Masataka Yoshimura

Kyoto University, Kioto, Kyoto, Japan

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Publications (120)48.2 Total impact

  • Masataka Yoshimura · Masaki Hasuike · Tomoyuki Miyashita · Hiroshi Yamakawa
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    ABSTRACT: Design optimisation technologies are a practical requirement when aiming to obtain optimal product design variable values from an initially given feasible design space, but such technologies also can contribute to the generation of more effective product design alternatives, namely, product design innovations. This paper proposes an effective evaluation method that enables improvement of product design ideas, using characteristic-based hierarchical optimisation strategies applicable to industrial machine products. After related characteristics are decomposed into simpler characteristics, or simpler characteristics are extracted from higher level characteristics, new optimisation strategies are constructed based on clarification of the relationships among all the characteristics. Innovative processes that lead to product design improvements are analysed in detail by examining optimum solutions for various design improvement ideas, using displays of Pareto optimum solution lines or surfaces. The proposed system design optimisation method that is based on evaluations of evolutional Pareto optimum solutions is presented and exemplified here using an articulated robot product design, and applied at the conceptual product design stage.
    No preview · Article · Nov 2013 · Journal of Engineering Design
  • Masataka Yoshimura · Masaki Satou · Tomoyuki Miyashita · Hiroshi Yamakawa
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    ABSTRACT: We propose a product design optimization method that maximizes the integrated satisfaction level for evaluative factors. Product designs include many evaluative factors that have complex interrelationships. To cope with such circumstances, we construct strategies and a practical method to obtain optimum design solutions. First, the evaluative items for the product are listed and each item is decomposed into evaluative factors. Next, to express designers’ or potential customers’ levels of satisfaction for the characteristic values of each evaluative factor, we define satisfaction functions that incorporate the relationship between characteristic values and satisfaction levels. Weighting coefficients for the evaluative factors are then obtained by the pair comparison method. Finally, an integrated satisfaction level is formulated by summing the characteristic values with their weighting coefficients over the entire set of evaluative factors. The integrated satisfaction level of the objective function is maximized, and optimum design solutions with maximum satisfaction levels are then obtained. If necessary, these solutions can be modified and improved by re-examining and adjusting the satisfaction functions and weighting coefficients. Furthermore, the proposed method can be used to find schemes that improve the integrated satisfaction level. The utility of the proposed method is demonstrated using a passenger train coach design.
    No preview · Article · Dec 2012
  • Masataka Yoshimura
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    ABSTRACT: Effective responses to rapidly changing markets require increasingly sophisticated design solutions that are best achieved by the continuous evolution and improvement of the existing optimised design solutions. To accomplish this process, design and manufacturing engineers who individually have specific expert knowledge and access to advanced technologies should work collaboratively to complete the development of new designs. This paper proposes product design optimisation methodologies and procedures that seek to enable effective collaborative product design optimisations. Maximisation of the potential for a particular collaborative project to achieve a successful outcome requires circumstances, where each collaborative member can freely propose his or her own ideas for design improvements. Also required are methodologies and procedures that break through the existing product design solutions, methodologies that are explicitly tailored to motivate all members participating in a collaborative project. To achieve success through such collaborations, a creative, flexible framework is needed, and optimisation scenarios that have an explicit goal of maximising the expected profits that result from the collaboration must be constructed. This paper describes the framework, methodologies and procedures that support such collaborations. The proposed framework and methodologies are applied to a machine product design, and their effectiveness is demonstrated.
    No preview · Article · Sep 2012 · Journal of Engineering Design
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    ABSTRACT: Topology optimization has been successfully used in many industries, such as mechanical industries, but it often encounters numerical problems such as grayscale representations of obtained composites. A type of structural optimization method using the level set theory for boundary expressions has been proposed, in which the outlines of target structures are implicitly represented using the level set function, and optimal configurations are obtained by updating this function based on the optimal criteria. However, this method has a drawback that it does not allow topological changes that either introducing a hole in the material domain. To overcome the above two problems, this paper proposes a new topology optimization method incorporating level set boundary expressions based on the concept of the phase field method, and we apply it to the minimum mean compliance problem. First, a structural optimization problem is formulated based on a boundary expression using the level set function. Next, a time evolution equation for updating the level set function is formulated based on the concept of the phase field method, and the minimum mean compliance problem is formulated using the level set boundary expression. An optimization algorithm for the topology optimization incorporating the level set boundary expression based on the concept of the phase field method is derived. Finally, several examples are provided to confirm the usefulness of the proposed structural optimization method.
    No preview · Article · Jan 2011 · Journal of Environment and Engineering
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    ABSTRACT: Structural optimization methods based on the level set method are a new type of structural optimization method where the outlines of target structures can be implicitly represented using the level set function, and updated by solving the so-called Hamilton–Jacobi equation based on a Eulerian coordinate system. These new methods can allow topological alterations, such as the number of holes, during the optimization process whereas the boundaries of the target structure are clearly defined. However, the re-initialization scheme used when updating the level set function is a critical problem when seeking to obtain appropriately updated outlines of target structures. In this paper, we propose a new structural optimization method based on the level set method using a new geometry-based re-initialization scheme where both the numerical analysis used when solving the equilibrium equations and the updating process of the level set function are performed using the Finite Element Method. The stiffness maximization, eigenfrequency maximization, and eigenfrequency matching problems are considered as optimization problems. Several design examples are presented to confirm the usefulness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.
    Full-text · Article · Sep 2010 · International Journal for Numerical Methods in Engineering
  • Kenji Doi · Masataka Yoshimura · Shinji Nishiwaki · Kazuhiro Izui
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    ABSTRACT: Manufacturing that minimises the exhaustion of natural resources, energy used and deleterious environmental impact is increasingly demanded by societies that seek to protect global environments as much as possible. To achieve this, life-cycle design (LCD) is an essential component of product design scenarios; however, LCD approaches have not been well integrated in optimal design methods that support quantitative decision-making. This study presents a method that yields quantitative solutions through optimisation analysis of a basic product design incorporating life-cycle considerations. We consider two types of optimisation approaches that have different aims, namely, (1) to reduce the use of raw materials and energy consumption and (2) to facilitate the reuse of the product or its parts when it reaches the end of its useful life. We also focus on how the optimisation results differ according to the approach used, from the viewpoint of the 3R concept (Reduce, Reuse and Recycling). Our method obtains optimum solutions by evaluating objectives fitted to each of these two optimisation approaches with respect to the product's life-cycle stages, which are manufacturing, use, maintenance, disposal, reuse and recycling. As an applied example, a simple linear robot model is presented, and Pareto optimum solutions are obtained for the multiobjective optimisation problem whose evaluated objectives are the operating accuracy of the robot and the different life-cycle costs for the two approaches. The characteristics of the evaluated objectives and design variables, as well as the effects of using material characteristics as design parameters, are also examined.
    No preview · Article · Jun 2010 · International Journal of Sustainable Engineering
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    ABSTRACT: The shortening of product delivery lead-times can usually be achieved by keeping high-level components in inventory, however in small-volume production systems, maintaining such inventories is often a costly as well as a risky business strategy. If the risk of maintaining unsold inventory can be decreased, even small-volume manufacturers may be able to justify holding more significant quantities of versatile inventory. This paper discusses a component commonality effect to breakthrough the trade-off relationship between inventory levels and delivery lead-times for such small-volume production systems. By using the same component in different products, inventory maintenance costs can be dramatically reduced, but component commonality design problems are inherently complex, since excessive module commonality may lead to lower product performances, and there are trade-off relationships between product performance and cost reductions obtained through component commonality. In this paper, such a design problem is formulated as a multiobjective component commonality design optimisation problem considering inventory level, delivery lead-time and product performance, and the optimal solutions are obtained as a Pareto optimal solution set. Detailed procedures concerning the proposed design method, including inventory simulation, are discussed and developed for a switchgear design problem. Finally, an example switchgear design problem is solved to illustrate that optimal use of component commonalities across different modules can significantly reduce inventory costs, while also shortening product delivery lead-times.
    No preview · Article · May 2010 · International Journal of Production Research
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    ABSTRACT: The SLSV (single-loop-single-vector) method is modified for the reliability-based optimization problem with multiple reliability constraints. The design problem is formulated to minimize the structural volume of frame structure in terms of cross-sectional area of each frame element subjected to the two mode reliability constraints. The two mode reliability criteria consist of the mean compliance and mean eigenfrequency. The limit state functions are formulated as normalized form to achieve numerical stability of the SLSV method, because the functions are directly adopted as constraint conditions. That is a large difference from the conventional double-loop method, where the limit state functions do not appear in the optimization loop. Through numerical examples of 2-D and 3-D frame design problems, higher computational efficiency and sufficient reliability approximation accuracy by the SLSV method are demonstrated in comparison with the conventional double loop method that the mode reliabilities are evaluated by the first order reliability method (FORM) in each optimization step. Additionally, the importance of normalization of the limit state functions in the SLSV method is also demonstrated.
    No preview · Article · Jan 2010 · Journal of Computational Science and Technology
  • A. Iga · T. Yamada · S. Nishiwaki · K. Izui · M. Yoshimura
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    ABSTRACT: In structural designs considering thermal loading, maximization of temperature diffusivity as well as structural stiffness are important and indispensable goals that optimal solutions to design problems need to achieve to reduce operating temperatures and extend product durability. In this paper, a new topology optimization method, based on the level set method and Finite Element Method and including design-dependent effects, is constructed for coupled thermal and structural problems, and multi-objective optimization problems having generic heat transfer boundaries in a fixed design domain are formulated. First, a topology optimization method for coupled thermal and structural problems that uses a level set method incorporating fictitious interface energy is briefly explained. Next, a new objective function that can take into account both temperature diffusivity and stiffness maximization is formulated, based on the concept of total potential energy maximization for the thermal and structural problems. An optimization algorithm that uses the Finite Element Method when solving the equilibrium equation and updating the level set function is then constructed. Finally, several numerical examples are presented to confirm the usefulness of the proposed method.
    No preview · Article · Jan 2010
  • Shintaro YAMASAKI · Shinji NISHIWAKI · Kazuhiro IZUI · Masataka YOSHIMURA
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    ABSTRACT: Vibration characteristics such as eigenfrequencies and eigenmodes are crucial factors that determine the dynamic performance of mechanical structures, and high performance structures that function dynamically can be designed by appropriately specifying such vibration characteristics. This paper proposes a structural optimization method for obtaining mechanical structures having specified vibration characteristics, based on the level set method. First, the basic details of a structural optimization method using the level set method, which can be applied to dynamic problems, are briefly discussed. Next, optimization problems that address the maximum eigenfrequencies, and the matching of eigenfrequencies with target values, are formulated. A new optimization algorithm based on the level set method is constructed, where a newly improved geometric reinitialization scheme is used for re-initializing a level set function, based on a zero level set surface. Using the proposed optimization algorithm, both the solving of the eigenvalue problem and the updating of the level set function are performed using the FEM, where non-structural meshes can easily be configured. Finally, several design examples are provided to confirm the usefulness of the proposed structural optimization method.
    No preview · Article · Jan 2010
  • T. Yamada · S. Nishiwaki · A. Iga · K. Izui · M. Yoshimura
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    ABSTRACT: In structural designs considering thermal loading, to control thermal stress and minimize decreases in material strength at high temperatures, it is important to maximize the thermal diffusivity of structures, in addition to the usual maximization of stiffness that optimal designs achieve. This paper presents a new level set-based topology optimization method for thermal problems with generic heat transfer boundaries in a fixed design domain that includes designdependent effects, using level set boundary expressions and the Finite Element Method. First, a topology optimization method using a level set model incorporating fictitious interface energy is briefly discussed. Next, an optimization problem is formulated using the concept of total potential energy to address the design of mechanical structures that aim to minimize the mean temperature of the structure under thermal loading. An optimization algorithm that uses the Finite Element Method when solving the equilibrium equation and updating the level set function is then constructed. Finally, several numerical examples are provided to confirm the utility of the proposed optimization method.
    No preview · Article · Nov 2009
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    ABSTRACT: Electromagnetic waveguides effectively conduct electromagnetic microwaves using resonance phenomena in RF-ranges, and are widely used in high-frequency electronic devices and equipment. The waveguide guiding characteristics related to eigen-frequencies and eigen-modes are critical factors determining the design performances pertaining to the bandwidth of appropriate response frequencies, and high performance electromagnetic waveguides can be obtained by designing cross-sections of waveguides that appropriately control such guiding characteristics at the conceptual design phase. This paper proposes a new application of a topology optimization method for the design of inhomogeneous electromagnetic waveguide cross-sections composed of dielectric material and air, with the resulting configurations performing according to specified guiding characteristics. First, the concept of topology optimization and a way to apply it to electromagnetic wave problems are explained. Next, design requirements for the design of waveguide cross-sections are clarified and corresponding objective functions and the optimization problem are formulated. A new multi-objective function is formulated to reduce grayscales since using a penalization parameter for physical property interpolation is ineffective in electromagnetic problems. The optimization algorithm is constructed based on these formulations, Sequential Linear Programming and the finite element method, where hybrid edge/nodal elements are used. Finally, several design examples of waveguide cross-sections are presented to confirm the usefulness of the proposed method.
    No preview · Article · Oct 2009 · Finite Elements in Analysis and Design
  • Kenji Doi · Yoshiyuki Chujo · Masataka Yoshimura · Shinji Nishiwaki · Kazuhiro Izui
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    ABSTRACT: This paper proposes an optimum system design method that especially considers product lifecycles and aims to help designers make effective decisions during the product design phase. By considering and estimating all lifecycle factors of cost and environmental impact in addition to the product performance, this method facilitates development of optimum design solutions that incorporate requirements pertaining to the product's entire lifecycle. Furthermore, quantitative estimation of lifecycle factors enables the numerical expression of optimum solutions, rather than depending primarily on experiment and designer intuition. To demonstrate the effectiveness of the proposed method, this paper develops an optimum system design method for a milling machine as an example of a machine product designed for long term use. The lifecycle cost and the lifecycle environmental impact are generally expressed as the summation of each value during manufacturing phase, usage phase, disposal phase and recycling phase. In this example model, Eco-indicator 99 is used to evaluate environmental impact. In the proposed lifecycle design optimisation method, the relationships among the product performance, the lifecycle cost and the lifecycle environmental impact are evaluated as a multi-objective optimisation problem. Analysis of the obtained Pareto optimum solution sets subsequently enables designers to pursue breakthrough product design solutions.
    No preview · Article · Sep 2009 · International Journal of Sustainable Engineering
  • Ranjan Kumar · Kazuhiro Izui · Masataka Yoshimura · Shinji Nishiwaki
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    ABSTRACT: To achieve truly optimal system reliability, the design of a complex system must address multilevel reliability configuration concerns at the earliest possible design stage, to ensure that appropriate degrees of reliability are allocated to every unit at all levels. However, the current practice of allocating reliability at a single level leads to inferior optimal solutions, particularly in the class of multilevel redundancy allocation problems. Multilevel redundancy allocation optimization problems frequently occur in optimizing the system reliability of multilevel systems. It has been found that a modular scheme of redundancy allocation in multilevel systems not only enhances system reliability but also provides fault tolerance to the optimum design. Therefore, to increase the efficiency, reliability and maintainability of a multilevel reliability system, the design engineer has to shift away from the traditional focus on component redundancy, and deal more effectively with issues pertaining to modular redundancy. This paper proposes a method for optimizing modular redundancy allocation in two types of multilevel reliability configurations, series and series–parallel. A modular design variable is defined to handle modular redundancy in these two types of multilevel redundancy allocation problem. A customized genetic algorithm, namely, a hierarchical genetic algorithm (HGA), is applied to solve the modular redundancy allocation optimization problems, in which the design variables are coded as hierarchical genotypes. These hierarchical genotypes are represented by two nodal genotypes, ordinal and terminal. Using these two genotypes is extremely effective, since this allows representation of all possible modular configurations. The numerical examples solved in this paper demonstrate the efficacy of a customized HGA in optimizing the multilevel system reliability. Additionally, the results obtained in this paper indicate that achieving modular redundancy in series and series–parallel systems provides significant advantages when compared with component redundancy. The demonstrated methodology also indicates that future research may yield significantly better solutions to the technological challenges of designing more fault-tolerant systems that provide improved reliability and lower lifecycle cost.
    No preview · Article · Aug 2009 · Computers & Industrial Engineering
  • K. Doi · M. Yoshimura · S. Nishiwaki · K. Izui
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    ABSTRACT: This research focuses on quantitative analysis techniques for optimization of conceptual designs for products where lifecycle considerations are crucial. A product for which energy saving is practically mandatory, such as a major home appliance, was chosen, and the proposed procedure for minimizing the total cost through the product's lifecycle focuses especially on the use and maintenance stages. A multiobjective optimization problem is developed to minimize two evaluative characteristics, the manufacturing cost of the product (I), and the sum of the energy and maintenance costs of the product over an assumed period of time (II), treating the longevity of specified portions of the product and energy consumption rate as design variables. The optimization simulation was carried out for a numerical example based on this model, and a Pareto optimum solution for costs (I) and (II) was obtained. Using this Pareto optimum solution, we analyzed the optimum values of design variables and clarified quantitatively how the design parameters affect the optimum solution. The proposed model demonstrates potential for use in decision making during the conceptual product design stage, when determining design variable values that meet desired lifecycle cost requirements is a goal.
    No preview · Article · Jul 2009 · International Journal of Performability Engineering
  • T. Yamamoto · S. Maruyama · S. Nishiwaki · M. Yoshimura
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    ABSTRACT: In this paper, we propose a new topology optimization method to be applied for designing layouts of poroelastic material in an acoustic cavity in order to depress sound pressure levels arising from acoustic resonance. In this method, mean sound pressure levels are minimized utilizing the attenuation of sound by poroelastic material such as sound absorbing material. Biot's theory is incorporated into the optimization scheme to deal with poroelastic material. Air medium contained in the design domain is approximately represented in the expression of Biot's theory. These unified expressions of poroelastic material and air medium by Biot's theory allow to utilize a material interpolation scheme in the density approach of topology optimization. We also propose a new material interpolation scheme that can be applied for poroelastic material. In this scheme, we interpolate several physical quantities such as bulk modulus, densities and porosity that are used in the governing equations of Biot's theory. Several one-and two-dimensional numerical examples are presented to demonstrate that the proposed method can provide clear configurations of poroelastic material that reduce mean sound pressure levels within prescribed evaluation domain for specified frequency ranges.
    No preview · Article · Jun 2009
  • A. Iga · S. Nishiwaki · K. Izui · M. Yoshimura
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    ABSTRACT: In structural designs considering thermal loading, in addition to heat conduction within the structure, the heat convection upon the structure’s surface can significantly influence optimal design configurations. In this paper, we focus on the influence of design-dependent effects upon heat convection and internal heat generation for optimal designs developed using a topology optimization scheme. The method for extracting the structural boundaries for heat convection loads is constructed using a Hat function, and heat convection shape dependencies are taken into account in the heat transfer coefficient using a surrogate model. Several numerical examples are presented to confirm the usefulness of the proposed method.
    No preview · Article · May 2009 · International Journal of Heat and Mass Transfer
  • Ranjan Kumar · Kazuhiro Izui · Masataka Yoshimura · Shinji Nishiwaki
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    ABSTRACT: Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)—the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.
    No preview · Article · Apr 2009 · Reliability Engineering [?] System Safety
  • K. Izui · S. Nishiwaki · M. Yoshimura · M. Nakamura · J.E. Renaud
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    ABSTRACT: Multiobjective optimization techniques such as Evolutionary Algorithms, which can obtain Pareto optimal solution set in a single calculation, have attracted attentions to conduct trade-off analysis in mechanical design process. Multiobjective Particle Swarm Optimization (MOPSO) has an advantage in obtaining Pareto optimal solution set in structural optimization problem since it can easily handle continuous design variables. However, this algorithm has not been applied to complicated structural and mechanical optimization problems due to its difficulty of constraint handling in its local search process while providing high-performance in global search. This paper proposes an approach to obtain Pareto optimal solutions using MOPSO combined with the Sequential Linear Programming (SLP) to enhance local search in multiobjective optimization. The MOPSO update scheme is applied to dominated solutions and the SLP is applied to non-dominated solutions. The application of the SLP along with optimal weighting coefficients results in a stable and fast in multiobjective optimization. Finally, truss structure design optimization problems are solved to verify efficiency of the proposed algorithm.
    No preview · Article · Apr 2009
  • Masakazu Kobayashi · Shinji Nishiwaki · Kazuhiro Izui · Masataka Yoshimura
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    ABSTRACT: This paper proposes an innovative, integrated design method for the design of practical and sophisticated compliant mechanisms. The approach consists of two optimisation methods, topology and shape optimisation, plus a scheme to implement designer input of ideas. In the first step, a designer explores the most fruitful design concepts for mechanisms that achieve the design specifications, by combining compliant mechanisms created by the topology optimisation with additional mechanisms prepared by the designer. In this first step, a support method based on the visualisation of the designer's thinking processes assists the designer in his or her exploration of new ideas and design concepts. In the second step, the shape optimisation yields a detailed optimal shape based on the design concept. The combination of compliant mechanisms with the additional mechanisms enables the creation of devices having increased capability or higher performance than would be possible using a single compliant mechanism designed by topology optimisation alone. Executing the shape optimisation after initial design concepts have been explored facilitates the determination of a detailed optimal shape, and also enables to consider non-linear analysis and stress concentration and to make accurate quantitative performance evaluations, which topology optimisation cannot provide.
    No preview · Article · Apr 2009 · Journal of Engineering Design

Publication Stats

570 Citations
48.20 Total Impact Points


  • 1989-2013
    • Kyoto University
      • Department of Aeronautics and Astronautics
      Kioto, Kyoto, Japan
  • 2007
    • Toyota Central R & D Labs., Inc.
      Nagoya, Aichi, Japan
  • 2006
    • Hiroshima University
      • Department of Civil and Environmental Engineering
      Hirosima, Hiroshima, Japan
  • 1994
    • Kyoto Institute of Technology
      Kioto, Kyōto, Japan