Integrating Safety Critical Software System in Probabilistic Safety Assessment

Vinod, Gopika; Santosh, T.V.; Saraf, R.K.; Ghosh, A.K.

doi:10.1016/j.nucengdes.2008.02.028

Cited by 10 publications

(1 citation statement)

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“…Los modelos para estimar la evolución de la fiabilidad se clasifican a su vez en modelos de caja blanca o modelos de caja negra [90,91]. Para los modelos de caja blanca, se considera generalmente la fiabilidad de los componentes del sistema y el esquema de conexión de dichos componentes [92,93,94].…”

Section: Estimar Y Predecir La Evolución De La Fiabilidadunclassified

Estudio de la fiabilidad software, según defectos, en controladores de velocidad para robots autónomos móviles

Paz¹

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Section: Estimar Y Predecir La Evolución De La Fiabilidadunclassified

Estudio de la fiabilidad software, según defectos, en controladores de velocidad para robots autónomos móviles

Paz¹

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On Cost‐effective Reuse of Components in the Design of Complex Reconfigurable Systems

Aizpurua

Papadopoulos

Muxika

et al. 2017

Quality & Reliability Eng

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Design strategies that benefit from the reuse of system components can reduce costs while maintaining or increasing dependability-we use the term dependability to tie together reliability and availability. D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) is a methodology that supports the design of complex systems with a focus on reconfiguration and component reuse. D3H2 systematizes the identification of heterogeneous redundancies and optimizes the design of fault detection and reconfiguration mechanisms, by enabling the analysis of design alternatives with respect to dependability and cost. In this paper, we extend D3H2 for application to repairable systems. The method is extended with analysis capabilities allowing dependability assessment of complex reconfigurable systems. Analysed scenarios include time-dependencies between failure events and the corresponding reconfiguration actions. We demonstrate how D3H2 can support decisions about fault detection and reconfiguration that seek to improve dependability while reducing costs via application to a realistic railway case study.A high-level function consists of a set of Main Functions (MF), for example, train operating properly = {traction system OK, signalling system OK, braking system OK, air conditioning control OK, . . . }. Main functions are performed in possibly different Physical Locations (PLs), for example, a single air conditioning control implementation may span a whole train car, or each car compartment in a train car may have its own air conditioning control. A main function consists of a set of subfunctions (SF), for example, input, control and output subfunctions. A subfunction may have multiple implementations (#) to carry out the subfunction, and these are ordered with respect to their priority.

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