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EN
Basic notions of the ageing multistate systems safety analysis are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems lifetimes in the safety state subsets and the mean values of their lifetimes in the particular safety states are defined. The multi-state system risk function and the moment of exceeding by the system the critical safety state are introduced. The exemplary safety structures of the multistate systems with ageing components are defined and their safety functions are determined. As a particular case, the safety functions of the considered multistate systems composed of components having exponential safety functions are determined. Applications of the proposed multistate system safety models to the evaluation and prediction of the safty characteristics of the exemplary series, parallel, “m out of n”, consecutive “m out of n: F”, series-parallel, parallel-series and “m out of l”-series systems are presented as well.
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Content available Complex technical systems safety prediction
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EN
There are presented general safety analytical models of complex multistate technical systems related to their operation processes. They are the integrated general models of complex technical systems, linking their multistate safety models and their operation processes models and considering variable at the different operation states safety structures and their components safety parameters. The conditional safety functions at the system particular operation states and independent of the system particular operation states the unconditional safety function and the risk function of the complex technical systems are defined. These joint models of the safety and the variable in time system operation processes are constructed for multistate series, parallel, “m out of n”, consecutive “m out of n: F”, series-parallel, parallel-series, series-“m out of k”, “mi out of li”-series, series-consecutive “m out of k: F” and consecutive “mi out of li: F”-series systems. The joint models are applied to determining safety characteristics of these systems related to their varying in time safety structures and their components safety characteristics. Under the assumption that the considered systems are exponential, the unconditional safety functions of these systems are determined. The proposed models and methods are applied to the safety analysis, evaluation and prediction of the one subsystem of the port grain transportation system related to varying in time their operation processes, structures and components safety parameters.
EN
There are presented the methods of the reliability prediction and optimization of complex technical systems related to their operation processes. The general model of the reliability of complex technical systems operating at variable operation conditions linking the semi-Markov modeling of their operation processes with the multistate approach to their reliability analysis and the linear programming are applied in maritime industry to the reliability and risk prediction and optimization of the container gantry crane.
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Content available Safety of multistate ageing systems
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EN
Basic notions of the ageing multistate systems safety analysis are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems lifetimes in the safety state subsets and the mean values of their lifetimes in the particular safety states are defined. The multi-state system risk function and the moment of exceeding by the system the critical safety state are introduced. The exemplary safety structures of the multistate systems with ageing components are defined and their safety functions are determined. As a particular case, the safety functions of the considered multistate systems composed of components having exponential safety functions are determined. Applications of the proposed multistate system safety models to the evaluation and prediction of the safty characteristics of the oil piping transportation system is presented as well.
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Content available Critical infrastructure operation process
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EN
The operation process of the critical infrastructure is considered and its operation states are introduced. The semi- Markov process is used to construct a general probabilistic model of the critical infrastructure operation process.
EN
There are presented the methods of prediction of the climate-weather change process. These are the methods and procedures for estimating the unknown basic parameters of the climate-weather change process semi-Markov model and identifying the distributions of the climate-weather change process conditional sojourn times at the climate-weather states. There are given the formulae estimating the probabilities of the climate-weather change process staying at the particular climate-weather states at the initial moment, the probabilities of the climate-weather change transitions between the climate-weather states and the parameters of the distributions suitable and typical for the description of the climate-weather change process conditional sojourn times at the particular climate-weather states. The proposed statistical methods applications for the unknown parameters identification of the climate-weather change process model determining the climate-weather change process parameters for the initial point of the port oil piping transportation system are presented.
EN
In the paper the new results of the safety investigations of the multistate complex systems with dependent components at variable operation conditions called critical infrastructures are presented. The multi-state safety function of the critical infrastructure system is defined and determined for an exemplary critical infrastructure. In the developed models, it is assumed that the system components have the multistate exponential safety functions with interdependent departures rates from the subsets of the safety states.
EN
Modelling and prediction of the operation and reliability of technical multistate ageing systems related to their operation processes called complex systems are briefly presented and applied to prediction of the operation processes and reliability characteristics of an exemplary complex non-homogeneous system composed of a series-parallel and a series-“m out of l” subsystems linked in series, changing its reliability structure and its components reliability parameters at variable operation conditions. Further, the linear programming is proposed to the operation and reliability optimization of complex technical systems operating at variable operation conditions. The method consists in determining the optimal values of limit transient probabilities at the system operation states that maximize the system lifetimes in the reliability state subsets. The proposed method is practically applied to the operation and reliability optimization of the considered exemplary complex system.
EN
In the article the traditional semi-Markov approach to a complex technical system operation process modeling is developed to modelling a critical infrastructure operation process including operating environment threats. The method of defining the parameters of this operation process is presented and a new procedure of their determining in the case when the critical infrastructure operating threats are not explicit sepatated in this process is proposed.
EN
The climate-weather change process for the critical infrastructure operating area is considered and its states are introduced. The semi-Markov process is used to construct a general probabilistic model of the climate-weather change process for the critical infrastructure operating area. To build this model the vector of probabilities of the climate-weather change process staying at the initials climate-weather states, the matrix of probabilities of the climate-weather change process transitions between the climate-weather states, the matrix of conditional distribution functions and the matrix of conditional density functions of the climate-weather change process conditional sojourn times at the climate-weather states are defined. To describe the climate-weather change process conditional sojourn times at the particular climate-weather states the uniform distribution, the triangular distribution, the double trapezium distribution, the quasi-trapezium distribution, the exponential distribution, the Weibull distribution, the chimney distribution and the Gamma distribution are suggested and introduced.
EN
In the paper, the traditional semi-Markov approach to a complex technical system operation process modeling is proposed to modelling a critical infrastructure operation process including operating environment threats. Next the model is applied to real critical infrastructures such as the maritime ferry technical system.
EN
Introductory general approach to EU-CIRCLE project taxonomy and methodology is presented. National and international critical infrastructure protection overview is performed. The critical infrastructure protection legal frames in Poland, the institutions responsible for them and their duties are presented in details. A general approach to and a scheme of operation and climate-weather change influence on critical infrastructure safety and critical infrastructure accident consequences modelling is proposed as well.
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Content available Complex system operation cost optimization
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EN
The general model of a complex system changing its safety structure, its components safety parameters and its operation cost during the variable operation process and linear programming are applied to optimize the system operation process in order to get the system operation cost optimal values. The optimization problem allowing to find the optimal values of the transient probabilities of the complex system operation process at the particular operation states that minimize the system unconditional operation cost mean value in the safety states subset not worse than a critical system safety state under the assumption that the system conditional operation cost mean values in this safety state subset at the particular operation states are fixed is presented. Further, the procedure of finding the optimal values operation cost is presented and applied to the exemplary complex technical system.
EN
The paper is concerned with the methods and procedures for identification of unknown parameters of a general probability model of a complex technical system operation process and their practical application. The general multistate model of a complex technical system operation process is proposed and the procedure of identifying its basic unknown parameters is presented. There are also suggested typical distribution functions describing the system operation process conditional sojourn times at particular operation states and the procedure of identifying their unknown parameters is proposed. An illustration of the proposed methods and procedures practical application to identifying the port oil piping transportation system operation process and its operation characteristics prediction is presented.
PL
Artykuł dotyczy metod i procedur identyfikacji nieznanych parametrów ogólnego modelu probabilistycznego procesu eksploatacji złożonego systemu technicznego oraz ich praktycznego zastosowania. Zaproponowany jest ogólny wielostanowy model procesu eksploatacji złożonego systemu technicznego oraz przedstawiona jest procedura identyfikacji jego nieznanych podstawowych parametrów. Zasugerowane są także typowe dystrybuanty warunkowe opisujące czasy przebywania procesu eksploatacji systemu w poszczególnych stanach eksploatacyjnych oraz zaproponowana jest procedura identyfikacji ich nieznanych parametrów. Przedstawiona jest ilustracja praktycznego zastosowania proponowanych metod i procedur do identyfikacji procesu eksploatacji portowego rurociągowego systemu transportu paliwa i do predykcji jego charakterystyk eksploatacyjnych.
EN
Integrated Safety and Reliability Decision Support System - IS&RDSS is presented in the form of detailed and clear scheme-algorithm. There is also presented the methodology of IS&RDSS that is composed of the methods of complex technical systems operation processes modelling, their unknown parameters concerning operation, reliability, availability, safety models identification, their reliability, availability and safety evaluation and prediction, their reliability, availability and safety improvement and their operation, reliability, availability, safety and cost optimization. The newest trends in the reliability and safety of complex technical systems analysis directed to the critical infrastructures and the nanosystems are describe as well.
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PL
Złożoność procesów eksploatacji systemów oraz ich wpływ na zmieniające się w czasie struktury tych systemów oraz parametry niezawodności i bezpieczeństwa ich elementów są często spotykane w rzeczywistej praktyce. Z uwagi na bezpieczeństwo oraz efektywność eksploatacji systemów technicznych podczas analizy ich niezawodności wskazanym jest odejście od dwustanowego modelu ich niezawodności. Przyjęcie założenia, że są one wielostanowymi systemami starzejącymi się z pogarszającymi się w czasie stanami niezawodnościowymi lub bezpieczeństwa ich elementów jest podstawą do bardziej dokładnej analizy procesu eksploatacji tych systemów. Założenie to pozwala na wyróżnienie progowego stanu krytycznego niezawodności lub bezpieczeństwa systemu, którego przekroczenie jest niebezpieczne dla otoczenia lub też nie zapewnia odpowiedniego poziomu efektywności eksploatacji tego systemu. Wtedy, podstawową charakterystyką niezawodności lub bezpieczeństwa systemu staje się rozkład czasu do przekroczenia stanu progowego zwany funkcją ryzyka systemu. Rozkład ten jest ściśle wyznaczony przez wielostanową funkcję niezawodności systemu lub odpowiednio wielostanową funkcją bezpieczeństwa systemu. Przedstawiony jest Zintegrowany System Wspomagania Decyzji dotyczących Bezpieczeństwa i Niezawodności - ZSWDBiN w postaci szczegółowego schematu zawierającego algorytm postępowania. Przedstawiona jest także metodologia ZSWDBiN zawierająca modele eksploatacji, niezawodności, gotowości i bezpieczeństwa złożonych systemów technicznych, metody identyfikacji nieznanych parametrów tych modeli oraz metody predykcji, optymalizacji oraz analizy kosztów eksploatacji tych systemów. Ponadto omówione są najnowsze wyzwania w analizie niezawodności i bezpieczeństwa złożonych systemów technicznych, ukierunkowane na infrastruktury krytyczne i nanosystemy.
EN
Integrated Safety and Reliability Decision Support System - IS&RDSS is presented in the form of detailed and clear scheme-algorithm. There is also presented the methodology of IS&RDSS that is composed of the methods of complex technical systems operation processes modeling, their unknown parameters operation, reliability, availability, safety models identification, their reliability, availability and safety evaluation and prediction, their reliability, availability and safety improvement and their operation, reliability, availability, safety and cost optimization. The newest trends in the reliability and safety of complex technical systems analysis directed to the critical infrastructures and the nanosystems are describe as well.
EN
Basic concepts of the safety analysis of ageing multistate systems are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems’ lifespans in the safety state subsets and the mean values of their lifespans in the particular safety states are defined. The multistate system risk function and the moment of exceeding the critical safety state are introduced. A series safety structure and a parallel-series safety structure of the multistate systems with ageing components are defined and their safety functions are determined. The multistate system safety models are applied to the prediction of safety characteristics of a maritime ferry.
EN
The main objective of this paper is to present recently developed, the general safety analytical models of complex multistate technical systems related to their operation processes and to apply them practically to critical infrastructures. To realize this goal, the integrated model of critical infrastructure safety related to its operation process is proposed. The basic safety characteristics of this model are presented as the very practically significant. Furthermore, the unconditional safety functions of systems with different safety structures are determined under assumption that their safety functions are exponential. In case of the critical infrastructure safety analysis, its safety function and risk function which graph corresponds to the fragility curve, its mean lifetime up to the exceeding a critical safety state, the moment when its risk function value exceeds the acceptable safety level, the component and critical infrastructure intensities of ageing/degradation and the coefficients of operation impact on component and critical infrastructure intensities of ageing are defined.
EN
In the paper, the traditional semi-Markov approach to a complex technical system operation process modeling is proposed to model and to identify the port oil piping transportation system operation process including operating environment threats.
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Content available Modeling Safety of Multistate Ageing Systems
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EN
First, basic notions of the multistate system safety analysis are introduced, i.e. the multistate components and the multistate system, the multistate system component safety function, the multistate system safety and the multistate system risk function are defined. Moreover, the multistate system component and the multistate system main safety characteristics, i.e. their mean values of the lifetimes and in the safety state subsets and in the particular safety states and standard deviations and the moment when the system risk function exceeds a fixed permitted level are determined. Furthermore, there are constructed safety models of the multi-state homogeneous and non-homogeneous series, parallel, “m out of n”, consecutive “m out of n: F”, series-parallel, parallel-series, series-“m out of n”, “m out of n”-series, series-consecutive “m out of n: F” and consecutive “m out of n: F”-series systems and their safety functions are determined. Moreover, a very often met in practiceseries system composed of multistate subsystems identical with the considered earlier multistate systems is considered and its safety function is determined.
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