• Journal of the Korea Institute of Building Construction
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• v.8 no.6
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• pp.91-98
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• 2008

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.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.53-62
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• 2015

Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.

• Korean Journal of Construction Engineering and Management
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• v.11 no.2
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• pp.94-105
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• 2010

Recently, resettlement problems of low income groups in the urban regeneration area have been issued in Korea because they have no capability to purchase (or lease) redeveloped housing (or apartment). There are several approaches for supplying affordable housing and one of these is the bidding system which can reduce construction cost. However, the lowest bidding system has many problems such as dumping and substandard quality. In this context, this study proposed bidding system based on technical proposal applying the concept of the lowest total combined bid price for optimization of bid price, reduction of construction cost and period, and maintenance of suitable quality. This bidding system embraces the best value and cost plus time concept on the basis of an improved lowest price bidding system. It consists of the following components: work unit based, project unit based, and period reducing technical proposals. The proposed bidding system for determining bidders are designed to evaluate the adequacy of each technical proposal in the order of the combined minimum price in an effort to effectively optimize bid prices and reduce the construction periods, as well as to maintain a minimum appropriate quality.

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.85-95
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• 2024

Direct air capture (DAC) technology plays a crucial role in mitigating climate change. Reports from the International Energy Agency and climate change emphasize its significance, aiming to limit global warming to 1.5 ℃ despite continuous carbon emissions. Despite initial costs, DAC technology demonstrates potential for cost reductions through research and development, operational learning, and economies of scale. Recent advancements in high-permeance polymer membranes indicate the potential of membrane-based DAC technology. However, effective separation of CO₂ from ambient air requires membranes with high selectivity and permeability to CO₂. Current research is focusing on membrane optimization to enhance CO₂ capture efficiency. This study underscores the importance of direct air capture, evolving cost trends, and the pivotal role of membrane development in climate change mitigation efforts. Additionally, this research delved into the theoretical background, conditions, composition, advantages, and disadvantages of permeance and selectivity in membrane-based DAC.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.43-51
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• 2016

Recently, the cost of construction projects has escalated due to a significant increase in size and complexity. Many construction projects have failed to meet their originally intended project deadline due to various factors such as weather, labor supply, equipment, procurement, accidents, etc. Consequently, emergency construction work scenario has to be implemented in order to shorten the duration and satisfy the original estimated schedule. However, many critical decisions in emergency scenario rely solely on the experience of a construction manager. Thus, this paper proposes TCTO optimization model to decide the most effective alternative out of various working scenarios which are generated by the combination of work group and work time. The developed TCTO model provides the optimum schedule that satisfies the practical constraints. Future research could involve the integration of resource leveling with the proposed model. This would make the model more versatile.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.89-94
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• 2021

Recently, manufacturing companies are introducing many intelligent production processes that apply IIoT/ICT to improve competitiveness, and a system that maintains availability, improves productivity, and optimizes management costs is needed as a preventive measure using environmental data generated from air ejectors. Therefore, in this study, a dedicated control board was developed and LoRa communication module was applied to remotely control it to collect and manage information about compressors from cloud servers and to ensure that all operators and administrators utilize common data in real time. This dramatically reduced M/S steps, increased system operational availability, and reduced local server operational burden. It dramatically reduced maintenance latency by sharing system failure conditions and dramatically improved cost and space problems by providing real-time status detection through wired and mobile utilization by maintenance personnel.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.289-296
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• 2021

The Korean construction industry has been implementing G-SEED, a certification system that evaluates the environmental properties of buildings for the purpose of reducing environmental burdens such as energy and resource consumption and pollutant emissions. Also, creating a pleasant environment in general is one more purpose of G-SEED certification system. However, G-SEED certification in practice is difficult and time consuming due to the complexity of the certification acquisition process coupled with little economic consideration for the materials of each certification item. Therefore, in this study, we present a model for the optimal selection of materials and economic assessment using a genetic algorithm. The development of the model involves building a material database based on life-cycle costing (LCC) targeted at "Application of Indoor Air Pollutant Low Emission Material" from G-SEED. Next, the model was validated using a real non-residential building case study. The result shows an average cost reduction rate of 74.5 % compared with the existing cost. This model is expected to be used as an economically efficient tool in G-SEED.

• Korean Chemical Engineering Research
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• v.43 no.2
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• pp.222-229
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• 2005

Five stage enriching membrane system for separating combustion gas (air 90%, $CO_2$ 10%) was proposed and simulated by using Aspen plus and Excel. The system recovers 90% $CO_2$ of the combustion gas and the purity of $CO_2$ recovered was more than 99%. Optimization yields a reduction in membrane area as well as operating and capital cost. Retentate concentration and permeate pressure of each stage were chosen as optimization variables. By analyzing the optimization results, we derived several design guide lines for the enriching membrane system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.117-118
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• 2015

These days buildings have more possibilities to occur construction delay as many variables and risks are inherent in them due to the enlargement and complexity. When a project is delayed, it generates extra working expenses and this causes a dispute between the employer and the constructor. Most construction sites conduct emergency construction work to recover the delay of the project duration. When an emergency construction is carried out in the actual construction site, it's necessary to utilize and distribute the proper working groups based on the procedure of successor and predecessor. Many constructions, however, have been going only with more number of work forces and working time. This study suggests a process management optimization plan with an application of emergency construction scenario by using linear programing.

• Korean Chemical Engineering Research
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• v.56 no.5
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• pp.647-654
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• 2018

In order to solve the global warming and reduce greenhouse gas emissions, it has been developed the $CO_2$ capture technology by oxy-fuel combustion. But there is a problem that the economic efficiency is low because the oxygen production cost is high. ASU (Air Separation Unit) is known to be most suitable method for producing large capacity of oxygen (>2,000 tpd). But most of them are optimized for high purity (>99.5%) oxygen production. If the ASU process is optimized for low purity(90~97%) oxygen producing, it is possible to reduce the production cost of oxygen by improving the process efficiency. In this study, the process analysis and comparative evaluation was conducted for developing large capacity ASU for oxy-fuel combustion. The process efficiency was evaluated by calculating the recovery rate and power consumption according to the oxygen purity using the AspenHysys. As a result, it confirmed that the optimal purity of oxygen for oxyfuel combustion is 95%, and the power consumption can be reduced by process optimization to 12~18%.