• International conference on construction engineering and project management
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• 2024.07a
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• pp.1230-1237
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• 2024

Personalized learning is a critical factor in optimizing performance on construction sites. Traditional pedagogical methods often adhere to a one-size-fits-all approach, failing to provide the nuanced adaptation required to cater to diverse knowledge needs, roles, and learning preferences. While advancements in technology have led to improvements in personalized learning within construction education, the crucial connection between instructors' roles and training enviornment to personalized learning success remains largely unexplored. To address these gaps, this research proposes a novel learning approach utilizing multi-agent, context-specific AI agents within construction virtual environments. This study aims to pioneer an innovative approach leveraging the Large Language Model's capabilities with prompt engineering to make domain-specific conversations. Through the integration of AI-driven conversations in a realistic 3D environment, users will interact with domain-specific agents, receiving personalized safety guidance and information. The system's performance is assessed using the five evaluation criteria including learnability, interaction, communication, relevancy and visualization. The results revealed that the proposed approach has the potential to significantly enhance safety learning in the construction industry, which may lead to improve practices and reduction in accidents on diverse construction sites.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.209-215
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• 2024

Many developed countries, including Korea, are rapidly aged owing to years of use. Infrastructures such as roads, water, and sewage are Social Overhead Capital (SOC), which provide convenience to the nation and support national economic growth. Thus, continuous maintenance and investment are required because infrastructure deterioration is directly related to social effects, such as quality of life and safety. In addition, because infrastructure maintenance costs a lot of the budget, it is necessary to appropriate criteria for budget allocation, given assessing the condition of infrastructure. This study developed an Infrastructure Maintenance Map (IMM) based on a Geographic Information System (GIS) for infrastructure maintenance budgets and investment priorities. The IMM uses maintenance information for roads, bridges, water, and sewage, obtained from Bridge Management System (BMS), Pavement Management System (PMS) and facility data in South Korea. The IMM can calculate deterioration levels and maintenance costs of infrastructure repair methods. Maintenance priorities are also evaluated based on Multi-Attribute Utility Theory using the deterioration level, economic feasibility, and effect of facilities. This study contributes to easy decision-making regarding infrastructure investment priorities and maintenance budgeting to the status of facility on the 3D map by IMM.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.807-814
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• 2024

Urban road maintenance creates potential risks for both road users and workers in addition to traffic congestion and delays. The adverse effects of maintenance work could be minimized through mitigation measures of work zone layout and construction arrangement, such as reducing the dimension of work zone segments and scheduling construction during low-traffic periods. However, these measures inevitably escalate construction costs. Consequently, decision-making in urban road maintenance necessitates a balance among multiple strategic objectives to facilitate optimal development via a comprehensive road maintenance management system. This study aims to propose an integrated framework to accomplish the multiple and conflicting objectives for maximizing safety and mobility while minimizing construction costs by optimizing the work zone layout and construction sequence dynamically. The framework enables the seamless information exchange among building information modeling (BIM), geographic information system (GIS), and domain-specific computational engines (DCE), which perform interdisciplinary assessments and visualization. Subsequently, a genetic algorithm is employed to determine the optimal plan considering multiple objectives due to its versatility in resolving highly complex conflict problems.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.1
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• pp.119-130
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• 2018

The VE/LCC study on the existing multi-utility tunnel examined the economical feasibility of the collective area through the cost-benefit analysis of the ten major routes of Seoul for the benefit (7 items) and the cost (5 items) through quantitative methods. In this paper, we analyzed the economic efficiency of 61 sectors by adding 3 items (reduced traffic accident, reduced vehicle noise, social-economic loss). The reduced traffic accident item is an improvement of the traffic accident cost that can be saved by the implementation of the project, and the reduced vehicle noise item is an indicator of the amount of noise change caused by the implement of the business. Finally, the social-economic loss items represent the impact on the local economy due to the construction of the multi-utility tunnel. The amounts of the additional items were compared and items added in the open type and tunnel type multi-utility tunnel were analyzed for each analysis. Result on the analysis, it analyzed the items applied to the basic and detail models in the economic evaluation of the multi-utility tunnel design, and makes it possible to evaluate the economic efficiency more efficiently. The economic evaluation of the basic and detailed models including the items presented in this study will be often used in the design of the multi-utility tunnel design.

• Journal of Environmental Policy
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• v.8 no.2
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• pp.83-118
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• 2009

Clean Development Mechanism(CDM) projects under the Kyoto Protocol have two objectives. One is to assist the Parties included in Annex I in achieving compliance with their quantified emission limitation and reduction commitments in cost-effective ways by allowing them to implement emission reduction projects in Non-Annex I countries and receive CERs, which will offset their reduction commitments. The other is to assist Parties not included in Annex I in achieving sustainable development and technology transfers through investments by Annex I countries. However, in reality, it is said that the former objective is achievable but the latter is not. In this light, this article suggests sustainability appraisal criteria applicable for Korea. Among various methodologies, we used the 'multi-attributes utility theory(MAUT)'; one of the 'multi-criteria analysis (MCA)' methodologies judged to be the most practical and relevant. Based on the guidelines of the MAUT methodology, we identified sustainability criteria that meet the guidelines. We took two tracks, the first to find the preferences of Korean experts, and the other to check foreign cases. In all, 37 preliminary criteria were suggested to Korean experts and each criterion was scored, from between 1 and 3, in terms of relevance, possibility of real improvement, easiness of data collection, and preferences. We combined foreign cases and the results of a survey conducted in Korea and selected 12 core criteria and 10 additional criteria. After that, all the criteria were converted into indicators. The indicators were applied to a CDM project for case study. We chose the "Sihwa Tidal Power Project", which is currently the biggest tidal power plant in the world. Twelve core indicators and 3 additional indicators were applied. In order to weight each indicator, the 'analytical hierarchy process (AHP)' was used. A total of 30 experts were asked to suggest weights and 21 answered. Among them, only 14 respondents were proven to meet the consistency ratio. We analyzed the 14 responses through Expert Choice and the CDM project was scored (+)53.082. In addition, sensitivity analysis was undertaken with the result of (+)44.667 to (+)65.522. As a result of this study, it was proven that this project would contribute to the sustainable development of Korea.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.1-12
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• 2011

Large-sized multi-touch screen is usually made using infrared rays. That is because it has technical constraints or cost problems to make the screen with the other ways using such as existing resistive overlays, capacitive overlay, or acoustic wave. Using infrared rays to make multi-touch screen is easy, but is likely to have technical limits to be implemented. To make up for these technical problems, two other methods were suggested through Surface project, which is a next generation user-interface concept of Microsoft. One is Frustrated Total Internal Reflection (FTIR) which uses infrared cameras, the other is Diffuse Illumination (DI). FTIR and DI are easy to be implemented in large screens and are not influenced by the number of touch points. Although FTIR method has an advantage in detecting touch-points, it also has lots of disadvantages such as screen size limit, quality of the materials, the module for infrared LED arrays, and high consuming power. On the other hand, DI method has difficulty in detecting touch-points because of it's structural problems but makes it possible to solve the problem of FTIR. In this thesis, we study the algorithms for effectively correcting the distort phenomenon of optical lens, and image processing algorithms in order to solve the touch detecting problem of the original DI method. Moreover, we suggest calibration algorithms for improving the accuracy of multi-touch, and a new tracking technique for accurate movement and gesture of the touch device. To verify our approaches, we implemented a table-based multi touch screen.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.110-119
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• 2011

Global warming caused by excessive greenhouse gas emission is causing climate change all over the world. In Korea, greenhouse gas emission from residential buildings accounts for about 10% of gross domestic emission. Also, the number of deteriorated multi-family housing complexes is increasing. Therefore, the goal of this research is to establish the bases to manage energy consumption continuously and methodically during MR&R period of multi-family housings. The research process and methodologies are as follows. First, research team collected the data on project characteristics and energy consumption of multi-family housing complexes in Seoul. Second, an ontology-based breakdown structure was established with some primary characteristics affecting the energy consumption, which were selected by statistical analysis. Finally, a predictive model of energy consumption was developed based on the ontology-based breakdown structure, with application of CBR, ANN, MRA and GA. In this research, PASW (Predictive Analytics SoftWare) Statistics 18, Microsoft EXCEL, Protege 4.1 were utilized for data analysis and prediction. In future research, the model will be more continuous and methodical by developing the web-base system. And it has facility manager of government or local government, or multi-family housing complex make a decision with definite references regarding moderate energy consumption.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.101-109
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• 2011

As climate change is becoming the main issue, various efforts are focused on saving building energy consumption both at home and abroad. In particular, it is very important to save energy by maintenance, repair and rehabilitation of existing multi-family housing complex, because energy consumption in residential buildings is not only forming a great part of gross energy consumption in Korea but the number of deteriorated complexes is also sharply increasing. However, energy saving is not considered as a main factor in decision making on rehabilitation project. Also, any supporting tool is not appropriately prepared in existing process. As the first step for development of decision support system on rehabilitation, this paper developed a breakdown structure, which makes clusters of multi-family housing complexes. Decision tree, one of data mining methods, was used to make clusters based on the characteristics and energy consumption data of multi-family housing complexes. Energy saving and CO2 reduction will be maximized by considering energy consumption during rehabilitation process of multi-family housing complex, based on these results and following research.

• Fire Science and Engineering
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• v.27 no.2
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• pp.80-88
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• 2013

The validation of Fire Dynamics Simulator (FDS) was conducted for the under-ventilated fire in well-confined multi-compartments representative of nuclear power plant. Numerical results were compared with experimental data obtained by the OECD/NEA PRISME project. The effects of the numerical boundary conditions (B.C.) in ventilated system and the flame suppression model applied within FDS on the thermal and chemical environments inside the compartment were discussed in details. It was found that numerical B.C. on the vent flow resulting from over-pressure at ignition and under-pressure at extinction should be considered carefully in order to predict accurately the species concentrations rather than temperatures and heat fluxes inside the multi-compartment. The default information of suppression model applied within FDS resulted in artificial phenomena such as flame extinction and re-ignition, and thus the FDS results on the under-ventilated fire showed good agreement with the experimental results as the modified suppression criteria of the fuel used was adopted.

• Fire Science and Engineering
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• v.27 no.2
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• pp.31-39
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• 2013

The Fire Dynamics Simulator (FDS) has been applied to simulate a full-scale pool fire in well-confined and mechanically ventilated multi-compartments representative of nuclear power plant. The predictive performance of FDS was evaluated through a comparison of the numerical data with experimental data obtained by the OECD/NEA PRISME project. To identify clearly the FDS results regarding to the user-dependence in the process of FDS implementation except for the intrinsic limitation of FDS such as simple combustion model, only the over-ventilated fire condition was chosen. In particular, the importance of accurate boundary conditions (B.C.) in mechanically ventilated system were discussed in details. It was known from FDS results that the B.C. on inlet and outlet vents did significantly affect the thermal and chemical characteristics inside the compartments. Finally, it was confirmed that the FDS imposed an accurate ventilation B.C. provided qualitatively good agreement with temperatures, heat fluxes and concentrations measured inside the nuclear-type multi-compartments.