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Drainage Performance of Various Subsurface Drain Materials- (배수개선공법개발에 관한 연구(I) -각종 지하배수용 암거재료의 배수성능-)

  • 김철회;이근후;유시조;서원명
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.21 no.3
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    • pp.104-120
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    • 1979
  • I. Title of the Study Studies on the Development of Improved Subsurface Drainage Methods. -Drainage Performance of Various Subsurface Drain Materials- II. Object of the Study Studies were carried out to select the drain material having the highest performance of drainage; And to develop the water budget model which is necessary for the planning of the drainage project and the establishment of water management standards in the water-logged paddy field. III. Content and Scope of the Study 1. The experiment was carried out in the laboratory by using a sand tank model. The drainage performance of various drain materials was compared evaluated. 2. A water budget model was established. Various parameters necessary for the model were investigated by analyzing existing data and measured data from the experimental field. The adaptability of the model was evaluated by comparing the estimated values to the field data. IV. Results and Recommendations 1. A corrugated tube enveloped with gravel or mat showed the highest drainage performance among the eight materials submmitted for the experiment. 2. The drainage performance of the long cement tile(50 cm long) was higher than that of the short cement tile(25 cm long). 3. Rice bran was superior to gravel in its' drain performance. 4. No difference was shown between a grave envelope and a P.V.C. wool mat in their performance of drainage. Continues investigation is needed to clarify the envelope performance. 5. All the results described above were obtained from the laboratory tests. A field test is recommended to confirm the results obtained. 6. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as follows; $$D=\Sigma\limit_{t=1}^{n}(Et-R_{\ell}-I+W_d)..........(17)$$ 7. Among the various empirical formulae for potential evapotranspiration, Penman's formular was best fit to the data observed with the evaporation pans in Jinju area. High degree of positive correlation between Penman;s predicted data and observed data was confirmed. The regression equation was Y=1.4X-22.86, where Y represents evaporation rate from small pan, in mm/100 days, and X represents potential evapotranspiration rate estimated by Penman's formular. The coefficient of correlation was r=0.94.** 8. To estimate evapotranspiration in the field, the consumptive use coefficient, Kc, was introduced. Kc was defined by the function of the characteristics of the crop soil as follows; $Kc=Kco{\cdot}Ka+Ks..........(20)$ where, Kco, Ka ans Ks represents the crop coefficient, the soil moisture coefficient, and the correction coefficient, respectively. The value of Kco and Ka was obtained from the Fig.16 and the Fig.17, respectively. And, if $Kco{\cdot}Ka{\geq}1.0,$ then Ks=0, otherwise, Ks value was estimated by using the relation; $Ks=1-Kco{\cdot}Ka$. 9. Into type formular, $r_t=\frac{R_{24}}{24}(\frac{b}{\sqrt{t}+a})$, was the best fit one to estimate the probable rainfall intensity when daily rainfall and rainfall durations are given as input data, The coefficient a and b are shown on the Table 16. 10. Japanese type formular, $I_t=\frac{b}{\sqrt{t}+a}$, was the best fit one to estimate the probable rainfall intensity when the rainfall duration only was given. The coefficient a and b are shown on the Table 17. 11. Effective rainfall, Re, was estimated by using following relationships; Re=D, if $R-D\geq}0$, otherwise, Re=R. 12. The difference of rainfall amount from soil moisture depletion was considered as the amount of drainage required. In this case, when Wd=O, Equation 24 was used, otherwise two to three days of lag time was considered and correction was made by use of storage coefficient. 13. To evaluate the model, measured data and estimated data was compared, and relative error was computed. 5.5 percent The relative error was 5.5 percent. 14. By considering the water budget in Jinju area, it was shown that the evaporation amount was greater than the rainfall during period of October to March in next year. This was the behind reasonning that the improvement of surface drainage system is needed in Jinju area.

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Development of Estimation System for Housing Remodeling Cost through Influence Analysis by Design Elements (설계요소별 영향분석을 통한 공동주택 리모델링 공사비개산견적 산출 시스템 개발)

  • Kim, Jun;Cha, Heesung
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.6
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    • pp.65-78
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    • 2018
  • In As urban apartment are aging, the necessity of reconstruction or remodeling to extend the life of buildings is increasing. In such a case, a co-housing association is formed to implement decisions on reconstruction or remodeling projects. At this time, the most important thing for the co-housing association is the business feasibility based on the input of the construction cost.In the case of reconstruction, it is possible to estimate the construction cost by using the accumulated construction cost data, and then evaluate the feasibility using the construction cost. However, in case of remodeling, it is difficult to calculate the accurate construction cost because the number of accumulated construction cost data is small. In addition, non-specialist clients often require estimates of various design factors, often negatively impacting the accuracy of estimates and the duration of estimates. Therefore, in this study, proposed method to reflect the opinion of the owner who is a non-expert, as a design element, and a method of calculating the expected construction cost according to the design element, and constructed this system so that it can be easily used by the non-specialist owner. In order to clearly reflect the requirements of the non-specialist owner in the estimates, extracts the design elements from the existing remodeling cases, classify them, and suggest a plan for the client to choose. In order to reflect the design factors to the estimates, the existing apartment house remodeling cases were investigated and the design factors were extracted to have a large effect on the construction cost. Finally, developed system based on MS Excel so that the above contents can be easily used by a non-specialist client. In order to verify the accuracy of the proposed estimate in this study, verified the accuracy of 80% of the results by substituting the case of remodeling quotations and obtained a positive result from the questionnaire survey to examine the ease of use of the non-specialist customer. In this study, propose an estimate estimation method using four cases. If the remodeling cases are accumulated continuously, the expected effect of this study will be higher.

Analysis and Prediction of Sewage Components of Urban Wastewater Treatment Plant Using Neural Network (대도시 하수종말처리장 유입 하수의 성상 평가와 인공신경망을 이용한 구성성분 농도 예측)

  • Jeong, Hyeong-Seok;Lee, Sang-Hyung;Shin, Hang-Sik;Song, Eui-Yeol
    • Journal of Korean Society of Environmental Engineers
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    • v.28 no.3
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    • pp.308-315
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    • 2006
  • Since sewage characteristics are the most important factors that can affect the biological reactions in wastewater treatment plants, a detailed understanding on the characteristics and on-line measurement techniques of the influent sewage would play an important role in determining the appropriate control strategies. In this study, samples were taken at two hour intervals during 51 days from $1^{st}$ October to $21^{st}$ November 2005 from the influent gate of sewage treatment plant. Then the characteristics of sewage were investigated. It was found that the daily values of flow rate and concentrations of sewage components showed a defined profile. The highest and lowest peak values were observed during $11:00{\sim}13:00$ hours and $05:00{\sim}07:00$ hours, respectively. Also, it was shown that the concentrations of sewage components were strongly correlated with the absorbance measured at 300 nm of UV. Therefore, the objective of the paper is to develop on-line estimation technique of the concentration of each component in the sewage using accumulated profiles of sewage, absorbance, and flow rate which can be measured in real time. As a first step, regression analysis was performed using the absorbance and component concentration data. Then a neural network trained with the input of influent flow rate, absorbance, and inflow duration was used. Both methods showed remarkable accuracy in predicting the resulting concentrations of the individual components of the sewage. In case of using the neural network, the predicted value md of the measurement were 19.3 and 14.4 for TSS, 26.7 and 25.1 for TCOD, 5.4 and 4.1 for TN, and for TP, 0.45 to 0.39, respectively.