• Journal of Environmental Science International
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• v.33 no.2
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• pp.131-138
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• 2024

The effect of magnetite particles on the anaerobic digestion (AD) of furfural wastewater was investigated using sequential anaerobic batch tests. The batch tests with four 500 mL anaerobic bioreactors were performed under two conditions: FC treatment for AD of furfural without magnetite particles, and FM treatment for AD of furfural with magnetite particles. The FC bioreactors showed a decreasing methane production rate (MPR) across the sequential batches, with a final batch MPR of 11.3 ± 0.4 mL CH₄/L/d, indicating the need for a methanogenesis enhancer to achieve high-rate AD of furfural. Conversely, FM bioreactors exhibited significantly higher MPR, exceeding FC values by 4-196%, with a final batch MPR of 33.5 ± 0.1 mL CH₄/L/d, which was about three times higher than FC. Additionally, FM bioreactors had faster degradation rates of furfural, valeric acid, and acetic acid compared to FC, with values exceeding those in PC by 3.0, 1.14, and 2.8 times, respectively. These results demonstrate that magnetite particles can enhance the AD of furfural not only by accelerating methanogenesis but also by accelerating the anaerobic degradation of furfural and its intermediates, such as volatile fatty acids. This study provides valuable insights for developing high-rate AD systems for furfural wastewater treatment.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.6
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• pp.893-906
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• 2011

The effect of ultrasound pretreatment on sludge degragability was investigated at different condotions: ultrasonic frequency(28, 40, 50kHz), intensity(10, 25, 50W), sonication time(10, 20, 30, 60min). Total suspended solid(TSS) and soluble chemical oxygen demand(SCOD) concentration were measured for the evaluation of pretreatment efficiency. The pretreated sludge was used as the feedstock for anaerobic digestion process. Biogas production and volatile suspended solid(VSS) removal were determined for evaluating the process performance. 1. TSS concentration of the sludge decreased at a constant rate as sonication operation was applied. The degradation rate of TSS increased when ultrasound frequency was decreased from 50kHz to 28kHz and intensity was increased from 10W to 50W. Efficiency of TSS degradation per input energy increased as ultrasonic frequency and intensity were decreased. At the frequency of 28 and 40kHz, SCOD concentration rapidly increased during the initial 30min of sonication time, and then it gradually increased. At 50kHz, SCOD concentration constantly increased for 60min of the sonication time. The SCOD production rate increased with increasing intensity under all ultrasound frequencies. 2. The optimum condition of ultrasound treatment was 28kHz, 50W and 60min for maximizing the biogas production, methane fraction, VSS removal. The highest values in biogas production, methane fraction in biogas, VSS removal were 370ml, 70%, 2.45g, respectively. Methane production rate per input energy increased at ultrasonic frequency and intensity decreased. 3. When raw sludge was pretreated at the condition of ultrasonic frequency of 28 and 40kHz in series, sequential-frequency sonication, intensity of 50W and 60min, biogas production, methane fraction, VSS removal were about the same that of 28kHz single-frequency sonication. When sequential-frequency sonication of 28 and 50kHz was applied in series, biogas production, methane fraction, VSS removal were 356 ~ 423ml, 69 ~ 71%, 2.41 ~ 2.78g, respectively. The pretreatment efficiency of 28-50kHz sequential-frequency sonication which sonication time of 28kHz and 50kHz was 40min and 20min was higher than that of 28kHz single-frequency sonication.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.1-5
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• 2023

Most of the production process is performed in a cleanroom in the case of facilities that produce semiconductor chips or display panels. Therefore, environmental management of cleanrooms is very important for product yield and quality control. Among them, airborne particles are a representative management item enough to be the standard for the actual cleanroom rating, and it is a part of the Fab or Facility monitoring system, and the sequential particle monitoring system is mainly used. However, this method has a problem in that measurement efficiency decreases as the length of the sampling tube increases. In addition, a statistically significant test of deterioration in efficiency has rarely been performed. Therefore, in this study, the statistically significant test between the number of particles measured by InSitu and the number of particles measured for each sampling tube ends(Remote). Through this, the efficiency degradation problem of the sequential particle monitoring system was confirmed by a statistical method.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4514-4521
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• 2022

In this study, the effects of heat and radiation on the degradation behaviour of fluoroelastomer under simulated normal operation and a severe accident environment were investigated using sequential testing of gamma irradiation and thermal degradation. Tensile properties and Shore A hardness were measured, and thermogravimetric analysis was used to evaluate the degradation behaviour of fluoroelastomer. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy were used to characterize the structural changes of the fluoroelastomer. Heat and radiation generated in nuclear power plant break and deform the chemical bonds, and fluoroelastomer exposed to these environments have decreased C-H and functional groups that contain oxygen and double bonds such as C-O, C=O and C=C were generated. These functional groups were formed by auto oxidation by reacting free radicals generated from the cleaved bond with oxygen in the atmosphere. In this auto oxidation reaction, crosslinks were generated where bonded to each other, and the mobility of molecules was decreased, and as a result, the fluoroelastomer was hardened. This hardening behaviour occurred more significantly in the severe accident environment than in the normal operation condition, and it was found that thermal stability decreased with the generation of unstable structures by crosslinking.

• ETRI Journal
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• v.45 no.6
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.

• Selected Papers of The Society of Naval Architects of Korea
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• v.2 no.1
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• pp.106-128
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• 1994

An elasto-plastic-damage constitutive model for ductile materials is proposed within the framework of a thermodynamic approach of continuum damage mechanics (CDM) in which internal irreversible thermodynamic changes of micro-structure of materials such as plastic deformation and damage evolution are considered as thermodynamic state variables. The new constitutive model can predict not only the elasto-plastic behaviors but also the sequential stiffness degradation process of ductile materials more rationally.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.175-177
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• 1995

The sensor signal validation and failure detection system must be able to detect, isolate, and identify sensor degradation as well as provide a reconstruction of the measurements. In this study, this is accomplished by combining the neural network, the Generalized Consistency Checking(GCC), and the Sequential Probability Ratio Test(SPRT) method in a decision estimator module. The GCC method is a computationally efficient system for redundant sensors, while the SPRT provides the ability to make decisions based on the degradation history of a sensor. The methodology is also extended to the detection of noise degradation. The acceptability of the proposed method is demonstration by using the simulation data in safety injection accident of nuclear power plants. The results show that the signal validation and sensor failure detection system is able to detect and isolate a bias failure and noise type failures under transient conditions. And also, the system is able to provide the validated signal by reconstructing the measurement signals in the failure conditions considered.

• New & Renewable Energy
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• v.16 no.4
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• pp.83-91
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• 2020

In this study, the reusability of the Fenton oxidation solution was evaluated to reduce the cost of the pretreatment process. Biomass was sequential subjected to Fenton oxidation-hydrothermal treatment and enzymatic hydrolysis to produce monosaccharides. The liquid solution recovered after Fenton oxidation contained OH radicals with a concentration of 0.11 mol/L. This liquid solution was reused for a new Fenton oxidation reaction. After Fenton oxidation, hydrothermal treatment was performed under the same conditions as before, and 9.34-13.63 g/L of xylose was detected. This concentration was slightly lower than that of a fresh Fenton oxidation solution (16.51 g/L) but was higher than that obtained by hydrothermal treatment without Fenton oxidation (2.72 g/L). The degradation rate during hydrothermal pretreatment involving Fenton oxidation was 36.02%, which decreased (29.24-31.05%) slightly when the liquid solution recovered after Fenton oxidation was reused. However, the degradation rate increased compared to that measured from hydrothermal treatment without Fenton oxidation (15.21%). Moreover, the yield after enzyme hydrolysis decreased in the following order: fresh Fenton oxidation-hydrothermal treatment (89.64%) > Fenton oxidation with reused solution-hydrothermal treatment (74.84%) > hydrothermal treatment without Fenton oxidation (32.05%).

• Current Optics and Photonics
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• v.2 no.5
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• pp.422-430
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• 2018

Rolling shutter operation of CMOS cameras can be utilized in optical camera communications in order to transmit data from an LED to mobile devices such as smart-phones. From temporally modulated light, a spatial flicker pattern is obtained in the captured image, and this is used for signal recovery. Due to the degradation of rolling shutter images caused by light smear, motion blur, and focus blur, the conventional decoding schemes for rolling shutter cameras based on the pattern width for 'OFF' and 'ON' cannot guarantee robust communications performance for practical uses. Aside from conventional techniques, such as polynomial fitting, histogram equalization can be used for blurry light mitigation, but it requires additional computation abilities resulting in burdens on mobile devices. This paper proposes a transition-based decoding scheme for rolling shutter cameras in order to offer simple and robust data decoding in the presence of image degradation. Based on the designed synchronization pulse and modulated data symbols according to the LED dimming level, the decoding process is conducted by observing the transition patterns of two sequential symbol pulses. For this, the extended symbol pulse caused by consecutive symbol pulses with the same level determines whether the second pulse should be included for the next bit decoding or not. The proposed method simply identifies the transition patterns of sequential symbol pulses other than the pattern width of 'OFF' and 'ON' for data decoding, and thus, it is simpler and more accurate. Experimental results ensured that the transition-based decoding scheme is robust even in the presence of blurry lights in the captured image at various dimming levels

• Smart Structures and Systems
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• v.12 no.6
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.