scholarly journals Scaleup tests and supporting research for the development of duct injection technology: Topical report No. 3, Task 3. 2: Scale-up testing; Topical report No. 4, Task 3. 3: Advanced configurations; Topical report No. 5, Task 3. 4: Process controls; Topical report No. 6, Task 3. 5: Failure modes; Task 3. 6: Waste characterization, Duct Injection Test Facility, Muskingum River Power Plant, Beverly, Ohio

1992 ◽  
Author(s):  
L.G. Felix ◽  
J.P. Gooch ◽  
R.L. Merritt ◽  
M.G. Klett ◽  
A.G. Demian ◽  
...  
Keyword(s):  
Power Plant ◽  
Failure Modes ◽  
Scale Up ◽  
Test Facility ◽  
Waste Characterization ◽  
Injection Test ◽  
Injection Technology ◽  
Process Controls

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

Component Test Facility (ComTest) Phase 1 Engineering for 760C (1400F) Advanced Ultra-Supercritical (A-USC) Steam Generator Development

2015 ◽  
Author(s):  
Paul S. Weitzel
Keyword(s):  
Power Plant ◽  
Engineering Design ◽  
Steam Generator ◽  
The United States ◽  
Department Of Energy ◽  
Test Facility ◽  
Plant Design ◽  
Front End ◽  
Operation And Maintenance ◽  
Component Test

Babcock & Wilcox Power Generation Group, Inc. (B&W) has received a competitively bid award from the United States (U.S.) Department of Energy to perform the preliminary front-end engineering design of an advanced ultra-supercritical (A-USC) steam superheater for a future A-USC component test program (ComTest) achieving 760C (1400F) steam temperature. The current award will provide the engineering data necessary for proceeding to detail engineering, manufacturing, construction and operation of a ComTest. The steam generator superheater would subsequently supply the steam to an A-USC intermediate pressure steam turbine. For this study the ComTest facility site is being considered at the Youngstown Thermal heating plant facility in Youngstown, Ohio. The ComTest program is important because it would place functioning A-USC components in operation and in coordinated boiler and turbine service. It is also important to introduce the power plant operation and maintenance personnel to the level of skills required and provide initial hands-on training experience. Preliminary fabrication, construction and commissioning plans are to be developed in the study. A follow-on project would eventually provide a means to exercise the complete supply chain events required to practice and refine the process for A-USC power plant design, supply, manufacture, construction, commissioning, operation and maintenance. Representative participants would then be able to transfer knowledge and recommendations to the industry. ComTest is conceived as firing natural gas in a separate standalone facility that will not jeopardize the host facility or suffer from conflicting requirements in the host plant’s mission that could sacrifice the nickel alloy components and not achieve the testing goals. ComTest will utilize smaller quantities of the expensive materials and reduce the risk in the first operational practice for A-USC technology in the U.S. Components at suitable scale in ComTest provide more assurance before applying them to a full size A-USC demonstration plant. The description of the pre-front-end engineering design study and current results will be presented.

scholarly journals Instrumenting full-scale Boron Injection Test Facility to support Atucha-2 NPP licensing

2018 ◽  
Vol 336 ◽  
pp. 154-162 ◽  
Author(s):  
Fabio Moretti ◽  
Fulvio Terzuoli ◽  
Francesco D'Auria ◽  
Oscar Mazzantini
Keyword(s):  
Full Scale ◽  
Test Facility ◽  
Injection Test

Onset of Gas Blowthrough During Melt Expulsion From a Hole in a RPV: Numerical Analysis Using the SIMMER Code

2006 ◽  
Author(s):  
Frank Kretzschmar
Keyword(s):  
Numerical Analysis ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Severe Accident ◽  
Core Material ◽  
Test Facility ◽  
Computer Codes ◽  
Direct Containment Heating ◽  
Heating Up

In the case of a severe accident in a nuclear power plant there is a residual risk, that the Reactor Pressure Vessel (RPV) does not withstand the thermal attack of the molten core material, of which the temperature can be about 3000 K. For the analysis of the processes governing melt dispersal and heating up of the containment atmosphere of a nuclear power plant in the case of such an event, it is important to know the time of the onset of gas blowthrough during the melt expulsion through the hole in the bottom of the RPV. In the test facility DISCO-C (Dispersion of Simulant Corium-Cold) at the FZK /6/, experiments were performed to furnish data for modeling Direct Containment Heating (DCH) processes in computer codes that will be used to extrapolate these results to the reactor case. DISCO-C models the RPV, the Reactor Coolant System (RCS), cavity and the annular subcompartments of a large European reactor in a scale 1:18. The liquid type, the initial liquid mass, the type of the driving gas and the size of the hole were varied in these experiments. We present results for the onset of the gas blowthrough that were reached by numerical analysis with the Multiphase-Code SIMMER. We compare the results with the experimental results from the DISCO-C experiments and with analytical correlations, given by other authors.

Condition Monitoring of a Nuclear Power Plant Check Valve Based on Acoustic Emission and a Neural Network

2005 ◽  
Vol 127 (3) ◽  
pp. 230-236 ◽  
Author(s):  
Min-Rae Lee ◽  
Joon-Hyun Lee ◽  
Jung-Teak Kim
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Condition Monitoring ◽  
Nuclear Power ◽  
Failure Modes ◽  
Check Valve ◽  
Flow Loop ◽  
Artificial Neural

The analysis of acoustic emission (AE) signals produced during object leakage is promising for condition monitoring of the components. In this study, an advanced condition monitoring technique based on acoustic emission detection and artificial neural networks was applied to a check valve, one of the components being used extensively in a safety system of a nuclear power plant. AE testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disk movement for valve degradation such as wear and leakage due to foreign object interference in a check valve. It is clearly demonstrated that the evaluation of different types of failure modes such as disk wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters. It is also shown that the leak size can be determined with an artificial neural network.

Failure Mode and Effect Analysis (FMEA) for Enhancing Reliability of Water Tube Boiler in Thermal Power Plant

2016 ◽  
Vol 8 (02) ◽  
pp. 79-86
Author(s):  
Kapil Dev Sharma ◽  
Shobhit Srivastava
Keyword(s):  
Power Plant ◽  
Failure Mode ◽  
Thermal Power Plant ◽  
Failure Modes ◽  
Thermal Power ◽  
Effect Analysis ◽  
Water Tube ◽  
Potential Failure ◽  
Fmea Method ◽  
Continuous Power

Failure mode and effect analysis is one of the QS-9000 quality system requirement supplements, with a wide applicability in all industrial fields. FMEA is the inductive failure analysis instruments which can be defined as a methodical group of activities intended to recognize and evaluate the potential failure modes of a product/ process and its effects with an aim to identify actions which could eliminate or reduce the chance of the potential failure before the problem occur. The purpose of this paper is to evaluate the FMEA research and application in the Thermal Power Plant Industry. The research will highlight the application of FMEA method to water tubes (WT) in boilers with an aim to find-out all the major and primary causes of boiler failure and reduce the breakdown for continuous power generation in the plant. Failure Mode and Effect Analysis technique is applied on most critical or serious parts (components) of the plant which having highest Risk Priority Number (RPN). Comparison is made between the quantitative results of FMEA and reliability field data from real tube systems. These results are discussed to establish relationships which are useful for future water tube designs.

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