Reliability Prediction of Passive Systems Based on Bivariate Probability Distributions

2008 ◽  
Vol 161 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Luciano Burgazzi
2010 ◽  
Vol 68 (1) ◽  
pp. 130-143 ◽  
Author(s):  
Philip J. Bacon ◽  
William S. C. Gurney ◽  
Eddie McKenzie ◽  
Bryce Whyte ◽  
Ronald Campbell ◽  
...  

Abstract Bacon, P. J., Gurney, W. S. C., McKenzie, E., Whyte, B., Campbell, R., Laughton, R., Smith, G., and MacLean, J. 2011. Objective determination of the sea age of Atlantic salmon from the sizes and dates of capture of individual fish. – ICES Journal of Marine Science, 68: 130–143. The sea ages of Atlantic salmon indicate crucial differences between oceanic feeding zones that have important implications for conservation and management. Historical fishery-catch records go back more than 100 years, but the reliability with which they discriminate between sea-age classes is uncertain. Research data from some 188 000 scale-aged Scottish salmon that included size (length, weight) and seasonal date of capture on return to the coast were investigated to devise a means of assigning sea age to individual fish objectively. Two simple bivariate probability distributions are described that discriminate between 1SW and 2SW fish with 97% reliability, and between 2SW and 3SW fish with 70% confidence. The same two probability distributions achieve this accuracy across five major east coast Scottish rivers and five decades. They also achieve the same exactitude for a smaller recent dataset from the Scottish west coast, from the River Tweed a century ago (1894/1895), and for salmon caught by rod near the estuary. More surprisingly, they also achieve the same success for rod-caught salmon taken at beats remote from the estuary and including capture dates when some fish could have been in the river for a few months. The implications of these findings for fishery management and conservation are discussed.


2004 ◽  
Vol 10 (2) ◽  
pp. 107-112 ◽  
Author(s):  
Romualdas Kliukas ◽  
Antanas Kudzys

An effect of service and proof actions on probabilistic reliability (serviceability, safety and durability) of building elements (components and members) of existing enclosure and bearing structures is under consideration. Time‐dependent models for reliability assessment of elements under sustained variable and multicycle actions are presented. Revised reliability indices of existing elements exposed to service permanent and variable actions are discussed. It is recommended to assess the long‐term reliability index of elements taking into account the effect of latent defects. Truncated probability distributions of physical‐mechanical resistances of elements and an effect of their latent defects on reliability index assessment are taken into account. Methodological peculiarities of durability prediction of elements and avoiding unfounded premature repairs or replacements are analysed. The applied illustration of the presented method on the probabilistic reliability prediction of deteriorating concrete covers is demonstrated.


2009 ◽  
Vol 2009 ◽  
pp. 1-18 ◽  
Author(s):  
Franco Pierro ◽  
Dino Araneo ◽  
Giorgio Galassi ◽  
Francesco D'Auria

The paper deals with the presentation of the Reliability Evaluation of Passive Safety System (REPAS) methodology developed by University of Pisa. The general objective of the REPAS is to characterize in an analytical way the performance of a passive system in order to increase the confidence toward its operation and to compare the performances of active and passive systems and the performances of different passive systems. The REPAS can be used in the design of the passive safety systems to assess their goodness and to optimize their costs. It may also provide numerical values that can be used in more complex safety assessment studies and it can be seen as a support to Probabilistic Safety Analysis studies. With regard to this, some examples in the application of the methodology are reported in the paper. A best-estimate thermal-hydraulic code, RELAP5, has been used to support the analyses and to model the selected systems. Probability distributions have been assigned to the uncertain input parameters through engineering judgment. Monte Carlo method has been used to propagate uncertainties and Wilks' formula has been taken into account to select sample size. Failure criterions are defined in terms of nonfulfillment of the defined design targets.


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