Solving reliability analysis problems in the polar space

Ezzati, Ghasem; Mammadov, Musa; Kulkarni, Siddhivinayak

doi:10.14419/ijamr.v3i4.3302

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…The above-mentioned limit-state functions can be used to set up a first-order (direct) reliability analysis problem to evaluate system reliability. This problem is generally modeled as below (Ezzati et al, 2014):…”

Section: Limit-state Function Of Wind Turbinesmentioning

confidence: 99%

Introducing a new system performance function to formulate reliability analysis problems of wind turbines

Artin

2023

Wind Engineering

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Consideration of safety is one of the current requirements to design a new system that is often implemented by defining the system failure probability. Renewable energy systems (RESs) do have the same requirements when it comes to safety and reliability. When designing a wind turbine, as a RES, its reliability is of the highest importance. So, efficient reliability models are required to ensure the turbine is working safely to generate electricity. A new model is introduced in this paper by taking into account the wind speed and the wind angle as two effective factors. These two random variables are reported to follow the Gaussian and Weibull probability distributions, and so are employed to define a limit-state function for the turbines. This limit-state function, which is also called system performance function, will then be used to find out the system failure probability.

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Section: Limit-state Function Of Wind Turbinesmentioning

confidence: 99%

Introducing a new system performance function to formulate reliability analysis problems of wind turbines

Artin

2023

Wind Engineering

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“…Statistical and reliability analysis methods are also applied in system performance evaluation in a wide range of industries including mechanical, civil and electrical engineering [7,8,13,18]. For this purpose, different distribution functions, such as normal, lognormal, Weibull, exponential and linear-exponential distribution functions, have been considered in the literature to improve system reliability [10,12,16,17].…”

Section: Introductionmentioning

confidence: 99%

Evaluating system reliability using linear-exponential distribution function

Ezzati¹,

Rasouli²

2014

IJASP

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Safety is a main criterion to design every system. Among various theories, which are applied to improve system safety, reliability theory is known as a powerful tool to reach higher safety levels in system design. In this paper, a compound of series and parallel systems is considered for reliability improvement. This system includes three items that two items are connected in parallel and their compound item is connected to the third item in series. It's assumed that the items are independent and their longevity follows linear-exponential distribution function. Reliability function of the mentioned system is formulated using linear-exponential distribution function. Then, three improvement methods will be applied to enhance system reliability. In each method, different sets of items will be considered for improvement and their reliability functions will be reformulated. A data analysis will be done in order to compare different improvement methods and a conclusion will be made based on the analyzed data.

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“…As a local optimisation algorithm, the conjugate gradient method will be adopted (see [4]). Furthermore, a new method will be introduced to solve a reliability analysis problem in the polar space (see [3]). The reliability analysis problem must be transformed into an unconstrained optimisation problem before solving in the polar space.…”

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confidence: 99%

Reliability-Based Design Optimisation Methods in Large-Scale Systems

Ezzati¹

2016

Bull. Aust. Math. Soc.

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Structural optimisation is an important field of applied mathematics, which has proved useful in engineering projects. Reliability-based design optimisation (RBDO) can be considered a branch of structural optimisation. Different RBDO approaches have been applied in real-world problems (for example, vehicle side impact models, shortcolumn design and so on).Double-loop, single-loop and decoupled approaches are three categories in RBDO. This research focuses on double-loop approaches, which consider reliability analysis problems in their inner loops and design optimisation calculations in their outer loops. Double-loop approaches have been studied and modified in order to improve their stability and efficiency, but many shortcomings still remain, particularly regarding reliability analysis methods. This thesis will concentrate on development of new reliability analysis methods that can be applied to solve RBDO problems. As a local optimisation algorithm, the conjugate gradient method will be adopted (see [4]). Furthermore, a new method will be introduced to solve a reliability analysis problem in the polar space (see [3]). The reliability analysis problem must be transformed into an unconstrained optimisation problem before solving in the polar space. Two methods will be introduced here and their stability and efficiency will be compared with the existing methods via numerical experiments. Further developments are presented in [5,6].Next, we consider applications of RBDO models to electricity networks (see [1,2]). Most of the current optimisation models of these networks are categorised as deterministic design optimisation models. A probabilistic constraint is introduced in this thesis for electricity networks. For this purpose, a performance function must be defined for a network in order to define safety and failure conditions.

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Solving reliability analysis problems in the polar space

Cited by 3 publications

References 22 publications

Introducing a new system performance function to formulate reliability analysis problems of wind turbines

Introducing a new system performance function to formulate reliability analysis problems of wind turbines

Evaluating system reliability using linear-exponential distribution function

Reliability-Based Design Optimisation Methods in Large-Scale Systems

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