• Journal of ILASS-Korea
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• v.23 no.4
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• pp.234-243
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• 2018

Since September 2017, a small diesel vehicle certification test mode has been enhanced from NEDC to WLTC. The main reason for the change of the certification test mode is that the certification test mode of the emission control standard of the diesel vehicle does not sufficiently reflect various driving patterns of the actual roads. Several automakers have developed after-treatment systems such as LNT, SCR, and DPF to meet enhanced emissions regulations. In this study, four small diesel cars were selected for sale in Korea, and the exhaust gas measurement test was performed in the WLTC mode, which reflects the driving characteristics of the actual roads. As a result of test, LNT vehicle exceeded Euro 6 NOx regulation and SCR vehicle satisfied Euro 6 NOx regulation. In addition, both LNT and SCR systems showed high NOX emission characteristics due to speed, RPA and Vxa. For the PN, all test vehicles were fitted with a DPF and met the Euro 6 PN regulations, with similar PN emissions results in LNT and SCR system.

• Journal of Biosystems Engineering
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• v.37 no.2
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• pp.113-121
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• 2012

Purpose: Particle separation in solution is one of important process in a unit operation as well as in an extract preparation for biosensors. Contrary to centrifuge-type of mesh-type filter, using an ultrasonic standing wave make the filtering process continuous and free from maintenance. It is needed to investigate the characteristics of particle movement in the ultrasonic standing wave field. Methods: Through the computer simulation the effects of major design and driving parameters on the alignment characteristics of particles were investigated, and a cylindrical chamber with up-stream flow type was devised using two circular-shape PZTs on both sides of the chamber, one for transmitting ultrasonic wave and the other for just reflecting it. Then, the system performance was experimentally investigated as well. Results: The speed of a particle to reach pressure-node plane increased as the acoustic pressure and size of particle increased. The maximum allowable up-stream flow rate could be calculated as well. As expected, exact numbers of pressure-node planes were well formed at specific locations according to the wavelength of ultrasonic wave. As the driving frequency of PZT got close to its resonance frequency, the bands of particles were observed clearer, which meant the particles were trapped into narrower space. Higher excitation voltages to the PZT produced a greater acoustic force with which to trap particles in the pressure-node planes, so that the particles gathered could move upwards without disturbing their alignments even at a higher inlet flow rate. Conclusions: This research showed the feasibility of particle separation in solution in the continuous way by an ultrasonic standing wave. Further study is needed to develop a device to collect or harvest those separated particles.

• Korean Chemical Engineering Research
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• v.56 no.5
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• pp.752-760
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• 2018

The lowering of temperature for combustion of diesel particulate matters (or diesel soot) is one of the important tasks in automotive industry that is searching for a way to meet up "high-fuel efficiency, low-emission" standard. In this study, it was discussed how the use of ozone over platinum-based catalyst promotes a low-temperature soot oxidation occurred at $150^{\circ}C$. The use of platinum catalyst did not increase oxidation rate largely but was very effective in improving the selectivity of carbon dioxide. The pre-oxidation of NO into $NO_2$ using ozone was rather crucial in improving the oxidation rate of soot at $150^{\circ}C$.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.134-142
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• 2022

Background: This study investigated the characteristics of optically stimulated luminescence dosimeters (OSLDs) with fully filled deep electron/hole traps in the kV energy ranges. Materials and Methods: The experimental group consisted of InLight nanoDots, whose deep electron/hole traps were fully filled with 5 kGy pre-irradiation (OSLD_exp), whereas the non-pre-irradiated OSLDs were arranged as a control group (OSLD_cont). Absorbed doses for 75, 80, 85, 90, 95, 100, and 105 kVp with 200 mA and 40 ms were measured and defined as the unit doses for each energy value. A bleaching device equipped with a 520-nm long-pass filter was used, and the strong beam mode was used to read out signal counts. The characteristics were investigated in terms of fading, dose sensitivities according to the accumulated doses, and dose linearity. Results and Discussion: In OSLD_exp, the average normalized counts (sensitivities) were 12.7%, 14.0%, 15.0%, 10.2%, 18.0%, 17.9%, and 17.3% higher compared with those in OSLD_cont for 75, 80, 90, 95, 100, and 105 kVp, respectively. The dose accumulation and bleaching time did not significantly alter the sensitivity, regardless of the filling of deep traps for all radiation qualities. Both OSLD_exp and OSLD_cont exhibited good linearity, by showing coefficients determination (R²) > 0.99. The OSL sensitivities can be increased by filling of deep electron/hole traps in the energy ranges between 75 and 105 kVp, and they exhibited no significant variations according to the bleaching time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.6
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• pp.655-662
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• 2012

Gas leakage in an oil refinery causes damage to the environment and unsafe conditions. Therefore, it is necessary to develop a technique that is able to detect the location of the leakage and to filter abnormal gas-leakage signals from normal background noise. In this study, the adaptation filter of the finite impulse response (FIR) least mean squares (LMS) algorithm and a cross-correlation function were used to develop a leakage-predicting program based on LABVIEW. Nitrogen gas at a high pressure of 120 kg/$cm^2$ and the assembled equipment were used to perform experiments in a reverberant chamber. Analysis of the data from the experiments performed with various hole sizes, pressures, distances, and frequencies indicated that the background noise occurred primarily at less than 1 kHz and that the leakage signal appeared in a high-frequency region of around 16 kHz. Measurement of the noise sources in an actual oil refinery revealed that the noise frequencies of pumps and compressors, which are two typical background noise sources in a petrochemical plant, were 2 kHz and 4.5 kHz, respectively. The fact that these two signals were separated clearly made it possible to distinguish leakage signals from background noises and, in addition, to detect the location of the leakage.

• Journal of the Korean Chemical Society
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• v.21 no.4
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• pp.293-303
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• 1977

Cellulosic organic solid wastes such as bark and sawdust, and filter papers as a pure cellulose were pyrolyzed at $300^{\circ}C$ under nitrogen current and mixed current of nitrogen and air. Amounts of condensates collected in air, water, and dry ice-acetone cooling traps, noncondensable gases, and carbonized residues were surveyed. The components of volatile liquids condensed in dry ice-acetone trap were separated by means of gas chromatograph and identified by retention times and syringe reactions. Pyrolysis under nitrogen current produced 13.4∼29.6${\%}$ of tar, 0.01∼0.12${\%}$ of aqueous liquids, 0.24∼1.43${\%}$ of volatile liquids, 9.84∼42.41${\%}$ of noncondensable gases, and 44.0∼65.81${\%}$ of carbonized residues. Pyrolysis under mixed current decreased tar and condensable liquids, but increased noncondensable gases.Volatile liquids collected under nitrogen current separated into the same 19 components by Porapak Q column regardless of the materials and only difference among materials was relative amounts of components. Volatile liquids collected under mixed current separated into six components and mainly lower molecular weight compounds such as methanol and formaldehyde were produced. According to the retention times and syringe reactions, methanol, formaldehyde, acetone, acetaldehyde, acetic acid, and three other compounds presumably containing hydroxyl group in the molecular structure were identified out of 19 compounds.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.17-34
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• 2023

Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.