지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록· 키워드
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Pearson's correlation was used to determine relations between infiltration and affecting factors using flow monitoring data measured in 24 areas with different characteristics. Factors showed relatively high correlations than others were indexed to determine infiltration rates of the study area. Among 8 factors(service area, sewer length, sewer diameter, multiplier of sewer length and diameter, number of manholes, population, number of properties, number of households) tested, the multiplier of sewer length and diameter, the number of population and the number of household in each service area indicated higher correlation coefficient(>0.8) than others. The goodness of fitness of linear regressions between infiltration and the factors followed the order: sewer length and diameter(0.68)> population(0.65)> number of household(0.60). Infiltration rates calculated by the multiplier of sewer length and diameter, the number of population and the number of household in each service area were 0.046~1.0396 $m^{3}/d{\cdot}mm-km$, 0.0917~1.7355 $m^{3}/capita{\cdot}d$, 0.196~4.529 $m^{3}/household {\cdot}d$ respectively. After sewerage rehabilitation work of the area, the infiltration rates calculated by above factors with high correlations are expected to be used for comparing effectiveness of the work once they are estimated under the same flow measuring conditions.
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