• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.6
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• pp.477-485
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• 2012

Geometric configurations such as hull shape, wall thickness, stiffener layout, and type of construction materials are the key factors influencing the structural performance of pressure hulls. Traditional theoretical approach provides quick and acceptable solutions for the design of pressure hulls within specific geometric configuration and material. In this paper, alternative approaches that can be used to obtain optimal geometric shape, wall thickness, construction material configuration and stiffener layout of a pressure hull are presented. CAE(Computer Aided Engineering) based design optimization tools are utilized in order to obtain the required structural responses and optimal design parameters. Optimal elliptical meridional profile is determined for a cylindrical pressure hull design using metamodel-based optimization technique implemented in a fully-integrated parametric modeler-CAE platform in ANSYS. While the optimal composite laminate layup and the design of ring stiffener for a thin-walled pressure hull are obtained using gradient-based optimization method in OptiStruct. It is noted that the proposed alternative approaches are potentially effective for pressure hull design.

• Journal of Biosystems Engineering
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• v.23 no.3
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• pp.219-228
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• 1998

This study was conducted to develop the mathematical model and computer simulation program(TPPMTV98) for predicting the tractive performance of tracked vehicles. It takes into account major design parameters of the vehicle as well as the pressure-sinkage and shearing characteristics of the soil, and the response of the soil to repetitive loading. Structural analysis and numerical iterative method were used for the derivation of mathematical model. The simulatiom model TPPMTV98 can predict the ground pressure distribution and the shear stress under a track, the motion resistance, the tractive effort and the drawbar pull of the vehicles as functions of slip. Predicted tractive performance results obtained by the simulation model were validated by comparing the results firm the Wong's model, the offectiveness of Wong's model validated by many of the experiment. It was found that there is fairy close agreement between the prediction by TPPMTV98 and the results from Wong's model. The computer simulation model TPPMTV98 can be used for the optimization of tracked vehicle design or for the evaluation of vehicle candidates for a given mission and environment.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.493-493
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• 2009

Recently, small vertical axis wind turbine attracts attention because of its clean, renewable and abundant energy resources to develop. Therefore, a cross-flow type wind turbine is proposed for small wind turbine development in this study because the turbine has relatively simple structure and high possibility of applying to small wind turbine. The purpose of this study is to investigate the effect of the turbine‘s structural configuration on the performance and internal flow characteristics of the cross-flow turbine model using CFD analysis. The results show that guide nozzle should be adopted to improve the performance of the turbine. Optimization of the nozzle shape will be key-importance for the high performance of the turbine.

• Earthquakes and Structures
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• v.1 no.3
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• pp.307-326
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• 2010

This paper is concerned with the optimal seismic design of added viscous dampers in yielding plane frames. The total added damping is minimized for allowable values of local performance indices under the excitation of an ensemble of ground motions in both regular and irregular structures. The local performance indices are taken as the maximal inter-story drift of each story and/or the normalized hysteretic energy dissipated at each of the plastic hinges. Gradients of the constraints with respect to the design variables (damping coefficients) are derived, via optimal control theory, to enable an efficient first order optimization scheme to be used for the solution of the problem. An example of a ten story three bay frame is presented. This example reveals the following 'fully stressed characteristics' of the optimal solution: damping is assigned only to stories for which the local performance index has reached the allowable value. This may enable the application of efficient and practical analysis/redesign type methods for the optimal design of viscous dampers in yielding plane frames.

• International Journal of High-Rise Buildings
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• v.2 no.2
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• pp.141-152
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• 2013

This paper presents a brief overview of the recently developed performance-control method of moment frame design subjected to monotonously increasing lateral loading. The final product of any elastic-plastic analysis is a nonlinear loaddisplacement diagram associated with a progressive failure mechanism, which may or may not be as desirable as expected. Analytically derived failure mechanisms may include such undesirable features as soft story failure, partial failure modes, overcollapse, etc. The problem is compounded if any kind of performance control, e.g., drift optimization, material savings or integrity assessment is also involved. However, there is no reason why the process can not be reversed by first selecting a desirable collapse mechanism, then working backwards to select members that would lead to the desired outcome. This article provides an overview of the newly developed Performance control methodology of design for lateral resisting frameworks with a view towards integrity control and prevention of premature failure due to propagation of plasticity and progressive P-delta effects.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1842-1850
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• 2017

Reducing the noise and vibration of the BLDC motors is very essential for some special applications. In this paper, a new structural design is introduced to increase the natural frequencies of the stator in BLDC motors as increasing the natural frequencies can reduce the severe effects of the structural resonances, including high levels of noise and vibration. The design is based on placing a single hole on definite regions at the stator cross sectional area (each region contains one tooth and its upper parts in the stator yoke) in an optimum way by which the natural frequencies at different modes are shifted to the higher values. The optimum diameter and locations for the holes are extracted by the Response Surface Methodology (RSM) and the modal analyses in the iterative process are done by Finite Element Method (FEM). Moreover, the motor performance by the optimum stator structure is analyzed by FEM and compared with the prototype motor. Preventing the stator magnetic saturation and the motor cogging torque enhancement are the two constraints of the optimization problem. The optimal structural design method is applied experimentally and the validity of the design method is confirmed by the simulated and experimental results.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.10-22
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• 2008

In an automotive body structure, a design configuration that fulfills structural requirements such as deflection, stiffness and strength is necessary for structural design and is composed of various components. The integrated design is used to obtain a minimum weight structure with optimal or feasible performance based on conflicting constraints and boundaries. The mechanical design must begin with the definition of one or more concepts for structure and specification requirements in a given application environment. Structural optimization is then introduced as an integral part of the product design and used to yield a superior design to the conventional linear one. Although finite element analysis has been firmly established and extensively used in the past, geometric and material nonlinear analyses have also received considerable attention over the past decades. Also, nonlinear analysis may be useful in the area of structural designs where instability phenomena can include critical design criteria such as plastic strain and residual deformation. This proposed approach can be used for complicated structural analysis for an integrated design process with the nonlinear feasible local flexibilities between system and subsystems.

• Smart Structures and Systems
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• v.5 no.1
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• pp.1-21
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• 2009

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

• Smart Structures and Systems
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• v.14 no.1
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• pp.17-37
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• 2014

In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.183-194
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• 2005

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the gHFNNs results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). In this tandem, a FNN supports the formation of the premise part of the rule-based structure of the gHFNN. The consequence part of the gHFNN is designed using PNNs. We distinguish between two types of the linear fuzzy inference rule-based FNN structures showing how this taxonomy depends upon the type of a fuzzy partition of input variables. As to the consequence part of the gHFNN, the development of the PNN dwells on two general optimization mechanisms: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gHFNN, the models are experimented with a representative numerical example. A comparative analysis demonstrates that the proposed gHFNN come with higher accuracy as well as superb predictive capabilities when comparing with other neurofuzzy models.