• Journal of Energy Engineering
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• v.28 no.3
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• pp.65-79
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• 2019

The study attempted to estimate the optimal facility capacity by combining renewable energy sources that can be connected with gas CHP in industrial complexes. In particular, we reviewed industrial complexes subject to energy use plan from 2013 to 2016. Although the regional designation was excluded, Sejong industrial complex, which has a fuel usage of 38 thousand TOE annually and a high heat density of $92.6Gcal/km^2{\cdot}h$, was selected for research. And we analyzed the optimal operation model of CHP Hybrid System linking fuel cell and photovoltaic power generation using HOMER Pro, a renewable energy hybrid system economic analysis program. In addition, in order to improve the reliability of the research by analyzing not only the heat demand but also the heat demand patterns for the dominant sectors in the thermal energy, the main supply energy source of CHP, the economic benefits were added to compare the relative benefits. As a result, the total indirect heat demand of Sejong industrial complex under construction was 378,282 Gcal per year, of which paper industry accounted for 77.7%, which is 293,754 Gcal per year. For the entire industrial complex indirect heat demand, a single CHP has an optimal capacity of 30,000 kW. In this case, CHP shares 275,707 Gcal and 72.8% of heat production, while peak load boiler PLB shares 103,240 Gcal and 27.2%. In the CHP, fuel cell, and photovoltaic combinations, the optimum capacity is 30,000 kW, 5,000 kW, and 1,980 kW, respectively. At this time, CHP shared 275,940 Gcal, 72.8%, fuel cell 12,390 Gcal, 3.3%, and PLB 90,620 Gcal, 23.9%. The CHP capacity was not reduced because an uneconomical alternative was found that required excessive operation of the PLB for insufficient heat production resulting from the CHP capacity reduction. On the other hand, in terms of indirect heat demand for the paper industry, which is the dominant industry, the optimal capacity of CHP, fuel cell, and photovoltaic combination is 25,000 kW, 5,000 kW, and 2,000 kW. The heat production was analyzed to be CHP 225,053 Gcal, 76.5%, fuel cell 11,215 Gcal, 3.8%, PLB 58,012 Gcal, 19.7%. However, the economic analysis results of the current electricity market and gas market confirm that the return on investment is impossible. However, we confirmed that the CHP Hybrid System, which combines CHP, fuel cell, and solar power, can improve management conditions of about KRW 9.3 billion annually for a single CHP system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.451-464
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• 2022

The high-level nuclear waste repository is a deep geological disposal system exposed to complex environmental conditions such as high temperature, radiation, and ground-water due to handling spent nuclear fuel. Continuous exposure can lead to cracking and deterioration of the structure over time. On the other hand, the high-level nuclear waste repository requires an ultra-long life expectancy. Thus long-term structural health monitoring is essential. Various sensors such as an accelerometer, earth pressure gauge, and displacement meter can be used to monitor the health of a structure, and a piezoelectric sensor is generally used. Therefore, it is necessary to develop a highly durable sensor based on the durability assessment of the piezoelectric sensor. This study designed an accelerated life test for durability assessment and life prediction of the piezoelectric sensor. Based on the literature review, the number of accelerated stress levels for a single stress factor, and the number of samples for each level were selected. The failure mode and mechanism of the piezoelectric sensor that can occur in the environmental conditions of the high-level waste repository were analyzed. In addition, two methods were proposed to investigate the maximum harsh condition for the temperature stress factor. The reliable operating limit of the piezoelectric sensor was derived, and a reasonable accelerated stress level was set for the accelerated life test. The suggested methods contain economical and practical ideas and can be widely used in designing accelerated life tests of piezoelectric sensors.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Journal of Energy Engineering
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• v.17 no.3
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• pp.167-174
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• 2008

Line source model is commonly used in analyzing the data obtained from thermal response test to estimate the effective soil formation thermal conductivity. In the application of line source model some part of initial data must be ignored in order to achieve more accurate result. The period of time for this initial data is called initial ignoring time(IIT) in this paper. However there has been no definite rule in determining this initial ignoring time. Therefore line source model requires experienced analyzer to select the useful data, which is somewhat subjective. One method often suggested is the calculation of IIT with non dimensional time $\tau=5$. However, this is a very theoretical result derived from a system of perfect line source model, which is somewhat different from the real system. A new method to determine IIT is presented in this study. This method requires error estimation first and IIT can be decided from the results of error estimation. This method is applied in the analysis of field test data and shows better result than the one obtained from the method using non dimensional time mentioned above as shown in Table 2.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.94-104
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• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.64-70
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• 2007

Raman spectroscopy is known to have strong potential for providing noninvasive dermatological diagnosis of skin cancer. According to the previous work, various well known methods including maximum a posteriori probability (MAP) and multilayer perceptron networks (MLP) showed competitive results. Since even the small errors often leads to a fatal result, we investigated the method that reduces classification error perfectly by screening out some ambiguous patterns. Those ambiguous patterns can be examined by routine biopsy. We incorporated an ambiguous pattern class in MAP, linear classifier using minimum squared error (MSE), MLP and reduced coulomb energy networks (RCE). The experiments involving 216 confocal Raman spectra showed that every methods could perfectly classify BCC by screening out some ambiguous patterns. The best results were obtained with MSE. According to the experimental results, MSE gives perfect classification by screening out 8.8% of test patterns.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.40-48
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• 2008

Security of self organized mobile ad hoc networks is an important issue because administration information in the networks is managed by the constituent nodes. Especially authentication mechanism is necessary for trust setup between newly joining nodes and the network. The authentication models and protocols which are based on the wireline infrastructure could not be practical for mobile ad hoc network. Although public key algorithm-based method is widely used for authentication, it is not easy to be applied to mobile ad hoc networks because they do not have infrastructure such as centralized CA which is needed for certificate verification. In this paper, we consider the public key based random CA group method proposed in [1] to provide efficient authentication scheme to mobile ad hoc networks and analyze the performance of the method, which is then compared to the home CA method. From the analysis results, we see that the random CA method where the function of CA is distributed to some mobile nodes and the authentication information is propagated to randomly chosen CAs shows higher reliability and lower cost than home CA method.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.25-31
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• 2015

Elastic behavior of the railway roadbed which supports the repeating dynamic loads of the train is mainly affected by the shear modulus of the upper roadbed. Therefore, shear wave velocity estimation of the uniformly compacted roadbed can be used to estimate the elastic behavior of the railway roadbed. The objective of this study is to suggest the relationship between the dynamic cone penetration index (DCPI) and the shear wave velocity ($V_s$) of the upper roadbed in order to estimate the shear wave velocity by using the dynamic cone penetration test (DCPT). To ensure the reliability of the relationship, the dynamic cone penetration test and the measurement of the shear wave velocity are conducted on the constructed upper roadbed. As a method for measurement of the shear wave velocity, cross hole is used and then the dynamic cone penetration test is performed at a center point between the source and the receiver of the cross hole. As a result of the correlation of the dynamic cone penetration index and the shear wave velocity at the same depths, the shear wave velocity is estimated as a form of involution of the dynamic cone penetration index with a determinant coefficient above 0.8. The result of this study can be used to estimate both the shear wave velocity and the strength of the railway roadbed using the dynamic cone penetrometer.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.41-48
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• 2015

An investigation of a void and a loose layer of the ground is essential in order to prevent the losses of life and properties caused by subsidence and sinkage of the ground. Recently, studies on the ground penetrating radar survey have been actively conducted in order to estimate the void and the loose layer of the ground. However, an error can be committed by contrarily predicting a dense ground and a loose layer because the ground penetrating radar estimates an interface depth between geo-materials that have different electrical impedances. In this study, a loose ground depth is estimated using the characteristics of the reflected electromagnetic wave obtained from the ground penetrating radar survey. To gather the signals according to the loose ground depths, the ground penetrating radar survey is conducted on a field which underwent a huge ground settlement. In addition, the dynamic cone penetration test is performed to verify the result of the loose ground depth estimation from the ground penetrating radar survey. From the analysis of the reflection characteristics of the electromagnetic wave, a phase of an electromagnetic wave reflected from a denser soil layer is found to be identical with that of the first measured signal. On the other hand, a phase of an electromagnetic wave reflected from the loose soil layer is found to be opposed to that of the first detected signal. The comparison between the dynamic cone penetration index and electromagnetic signals by the ground penetrating radar shows that the estimated depth of the loose or dense layer is perfectly matched with a high reliability. The ground penetrating radar survey and the signal analysis performed in this study can be used not only for the survey of interface depth between the discontinuity layers but also for the estimation of the loose layer.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.121-129
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• 2019

An Earthquake Early Warning (EEW) system is a technology that alerts people to an incoming earthquake by using P waves that are detected before the arrival of more severe seismic waves. P-wave analysis is therefore an important factor in the production of rapid seismic information as it can be used to quickly estimate the earthquake magnitude and epicenter through the amplitude and predominant period of the observed P-wave. However, when a large-magnitude teleseismic earthquake is observed in a local seismic network, the significantly attenuated P wave phases may be mischaracterized as belonging to a small-magnitude local earthquake in the initial analysis stage. Such a misanalysis may be sent to the public as a false alert, reducing the credibility of the EEW system and potentially causing economic losses for infrastructure and industrial facilities. Therefore, it is necessary to develop methods that reduce misanalysis. In this study, the possibility of seismic misclassifying teleseimic earthquakes as local events was reviewed using the Filter Bank method, which uses the attenuation characteristics of P waves to classify local and outside Korean peninsula (regional and teleseismic) events with filtered waveform depending on frequency and epicenter distance. The data used in our analysis were analyzed for maximum P_v values using 463 events with local magnitudes (2 < M_L ≦ 3), 44 (3 < M_L ≦ 4), 4 (4 < M_L ≦ 5), 3 (M_L > 5), and 89 outside Korean peninsula earthquakes recorded by the KMA seismic network. The results show that local and telesesimic earthquakes can be classified more accurately when combination of filtering bands of No. 3 (6-12 Hz) and No. 6 (0.75-1.5 Hz) is applied.