Journal articles: 'Stochastic Fault Tree'

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Chovanec, A., A. Breznická, and P. Mikuš. "The fault tree stochastic analysis." IOP Conference Series: Materials Science and Engineering 776 (April 2, 2020): 012024. http://dx.doi.org/10.1088/1757-899x/776/1/012024.

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Jenab, K., and B. S. Dhillon. "Stochastic Fault Tree Analysis With Self-Loop Basic Events." IEEE Transactions on Reliability 54, no. 1 (March 2005): 173–80. http://dx.doi.org/10.1109/tr.2004.842087.

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Chiacchio, Aizpurua, Compagno, Khodayee, and D’Urso. "Modelling and Resolution of Dynamic Reliability Problems by the Coupling of Simulink and the Stochastic Hybrid Fault Tree Object Oriented (SHyFTOO) Library." Information 10, no. 9 (September 11, 2019): 283. http://dx.doi.org/10.3390/info10090283.

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Dependability assessment is one of the most important activities for the analysis of complex systems. Classical analysis techniques of safety, risk, and dependability, like Fault Tree Analysis or Reliability Block Diagrams, are easy to implement, but they estimate inaccurate dependability results due to their simplified hypotheses that assume the components’ malfunctions to be independent from each other and from the system working conditions. Recent contributions within the umbrella of Dynamic Probabilistic Risk Assessment have shown the potential to improve the accuracy of classical dependability analysis methods. Among them, Stochastic Hybrid Fault Tree Automaton (SHyFTA) is a promising methodology because it can combine a Dynamic Fault Tree model with the physics-based deterministic model of a system process, and it can generate dependability metrics along with performance indicators of the physical variables. This paper presents the Stochastic Hybrid Fault Tree Object Oriented (SHyFTOO), a Matlab® software library for the modelling and the resolution of a SHyFTA model. One of the novel features discussed in this contribution is the ease of coupling with a Matlab® Simulink model that facilitates the design of complex system dynamics. To demonstrate the utilization of this software library and the augmented capability of generating further dependability indicators, three different case studies are discussed and solved with a thorough description for the implementation of the corresponding SHyFTA models.

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Bose, S. Subash Chandra, Badria Sulaiman Alfurhood, Gururaj H. L, Francesco Flammini, Rajesh Natarajan, and Sheela Shankarappa Jaya. "Decision Fault Tree Learning and Differential Lyapunov Optimal Control for Path Tracking." Entropy 25, no. 3 (March 2, 2023): 443. http://dx.doi.org/10.3390/e25030443.

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This paper considers the main challenges for all components engaged in the driving task suggested by the automation of road vehicles or autonomous cars. Numerous autonomous vehicle developers often invest an important amount of time and effort in fine-tuning and measuring the route tracking to obtain reliable tracking performance over a wide range of autonomous vehicle speed and road curvature diversities. However, a number of automated vehicles were not considered for fault-tolerant trajectory tracking methods. Motivated by this, the current research study of the Differential Lyapunov Stochastic and Decision Defect Tree Learning (DLS-DFTL) method is proposed to handle fault detection and course tracking for autonomous vehicle problems. Initially, Differential Lyapunov Stochastic Optimal Control (SOC) with customizable Z-matrices is to precisely design the path tracking for a particular target vehicle while successfully managing the noise and fault issues that arise from the localization and path planning. With the autonomous vehicle’s low ceilings, a recommendation trajectory generation model is created to support such a safety justification. Then, to detect an unexpected deviation caused by a fault, a fault detection technique known as Decision Fault Tree Learning (DFTL) is built. The DLS-DFTL method can be used to find and locate problems in expansive, intricate communication networks. We conducted various tests and showed the applicability of DFTL. By offering some analysis of the experimental outcomes, the suggested method produces significant accuracy. In addition to a thorough study that compares the results to state-of-the-art techniques, simulation was also used to quantify the rate and time of defect detection. The experimental result shows that the proposed DLS-DFTL enhances the fault detection rate (38%), reduces the loss rate (14%), and has a faster fault detection time (24%) than the state of art methods.

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Xu, Yi Xin, Yan Bai, and Ren Shu Wang. "GSPN-Based Reliability Model of Wireless Control System." Applied Mechanics and Materials 392 (September 2013): 374–78. http://dx.doi.org/10.4028/www.scientific.net/amm.392.374.

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It is difficult to model and solve the reliability of complicated dynamic system in the traditional reliability modeling method. A new reliability modeling method based on generalized stochastic petri net (GSPN) is proposed to analyze the wireless control system (WCS). After studying the common faults of the WCS, a dynamic fault tree is constructed to analyze the system, and it is transformed into formalization definition of GSPN. Finally, a certain type of WCS is selected to validate the proposed method. This method has important value to other WCS design and analysis.

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Tang, Li Zhi, Jun Du, Kun Peng Xu, and Xue Qing Qi. "Distribution System Restoration Based on Hybrid Particle Swarm." Advanced Materials Research 732-733 (August 2013): 662–68. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.662.

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By the heuristic algorithm and particle swarm optimization algorithm combining hybrid particle swarm algorithm proposed combination of heuristic search and stochastic optimization,stochastic optimization process using a spanning tree and the loop matrix operations combined to ensure the system topology constraints to improve the efficiency of solution. The analysis shows that the proposed method calculation speed,easy to converge to the global optimal solution. It can effectively solve the problem of distribution network fault recovery.

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Huang, Tao, Zining Cao, and Qing Li. "Verification and Fault Analysis based on Combination of AADL and Modelica." Journal of Physics: Conference Series 2261, no. 1 (June 1, 2022): 012014. http://dx.doi.org/10.1088/1742-6596/2261/1/012014.

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Abstract CPS is a multidimensional complex system that can realize the interaction between computing process and physical process. Aiming at the problems of fault occurrence and uncertain behavior, this paper proposes the fault analysis stochastic hybrid automata as a formal model, the attributes of randomness and fault analysis are added through AADL behavior attachment to expand the attributes of hybrid automata, and applies the extended automata to the embedded system for system description and fault analysis. The model is used to model the fire control system, and AADL, Modelica and fault tree are combined to form a new model. The behavior is analyzed, and the conversion algorithm and conversion example are given.

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Liu, Wuqiang, Xiaoqiang Yang, and Shen Jinxing. "An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutation Entropy." Shock and Vibration 2020 (November 26, 2020): 1–18. http://dx.doi.org/10.1155/2020/8851310.

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The health condition of rolling bearings, as a widely used part in rotating machineries, directly influences the working efficiency of the equipment. Consequently, timely detection and judgment of the current working status of the bearing is the key to improving productivity. This paper proposes an integrated fault identification technology for rolling bearings, which contains two parts: the fault predetection and the fault recognition. In the part of fault predetection, the threshold based on amplitude-aware permutation entropy (AAPE) is defined to judge whether the bearing currently has a fault. If there is a fault in the bearing, the fault feature is adequately extracted using the feature extraction method combined with dual-tree complex wavelet packet transform (DTCWPT) and generalized composite multiscale amplitude-aware permutation entropy (GCMAAPE). Firstly, the method decomposes the fault vibration signal into a set of subband components through the DTCWPT with good time-frequency decomposing capability. Secondly, the GCMAAPE values of each subband component are computed to generate the initial candidate feature. Next, a low-dimensional feature sample is established using the t-distributed stochastic neighbor embedding (t-SNE) with good nonlinear dimensionality reduction performance to choose sensitive features from the initial high-dimensional features. Afterwards, the featured specimen representing fault information is fed into the deep belief network (DBN) model to judge the fault type. In the end, the superiority of the proposed solution is verified by analyzing the collected experimental data. Detection and classification experiments indicate that the proposed solution can not only accurately detect whether there is a fault but also effectively determine the fault type of the bearing. Besides, this solution can judge the different faults more accurately compared with other ordinary methods.

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Chiacchio, Ferdinando, Fabio Famoso, Diego D’Urso, Sebastian Brusca, Jose Aizpurua, and Luca Cedola. "Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model." Energies 11, no. 2 (January 31, 2018): 306. http://dx.doi.org/10.3390/en11020306.

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Wang, Bing, Guangdong Tian, Yanping Liang, and Tiangang Qiang. "Reliability Modeling and Evaluation of Electric Vehicle Motor by Using Fault Tree and Extended Stochastic Petri Nets." Journal of Applied Mathematics 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/638013.

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Performing reliability analysis of electric vehicle motor has an important impact on its safety. To do so, this paper proposes its reliability modeling and evaluation issues of electric vehicle motor by using fault tree (FT) and extended stochastic Petri nets (ESPN). Based on the concepts of FT and ESPN, an FT based ESPN model for reliability analysis is obtained. In addition, the reliability calculation method is introduced and this work designs a hybrid intelligent algorithm integrating stochastic simulation and NN, namely, NN based simulation algorithm, to solve it. Finally, taking an electric vehicle motor as an example, its reliability modeling and evaluation issues are analyzed. The results illustrate the proposed models and the effectiveness of proposed algorithms. Moreover, the results reported in this work could be useful for the designers of electric vehicle motor, particularly, in the process of redesigning the electric vehicle motor and scheduling its reliability growth plan.

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Talebberrouane, Mohammed, Faisal Khan, and Zoubida Lounis. "Availability analysis of safety critical systems using advanced fault tree and stochastic Petri net formalisms." Journal of Loss Prevention in the Process Industries 44 (November 2016): 193–203. http://dx.doi.org/10.1016/j.jlp.2016.09.007.

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Zenchenkova, Diana V., and Sergei M. Travin. "Analysis and assessment of the risk of accidents of a structure as a system by the method of "Fault Tree Analysis" on the example of a nuclear power facility under seismic impact." Earthquake Engineering. Construction Safety, no. 1 (February 25, 2021): 78–93. http://dx.doi.org/10.37153/2618-9283-2021-1-78-93.

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The article discusses a method for analyzing the risk assessment of failures of the structure as a system by developing a "Fault Tree Analysis". Formulas were proposed for the numerical estimation of the probability of system failure, taking into account the stochastic dependence of the failures of its elements. On the example of a nuclear power facility, a "wet" stand-alone storage facility for spent nuclear fuel, an analysis of possible scenarios of a facility failure was carried out, a "Fault Tree Analysis" was developed and calculated under seismic impact. It has been determined that the risk of structure as a system under seismic impact is determined by the risk of falling process equipment and building structures on the overlap of storage compartments or stored nuclear fuel. To increase the safety of building structures under seismic impact, it is necessary to pay special attention to the design features of the frame part and the interface between the monolithic storage compartment and the frame part, as the most vulnerable link.

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Khodayee, Soheyl Moheb, Ferdinando Chiacchio, and Yiannis Papadopoulos. "A Novel Approach Based on Stochastic Hybrid Fault Tree to Compare Alternative Flare Gas Recovery Systems." IEEE Access 9 (2021): 51029–49. http://dx.doi.org/10.1109/access.2021.3069807.

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Chiacchio, Ferdinando, Diego D'Urso, Lucio Compagno, Marzio Pennisi, Francesco Pappalardo, and Gabriele Manno. "SHyFTA, a Stochastic Hybrid Fault Tree Automaton for the modelling and simulation of dynamic reliability problems." Expert Systems with Applications 47 (April 2016): 42–57. http://dx.doi.org/10.1016/j.eswa.2015.10.046.

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Kaviris, George, Angelos Zymvragakis, Pavlos Bonatis, Vasilis Kapetanidis, and Nicholas Voulgaris. "Probabilistic and Scenario-Based Seismic Hazard Assessment on the Western Gulf of Corinth (Central Greece)." Applied Sciences 12, no. 21 (November 3, 2022): 11152. http://dx.doi.org/10.3390/app122111152.

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The Gulf of Corinth (Central Greece) is one of the most rapidly extending rifts worldwide, with its western part being the most seismically active, hosting numerous strong (M ≥ 6.0) earthquakes that have caused significant damage. The main objective of this study was the evaluation of seismic hazard through a probabilistic and stochastic methodology. The implementation of three seismotectonic models in the form of area source zones via a logic tree framework revealed the expected level of peak ground acceleration and velocity for return periods of 475 and 950 years. Moreover, PGA values were obtained through the stochastic simulation of strong ground motion by adopting worst-case seismic scenarios of potential earthquake occurrences for known active faults in the area. Site-specific analysis of the most populated urban areas (Patras, Aigion, Nafpaktos) was performed by constructing uniform hazard spectra in terms of spectral acceleration. The relative contribution of each selected fault segment to the seismic hazard characterizing each site was evaluated through response spectra obtained for the adopted scenarios. Almost all parts of the study area were found to exceed the reference value proposed by the current Greek National Building Code; however, the three urban areas are covered by the Eurocode 8 regulations.

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Aliee, Hananeh, and Hamid Reza Zarandi. "A Fast and Accurate Fault Tree Analysis Based on Stochastic Logic Implemented on Field-Programmable Gate Arrays." IEEE Transactions on Reliability 62, no. 1 (March 2013): 13–22. http://dx.doi.org/10.1109/tr.2012.2221012.

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Chiacchio, Ferdinando, Jose Ignacio Aizpurua, Lucio Compagno, and Diego D'Urso. "SHyFTOO, an object-oriented Monte Carlo simulation library for the modeling of Stochastic Hybrid Fault Tree Automaton." Expert Systems with Applications 146 (May 2020): 113139. http://dx.doi.org/10.1016/j.eswa.2019.113139.

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Ozirkovskyy, Leonid, Bohdan Volochiy, Oleksandr Shkiliuk, Mykhailo Zmysnyi, and Pavlo Kazan. "Functional safety analysis of safety-critical system using state transition diagram." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 2 (May 18, 2022): 145–58. http://dx.doi.org/10.32620/reks.2022.2.12.

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The subject of research is to determine the functional safety indicators of a fault-tolerant safety-critical system, namely, the minimal cut sets’ probability for a given duration of the system’s operation, using the state transition diagram (STD). The aim is to create a new method for analyzing the functional safety of a fault-tolerant safety-critical system. This method is based on the methodology of developing models of operational reliability behavior in the form of STD. This methodology provides a detailed representation of inoperable states and their relation with pre-failure (inoperable critical) states. The task is to propose a new classification for inoperable states of the STD to obtain all possible emergencies in the same space of inoperable states. This approach allows consideration the correlations between the failures, that it is impossible to use the fault trees. Since the space of inoperable states can reach hundreds and thousands of states, a method is proposed for their automated determination according to the classification. The state space method was used to conduct the validation of the method of functional safety analysis. The following results were obtained: the system of Chapman-Kolmogorov differential equations is formed in accordance with the STD and it provides the dependence of the functional safety indicator – the minimal cut sets’ probability as a function of the operational duration of the fault-tolerant safety-critical system. This dependence is called the emergency function. The method for determining the emergency function is based on the usage of the emergency mask. Note that the proposed model of operational reliability behavior in the form of STD provides the possibility to conduct both the functional safety and the reliability indicators. The value of the minimal cut sets’ probability for a given duration of operation is determined using the fault tree for the validation of the proposed method of functional safety analysis. The fault tree was built by Reliasoft BlockSim software. The obtained value coincides with the value of the minimal cut sets’ probability, which was defined by the emergency function for the same operational duration. Thus, the designer can comprehensively analyze the feasibility of introducing redundancy (structural, temporal, functional). Conclusions: the scientific novelty of the obtained results is the following: the new method for determining safe, critical and catastrophic states in the set of inoperable states is used in the methodology of the STD developing to obtain the stochastic model of operational reliability behavior of fault-tolerant safety-critical system. This technique ensures an automated defining of emergency function by using an improved structural-automatic model.

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Nan, Yu, and Li Jun-zhou. "Extend Dynamic Fault Tree Algorithm Based on Stochastic Petri Net and Micro-Satellite On-Board Computer Case Analysis." Open Automation and Control Systems Journal 7, no. 1 (September 14, 2015): 1051–56. http://dx.doi.org/10.2174/1874444301507011051.

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Kumar, Ranjan, Pavel Kudinov, Sevostian Bechta, Florence Curnier, and Michel Marques. "Dynamic Hybrid Reliability Studies of a Decay Heat Removal System." International Journal of Reliability, Quality and Safety Engineering 22, no. 04 (August 2015): 1550020. http://dx.doi.org/10.1142/s0218539315500205.

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Some critical safety systems exhibit the characteristics of hybrid stochastic class whose performance depends on the dynamic interactions of deterministic variables of physical phenomena and probabilistic variables of system failures. However, conventional probabilistic safety assessment (PSA) method involves static event and linked fault tree analysis and does not capture the dynamic interactions of such hybrid stochastic systems. Additionally, the existing dynamic PSA methods do not consider any repair possibility of some failed components during safety assessment. To address these issues, this paper presents a dynamic hybrid reliability assessment scheme for performance studies of repairable nuclear safety systems during a mission time. This scheme combines the features of reliability block diagram (RBD) for system compositions and partial differential equations for system physics using a customized stochastic hybrid automata tool implemented on Python platform. A case study of decay heat removal (DHR) systems has been performed using the introduced scheme. The impacts of failure rates and repair rates on sodium temperature evolution over a mission time have been analyzed. The results provide useful safety insights in mission safety tests of DHR systems. In sum, this work advances the dynamic safety assessment approach for complex system designs including nuclear power plants.

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Kuznetsov, Mykola, Igor Kuznetsov, and Alla Shumska. "EVALUATING THE STOCHASTIC GRADIENT TO OPTIMIZE THE EFFICIENCY OF SYSTEMS WHICH ARE DESCRIBED BY FAULT TREES WITH EFFICIENCY." International Scientific Technical Journal "Problems of Control and Informatics 67, no. 4 (September 1, 2022): 76–88. http://dx.doi.org/10.34229/2786-6505-2022-4-6.

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The system is considered, the structure and functioning of which is described by a fault tree with efficiency. It is a model that makes it possible to describe in a formalized form the process of changing the efficiency of the system and its subsystems operation under the influence of components failures and repair terminations. The failure-free operation times and repair times of components have distribution functions of the general form. The studied characteristic is the mean system efficiency in a fixed time interval. A general method enabling to construct the stochastic gradient of some functional from the trajectories of the Markov process describing the behavior of the system, with respect to normalizing parameters of some random variables is proposed. The unbiasedness of the estimates is proved. This method is applied to evaluate the stochastic gradient of the average system efficiency with respect to some normalizing parameters of the failure-free operation time of the components. The corresponding algorithm is given. A numerical example demonstrates the application of this method for the determining of mathematically justified requirements to the reliability of components in order to ensure the required average efficiency of system operation in a given time interval.

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Tian, Heng, Fuhai Duan, Liang Fan, and Yong Sang. "Fault diagnostic strategy of multivalued attribute system based on growing algorithm." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 2 (May 1, 2018): 235–45. http://dx.doi.org/10.1177/1748006x18770356.

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Traditionally, fault diagnostic strategy is used to obtain the optimal test sequence for binary systems. Actually, a lot of systems are not binary systems, such as multivalued attribute systems. Traditional algorithms generating the test sequence for binary systems and multivalued attribute systems select tests, and then identify and isolate the failure states based on the outcomes of tests. In this study, a novel diagnostic strategy for multivalued attribute system is introduced. This strategy chooses failure states and then finds a suitable test set for the selected failure states. This can avoid the backtracking approach of traditional algorithms. In order to implement this strategy, three main procedures are presented: (1) test sequencing problem is simplified to a combination of the basic test sets with unnecessary tests, and the sets for fault detection and isolation are defined, (2) the optimal test sequence generating algorithm for an individual failure state is proposed, and (3) the priority levels of failure state are determined based on the probability, and a new algorithm, which is used to generate the test sequence for all failure states, is presented. As the implementation process for the new algorithm resembles the growth of branches on a tree, it is defined as growing algorithm. Finally, two cases are used to show how the growing algorithm works, and stochastic simulation experiments are employed to validate universality and stability of the algorithm. The case studies and stochastic simulation experiments demonstrate that the results obtained by the growing algorithm are as accurate as those obtained by the rollout algorithm, and the growing algorithm needs a short running time. Therefore, the growing algorithm is suitable for multivalued attribute system, and it obtains good calculation results with a short running time and high efficiency.

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Ahmed, Hosameldin O. A., and Asoke K. Nandi. "Intrinsic Dimension Estimation-Based Feature Selection and Multinomial Logistic Regression for Classification of Bearing Faults Using Compressively Sampled Vibration Signals." Entropy 24, no. 4 (April 5, 2022): 511. http://dx.doi.org/10.3390/e24040511.

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As failures of rolling bearings lead to major failures in rotating machines, recent vibration-based rolling bearing fault diagnosis techniques are focused on obtaining useful fault features from the huge collection of raw data. However, too many features reduce the classification accuracy and increase the computation time. This paper proposes an effective feature selection technique based on intrinsic dimension estimation of compressively sampled vibration signals. First, compressive sampling (CS) is used to get compressed measurements from the collected raw vibration signals. Then, a global dimension estimator, the geodesic minimal spanning tree (GMST), is employed to compute the minimal number of features needed to represent efficiently the compressively sampled signals. Finally, a feature selection process, combining the stochastic proximity embedding (SPE) and the neighbourhood component analysis (NCA), is used to select fewer features for bearing fault diagnosis. With regression analysis-based predictive modelling technique and the multinomial logistic regression (MLR) classifier, the selected features are assessed in two case studies of rolling bearings vibration signals under different working loads. The experimental results demonstrate that the proposed method can successfully select fewer features, with which the MLR-based trained model achieves high classification accuracy and significantly reduced computation times compared to published research.

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Okwuosa, Chibuzo Nwabufo, and Jang-wook Hur. "A Filter-Based Feature-Engineering-Assisted SVC Fault Classification for SCIM at Minor-Load Conditions." Energies 15, no. 20 (October 14, 2022): 7597. http://dx.doi.org/10.3390/en15207597.

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In most manufacturing industries, squirrel cage induction motors (SCIMs) are essential due to their robust nature, high torque generation, and low maintenance costs, so their failure often times affects productivity, profitability, reliability, etc. While various research studies presented techniques for addressing most of these machines’ prevailing issues, fault detection in cases of low slip or, low load, and no loading conditions for motor current signature analysis still remains a great concern. When compared to the impact on the machine at full load conditions, fault detection at low load conditions helps mitigate the impact of the damage on SCIM and reduces maintenance costs. Using stator current data from the SCIM’s direct online starter method, this study presents a feature engineering-aided fault classification method for SCIM at minor-load conditions based on a filter approach using the support vector classification (SVC) algorithm as the classifier. This method leverages the loop-hole of the Fourier Transform at minor-load conditions by harnessing the uniqueness of the Hilbert Transform (HT) to present a methodology that combines different feature engineering technologies to excite, extract, and select 10 discriminant information using a filter-based approach as the selection tool for fault classification. With the selected features, the SVC performed exceptionally well, with a significant diagnostic performance accuracy of 97.32%. Further testing with other well-known robust classifiers such as decision tree (DT), random forest (RF), k-nearest neighbor (KNN), gradient boost classifier (GBC), stochastic gradient descent (SGD), and global assessment metrics revealed that the SVC is reliable in terms of accuracy and computation speeds.

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Zeng, Yining, Rongxing Duan, Shujuan Huang, and Tao Feng. "Reliability analysis for complex systems based on generalized stochastic petri nets and EDA approach considering common cause failure." Engineering Computations 37, no. 5 (December 19, 2019): 1513–30. http://dx.doi.org/10.1108/ec-05-2019-0241.

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Purpose This paper aims to deal with the problems of failure dependence and common cause failure (CCF) that arise in reliability analysis of complex systems. Design/methodology/approach Firstly, a dynamic fault tree (DFT) is used to capture the dynamic failure behaviours and converted into an equivalent generalized stochastic petri net (GSPN) for quantitative analysis. Secondly, an efficient decomposition and aggregation (EDA) theory is combined with GSPN to deal with the CCF problem, which exists in redundant systems. Finally, Birnbaum importance measure (BIM) is calculated based on the EDA approach and GSPN model, and it is used to take decisions for system improvement and fault diagnosis. Findings In this paper, a new reliability evaluation method for dynamic systems subject to CCF is presented based on the DFT analysis and the GSPN model. The GSPN model is easy to capture dynamic failure behaviours of complex systems, and the movement of tokens in the GSPN model represent the changes in the state of the systems. The proposed method takes advantage of the GSPN model and incorporates the EDA method into the GSPN, which simplifies the reliability analysis process. Meanwhile, simulation results under different conditions show that CCF has made a considerable impact on reliability analysis for complex systems, which indicates that the CCF should not be ignored in reliability analysis. Originality/value The proposed method combines the EDA theory with the GSPN model to improve the efficiency of the reliability analysis.

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Arena, Simone, Irene Roda, and Ferdinando Chiacchio. "Integrating Modelling of Maintenance Policies within a Stochastic Hybrid Automaton Framework of Dynamic Reliability." Applied Sciences 11, no. 5 (March 5, 2021): 2300. http://dx.doi.org/10.3390/app11052300.

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The dependability assessment is a crucial activity for determining the availability, safety and maintainability of a system and establishing the best mitigation measures to prevent serious flaws and process interruptions. One of the most promising methodologies for the analysis of complex systems is Dynamic Reliability (also known as DPRA) with models that define explicitly the interactions between components and variables. Among the mathematical techniques of DPRA, Stochastic Hybrid Automaton (SHA) has been used to model systems characterized by continuous and discrete variables. Recently, a DPRA-oriented SHA modelling formalism, known as Stochastic Hybrid Fault Tree Automaton (SHyFTA), has been formalized together with a software library (SHyFTOO) that simplifies the resolution of complex models. At the state of the art, SHyFTOO allows analyzing the dependability of multistate repairable systems characterized by a reactive maintenance policy. Exploiting the flexibility of SHyFTA, this paper aims to extend the tools’ functionalities to other well-known maintenance policies. To achieve this goal, the main features of the preventive, risk-based and condition-based maintenance policies will be analyzed and used to design a software model to integrate into the SHyFTOO. Finally, a case study to test and compare the results of the different maintenance policies will be illustrated.

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Yang, Haiyun, Youchao Sun, Longbiao Li, Yundong Guo, Siyu Su, and Qijun Huangfu. "Safety Analysis of Integrated Modular Avionics System Based on FTGPN Method." International Journal of Aerospace Engineering 2020 (September 1, 2020): 1–12. http://dx.doi.org/10.1155/2020/8811565.

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Compared with federated avionic architecture, the integrated modular avionic (IMA) system architecture in the aircraft can provide more sophisticated and powerful avionic functionality, and meanwhile, it becomes structurally dynamic, variably interconnected, and highly complex. The traditional approach such as fault tree analysis (FTA) becomes neither convenient nor sufficient in making safety analysis of the IMA system. In order to overcome the limitations, the approach that FTA combines with generalized stochastic petri net (GSPN) is proposed. First, FTA is used to establish the static model for the top level of the IMA system, while GSPN is used to build a dynamic model for each cell system. Finally, the combination model is generated, which is called the FTGPN model. Moreover, the FTGPN model is made safety analysis with the PIPE2 tool. According to the simulation result, corresponding measures are taken to meet the safety requirements of the IMA system.

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Li, Yao, Caichao Zhu, Xu Chen, and Jianjun Tan. "Fatigue Reliability Analysis of Wind Turbine Drivetrain Considering Strength Degradation and Load Sharing Using Survival Signature and FTA." Energies 13, no. 8 (April 23, 2020): 2108. http://dx.doi.org/10.3390/en13082108.

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The wind turbine drivetrain suffers significant impact loads that severely affect the reliability and safety of wind turbines. Bearings and gears within the drivetrain are critical components with high repair costs and lengthy downtime. To realistically assess the system reliability, we propose to establish an electromechanical coupling dynamic model of the wind turbine considering the control strategy and environmental parameters and evaluate the system’s reliability of wind turbine drivetrain based on loads of gears and bearings. This paper focuses on the dynamic reliability analysis of the wind turbine under the control strategy and environmental conditions. SIMPACK (v9.7, Dassault Systèmes, Gilching, Germany) is used to develop the aero-hydro-servo-elastic coupling dynamic model with the full drivetrain that considers the flexibility of the tower and blade, the stochastic loads of wind and waves, gear meshing features, as well as the control strategy. The system reliability level of wind turbine drivetrain at different wind conditions is assessed using survival signature and fault tree analysis (FTA), and the influences of strength degradation of the transmission components on the system reliability are explored. Following this, the bending fatigue reliability and contact fatigue reliability concerning different wind conditions are compared in this paper. A case study is performed to demonstrate the effectiveness and feasibility of the proposed methodology.

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Zhou, Xuesheng, Jun Yang, Jian Wang, and Jingwei Li. "Model and simulation of the fuzzy reliability assessment of the electric vehicle motor." Advances in Mechanical Engineering 14, no. 8 (August 2022): 168781322211204. http://dx.doi.org/10.1177/16878132221120406.

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The energy crisis has spurred the development of electric vehicles (EVs). As one of key components of EVs, the reliability of motor drive system directly affects the wide application of EVs. Due to the bad working environment and complex working mode, the reliability of the motor is more prominent. However, at present, there are few researches on the reliability of drive motor of EVs. Therefore, research on the reliability of electric vehicle motor drive system is of great significance. In this work, the reliability theory and prior motor reliability work were applied to the validity research of driving motor of EVs. Correlation studies were performed by using a permanent magnet synchronous motor. The failure modes of the driving motor and factors influencing reliability were examined considering the environment and motor to establish a fault tree model and analyze reliability weaknesses, including the winding insulation, bearings, and permanent magnets. The reliability of the motor was then modeled via MATLAB using a hybrid intelligent algorithm based on stochastic simulation and a neural network. The results showed that the model and the algorithm were effective. In addition, this work is helpful for electric vehicle designers to improve the reliability of electric vehicle motors.

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Marhavilas, Panagiotis K., Michael G. Tegas, Georgios K. Koulinas, and Dimitrios E. Koulouriotis. "A Joint Stochastic/Deterministic Process with Multi-Objective Decision Making Risk-Assessment Framework for Sustainable Constructions Engineering Projects—A Case Study." Sustainability 12, no. 10 (May 23, 2020): 4280. http://dx.doi.org/10.3390/su12104280.

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This study, on the one hand, develops a newfangled risk assessment and analysis (RAA) methodological approach (the MCDM-STO/DET one) for sustainable engineering projects by the amalgamation of a multicriteria decision-making (MCDM) process with the joint-collaboration of a deterministic (DET) and a stochastic (STO) process. On the other hand, proceeds to the application of MCDM-STO/DET at the workplaces of the Greek construction sector and also of the fixed-telecommunications technical projects of OTE SA (that is, the Greek Telecommunications Organization S.A.) by means of real accident data coming from two official State databases, namely of “SEPE” (Labor Inspectorate, Hellenic Ministry of Employment) and of “IKA” (Social Insurance Institution, Hellenic Ministry of Health), all the way through the period of the years2009–2016.Consequently, the article’s objectives are the following: (i) The implementation and execution of the joint MCDM-STO/DET framework, and (ii) to make known that the proposed MCDM-STO/DET algorithm can be a precious method for safety managers (and/or decision-makers) to ameliorate occupational safety and health (OSH) and to endorse the sustainable operation of technical or engineering projects as well. Mainly, we mingle two different configurations of the MCDM method, initially the Analytical Hierarchy-Process (the typical-AHP), and afterwards the Fuzzy-Extended AHP (the FEAHP) one, along with the Proportional Risk Assessment Technique (PRAT) and the analysis of Time-Series Processes (TSP), and finally with the Fault-Tree Analysis (FTA).

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Shoar, Shahab, Hamid R. Zarandi, Farnad Nasirzadeh, and Elham Cheshmikhani. "Fast Fault Tree Analysis for Hybrid Uncertainties Using Stochastic Logic Implemented on Field-Programmable Gate Arrays: An Application in Quantitative Assessment and mitigation of Welding Defects Risk." Quality and Reliability Engineering International 33, no. 7 (December 1, 2016): 1367–85. http://dx.doi.org/10.1002/qre.2110.

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Chiacchio, Ferdinando, Fabio Famoso, Diego D’Urso, and Luca Cedola. "Performance and Economic Assessment of a Grid-Connected Photovoltaic Power Plant with a Storage System: A Comparison between the North and the South of Italy." Energies 12, no. 12 (June 19, 2019): 2356. http://dx.doi.org/10.3390/en12122356.

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Grid-connected low voltage photovoltaic power plants cover most of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night-time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies, the installation of a system of battery looks like a promising solution by giving the possibility to increase auto-consumption dramatically. In this paper, a model-based approach to analyze and discuss the performance and the economic feasibility of grid-connected domestic photovoltaic power plants with a storage system is presented. Using as input to the model the historical series (2008–2017) of the main ambient variables, the proposed model, based on Stochastic Hybrid Fault Tree Automaton, allowed us to simulate and compare two alternative technical solutions characterized by different environmental conditions, in the north and in the south of Italy. The performances of these systems were compared and an economic analysis, addressing the convenience of the storage systems was carried out, considering the characteristic useful-life time, 20 years, of a photovoltaic power plant. To this end the Net Present Value and the payback time were evaluated, considering the main characteristics of the Italian market scenario.

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Nguyen, Tuan Anh, Dugki Min, and Jong Sou Park. "A Comprehensive Sensitivity Analysis of a Data Center Network with Server Virtualization for Business Continuity." Mathematical Problems in Engineering 2015 (2015): 1–20. http://dx.doi.org/10.1155/2015/521289.

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Sensitivity assessment of availability for data center networks (DCNs) is of paramount importance in design and management of cloud computing based businesses. Previous work has presented a performance modeling and analysis of a fat-tree based DCN using queuing theory. In this paper, we present a comprehensive availability modeling and sensitivity analysis of a DCell-based DCN with server virtualization for business continuity using stochastic reward nets (SRN). We use SRN in modeling to capture complex behaviors and dependencies of the system in detail. The models take into account (i) two DCell configurations, respectively, composed of two and three physical hosts in a DCell0unit, (ii) failure modes and corresponding recovery behaviors of hosts, switches, and VMs, and VM live migration mechanism within and between DCell0s, and (iii) dependencies between subsystems (e.g., between a host and VMs and between switches and VMs in the same DCell0). The constructed SRN models are analyzed in detail with regard to various metrics of interest to investigate system’s characteristics. A comprehensive sensitivity analysis of system availability is carried out in consideration of the major impacting parameters in order to observe the system’s complicated behaviors and find the bottlenecks of system availability. The analysis results show the availability improvement, capability of fault tolerance, and business continuity of the DCNs complying with DCell network topology. This study provides a basis of designing and management of DCNs for business continuity.

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Galiatsatou, Panagiota, Christos Makris, and Panayotis Prinos. "Optimized Reliability Based Upgrading of Rubble Mound Breakwaters in a Changing Climate." Journal of Marine Science and Engineering 6, no. 3 (August 2, 2018): 92. http://dx.doi.org/10.3390/jmse6030092.

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The present work aims at presenting an approach on implementing appropriate mitigation measures for the upgrade of rubble mound breakwaters protecting harbors and/or marinas against increasing future marine hazards and related escalating exposure to downtime risks. This approach is based on the reliability analysis of the studied structure coupled with economic optimization techniques. It includes the construction of probability distribution functions for all the stochastic variables of the marine climate (waves, storm surges, and sea level rise) for present and future conditions, the suggestion of different mitigation options for upgrading, the construction of a fault tree providing a logical succession of all events that lead to port downtime for each alternative mitigation option, and conclusively, the testing of a large number of possible alternative geometries for each option. A single solution is selected from the total sample of acceptable geometries for each upgrading concept that satisfy a probabilistic constraint in order to minimize the total costs of protection. The upgrading options considered in the present work include the construction or enhancement of a crown wall on the breakwater crest, the addition of the third layer of rocks above the primary armor layer of the breakwater (combined with crest elements), the attachment of a berm on the primary armor layer, and the construction of a detached low-crested structure in front of the breakwater. The proposed methodology is applied to an indicative rubble mound breakwater with an existing superstructure. The construction of a berm on the existing primary armor layer of the studied breakwater (port of Deauville, France), seems to be advantageous in terms of optimized total costs compared to other mitigation options.

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Chybowski, Leszek, Daniel Wiaterek, and Andrzej Jakubowski. "The Impact of Marine Engine Component Failures upon an Explosion in the Starting Air Manifold." Journal of Marine Science and Engineering 10, no. 12 (December 1, 2022): 1850. http://dx.doi.org/10.3390/jmse10121850.

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Based on available sources, the frequency of explosions in the marine engine’s starting air manifolds is determined under real conditions. A cause-and-effect analysis of these explosions and their root causes are identified. A probabilistic model of an explosion in the starting air manifold of a marine engine is built using a fault tree analysis (FTA). Using a stochastic simulation (Monte Carlo) and an exact reliability availability calculation (ERAC) algorithm applied to the developed FTA model, selected reliability measures are calculated to describe an incident of the top event, which involves an explosion in the starting air manifold. For such an event, several factors are calculated, including the availability, the unavailability, the failure frequency, and the mean time to failure. Based on the simulations, the relative frequency of the top event is determined in relation to the number of events that can simultaneously occur and lead to an explosion. The significance of each basic event is assessed to determine their individual impact on the explosion incident. The following measures are used: the Vesely–Fussell measure of importance, the criticality measure of importance, the Birnbaum measure of reliability importance, and the Birnbaum measure of structural importance. The results of the analysis show that defective starting air valves are most responsible for the explosion incident in the starting air manifold. During the first year of the ship’s operation, the reliability does not fall below the value of 0.65, while the mean time to failure and the top event frequency are statistically at the level of one explosion per approximately 2.28 years of continuous engine operation.

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Fourneau, Jean-Michel, and Nihal Pekergin. "Dynamic Fault Trees with Rejuvenation: Numerical Analysis and Stochastic Bounds." Electronic Notes in Theoretical Computer Science 327 (October 2016): 27–47. http://dx.doi.org/10.1016/j.entcs.2016.09.022.

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Manno, Gabriele, Ferdinando Chiacchio, and Francesco Pappalardo. "The Dynamic-to-Static Conversion of Dynamic Fault Trees Using Stochastic Dependency Graphs and Stochastic Activity Networks." Engineering 05, no. 02 (2013): 157–66. http://dx.doi.org/10.4236/eng.2013.52023.

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Zhu, Peican, Jie Han, Leibo Liu, and Ming J. Zuo. "A Stochastic Approach for the Analysis of Fault Trees With Priority AND Gates." IEEE Transactions on Reliability 63, no. 2 (June 2014): 480–94. http://dx.doi.org/10.1109/tr.2014.2313796.

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Cheshmikhani, Elham, and Hamid R. Zarandi. "Probabilistic analysis of dynamic and temporal fault trees using accurate stochastic logic gates." Microelectronics Reliability 55, no. 11 (November 2015): 2468–80. http://dx.doi.org/10.1016/j.microrel.2015.06.047.

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FLAMMINI, FRANCESCO, STEFANO MARRONE, MAURO IACONO, NICOLA MAZZOCCA, and VALERIA VITTORINI. "A MULTIFORMALISM MODULAR APPROACH TO ERTMS/ETCS FAILURE MODELING." International Journal of Reliability, Quality and Safety Engineering 21, no. 01 (February 2014): 1450001. http://dx.doi.org/10.1142/s0218539314500016.

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European Railway Traffic Management System/European Train Control System (ERTMS/ETCS) is a recent standard aimed at improving performance, safety and inter-operability of modern railways. In order to be compliant to ERTMS/ETCS, a railway signalling system must meet strict nonfunctional requirements on system level failure modes. In this paper, a multiformalism model is employed to perform an availability analysis of an ERTMS/ETCS reference architecture at early phases of its development cycle. At this aim, a bottom-up analysis is performed from subsystem failure models (expressed by means of Generalized Stochastic Petri Nets, Fault Trees and Repairable Fault Trees) up to the overall system model. The modular approach, here used, allows to evaluate the influence of basic design parameters on the probability of system-level failure modes and demonstrates that system availability is within the bound required by the ERTMS/ETCS specification. The results show that the multiformalism modeling approach helps to cope with complexity, eases the verification of availability requirements and can be successfully applied to the analysis of complex critical systems.

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Codetta-Raiteri, Daniele. "The Conversion of Dynamic Fault Trees to Stochastic Petri Nets, as a case of Graph Transformation." Electronic Notes in Theoretical Computer Science 127, no. 2 (March 2005): 45–60. http://dx.doi.org/10.1016/j.entcs.2005.02.005.

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Zhu, Peican, Jie Han, Leibo Liu, and Fabrizio Lombardi. "A Stochastic Approach for the Analysis of Dynamic Fault Trees With Spare Gates Under Probabilistic Common Cause Failures." IEEE Transactions on Reliability 64, no. 3 (September 2015): 878–92. http://dx.doi.org/10.1109/tr.2015.2419214.

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Zhang, Zelin, Jun Wu, Yufeng Chen, Ji Wang, and Jinyu Xu. "Distinguish between Stochastic and Chaotic Signals by a Local Structure-Based Entropy." Entropy 24, no. 12 (November 30, 2022): 1752. http://dx.doi.org/10.3390/e24121752.

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As a measure of complexity, information entropy is frequently used to categorize time series, such as machinery failure diagnostics, biological signal identification, etc., and is thought of as a characteristic of dynamic systems. Many entropies, however, are ineffective for multivariate scenarios due to correlations. In this paper, we propose a local structure entropy (LSE) based on the idea of a recurrence network. Given certain tolerance and scales, LSE values can distinguish multivariate chaotic sequences between stochastic signals. Three financial market indices are used to evaluate the proposed LSE. The results show that the LSEFSTE100 and LSES&P500 are higher than LSESZI, which indicates that the European and American stock markets are more sophisticated than the Chinese stock market. Additionally, using decision trees as the classifiers, LSE is employed to detect bearing faults. LSE performs higher on recognition accuracy when compared to permutation entropy.

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Kanj, Hassan, Wael Hosny Fouad Aly, and Sawsan Kanj. "A Novel Dynamic Approach for Risk Analysis and Simulation Using Multi-Agents Model." Applied Sciences 12, no. 10 (May 17, 2022): 5062. http://dx.doi.org/10.3390/app12105062.

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Static risk analysis techniques (SRATs) use event graphs and risk analysis assessment models. Those techniques are not time-based techniques and hence are inadequate to model dynamic stochastic systems. This paper proposes a novel dynamic approach to model such stochastic systems using Dynamic Fault Trees (DFT). The proposed model is called Generic Dynamic Agent-Based Model (GDABM) for risk analysis. GDABM is built on top of the well-known Agent-Based Modeling and Simulation (ABMS) technique. GDABM can model the dynamic system agents in both nominal (failure-free) and degraded (failure) modes. GDABM shows the propagation of failure between system elements and provides complete information about the system’s configurations. In this paper, a complete detailed case study is provided to show the GDABM capabilities to model and study the risk analysis for such dynamic systems. In the case study, the GDABM models the risk analysis for a chemical reactor/operator and performs a complete risk analysis for the entire system. The GDABM managed to simulate the dynamic behavior of the system’s components successfully using Repast Simphony 2.0. Detailed agent behavioral modes and failure modes are provided with various scenarios, including different time stamps. The proposed GDABM is compared to a reference model. The reference model is referred to as the ABM model. GDABM has given very promising results. A comparison study was performed on three performance measures. The performance measures used are (1) Accuracy, (2) response time, and (3) execution time. GDABM has outperformed the reference model by 15% in terms of accuracy and by 27% in terms of response time. GDABM incurs a slightly higher execution time (13%) when compared to the ABM reference model. It can be concluded that GDABM can deliver accepted performance in terms of accuracy and response time without incurring much processing overhead.

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Zeng, Yining, Rongxing Duan, Tao Feng, Shujuan Huang, and Jiejun He. "A fault diagnostic system based on Petri nets and gray relational analysis for train–ground wireless communication systems." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, April 1, 2021, 1748006X2110069. http://dx.doi.org/10.1177/1748006x211006993.

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The system structure of train–ground wireless communication systems (TWCSs) is extremely complicated due to the use of fault tolerant technology to improve their performance. This complex structure raises several challenges in fault diagnosis for TWCSs, such as epistemic uncertainty, dynamic fault behaviors, and common cause failure (CCF). A fault diagnostic system is proposed to deal with these challenges based on Petri nets and gray relational analysis in this paper. Specifically, the fuzzy analytic hierarchy process is used to evaluate the failure data of components to handle epistemic uncertainty. Furthermore, the dynamic fault tree of TWCSs is established and converted into a generalized stochastic Petri net to calculate several reliability parameters used for fault diagnosis. Besides, a β factor model is employed to resolve the problem of CCF in TWCSs. In addition, Birnbaum importance measure (BIM), risk achievement worth (RAW) and test cost are considered comprehensively to obtain the optimal diagnostic sequence using an improved gray relational analysis. Finally, a numerical example is presented to demonstrate the efficiency of the proposed fault diagnostic system.

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Gurunathan, Thangamani. "Availability modeling and estimation of Fluid Catalytic Cracking Unit using generalized Stochastic Petri Nets." International Journal of Quality & Reliability Management ahead-of-print, ahead-of-print (December 22, 2020). http://dx.doi.org/10.1108/ijqrm-07-2019-0242.

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PurposeThe purpose of this paper to present a practical and systematic approach to estimate the availability of a process plant using generalized stochastic Petri nets (GSPNs). The actual live problem at a fluid catalytic cracking unit (FCCU) of a refinery is used to demonstrate this approach.Design/methodology/approachA majority of models used for estimation of availability of a complex system are based on the assumptions that the failure of the system is associated with only a few states, and the system does not face different operating conditions, repair actions and common-cause failures. In reality, this is often not the case. Therefore, it is necessary to construct more sophisticated models without such assumptions. In this paper, an attempt has been made to model interaction of component failures, partial failures of components and common-cause failures.FindingsThe superiority of this approach over other modeling approaches such as fault tree and Markov analysis is demonstrated. The proposed GSPN is a promising tool that can be conveniently used to model and analyze any complex systems.Practical implicationsGSPN was used to model the reactor-regenerator section of FCCU, which is quite a large system, which shows the strength of modeling capability. The use of Petri nets (PNs) for modeling complex systems for the purpose of availability assessment is demonstrated in this paper. Sensitivity analysis was also carried out for various subsystem/components.Originality/valueNo similar work has been conducted for FCCU using GSPN as per literature incorporating different operating conditions and common-cause failures. The understanding and usage of PNs require a steep learning curve for the practitioners, and this paper provides an approach to estimate availability measures for the complex system.

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Dantuluri, Naveen Aditya Verma, and Pierluigi Pisu. "Safety Diagnostics and Degraded Operational Modes." Annual Conference of the PHM Society 13, no. 1 (November 24, 2021). http://dx.doi.org/10.36001/phmconf.2021.v13i1.3038.

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Unmanned ground combat vehicles (UGCV) promise numerous ultimate military, civilian, and space applications. The focus of this research mainly deals with how a non-geometric hazard scenario may potentially lead to a mission ending situation and a non geometric hazard can be considered as any terrain feature or object that is adjudged to be non-traversable by virtue of its physical properties. The novelty of this research lies in how a UGCV in a military applications can overcome the challenges of traversing through ever changing natural obstacles when compared to the reinforcing obstacles which are encountered by autonomous vehicle in a conventional structured scenario (see Figure 1).Figure 1. Traversal across an off-road terrain facing uneven terrain and obstacles.An operational design domain (ODD) can help specify potential unsafe situations and restrict the vehicle’s operation within them. A complete ODD will guarantee that the safety arguments can be dealt in a streamlined manner and in scenarios of restricting the ODD, the overall availability of the system gets reduced. With a semantic ODD structure for the UGVC, the standard development of the safety process for an automotive system is achieved and with the already created safety protocols, the overall situation space is reduced during critical situations.DISTRIBUTION A. Approved for public release; distribution unlimited. OPSEC5045The process of identifying reduced operational domain (ROD) starts with the quantificationand analysis of maneuvers and further leads to the identification of critical situations. Criticalareas are conditions of the environment that cause unintentional behaviour which eventuallyleads to an accident. A state machine constituting nominal behaviour will form the basis for acomponent fault tree (CFT) which is used to identify conditions that cause critical situations.Subsequently, the corresponding risk of an identified critical situation is assessed as a part ofthis process.The safety diagnostics mainly depends on a probabilistic model-based controller examining adynamic environment in which the stochastic evolution depends on the input of observationsand the current behaviour of the UGCV. In order to model the real-life performance of safetycritical systems realistically and accurately, Markov chain and Bayesian filters are highlyuseful. The finite state essence of the discrete controller may possibly lead to incorrectbehaviour of the complete system if an unforeseen situation occurs and for which there is alack of any predefined contingency. For this purpose, it becomes important to have a sense ofa complete set of admissible scenarios and also to develop a structured decision-making processfor each of the previously mentioned scenarios. State machine and failure propagation treescan help in determining the failure probabilities which keep updating based on changes incircumstances and this would help define if a mission should continue. As a part of thisresearch, Markov decision process which forms the basis for decision making process isemployed to identify and compare a set of state sequences and this in turn would help inrealizing better maneuverability of the vehicle.The assignment of ROD can be accomplished with the complete risk assessment of the criticalsituations. By assigning the ROD, the aim of increasing the overall availability of the systemwhich degraded from the nominal driving behaviour is fulfilled and this would allow for thesafe operation of UGCV.

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Hensel, Christian, Sebastian Junges, Joost-Pieter Katoen, Tim Quatmann, and Matthias Volk. "The probabilistic model checker Storm." International Journal on Software Tools for Technology Transfer, July 6, 2021. http://dx.doi.org/10.1007/s10009-021-00633-z.

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AbstractWe present the probabilistic model checker Storm. Storm supports the analysis of discrete- and continuous-time variants of both Markov chains and Markov decision processes. Storm has three major distinguishing features. It supports multiple input languages for Markov models, including the Jani and Prism modeling languages, dynamic fault trees, generalized stochastic Petri nets, and the probabilistic guarded command language. It has a modular setup in which solvers and symbolic engines can easily be exchanged. Its Python API allows for rapid prototyping by encapsulating Storm’s fast and scalable algorithms. This paper reports on the main features of Storm and explains how to effectively use them. A description is provided of the main distinguishing functionalities of Storm. Finally, an empirical evaluation of different configurations of Storm on the QComp 2019 benchmark set is presented.

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Journal articles on the topic 'Stochastic Fault Tree'

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