This page has only limited features, please log in for full access.
This paper presents recent contributions to the Marie Skłodowska-Curie Innovative Training Network titled INFRASTAR (Innovation and Networking for Fatigue and Reliability Analysis of Structures-Training for Assessment of Risk) in the field of reliability approaches for decision-making for wind turbines and bridges . Stochastic modeling of uncertainties for fatigue strength parameters is an important step as a basis for reliability analyses. In this paper, the Maximum Likelihood Method (MLM) is used for fitting the statistical parameters in a regression model for the fatigue strength of reinforcement bars. Furthermore, application of the Bootstrapping method is investigated. The results indicate that the latter methodology does not work well in the considered case study because of run-out tests within the test data. Moreover, the use of the Bayesian inference with the Markov Chain Monto Carlo approach is studied. These results indicate that a reduction in the statistical uncertainty can be obtained, and thus, better parameter estimates are obtained. The results are used for stochastic modelling in reliability assessment of a case study with a composite bridge. The reduction in statistical uncertainty shows high impact on the fatigue reliability in a case study on the Swiss viaduct Crêt De l’Anneau.
Sima Rastayesh; Amol Mankar; John Dalsgaard Sørensen; Sajjad Bahrebar. Development of Stochastic Fatigue Model of Reinforcement for Reliability of Concrete Structures. Applied Sciences 2020, 10, 604 .
AMA StyleSima Rastayesh, Amol Mankar, John Dalsgaard Sørensen, Sajjad Bahrebar. Development of Stochastic Fatigue Model of Reinforcement for Reliability of Concrete Structures. Applied Sciences. 2020; 10 (2):604.
Chicago/Turabian StyleSima Rastayesh; Amol Mankar; John Dalsgaard Sørensen; Sajjad Bahrebar. 2020. "Development of Stochastic Fatigue Model of Reinforcement for Reliability of Concrete Structures." Applied Sciences 10, no. 2: 604.
This paper uses a system engineering approach based on the Failure Mode and Effect Analysis (FMEA) methodology to do risk analysis of the power conditioner of a Proton Exchange Membrane Fuel Cell (PEMFC). Critical components with high risk, common cause failures and effects are identified for the power conditioner system as one of the crucial parts of the PEMFCs used for backup power applications in the telecommunication industry. The results of this paper indicate that the highest risk corresponds to three failure modes including high leakage current due to the substrate interface of the metal oxide semiconductor field effect transistor (MOSFET), current and electrolytic evaporation of capacitor, and thereby short circuit, loss of gate control, and increased leakage current due to gate oxide of the MOSFET. The MOSFETs, capacitors, chokes, and transformers are critical components of the power stage, which should be carefully considered in the development of the design production and implementation stage. Finally, Bayesian networks (BNs) are used to identify the most critical failure causes in the MOSFET and capacitor as they are classified from the FMEA as key items based on their Risk Priority Numbers (RPNs). As a result of BNs analyses, high temperature and overvoltage are distinguished as the most crucial failure causes. Consequently, it is recommended for designers to pay more attention to the design of MOSFETs’ failure due to high leakage current owing to substrate interface, which is caused by high temperature. The results are emphasizing design improvement in the material in order to be more resistant from high temperature.
Sima Rastayesh; Sajjad Bahrebar; Frede Blaabjerg; Dao Zhou; Huai Wang; John Dalsgaard Sørensen. A System Engineering Approach Using FMEA and Bayesian Network for Risk Analysis—A Case Study. Sustainability 2019, 12, 77 .
AMA StyleSima Rastayesh, Sajjad Bahrebar, Frede Blaabjerg, Dao Zhou, Huai Wang, John Dalsgaard Sørensen. A System Engineering Approach Using FMEA and Bayesian Network for Risk Analysis—A Case Study. Sustainability. 2019; 12 (1):77.
Chicago/Turabian StyleSima Rastayesh; Sajjad Bahrebar; Frede Blaabjerg; Dao Zhou; Huai Wang; John Dalsgaard Sørensen. 2019. "A System Engineering Approach Using FMEA and Bayesian Network for Risk Analysis—A Case Study." Sustainability 12, no. 1: 77.
This paper presents a methodology based on the failure mode and effect analysis (FMEA) to analyze the failures in the power stage of wind-fuel cell hybrid energy systems. Besides, fault tree analysis (FTA) is applied to describe the probabilistic failures in the vital subcomponents. Finally, the reliability assessment of the system is carried out for a five-year operation that is guaranteed by the manufacturer. So, as the result, the reliability analysis proves that the metal oxide semiconductor field effect transistor (MOSFET) and electrolytic capacitor are the most critical components that introduce damages in the power circuit. Moreover, a comparative study on the reliability assessment by the exponential distribution and the Weibull distribution show that the B1 lifetime obtained by the Weibull distribution is closer to reality.
Sima Rastayesh; Sajjad Bahrebar; Amir Sajjad Bahman; John Dalsgaard Sørensen; Frede Blaabjerg. Lifetime Estimation and Failure Risk Analysis in a Power Stage Used in Wind-Fuel Cell Hybrid Energy Systems. Electronics 2019, 8, 1412 .
AMA StyleSima Rastayesh, Sajjad Bahrebar, Amir Sajjad Bahman, John Dalsgaard Sørensen, Frede Blaabjerg. Lifetime Estimation and Failure Risk Analysis in a Power Stage Used in Wind-Fuel Cell Hybrid Energy Systems. Electronics. 2019; 8 (12):1412.
Chicago/Turabian StyleSima Rastayesh; Sajjad Bahrebar; Amir Sajjad Bahman; John Dalsgaard Sørensen; Frede Blaabjerg. 2019. "Lifetime Estimation and Failure Risk Analysis in a Power Stage Used in Wind-Fuel Cell Hybrid Energy Systems." Electronics 8, no. 12: 1412.
Proton exchange membrane fuel cell recently emerges in the telecom backup power, where its reliability and availability issues are with high priority. In this paper, as one of the fragile sub-systems, the reliable performance of the power conditioner, including the power stage, the controller, the gate driver, the auxiliary the power supply and the printed circuit board, is the key focus. According to the configuration and main functions of the aforementioned key components, the fault tree structure of power conditioner can be established. With the help of the Weibull distribution, the random failure mode and wear-out failure mode impacts on the reliability can be estimated. Moreover, the reliability and availability curves can be studied by considering the maintenance scheme. In this case study, it can be seen that the wear-out issue is more worthy to be taken care compared to the random failure. Moreover, the regular maintenance with the key components significantly increases the reliability and availability performance of the power conditioner.
Sajjad Bahrebar; D. Zhou; S. Rastayesh; H. Wang; F. Blaabjerg. Reliability assessment of power conditioner considering maintenance in a PEM fuel cell system. Microelectronics Reliability 2018, 88-90, 1177 -1182.
AMA StyleSajjad Bahrebar, D. Zhou, S. Rastayesh, H. Wang, F. Blaabjerg. Reliability assessment of power conditioner considering maintenance in a PEM fuel cell system. Microelectronics Reliability. 2018; 88-90 ():1177-1182.
Chicago/Turabian StyleSajjad Bahrebar; D. Zhou; S. Rastayesh; H. Wang; F. Blaabjerg. 2018. "Reliability assessment of power conditioner considering maintenance in a PEM fuel cell system." Microelectronics Reliability 88-90, no. : 1177-1182.
A marine energy system, which is fundamentally not paired with electric grids, should work for an extended period with high reliability. To put it in another way, by employing electrical utilities on a ship, the electrical power demand has been increasing in recent years. Besides, fuel cells in marine power generation may reduce the loss of energy and weight in long cables and provide a platform such that each piece of marine equipment is supplied with its own isolated wire connection. Hence, fuel cells can be promising power generation equipment in the marine industry. Besides, failure modes and effects analysis (FMEA) is widely accepted throughout the industry as a valuable tool for identifying, ranking, and mitigating risks. The FMEA process can help to design safe hydrogen fueling stations. In this paper, a robust FMEA has been developed to identify the potentially hazardous conditions of the marine propulsion system by considering a general type-2 fuzzy logic set. The general type-2 fuzzy system is decomposed of several interval type-2 fuzzy logic systems to reduce the inherent highly computational burden of the general type-2 fuzzy systems. Linguistic rules are directly incorporated into the fuzzy system. Finally, the results demonstrate the success and effectiveness of the proposed approach in computing the risk priority number as compared to state-of-the-art methods.
Sajjad Bahrebar; Frede Blaabjerg; Huai Wang; Navid Vafamand; Mohammad-Hassan Khooban; Sima Rastayesh; Dao Zhou. A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application. Energies 2018, 11, 721 .
AMA StyleSajjad Bahrebar, Frede Blaabjerg, Huai Wang, Navid Vafamand, Mohammad-Hassan Khooban, Sima Rastayesh, Dao Zhou. A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application. Energies. 2018; 11 (4):721.
Chicago/Turabian StyleSajjad Bahrebar; Frede Blaabjerg; Huai Wang; Navid Vafamand; Mohammad-Hassan Khooban; Sima Rastayesh; Dao Zhou. 2018. "A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application." Energies 11, no. 4: 721.