• International Journal of Fluid Machinery and Systems
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• v.5 no.3
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• pp.134-142
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• 2012

The competition to deliver ultra-low emitting vehicles at a reasonable cost is driving the automotive industry to invest significant manpower and test laboratory resources in the design optimization of increasingly complex exhaust after-treatment systems. Optimization can no longer be based on traditional approaches, which are intensive in hardware use and laboratory testing. The CFD is in high demand for the analysis and design in order to reduce developing cost and time consuming in experiments. This paper describes the development of a comprehensive practical model based on experiments for simulating the performance of automotive three-way catalytic converters, which are employed to reduce engine exhaust emissions. An experiment is conducted to measure species concentrations before and after catalytic converter for different loads on engine. The model simulates the emission system behavior by using an exhaust system heat conservation and catalyst chemical kinetic sub-model. CFD simulation is used to study the performance of automotive catalytic converter. The substrate is modeled as a porous media in FLUENT and the standard k-e model is used for turbulence. The flow pattern is changed from axial to radial by changing the substrate model inside the catalytic converter and the flow distribution and the conversion efficiency of CO, HC and NOx are achieved first, and the predictions are in good agreement with the experimental measurements. It is found that the conversion from axial to radial flow makes the catalytic converter more efficient. These studies help to understand better the performance of the catalytic converter in order to optimize the converter design.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.299-307
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• 2022

Harmony Search (HS) is a relatively recently developed meta-heuristic optimization algorithm, and various studies have been conducted on it. HS is based on the musician's improvisational performance, and the objective variables play the role of the instrument. However, each instrument is given only a sound range, and there is no concept of a scale that can be said to be the basis of music. In this study, the performance of the algorithm is improved by introducing a scale to the existing HS and quantizing the bandwidth. The introduced scale was applied to HM initialization instead of the existing method that was randomly initialized in the sound band. The quantization step can be set arbitrarily, and through this, a relatively large bandwidth is used at the beginning of the algorithm to improve the exploration of the algorithm, and a small bandwidth is used to improve the exploitation in the second half. Through the introduction of scale and bandwidth quantization, it was possible to reduce the algorithm performance deviation due to the initial value and improve the algorithm convergence speed and success rate compared to the existing HS. The results of this study were confirmed by comparing examples of optimization values for various functions with the conventional method. Specific comparative values were described in the simulation.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• Earthquakes and Structures
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• v.27 no.1
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• pp.1-15
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• 2024

In order to enhance the seismic performance of base-isolated structures on soft foundations, the hybrid system of base-isolated system (BIS) and shape memory alloy inerter (SMAI), referred to as BIS+SMAI, is for the first time here proposed. Considering the nonlinear hysteretic relationships of both the isolation layer and SMA, and soil-structure interaction (SSI), the equivalent linearized state space equation is established of the structure-BIS+SMAI system. The displacement variance based on the H₂ norm is then formulated for the structure with BIS+SMAI. Employing the particle swarm optimization, the optimization design methodology of BIS+SMAI is presented in the frequency domain. The evolvement rules of BIS+SMAI in the effectiveness, robustness, SMA driving force, inertia force, stroke, and damping enhancement effect are revealed in the frequency domain through changing the inerter-mass ratio, structural height, aspect ratio, and relative stiffness ratio between the soil and structure. Meanwhile, the validation of BIS+SMAI is conducted using real earthquake records. Results demonstrate that BIS+SMAI can effectively reduce the isolation layer displacement. The inerter can significantly increase the hysteretic displacement of SMA and thus enhance its energy dissipation capacity, implying that BIS+SMAI has better effectiveness than BIS+SMA. Although BIS+SMAI and BIS+ tuned inerter damper (TID) have practically the same effectiveness, BIS+SMAI has the lower optimum damping, significantly smaller inertia force, and higher robustness to perturbations of the optimum parameters. Therefore, BIS+SMAI can be used as a more engineering realizable hybrid system for enhancing the performance of base-isolated structures in soft soil areas.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.37-46
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• 1996

This paper proposes a cost-effective solution to the synonym problem of virtual caches. In the proposed solution, a minimal hardware addition guarantees the correctness whereas the software counterpart helps improve the performance. The key to this proposed solution is an addition of a small physically-indexed cache called U-cache. The U-cache maintains the reverse translation information of the cache blocks that belong to unaligned virtual pages only, where aligned measns that the lower bits of the virtual page number match those of the corresponding physical page number. The page alignment is a simple software optimization to improve the performance of the U-cche hardware. With the combination of both hardware and software, the proposed solution reduces the hardware costs and minimizes software modification and performance degradation. Performance evaluation base on ATUM traces shows that a U-cache, with only a few entries, performs almost as well as fully-configured hardware-based solution when more than 95% of the pages are aligned.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2483-2491
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• 2002

This study presents an efficient method for robust optimal design. In order to avoid the excessive evaluations of the exact performance functions, two-point diagonal quadratic approximation method is employed for approximating them during optimization process. This approximation method is one of the two point approximation methods. Therefore, the second order sensitivity information of the approximated performance functions are calculated by an analytical method. As a result, this enables one to avoid the expensive evaluations of the exact $2^{nd}$ derivatives of the performance functions unlike the conventional robust optimal design methods based on the gradient information. Finally, in order to show the numerical performance of the proposed method, one mathematical problem and two mechanical design problems are solved and their results are compared with those of the conventional methods.

• 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.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1108-1110
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• 2005

This paper presents a method for more efficient application of response surface methodology, one of the optimization methods, in optimal design of electrical devices. The proposed method is applied for improving torque performance of a prototype interior permanent magnet synchronous motor(IPMSM). In the end, the performance between the prototype and the optimized IPMSM is compared to verify usefulness of the method based on finite element analysis.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.589-594
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• 2004

In design of suspension system for KHST, it was applied the approximated optimization method using meta-models which called Response Surface Model and Neural Network Model for 29 design variables and 46 performance index. These models was coded using correlation between design variables and performance indices that is made by the 66 times iterative execution through the design of experimental table consisted orthogonal array L32 and D-Optimal design table. The results show that the optimization process is very efficient and simply applicable for complex mechanical system such as railway vehicle system. Also it was compared with the sensitivity of some design variables in order to know the characteristics of two models. This paper describes the general method for dynamic analysis and design process of railway vehicle system applied to KHST development, and proposed the efficient methods for vibration mode analysis process dealing with test data and the function based approximation method using meta-model applicable for a complex mechanical system. This method will be able to apply to the other railway vehicle system in oder to systematize and generalize the design process of railway vehicle dynamic system.