Toward Optimal Design of Rainbow Metamaterials

This paper presents an optimal design strategy for a floating raft vibration isolation system which is extensively deployed for mounting engines in ships and underwater vehicles. Multiple design variables of the floating raft including total mass, static stress, resonance frequencies, and vibration isolation effects within a prescribed frequency range are taken into account so as to determine the optimization objective, which are the critical concerns in early design stage, i.e., vibration attenuation and the comfort of the crews. In addition to the conventional constraints like geometric sizes and mass, the static stress and vibration level of the floating raft vibration isolation system under specific load cases are also considered. According to the above requirements and principles, an optimal model is developed. Through comprehensive optimization analysis, an optimized design of a floating raft system is provided, which can ensure lower vibration level of the foundation in a prescribed frequency range without at expenses of unnecessary weight and excessive equipment motions. This design strategy would lend itself to bridge structural and acoustic design in a unified way during early design stage.

Integrated optimization of structural topology and control for piezoelectric smart trusses using genetic algorithm

In this study, the optimization of logistics strategies for long-duration space-station operations is investigated; both the visit times and payload manifests of a series of coordinated flights of cargo vehicles are considered at the same time. An optimization model is established that employs both the launch time and manifesting mix of payload classes as design variables and considers the rendezvous launch window, onboard consumption demand, and vehicles’ carrying capabilities as constraints. Four metrics are defined to quantify the utilization benefit and operational robustness of a space-station operational scenario. Each metric is used as the optimization objective function, and a genetic algorithm is employed to obtain the optimal solutions. The approach is demonstrated with a notional one-year operational scenario of China’s future space station. The results indicate that the visit times of cargo vehicles have a considerable influence on logistics strategies, and each objective function of different metrics yields a different optimal logistics strategy.

The objective of this investigation is to carry out the topology design optimization of the pickup suspension of high-speed optical pickups in DVD’s or CD ROM’s. The specific design target here is to increase the torsional eigenfrequency of the pickup as high as possible while keeping the focusing eigenfrequency between 25 Hz and 35 Hz, and the tracking eigenfrequency between 43 Hz and 57 Hz. These frequency ranges are set to meet other design constraints such as servo-controllability. A typical pickup consists of a bobbin having an optical lens and suspension plates to support it. Since the eigenfrequencies of the bobbin itself are in the order of 10 kHz, it can be modeled as a point mass when dealing with the low-frequency dynamic characteristics in consideration. These modeling techniques are verified in the previous researchers. In modeling the bobbin, we also consider its moments of inertia. In designing the suspension system, damping bond is usually applied to control the quality factors at the focusing and tracking frequencies. The location of the damping treatment on the suspension system may be determined by an optimization method, but this is not pursued in this work since the result by the earlier work can be applied to the present suspension system. Unlike static problems such as compliance minimization problems with single and multiple loads or compliant mechanism problems with single and multiple input/outputs, optimization problems involving eigenvalues suffer from mode-switching, which often causes serious difficulties in solution convergence. Mode-switching represents the phenomenon that eigenmodes are changed during the update of design variables. If the design target were simply to maximize a few lowest eigenfrequencies, the mode-switching problem would be handled rather easily. However, the present optimization problem is not the case because we must follow the eigenfrequencies of the specific modes such as tracking, focusing and twisting modes during the optimization process. To handle this situation satisfactorily, we should employ a technique to track the desired modes. In the present investigation, the desired modes are traced by means of the modal assurance criterion (MAC), which has been widely used in experimental modal analysis. For the pickup consisting of a bobbin and suspension plates, the present design goal can be achieved by optimizing the configuration of the suspension plates. To find an optimal plate configuration, we employ the topology optimization method, but the specific method employed here is the multiscale topology optimization method. In the multiscale optimization method, the density design variables are transformed into multiscaled design variables by a series of nonlinear and linear transformations. With the multiscale topology optimization method, the optimization can be completed more efficiently than the optimization by 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization 4-6 September 2002, Atlanta, Georgia AIAA 2002-5483 Copyright © 2002 by the author(s). Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. the standard single-scale direct density method. As an optimizer, the feasible direction method is employed to handle effectively multiple constraints on eigenfrequencies. By the present application of the topology optimization method, the twisting eigenfrequency has been maximized while the focusing and tracking eigenfrequencies are kept in the prescribed frequency range. The optimized suspension plate in the present work outperforms the designs improved from the existing rectangular bend-type plates.

A Taguchi study was performed to determine the important players in the aeroelastic tailoring design process and to find the best composition of the optimization's objective function. The Wing Aeroelastic Synthesis Procedure (TSO) was used to ascertain the effects that factors such as composite laminate constraints, roll effectiveness constraints, and built-in wing twist and camber have on the optimum, aeroelastically tailored wing skin design. The results show the Taguchi method to be a viable engineering tool for computational inquiries, and provide some valuable lessons about the practice of aeroelastic tailoring.

Analysis on the effect of novel topological optimization fin structures considering eccentricity on the heat storage and release characteristics of shell and tube phase change heat accumulator

Urban combat environment is affected by buildings and traffic network with certain spatial characteristics. A single unmanned combat vehicle carries out the coverage reconnaissance task will be constrained by the limited information and low efficiency, so multiple UGVs(Unmanned Ground Vehicles) cooperative coverage becomes an effective means to solve the problem. In this paper, the urban coverage reconnaissance task is formulated as a vehicle routing problem, and a new traversal model is proposed, which takes account the connectivity characteristics of the road. At the same time, different from the traditional routing planning, which takes the total cost of executing tasks as the optimization objective. We consider the time efficiency of the battlefield, and takes the coverage reconnaissance time as the optimization objective function (in most cases of multiple UGVs coverage tasks, the longest task execution time is taken as the optimization objective). And we proposed a neural combinatorial optimization technique to solve the problem. Through simulation experiments, the feasibility and effectiveness of the proposed model is verified.

Torque ripple is a major problem for switched reluctance motors, which may cause undesirable vibration and acoustic noise, especially at low speed. This paper presents an optimal topology structure of rotor for 8/6 pole switched reluctance motor by using the level set method. The nonlinear ferromagnetic material boundary of rotor pole is implicitly represented through an embedded level set function. This method is applied to obtaining the optimal distributions of material in the design domain for minimizing torque ripple and maximizing average torque. In the optimization objective function, the reluctivity of ferromagnetic material is selected as the design variable. The normal velocity is derived from sensitivity analysis, where the adjoint variable method is utilized. Two-dimensional finite element method is employed to calculate the electromagnetic parameters of this electric machine. Analysis results obtained from the transient simulation of electromagnetic field coupled with control circuit show that the torque ripple is reduced effectively by using the optimized rotor structure.

Influence of gear tooth addendum and dedendum on the helical gear optimization considering mass, efficiency, and transmission error

Multi-objective optimization of a typical parallel tracking mechanism considering parameter uncertainty is carried out in this paper. Both dimensional and sectional parameters are regarded as design variables. Workspace, kinematic, stiffness, and dynamic performances are simultaneously considered in formulating optimal objectives and constraint conditions. Considering manufacturing and assembling errors, parameter uncertainty is modeled and evaluated to minimize their effects on the optimized performances. Analytical models between objectives and design variables are established to improve the efficiency of optimization while its accuracy is assured. The study of parameter uncertainty and analytical mapping model is incorporated in the optimization of the parallel tracking mechanism. With the aid of particle swarm algorithm, a cluster of solutions, called Pareto frontier, are obtained. By proposing an index, a cooperative equilibrium point representing the balance among objectives is selected and the optimized parameters are determined. The present study is expected to help designers build optimized parallel tracking mechanism in an effective and efficient manner.

Pareto multi-objective optimization of tandem cold rolling settings for reductions and inter stand tensions using NSGA-II

IntroductionIn recent years, SMPMSM is quietly famous compared with other conventional motors in industrial applications due to higher efficiency, higher reliability, low cost, and smooth torque [1]–[3]. In general, several objective optimizations need to be consider, which required an optimization technique for an electrical motor. This paper deals with an optimal design of a surface-mounted permanent magnet synchronous machine (SMPMSM) with an exact analytical subdomain model by using a genetic algorithm method. To analyze the characteristic of permanent magnet (PM) motors, the classical optimization method, such as the finite element method (FEM), is intensively used. However, FEM has several time problems that require a longer computational time to evaluate the performance of PM motors. This problem can be overcome by using a genetic algorithm (GA) method combined with a subdomain model (SD), which developed an improved performance of SMPMSM, for instance, total harmonic distortion (THDv) and phase back-EMF. In this design, a three-phase 12-slot/8-pole PM motor is established with an exact SD model with radial magnetization patterns. Then, the GA ensemble with SD model to search the optimality of SMPMSM machine design. In the final analysis, the optimal new design of SMPMSM demonstrated by comparing with the initial design that is investigated by FEM. The result of induced back-EMF, and magnetic flux density of optimal design is compared with the initial design to show the advantages of GA optimization method.Analytical Model, Genetic Algorithm and Parameter of optimizationThe purpose of this analysis is to investigate the optimization design of a three-phase 12-slot/8-pole SMPMSM with a radial magnetization pattern. This optimization problem has been solved by obtains the minimum THDv as a fitness function. In order to process the optimization design of SMPMSM, several parameters need to be optimized i.e magnet pole-pitch, αp and slot-opening angle, boa. The roulette method is used to select the objective function of optimization with 50 maximum generations per iteration. The cross and mutation probability need to be set which requires linear and uniform recombination which is 0.89 and 0.025 respectively. The parameters of 12-slot/8-pole SMPM motor as follows: radius of the rotor, Rr = 23mm, the radius of PM surface Rm = 26mm, the inner radius of the stator Rsb = 42.5mm, axial length, la = 50mm, air-gap length, lg = 1mm, remanence of the magnet, Br, 1.12T, relative coil permeability, µr = 1.05 with the number of pole pairs, Np is 8 and number of stator slots, Ns is 12.The result, Discussion and ConclusionThe phase back electromotive force has a significant relationship with flux-linkage because phase back electromotive force is derived from the rate of change of flux-linkage. In Fig. 1. show the waveform of phase back electromotive force against rotor position of initial and optimal design in radial magnetization patterns. The initial design of phase back electromotive force waveform shows more trapezoidal compare with the optimal design which has a sinusoidal waveform. The comparison of total harmonic distortion between the initial and optimal design of SMPMSM are demonstrated in Fig. 2 below. The result from Fig.2. shows the highest total harmonic distortion of 12-slot/8-pole motor is an initial design which is 11.34% compared with the optimal design where 1.3%. The magnitude of harmonic in phase back electromotive force |En| of initial design shows 22.24 V compare to optimal design which is 17.4 V. This shows a good agreement that the optimal motor design gives lowest total harmonic distortion compare with the initial design. The optimizes of SMPMSM motor with the following parameters are given in Table 1. **

This work presents a study of the impact of the linearity assumption of the mechanical model in the overall performance of an energy harvesting piezoelectric beam. Also, a brief assessment of geometrical optimization solutions using different objective functions is presented. The mechanical model of the harvester is based on both linear and nonlinear variants of the electrical and mechanical constitutive equations for the piezoelectric material. The nonlinear elastic, damping and electromechanical coupling parameters are obtained via least squares identification using physical experimentation; the experimental tests are performed at different ground excitation accelerations. The computational optimization of the harvester is done using the genetic algorithm implemented in Matlab. Different objective functions are tested, i.e. broadband maximum peak power, maximum power at a particular frequency and broadband mean power; the influence of the selection of each of them in the total recovery of the power of the device is analyzed. The most suitable function to recover the vibratory energy from conventional transport vehicles is found.

Shape optimization in laminated composite plates

Design candidates obtained from optimization techniques may have meaningful information, which provides not only the best solution, but also a relationship between object functions and design variables. In particular, trade-off studies for optimum airfoil shape design involving various objectives and design variables require the effective analysis tool to take into account a complexity between objectives and design variables. In this study, for the multiple-conflicting objectives that need to be simultaneously fulfilled, the real-coded Adaptive Range Multi-Objective Genetic Algorithm code, which represents the global and stochastic multi-objective evolutionary algorithm, was developed for an airfoil shape design. Furthermore, the PARSEC method reflecting geometrical properties of airfoil is adopted to generate airfoil shapes. In addition, the Self-Organizing Maps, based on the neural network, are used to visualize trade-offs of a relationship between the objective function space and the design variable space obtained by evolutionary computation. The Self-Organizing Maps that can be considered as data mining of the engineering design generate clusters of object functions and design variables as an essential role of trade-off studies. The aerodynamic data for all candidate airfoils is obtained through Computational Fluid Dynamics. Lastly, the relationship between the maximum lift coefficient and maximum lift-to-drag ratio as object functions and 12 airfoil design parameters based on the PARSEC method is investigated using the Self-Organizing Maps method.