• ETRI Journal
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• v.43 no.2
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• pp.260-271
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• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• Advances in Computational Design
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• v.6 no.1
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• pp.31-42
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• 2021

This research aims to demonstrate the optimal geometrical design of splayed multiple cross-sectional pin fin heat sinks (SMCSPFHS), which are a type of side-inlet-side-outlet heat sink (SISOHS). The optimiser strength Pareto evolutionary algorithm2 (SPEA2)is employed to explore a set of Pareto optimalsolutions. Objective functions are the fan pumping power and junction temperature. Function evaluations can be accomplished using computational fluid dynamics(CFD) analysis. Design variablesinclude pin cross-sectional areas, the number of fins, fin pitch, thickness of heatsink base, inlet air speed, fin heights, and fin orientations with respect to the base. Design constraints are defined in such a way as to make a heat sink usable and easy to manufacture. The optimum results obtained from SPEA2 are compared with the straight pin fin design results obtained from hybrid population-based incremental learning and differential evolution (PBIL-DE), SPEA2, and an unrestricted population size evolutionary multiobjective optimisation algorithm (UPSEMOA). The results indicate that the splayed pin-fin design using SPEA2 issuperiorto those reported in the literature.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.171-171
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• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.196-203
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• 2022

The resource constrained scheduling problem (RCSP) constitutes one of the most challenging problems in Project Management, as it combines multiple parameters, contradicting objectives (project completion within certain deadlines, resource allocation within resource availability margins and with reduced fluctuations), strict constraints (precedence constraints between activities), while its complexity grows with the increase in the number of activities being executed. Due to the large solution space size, this work investigates the application of Genetic Algorithms to approximate the optimal resource alolocation and obtain optimal trade-offs between different project goals. This analysis uses the cost of exceeding the daily resource availability, the cost from the day-by-day resource movement in and out of the site and the cost for using resources day-by-day, to form the objective cost function. The model is applied in different case studies: 1 project consisting of 10 activities, 4 repetitive projects consisting of 40 activities in total and 16 repetitive projects consisting of 160 activities in total, in order to evaluate the effectiveness of the algorithm in different-size solution spaces and under alternative optimization criteria by examining the quality of the solution and the required computational time. The case studies 2 & 3 have been developed by building upon the recurrence of the unit/sub-project (10 activities), meaning that the initial problem is multiplied four and sixteen times respectively. The evaluation results indicate that the proposed model can efficiently provide reliable solutions with respect to the individual goals assigned in every case study regardless of the project scale.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• Water for future
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• v.18 no.4
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• pp.347-359
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• 1985

This study aims at the development of DP-Model for the establishment of monthly optimal operation policy of single multi-puppose reservoir by which the water demand of downstream can be satisfied under the various physical constraints. Series, A. B. C. of inflow are selected out of future monthly inflow data which are simulated form the past monthly average inflow of Andong dam site. the neight possible alternatives in each inflow series are established in order that Andong dam can supply the water demand of Nagdong main stream of 30% to 100%. Nextly, the reservoir rule curves is derived for each alternative by the detailed seguential analysis of stroage, future inflow and water demand based on the reservoir continuite equation. Then, and alternative which can satisfy the objective function of system based on the rule curves in the exteream is determined as an optimal operation policy from the application of developed DP=Model.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.111-116
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• 2008

The objective of this paper was to show the possibility of demand-controlled ventilation (DCV) using the current Korean ventilation standard for multi-purposed facilites. Two attractive DCV approaches; $CO_2$-DCV and RFID-DCV were applied to DCV simulations for a theoretical public assembly space served by a dedicated outdoor air system (DOAS) with enthalpy recovery device. A numerical model for predicting realtime occupant number, ventilation rate, and $CO_2$ concentration under given conditions was developed using a commercial equation solver program. It was found that the current ventilation standard causes unstable ventilation system control in DCV applications, especially under $CO_2$-DCV. It is because the ventilation rate (per person) used in Korea is the sum of the outdoor air required to remove or dilute air contaminants generated by both occupant and building itself, and not a pure function of occupant numbers. Finally, it makes DCV control unstable when ventilation flow is regulated only by the number of occupants. In order for solving this problem, current Korean ventilation standard was modified as a form of ASHRAE Standard 62.1-2007 showing good applicability to various DCV approaches. It was found that this modification enhances applicability of the current ventilation standard to DCV significantly.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.118-125
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• 2003

This paper presents a scheme for the placement of dispersed generator systems(DGs) based on load model in unbalanced systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm The method proposed is applied to IEEE 13 bus unbalanced distribution systems to demonstrate its effectiveness.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.77-84
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• 1999

Numerical design optimization techniques are implemented for the improvement of the ram accelerator performance. The design object is to find the minimum ram tube length required to accelerate projectile from initial velocity $V_0$ to target velocity $V_e$. The premixture is composed of $H_2,\;O_2,\;N_2$ and the mole numbers of these species are selected as design variables. The objective function and the constraints are linearized during the optimization process and gradient-based Simplex method and SLP(Sequential Linear Programming) have been employed. With the assumption of two dimensional inviscid flow for internal flow field, the analyses of the nonequilibrium chemical reactions for 8 steps 7 species lave been performed. To determined the tube length, ram tube internal flow field is assumed to be in a quasi-steady state and the flow velocity is divided into several subregions with equal interval. Hence the thrust coefficients and accelerations for corresponding subregions are obtained and integrated for the whole velocity region. With the proposed design optimization techniques, the total ram tube length had been reduced $19\%$ within 7 design iterations. This optimization procedure can be directly applied to the multi-stage, multi-premixture ram accelerator design optimization problems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.10
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• pp.868-875
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• 2007

In this paper, performance characteristics of a domestic kim-chi refrigerator are predicted by using the theoretical calculation and experimental method. The objective of this study is to find out the best design points of the refrigeration system and to calculate an adiabatic characteristic with variation to outdoor temperatures. The best design points such as refrigerant charge amount and capillary length were experimentally investigated. And the theoretical calculation is conducted as a function of calculation parameters and outdoor temperatures. According to this study results, the best design points of a refrigeration system with 2 rooms are 95 g of a refrigerant charge amount and 3500 / 3500 mm of capillary lengths and the best design points of a refrigeration system with 3 rooms are 100 g of a refrigerant charge amount and 3000/3000/6000mm of capillary lengths. And the power consumptions of both systems are 13.57 and 18.2 kWh/month. The worst part of heat loss is a front side of a domestic kim-chi refrigerator body.