• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1969-1976
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then, a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs in other groups. The neural network model with back propagation algorithm is used, and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines for the design of environmentally conscious products in conceptual design phase.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.877-880
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• 2003

In a competitive and globalized business environment, the need for the green products becomes stronger. To meet these trends, the environmental assessment besides delivery, cost and quality of products should be considered as an important factor in new product development phase. In this paper. a knowledge-based approximate life cycle assessment system (KALCAS) for the collaborative design environment is developed to assess the environmental impacts in context of product concept development. It aims at improving the environmental efficiency of the product using artificial neural networks consisting of high-level product attributes and LCA results. The overall framework of the collaborative environment including KALCAS is proposed. This architecture uses the CO environment to allow users on a wide variety of platforms to access the product data and other related information. It enables us to trade-off the evaluation results between the objectives of the product development including the approximate environmental assessment in the collaborative design environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Structural Engineering and Mechanics
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• v.31 no.1
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• pp.11-24
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• 2009

In China, the oil and natural gas resources of Bohai Bay are mainly marginal oil fields. It is necessary to build both ice-resistant and economical offshore platforms. However, risk is involved in the design, construction, utilization, maintenance of offshore platforms as uncertain events may occur within the life-cycle of a platform under the extreme ice load. In this study, the optimum design model of the expected life-cycle cost for ice-resistant platforms based on cost-effectiveness criterion is proposed. Multiple performance demands of the structure, facilities and crew members, associated with the failure assessment criteria and evaluation functions of costs of construction, consequences of structural failure modes including damage, revenue loss, death and injury as well as discounting cost over time are considered. An efficient approximate method of the global reliability analysis for the offshore platforms is provided, which converts the implicit nonlinear performance function in the conventional reliability analysis to linear explicit one. The proposed life-cycle optimum design formula are applied to a typical ice-resistant platform in Bohai Bay, and the results demonstrate that the life-cycle cost-effective optimum design model is more rational compared to the conventional design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.4
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• pp.705-716
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• 2017

As many environmental pollution problems have arisen, various studies related to the environmental evaluation have been carried out in the construction industry. However, there is no methodology for estimating the environmental load quickly for design alternatives of civil facilities in the design phase. This study aim to establish criteria of works information and designed parts which can efficiently estimate environmental loads of PSC beam bridge based on standard quantity at the early design phase. For this purpose, a detailed environmental loads database was constructed by performing Life Cycle Assessment (LCA) based on detailed design data of 25 bridges. In addition, major work with high impact on environmental load were selected, and the analysis of characteristics of environmental load according to the required materials and 8 impact categories were conducted. As a result, the superstructure accounted for 42.91%. In the superstructure, remicon of the material base and PSC beam work occupied 53.13% and 31.25%. In the substructure, remicon, rebar, and cement, which are material base, accounted for more than 93%. It is expected that this major work and material information for each part of bridge can be utilized in the construction of the model, which can estimate the approximate environmental load, reflecting the characteristics of the structure in the design phase.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.676-693
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• 2016

Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.307-315
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• 2016

Many countries are trying to reduce a greenhouse gas to step up their fight against climate change. There are many studies related to building only for reducing a greenhouse gas in construction area but studies related to reducing a comprehensive environmental load including various pollutants that affects the global environment are lacking. This study aims to analyse the characteristics of environmental load by work type for tunnel projects. Analysis showed that seven work types, including lining concrete, shotcrete, tunnel portal and open-cut tunnel work, etc., are representative works generated environmental load. These seven works represent 89.22 percent of total environmental load. In addition, comparison results of environmental load per tunnel's length by work type showed that a major factor of environmental load is caused by a tunnel portal and open-cut tunnel work with relatively short length (excavation length). And lining concrete and shotcrete work are larger than any other environmental load with tunnel's total length. It is expected that the result of this study will be used to make a estimation model for environmental load using approximate quantity survey of representative work types in the early stage of tunnel design. And it will be play a considerable role in establishing of environment management plan for sustainable infrastructure construction.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.4
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• pp.270-279
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• 2012

In this study, greenhouse gas emissions occurring from the construction of Jangbogo Antarctic research station were estimated in terms of material production stages and building stages, respectively. In detail, greenhouse gas emissions during the building stages were estimated in terms of marine transportation, inland transportation, construction equipment utilization, and construction camp operation, respectively. As a result, greenhouse gas emissions from material production stages with life cycle assessment were 8,933 ton (as $CO_{2eq}$), equivalent to the 23.8% of total greenhouse gas emissions from the construction of Jangbogo Antarctic research station, and these results indicate that greenhouse gas emissions occurring from material production stages should not be ignored. During the building stages, greenhouse gas emissions occurring from first year were greater than those from second year due to the increase in fuel consumption of freighter during second year. Additionally, marine transportation compared to inland transportation, construction equipment utilization, and construction camp operation was found to be the greater contributor for greenhouse gas emissions during the building stages. The total greenhouse gas emissions estimated from both material production stages and building stages was 34,486 ton (as $CO_{2eq}$), and greater than those estimated from comprehensive environmental evaluation (CEE) of existing other research stations. This difference is mainly attributed from approximate estimation of greenhouse gas emissions of existing other research stations without considering material production stages.