• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.12
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• pp.1265-1273
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• 2015

A coal handling machine is a type of equipment used for loading coal, the main material in a steam power plant, along a conveyer belt from a ship, and is placed after the driving chain bucket. However, studies on the boom hoisting cylinder, which is a hydraulic system used to control the angle of the boom based on loading location, indicate that domestic models are insufficient, and are thereby often substituted with a foreign product. In this study, a technique for analyzing the contact pressure in a thick-walled cylinder was established by comparing the contact pressure, which is calculated theoretically based on the results obtained from FEM simulation, and by checking whether the working oil is leaking from the boom hoisting cylinder using a v-seal. In addition, the driving motion was simulated according to the strokes of the cylinder, and the structural stability was verified under the maximum output conditions.

• Plant Journal
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• v.9 no.4
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• pp.26-30
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• 2013

Based on case that HRSG low pressure steam generator tube was damaged by FAC in 500 MW A CCPP. This case analyzed the effect of application about the block of hydrazine water treatment which is applied for increasing dissolved oxygen. And also try to deduce the major factor of FAC Which is caused by lacking of dissolved oxygen of boiler feed system. After 1 year of water treatment, the figure of dissolved oxygen in the boiler feed water has increased from 0.15 ppb to 3~5 ppb and the figure of oxidation reduction potential has increased from -245 mV to 170 mV. And Iron content, the corrosion products by FAC has decreased from 18.5 ppb to 5~7 ppb. According to the result of experiment, we could able to confirm that the interception of hydrazine of water treatment is effective to reduce FAC.

• Corrosion Science and Technology
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• v.12 no.3
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• pp.125-131
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• 2013

The most common pipe wall thinning degradation mechanisms that can occur in the steam and feedwater systems are FAC (Flow Acceleration Corrosion), cavitation, flashing, and LDIE (Liquid Droplet Impingement Erosion). Among those degradation mechanisms, FAC has been investigated by many laboratories and industries. Cavitation and flashing are also protected on the piping design phase. LDIE has mainly investigated in aviation industry and turbine blade manufactures. On the other hand, LDIE has been little studied in NPP (Nuclear Power Plant) industry. This paper presents the development of prediction system for pipe wall thinning caused by LDIE in terms of erosion rate based on air-water ratio and material. Experiment is conducted in 3 cases of air-water ratio 0.79, 1.00, and 1.72 using the three types of the materials of A106B, SS400, and A6061. The main control parameter is the air-water ratio which is defined as the volumetric ratio of water to air (0.79, 1.00, 1.72). The experiments were performed for 15 days, and the surface morphology and hardness of the materials were examined for every 5 days. Since the spraying velocity (v) of liquid droplets and their contact area ($A_c$) on specimens are changed according to the air-water ratio, we analyzed the behavior of LDIE for the materials. Finally, the prediction equations(i.e. erosion rate) for LDIE of the materials were determined in the range of the air-water ratio from 0 to 2%.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.426-433
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• 2002

In this paper, we have studied the images which have been reconstructed by using combination of images acquired by the variation of operating frequency. When inner images have been reconstructed, they have been superposed by the surface state effect. In this case, the images of the phase object can be enhanced by the contrast of inner images. In this experiment, there are two kinds of specimens, one is a reference block haying 1/4T, 1/2T, 3/4T side drilled holes as main run piping material 111 the steam generator in NPP(Neuclear Power Plant)s and the another is a part of a hemisphere type specimen having about 1-2㎜ distance gap. It has been shown that the two results of defect shapes have better than before in this processing and phase contrast grow about twice. And we have constructed the acoustic microscope by using a quadrature detector that enables to acquire the amplitude and phase of the reflected signal simultaneously Further more ore have studied the reconstruction method of the amplitude and phase images and the enhancement method of the defect images contrast.

• Tribology and Lubricants
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• v.37 no.3
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• pp.99-105
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• 2021

In this study, for a high-pressure turbine (HPT) of 800 MW class supercritical thermal-power plant, considering aerodynamic cross-coupling, we performed a rotordynamic logarithmic decrement (LogDec) stability analysis with various tilting pad journal bearing (TPJB) designs, which several steam turbine OEMs (original equipment manufacturers) currently apply in their supercritical and ultra-supercritical HPTs. We considered the following TPJB designs: 6-Pad load on pad (LOP)/load between pad (LBP), 5-Pad LOP/LBP, Hybrid 3-Pad LOP (lower 3-Pad tilting and upper 1-Pad fixed), and 5-Pad LBPs with the design variables of offset and preload. We used the API Level-I method for a LogDec stability analysis. Following results are summarized only in a standpoint of LogDec stability. The Hybrid 3-Pad LOP TPJBs most excellently outperform all the other TPJBs over nearly a full range of cross-coupled stiffness. In a high range of cross-coupled stiffness, both the 6-Pad LOP and 5-Pad LOP TPJBs may be recommended as a practical conservative bearing design approach for enhancing a rotordynamic stability of the HPT. As expected, in a high range of cross-coupled stiffness, the 6-Pad LBP TPJBs exhibit a better performance than the 5-Pad LBP TPJBs. However, contrary to one's expectation, notably, the 5-Pad LOP TPJBs exhibit a slightly better performance than the 6-Pad LOP TPJBs. Furthermore, we do not recommend any TPJB design efforts of either increasing a pad offset from 0.5 or a pad preload from 0 for the HPT in a standpoint of stability.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.880-885
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• 2024

For Safety Assisted Engineering works, real-time simulators have emerged as a mandatory tool among all the key actors involved in the nuclear industry (utilities, designers and safety authorities). EDF, Electricité de France, as the leading worldwide nuclear power plant operator, has a crucial need for efficient and updated simulation tools for training, operating and safety analysis support. This paper will present the work performed at EDF/DT to develop a new generation of engineering simulator to fulfil these tasks. The project is called SiRENE, which is the acronym of Re-hosted Engineering Simulator in French. The project has been economically challenging. Therefore, to benefit from existing tools and experience, the SiRENE project combines: - A part of the process issued from the operating fleet training full-scope simulator. - An improvement of the simulator prediction reliability with the integration of High-Fidelity models, used in Safety Analysis. These High-Fidelity models address Nuclear Steam Supply System code, with CATHARE thermal-hydraulics system code and neutronics, with COCCINELLE code. - And taking advantage of the last generation and improvements of instructor station. The intensive and challenging uses of the new SiRENE engineering simulator are also discussed. The SiRENE simulator has to address different topics such as verification and validation of operating procedures, identification of safety paths, tests of I&C developments or modifications, tests on hydraulics system components (pump, valve etc.), support studies for Probabilistic Safety Analysis (PSA). etc. It also emerges that SiRENE simulator is a valuable tool for self-training of the newcomers in EDF nuclear engineering centers. As a modifiable tool and thanks to a skillful team managing the SiRENE project, specific and adapted modifications can be taken into account very quickly, in order to provide the best answers for our users' specific issues. Finally, the SiRENE simulator, and the associated configurations, has been distributed among the different engineering centers at EDF (DT in Lyon, DIPDE in Marseille and CNEPE in Tours). This distribution highlights a strong synergy and complementarity of the different engineering institutes at EDF, working together for a safer and a more profitable operating fleet.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.4
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• pp.211-217
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• 2001

Physical oceanographic environments in the coastal sea of Chung-Moon located in the south coast of Cheju Island, Korea, where water pollutions by growing tourism complex possibly start to influence on the ecological system, are studied with hydrographic data observed monthly during July 1997 to June 2000. Winter and summer characteristics are shown in December to April and June to October, respectively, and transitional characteristics are shown in May and November. Waters show 14{\sim}16^{\circ}C$ and 34${\sim}$34.7 psu in winter and $15{\sim}27^{\circ}C$ and 32${\sim}$34.3 psu in summer. It tells that Tsushima water distributes in the whole column in winter and in the lower layer in summer, and Yangtze coastal water appears in the surface water in summer. When the influence of Yangtze coastal water is strong, salinities below 30psu are shown. Stratification is formed in the depth of about 20 m from June to October, so that it is not shown in the near shore stations, of which the depth is about10 m. Isotherms and isohalines sometimes tend to be perpendicular to the coast line in the surface, which seems to show influences from the steam power plant near St. 1 and the sewage disposal plant near St. 3. During the observation period, temperatures in St. 1 are a little higher than those in St. 2 and St. 3 except for a couple of months in summer and salinities in St. 3 are mostly a little lower than those in St. 1 and St. 2. Their effects seem to be no more than $0.4^{\circ}C$ in a distance of 300 m and no more than 0.1 psu within a distance of 30 m.