Thermal Hydraulic Analysis of Severe Accident in PFBR

2010 ◽  
Author(s):  
K. Velusamy ◽  
P. Chellapandi ◽  
G. R. Raviprasan ◽  
P. Selvaraj ◽  
S. C. Chetal
Keyword(s):  
Atmospheric Pressure ◽  
Fluid Dynamic ◽  
Hydraulic Modeling ◽  
Severe Accident ◽  
Maximum Temperature ◽  
Maximum Pressure ◽  
Dynamic Calculation ◽  
Thermal Hydraulic Modeling ◽  
Thermal Hydraulic Analysis ◽  
Design Pressure

During a core disruptive accident (CDA), the amount of primary sodium that can be released to Reactor Containment Building (RCB) in Prototype Fast Breeder Reactor (PFBR) is estimated to be 350 kg/s, by a transient fluid dynamic calculation. The pressure and temperature evolutions inside RCB, due to consequent sodium fire have been estimated by a constant burning rate model, accounting for heat absorption by RCB wall, assuming RCB isolation based on area gamma monitors. The maximum pressure developed is 7000 Pa. In case RCB isolation is delayed, then the final pressure inside RCB reduces below atmospheric pressure due to cooling of RCB air. The negative pressure that can be developed is estimated by dynamic thermal hydraulic modeling of RCB air / wall to be −3500 Pa. These investigations were useful to arrive at the RCB design pressure. Following CDA, RCB is isolated for 40 days. During this period, the heat added to RCB is dissipated to atmosphere only by natural convection. Considering all the possible routes of heat addition to RCB, evolution of RCB wall temperature has been predicted using HEATING5 code. It is established that the maximum temperature in RCB wall is less than the permissible value.

scholarly journals Time Series Analysis on Incidence of Pulmonary Tuberculosis With Weather Factors During 2004-2017 in Guangdong Province, China

2021 ◽  
Author(s):  
Tianyu Qin ◽  
Yu Hao ◽  
Juan He
Keyword(s):  
Wind Speed ◽  
Atmospheric Pressure ◽  
Guangdong Province ◽  
Maximum Temperature ◽  
Maximum Pressure ◽  
Weather Factors ◽  
Sarima Model ◽  
Extreme Wind ◽  
Wind Speed Maximum ◽  
Extreme Wind Speed

Abstract Background: Although the occurrence of some infectious diseases including TB was found to be associated with specific weather factors, few studies have incorporated weather factors into the model to predict the incidence of tuberculosis (TB). We aimed to establish an accurate forecasting model using TB data in Guangdong Province, incorporating local weather factors.Methods: Data of sixteen meteorological variables (2003-2016) and the TB incidence data (2004-2016) of Guangdong were collected. Seasonal autoregressive integrated moving average (SARIMA) model was constructed based on the data. SARIMA model with weather factors as explanatory variables (SARIMAX) was performed to fit and predict TB incidence in 2017. Results: Maximum temperature, maximum daily rainfall, minimum relative humidity, mean vapor pressure, extreme wind speed, maximum atmospheric pressure, mean atmospheric pressure and illumination duration were significantly associated with log(TB incidence). After fitting the SARIMAX model, maximum pressure at lag 6 (β= -0.007, P < 0.05, 95% confidence interval (CI): -0.011, -0.002, mean square error (MSE): 0.279) was negatively associated with log(TB incidence), while extreme wind speed at lag 5 (β=0.009, P < 0.05, 95% CI: 0.005, 0.013, MSE: 0.143) was positively associated. SARIMAX (1, 1, 1) (0, 1, 1)12 with extreme wind speed at lag 5 was the best predictive model with lower Akaike information criterion (AIC) and MSE. The predicted monthly TB incidence all fall within the confidence intervals using this model. Conclusions: Weather factors have different effects on TB incidence in Guangdong. Incorporating meteorological factors into the model increased the accuracy of prediction.

Thermal-Hydraulic Modeling and Severe Accident Radionuclide Transport

1995 ◽  
Vol 112 (2) ◽  
pp. 238-249 ◽  
Author(s):  
F. Oriolo ◽  
W. Ambrosini ◽  
G. Fruttuoso ◽  
F. Parozzi ◽  
R. Fontana
Keyword(s):  
Hydraulic Modeling ◽  
Severe Accident ◽  
Radionuclide Transport ◽  
Thermal Hydraulic Modeling

scholarly journals Thermal-hydraulic analysis of LTS cables for the DEMO TF coil using simplified models

Nukleonika ◽  
2017 ◽  
Vol 62 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Monika Lewandowska ◽  
Aleksandra Dembkowska
Keyword(s):  
New Technologies ◽  
Heat Removal ◽  
Maximum Temperature ◽  
Maximum Pressure ◽  
Hydraulic Analysis ◽  
National Agency ◽  
Simplified Models ◽  
Design Concepts ◽  
Design Activities ◽  
Thermal Hydraulic Analysis

Abstract The conceptual design activities for the DEMOnstration reactor (DEMO) – the prototype fusion power plant – are conducted in Europe by the EUROfusion Consortium. In 2015, three design concepts of the DEMO toroidal field (TF) coil were proposed by Swiss Plasma Center (EPFL-SPC, PSI Villigen), Italian National Agency for New Technologies (ENEA Frascati), and Atomic Energy and Alternative Energies Commission (CEA Cadarache). The proposed conductor designs were subjected to complete mechanical, electromagnetic, and thermal-hydraulic analyses. The present study is focused on the thermal-hydraulic analysis of the candidate conductor designs using simplified models. It includes (a) hydraulic analysis, (b) heat removal analysis, and (c) assessment of the maximum temperature and the maximum pressure in each conductor during quench. The performed analysis, aimed at verification whether the proposed design concepts fulfil the established acceptance criteria, provides the information for further improvements of the coil and conductors design.

scholarly journals Thermal-hydraulic modeling of reactivity accidents in MTR reactors

2006 ◽  
Vol 21 (2) ◽  
pp. 21-32 ◽  
Author(s):  
Hany Khater ◽  
Talal Abu-El-Maty ◽  
El-Din El-Morshdy
Keyword(s):  
Present Model ◽  
Reactor Core ◽  
Hydraulic Modeling ◽  
Control Rod ◽  
Reactor Kinetics ◽  
Fortran Language ◽  
Thermal Hydraulic Modeling ◽  
Thermal Hydraulic Analysis ◽  
Reactivity Insertion ◽  
Good Agreement

This paper describes the development of a dynamic model for the thermal-hydraulic analysis of MTR research reactors during a reactivity insertion accident. The model is formulated for coupling reactor kinetics with feedback reactivity and reactor core thermal-hydraulics. To represent the reactor core, two types of channels are considered, average and hot channels. The developed computer program is compiled and executed on a personal computer, using the FORTRAN language. The model is validated by safety-related benchmark calculations for MTR-TYPE reactors of IAEA 10 MW generic reactor for both slow and fast reactivity insertion transients. A good agreement is shown between the present model and the benchmark calculations. Then, the model is used for simulating the uncontrolled withdrawal of a control rod of an ETRR-2 reactor in transient with over power scram trip. The model results for ETRR-2 are analyzed and discussed.

Comparison of Thermal Hydraulic Simulations of Beyond Design Basis Events Using the MAAP4 and CENTS Computer Codes

2009 ◽  
Author(s):  
N. Reed LaBarge ◽  
Barbara R. Baron ◽  
Raymond E. Schneider ◽  
Mathew C. Jacob
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Computer Code ◽  
Hydraulic Modeling ◽  
Severe Accident ◽  
Pressurized Water ◽  
Design Basis ◽  
Best Estimate ◽  
Water Reactors ◽  
Thermal Hydraulic Modeling

The MAAP4 computer code (Reference 1) is often used to perform thermal hydraulic simulations of severe accident sequences for nuclear power plant Probabilistic Risk Assessments (PRAs). MAAP4 can be used to simulate accidents for both Boiling Water Reactors (BWRs) as well as Pressurized Water Reactors (PWRs). This assessment employs MAAP 4.0.6a for PWRs (References 1 and 5), which incorporates explicit thermal hydraulic modeling of the Reactor Coolant System (RCS) and Steam Generators (SGs), along with a nodalized integrated containment model. In the PRA environment, MAAP4 has been used for applications such as the development of PRA Level 1 and Level 2 success criteria and human action timings. The CENTS computer code (Reference 2) is a simulation tool that is typically used to analyze non-Loss of Coolant Accident (non-LOCA) events postulated to occur in nuclear power plants incorporating Combustion Engineering (CE) and Westinghouse Nuclear Steam Supply System (NSSS) designs. It is licensed by the NRC perform design basis non-LOCA safety analyses. It is a best estimate code which uses detailed thermal hydraulic modeling of the RCS and SGs; however, it does not model the containment performance. It is used to perform a wide spectrum of licensing and best estimate non-LOCA event analysis and has the capability to simulate operator actions. The CENTS models are the basis for several full scope simulators in the industry. The purpose of the analyses described in this paper is to compare MAAP4 and CENTS predictions for the Station Blackout (SBO) and Total Loss of Feedwater (TLOFW) scenarios for a representative PWR in the Westinghouse fleet that employs a CE NSSS design. The results of this comparison are used to highlight postulated MAAP4 user challenges and assist in developing guidance on selecting MAAP4 parameters for use in these scenarios. The results of the analyses presented in this paper indicate several useful insights. Overall, this paper shows that when care is taken to normalize the MAAP4 and CENTS primary side natural circulation flowrate and SG modeling, the trends of the MAAP4 and CENTS predictions of core uncovery agree reasonably well.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

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