• Title/Summary/Keyword: safety assessment input data

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Seismic analysis of a steam generator for Gyeongju and Pohang earthquakes

  • Myung Jo Jhung;Youngin Choi;Changsik Oh;Gangsig Shin;Chan Il Park
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1577-1586
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    • 2023
  • Safety qualification of a steam generator is a crucial issue related to faulted condition design loads, including earthquake loads, and it should be ensured that the structural integrity of a steam generator does not exceed its design load. Using data from the Gyeongju and Pohang earthquakes, the two most powerful recorded seismic events in Korea, seismic analyses of a typical steam generator are conducted in this study. The modal characteristics are used to develop an input deck for these analyses. With a time history analysis, the responses of the steam generator in the event of an earthquake are obtained. In particular, the displacement, velocity, and acceleration responses are obtained in the time domain, with these outcomes then used for a detailed structural analysis as part of the ensuing assessment. The response spectra are also generated to determine the response characteristics in the frequency domain, focusing on the response comparisons between the Gyeongju and Pohang earthquakes. Structural integrity can be ensured by performing additional analysis using results obtained from the time history analysis considering the input excitations of various earthquakes considered in the design.

The Development of the Anchor Dragging Risk Assessment Program (선박 주묘 위험성 판별 프로그램 개발에 관한 연구)

  • Kim, Joo-Sung;Park, Jun-Mo;Jung, Chang-Hyun
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.24 no.6
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    • pp.646-653
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    • 2018
  • Marine accidents caused by dragging anchors occur constantly due to enlargement of ships' size and unusual weather conditions. Nevertheless, vessel operators rely on their experience because the calculations of actual holding power and external forces are complex and inconvenient. The purpose of this study was to propose a program for the anchor dragging risk assessment in order to provide crew and VTSO with the information to determine easily the danger of dragging and take appropriate action. The input data in this program were composed of the ship's basic particulars, anchoring condition, and external environment etc. on calculating for the wind pressure, frictional force, drift force, and holding power. Three dragging anchor accidents were applied to the program's data input at the time of the day, then the result was assessed by 'warning', which was verified with a high confidence. As a result, the risk of dragging anchors can be predicted in advance through this program. In further studies, it is necessary to simplify the input data and improve user convenience through automatic input from various equipment.

Estimation of Wave Parameters for Probabilistic Tsunami Hazard Analysis Considering the Fault Sources in the Western Part of Japan (일본 서부 단층 지진원을 고려한 확률론적 지진해일 재해도 분석의 파고 변수 도출)

  • Rhee, Hyun-Me;Kim, Min Kyu;Sheen, Dong-Hoon;Choi, In-Kil
    • Journal of the Earthquake Engineering Society of Korea
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    • v.18 no.3
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    • pp.151-160
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    • 2014
  • Probabilistic tsunami hazard analysis (PTHA) is based on the approach of probabilistic seismic hazard analysis (PSHA) which is performed using various seismotectonic models and ground-motion prediction equations. The major difference between PTHA and PSHA is that PTHA requires the wave parameters of tsunami. The wave parameters can be estimated from tsunami propagation analysis. Therefore, a tsunami simulation analysis was conducted for the purpose of evaluating the wave parameters required for the PTHA of Uljin nuclear power plant (NPP) site. The tsunamigenic fault sources in the western part of Japan were chosen for the analysis. The wave heights for 80 rupture scenarios were numerically simulated. The synthetic tsunami waveforms were obtained around the Uljin NPP site. The results show that the wave heights are closely related with the location of the fault sources and the associated potential earthquake magnitudes. These wave parameters can be used as input data for the future PTHA study of the Uljin NPP site.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies

  • Azadeh, Ali;Sheikhalishahi, Mohammad
    • Safety and Health at Work
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    • v.6 no.2
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    • pp.77-84
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    • 2015
  • Background: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

SAFETY ANALYSIS METHODOLOGY FOR AGED CANDU® 6 NUCLEAR REACTORS

  • Hartmann, Wolfgang;Jung, Jong Yeob
    • Nuclear Engineering and Technology
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    • v.45 no.5
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    • pp.581-588
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    • 2013
  • This paper deals with the Safety Analysis for $CANDU^{(R)}$ 6 nuclear reactors as affected by main Heat Transport System (HTS) aging. Operational and aging related changes of the HTS throughout its lifetime may lead to restrictions in certain safety system settings and hence some restriction in performance under certain conditions. A step in confirming safe reactor operation is the tracking of relevant data and their corresponding interpretation by the use of appropriate thermal-hydraulic analytic models. Safety analyses ranging from the assessment of safety limits associated with the prevention of intermittent fuel sheath dryout for a slow Loss of Regulation (LOR) analysis and fission gas release after a fuel failure are summarized. Specifically for fission gas release, the thermal-hydraulic analysis for a fresh core and an 11 Effective Full Power Years (EFPY) aged core was summarized, leading to the most severe stagnation break sizes for the inlet feeder break and the channel failure time. Associated coolant conditions provide the input data for fuel analyses. Based on the thermal-hydraulic data, the fission product inventory under normal operating conditions may be calculated for both fresh and aged cores, and the fission gas release may be evaluated during the transient. This analysis plays a major role in determining possible radiation doses to the public after postulated accidents have occurred.

Fragility assessment of RC bridges using numerical analysis and artificial neural networks

  • Razzaghi, Mehran S.;Safarkhanlou, Mehrdad;Mosleh, Araliya;Hosseini, Parisa
    • Earthquakes and Structures
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    • v.15 no.4
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    • pp.431-441
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    • 2018
  • This study provides fragility-based assessment of seismic performance of reinforced concrete bridges. Seismic fragility curves were created using nonlinear analysis (NA) and artificial neural networks (ANNs). Nonlinear response history analyses were performed, in order to calculate the seismic performances of the bridges. To this end, 306 bridge-earthquake cases were considered. A multi-layered perceptron (MLP) neural network was implemented to predict the seismic performances of the selected bridges. The MLP neural networks considered herein consist of an input layer with four input vectors; two hidden layers and an output vector. In order to train ANNs, 70% of the numerical results were selected, and the remained 30% were employed for testing the reliability and validation of ANNs. Several structures of MLP neural networks were examined in order to obtain suitable neural networks. After achieving the most proper structure of neural network, it was used for generating new data. A total number of 600 new bridge-earthquake cases were generated based on neural simulation. Finally, probabilistic seismic safety analyses were conducted. Herein, fragility curves were developed using numerical results, neural predictions and the combination of numerical and neural data. Results of this study revealed that ANNs are suitable tools for predicting seismic performances of RC bridges. It was also shown that yield stresses of the reinforcements is one of the important sources of uncertainty in fragility analysis of RC bridges.

Comparative Study of Korean Workers' Exposure to Dichloromethane by Process Category between Work Environment Monitoring Program and ECETOC TRA (국내 디클로로메탄 제조·사용 사업장 근로자의 공정별 노출수준에 대한 작업환경측정값과 ECETOC TRA 모델값 비교연구)

  • Jeong, Sujin;Bae, Gyewan;Lee, Naroo
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.31 no.4
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    • pp.317-330
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    • 2021
  • Objectives: By law, companies in Korea must periodically measure workers' exposure to harmful chemicals (the system is called the Work Environment Monitoring Program (WMP)[a]) and report the results to the government. The government also measures exposure to monitor the WMP's reliability (called Reliability Assessment (RA) for WMP[b]). The issue is that measured data from these two sources are so different that the objectivity of WMP needs to be confirmed by comparing the results using the European Centre for Ecotoxicology and Toxicology of Chemicals' Targeted Risk Assessment (ECETOC TRA). Methods: Step 1: Data collection from WMP reports submitted by companies (n=586) and RA for WMP written by the government (n=33). Step 2: Data Standardization by key information included. Step 3: Data conversion to input-variables required to run the ECETOC TRA model, and run the model with specific data (n=514) which meet the predetermined exposure scenario. Step 4: Statistical data analysis by process category (PROC) and ventilation type from each source ([A] and [B]). Step 5: Additional analysis of any unexpected results. Results: The process categories of the production and handling of Dichloromethane were classified into 12 PROCs, and ten of them were selected to run ECETOC TRA. Modeled values tended to be higher than measured values from both sources. For the measured values from WMP, RCR distribution by PROC was narrow (0.197-0.267, 95% CI) and did not have a relationship with ventilation type, which differs from the tendency of the modeling result. Meanwhile, the measured values from RA for WMP were relatively widely distributed (0.301-1.177, 95% CI) by PROC. In particular PROCs (13,19) were high enough to exceed 1. Also, they become low with better ventilation types and appear differently depending on the ventilation type, similar to the model result. Conclusions: This study revealed that ECETOC TRA might have the potential to serve as a screening tool for exposure assessment and to be used as assistive method for WMP to estimate exposure. Further empirical study is required to confirm its availability as a screening tool.

Collision Risk Assessment for Pedestrians' Safety Using Neural Network (신경 회로망을 이용한 보행자와의 충돌 위험 판단 방법)

  • Kim, Beom-Seong;Park, Seong-Keun;Choi, Bae-Hoon;Kim, Eun-Tai;Lee, Hee-Jin;Kang, Hyung-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.1
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    • pp.6-11
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    • 2011
  • This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.

Model Algorithms for Estimates of Inhalation Exposure and Comparison between Exposure Estimates from Each Model (흡입 노출 모델 알고리즘의 구성과 시나리오 노출량 비교)

  • Park, Jihoon;Yoon, Chungsik
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.29 no.3
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    • pp.358-367
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    • 2019
  • Objectives: This study aimed to review model algorithms and input parameters applied to some exposure models and to compare the simulated estimates using an exposure scenario from each model. Methods: A total of five exposure models which can estimate inhalation exposure were selected; the Korea Ministry of Environment(KMOE) exposure model, European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment(ECETOC TRA), SprayExpo, and ConsExpo model. Algorithms and input parameters for exposure estimation were reviewed and the exposure scenario was used for comparing the modeled estimates. Results: Algorithms in each model commonly consist of the function combining physicochemical properties, use characteristics, user exposure factors, and environmental factors. The outputs including air concentration ($mg/m^3$) and inhaled dose(mg/kg/day) are estimated applying input parameters with the common factors to the algorithm. In particular, the input parameters needed to estimate are complicated among the models and models need more individual input parameters in addition to common factors. In case of CEM, it can be obtained more detailed exposure estimates separating user's breathing zone(near-field) and those at influencing zone(far-field) by two-box model. The modeled exposure estimates using the exposure scenario were similar between the models; they were ranged from 0.82 to $1.38mg/m^3$ for concentration and from 0.015 to 0.180 mg/kg/day for inhaled dose, respectively. Conclusions: Modeling technique can be used for a useful tool in the process of exposure assessment if the exposure data are scarce, but it is necessary to consider proper input parameters and exposure scenario which can affect the real exposure conditions.

Methodology of seismic-response-correlation-coefficient calculation for seismic probabilistic safety assessment of multi-unit nuclear power plants

  • Eem, Seunghyun;Choi, In-Kil;Yang, Beomjoo;Kwag, Shinyoung
    • Nuclear Engineering and Technology
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    • v.53 no.3
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    • pp.967-973
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    • 2021
  • In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.