• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.2
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• pp.19-27
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• 2012

This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.849-854
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• 2009

Pollutant unit load (unit-load) reported by Ministry of Environment (MOE) in 1995 has been a useful method for watershed management and environmental policy decision. The unit-load has been estimated using effective rainfall ratio method. However, reliability of unit-load determined by the method has been criticized especially for paddy field and upland conditions. In this paper the unit-load of paddy field estimated by effective rainfall ratio method was compared with continuous monitoring data. Annual loads was simulated by the method choosing 5~6 storm events randomly from whole events collected. Probability distribution of difference between results by the method and measured data was investigated. The results showed that unit-load derived by the method was generally lesser than measured unit-load and showed wide variations. Therefore, unit-load estimation of paddy fields by effective rainfall ratio method need caution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.913-920
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• 1996

In this study, the counting method for multi-axial and multi-point load states was proposed. Using this counting method, the load spectrum is generated from the service load history which is measured for boom structure of excavator. Loading state for loading points of boom structure is described as a multi-dimensional state space. From this load spectrum, the stress spectrum was generated by FEM analysis using the superposition of the unit load. The cumulated damage at the severe damage point of In nm structure by the failure example is calculated by Palmgren-Miner's rule. As a result of this study, the fatigue life estimation using the multi-axial and multi-point load counting method is useful.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.37-46
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• 2005

From 2000 to 2004, the research was carried out at Naerin-cheon and Inbook-cheon, the upper streams of Soyang Lake, to study the relationship between precipitation and eutrophication-causing water pollutants, BOD, T-N and T-P. During the five years, the amount of flowing water was measured, and the water quantity was examined under different precipitation levels. From the observation, outflow patterns of the water pollutants and changes in the water quality factors at the time of rainfall were clarified. In addition, estimation of the unit load was made for each stream; for Naerin-cheon at the time of rainfall, we estimated BOD to be $1,112kg/km^2/year$, T-N to be $2,077kg/km^2/year$, and T-P to be $223kg/km^2/year$; for Inbook-cheon at the time of rainfall, we estimated BOD to be $1,229kg/km^2/year$, T-N to be $1,565kg/km^2/year$, and T-P to be $255kg/km^2/year$. For the time of no rainfall different estimation was made; for Naerin-cheon, we estimated BOD to be $2,403g/km^2/day$, T-N to be $5,004g/km^2/day$, and T-P to be $53g/km^2/day$; and for Inbook-cheon, we estimated BOD to be $1,550g/km^2/day$, T-N to be $2,283g/km^2/day$, and T-P to be $42g/km^2/day$.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.235-240
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• 2015

To evaluate the unit load generation and discharge, pig cage test was conducted. Feed intake, drink amount, and urine generation increased growth stage (heavy weight) of the pig more great. However, the sum of the urine and manure did not show a significant difference in the growth stages of pigs. Because of the limit of the experiment, e.g., research period, high pigpen temperature, breed-related stress and etc., it could not be derived the results of the four seasons. Therefore, in order to generalize the results, the feed intakes were calibrated using a NRC (National Research and nutritional requirements of pigs from the Commission) standards. The finalized unit load generation and generation amounts of manure and urine were estimated at BOD 104.1 g/head/d, T-N 21.2 g/head/d, T-P 4.9 g/head/d, manure 0.96 L/d, urine 1.66 L/d with consideration of revised feed intake. Compare to the former research results of MOE (Ministry of Environment, 1999) and NIAS (National Institute of Animal Science, 2008), the generation amounts of manure and urine were similar to the NIAS's values. In case of unit load generation, BOD and T-N were almost similar in all of them. However, the T-P unit load generation of MOE was more difference, e.g., 2.5 times high, compare to this study.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.224-231
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• 2012

It is necessary to develop flow duration curve (FDC) on each unit watershed in order to analyze flow conditions in the stream for the management of Total Maximum Daily Loads (TMDLs). This study investigated a simple method to develop FDC for the general use of the curve. A simple equation for daily flow estimation was derived from the regression analysis between the 8-day interval flow data of a unit watershed and the daily flow monitoring data of an adjacent upstream region. FDC can be prepared with the calculation of daily flow by the equation for each unit watershed. An annual and a full-period FDC were drawn for each unit watershed in Guem river basin. Standard flow such as low and ordinary flow can be obtained from the annual FDC. Major percentile of flow such as 10, 25, 50, 75 or 90% can be obtained from the full-period FDC. It is considered that this simple method of developing FDC can be utilized more widely for the calculation of standard flow and the assessment of water quality in the process of TMDLs.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.22-31
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• 2001

The purpose of this study is to compare calculated pollutant loadings using pollutant load unit factors and vector type coverage, and expected mean concentration(EMC) and raster type of digital elevation model(DEM). This study is also focusing on comparison of the advantages and the disadvantages of the two methods, and seeking for a method of calculation of pollutant loadings using DEM. Estimation of pollutant inputs using pollutant load unit factors has limitations in identifying seasonal variations of pollutant loadings. Seasonal changes of runoffs should be considered in the calculation of pollutant loadings from catchments into reservoirs. Evaluation of pollutant inputs using runoff-coefficient and EMC can overcome these drawbacks. Proper EMC and runoff-coefficient values for the Koeup stream catchments of the Koheung estuarine lake were drawn from review of related papers. Arc/Info was employed to establish database of spatial and attribute data of point and non-point pollutant sources and characteristics of the catchments. ArcView was used to calculate point and non-point pollutant loadings. Pollutant loads estimated with either unit factors-coverages, i.e., pollutant load unit factors and vector coverages f point sources and land use, or EMC and digital elevation mode(DEM) were compared with stream monitoring loads. We have found that some differences were shown between monitoring results and estimated loads by Unit Factors-Coverage and EMC-DEM. Monthly variations of pollutant loads evaluated with EMC-DEM were similar to those with monitoring result. The method using EMC-DEM can calculate accumulated flows and pollutant loads and can be utilized to identify stream networks. A future research on correcting the difference between vector type stream using flow direction grid and digitalizing vector type should be conducted in order to obtain more exact calculation of pollutant loadings.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.1
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• pp.32-37
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• 2011

The present study has been conducted to propose an algorithm regarding real-time load estimation of a gas engine-driven heat pump. In the study, thermal load of an indoor unit is estimated in terms of air-side and refrigerant-side. The air-side estimation is based on a typical heat exchanger model and is found to be in good agreement with experimental data. When it comes to the refrigerant-side load, a pressure difference across a valve must be estimated. For the estimation, it is assumed to be proportional to a bigger pressure difference that is available either by measurement or by estimation. Relative good agreement between the air- and refrigerant-sides suggests that the assumption may be plausible for the load estimation. The summed flow rate of all of indoor units is in good agreement with the throughput of the compressor which are calculated from the manufacturer's software. Accordingly, estimated thermal loads are also in good agreement. The proposed algorithm may be further developed for improved control algorithm and fault diagnosis.