• 콘크리트학회지
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• 제9권1호
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• pp.44-59
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• 1997

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2000년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2000
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• pp.341-347
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• 2000

Even for the same structure, the analysis results as well as design values might have differences depending on the selected analysis model. Therefore it is desirable to determin model considering the required accuracy of the analysis results, the given time restried economy. " Standard Specification for Roadway Bridges" Division V, Seismic Design prove "Single Mode Spectral Analysis Method" as the basic analysis method for the earthquake design of roadway bridges classified as "regular". In this study a 5 span steel box girl selected which satisfies the regularity and the applicability of the provided analysis simplified model in checked. For the comparision of the analysis results, "Multi-Mode Spect Method" is used with a detailed model.hod" is used with a detailed model.odel.

• 대한교통학회지
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• 제28권3호
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• pp.131-143
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• 2010

본 연구에서는 지방부 2차로 도로구간에 대한 사고예측계수를 개발하고자 하였으며, 사고예측계수(AMF)는 설계 안전성 평가시 도로구간의 기하구조적요인, 운영적 요인 등 개별 요소가 사고빈도에 미치는 영향을 반영하는 계수이다. 개발한 지방부 2차로 도로의 사고예측계수항목은 기존문헌과 모형을 통해 횡단보도와 진출입구의 밀도, 지형(산악지), 토지이용도(주거), 중앙분리대의 설치여부로 결정되었다. 사고예측계수의 개발은 모형을 이용한 방법을 채택하였으며 산출된 값에 대해서는 전문가 평가를 통하여 항목의 적정성을 평가하고, AMF의 예측력, 국내도로 특성 반영도 등 두 가지 측면에서 적용성 평가를 수행하였으며 국외의 AMF를 적용했을 시와 비교분석하여 평가하였다. 전문가를 통한 적정성에 대한 평가에서는 개발된 계수의 항목이 전반적으로 적정한 것으로 평가되었으나 토지이용도의 주거 항목의 값에 대하여 과대 예측하는 결과를 유발 할 수 있을 것으로 평가되었다. 한편, 국외의 사고예측계수 및 실제사고와의 비교분석결과는 전체 예측빈도로 판단한 결과, 미국에서 개발 중인 IHSDM과 본 연구의 결과가 실제에 가장 근접하는 것으로 나타났으며 미국 텍사스 RSDS의 값은 전반적으로 결과를 과대 예측하는 것으로 나타났다. 또한 실제 사고발생위험도가 높은 도로구간에 대한 예측은 본 연구의 계수 값을 적용하는 경우 반영도가 더 좋은 것으로 나타났다.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 1997년도 춘계 학술발표회 논문집 Proceedings of EESK Conference-Fall 1997
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• pp.101-106
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• 1997

In order to check the safety against earthquakes a seismic design of an arch bridge is carried out in this study according to the Division V (Seismic Design) of the "Standard for the Roadway Bridges", where the application procedures including the determination of coefficients, the analysis method as well as the safety checks are provided. provided.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2005년도 춘계 학술발표회 논문집
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• pp.475-482
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• 2005

Many public facilities including roadway, railway, and embedded pipe lines in this country have been damaged by the repeated freezing and thawing of the soil during winter and spring every year. However, there are only few research results in field of frozen ground in this country. Also, there are no the formulation of the reasonable equation for frost penetration depths and of the criterion for identifing potentially frost-susceptible soil in design manual of pavement yet. Through this study it is anticipated to asses the frost action problem in roadway, railway, and water suppply lines and to establish the design criterion about pavement in seasonal cold region.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2008년도 제7회 추계학술대회 및 정기총회
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• pp.309-310
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• 2008

• 지반과기술
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• 제4권2호
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• pp.37-46
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• 2007

• Steel and Composite Structures
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• 제39권1호
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• pp.21-33
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• 2021

This paper aims to improve the current state-of-the-art in long-term deflection prediction in steel-concrete composite beams. The efficiency of a time-dependent finite element model based on linear creep theory is verified with available experimental data. A parametric numerical study is then carried out, which focuses on the effects of concrete creep and/or shrinkage, ultimate shrinkage strain and reinforcing bars in the slab. The study shows that the long-term deformations in composite beams are dominated by concrete shrinkage and that a higher area of reinforcing bars leads to lower long-term deformations and steel stresses. The AISC model appears to overestimate the shrinkage-induced deflection. A modified ACI equation is proposed to quantify time-dependent deflections in composite beams. In particular, a modified reduction factor reflecting the influence of reinforcing bars and a coefficient reflecting the influence of ultimate shrinkage are introduced in the proposed equation. The long-term deflections predicted by this equation and the results of extensive numerical analyses are found to be in good agreement.

• 한국항만학회지
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• 제7권2호
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• pp.19-36
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• 1993

In this study for relieving traffic congestion on the main arterial in Pusan using TSM Techniques, the travel system, roadway system and signal system analyses were dine. Through these above analyses, it was shown that the peak-time periods on the main arterial were shaped between 10 : 00 and 11 : 00 in the morning and between 15 : 00 and 16 : 00 in the afternoon for the business and shopping trips. Especially, there appeared to be about 23% reduction in the average delay when roadway system management including left-turn links increased were done, about 29% reduction in the average delay when signal system management including the signal phases and timings readjusted were conducted, and about 48% reduction in average delay when roadway system and signal system management were taken into consideration simultaneously. Based upon these results, it was concluded that there might be considerably better results in the average delay if the progressive signal system analyses on the arterial were applied with the land and road widths balanced, the difference on the turning vehicles and mid-block volumes readjusted, and roadside parking traffic prohibited.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.