Optimal Design of a Steel Box Girder Bridge Considering Life Cycle Cost

신영석,박장호,하동호 대한토목학회 2009 KSCE JOURNAL OF CIVIL ENGINEERING Vol.13 No.6

Life cycle cost has come to occupy an important position in the design of bridges and many researchers have made an effort to develop cost models to take life cycle cost into account rationally. This paper derived load carrying capacity curves including repair and rehabilitation histories for members of bridge and performed optimal design of a steel box girder bridge consisting of concrete deck, steel box girders and piers considering life cycle cost. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, and user cost. The optimization method is applied to the design of bridge members with minimal value. The objective function is set to the annual cost, which is obtained by dividing the total life cycle cost by the service life, and constraints are formulated on the basis of Korean Standards. The optimal design is performed for various service lives and the effect of design factors is investigated. The results suggest that although it is not easy to consider various cost factors accurately, those cost factors which are affected by the various environmental conditions and uncertainties should be considered. Life cycle cost has come to occupy an important position in the design of bridges and many researchers have made an effort to develop cost models to take life cycle cost into account rationally. This paper derived load carrying capacity curves including repair and rehabilitation histories for members of bridge and performed optimal design of a steel box girder bridge consisting of concrete deck, steel box girders and piers considering life cycle cost. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, and user cost. The optimization method is applied to the design of bridge members with minimal value. The objective function is set to the annual cost, which is obtained by dividing the total life cycle cost by the service life, and constraints are formulated on the basis of Korean Standards. The optimal design is performed for various service lives and the effect of design factors is investigated. The results suggest that although it is not easy to consider various cost factors accurately, those cost factors which are affected by the various environmental conditions and uncertainties should be considered.

Cost-effective optimal design of a pump-and-treat system for remediating groundwater contaminant at an industrial complex

Yu-Chul Park 한국지질과학협의회 2016 Geosciences Journal Vol.20 No.6

Trichloroethylene (TCE) and other solvents are found as groundwater contaminants in industrial complexes. Pump-andtreat (PAT) systems are commonly selected for remediation, but have the disadvantages of long operation time and high cost. To reduce the remediation time and cost of PAT systems, a cost-effective optimal design was obtained with a simulation–optimization model. MODFLOW and MT3DMS were used for simulating groundwater flow and contaminant transport. A genetic algorithm was used for optimization, and a parallel computing technique was used for faster optimization. Cost-effective optimal design was achieved using two objective functions, which calculated the total remediation cost by means of installation, operational, and maintenance costs. Based on the restrictions in the study area, two remediation scenarios were examined. Scenario 1 involved the removal of TCE, and Scenario 2 involved the containment of TCE within the compliance line. The total remediation costs of scenario 2 were 77.4~90.4% of scenario 1. The remediation time decreased from 9.87 years in scenario 1 to 8.13 years in scenario 2. Sensitivity analysis determined the effects of installation, operational, and maintenance costs on the total remediation cost, showing that optimal total cost and remediation time were most affected by operational cost. A parallel computing technique using 40 networked slave processes increased optimization speed by 16.9 times. However, the efficiency of the parallel computing technique decreased as networking time increased.

Research on Dynamic Cost-Sensitive SVM Classifier based on Chaos Particle Swarm Optimization Algorithm

Ruili Zhang 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10

In order to improve the performance of Support Vector Machine (SVM) classifier for imbalanced data, this paper proposes dynamic cost-sensitive SVM classifier based on chaos particle swarm optimization (CPDC_SVM). Firstly, this paper introduces dynamic cost-sensitive thought to SVM classifier, and gives the method for structuring dynamic cost and cost-sensitive SVM model. Secondly, we propose the evaluation methodology performance for classifier, and adopts decimal base to code the particles. At last, chaos thought is introduced in particle swarm optimization algorithm, and the Algorithm of the dynamic cost-sensitive SVM classifier is given, which improves convergent speed and accuracy of particle swarm optimization, and can optimize dynamic cost-sensitive SVM well, so CPDC_SVM adds effectively the convergence speed and accuracy for the particle swarm optimization algorithm. Experimental results show CPDC_SVM has higher precision than traditional SVM classifier, and dynamic cost and chaos particle swarm optimization can improve the performance for classifier.

교량의 생애주기비용 최적설계

박장호,신영석 한국안전학회 2010 한국안전학회지 Vol.25 No.6

The importance of the life cycle cost (LCC) analysis for bridges has been recognized over the last decade. However, it is difficult to predict LCC precisely since the costs occurring throughout the service life of the bridge depend on various parameters such as design, construction, maintenance, and environmental conditions. This paper presents a methodology for the optimal life cycle cost design of a bridge. Total LCC for the service life is calculated as the sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, user cost, and disposal cost. The optimization method is applied to design of a bridge structure with minimal cost, in which the objective function is set to LCC and constraints are formulated on the basis of Korean Bridge Design Code. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on damage probabilities to consider the uncertainty of load and resistance. Repair and rehabilitation cost is determined using load carrying capacity curves and user cost includes traffic operation costs and time delay costs. The optimal life cycle cost design of a bridge is performed and the effects of parameters are investigated

Cost and Efficiency Optimizations of ZnO/EG Nanofluids Using Non-dominated Sorting Genetic Algorithm Coupled with a Statistical Method

Esfe Mohammad Hemmat,Hajmohammad Hadi,Motallebi Seyed Majid,Toghraie Davood 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.1

In this study, optimization of ZnO/EG nanofl uids was investigated to increase effi ciency and reduce costs. To determine the effi ciency of nanofl uid, the defi nition of Mouromtseff number was used. The cost of nanofl uid in terms of the volume fraction of nanoparticles ( φ ) was determined. Then, Mouromtseff functions and costs were calculated by response surface methodology (RSM) with regression up to 96%. To determine the minimum cost and maximum effi ciency in terms of Mouromtseff number, a non-dominated sorting genetic algorithm (NSGA II) which is powerful in achieving optimal response was employed. In the end, the Pareto front, optimal values of Mouromtseff , and the minimum corresponding cost were obtained. Also, for achieving an optimal pattern of minimum cost in terms of maximum thermal effi ciency, a suitable correlation was presented. The results show that to achieve maximum thermal effi ciency, the minimum cost is $ 360 per liter and also the minimum cost to achieve the optimal effi ciency coeffi cient is in φ = 0.5%. Nanofl uid optimization can also reduce nanofl uid costs by up to 10%.

Resource-Constrained Time-Cost Tradeoff for Repetitive Construction Projects

Gholamreza Heravi,Saeed Moridi 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.8

The time-cost tradeoff problem is to find optimal combinations of construction options with the objective of minimizing project time and cost. In order to search for such a set of optimal solutions, the total time and cost of projects needs to be calculated properly. In repetitive construction projects (RCPs), due to division of work into several units and involvement of many resources for activities completion, scheduling is unique and more complicated. Scheduling method in this paper besides addressing common constraints such as precedence relationships, required lead time and lag distance between activities, enables project managers to consider all resources and their shortages in scheduling. To raise the practicality of model, in addition to direct and indirect costs, resource idle cost is considered as a cost element in estimating total cost of project. The time variant multi-objective particle swarm optimization is applied to find non-dominated solutions on the basis of minimizing time and cost of project. An application example is presented at the end to illustrate the performance of the model. This research presents a resource-constrained time-cost tradeoff model to find the optimal set of crew combinations for project activities in RCPs, considering time and cost simultaneously.

Calculating Wind Variability Costs with Considering Ramping Costs of Conventional Power Plants

Xuemei Dai,Kaifeng Zhang,Jian Geng,Ying Wang,Kun Yuan 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.3

Due to the variability of the wind power, conventional power plants are required to ramp more frequently to mitigate the imbalance of generation and supply, which increase the total cost of power systems. The increase of the cost is termed the “variability cost” of wind power. Generally, it includes the additional ramping cost, reserve cost and fuel cost of conventional plants. In this paper, we propose an alternative scenario construction method to calculate the “variability cost” of wind power from the viewpoint of the power system schedule. Firstly, in the alternative scenario, a new energy proxy with zero wind variability costs is constructed. Then, a unit commitment optimization model considering ramping costs is developed. The operation costs of power systems under two scenarios (alternative one and real one) are calculated and the diff erence between two costs is the variability cost. Furthermore, we apply the proposed method to calculate the variability costs of the wind farm cluster. The simulations show that the variability cost increases with higher penetration and higher variability of wind power. Meanwhile, it is found that the variability cost of the wind farm cluster as a whole is lower than the sum of variability costs of each wind farm.

Multi-objective energy-cost design optimization for the variable-speed wind turbine at high-altitude sites

Song, Dongran,Liu, Junbo,Yang, Jian,Su, Mei,Yang, Sheng,Yang, Xuebing,Joo, Young Hoon Elsevier 2019 Energy conversion and management Vol.196 No.-

<P><B>Abstract</B></P> <P>As the development of wind power utilization, onshore wind turbines have been installed at various sites with different altitudes. Although the site-specific design is an effective way to reduce the levelized energy cost of the wind turbines, the influence of the site altitude on the energy cost is not considered in the existing site-specific designs. To fill the knowledge gap, this study presents the site-specific design optimization of the wind turbines at the high-altitude sites, based on a multi-objective trade-off between maximization of the energy production and minimization of the production cost. For this purpose, two improved estimation models of the annual energy production and the annual production cost are firstly introduced for the high-altitude wind turbines. On this basis, the multi-objective energy-cost optimization problem is formulated as two nonlinear functions relevant to two key designed parameters: the rated power and the rotor radius. After that, a multi-objective particle swarm optimization method is proposed. Finally, the proposed method is applied to the Huitengxile and Maanshan wind farms, located in Inner Mongolia and Yunnan-Kweichow plateaus of China, respectively. The results show that the energy cost has been noticeably increased by about 15% and 18% in the two applications comparing with the results ignoring the site altitude. Moreover, a trade-off between various alternative energy-cost solutions has been provided by the generated set of the optimally designed parameters. Thus, a two-step criterion has been proposed to help the turbine designers select the designed parameters according to their preference.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Multi-objective optimization for the site-specific turbine design. </LI> <LI> Improved energy and cost estimations for the high-altitude wind turbine. </LI> <LI> Proposed method applied to two high-altitude wind farms. </LI> <LI> Trade-off results between the energy and the cost in the two applications. </LI> <LI> Novel two-step criterion for selecting the optimally designed parameters. </LI> </UL> </P>

에너지 시스템에 대한 성능 및 비용의 최적화 수식

김덕진(Deok-Jin Kim) 대한설비공학회 2010 대한설비공학회 학술발표대회논문집 Vol.2010 No.6

Thermoeconomics, or exergoeconomics, can be classified into the three fields: cost allocation, cost optimization, and cost analysis. In this study, a new cost optimization methodology for energy systems is proposed. Conventional optimization formula can accomplish only cost or only performance. However, the proposed formula can accomplish the cost and performance at the same time. The formula is composed of fuel cost, capital cost, and overall system efficiency, which is very simple and clear. That is, the number of the proposed equation is only one, and it is developed with a wonergy newly introduced in this paper. The wonergy is defined as an energy that can equally evaluate the worth of each product. Any energy, including enthalpy or exergy, can be applied to the wonergy and be evaluated by this equation. To confirm its validity, the optimization of the CGAM problem was analyzed. Exergy is generally recognized as the most reasonable criterion in exergoeconomics. From the results of optimization using the suggested formula, however, both of exergy and enthalpy were reasonable. Therefore, we conclude that various forms of wonergy should be applied to the analysis of optimization.

Particle Swarm Optimization을 이용한 공기-비용 절충관계 최적화 모델에 관한 연구

박우열,안성훈 한국건축시공학회 2008 한국건축시공학회지 Vol.8 No.6

It is time-consuming and difficulty to solve the time-cost trade-off problems, as there are trade-offs between time and cost to complete the activities in construction projects and this problems do not have unique solutions. Typically, heuristic methods, mathematical models and GA models has been used to solve this problems. As heuristic methods and mathematical models are have weakness in solving the time-cost trade-off problems, GA based model has been studied widely in recent. This paper suggests the time-cost trade-off optimization algorithm using particle swarm optimization. The traditional particle swarm optimization model is modified to generate optimal tradeoffs among construction time and cost efficiently. An application example is analyzed to illustrate the use of the suggested algorithm and demonstrate its capabilities in generating optimal tradeoffs among construction time and cost. Future applications of the model are suggested in the conclusion