• Journal of the Korean GEO-environmental Society
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• v.23 no.12
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• pp.5-15
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• 2022

Conventionally, because evaluation methods of the bearing capacity for double steel pipe-concrete composite pile design have not been established, the conventional vertical bearing capacity equations for steel hollow pile are used. However, there are severe differences between the predictions from these equations, and the most conservative one among vertical bearing capacity predictions are conventionally adopted as a design value. Consequently, the current prediction method for vertical bearing capacity of composite pile prediction composite pile causes design reliability and economical feasibility to be low. This paper investigated mechanical behaviors of a new composite pile, with a cross-section composed of double steel pipes filled with concrete (DSCT), vertical bearing capacities were analyzed for several DSCT pile conditions. Axisymmetric finite element models for DSCT pile and surrounding ground were created and they were used to analyze effects on behaviors of DSCT pile pile by embedding depth, stiffness of plugging material at pile tip, height of plugging material at pile tip, and rockbed material. Additionally, results from conventional design prediction equations for vertical bearing capacity at steel hollow pile tip were compared with that from numerical results, and the use of the conventional equations for steel hollow pile was examined to apply to that for DSCT pile.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.275-287
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• 2017

During the feasibility study of new rail lines, maintenance cost of railway infrastructure has mostly been estimated based on the track length and on simplified parameters; however, the estimation reliability can be improved by employing the correction factor from UIC 715, as well as the line classification in UIC 714. The correlations between maintenance cost and various parameters such as weighted track length based on line classification, radius of curvature, gradient and worn -out rate have been analyzed according to the case studies. Prediction of the maintenance cost has been carried out using the cost data, which were representative of the whole cost data; as a result, it was demonstrated that a cost model based on the line classification and the correction factor was more reliable than the existing models. Furthermore, possibilities of using data from both the track measurement vehicle and from the maintenance information system, which are under development, have been investigated and, based on this investigation, a combined cost model using line classification, radius of curvature, gradient and worn-out rate, among other factors, will be proposed in the near future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.42-52
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• 2013

In this study, value of VMS (Variable Message Sign) traffic information is estimated by using CVM (Contingent Valuation Method), which is developed to quantify the value of non-marketable goods in environmental economics. CVM is used to estimate the value of goods provided by a project under consideration and then the project feasibility can be indirectly examined on the basis of the estimated value. This study focuses on estimating to estimate value of traffic information provided through VMS, a part of the transportation system enhancement project by Korea Expressway Corporation which is aimed at mitigating traffic problems on expressways. In particular, this study analyzes value of information separately by trip purpose, information type, and traffic flow condition. A state preference survey was designed to estimate the value of non-marketable traffic information. To maximize reliability of the survey results, a pilot survey was taken before the main survey. The open-ended question method was adopted in capturing users' willingness-to-pay. Both Tobit and binary Probit models were applied in estimating the value of VMS traffic information and their parameters were estimated using the maximum likelihood estimation. The estimation results suggests that the value of traffic information perceived by users is 518.28 KRW.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.