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Investigating ship system performance degradation and failure criticality using FMECA and Artificial Neural Networks
Published in C. Guedes Soares, T.A. Santos, Trends in Maritime Technology and Engineering Volume 2, 2022
Therefore, the criticality ranking based on risk use a combination of the consequence (severity) of the failure and the anticipated likelihood of the consequence occurring (ABS, 2015). Criticality analysis will highlight failure modes with probability of occurrence and severity of consequence, allowing corrective actions to be implemented where they produce greatest impact. Given the overall lack of reliability data for many marine systems and components, performing an assessment on qualitative level based on experience and knowledge of the system is sometimes the only means by which to achieve a meaningful criticality assessment. Accordingly, research presents the combination of FMECA and ANN for the investigation of mission critical components of a marine diesel generator. For the FMECA a survey was conducted based on presented in the form of common failures that contributes to about 40 per cent in DGs non availability. Therefore, respondents were asked to rank faults/failures based on 3 criteria on a linear scale from one (1) to ten (10). These criteria were Criticality, Severity and Likelihood as define below:
Relating Product Reliability to Risk
Published in Ali J Jamnia, Khaled Atua, Executing Design for Reliability within the Product Life Cycle, 2019
This type of analysis where the criticality of component failure on the overall functionality of the system or its outcome is considered is called failure modes and effects criticality analysis. This process was first outlined in MIL-STD-1629A in 1980. Later, in 1993, the Reliability Analysis Center (RAC), a Department of Defense Information Analysis Center, adopted this approach as a reliability evaluation/design technique. However, in 2006, IEC 60812, second edition, applied this methodology to risk analysis.
Risk Assessment Techniques and Methods of Approach
Published in D. Kofi Asante-Duah, Hazardous Waste Risk Assessment, 2021
Event trees and fault trees are not the only analytical tools available for performing a PRA. Although event tree and fault tree analyses are the most powerful methods in PRA, other relatively simpler and also more complex methods are available. Several so-called system analysis methods exist that can be used in addition to, or in support of, the event and fault tree approaches. Pertinent techniques include the following: Failure modes and effects analysis (FMEA), which identifies failure modes for the components of concern and traces their effects on other components, subsystems, and systems. This approach provides an orderly examination of the hazardous conditions in a system and is simple to apply. It includes an assessment of criticality and probability of occurrence of each potential component failure mode. It is an inductive analysis that systematically details, on a component-by-component basis, all possible failure modes and identifies their resulting effects on the system.Reliability Block Diagrams (RBDs), are models generated by an inductive process whereby a given system, divided into blocks representing distinct elements, is represented according to system-success pathways and scenarios.Hazard analysis (HAZAN), or hazard quantification, is limited to the identification of hazards and considerations of strategies to employ to avoid the hazards. It involves the estimation of the expected frequencies or probabilities of events with adverse or potentially adverse consequences.Hazard and operability study (HAZOP), is a systematic, inductive technique for identifying hazards and operability problems through an entire system using guide words to identify deviations leading to hazardous situations. After the serious hazards have been identified via a HAZOP study or some other qualitative approach, a quantitative examination would be performed. HAZOP highlights specific deviations for which mitigative measures need to be developed.
Numerical study of initiating phase of core disruptive accident in small sodium-cooled fast reactors with negative void reactivity
Published in Journal of Nuclear Science and Technology, 2023
Shinya Ishida, Yoshitaka Fukano, Yoshiharu Tobita, Yasushi Okano
The accident progression for the UTOP event with the small SFR was analyzed by SAS4A in the same way as for ULOF. Figures 11 and 12 show the calculated transition of the total reactivity, the normalized power, and various reactivities of the UTOP reference case. The UTOP event progression is summarized as follows: The positive reactivity insertion from the control rod withdrawal increased power.The power increase caused the fuel to melt, and the internal pressure increase caused the cladding to rupture.Negative reactivity due to the fuel dispersal and the coolant voiding caused by FCI results in power decrease.The wrapper tube melted and failed due to the heat transfer between the fuel and the wrapper tube.The prompt criticality (1.0$) was never exceeded throughout the initiating phase.
Development of Multiphysics Framework to Analyze Dynamic Gap Heat Transfer and Cross-Flow Effect on Partial Rod Ejection Accident
Published in Nuclear Science and Engineering, 2023
Awais Zahur, Muhammad Rizwan Ali, Deokjung Lee
For the HFP case, the peak reactivity added in the system is 1.16 $ at 107 ms. Prompt criticality (reactivity = 1 $) is achieved at 86.2, 86.6, 87.0, and 87.6 ms for the dynamic-1D, dynamic-SC, static-SC, and static-1D cases, respectively. Prompt criticality results in a rapid increase in the power and, subsequently, temperatures. Figure 8 shows that the reactivity and total core power at the end of the transient are higher for the dynamic gHTC cases. The effect of cross flow is not visible in Fig. 9. However, it clearly discriminates the dynamic/static gap effect. The minimum DNBR remains low (less safety margin) for the dynamic gap cases. This is because dynamic cases result in higher heat transfer to cladding and, thereby, to the coolant. The dynamic gap effect in the FP results in fast heat transfer from fuel to cladding. Thereby, the peak fuel temperature in this case is low compared with the static gap cases. Furthermore, fuel enthalpy is also lower in the dynamic gap cases owing to the high heat transfer, low fuel centerline, and low clad surface temperature. In the case of the HFP initial condition, the dynamic gap width predicted by FRAPTRAN initially is higher than the static fixed gap width [5640 W/(m2‧K)] considered in this work. Thereby, after the REA, the value of the dynamic gHTC remains higher than the static value. The peak values of the safety parameters with their respective times are shown in Table III.
Development of new treatment of fuel isotope vector in the core disruptive accident analysis of fast reactors
Published in Journal of Nuclear Science and Technology, 2023
Hirotaka Tagami, Shinya Ishida, Yoshiharu Tobita
After the axial dispersion, the disrupted core materials repeat one-dimensional vertical compaction and dispersion a few times until a wrapper tube failure and the reactivity oscillates. The result of the Pu-vector case shows that a spreading of core disruption with the first power peak increases one-dimensional broken fuel dispersion and compaction. The reactivity finally reaches a prompt criticality due to whole core sodium voiding and the one-dimensional disrupted fuel compaction before a wrapper tube failure. A transient in the fertile/fissile case is milder, because the core disruption slowly spreads due to the small first power peak and the spatially smooth distribution of SA powers. The reactivity in optimized case reaches prompt criticality similar to the Pu-vector case.