• Nuclear Engineering and Technology
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• 제38권4호
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• pp.383-390
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• 2006

Having its roots in medical applications, industrial gamma ray CT has opened up new roads far investigating and modeling industrial processes. Using a line of research related to industrial gamma ray CT, the authors set up a system of single source and detector gamma transmission tomography for wood timber and a packed bed phantom. The hardware of the CT system consists of two servo motors, a data logger, a computer, a radiation source and a radiation detector. One motor simultaneously moves the source and the detector for a parallel beam scanning, whereas the other motor rotates the scan table at a preset projection angle. The image is reconstructed from the measured projections by the filtered back projection method. The phantom was designed to simulate a cross section of a packed bed with a void. The radiation source was 20mCi of Cs-137 and the detector was a 1 inch $\times$ 1 inch NaI (TI) scintillator shielded by a lead collimator. The experimental gamma ray CT image has sufficient resolution to reveal air holes and the density distribution inside the phantom. The system could possibly be applied to a packed bed column or a pipe flow in a petrochemical plant.

• Advances in Energy Research
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• 제1권2호
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• pp.127-146
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• 2013

Torrefaction technologies convert assorted biomass feedstocks into energy-concentrated, carbon neutral fuel that is economically transported and easily ground for blending with fossil coals at numerous power plants around the world without needs to retrofit. Utilization of torrefied biomass in conventional electric generating units may be an increasingly attractive alternative for electricity generation as aging power plants in the world need to be upgraded or improved. This paper examines the economic feasibility of torrefaction in different scenarios by modeling torrefaction plants producing 136,078 t/year (150,000 ton/year) biocoal from wood and corn stover. The utilization of biocoal blends in existing coal-fired power plants is modeled to determine the demand for this fuel in the context of emerging policies regulating emissions from coal in the U.S. setting. Opportunities to co-locate torrefaction facilities adjacent to corn ethanol plants and coal-fired power plants are explored as means to improve economics for collaborating businesses. Life cycle analysis was conducted in parallel to this economic study and was used to determine environmental impacts of converting biomass to biocoal for blending in coal-fired power plants as well as the use of substantial flows of off-gasses produced in the torrefaction process. Sensitivity analysis of the financial rates of return of the different businesses has been performed to measure impacts of different factors, whether input prices, output prices, or policy measures that render costs or rewards for the businesses.

• 한국가스학회지
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• 제2권3호
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• pp.12-17
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• 1998

공정의 위험성 평가를 위한 이상트리 작성은 많은 시간과 인력을 요하는 작업으로 대규모 화학공장에 적용하기가 매우 힘들다. 본 연구에서는 화학공정의 이상트리 합성을 위해서, 공정변수간의 인과관계를 나타내는 부호 유향그래프로 발생 가능한 모든 공정이상과 원인들을 표현하고, 부호 유향그래프상에 존재하는 경로특성에 따라 일반 조작자와 루프 조작자를 정의하여 이상사건의 원인을 탐색할 때 해당하는 경로의 특성에 맞는 조작자로 대치함으로써 이상트리를 자동합성하였다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(1)
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• pp.425-432
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• 1996

Integrated performance test of Chemical and Volume Control System (CVCS) was successfully performed in 1994. However, an extensive effort to correct hardware and software problems in the letdown line was required mainly due to the lack of adequate simulation code to predict the test accurately. Although the LTC computer code was used during the YGN 3'||'&'||'4 NSSS design process, the code can not satisfactorily predict the test due to its insufficient letdown line modeling. This study developed a numerical model to simulate the letdown test by modifying the current LTC code, and then verified the model by comparing with the test data. The comparison shows that the modified LTC computer code can predict the transient behavior of letdown system tests very well. Especially, the model was verified to be able to predict the "Stiction" phenomena which caused instantaneous fluctuations in the letdown backpressure and flowrate. Therefore, it is concluded that the modified LTC computer code with the ability of calculating the "Stiction" phenomena wi11 be very useful for future plant desist and test predictions.predictions.

• Natural Product Sciences
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• 제25권3호
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• pp.215-221
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• 2019

Inflammation is the crucial biological process of immune system which acts as body's defense and protective response against the injuries or infection. However, the systemic inflammation devotes the adverse effects such as multiple inflammation associated diseases. One of the best ways to treat this entity is by blocking the tumor necrosis factor alpha ($TNF-{\alpha}$) and TNF-related apoptosis-inducing ligand (TRAIL) to avoid the proinflammation cytokines production. Thus, this study aims to evaluate the potency of Sambucus bioactive compounds as anti-inflammation through in silico approach. In order to assess that, molecular docking was performed to evaluate the interaction properties between the $TNF-{\alpha}$ or TRAIL with the ligands. The 2D structure of ligands were retrieved online via PubChem and the 3D protein modeling was done by using SWISS Model. The prediction results of the study showed that caffeic acid (-6.4 kcal/mol) and homovanillic acid (-6.6 kcal/mol) have the greatest binding affinity against the $TNF-{\alpha}$ and TRAIL respectively. This evidence suggests that caffeic acid and homovanillic acid may potent as anti-inflammatory agent against the inflammation associated diseases. Finally, this study needs further examination and evaluation to validate the potency of Sambucus bioactive compounds.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3164-3182
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• 2023

The CRUD on the fuel cladding under the pressurized water reactor (PWR) operating condition causes several issues. The CRUD can act as thermal resistance and increases the local cladding temperature which accelerate the corrosion process. The hideout of boron inside the CRUD results in axial offset anomaly and reduces the plant's shutdown margin. Recently, there are efforts to revise the acceptance criteria of emergency core cooling systems (ECCS), and additionally require the modeling of the thermal resistance effect of the CRUD during the performance analysis. There is an urgent need for the evaluation of the effect of the CRUD deposition on the cladding heat transfer under PWR operating conditions, but the experimental database is very limited. The experimental facility called DISNY was designed and constructed to analyze the CRUD-related multi-physical phenomena, and the performance analysis of the constructed DISNY facility was conducted. The thermal-hydraulic and water chemistry conditions to simulate the CRUD growth under PWR operating conditions were established. The design characteristics and feasibility of the DISNY facility were validated by the MARS-KS code analysis and separate performance tests. In the current study, detailed design features, design validation results, and future utilization plans of the proposed DISNY facility are presented.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권2호
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• pp.459-470
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• 2014

During ship design, welding-induced distortions are roughly estimated as a function of the size of the component as well as the welding process and residual stresses are assumed to be locally in the range of the yield stress. Existing welding simulation methods are very complex and time-consuming and therefore not applicable to large structures like ships. Simplified methods for the estimation of welding effects were and still are subject of several research projects, but mostly concerning smaller structures. The main goal of this paper is the application of a multi-layer welding simulation to the block joint of a ship structure. When welding block joints, high constraints occur due to the ship structure which are assumed to result in accordingly high residual stresses. Constraints measured during construction were realized in a test plant for small-scale welding specimens in order to investigate their and other effects on the residual stresses. Associated welding simulations were successfully performed with fine-mesh finite element models. Further analyses showed that a courser mesh was also able to reproduce the welding-induced reaction forces and hence the residual stresses after some calibration. Based on the coarse modeling it was possible to perform the welding simulation at a block joint in order to investigate the influence of the resulting residual stresses on the behavior of the real structure, showing quite interesting stress distributions. Finally it is discussed whether smaller and idealized models of definite areas of the block joint can be used to achieve the same results offering possibilities to consider residual stresses in the design process.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2000년도 춘계학술발표대회
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• pp.125-128
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• 2000

본 연구에서는 순환식 돈분 폐수 처리 시스템에서의 미생물 분포에 따른 폐수 처리 효과를 모델링하기 위해 신경회로망과 PCA를 이용하는 새로운 방법을 제안하였다. PCA 분석 결과를 바탕으로 신경회로망의 최적 입력 조건을 찾고, 실측 데이터를 이용하여, 폐수 처리 시스템의 각 탱크를 별도로 학습함으로써 비교적 적은 수의 데이터에도 불구하고 정확한 모델링 결과를 얻었다. 제안한 시스템은 폐수 처리 시스템의 효과적인모니터링 시스템으로 사용할 수 있으며, 향후 실제 돈분 처리 시스템에서 원하는 기준의 방류수를 얻기 위한 최적의 입력조건 (미생물밀도 등)을 결정하는데 있어서 에뮬레이터로 사용될 수 있을 것으로 기대된다.

• 한국환경과학회지
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• 제25권11호
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• pp.1493-1498
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• 2016

The efficiencies of Gang-Byeon sewage treatment facilities, which are based on GPS-X modelling, were analysed and used to design recycle water treatment processes. The effluent of an aeration tank contained total kjeldahl nitrogen (TKN) of 1.8 mg/L with both C-1 and C-2 conditions, confirming that most ammonia nitrogen ($NH_3{^+}-N$) was converted to nitrate nitrogen ($NO_3{^-}-N$). The concentrations of $NH_3{^+}-N$ and $NO_3{^-}-N$ were found to be 222.5 and 227.2 mg/L, respectively, with C-1 conditions and 212.2 and 80.4 mg/L with C-2 conditions. Although C-2 conditions with higher organic matter yielded a slightly higher nitrogen removal efficiency, sufficient denitrification was not observed to meet the discharge standards. For the total nitrogen (T-N) removal efficiency, the final effluent concentrations of T-N were 293.8 mg/L with biochemical oxygen demand (BOD) of 2,500 mg/L, being about 1.5 times lower than that (445.3 mg/L) with BOD of 2,000 mg/L. Therefore, an external carbon source to increase the C/N ratio was required to get sufficient denitrification. During the winter period with temperature less than $10^{\circ}C$, the denitrification efficiency was dropped rapidly even with a high TKN concentration (1,500 mg/L). This indicates that unit reactors (anoxic/aerobic tanks) for winter need to be installed to increase the hydraulic retention time. Thus, to enhance nitrification and denitrification efficiencies, flexible operations with seasons are recommended for nitrification/anoxic/denitrification tanks.

• International Journal of Control, Automation, and Systems
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• 제1권2호
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.