• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.253-258
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• 2016

This paper proposes a method that utilizes optimization approach for localization of an indoor mobile robot. Bayesian filters which have been widely used for localization of a mobile robot use many control parameters to take the uncertainties in measurement and environment into account. The estimation performance depends on the selection of these parameter values. Also, the performance of the Bayesian filters deteriorate as the non-linearity of the motion and measurement increases. On the other hand, the optimization approach uses fewer control parameters and is less influenced by the non-linearity than the Bayesian methods. This paper compares the localization performance of the proposed method with the performance of the extended Kalman filter to verify the feasibility of the proposed method. Measurements of ranges from beacons of ultrasonic satellite to the robot are used for localization. Mahalanobis distance is used for detection and rejection of outlier in the measurements. The optimization method sets performance index as a function of the measured range values, and finds the optimized estimation of the location through iteration. The method can improve the localization performance and reduce the computation time in corporation with Bayesian filter which provides proper initial location for the iteration.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.953-960
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• 2020

This paper presents an optimization of gear web design used in a main gear train of an engine reduction gearbox for a rotorcraft. The optimization involves the minimization of a total weight, transmission error, misalignment, and face load distribution factor. In particular, three design variables such as a gear web thickness, location of rim-web connection, and location of shaft-web connection were set as design parameters. In the optimization process, web, rim and shaft of gears were converted from the 3D CAD geometry model to the finite element model, and then provided as input to the gear simulation program, MASTA. Lastly, NSGA-II optimization method was used to find the best combination of design parameters. As a result of the optimization, the total weight, transmission error, misalignment, face load distribution factor were all reduced, and the maximum stress was also shown to be a safe level, confirming that the overall gear performance was improved.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.131-138
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• 2004

Automatic flight control system (AFCS) for a low-cost unmanned aerial vehicle is described in this paper. Development process and block diagram of the AFCS are introduced. The flight control law for longitudinal and lateral channel autopilot is designed using optimization process. In this procedure, the performance index is composed of desired location of closed loop system poles and H$_2$norm of the resultant flight control system. This procedure is applied to the autopilot design of an unmanned target vehicle. Performance of the AFCS is evaluated by processor-in-the-loop simulation test and flight test. These results show that the AFCS has acceptable performance fur low cost UAV.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.10
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• pp.1048-1054
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• 2004

The Passive acoustic control is used in various fields, such as structures, automobiles, aircraft and so on. It is used in variety of acoustic field with the absorbing material, as one of the methods which can control the acoustic in optional space. In that case of passive control using this absorption material, it would be important to maximize the control performance of material property, numbers, geometry shape and the attached location of boundary area of the absorbing material. But realistically these variables, specially material Property, have no broad choice. Therefore, the position of absorbing material is the most important variable. In this study, we use the optimization method to minimize acoustic energy of optional space in the interest frequency attaching some absorbing materials to the boundary area. For analysis and optimization, this study uses the FEA and the conjugate gradient method. This optimization process is very efficient and useful in the passive acoustic control.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.261-273
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• 2022

Over the last decade, the scientific community has been actively developing technologies for automated software bug fixes called Automated Program Repair (APR). Several APR techniques have recently been proposed to effectively address multiple classroom programming errors. However, little attention has been paid to the advances in effective APR techniques for software bugs that are widely occurring during the software life cycle maintenance phase. To further enhance the concept of software testing and debugging, we recommend an optimized automated software repair approach based on hybrid technology (OAPR-HOML'1). The first contribution of the proposed OAPR-HOML'1 technique is to introduce an improved grasshopper optimization (IGO) algorithm for fault location identification in the given test projects. Then, we illustrate an opposition learning based artificial neural network (OL-ANN) technique to select AST node-level transformation schemas to create the sketches which provide automated program repair for those faulty projects. Finally, the OAPR-HOML'1 is evaluated using Defects4J benchmark and the performance is compared with the modern technologies number of bugs fixed, accuracy, precession, recall and F-measure.

• Journal of computational fluids engineering
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• v.17 no.2
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• pp.1-10
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• 2012

This paper presents the numerical simulation results of heat transfer and friction loss for a rotating two-pass duct with the airfoil-guide vanes in the turning region. The Kriging model is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of flow field and heat transfer with shear stress transport turbulent model. To improve the heat transfer performance, angle and location of the airfoil-guide vanes have been selected as design variables. The optimization problem has been defined as a minimization of the objective function, which is defined as a linear combination of heat transfer related term and friction loss related term with a weight factor. The airfoil-guide vanes in the turning region keep the high level of heat transfer while the friction loss has a low value. By comparing the presence or absence of airfoil-guide vanes, it is shown that the airfoil-guide vanes exhibited the best heat transfer performance to improve the blade cooling except the first passage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4665-4671
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• 2013

Engine mounting system is the most responsible system for NVH performance of vehicle. The vibration at idle shake, road shake, Key ON/OFF, gear shift tuned by the engine mount position and stiffness. Previously described Engine mounting system theory investigated and summarized in this paper. Decoupling of the Power train rigid mode and Reducing the angle between Torque-Roll-Axis and Elastic-roll-Axis is starting point of optimization. Multi-optimization analysis was performed because of variety simulation case and FE-model. Eventually, Find the best mount location and the stiffness has improved the performance of the vehicle NVH.