One of the significant safety issues in nuclear power plants is the rupture of steam generator tubes leading to the loss of radioactive primary coolant inventory and establishment of a path that would bypass the plant's containment structure. Frequency of steam generator tube ruptures is required in probabilistic safety assessments of pressurized water reactors to determine the risks of radionuclide release. The estimation of this frequency has traditionally been based on non-homogeneous historical data that are not applicable to small modular reactors consisting of new steam generator designs.
In this research a probabilistic mechanistic-based approach has been developed for assessing the frequency of steam generator tube ruptures. Physics-of-failure concept has been used to formulate mechanistic degradation models considering the underlying degradation conditions prevailing in steam generators. Uncertainties associated with unknown or partially known factors such as material properties, manufacturing methods, and model uncertainties have been characterized, and considered in the assessment of rupture frequency. An application of the tube rupture frequency assessment approach has been demonstrated for tubes of a typical helically-coiled steam generator proposed in most of the new small modular reactors. The tube rupture frequency estimated through the proposed approach is plant-specific and more representative for use in risk-informed safety assessment of small modular reactors.
Information regarding the health condition of steam generator tubes from in-service inspections may be used to update the pre-service estimates of tube rupture frequency. In-service inspection data are uncertain in nature due to detection uncertainties and measurement errors associated with nondestructive evaluation methods, which if not properly accounted for, can result in over- or under-estimation of tube rupture frequency. A Bayesian probabilistic approach has been developed in this research that combines prior knowledge on defects with uncertain in-service inspection data, considering all the associated uncertainties to give a probabilistic description of the real defect size and density in the tubes. An application of the proposed Bayesian approach has been provided. Defect size and density estimated through the proposed Bayesian approach can be used to update the pre-service estimates of tube rupture frequency, in order to support risk-informed maintenance and regulatory decision-making.
|Commitee:||Bruck, Hugh, Dieter, George, Mosleh, Ali, Wereley, Norman M.|
|School:||University of Maryland, College Park|
|School Location:||United States -- Maryland|
|Source:||DAI-B 73/12(E), Dissertation Abstracts International|
|Subjects:||Mechanical engineering, Nuclear engineering|
|Keywords:||Failure mechanisms, Nondestructive evaluation, Reliability, Ruptures, Small modular reactors, Steam generation|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be