• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1506-1510
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• 2006

현재 기상청에서 제공하는 강수자료는 정시자료로서 수문학적 의미의 임의지속시간 강수자료라 볼 수 없다. 따라서 이러한 정시자료를 임의지속시간 강수자료로 변환하여 사용하여야 한다. 이러한 환산계수는 국외에서는 Weiss(1964), Dwyer와 Reed(1995) 등에 의하여 제시되어졌고, 국내에서는 김규호 등(1988)등이 환산계수를 제시한 바 있다. 그렇지만 기존 연구의 자료들은 목측에 의한 자료로서 많은 불확실성을 가지고 있다. 최근 관측기기의 발달에 의하여 기상청에서는 1분 단위의 관측 자료를 구축하였다. 따라서 본 연구에서는 이러한 1분 단위 강수자료를 이용하여 수문학적 의미의 임의지속시간 강수자료를 적출하여 보다 정확하게 강수자료의 환산계수(Adjustment factor)를 구축하는데 목적이 있다. 본 연구에서는 서울지방 7개 자동기상관측소(AWS:Automatic Weather Station)에서 관측된 6개년(2000년${\sim}$2005년) 1분 강수자료를 이용하여 고정시간 연 최대강수량과 임의시간 연 최대강수량간의 관계를 연구하였다. 1분 강수자료를 이용하여 고정시간과 임의지속시간에 대한 연 최대치 강수 계열을 구축.도시한 후 선형회귀분석에 의해 선정된 계수를 환산계수로 제시하였다. 고정시간 1시간부터 24시간까지의 최대강수량과 임의시간 간격 최대강수량의 비율을 분석한 결과 환산계수는 지속시간이 증가함에 따라 비선형적으로 감소하는 것으로 나타났다. 이러한 관계를 이용하면 정시 강수자료를 보다 정확하게 임의지속시간 강수자료로 환산할 수 있을 것으로 판단된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.52-62
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• 2013

Design Hourly Factor(DHF) is defined as the ratio of design hourly volume(DHV) to Average Annual Daily Traffic(AADT). Generally DHV used the 30th rank hourly volume. But this case DHV is affected by holiday volumes so the road is at risk for overdesigning. Computing K factor is available for counting 8,760 hour traffic volume, but it is impossible except permanent traffic counts. This study applied three method to make DHF, using 30th rank hourly volume to make DHF(method 1), using peak hour volume to make DHF(method 2). Another way to make DHF, rank hourly volumes ordered descending connect a curve smoothly to find the point which changes drastic(method 3). That point is design hour, thus design hourly factor is able to be computed. In addition road classified 3 type for national highway using factor analysis and cluster analysis, so we can analyze the characteristic of DHF by road type. DHF which was used method 1 is the largest at any other method. There is no difference in DHF by road type at method 2. This result shows for this reason because peak hour is hard to describe the characteristic of hourly volume change. DHF which was used method 3 is similar to HCM except recreation road but 118th rank hourly volume is appropriate.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.582-590
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• 2015

Road type classification and K-factors are important role when design of number of lane. In this study not only classifies road type and estimating of K-factor but also economic evaluation tries for feasibility verification. Road type analysis results, time of day traffic volume variation, weekend-factor and vacation-factor are large in recreation roads. Weekday traffic volume and weekend traffic volume are similar patterns in provincial roads. AADT is high and time of day traffic volume variation is small in urban roads. In this study compares with economic analysis that designing of number of lane between KHCM's K-factor and this study K-factor. Economic analysis results, designed roads by this study's K-factor reduce cost about 4,708 hundred million won. So this study's K-factor is economical on provincial 4 lane roads.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.155-162
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• 2008

This study shows how to estimate the design hour factor when the counting stations don't have all of the hourly volumes such as in a coverage survey. A coverage survey records traffic volume from 1 to 5 times in a year so it lacks the detailed information to calculate the design hour factor. This study used the traffic volumes of permanent surveys to estimate the design hour factor in coverage surveys using correlation and regression analysis. A total 7 independent variables are used : the coefficient of variance of hourly volume, standard deviation of hourly volume, peak hour volume, AADT, heavy traffic volume proprotion, day time traffic volume proportion and D factor. All of variables are plotted on a curve, so it must use non-linear regression to analyze the data. As a result the coefficient of determination and MAE are good at logarith model using AADT.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.79-88
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• 2007

Design Hourly Volume (DHV) is the hourly volume used for designing a section of road. DHV is also used to estimate the expected number of vehicles to pass or traverse the relevant section of road in a future target year. The Design Hour Factor (DHF) is defined as the ratio of DHV to Average Annual Daily Traffic (AADT). In addition to high precision of predicted traffic volume, in order to design a roadway to be the proper scale, applying appropriate DHFs considering traffic flow characteristics and type of area which surrounds the relevant roadway is important. This study categorizes sections of expressway (Suh Hae An Expressway) according to their area type and estimates DHFs utilizing traffic data obtained from a vehicle detection system (VDS). This study shows that DHFs calculated using VDS data are different from those using traffic data acquired from a coverage survey. While AADTs from both data show similar values, peak hour volumes from both data show significant differences especially for recreational areas. DHFs from the coverage survey are quite different from the values provided by the Korean design guide or previous research results and DHFs for urban areas are higher than recreational areas. However, DHFs from VDS shows similar values to previous research results. The result of this study suggests that using VDS for estimating DHFs is more reliable than using a coverage survey.

• Journal of the Korean Geosynthetics Society
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• v.21 no.1
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• pp.23-32
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• 2022

This study is conducted to minimize the problems caused by the difference between the settlement and settlement time of the one-dimensional consolidation analysis by the Terzaghi's consolidation theory, which is generally used in domestic soft soil design, from the settlement and settlement time measured at the field site. Consolidation-time factor considering the field site characteristics can be determined using the relationship among the degree of consolidation, settlement time, and time factor, the time-settlement curve measured at the field is reverse- analysis using a numerical-analysis technique to reproduce the same consolidation behavior as in the field. Time-settlement and time-excessive pore water pressure data when the same consolidation behavior as the site is reproduced Consolidation-time factor of the soil of Songsan Green City by settlement and excess pore water pressure was calculated using the settlement and excess pore water pressure for each settlement time. If the results of this study use the Terzaghi consolidation-time factor, which does not consider the consolidation characteristics of the soft ground target area, it is difficult to determine the end time of the soft ground during construction. It is necessary to use the established settlement-time factor.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1215-1219
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• 2008

수공구조물 설계에 있어 가장 중요한 기준이 되는 확률강우량은 기존에 발생한 시간강우와 일강우 자료를 이용하여 지속시간별 연최대치 계열을 빈도해석하여 수행하고 있다. 현재 기상청에서 제공하는 강우자료는 00시 00분부터 01시 00분까지 누적된 강우량을 01시 강우량으로 제공하고 있다. 이는 한 호우 사상에서 총강우량은 동일할지 모르지만, 강우의 발생별 시점, 종점 및 누적 강우량은 다르게 산정된다. 이와 같이 확률강우량 산정시 고정시간 강우자료를 수문학적 의미인 임의 지속시간별 강우량자료로 변환이 필요하다. 따라서, 본 연구에서는 37개 지점의 1분 단위 강우 관측자료를 이용하여 고정시간별 연 최대치 계열과 임의 지속시간별 연 최대치 계열을 추출한 후 두 자료에 따른 지속시간별 환산계수를 산정하였으며, 기존에 산정된 환산계수와 비교 분석하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.515-524
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• 2008

An estimation of reliable probability precipitation is one of the most important processes for reasonable hydrologic structure design. A probability precipitation has been calculated by frequency analysis using annual maximum rainfall series on the each duration among the observed rainfall data. Annual maximum rainfall series have abstracted on hourly rainfall data or daily rainfall data. So, there is necessary to proper conversion factor between the fixed and sliding durations. Therefore, in this study, conversion factors on the each duration between fixed and sliding durations have calculated using minutely data compared to hourly and daily data of 37 stations observed by Meteorological Administration in Korea. Also, regression equations were computed by regression analysis of conversion factors on the each duration. Consequently, conversion factors were used basis data for calculations of stable probability precipitation.

• Journal of Radiation Protection and Research
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• v.29 no.4
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• pp.269-273
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• 2004

The hybrid dead time model adopting paralyzable (or extendable) and non-paralyzable (or non-extendable) dead times has been introduced to extend the usable range of G-M counters in high counting rate environment and the relationship between true and observed counting rates is more accurately expressed in the hybrid model. GMSIM, dead time effects simulator, has been developed to analyze the counting statistics of G-M counters using Monte Carlo simulations. GMSIM accurately described the counting statistics of the paralyzable and non-paralyzable models. For G-M counters that follow the hybrid model, the counting statistics behaved in between two idealized models. In the future, GMSIM may be used in predicting counting statistics of three G-M dead time models, which are paralyzable, non-paralyzable and hybrid models.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.433-433
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• 2012

제주지역의 지하수 함양 지체시간을 분석하기 위해 18개 지점의 지하수 관측자료를 기초로 강수-지하수위 자료를 강수사상별로 분류하여 분석하였다. 지하수 함양에 결정적인 영향을 주는 인자로 지하수위의 대수층 두께와 지점의 투수계수를 설정하였다. 대체로 고도가 낮은 지역에서는 지하수 함양 지체가 짧았으나 고도가 높아질 수록 대수층 두께도 증가하여 지하수 함양지체시간은 길게 나타났다. 하지만 대수층 두께만으로 지체시간이 결정되는 것은 아니며 이에 투수계수 자료를 함께 분석해야만 타당한 결과를 얻을 수 있을 것으로 판단하여 대수층 두께와 지점 투수계수를 변수로 두고 관측된 지하수 함양지체시간과의 관계를 다중선형회귀분석을 통해 구하였다. 다중상관계수는 0.9정도로 높게 나타났으며, 대수층 두께에 대한 통계학적 유의성도 적합하게 나타났다. 이와 같이 결정된 회귀식은 향후 지하수 함양지체시간의 공간분포를 결정함에 있어 활용이 가능하며 분포형 수문모형과 연계시킬 경우 통합모델링에 적절하게 반영될 수 있을 것으로 판단된다.