Ferdinando Chiacchio

MatCarloRe: An integrated FT and Monte Carlo Simulink tool for the reliability assessment of dynamic fault tree

With the aim of a more effective representation of reliability assessment for real industry, in the last years concepts like dynamic fault trees (DFT) have gained the interest of many researchers and engineers (dealing with problems concerning safety management, design and development of new products, decision analysis and project management, maintenance of industrial plant, etc.). With the increased computational power of modern calculators is possible to achieve results with low modeling efforts and calculating time. Supported by the strong mathematical basis of state space models, the DFT technique has increased its popularity. Nevertheless, DFT analysis of real application has been more likely based on a specific case to case resolution procedure that often requires a great effort in terms of modeling by the human operator. Moreover, limitations like the state space explosion for increasing number of components, the constrain of using exponential distribution for all kind of basic events constituting any analyzed system and the ineffectiveness of modularization for DFT which exhibit dynamic gates at top levels without incurring in calculation and methodological errors are faces of these methodologies. In this paper we present a high level modeling framework that exceeds all these limitations, based on Monte Carlo simulation. It makes use of traditional DFT systemic modeling procedure and by replicating the true casual nature of the system can produce relevant results with low effort in term of modeling and computational time. A Simulink library that integrates Monte Carlo and FT methodologies for the calculation of DFT reliability has been developed, revealing new insights about the meaning of spare gates.

Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches

Abstract Safety assessment in industrial plants with ‘major hazards’ requires a rigorous combination of both qualitative and quantitative techniques of RAMS. Quantitative assessment can be executed by static or dynamic tools of dependability but, while the former are not sufficient to model exhaustively time-dependent activities, the latter are still too complex to be used with success by the operators of the industrial field. In this paper we present a review of the procedures that can be used to solve quite general dynamic fault trees (DFT) that present a combination of the following characteristics: time dependencies, repeated events and generalized probability failure. Theoretical foundations of the DFT theory are discussed and the limits of the most known DFT tools are presented. Introducing the concept of weak and strong hierarchy, the well-known modular approach is adapted to study a more generic class of DFT. In order to quantify the approximations introduced, an ad-hoc simulative environment is used as benchmark. In the end, a DFT of an accidental scenario is analyzed with both analytical and simulative approaches. Final results are in good agreement and prove how it is possible to implement a suitable Monte Carlo simulation with the features of a spreadsheet environment, able to overcome the limits of the analytical tools, thus encouraging further researches along this direction.

A Weibull-based compositional approach for hierarchical dynamic fault trees

The solution of a dynamic fault tree (DFT) for the reliability assessment can be achieved using a wide variety of techniques. These techniques have a strong theoretical foundation as both the analytical and the simulation methods have been extensively developed. Nevertheless, they all present the same limits that appear with the increasing of the size of the fault trees (i.e., state space explosion, time-consuming simulations), compromising the resolution.

Mathematical modeling of the immune system recognition to mammary carcinoma antigen

The definition of artificial immunity, realized through vaccinations, is nowadays a practice widely developed in order to eliminate cancer disease. The present paper deals with an improved version of a mathematical model recently analyzed and related to the competition between immune system cells and mammary carcinoma cells under the action of a vaccine (Triplex). The model describes in detail both the humoral and cellular response of the immune system to the tumor associate antigen and the recognition process between B cells, T cells and antigen presenting cells. The control of the tumor cells growth occurs through the definition of different vaccine protocols. The performed numerical simulations of the model are in agreement with in vivo experiments on transgenic mice.

Agent-based modeling of the immune system: NetLogo, a promising framework.

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

Conception of Repairable Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab® toolbox based on the ATS formalism

Dynamic Fault Tree (DFT) is a well-known stochastic technique for conducting reliability studies of complex systems. At the state of the art, existing tools (both academic and commercial) do not fully support DFT with repairable components and repeated events, lowering the penetration of this powerful technique in real industrial applications (e.g., industrial processes and plants, computer, electronic and network applications). One of the main reasons limiting the attractiveness of DFT is that, originally, DFTs were conceived without repairable components; only recently few related works have started to deal with a formal semantic, which would avoid undefined behavior and misinterpretation of DFT. Other researchers have tackled the problem by introducing extensions of the original Fault Trees (FTs) technique like Boolean Driven Markov Processes (BDMPs) and Generalized Fault Trees (GFTs). However, despite they consider repairable systems and repeated events, we have found that the introduction of a different formalism with more complex features has again limited the penetration of these powerful methods in real applications. The target of this work is the original DFT technique. Starting from the state of the art, a set of standardized rules that frame the behaviors of dynamic gates are designed and a well-defined semantic for repairable-DFT is drawn through the application of a novel formalism, the Adaptive Transitions System (ATS). The proposed theoretical framework is afterward used to code a software tool, RAATSS, for the resolution of extended, repairable-DFT. Moreover, this work introduces some novel concepts regarding the modeling of a system by a DFT and provides a basic hint of the ATS capabilities to describe interdependencies in complex system.

An open-source application to model and solve dynamic fault tree of real industrial systems

In recent years, a new generation of modeling tools for the risk assessment have been developed. The concept of ¿dynamic¿ was exported also in the field of reliability and techniques like dynamic fault tree, dynamic reliability block diagrams, boolean logic driven Markov processes, etc., have become of use. But, despite the promises of researchers and the efforts of end-users, the dynamic paradox hangs: risk assessment procedures are not as straight as they were with the traditional static methods and, what is worse, it is difficult to assess the reliability of these results. Far from deny the importance of the scientific achievement, we have tested and cursed some of these dynamic tools realizing that none of them was appropriate to solve a real case. In this context, we decided to develop a new DFT reliability solver, based on the Monte Carlo simulative approach. The tool is greatly powerful because it is written with Matlab® code, hence is open-source and can be extended. In this first version, we have implemented the most used dynamic gates (PAND, SEQ, FDEP and SPARE), the existence of repeated events and the possibility to simulate different cumulative distribution function of failure (Weibull, negative exponential CDF and constant). The tool is provided with a snappy graphic user interface written in Java®, which allows an easy but efficient modeling of any fault tree schema. The tool has been tested with many literature cases of study and results encourage other developments.

SHyFTA, a Stochastic Hybrid Fault Tree Automaton for the modelling and simulation of dynamic reliability problems

Discussion about the state of the art of expert systems and reliability assessment.Formalisation of the Stochastic Hybrid Fault Tree Automaton modelling technique.Conception of Hybrid Basic Events.Experimental Comparison of DFT and SHyFTA model for an industrial case study.Implementation of the SHyFTA in Simulink using MatCarloRE library. Reliability assessment of industrial processes is traditionally performed with RAMS techniques. Such techniques are static in nature because they are unable to consider the multi-state operational and failure nature of systems and the dynamic variations of the environment in which they operate.Stochastic Hybrid Automaton appears to overcome this weakness coupling a deterministic and a stochastic process and integrating the features of a dynamic system with the concepts of dynamic reliability.At the state of the art, no attempts to enhance a formal RAMS technique with dynamic reliability has been tried, nor a computer-aided tool that plays as expert system has been coded yet.The aim of this paper is to fill this gap with a simulation formalism and a modelling tool able to combine the Dynamic Fault Tree technique and the Stochastic Hybrid Automaton within the Simulink environment. To this aim the MatCarloRE toolbox was adapted to interact with a Simulink dynamic system. The resulting assembly represents an important step ahead for the delivering of a user-friendly computer-aided tool for the dynamic reliability.

Cancer Vaccines: State of the Art of the Computational Modeling Approaches

Cancer vaccines are a real application of the extensive knowledge of immunology to the field of oncology. Tumors are dynamic complex systems in which several entities, events, and conditions interact among them resulting in growth, invasion, and metastases. The immune system includes many cells and molecules that cooperatively act to protect the host organism from foreign agents. Interactions between the immune system and the tumor mass include a huge number of biological factors. Testing of some cancer vaccine features, such as the best conditions for vaccine administration or the identification of candidate antigenic stimuli, can be very difficult or even impossible only through experiments with biological models simply because a high number of variables need to be considered at the same time. This is where computational models, and, to this extent, immunoinformatics, can prove handy as they have shown to be able to reproduce enough biological complexity to be of use in suggesting new experiments. Indeed, computational models can be used in addition to biological models. We now experience that biologists and medical doctors are progressively convinced that modeling can be of great help in understanding experimental results and planning new experiments. This will boost this research in the future.

Analysis of OPC UA performances

OPC UA is the evolution of the well known OPC COM and XML specifications. OPC UA adopts a very complex software infrastructure to realise the communication among industrial applications; furthermore it features many mechanisms realising data exchanges, whose tuning depends on several parameters. The aim of this paper is to deal with the performance evaluation of OPC UA. The main data exchange mechanisms which may influence performance of the client/server communications will be pointed out; then, the analysis of the overhead they introduce will be presented and discussed. Finally, some guidelines about the setting of OPC UA mechanisms will be given on the basis of the results achieved.