• Korean Journal of Clinical Laboratory Science
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• v.47 no.3
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• pp.117-124
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• 2015

Mesenchymal stem cells (MSCs) are an attractive tool in tissue engineering as they have the required potential to treat injured articular cartilage. UV-exposed DTOPV (S-triazine bridged p-phenylene vinylene) is a biocompatible and fluorescent polymer with a hydrophilic surface. Previous studies have demonstrated that the surface wettability and hydrophilicity play critical roles in regulating cell adhesion and proliferation. The objective of this study was to improve the potential of in vitro MSC differentiation into Chondrocytes using DTOPV. MSCs were cultured on two different substrates: (1) tissue culture polystyrene (TCPS) as a reference and (2) UV-exposed and patterned DTOPV films. Chondrogenesis of MSCs was induced for two weeks on TCPS and DTOPV in the presence of an induction medium containing transforming growth factor (TGF)-${\beta}3$. Interestingly, the MSCs on TCPS adhered and spread, while those on DTOPV tended to form aggregates within several days. The cells cultured on DTOPV for two weeks had a round morphology, with stronger Safranine O staining of the extracellular matrix than that of the cells cultured on TCPS. Also, Type II collagen gene was significantly expressed in cells induced on DTOPV. These results indicate that chondrogenic differentiation of MSCs proceeds more rapidly on DTOPV than on TCPS. Therefore, in cartilage tissue engineering, DTOPV could be used to induce effective chondrogenic differentiation of MSCs.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Journal of Gastric Cancer
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• v.12 no.3
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• pp.149-155
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• 2012

Purpose: Although serosal invasion is a critical predisposing factor for peritoneal dissemination in advanced gastric cancer, the accuracy of preoperative assessment using routine imaging studies is unsatisfactory. This study was conducted to identify high-risk group for serosal invasion using preoperative factors in patients with advanced gastric cancer. Materials and Methods: We retrospectively analyzed clinicopathological features of 3,529 advanced gastric cancer patients with Borrmann type I/II/III who underwent gastrectomy at Korea Cancer Center Hospital between 1991 and 2005. We stratified patients into low-(${\leq}40%$), intermediate-(40~70%), and high-risk (>70%) groups, according to the probability of serosal invasion. Results: Borrmann type, size, longitudinal and circumferential location, and histology of tumors were independent risk factors for serosal invasion. Most tumors of whole stomach location or encircling type had serosal invasion, so they belonged to high-risk group. Patients were subdivided into 12 subgroups in combination of Borrmann type, size, and histology. A subgroup with Borrmann type II, large size (${\geq}7$ cm), and undifferentiated histology and 2 subgroups with Borrmann type III, large size, and regardless of histology belonged to high-risk group and corresponded to 25% of eligible patients. Conclusions: This study have documented high-risk group for serosal invasion using preoperative predictors. And risk stratification for serosal invasion through the combination with imaging studies may collaboratively improve the accuracy of preoperative assessment, reduce the number of eligible patients for further staging laparoscopy, and optimize therapeutic strategy for each individual patient prior to surgery.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.133-144
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• 2003

Horizontal consolidation characteristics of Busan marine clay were investigated by computing coefficient of horizontal consolidation from Piezocone data and comparing their results with those of standard consolidation test. It is well known that current prediction models of $c_h$ for high plastic soils have large uncertainties, and show a great difference between the predicted and the measured values. However, the spherical models and expanding cavity theory of Torstensson(1977), and Burns & Mayne(1998) based on modified Cam-Clay model with critical limit state concepts have relative reliability in estimating $c_h$ and good applicability in highly plasticity soils. In this paper, a normalization technique was used to evaluate $c_h$ using the Burns and Mayne's method based on the dissipation test, and their normalized consolidation curves give 0.015 of time factor($T_{50}$) when 50% degree of consolidation is completed. Comparison study using Piezocone data obtained at other similar ground site shows 1.5 times less systematicality than that of standard consolidation test, which indicates considerable approximation with the measured values because standard consolidation test gives the difference of three to few times compared with the measured values. In addition, design chart for estimating $c_h$ based on the chart from Robertson et al.(1992) and using the other method of the direct prediction from the of dissipation test was newly proposed. It is judged that new proposed chart is very applicable to Korean marine soils, especially in very high plastic soils.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.33-62
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• 2009

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

• Journal of the Korean Society of Radiology
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• v.7 no.2
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• pp.121-129
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• 2013

In this study measured patient exposure dose for purpose exposure area and peripheral critical organs by using optically stimulated luminescence dosimeters (OSLDs) from computed tomography (CT), based on the measurement results, we predicted the radiobiological effects, and would like to advised ways of reduction strategies. In order to experiment, OSLDs received calibration factor were attached at left and right lens, thyroid, field center, and sexual gland in human body standard phantom that is recommended in ICRP, and we simulated exposure dose of patients in same condition that equal exposure condition according to examination area. Average calibration factor of OSLDs were $1.0058{\pm}0.0074$. In case of left and right lens, equivalent dose was measure in 50.49 mGy in skull examination, 0.24 mGy in chest, under standard value in abdomen, lumbar spine and pelvis. In case of thyroid, equivalent dose was measured in 10.89 mGy in skull examination, 7.75 mGy in chest, 0.06 mGy in abdomen, under standard value in lumber spine and pelvis. In case of sexual gland, equivalent dose was measured in 21.98 mGy, 2.37 mGy in lumber spine, 6.29 mGy in abdomen, under standard value in skull examination. Reduction strategies about diagnosis reference level (DRL) in CT examination needed fair interpretation and institutional support recommending international organization. So, we met validity for minimize exposure of patients, systematize influence about exposure dose of patients and minimize unnecessary exposure of tissue.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.139-167
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• 2009

A new public insurance for long-term care was introduced in July 2008 to provide for the rising demand for long-term care as the population is aging rapidly. The demand for long-term care is expected to rise further because more and more elderly are living alone or in households with only other elderly, such as his/her spouse, without informal care of their adult children. Even when the elderly are living together with their adult children, daughters and daughters in law, once the main informal care-givers, are not available because they choose to become economically active and work more over time. Experiences of countries such as Japan and Germany with similar public long-term care insurance scheme highlight the importance of detailed analysis on the demand for long-term care for the financial stability of the insurance scheme. Countries which had underestimated the demand for long-term care at the time of adopting the scheme went through financial instability of insurance schemes. This study analyzes the determinants of the demand for long-term care using data from the second demonstration project (April 2006~April 2007) of the long-term care insurance scheme for the elderly in Korea. Taking full advantage of detailed data on the long-term care, this paper analyzes the eligibility for the long-term care insurance scheme and its use. According to study results, even when common diseases among the elderly such as cancer, diabetes, arthritis, dementia, hypertension, etc. are controlled together with other individual and socioeconomic factors, limitations the elderly are faced with in their twelve activities of daily living significantly affect the eligibility for the Korean Long-term Care Insurance Scheme. This means that limitations in daily living activities are more critical than common diseases among the elderly are to the eligibility for the Korean Long-term Care Insurance Scheme. Bathing and toileting problems have been found to be the most important factor affecting the eligibility for the insurance scheme, followed by eating, dressing and moving around inside the house. Moreover, the choices of whether to use long-term care and which to use between home care and institutional care are found to be significantly influenced by health status and various socioeconomic factors of the elderly. In particular, those with more limitations in daily living activities and the female elderly are more likely to use long-term care and institutional care rather than home care. As for home care users, those living alone or with adult children and those with monthly household income of more than 500,000 won are more likely to use home care. Most importantly, even when the monthly household income of the elderly is controlled, the elderly recipients of the National Basic Living Security, who are not charged for long-term care, are more likely to choose home care. This implies that price as well as income is a critical factor for the decision to use long-term care. Further study on the duration of long-term care use will surely enhance the long-term care policy, when panel data is available for simultaneous analysis of the likelihood of long-term care use and its use duration.

• Asian Oncology Nursing
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• v.8 no.1
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• pp.1-7
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• 2008

Purpose: Peripheral blood stem cell transplantation (PBSCT) has been widely used. The optimal time for collection is a critical factor to obtain proper counts of CD34 cell by peripheral blood stem cell collection (PBSC). The purpose of this study was to identify the factors influencing peripheral blood stem cell collection in order to figure out the more effective timing for PBSC. Method: The subjects of this study were 189 patients undergoing 3 leukapheresis from January 28, 2005 to December 31,2006. Group's characteristics, checkup opinion of pre-peripheral blood on the day of harvest & outcome of PBSC were analyzed and evaluated using SAS statistics program after grouping patients as below; group 1-CD34 cell counts $<2{\times}10^6/kg$ (n=97); group $2-2{\times}10^6/kg$ ${\leq}CD34$ cell counts $<4{\times}10^6/kg$ (n=26); group 3-CD34 cell counts ${\geq}4{\times}10^6/kg$ (n=63). Results: Based on outcome of peripheral blood stem cell according to diagnosis, acute myelocytic leukemia (AML) was 65.5% at Group 1, Lymphoma was 21.7% at Group 2 and multiple myeloma (MM) was 70.8% at Group 3. There were significant differences in CD34 cell counts according to diagnosis (p=0.00004). Type of cytokine mobilization according to diagnosis, Lenograsim was using 62.5% of MM & 38.2% of AML and filgrastim is using 22.0% of AML only. Circular peripheral blood CD34 cell counts prior to harvest was $258.1/{\mu}L$ at Group 3 which was much higher comparing to Group 1 ($10.5/{\mu}L$) and Group 2 ($39.9/{\mu}L$) (p<0.001). TNC counts of collected peripheral blood stem cell was $15.36{\times}10^6/kg$ at Group 3 and it's much higher than Group 2 ($13.16{\times}10^6/kg$) and Group 1 ($12.36{\times}10^6/kg$) (p=0.083). There was no significant difference in MNC counts inbetween 3 groups. Conclusions: Circular peripheral blood CD34+ cell counts prior to harvest was much higher at Group 3 than Group 1 and Group 2. Therefore, the number of CD34+ cells on the day of harvest can be used as an accurate predictor for peripheral blood stem cell.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.717-722
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• 2016

In this paper, in order to support the peak current limiting function depending on the intensity of the fault current at the early stage of failure, a two magnetically coupled type superconducting fault current limiter (SFCL) is proposed, which includes high-Tc superconducting (HTSC) element 1, where the existing primary and secondary coils are connected to one iron core in parallel, and HTSC element 2, which is connected to the tertiary winding using an additional iron core. The results of the experiments in this study confirmed that the two magnetic coupling type SFCL having coil 1 and coil 2 connected in parallel using dual iron cores is capable of having only HTSC element 1 support the burden of the peak current when a failure occurs. The reason for this is that although HTSC element 1 was quenched and malfunctioned because the instantaneous factor of the initial fault current was large, the current flowing to coil 3 did not exceed the critical current, which would otherwise cause HTSC element 2 to be quenched and not function. In order to limit the peak current upon fault through the sequential HTSC elements, the design should allow it to have the same value as the low value of coil 1 while having coil 3 possess a higher self-inductance value than coil 2. In addition, a short-circuit simulation experiment was conducted to examine and validate the current limiting and recovery characteristics of the SFCL when the winding ratio between coil 1 and coil 2 was 0.25. Through the analysis of the short-circuit tests, the current limiting and recovery characteristics in the case of the additive polarity winding was confirmed to be superior to that of the subtractive polarity winding.