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This model is then extended in order to model fault and recovery processes.
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Accident theories, metaphors and investigation methods are widely discussed; Hazard – Barrier – Target Model, Swiss Cheese Model, Bow-Tie Model, Fault Tree Analysis and Event Tree Analysis are explained.
The conceptual model fault for Model-1 and Model-2, divided into seven areas, (a)–(g).
The model fault traces (b, c and d) used in the inversion are shown by thick red lines.
The model fault could also switch directions and rupture south to north, as the Parkfield segment did in 2004.
Red lines with ticks are the model fault traces of the Futagawa and Hinagu faults used for the inversion analysis.
The proposed framework combines functional and behavioral modeling, fault injection and simulation.
By incorporating digraph models, fault trees and fuzzy inference mechanisms in a unified framework, a novel approach for fault diagnosis is developed in this work.
A novel multiple-model fault detection and isolation scheme for non-linear dynamic systems, that of a Neuro-Fuzzy Decoupling Fault Detection Scheme (NFDFDS) is presented, a hybrid scheme incorporating both neuro-fuzzy and model-based methods.
Advances in modeling including optimization, product modeling, fault detection and diagnostics, inverse models.
The major contribution is the presentation of adequate models that can be used to model fault-tolerant systems and generate the code automatically.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com