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Fiber-reinforced composite materials, exemplified by CFRP, offer the possibility of achieving lightweight, high-stiffness, and high-strength structures by continuously and evenly distributing fibers. While topology and orientation optimization methods have been developed for anisotropic materials in the past, there remains a gap in design methods that consider manufacturability, especially for continuous fiber materials. In this study, we propose a design method that takes into account manufacturability, focusing on the aspects of continuity and uniformity in fiber-reinforced composite optimum design. Specifically, we introduce a two-stage optimization approach. In the first stage, we conduct concurrent optimization of topology and fiber orientation. We utilize a level-set function to represent topological configuration, while for orientation, we introduce a “double angle vector”, which enables us to consider fiber properties such as angular periodicity. These design variables are updated by solving partial differential equations based on reaction–diffusion equations. In the second stage, leveraging the optimal orientations obtained in the first stage, we optimize the path-line generation for the manufacture of continuous fiber materials. We introduce a scalar function representing path lines and formulate an optimization problem to ensure that the path lines are both evenly spaced and continuous. The update of design variables in this state is also achieved via solving the partial differential equation. Through the development of this two-stage optimization method, we aim to create an optimal structure with manufacturable continuous fiber materials, incorporating both the topology and fiber orientation that satisfy the requirements of continuity and uniformity.

For improving consumer satisfaction, a design process for individual production based on additive manufacturing technology is required to consider appearance as well as functionality. Although topology optimization is a powerful technology to design highly functional structure, it has difficulty considering aesthetic features. This paper presents a new topology optimization method considering aesthetic preferences with a manufacturing constraint by incorporating the image processing used for style transfer and object recognition. To consider aesthetic features, we introduce texture energy which evaluates the similarity between the input preference image and structure represented by the level set method. To identify the unmanufacturable regions disconnected from the main structure, the connected component labeling process based on the object recognition method is applied to the binary image of the level set function. A topology optimization problem of maximizing stiffness is formulated considering aesthetic preferences and imposing the structural connectivity constraint, where the objective function is defined as a combination of minimizing mean compliance and texture energy. A reaction diffusion equation is used to update the level set function, where the Lagrange multiplier of structural connectivity constraint is calculated to eliminate unmanufacturable disconnect regions. Numerical examples are provided to confirm the validity and utility of the proposed method.

A multi-material structure that is composed of several different material properties is promising for achieving an ideal functionality that can outperform a single material structure. In the course of automotive design, the combination of lightweight and stiff materials can reduce the weight of a car body without sacrificing its performance. This paper proposes a multi-material topology optimization (MMTO) framework for the eigenfrequency maximization problem based on the Multi-material level set (MMLS) based topology optimization. The key idea of MMLS is to use M level set functions to represent M material regions and one void region without overlap. To demonstrate the proposed method, first, we formulate an MMTO problem for maximizing the eigenfrequency based on the shape representation by the MMLS method. Next, we derive the topological derivatives of multiple materials in the eigenfrequency problem and construct an optimization algorithm in which the level set functions are evolved by solving a reaction–diffusion equation (RDE) based on the topological derivatives. Several numerical examples are provided to validate the proposed methodology.

This paper presents a layout optimization method of the spot locations of pencil beam scanning for particle beam cancer therapy. With the pencil beam scanning technique, the particle beam is scanned from spot to spot in the tumor by using scanning magnets. To provide clinically ideal dose distributions and less-invasive treatment to the patients, both the spot locations and the number of particles given to each spot should be optimized. However, the spot layout is fixed with a lattice pattern in many prior studies. We propose the optimization method to derive the non-lattice spot layout to realize an acceptable dose distribution with a reduced number of spots. With the proposed method, a large enough number of spots were located densely at the initial state, and then the spots with the smallest contribution were removed one by one through iterations. The number of particles given to each spot was determined by solving a quadratic problem. Furthermore, we also propose the idea to accelerate the optimization process by simultaneously removing multiple spots. The algorithm was confirmed by numerical examples of both two-dimensional and three-dimensional cases. The dose quality with the optimized spot layout was better than that with the conventional lattice spot patterns, with all tested cases. In the optimized spot layout, the spots were located on the closed lines which were concentric to the target contour. We also confirmed the proposed method of multiple-remotion can accelerate the optimization process without violating the dose quality.

Stability and buckling have attracted extensive attention in the design of structural elements, especially in the design of thin-walled structures since they may naturally have poor stability and be prone to buckling failure. This paper proposes a level-set based topology optimization (TO) method that can maximize the lowest linear buckling load under a mean compliance constraint. First, we conduct the linearized buckling analysis and formulate the optimum design problem. Second, we derive the design sensitivity and revisit the reaction-diffusion equation-based level-set topology optimization. Finally, we solve several two-dimensional benchmark problems and the design results are presented to validate the proposed method.

This paper presents a new structural design framework that incorporates the concept of topology optimization and genetic algorithms to improve the manufacturability and structural robustness of the optimal structure. The level set function is employed as a topological design variable to obtain clear structural boundaries, and the manufacturability of the structure is mathematically defined based on the manufacturing directions and the fictitious heat fluxes. To gain the manufacturable structure design, the optimization problem is formulated to find both the optimal shape of the structure and the optimal directions of the adjustable manufacturing tools. A level set-based optimization regarding manufacturability has been studied in previous papers, however, due to the influence of the manufacturing directions, the objective value tends to be captured in local optima as the structure becomes more complex. To cope with this issue, we decided to adapt a heuristic based approach, genetic algorithm, to the optimization method. Simultaneously, to reduce the computation time, we applied Design of Experiments for the initial population of the genetic algorithm. The initial population of the manufacturing directions is installed using Latin Hypercube sampling for both a good representation and computational efficiency. To demonstrate the effectiveness of the proposed method, several design examples are provided, and the differences from the optimal solution, derived by a previous gradient-based optimization scheme, are mentioned.

Topology optimization is the most flexible structural optimization method that allows the topological modification as well as the shape changes. Topology optimization techniques have recently been utilized in engineering applications regarding multi-physics or multi-disciplinary optimization. The manufacturing evaluation is an important factor for the practical application to the field of industry. For example, conventional manufacturing processes such as molding and casting, require fulfillment of specific geometric conditions due to the path of the tools. To obtain the optimal structures satisfying such conditions, a new level set-based topology optimization method, based on the convection-diffusion equations with fictions fluxes, are utilized to impose the geometric constrains regarding manufacturability, has been developed. In this method, handling geometric constraints for the manufacturability depends on the fictitious heat fluxes. The propagation of the fictitious fluxes distinguishes the non-manufacturable domain. However, in previous approaches, the manufacturing directions are regarded as design parameters where the values are fixed before the optimization procedure. As the non-manufacturable domain is dominated by the path of the manufacturing tools, the appropriate selection of these parameter values is necessary to obtain the optimal design with the best manufacturability constraints. Thus, these parameters should be appropriately set during the optimization process. In this method, we develop a new topology optimization method where the manufacturing directions are also considered as design variables. A sensitivity analysis based on the adjoint equation is introduced to obtain optimized manufacturing directions. Several engineering applications are introduced and optimized through the new method and the previous methods to confirm the availability of the proposed method.

Topology optimization has been widely used in industry for designing high performance structures, but these structures are often complicated shape and cannot be manufactured directly. To solve this problem, it is necessary that geometrical constraints for manufacturability be satisfied in the optimization process. This paper proposes a scheme for imposing geometrical constraints, known as overhang constraints, in topology optimization for additive manufacturing (AM). As a feature of AM, when the inclination angle of an overhang is lower than a certain angle, AM components require temporary support materials to prevent the components from collapsing during fabrication. After the fabrication, these support materials are removed mechanically or chemically. As the use of support materials increase, manufacturing costs increase. Consequently, in order to reduce support materials, it is necessary to control the minimal inclination angle of an overhang in topology optimization. In the proposed method, the inclination angle of an overhang is represented using a fictitious physical model described by a steady-state diffusion equation. The overhang constraint can be imposed in the optimization procedure by constraining the value of the fictitious physical field. Several numerical examples are given to show the validity and effectiveness of the proposed method.

This paper proposes a novel topology optimization method for unsteady state incompressible Navier-Stokes flow. Many methods of topology optimization for steady state flow have been proposed, whereas most fluid flow problems should be considered as unsteady state. Therefore, a topology optimization method focusing on unsteady state fluid flow governed by the incompressible Navier-Stokes equation is considered in this paper. In addition, the defined boundary condition on the wall of an optimized structure should be precisely evaluated because it describes the specific fluid flow profile, such as velocity and pressure, on the wall that the fluid contacts. In order to solve flow profile near walls, an immersed boundary method is applied in the proposed method. The finite volume method is adopted to discretize primal and adjoint problems. These problems are solved using the Pressure-Implicit with Splitting of Operators (PISO) method. In this study, sensitivity analysis based on a topological derivative is applied. The update scheme for the design variable uses a reaction-diffusion equation. Some examples are shown and the effectiveness of our method is discussed in this paper.

The development of handling technology for microscopic biological samples such as cells and spheroids has been required for the advancement of regenerative medicine and tissue engineering. In this study, we developed micro-tweezers with a compliant mechanism to manipulate organoids. The proposed method combines high-resolution microstereolithography that uses a blue laser and topology optimization for shape optimization of micro-tweezers. An actuation system was constructed using a linear motor stage with a force control system to operate the micro-tweezers. The deformation of the topology-optimized micro-tweezers was examined analytically and experimentally. The results verified that the displacement of the tweezer tip was proportional to the applied load; furthermore, the displacement was sufficient to grasp biological samples with an approximate diameter of several hundred micrometers. We experimentally demonstrated the manipulation of an organoid with a diameter of approximately 360 µm using the proposed micro-tweezers. Thus, combining microstereolithography and topology optimization to fabricate micro-tweezers can be potentially used in modifying tools capable of handling various biological samples.

This paper proposes a new topology optimization method for steady state incompressible viscous flow. Since fluid flow profiles, such as velocity and pressure profiles, describe specific behavior on walls that fluid contacts, defined boundary conditions in such profiles should be precisely evaluated. The immersed boundary method is implemented here to represent fluid flow profiles, and enhanced accuracy is obtained through their rigorous use during optimization. The topological derivative is derived for the sensitivity analysis and the finite volume method is used for numerical analysis during the optimization process. Several numerical examples are provided to confirm that the optimal configurations accurately represent flow distributions, in contrast to previous research in which a specific treatment for internal wall boundaries was not considered.

Thermal design is essential when developing various types of technological devices, especially miniaturized electronic devices. Conventional thermal design methods that only focus on macrostructures can provide only limited improvements in electronic device performance. On the other hand, in recent years, the implementation of nanostructural designs that take advantage of the unique properties of heat conduction at the nanoscale has resulted in electronic devices offering unprecedentedly high performance. Nanoscale heat conduction is a ballistic process, whereas heat conduction at the macroscale is diffusive. When a system is a two-phase domain, temperature discontinuities occur on the material interfaces. High-performance devices have been developed by utilizing these unique phenomena, especially the interface effect. However, few reports have proposed thermal design criteria, and thermal designs have been dependent on heuristic approaches. The development of design guidelines applicable to nanoscale thermal problems is a fundamental requirement, and one of the most effective design criteria is shape sensitivity, which indicates how to deal with material interfaces based on physics and mathematics. In this paper, we propose a shape sensitivity analysis method for a two-phase thermal design problem considering temperature discontinuities. We first explain the difference between nanoscale and macroscale heat conduction and introduce a numerical analysis method for nanoscale heat conduction based on the Boltzmann transport equation. Next, we construct a method for shape sensitivity analysis for a heat conduction problem considering two-phase nanoscale effects such as temperature discontinuities, by expanding the work of Pantz, based on Céa’s method. The validity of our shape sensitivity analysis is demonstrated through two numerical examples.

The uniformity of deposition thickness in electroplating processes is vital to the realization of desirable surface qualities of many products. The thickness distribution of deposits varies according to numerous factors, such as the arrangement and shapes of auxiliary cathodes, anodes and shields, and the detailed configuration of the plating process. In recent years, computer analyses such as the Finite Element Method (FEM) have become widespread. Such analytical tools can predict thickness distributions, search for optimal process configurations, and avoid production problems, to some extent, but the selection of the most effective analytical conditions still depends on skilled analysts. This study presents a topology optimization method to achieve uniform deposition thickness, applied to the design of the shields placed in an electroplating bath. The proposed method uses level set boundary expressions and the FEM to analyze the electrochemical field. The Kreisselmeier-Steinhauser (KS) function for the current density distribution on a cathode is employed as an objective function, since current density is nearly proportional to the thickness of the resulting electroplating. The magnitude of the current density on the cathode is set as a constraint so that it does not fall below a certain value, to avoid lengthy plating times that would occur if the current density were too low. Numerical examples are presented to confirm the utility of the proposed method and the results demonstrate that the proposed method can obtain appropriate shapes and arrangements of shields.

We construct a topology optimization method for two dimensional rarefied gas flow problems, based on level-set boundary expressions. The degree of rarefaction is expressed by the Knudsen number, which is the ratio of the mean free path and the characteristic length of the system. As the Knudsen number approaches 0 in the limit, flow behaviors can be described by Navier-Stokes equations and topology optimization methods for such flows have already been proposed. On the other hand, the governing equation for flows which have a large rarefaction is the Boltzmann equation and topology optimization methods for such flows have not been seen. This paper presents the topology optimization method for rarefied gas flows whose Knudsen number is approximately 1, aiming at an application for the design of flow channels in micromachines. We use the Bhatnagar-Gross-Krook (BGK) model of the Boltzmann equation and extend it to the entire design domain that includes both rarefied gas and solid domains. First, we briefly discuss the Boltzmann equation and the level set-based topology optimization method. Second, an optimization problem is formulated to address the design of flow channels that aim to maximize the flow velocity induced along a temperature gradient. Finally, several numerical examples demonstrate the validity and usefulness of the proposed method.

This paper proposes a scheme for imposing geometrical constraints in topology optimization for molding and milling so that optimal configurations that guarantee manufacturability can be obtained, based on the fictitious physical model. First, a level set-based topology optimization method is briefly described, and geometrical requirements for molding and milling are clarified. In molding, molded products must embody certain geometrical features so that mold parts can be separated, and milling cannot proceed unless the desired shape allows tool cutting faces to reach the workpiece. A fictitious physical model described by a steady-state advection-diffusion equation is then constructed based on the requirements. In the fictitious physical model, material domains are represented as virtual heat sources and an advection direction is aligned with a prescribed direction, along which mold parts are moved, or attitude in the case of a milling tool. Void regions, where the value of the fictitious physical field is high, represent either undercut geometries which would prevent the mold from being parted, interior voids that cannot be manufactured, or regions that a milling tool cannot reach. Next, a geometrical constraint is formulated based on the fictitious physical model. An optimization algorithm is then constructed. Finally, in the numerical examples, the proposed method yields manufacturable optimal configurations, confirming the validity and the utility of the proposed method.

Topology optimization is the most flexible type of structural optimization method. This method has been applied in a variety of physics problems dealing with a multitude of design problems. In a given design problem, however, the optimization problem often has conflicting evaluative functions, such as the need for high rigidity in combination with minimal weight. The difficulty of simultaneously achieving high performance for two or more functions may be further compounded because current topology optimization methods typically only deal with a single material. On the other hand, when multiple kinds of materials having various properties can be selected for use, the range of a designer's choices is increased and an appropriate solution that greatly improves product functions may be achieved. Thus, this paper presents a new topology optimization method for multi-materials that obtains high-performance configurations. We apply the Multi-Material Level Set (MM-LS) topology description model in the topology optimization method, which uses a total of n level set functions to represent n materials, plus the void phase. The advantage of the MM-LS model is that clear optimal configurations are obtained and the design sensitivity for multi-material structures can be easily calculated. The level set functions that are design variables are updated using the topological derivatives, which also function as design sensitivities, and we derive the topological derivatives for multiple materials. Through several numerical examples, we demonstrate the validity of the proposed method.

This paper presents a local-in-time (LT) discrete adjoint-based topology optimization method for unsteady incompressible viscous flows incorporating the lattice Boltzmann method (LBM). For the optimization of unsteady flows, straightforward global implementations of the time-dependent optimization are usually adopted. However, such global implementations require that the entire flow solution history be available to calculate the solution of the adjoint equation reversed in time. For 3-D design optimization problems, the storage requirements can become prohibitively large. In this paper, the LT discrete adjoint-based method is applied to a LBM-based topology optimization to reduce the storage requirement. The basic idea of the LT method is to divide the entire time interval into several subintervals and to approximate the global sensitivity derivative as a combination of local sensitivity derivatives computed for each time subinterval. In this approach, flow solutions for only a single subinterval need to be stored. Since each time subinterval includes only a few (possibly one) time steps, the data storage requirements can be tremendously reduced. This method is applied in a pressure drop minimization problem considering unsteady viscous fluid. Two- and three-dimensional numerical examples are provided to confirm the validity and utility of the presented method.

Structural topology optimization has been applied to nonlinear structural problems, but conventional methods considering geometrical nonlinearity encounter difficulties during nonlinear analysis using the FEM (Finite Element Method). In this study, we propose a new level set-based topology optimization method considering geometrical nonlinearity, using a meshfree particle technique, for optimizing elastic structures that undergo finite displacement. In the proposed method, the MPS (Moving Particle Semi-implicit) method is used for solving the state equation, since it does not use a mesh for geometrically nonlinear analysis. In this paper, first, a topology optimization problem is formulated based on the level set method, and a method for regularizing the optimization problem using the Tikhonov regularization method is explained. The reaction-diffusion equation that updates the level set function is then derived and an optimization algorithm, which uses the FEM to solve the reaction-diffusion equation when updating the level set function, is constructed. Next, the particle interaction model and the treatment of geometrical nonlinearity in the MPS method are described and the implementation that combines the level set-based topology optimization with the MPS method is explained. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed topology optimization method for geometrically nonlinear problems.

This study evaluates a robust optimum design of a compliant mechanism considering uncertainty of the load direction. For the topology optimization, this study adopts a level set based approach incorporating a fictitious interface energy term. The method is known to have several advantages such as the allowance of topological as well as shape changes, and the ability to qualitatively control the geometrical complexity of the obtained optimum configurations. The design objectives are to maximize the displacement at the gripping position and the robustness under variations of the applied load direction. In addition, the eigenfrequency maximization is considered to acquire the structural stiffness. The design problem is formulated as a multiobjective design problem. Conventionally, the robust design problem has been formulated as a weighted sum of the mean value and the standard deviation of the performance index. Integrating the multiobjective optimization to the level set-based topology optimization method, this study adopts the lp-norm method that can obtain the Pareto solution even when the Pareto frontier is a non-convex form. Through numerical examples of a compliant mechanism design, validity of the proposed method is verified. Then, the robustness of the obtained optimum configuration is discussed.

We construct a structural optimization method targeting lattice structures composed of a sufficiently large array of unit cells where each unit cell consists of several beam elements, with the aim of maximizing the stiffness of the entire structure under a volume constraint. In this method, micropolar continuum theory is introduced for continuum modeling of the lattice structures because micropolar continua and beam elements both have rotational degrees of freedom in addition to translational degrees of freedom. That is, the material behavior of a micropolar continuum that is equivalent to the lattice structure is obtained so that the strain energy density of the micropolar continuum is equal to the volume average of the strain energy stored in a unit cell of the lattice structure, which is derived from the framework of classical beam theory. The conventional finite element method is expanded for numerical analyses of the micropolar continuum to take the rotational degrees of freedom into account. The optimization algorithm has the width of each frame element set as a design variable and represented as a continuous distribution in the modeling of the micropolar continuum. Finally, two design examples are provided to confirm the validity and effectiveness of the proposed method.

This study investigates the robust topology optimization of a thin plate structure under a concentrated load with load position uncertainty. The effect of uncertain load direction, load magnitude, and load distribution in topology optimization problems has been investigated in previous research, but few studies have dealt with robust topology optimization considering load position uncertainty. In this study, load position uncertainty is modeled using the convex hull model, in which the load position uncertainty is confined within a circular area whose center is at the nominal load position. The worst load condition is defined as that when the applied load is at a position in the convex hull that gives the worst value of the mean compliance. Here, the robust objective function is formulated as a weighted sum of the mean compliance obtained from the mean load condition and the worst compliance obtained from the worst load condition, with a plate model based on Reissner-Mindlin plate theory. The robust topology optimization problem is formulated using a level set-based topology optimization method. Through numerical examples, robust optimum configurations are compared with deterministic optimum configurations and the validity of the proposed robust design method is then discussed.

The aim of this research is to construct a topology optimization method for the design of micropumps driven by induced-charge electro-osmosis. Micropumps are one of the most important components in micro-fluid devices such as μ-TAS (Micro Total Analysis Systems). In particular, electro-osmotic micropumps offer many advantages. They have a simple structure, are easy to miniaturize, and generate flow that is free from pulsation, but such pumps are typically driven by direct current fields, so electrolysis may cause problems. To avoid the problems of electrolysis, a phenomenon called induced-charge electro-osmosis is attracting increasing attention because, being driven by alternating current fields, electrolysis is much less prevalent. Since the amount of liquid discharge is controlled through the electro-osmotic phenomenon, the micropump performance is greatly influenced by the shapes and locations of the dielectric material in its interior. For the design of the distribution of dielectric material in a micropump, we construct a topology optimization method for the micropump design that maximizes the amount of liquid discharge, using level set boundary expressions so that the expressed structural boundaries are free from expanded grayscale areas. Several numerical examples are provided to confirm the utility of the proposed method.

In this study, a robust topology optimization method is proposed for compliant mechanisms, where the effect that variation of the input load direction has on the output displacement is considered. Variations are evaluated through a sensitivity-based robust optimization approach, with the variance evaluated using first-order derivatives. The robust objective function is defined as a combination of maximizing the output deformation under the mean input load and minimizing variation in the output deformation as the input load is varied, where variance due to changes in load can be obtained through mutual compliance and the presence of a pseudo load. For the topology optimization, a modified homogenization design method using the continuous approximation assumption of material distribution is adopted. The validity of the proposed method is confirmed with two compliant mechanism design problems. The effect that varying the input load direction has upon the obtained configurations is investigated by comparing these with deterministic optimum topology design results.

Conflicting interrelationships among objective functions are often encountered in real-world engineering design problems. If such exist in a multiobjective optimization problem, no unique solution can simultaneously minimize all of the objective functions. Instead, the solutions of a multiobjective optimization problem are obtained as non-dominated solutions called a Pareto optimal solution set. Since a comprehensive Pareto optimal solution set enables the analysis of the trade-off relationships between conflicting objective functions, obtaining such a solution set can be highly beneficial because it increases flexibility when making engineering design decisions. Therefore, this paper proposes an aggregative gradient-based multiobjective optimization method for bi-objective optimization problems, which can ensure the diversity of the Pareto optimal solution set. The proposed method utilizes an aggregative optimization approach where multiple points are concurrently updated during the optimization process. First, an appropriate searching direction for each point is calculated by solving a linear programming problem considering point distribution. Next, design sensitivities are calculated at each point for use as gradient information in the objective functions and constraints. Then, the design variables of all points are updated using a local optimization technique that considers the previously calculated searching direction. During this update process, the proposed method introduces distance constraints among all the points in the objective function space in order to maintain their diversity, which ensures the diversity of the obtained Pareto optimal solution set. These steps are iteratively conducted until the optimization process is converged. Several numerical examples, including a topology optimization problem, are provided to confirm the usefulness of the proposed bi-objective optimization method.

Much effort has been made to experimentally fabricate acoustic metamaterials that display novel properties, such as single or double negativity, negative refractive index. The novel properties displayed by acoustic metamaterials and their deep subwavelength nature, whereas the size of phononic crystals is in a comparable scale to wavelength, facilitate the development of real-world applications, from sound attenuation to superlenses, and acoustic cloaking. Compared with a conventional trial and error method, a systematic structural design methodology such as topology optimization is useful to achieve optimal designs of acoustic metamaterials. This paper proposes a topology optimization method for the design of acoustic metamaterials with the property of negative mass density. We consider mass-in-mass system that consists of a solid inclusion coated with a soft materials embedded in matrix material to produce a local dipole resonance that demonstrate negative mass density. The optimization is conducted to find optimal configurations of a locally resonant unit cell structure which achieves negative mass density at a certain desired frequency. The S-parameter retrieval method is efficaciously applied to describe the acoustic metamaterial according to its effective mass density. A level set-based method is employed to obtain the optimal configurations that have clear boundaries without gray scales, which would otherwise limit fabricability of the obtained acoustic metamaterial designs. The sensitivity analysis is performed by the adjoint variable method, and a reaction-diffusion equation is used to update the level set function. Several numerical examples are provided to demonstrate how the algorithm works, and the obtained optimal configurations illustrate the achievement of acoustic metamaterials that have negative mass density at certain prescribed frequencies.

Historically, fluidic devices such as switches, amplifiers, and oscillators, have an advantage, compared with electronic devices, in terms of maintenance-free operation and operating life. Therefore, prior to the great progress in electronic technologies that has occurred during the past several decades, the structure and function of fluidic devices were the subject of extensive research. In particular, the structures of these fluidic devices are often composed of complicated flow channel layouts. Recently, fluidic devices are again attracting significant attention, stimulated by progress in the development of MEMS technologies. In this study, to develop an energy-efficient structure for a MEMS-scale fluidic device, we apply a topology optimization method to an optimal design problem for a steady state incompressible viscous flow field. We use a level set-based topology optimization method incorporating the concept of the phase field method for the topology optimization so that clear boundaries between the solid and fluid domains are expressed in the optimal configurations. To define the topology optimization problem for a fluid regime, the expressions of the primary and adjoint problems are formulated concretely, to minimize viscous energy dissipation. Moreover, to ensure the intended design outflow rate at a designated outlet, the optimization problem includes an outflow rate inequality constraint in this paper. Following the concept of the standard adjoint variable method, a stable optimization process that satisfies the outflow rate inequality constraint is achieved. Two numerical examples, one for two-terminal and the other for multi-terminal flow, are provided to demonstrate the usefulness of the proposed level set-based topology optimization method.

The topology optimization method using the level set method and incorporating a fictitious interface energy derived from the phase field method was proposed by part of the authors. The method has been applied to several structural and multidisciplinary design problems. However, the method has not been applied to the plate bending structural design problem using the two-dimensional plate bending element model yet, regardless that the thin plate structures are widely used in engineering applications that require lightweightness. This paper extends the topology optimization method to the thin plate structure for maximizing stiffness under out-of-plane deformation by using the thin plate bending elements based on Reissner-Mindlin theory. The structural design problem using the thin plate bending elements is formulated as the mean compliance minimization under volume constraint problem. Through simple numerical examples, effects of the proposed method are illustrated. At first, the method significantly reduces computational cost for the thin plate maximizing stiffness design problem in comparison with the three-dimensional solid model. The obtained optimum configuration is shown to be equivalent to that of the three-dimensional solid model. Then, it is shown that the advantages of the method such as high convergence property, low initial design dependency, and the effect of the regularization parameters on the complexity of the configuration are also held in the plate bending element model.

Damping material is usually applied on the steel panel of a vehicle to reduce vibration level. On the other hand, the weight reduction is also required to improve fuel consumption. Therefore, modal loss factors induced by damping material on the steel panel of a vehicle body structure need to be maximized with a given volume. In this paper we propose a practical design method to maximize modal loss factors by optimizing the material distribution of damping material under a volume constraint. The modal loss factor of an eigen mode can be written as the ratio of the strain energy stored in the damping material over the total strain energy in the system under consideration. In the proposed method, we assume the eigenvectors are almost the same as the eigenvectors when damping material is removed. The modal loss factor can then be represented by using a corresponding eigenvalue where the mass density of the damping material is ignored whereas the stiffness is taken into account. Several numerical examples are provided to show the optimal distribution of the damping material by using a flat panel. Damping material is distributed in the domain where the strain energy is stored, which agrees well with our experiences. Moreover, by applying a sensitivity filter that utilizes a weighted average of design sensitivities over local area, damping material can be distributed collectively in a single domain to meet practical requirements for manufacturing,

Objective: Rare coexistence of disease or pathology Background: Group G streptococcus (GGS) infection is reported to have invasive pathogenicity similar to that of group A streptococcus (GAS) infection, causing a strong systemic inflammatory response with bacteremia and various complications. Herein, we report a case of posterior reversible encephalopathy syndrome (PRES) as a rare complication of a GGS infection. Case Report: An 89-year-old Japanese man presented to our hospital with gastrointestinal bleeding and shoulder pain. Close examination revealed a refractory duodenal ulcer (DU) with disseminated intravascular coagulation and soft tissue infection of the right arm, which was found to be caused by GGS. A hemorrhagic tendency due to disseminated intravascular coagulation made it difficult to achieve hemostasis, leading to repeated blood transfusions. Although remission of both the DU and infection was achieved with treatment, impairment of swallowing function and vision subsequently appeared. Magnetic resonance imaging revealed hyperintense lesions with elevated apparent diffusion coefficient (ADC) values on T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging (DWI). The patient was diagnosed with PRES, which did not improve even after discharge on day 118. Conclusions: GGS infection developed with refractory duodenal ulcer bleeding, resulting in PRES with irreversible sequelae. The occurrence of PRES, which may be a rare complication of GGS infection, should be considered when central nervous system manifestations are observed in case of invasive streptococcal infection with a systemic inflammatory response. [ABSTRACT FROM AUTHOR]