Dependent failures developments

Dependent failures, or multiple related failures, destroy the assumption of independence of component failures which is used in the synthesis of system reliability. To obtain an understanding of the impact of dependencies on the reliability of a system, the analyst needs to have knowledge of the root causes of related failures, the coupling mechanism that allows single failures to combine to create a dependent event, and the potential defences that could be introduced to mitigate against a dependency. An assessment of dependencies also benefits from the application of a structured analysis, combining engineering knowledge of a system, together with generic and plant-specific data into a model which will lead to the quantification of the impact of dependencies on system reliability.This paper describes some of the developments that have taken place in recent years with the objective of improving the modelling of dependencies and the classification and coding of multiple related failure data. The development of procedures to provide a structured assessment of dependent failures within a probabilistic safety assessment is also described, together with the development of a database for the storage and retrieval of multiple related failure data.     

Sequential application of heterogeneous models for the safetyanalysis of a control system: a case study

This paper shows how heterogeneous stochastic modelling techniques of increasing modelling power can be applied to assess the safety of a digital control system. First, a Fault-Tree (FT) has been built to model the system, assuming two-state components and independent failures. Then, the FT is automatically converted into a Bayesian Network, allowing to include more modelling details and localized dependencies. Finally, in order to accommodate repair activities and perform an availability analysis, the FT is converted into a Stochastic Petri Net (SPN). Moving from a combinatorial model (the FT) to a state space based model (the SPN) increases the modelling flexibility, but incurs into the state space explosion problem. In order to alleviate the state space explosion problem, this paper resorts to the use of a particular type of high level (coloured) Petri nets called SWN. A digital control system is considered as a case study, and safety measures have been evaluated, referring to the emergent standard IEC 61508.     

Electron shuttle instability for nano electromechanical mass sensing

We discuss the potential use of the electromechanical shuttle instability in suspended nanostructures (e.g., nanotubes or nanowires) for nanomechanical sensing. The tunneling-assisted (shuttle-like) electron transport mechanism is addressed from a mechanical and electromechanical point of view, showing strong dependencies on the fundamental frequency, the mechanical restoring and damping force, and the electromechanical charging of the suspended nanostructure. We propose to use these nonlinear dependencies to sense minute mass (and tension) changes. Therefore, we introduce a conceptual sensing device and investigate its operation in the frame of a simple model system. Finally, we discuss different measurement techniques and report on high sensitivities (e.g., 1 nA/zeptogram (zg), or 1 mV/zg depending on the measurement technique) and potential resolutions in the range of 10 zg (10(-23) kg).     

Coherence region of the Priority‐AND gate: Analytical and numerical examples

In recent years, the need for a more accurate dependability modelling (encompassing reliability, availability, maintenance, and safety) has favoured the emergence of novel dynamic dependability techniques able to account for temporal and stochastic dependencies of a system. One of the most successful and widely used methods is Dynamic Fault Tree that, with the introduction of the dynamic gates, enables the analysis of dynamic failure logic systems such as fault‐tolerant or reconfigurable systems. Among the dynamic gates, Priority‐AND (PAND) is one of the most frequently used gates for the specification and analysis of event sequences. Despite the numerous modelling contributions addressing the resolution of the PAND gate, its failure logic and the consequences for the coherence behaviour of the system need to be examined to understand its effects for engineering decision‐making scenarios including design optimization and sensitivity analysis. Accordingly, the aim of this short communication is to analyse the coherence region of the PAND gate so as to determine the coherence bounds and improve the efficacy of the dynamic dependability modelling process.     

Do not blame the driver: A systems analysis of the causes of road freight crashes

Although many have advocated a systems approach in road transportation, this view has not meaningfully penetrated road safety research, practice or policy. In this study, a systems theory-based approach, Rasmussens’s (1997) risk management framework and associated Accimap technique, is applied to the analysis of road freight transportation crashes. Twenty-seven highway crash investigation reports were downloaded from the National Transport Safety Bureau website. Thematic analysis was used to identify the complex system of contributory factors, and relationships, identified within the reports. The Accimap technique was then used to represent the linkages and dependencies within and across system levels in the road freight transportation industry and to identify common factors and interactions across multiple crashes. The results demonstrate how a systems approach can increase knowledge in this safety critical domain, while the findings can be used to guide prevention efforts and the development of system-based investigation processes for the heavy vehicle industry. A research agenda for developing an investigation technique to better support the application of the Accimap technique by practitioners in road freight transportation industry is proposed.     

Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability

While the event-tree (ET)/fault-tree (FT) methodology is the most popular approach to probability risk assessment (PRA), concerns have been raised in the literature regarding its potential limitations in the reliability modeling of dynamic systems. Markov reliability models have the ability to capture the statistical dependencies between failure events that can arise in complex dynamic systems. A methodology is presented that combines Markov modeling with the cell-to-cell mapping technique (CCMT) to construct dynamic ETs/FTs and addresses the concerns with the traditional ET/FT methodology. The approach is demonstrated using a simple water level control system. It is also shown how the generated ETs/FTs can be incorporated into an existing PRA so that only the (sub)systems requiring dynamic methods need to be analyzed using this approach while still leveraging the static model of the rest of the system.     

Eliciting conditional and unconditional rank correlations from conditional probabilities

Causes of uncertainties may be interrelated and may introduce dependencies. Ignoring these dependencies may lead to large errors. A number of graphical models in probability theory such as dependence trees, vines and (continuous) Bayesian belief nets [Cooke RM. Markov and entropy properties of tree and vine-dependent variables. In: Proceedings of the ASA section on Bayesian statistical science, 1997; Kurowicka D, Cooke RM. Distribution-free continuous Bayesian belief nets. In: Proceedings of mathematical methods in reliability conference, 2004; Bedford TJ, Cooke RM. Vines—a new graphical model for dependent random variables. Ann Stat 2002; 30(4):1031–68; Kurowicka D, Cooke RM. Uncertainty analysis with high dimensional dependence modelling. New York: Wiley; 2006; Hanea AM, et al. Hybrid methods for quantifying and analyzing Bayesian belief nets. In: Proceedings of the 2005 ENBIS5 conference, 2005; Shachter RD, Kenley CR. Gaussian influence diagrams. Manage Sci 1998; 35(5) [15].] have been developed to capture dependencies between random variables. The input for these models are various marginal distributions and dependence information, usually in the form of conditional rank correlations. Often expert elicitation is required. This paper focuses on dependence representation, and dependence elicitation. The techniques presented are illustrated with an application from aviation safety.     

DEPEND-HRA—A method for consideration of dependency in human reliability analysis

A consideration of dependencies between human actions is an important issue within the human reliability analysis. A method was developed, which integrates the features of existing methods and the experience from a full scope plant simulator. The method is used on real plant-specific human reliability analysis as a part of the probabilistic safety assessment of a nuclear power plant. The method distinguishes dependency for pre-initiator events from dependency for initiator and post-initiator events. The method identifies dependencies based on scenarios, where consecutive human actions are modeled, and based on a list of minimal cut sets, which is obtained by running the minimal cut set analysis considering high values of human error probabilities in the evaluation. A large example study, which consisted of a large number of human failure events, demonstrated the applicability of the method. Comparative analyses that were performed show that both selection of dependency method and selection of dependency levels within the method largely impact the results of probabilistic safety assessment. If the core damage frequency is not impacted much, the listings of important basic events in terms of risk increase and risk decrease factors may change considerably. More efforts are needed on the subject, which will prepare the background for more detailed guidelines, which will remove the subjectivity from the evaluations as much as it is possible.     

Risk-significant functional dependencies in pressurized water reactors

This work provides evidence that functional dependencies among nuclear plant systems, particularly those among frontline safety systems and support systems, are often major contributors to the calculated risks in completed probabilistic risk assessments (PRAs). The study, furthermore, determined how the risk impact of functional dependencies could be reduced in future nuclear power plant designs. The risk reduction insights are summarized by a set of nine generalized design approaches, which we call design principles. These approaches are not new to the nuclear industry nor are the dependencies they address. The contribution made by this study is the use of PRA insights in pointing out the relative importance of the dependencies in terms of their contributions to risk.     

Oxygen defects in irradiated germanium

The defects present in oxygen-rich irradiated germanium have been extensively characterised from an experimental point of view. Here, we summarise recent theoretical findings obtained using the cluster method and discuss their relation with the experimental data. In order to find a microscopic interpretation of the reactions taking place in this material upon annealing up to 400°C, we performed nudged elastic band (NEB) calculations of the migration and dissociation paths of VO, as well as a modelling of other oxygen-related complexes that are expected to form in this temperature range. Energy barriers of 1.5 (1.1) eV and 1.2 (0.9) eV for the dissociation and migration of the neutral (negatively charged) VO defect are found. We compare these with the activation energies estimated from the analysis of Hall effect, deep level transient spectroscopy (DLTS) and infra-red (IR) spectroscopy annealing data reported in literature.     

Data-driven cardiovascular flow modelling: examples and opportunities

High-fidelity blood flow modelling is crucial for enhancing our understanding of cardiovascular disease. Despite significant advances in computational and experimental characterization of blood flow, the knowledge that we can acquire from such investigations remains limited by the presence of uncertainty in parameters, low resolution, and measurement noise. Additionally, extracting useful information from these datasets is challenging. Data-driven modelling techniques have the potential to overcome these challenges and transform cardiovascular flow modelling. Here, we review several data-driven modelling techniques, highlight the common ideas and principles that emerge across numerous such techniques, and provide illustrative examples of how they could be used in the context of cardiovascular fluid mechanics. In particular, we discuss principal component analysis (PCA), robust PCA, compressed sensing, the Kalman filter for data assimilation, low-rank data recovery, and several additional methods for reduced-order modelling of cardiovascular flows, including the dynamic mode decomposition and the sparse identification of nonlinear dynamics. All techniques are presented in the context of cardiovascular flows with simple examples. These data-driven modelling techniques have the potential to transform computational and experimental cardiovascular research, and we discuss challenges and opportunities in applying these techniques in the field, looking ultimately towards data-driven patient-specific blood flow modelling.     

Analysis and synthesis of the behaviour of complex programmable electronic systems in conditions of failure

This paper introduces a new method for safety analysis which modifies, automates and integrates a number of classical safety analysis techniques to address some of the problems currently encountered in complex safety assessments. The method enables the analysis of a complex programmable electronic system from the functional level through to low levels of its hardware and software implementation. In the course of the assessment, the method integrates design and safety analysis and harmonises hardware safety analysis with the hazard analysis of software architectures. It also introduces an algorithm for the synthesis of fault trees, which mechanises and simplifies a large and traditionally problematic part of the assessment, the development of fault trees. In this paper, we present the method and discuss its application on a prototypical distributed brake-by-wire system for cars. We argue that the method can help us rationalise and simplify an inherently creative and difficult task and therefore gain a consistent and meaningful picture of how a complex programmable system behaves in conditions of failure.     

Determination of the relaxation function for viscoelastic materials at low velocity impact

The work discusses impact microindentation and its possible application for determination and control of physico-mechanical characteristics of viscoelastic materials. Technique and algorithm for determination of the relaxation function at the dynamic intrusion of the indenter into the viscoelastic half-space are proposed. Experimental dependencies for intrusion of spherical and conical indenter into rubber in the range of initial velocities 0.3–3 m/s were established. It was shown that obtained results do not depend on the shape of the indenter tip and its velocity. The analysis of the results was carried out from the point of view of time and temperature dependencies that are typical for elastomers. Obtained results can be used for analysis and prediction of elastomeric material's response to the applied load with consideration of the loading history.     

Integrated mechanistic and data-driven modelling for multivariate analysis of signalling pathways.

Mathematical models of highly interconnected and multivariate signalling networks provide useful tools to understand these complex systems. However, effective approaches to extracting multivariate regulation information from these models are still lacking. In this study, we propose a data-driven modelling framework to analyse large-scale multivariate datasets generated from mathematical models. We used an ordinary differential equation based model for the Fas apoptotic pathway as an example. The first step in our approach was to cluster simulation outputs generated from models with varied protein initial concentrations. Subsequently, decision tree analysis was applied, in which we used protein concentrations to predict the simulation outcomes. Our results suggest that no single subset of proteins can determine the pathway behaviour. Instead, different subsets of proteins with different concentrations ranges can be important. We also used the resulting decision tree to identify the minimal number of perturbations needed to change pathway behaviours. In conclusion, our framework provides a novel approach to understand the multivariate dependencies among molecules in complex networks, and can potentially be used to identify combinatorial targets for therapeutic interventions.     

Functional block diagrams and automated construction of event trees

Functional block diagrams are introduced as graphical representations of the function of a system. A functional block provides the output of a system as the outcome of a joint event defined by the inputs to the system and its various states. Functional blocks corresponding to different subsystems are combined together to form a functional block diagram representing the functional characteristics of the combined system. Conversely, a complex system represented by a single functional block is decomposed to constituent components with a corresponding functional block diagram. It is demonstrated that a functional block diagram is an alternative representation of an event-tree corresponding to the outcome space of the underlying joint event. The concept of output space partition is introduced and an algorithm is developed for generating the most compact form of the event-tree consistent with a given partition. This algorithm forms the basis of a technique for the automated construction of an event-tree starting from a developed functional block diagram. This technique is amenable to computerization. Finally, as a demonstration of the technique, the event-trees of a boiling water reactor (BWR) are developed.     

Energetics of Stone–Wales defects in deformations of monoatomic hexagonal layers

Stone–Wales (SW) bond rotation and the resulting defect in a hexagonal lattice represent an elementary step in mechanical relaxation. We analyze the energy of such defects and the dependencies on the applied strain magnitude and direction, as well as on the lattice curvature. The results of extensive molecular simulations can be summarized in a single equation for the formation energy. Further, we calculate the interaction between the SW defects and discuss its role in the relaxation process. The atomic structure of transition state and the corresponding barriers are investigated in view of their significance for the rate of SW transformations and therefore the rate of mechanical failure of material.     

A Monte Carlo simulation approach to the availability assessment of multi-state systems with operational dependencies

This paper deals with multi-state systems (MSS), whose performance can settle on different levels, e.g. 100%, 80%, 50% of the nominal capacity, depending on the operative conditions of the constitutive multi-state elements. Examples are manufacturing, production, power generation and gas and oil transportation systems. Often in practice, MSS are such that operational dependencies exist between the system state and the state of its components. For example, in a production line of nodal series structure, with no buffers between the nodes, if one of the nodes throughput changes (e.g. switches from 100% to 50% due to a deterministic or stochastic transition of one of its components), the other nodes must be reconfigured (i.e. their components must deterministically change their states) so as to provide the same throughput.In this paper, we present a Monte Carlo simulation technique which allows modelling the complex dynamics of multi-state components subject to operational dependencies with the system overall state. A correlation method is tailored to model the automatic change of state of the relevant components following a change in one of the system nodes. The proposed technique is verified on a simple case study of literature.     

Volume modelling for emerging manufacturing technologies

The next generation manufacturing technologies will draw on new developments in geometric modelling. Based on a comprehensive analysis of the desiderata of next generation geometric modellers, we present a critical review of the major modelling paradigms, namely, CSG, B-Rep, non-manifold, and voxel models. We present arguments to support the view that voxel-based modellers have attributes that make it the representation scheme of choice in meeting the emerging requirements of geometric modelling.     

Integration of safety analysis in model-driven software development

Safety critical software requires integrating verification techniques in software development methods. Software architectures must guarantee that developed systems will meet safety requirements and safety analyses are frequently used in the assessment. Safety engineers and software architects must reach a common understanding on an optimal architecture from both perspectives. Currently both groups of engineers apply different modelling techniques and languages: safety analysis models and software modelling languages. The solutions proposed seek to integrate both domains coupling the languages of each domain. It constitutes a sound example of the use of language engineering to improve efficiency in a software-related domain. A model-driven development approach and the use of a platform-independent language are used to bridge the gap between safety analyses (failure mode effects and criticality analysis and fault tree analysis) and software development languages (e.g. unified modelling language). Language abstract syntaxes (metamodels), profiles, language mappings (model transformations) and language refinements, support the direct application of safety analysis to software architectures for the verification of safety requirements. Model consistency and the possibility of automation are found among the benefits.