• 한국조사연구학회지:조사연구
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• 제12권2호
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• pp.27-50
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• 2011

도시의 행정수요 측정과 도시경제 운영을 위해 주간활동인구를 파악해야 할 필요성이 증가하였다. 상주인구를 보완하는 개념으로서 센서스의 통근 통학 자료에 근거를 둔 주간인구가 활용되고 있으나 서비스 경제가 압도적인 서울과 같은 대도시의 주간활동인구 파악에는 한계가 있다. 본 연구에서는 도시의 주간활동인구를 파악하기 위한 개념으로서 유동인구를 제시하고 서울시 유동인구 조사의 방법을 소개하였으며 주요 분석결과를 제시하였다. 유동인구 조사자료의 분석 결과 센서스 기반 주간인구에서는 파악할 수 없었던 시간대별, 공간대별 도시 주간활동인구의 분포를 밝힐 수 있었다. 끝으로 유동인구 조사자료를 통해 파악한 주간인구와 센서스 기반 주간인구를 자치구 수준에서 비교함으로써 유동인구 조사 자료의 주요 특성들을 밝혔다.

• 한국BIM학회 논문집
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• 제9권1호
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

• 한국방재학회 논문집
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• 제8권1호
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• pp.145-151
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• 2008

농어촌지역의 하수종말처리시설 민간투자사업에 대한 계획인구 및 계획하수량 산정 방법을 검토하였다. 기존의 추정 방법에서는 인구 감소 추세임에도 불구하고, 인구가 정체될 것으로 가정하여 계획인구를 추정하고 있으며, 수도보급률이 매우 낮은 지역에서의 계획하수량을 정수장 급수보급량을 이용하여 산정하고 있다. 결과적으로 계획 인구 및 계획하수량의 과다 산정은 필요이상의 하수종말처리시설이 만들어지게 되는 결과를 가져오게 된다. 그러므로 본 연구에서는 계획 인구는 통계청의 장래인구 추계결과를 따르는 것으로 하고, 수도가 보급된 지역에서는 급수사용량을, 수도가 보급되지 않은 지역에서는 지하수 사용량을 이용하여 계획하수량을 산정하는 방안을 제시하였다.

• 상하수도학회지
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• 제25권6호
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• pp.877-884
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• 2011

Although peak loading coefficient is one of critical design factors for sewer works, its detailed affecting factors were not analyzed because of limited data availability. This study analyzed the affecting factors on peak loading coefficient with plenty data obtained from several newly constructed sewer works. Simple and multiple regression analysis methods were adopted to analyze the relationships of each variable with or without data filtering. Drainage population, drainage area, population density, and daily sewage flow per person showed very weak relationships under diverse characteristics of cities. However, daily sewage flow per person showed stronger relationships with peak loading when daily sewage flow per person was splitted into two ranges. Population density (i.e., drainage population divided by drainage area) and daily sewage flow per person considerably were related with peak loading coefficient when daily sewage flow per person is less than about 400 Lpcd.

• 상하수도학회지
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• 제19권6호
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• pp.749-757
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• 2005

The present study analyzed actual cases of designed flow estimation method and designed flow rate of sewage pipe lines. In order to examine the effects of peak-hour demand factor estimation with given daily highest peak loading, we analyzed its effects on designed flow rate with changing the peak-hour demand factor from 2.0 to 10.0. The results of this study are as follows. When reviewing the recent designs, we found that 59.4% of pipe line with 250mm and 300mm diameter, which fall under minimum allowable pipeline did not meet the minimum velocity which is specified as 0.6m/sec in design standards. The pipe line that have minimal access population or have very low slope did not satisfy the minimum velocity. In estimating the designed sewage flow, the applied daily highest peak loading and hourly highest peaking loading were the load factor for the entire population of the planned area, and for the peak loading of the initial pipes connected to a very small population, we applied the same factor as that applied to the entire area and, as a result, the hourly highest flow was underestimated. Because, in case of the initial pipes, the method of applying the same peak loading to all subject areas is highly possible to produce underestimated design flow, when estimating the designed flow of the initial pipes connected to a small population need to adopt a rational flow factor according to the size of population. For this, it is considered to investigate and analyze raw data on daily and hourly variation of sewage flow.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3197-3202
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• 2007

An analysis program for pedestrian flow has been developed to investigate the flow patterns of passenger in railway stations. Analysis algorithms for pedestrian flow based on DEM(Discrete Element Method) are newly developed. There are lots of similarity between particle-laden two phase flow and passenger flow. The velocity component of 1st phase corresponds to the unit vector of calculation cell, each particle to passenger, volume fraction to population density and the particle velocity to the walking velocity, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger. By using the developed program, we compared the simulation results of the effects of the location and size of exit and elapsed time.

• 한국철도학회논문집
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• 제8권4호
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• pp.337-341
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• 2005

Algorithm for passenger flow analysis based on DEM(Discrete Element Method) is newly developed. In the new algorithm, there are many similarity between multi phase flow and passenger flow. The velocity component of 1st phase corresponds to the direction vector of cell, each particle to each passenger, volume fraction to population density and the momentum equation of particle to the walking velocity equation of passenger, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger, To verify the effectiveness of new algorithm, passenger flow analysis for simple railway station model is conducted. The results for passenger flow in the model station are satisfying qualitatively and quantitatively.

• 한국철도학회논문집
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• 제9권3호
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• pp.271-276
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• 2006

Insight into behaviour of pedestrians as welt as tools to assess passenger flow condition is important in such instances as planning and geometric design of railway station under regular and safety-critical circumstances. Algorithm for passenger flow analysis based on DEM (Discrete Element Method) is newly developed. There are lots of similarity between particle-laden two phase flow and passenger flow. The velocity component of 1st phase corresponds to the unit vector of calculation cell, each particle to passenger, volume fraction to population density and the particle velocity to the walking velocity, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger. To verify the effectiveness of new algorithm, passenger flow analysis for the basic models of railway station is conducted.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.387-391
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• 2006

Insight into behaviour of pedestrians as well as tools to assess passenger flow conditions are important in for instance planning and geometric design of railway station under regular and safety-critical circumstances. Algorithm for passenger flow analysis based on DEM(Discrete Element Method) is newly developed. There are lots of similarity between particle-laden two phase flow and passenger flow. The velocity component of 1st phase corresponds to the unit vector of calculation cell, each particle to passenger, volume fraction to population density and the particle velocity to the walking velocity, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger. To verify the effectiveness of new algorithm, passenger flow analysis for the basic models of railway station is conducted.

• 지적과 국토정보
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• 제49권1호
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• pp.181-195
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• 2019

본 연구의 목적은 통신 데이터를 통해 구축한 유동인구 데이터를 활용하여 서울시 도심도보관광코스 내 유동인구 특성을 파악하고 효과적으로 시각화하여 공간적인 맥락을 분석하는 것이다. 도로에 따른 유동인구 추정을 위해 유동인구 데이터 정제 기법을 개발하여 도보관광코스 별 유동인구 데이터를 구축하였다. 도보관광코스 분석에 적합한 형태로 정제하기 도로 주변 유동인구 값을 고려한 유동인구 추정하여 도보관광코스 내 유동인구를 할당하였다. 정제된 데이터를 바탕으로 서울도보관광 18개 코스 각각의 유동인구 특성과 공간 특성을 도출하였다. 도보관광코스 내 유동인구의 공간 밀도와 집중 구간을 분석하기 위해 커널 밀도분석과 Getis-Ord $G^*_i$ 통계를 적용하였으며 3D 시각화를 통해 서울도보관광 18개 코스별 유동인구 특성을 성, 연령, 시간, 요일에 따라 정량적으로 파악하였다. 그 결과 청계천 제1코스, 경희궁-서대문코스, 인사동-운현궁 코스 순으로 유동인구 규모가 크게 나타났으며 주중에는 인사동-운현궁, 주말에는 성북동 코스의 유동인구가 많았다. 남성 유동인구 비율이 가장 높은 코스는 청계천 제1코스, 여성 유동인구 비율이 가장 높은 코스는 몽촌토성 코스였다. 주말 유동인구 비율이 가장 높은 도보관광코스는 성북동 코스임을 확인할 수 있었다.