of stiffness and toughness was improved by a factor of 13 compared to element-by-element techniques. [ABSTRACT FROM AUTHOR]