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We investigated the suppression of residual warpage using a negative thermal expansion (NTE) material filler, Zn1.6Mg0.4P2O7. To focus on the effect of thermal expansion on residual warpage, we used acrylonitrile-butadiene-styrene, which is an amorphous polymer with a small volume change around the liquid–solid phase transition, as the matrix. Composite pellets were prepared using a kneader, and filaments were produced for fused deposition modeling (FDM) using an extruder. We fabricated a bar-like test piece using a standard FDM machine and measured the warpage deformation using 3D scanning. The experimental results were supported by the finite element method. We also compared similarly sized SiO2 powders to discuss the advantages of NTE over conventional fillers. The warpage of a 100 mm x 5 mm x 2 mm bar-like test piece was reduced by approximately 75% by introducing Zn1.6Mg0.4P2O7 at 40 vol%. The effect of Zn1.6Mg0.4P2O7 at 30 vol% is similar to that of a conventional SiO2 filler at 40 vol%. Reducing the residual deformation through fillers would reduce energy consumption and simplify the device by avoiding build stage and chamber heating.

The purpose of this paper is to construct a methodology which can produce a lightweight panel structure while being satisfied with more than one constraint by using some simple model. In this study, we chose a problem including bending stiffness and the 1st order eigen frequency as constraints and volume minimization as objective function among basic performances which a vehicle requires. So far, we have been trying to solve the problem by using a method consisting of Fully Stressed Design (FSD) and Genetic Algorithm (GA). FSD is an optimization which evaluates only stiffness of a structure based on relationship between thickness and stress, while GA, a broad array method, can have various number of objective functions and constraints. Prior to this study, the authors found a process was effective that stresses on the elements were to be equalized in the 1st step by applying FSD that made an individual superior on static stiffness. In this study, proposed method, which includes a process of equalization on normalized stresses on eigen vibrations, are added to that of static stresses in the 1st step. In the 2nd step, GA is selected. GA conducts operations, such as select, crossing, and mutation repeatedly until this attains a final solution. As for the model, we chose a sandwich panel which is equipped with top and bottom plates and interlayer lattice stiffeners. The reason for this selection is that the sandwich panel is lightweight and superior to stiffness, dumping, and strength. As a result, the obtained model presents a lightweight structure while being satisfied with the requirements of both stiffness and eigen frequency. Moreover, the proposed method attains optimized results earlier than GA without using FSD.

This study proposes a systematic inverse design framework for constructing multistable mechanical metamaterials with programmable gradients. Herein, we designed the tailored bistable cells with precisely controlled maximum instability forces through the topology optimization approach. Then, the designed bistable structures were programmed to construct the multistable mechanical metamaterials with different target gradient snapping sequences and deformation models. Consequently, the simulation and experimental results showed the feasibility of the design method, which successfully produced two- and three-dimensional mechanical metamaterial structures with different functions. Finally, we verified the expected deformation sequences and multistable behaviors of mechanical metamaterials by testing the designed specimens prepared via additive manufacturing. Overall, our findings show that the proposed design strategy offers a new paradigm for developing precisely tailored and programmable mechanical metamaterials.

Fiber-reinforced composites are currently considered engaging materials by engineers and researchers in automobile, aerospace, robotics, and other related industries and scholars in academics due to their superior mechanical properties. Using the materials as structural materials allows engineers to make lightweight but high-stiff mechanical structures happen in reality. By adopting a structural optimization methodology, they can explore further and bring out the mechanical properties of composites as much as possible to design innovative composites structures. Based on this background, it has already been a hot research topic to establish a method for concurrent optimization of topology and fiber orientation in the structural optimization research field. This optimization method will be more effective in the real world by considering uncertainties that engineers commonly encounter. However, anisotropic topology optimization researches on this motivation are very rare. In the present work, we propose a robust topology and orientation optimization methodology accounting for fiber manufacturing uncertainty, namely orientation uncertainty. The proposed method is built upon the Phase Field and the Method of Moving Asymptotes based SIMP type topology optimization and EOLE-PCE uncertainty quantification. Numerical analysis is done by the Finite Element Method. The effectiveness of the proposed method is validated through the compliance minimization problem and the fundamental eigenfrequency maximization problem.

In recent years, the popularity of fiber-reinforced materials in the aerospace and automobile industries grows due to their high stiffness-to-weight ratios. Thus, a structural design methodology is needed to bring out the celebrated mechanical properties of these materials as much as possible. From this aspect, topology optimization has been considered as an effective method for such a method. As a natural consequence of the trend, intensive researches on topology optimization methodologies to handle the anisotropy of fibrous materials has been conducted. However, these researches were limited to the static problem, i.e., compliance minimization problem. In the present work, we propose a dynamic topology optimization method for fiber-reinforced materials which is capable of optimizing element-by-element orientations. Our method builds upon a framework of SIMP type topology optimization and can optimize each element’s density and orientation as design variables. Numerical analysis is done by Finite Element Method and Method of Moving Asymptotes is implemented as an updating scheme of design variables. The effectiveness of our method is validated through the eigenfrequency maximization problem and eigenfrequency gap maximization problem.

By using sparse modeling to formulate the relationship between the data of the design image of an automobile body frame and the amount of frame function, we developed a method to extract the features of the image that are important for improving the function. The important areas of the cross-sectional shape visualized by the method and the design guidelines for the cross-sectional shape derived from the visualization are consistent with the findings obtained in previous studies. In addition, we were able to obtain new findings that were not previously available. In other words, this method has the potential to elucidate unknown important factors that are not assumed by designers and to derive general purpose design guidelines by utilizing a large amount of design image data obtained in shape optimization.

Biodegradable materials have demonstrated promising potential for the treatment of bone fractures. Therefore, it is crucial to design biodegradable composites considering the degradation effect. Accordingly, to realize a composite material with controlled stiffness at the bone repair stage, this study introduces a novel topological optimization technique for the material layout design in microstructure, considering material degradation. In this approach, two sets of variables are adopted: a density field that defines the material layout, which is also the design variable, and a time field that determines the effect of material degradation on composite material properties. A continuous degradation update formula is proposed by integrating the Heaviside function and the Kreisselmeier–Steinhauser function to guarantee its derivability. The objective of this study was to maximize the material stiffness in some fixed time steps under a specified volume fraction. The sensitivity of the aforementioned objective relative to the design variable was deduced by considering the material degradation over time. The proposed design approach was demonstrated with several design examples, considering different degradable interface boundary conditions. Furthermore, the obtained results were compared with the results obtained without considering material degradation, thereby verifying the effectiveness of the proposed method.

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO2 emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables. Keywords: Structural optimization, Stiffener layout, Hybrid GA, Design variable

From the viewpoint of suppressing global warming, it is required to reduce CO2 emissions during driving by improving the fuel efficiency of automobiles. For that purpose, it is necessary to reduce the weight of the vehicle body frame to reduce running resistance. The most important function required of the frame member is the strength function to secure a space for the occupants to survive in the event of a collision. In general, the weight reduction and strength functions of the frame are in conflict, and structural design technology that suppresses cross-sectional collapse is important. We studied the plate shape that controls the in-plane bending buckling of the vertical plate of the cross section with the aim of suppressing the cross-sectional collapse of the automobile body frame formed of thin and high-strength steel sheets and utilizing the material strength of the steel sheet. From the theory of post-buckling strength of thin plates, we focused on the support conditions of the vertical plate and clarified the relationship with the shape of the peripheral structure. In addition, we derived a new shape proposal that suppresses buckling based on the shape of the vertical plate itself, and confirmed that it is possible to develop a buckling resistance that approaches the theoretical value that directly constrains the periphery.

The granular damper enables damping of vibration by enclosing a plurality of particles in the structure. The vibration damping principle of the granular damper is the dissipation of energy due to friction between particles. Since this damper is easy to install, it has been applied research as a vibration control structure for various machines. In order to ensure vibration damping performance and perform design, it is necessary to predict the frictional force between particles and the collision force with a container by simulation. The purpose of this research is to propose the evaluation method of the vibration damping performance of the granular damper and the prediction method by the discretized element method using the fine particles with the basic particle diameter of 100 μm or less. As for the experimental method, various evaluations have been made possible by a simple test method in which fine particles are enclosed in a metal plate. With this test method, we succeeded in obtaining a good damping effect even with a granular damper with a particle size of 100 μm or less, and finding the control factors necessary for design.

Designing sophisticate ship structures that satisfy several design criteria simultaneously with minimum weight and cost is an important engineering issue. For a ship structure composed of a shell and stiffeners, this issue is more serious because their mutual effect has to be addressed. In this study, a two-stage optimization method is proposed for the conceptual design of stiffeners in a ship's prow. In the first stage, a topology optimization method is used to determine a potential stiffener distribution based on the optimal results, whereupon stiffeners are constructed according to stiffener generative theory and the material distribution. In the second stage, size optimization is conducted to optimize the plate and stiffener sections simultaneously based on a parametric model. A final analysis model of the ship-prow structure is presented to assess the validity of this method. The analysis results show that the two-stage optimization method is effective for stiffener conceptual design, which provides a reference for designing actual stiffeners for ship hulls. Keywords: Prow stiffener, Two-stage optimization, Manufacturing constraints, Multi-objective function, Compromise programming

Abstrak Efek dari krisis ekonomi global adalah menurunnya aktivitas ekspor dan impor yang mempengaruhi terhadap menurunnya permintaan pembangunan kapal baru. Hal ini mengakibatkan galangan kapal melakukan efisiensi di seluruh aspek untuk tetap bertahan salah satunya dengan mengurangi biaya produksi sebuah kapal. Banyak studi terkait pengurangan berat dan biaya yang telah dilakukan dengan menggunakan metode optimasi. Penulis memilih struktur dek kapal yang terdiri dari pelat dan stiffener sebagai studi kasus. Pada studi ini, penulis mengoptimasi biaya fabrikasi struktur dek kapal yang terdiri dari biaya material dan biaya pengelasan dengan menggunakan hybrid algoritma genetika yang mengkombinasikan algoritma genetika dan metode optimasi lanjut. Algoritma genetika mengoptimasi variabel desain diskrit yang terdiri dan jumlah stiffener dan ukuran stiffener sedangkan metode optimasi lainnya mengoptimalkan variabel desain kontinyu yang terdiri dari jarak stiffener dan ketebalan pelat. Penulis mengambil bagian dari dek kapal tanker menjadi target optimasi yang kemudian dibandingkan hasilnya dengan data awal kapal. Hasil menunjukkan bahwa metode optimasi ini dapat mengurangi biaya fabrikasi dek kapal hingga 25 %. Abstract The impact of the global economic crisis is a decline in import and export activities resulting in a decrease in shipbuilding demand. Shipyard companies do efficiency in all aspects to survive which one of them is reduced production cost of a ship. Many studies for a lightweight and low-cost structure are being done which we also propose to solve the problem with the optimization method. We selected deck structure as a case study which is composed of plates and stiffeners. In this study, we optimized fabrication cost such the material cost and welding cost with a hybrid genetic algorithm (GA) which applied a genetic algorithm and other optimization methods. Genetic algorithm optimized the discrete design variables which are a number of stiffener and type of stiffener and other optimization methods optimized the continuous design variables which are stiffener spacing and plate thickness. We carried out part of deck structure of crude oil tanker, and the optimization results compared with data of existing ship. The result shows that the optimization method can decrease the fabrication cost of deck structure about 25 %.

Structure can get various mechanical characteristics by applying periodic structures as typified by lattice structures. Lattice structures are generally used inside the structural member in order to reduce the weight. One advantage of lattice structures is that we do not need to change the whole structural shape when we replace the solid part of a component with the lattice structures. Another advantage is the lightness of the weight, and hence it is important to design a high performance lattice shape with low weight. However, a framework for development of micro lattice structures considering both stiffness and weight has not been established. Thus, we propose a method for designing and producing micro lattice structures. We use a topology optimization method for a designing methodology. Topology optimization is an effective method in designing high performance lattice structure since topology optimization allows us to change the topology and to design a complicated shape. We use a metal additive manufacturing (AM) machine for producing the optimal lattice structures. AM allows us to produce a complicated structure which removal and forming manufacturing cannot produce. We use a bulk modulus as the objective function since it is one of the important mechanical characteristics in design. In this research, we use a homogenization method to compute the bulk modulus. Objective function was modified so that isotropy of the optimal shape is retained when the solution is updated. In addition, structures produced by AM need holes so that internal metal powder can be removed. Hence, we defined the design domain so that the optimal structure becomes open cell structure. Then, high bulk modulus shapes were derived using topology optimization. The lattice structures were produced by metal AM machine after being modified for production.

The extraordinary mechanical properties of additive manufactured two-scale lattice structures can be substantially enhanced by employing optimisation techniques at both macroscopic and microscopic scales. Nonetheless, maintaining structural strength in designs that simultaneously incorporate complicated macroscopic and microscopic configurations presents a significant challenge. In this study, a two-scale topology optimisation method with microscopic stress constraints is proposed to find a two-scale structure with maximised stiffness while making the microscopic stress satisfy specified strength criteria. Herein, a two-scale structural stress characterisation based on the microscopic characterised stress field is firstly established to avoid the great computational effort caused by microscopic stress analysis at every macroscopic localisation. Then, a two-scale stress-constrained aggregation strategy is proposed to reduce the vast number of stress constraints involved in two-scale optimisation. The sensitivities of the aggregated stress constraints are derived using the adjoint variable method, and the optimisation problem is solved using a gradient-based mathematical algorithm. Numerical examples illustrate the effect of the stress constraints by comparing the optimisation results with and without microscopic stress constraints. Finally, specimens optimised using the proposed method are realised through additive manufacturing, and the results are further validated by testing stress distribution using a non-contact full-field strain measurement system.

In this paper, we propose a new control method to boost electrical energy. Vibration energy harvesting extracts electrical energy from structural vibrations. To boost the harvested energy, synchronized switching harvesting on inductor (SSHI) technique has been proposed and developed. With a harvesting circuit including an inductor and a switch, SSHI technique controls electric current by switching action. The technique effectively converts the mechanical energy of structural vibration to electrical energy, but at the same time, it suppresses the amplitude of mechanical vibration. Because the voltage generated by a piezoelectric transducer depends on the vibrational amplitude, the decrease in the vibrational amplitude leads to the reduction in the generated voltage. As a result, the harvested energy is decreased. We confirm that the vibrational amplitude and the harvested energy are decreased with SSHI. To solve this critical problem, we devise a new control strategy to boost the harvested energy. The original SSHI conducts switching action at every peaks of vibrational displacement. In order to avoid the suppression of vibration, our control strategy is designed to temporarily stop the switching action. The structure is excited to vibrate by a vibration exciter. While switching action is stopped, the vibrational amplitude will be recovered from the suppressed amplitude by the excitation force, which makes the vibrational amplitude as high as possible. Accordingly, the harvested energy will increase. We experimentally demonstrate that our control strategy holds back only 12.6% reduction of the vibrational amplitude, while the original SSHI causes as much as 76.4% reduction. The piezoelectric voltage is up to 2.9 times greater than that with the original SSHI. Experimental results show that the proposed control strategy can generate 8.4 times larger electrical energy than the original SSHI.

An optimization technique using the hybrid GA for large structures in which a lot of stiffeners are attached is proposed in this paper. The object function is the mass of structure and the design variables are the number and the position of stiffeners, the shape of stiffener and the thickness of plate. These design variables make a combinational optimization problem for which genetic algorithm is effective. However, this optimization problem includes the position of stiffener and the thickness of plate which are kinds of continuous design variables. A lots of bits are needed for expressing continuous design variables by strings of genetic algorithm in order to have reasonably small increments of them, which results in a large calculation amount. In order to overcome this problem, a hybrid GA is introduced in this paper. Hybrid GA is optimization method which combines GA with another optimization technique which handles continuous design variables. The relation among the thickness of plate, the span of stiffeners attached on the plate, the deflection and the stress of plate are introduced in order to predict suitable design variables in this added optimize technique. The proposed optimization method makes it possible to optimize continuous design variables, the position of stiffeners and the thickness of plate,with small calculation amount. Several selected problems are solved to show the capacity and validity of the proposed method.

In this paper, we present the benefits of bond-graph analysis for mechanical-electrical systems, which are energy-harvesters based on structural vibrations and electric loads. The bond-graph is an energy-based approach to describing physical-dynamic systems. It shows power flow graphically, which helps us understand the behavior of complicated systems in simple terms. Energy-harvesting involves conversion of power in mechanical form to the electrical one and the bond-graph is a good tool to analyze this flow. The bond-graph method can be used to calculate the dynamics of the combining mechanical and electrical systems simultaneously. The biggest advantage of the bond-graph technique is that it can be used with the systems that are subject to component alternations, such as inserting, removing and swapping. The bond-graph method involves solving simultaneous algebraic equations, instead of differential equations. On the other hand, in common simulation methods, such as solving differential equations, it is difficult to change the number of components because the differential equations will have to be reconstructed. Because the bond-graph has not been used for harvesting analysis, bond-graph models for harvesting need to be created in advance of numerical analysis. In this paper, we first proposed a piezoelectric model that matches the bond-graph method. We also propose a diode-bridge model and a harvesting controller model that are suitable for bond-graph analysis. We then analyze a self-powered energy harvester that has multi-bifurcated and looped flow in the mechanical-electrical coupled dynamics.

Additive manufacturing (AM) could be a novel method of fabricating composite and porous materials having various effective performances based on mechanisms of their internal geometries. Materials fabricated by AM could rapidly be used in industrial application since they could easily be embedded in the target part employing the same AM process used for the bulk material. Furthermore, multi-material AM has greater potential than usual single-material AM in producing materials with effective properties. Negative thermal expansion is a representative effective material property realized by designing a composite made of two materials with different coefficients of thermal expansion. In this study, we developed a porous composite having planar negative thermal expansion by employing multi-material photopolymer AM. After measurement of the physical properties of bulk photopolymers, the internal geometry was designed by topology optimization, which is the most effective structural optimization in terms of both minimizing thermal stress and maximizing stiffness. The designed structure was converted to a three-dimensional stereolithography (STL) model, which is a native digital format of AM, and assembled as a test piece. The thermal expansions of the specimens were measured using a laser scanning dilatometer. Negative thermal expansion corresponding to less than −1 × 10−4 K−1 was observed for each test piece of the N = 3 experiment.

Cooling structures require sufficient thermal conductivity. However, structure with thermal conducting could suffer high temperature, and thermal deformation could become serious. Thus, designing structures suppressing thermal deformation is an important task for designing cooling structures. Structural characteristics like stiffness and thermal conductivity are affected by structural shape. Thus, we intend to design structure with sufficient thermal conductivity, small thermal deformation, and light weight. Since these design factors have a trade off relationship, this research aims to develop design method achieving these characteristics with high levels. Structural optimization methods are able to be utilized designing structure satisfying contradicting design factors. Topology optimization (TO) is one of the most flexible optimization methodology. Thus, TO is selected as structural optimization in this research. Since we intend to design structures have sufficient thermal conductivity and minimum thermal deformation, the target of optimization is maximization of stiffness for thermal stress and thermal conductivity is introduced as a constraint. As criteria of stiffness and thermal conductivity, the structural compliance and thermal compliance are used. The structural optimization is implemented using solid isotropic material with penalization (SIMP) method of TO. Design variables are updated by sequential linear programming (SLP) in the early stage. In the latter stage, phase field method is applied to update design variables. To clarify the validity and the utility of the proposed methodology, some numerical examples are studied. Through these numerical examples, optimal shapes with high thermal conductivity and high stiffness for thermal deformation are clarified.

Vibration suppression is one of the most important problems in the design and operation of space structures. Due to limited launch capabilities, such structures need to be extremely light-weight although some structures succumb to vibrations because of their low structural stiffness. Moreover, vibrational energy is hard to disperse in the vacuum of space, in contrast to ground environments. These problems can be overcome by vibration control schemes.Vibration control schemes can be categorized into three types: active, passive and semi-active. The semi-active vibration control (SAVC), dynamically changes some property of the structure according to feedback from the state, without adding extra energy. SAVC systems are usually able to achieve higher performance than the passive vibration control schemes without the disadvantages of the active vibration control systems. In this study, optimal piezo actuator layout is solved by the introduction of Shock Response Spectrum (SRS) constraint which evaluates vibration and a shock.

Cloaking techniques conceal objects by controlling the flow of electromagnetic waves to minimize scattering. Herein, the effectiveness of homogenized anisotropic materials in non-resonant dielectric multilayer cloaking is studied. Because existing multilayer cloaking by isotropic materials can be regarded as homogenous anisotropic cloaking from a macroscopic view, anisotropic materials can be efficiently designed through optimization of their physical properties. Anisotropic properties can be realized in two-phase composites if the physical properties of the material are within appropriate bounds. The optimized anisotropic physical properties are identified by a numerical optimization technique based on a full-wave simulation using the finite element method. The cloaking performance measured by the total scattering width is improved by about 2.8% and 25% in eight- and three-layer cylindrical cloaking materials, respectively, compared with multilayer cloaking by isotropic materials. In all cloaking examples, the optimized microstructures of the two-phase composites are identified as the simple lamination of two materials, which maximizes the anisotropy. The same performance as published for eight-layer cloaking by isotropic materials is achieved by three-layer cloaking using the anisotropic material. Cloaking with an approximately 50% reduction of total scattering width is achieved even in an octagonal object. Since the cloaking effect can be realized using just a few layers of the laminated anisotropic dielectric composite, this may have an advantage in the mass production of cloaking devices.