Wyniki wyszukiwania - BazTech

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Belief reliability-based design optimization method with quantile index under epistemic uncertainty

Chen Yubing, Wen Meilin, Zhang Qingyuan, Kang Rui

Eksploatacja i Niezawodność

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2023

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Vol. 25, no. 2

art. no. 163545

EN

Product reliability design optimization is affected by epistemic uncertainty greatly, which leaves significant risks in product use. In this paper, a new belief reliability-based design optimization (BRBDO) method under epistemic uncertainty is established to handle this problem. First, the belief reliability theory is introduced into the design optimization problem, and a quantile index is proposed to quantify belief reliability level based on uncertainty theory, through which a rapid analysis method called first order belief reliability analysis (FOBRA) method is developed. Then, according to the different trade-off strategies, two types of design optimization models are established, and corresponding FOBRA-based computation methods are also demonstrated. Finally, several case applications are studied to verify the effectiveness of the analysis and design optimization methods proposed in this paper. The results indicate that the BRODO method with the quantile index can save a lot of computational time with acceptable accuracy and can rationally cope with epistemic uncertainty.

2

Effective sensor placement based on a VIKOR method considering common cause failure in the presence of epistemic uncertainty

Duan Rong-Xing, He Jie-Jun, Feng Tao, Huang Shu-Juan, Chen Li

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 2

253--262

EN

Owing to expensive cost and restricted structure, limited sensors are allowed to install in modern systems to monitor the working state, which can improve their availability. Therefore, an effective sensor placement method is presented based on a VIKOR algorithm considering common cause failure (CCF) under epistemic uncertainty in this paper. Specifically, a dynamic fault tree (DFT) is developed to build a fault model to simulate dynamic fault behaviors and some reliability indices are calculated using a dynamic evidence network (DEN). Furthermore, a VIKOR method is proposed to choose the possible sensor locations based on these indices. Besides, a sensor model is introduced by using a priority AND gate (PAND) to describe the failure sequence between a sensor and a component. All placement schemes can be enumerated when the number of sensors is given, and the largest system reliability is the best alternative among the placement schemes. Finally, a case study shows that CCF has some influence on sensor placement and cannot be neglected in the reliabilitybased sensor placement.

3

Reliability-based safety evaluation of the BISTOON historic masonry arch bridge

Pouraminian Majid, Pourbakhshian Somayyeh, Noroozinejad Farsangi Ehsan, Berenji Sevil, Keyani Borujeni Salman, Moosavi Asl Mirhasan, Mohammad Hosseini Mehdi

Civil and Environmental Engineering Reports

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2020

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Vol. 30, no. 1

87--110

EN

This research examines the probabilistic safety assessment of the historic BISTOON arch bridge. Probabilistic analysis based on the Load-Resistance model was performed. The evaluation of implicit functions of load and resistance was performed by the finite element method, and the Monte-Carlo approach was used for experiment simulation. The sampling method used was Latin Hypercube. Four random variables were considered including modulus of elasticity of brick and in filled materials and the specific mass of brick and infilled materials. The normal distribution was used to express the statistical properties of the random variables. The coefficient of variation was defined as 10%. Linear behavior was assumed for the bridge materials. Three output parameters of maximum bridge displacement, maximum tensile stress, and minimum compressive stress were assigned as structural limit states. A sensitivity analysis for probabilistic analysis was performed using the Spearman ranking method. The results showed that the sensitivity of output parameters to infilled density changes is high. The results also indicated that the system probability of failure is equal to rhofsystem=1,55x10-3. The bridge safety index value obtained is betat=2.96, which is lower than the recommended target safety index. The required safety parameters for the bridge have not been met and the bridge is at the risk of failure.

4

Reliability assessment and sensitivity analysis of concrete gravity dams by considering uncertainty in reservoir water levels and dam body materials

Pouraminian Majid, Pourbakhshian Somayyeh, Noroozinejad Farsangi Ehsan

Civil and Environmental Engineering Reports

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2020

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Vol. 30, no. 1

1--17

EN

An elaborate safety assessment of the Pine Flat (PF) concrete gravity dam (CGD) has been conducted in this paper. Structural analysis was performed by taking into account the uncertainties in the physical and mechanical properties of the dam body materials and the reservoir water level. The coefficient of variation of 5 and 10 percent and the Gaussian distribution (GAUS) are assigned to random variables (RVs). Sensitivity analysis (SA) of the RVs is done, and important parameters introduced. SA is done to identify the most influential RVs on the structural response. Also, the modulus of elasticity of concrete is the most effective parameter in response to horizontal deformation of the dam crest. The concrete density and US hydrostatic pressure height are the most effective parameters, and the Poisson's ratio is the insignificant parameter on the dam response. To be confident in the safety of the dam body under usual loading, including the dam weight and the upstream (US) hydrostatic pressure, the reliability index (RI) has been obtained by Monte Carlo simulation. The RI for the coefficients of variation of 5 and 10 percent were obtained at 4.38 and 2.47, respectively. If the dispersion of RVs is high, then the dam will be at risk of failure.

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Diagnosis strategy for complex systems based on reliability analysis and MA DM under epistemic uncertainty

Duan R., Zhou H., Fan J.

Eksploatacja i Niezawodność

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2015

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Vol. 17, no. 3

345--354

EN

Fault tolerant technology has greatly improved the reliability of train-ground wireless communication system (TWCS). However, its high reliability caused the lack of sufficient fault data and epistemic uncertainty, which increased significantly challenges in system diagnosis. A novel diagnosis method for TWCS is proposed to deal with these challenges in this paper, which makes the best of reliability analysis, fuzzy sets theory and MADM. Specifically, it adopts dynamic fault tree to model their dynamic fault modes and evaluates the failure rates of the basic events using fuzzy sets theory and expert elicitation to hand epistemic uncertainty. Furthermore, it calculates some quantitative parameters information provided by reliability analysis using algebraic technique and Bayesian network to overcome some disadvantages of the traditional methods. Diagnostic importance factor, sensitivity index and heuristic information values are considered comprehensively to obtain the optimal diagnostic ranking order of TWCS using an improved TOPSIS. The proposed method takes full advantages of the dynamic fault tree for modelling, fuzzy sets theory for handling uncertainty and MADM for the best fault search scheme, which is especially suitable for fault diagnosis of the complex systems.

PL

Technologia odporna na błędy przyczyniła się do dużej poprawy niezawodności systemów łączności bezprzewodowej pociąg-ziemia (TWCS). Jednakże wysoka niezawodność tych systemów pociąga za sobą brak wystarczających danych o uszkodzeniach oraz niepewność epistemologiczną, której zwiększenie stworzyło liczne wyzwania w zakresie diagnostyki systemów. W niniejszej pracy zaproponowano nowatorską metodę diagnozowania TWCS, która odpowiada na owe wyzwania wykorzystując analizę niezawodności, teorię zbiorów rozmytych oraz metody wieloatrybutowego podejmowania decyzji MADM. W szczególności, zaproponowana metoda wykorzystuje dynamiczne drzewa błędów do modelowania dynamicznych stanów niezdatności oraz pozwala na oszacowanie częstości występowania uszkodzeń dla zdarzeń podstawowych z wykorzystaniem teorii zbiorów rozmytych oraz oceny eksperckiej, rozwiązując w ten sposób problem niepewności epistemologicznej. Ponadto, metoda ta umożliwia obliczenie niektórych parametrów ilościowych na podstawie informacji pochodzących z analizy niezawodności, z zastosowaniem techniki algebraicznej oraz sieci bayesowskich, co pozwala na obejście ograniczeń tradycyjnie stosowanych metod. W artykule przeprowadzono szczegółową analizę czynnika ważności diagnostycznej, wskaźnika czułości oraz wartości informacji heurystycznej w celu określenia optymalnej kolejności działań diagnostycznych dla TWCS z zastosowaniem poprawionej wersji TOPSIS Proponowana metoda w pełni wykorzystuje zalety metody drzewa błędów do modelowania, teorii zbiorów rozmytych – do rozwiązywania problemu niepewności oraz MADM – do wyznaczania najlepszej metody wyszukiwania niezdatności, co jest szczególnie przydatne w przypadku diagnozowania niezdatności systemów złożonych.