L.E.O. Satellite Power Subsystem Reliability Analysis

M. Zahran,S. Tawfik,Gennady Dyakov 전력전자학회 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.2

Satellites have provided the impetus for the orderly development of reliability engineering research and analysis because they tend to have complex systems and hence acute problems. They were instrumental in developing mathematical models for reliability, as well as design techniques to permit quantitative specification, prediction and measurement of reliability. Reliability engineering is based on implementing measures which insure an item will perform its mission successfully. The discipline of reliability engineering consists of two fundamental aspects; (1<SUP>st</SUP>) paying attention to details, and (2<SUP>nd</SUP>) handling uncertainties. This paper uses some of the basic concepts, formulas and examples of reliability theory in application.<br/> This paper emphasizes the practical reliability analysis of a Low Earth Orbit (LEO) Micro-satellite power subsystem. Approaches for specifying and allocating the reliability of each element of the power system so as to meet the overall power system reliability requirements, as well as to give detailed modeling and predicting of equipment/system reliability are introduced. The results are handled and analyzed to form the final reliability results for the satellite power system. The results show that the Electric Power Subsystem (EPS) reliability meets the requirements with quad microcontrollers (MC), two boards working as main and cold redundant while each board contains two MCs in a hot redundant.

Reliability growth analysis of <i>k-out-of-N</i> systems using matrix-based system reliability method

Byun, Ji-Eun,Noh, Hee-Min,Song, Junho Elsevier 2017 Reliability engineering & system safety Vol.165 No.-

<P><B>Abstract</B></P> <P>The advent of ever more complex systems in extensive areas of industries hampers efficient and accurate analysis of reliability and effective reliability-based decision making. Such difficulties may arise from the intricate formulation of system failure events, statistical dependence between component failure events, and the convoluted quantification of underlying probabilities of basic events. So-called <I>k-out-of-N</I> systems, which survive or succeed when at least <I>k</I> components are available among the total of <I>N</I> components, give rise to a high level of complexity. This type of systems are commonly introduced to secure a proper level of redundancy in operating engineering systems, but the intricate definition of the system events may elude the system reliability analysis. It is noted that such <I>k-out-of-N</I> systems are often tested and corrected over a certain period of time before their official usage or release in order to assure the target reliability of the system. For the purpose of reliability prognosis based on the data collected from the test period, reliability growth models (RGMs) have been widely used in software and hardware engineering. However, RGMs have been applied mostly to individual components, not at the system level. Furthermore, in complex systems such as <I>k-out-of-N</I> system, it is challenging to relate the reliability growth of components with that of the system. To address this need, in this paper, the matrix-based system reliability (MSR) method is extended to <I>k-out-of-N</I> systems by modifying the formulations of event and probability vectors. The proposed methods can incorporate statistical dependence between component failures for both homogeneous and non-homogeneous <I>k-out-of-N</I> systems, and can compute measures related to parameter sensitivity and relative importance of components. The reliability growths of components represented by RGMs are incorporated into the proposed system reliability method, so that the trend of <I>system</I> reliability growth can be effortlessly evaluated and predicted. Two numerical examples are introduced in this paper to demonstrate the proposed method and its applications: (1) hypothetical systems each consisting of series, parallel and <I>k-out-of-N</I> subsystems, and (2) a simplified high speed train system modeled by multiple <I>k-out-of-N</I> subsystems. Two types of RGMs, i.e. non-homogeneous Poisson process (NHPP) and Duane models are employed in these examples.</P> <P><B>Highlights</B></P> <P> <UL> <LI> MSR method is extended to evaluate the reliability growth of <I>k-out-of-N</I> systems. </LI> <LI> The time-varying reliability of system can be evaluated from that of components. </LI> <LI> The extended MSR method can account for statistical dependence between components. </LI> <LI> By-products of reliability analysis can support systematic decision-making. </LI> <LI> Numerical examples show the MSR method is applicable to various configurations. </LI> </UL> </P>

Human Reliability Analysis of Soft Control Operations in Nuclear Power Plants: Issues and Perspectives

Seung Jun Lee,Wondea Jung 대한인간공학회 2013 大韓人間工學會誌 Vol.32 No.1

Objective: The aim of this study is to describe several issues which should be considered in the human reliability analysis of soft control operations in nuclear power plants. Background: The operational environment of advanced main control rooms is totally different from that of conventional control rooms. The soft control is one of the major distinguishable features of the advanced main control rooms. The soft control operations should be analyzed to estimate the effects on human reliability. Method: The literatures, about task analysis, simulation data analysis, and a human reliability analysis method for the soft control, were reviewed. From the review, important issues for the human reliability analysis of the soft control were raised. Results: The results of task and simulation data analysis showed that the soft control characteristics could have large effect on human reliability and they should be considered in the human reliability analysis of the soft control operations. Conclusion: The soft control may affect human error and performance of operators. The issues described in this paper should be considered in the human reliability method for the advanced main control rooms. Application: The results of the soft control operation analysis might help to design more efficient interface and education/training program for preventing human errors. The described issues might help to develop a human reliability analysis method for soft control operations.

Bayesian approach for reliability analysis of side load spring design problem

안다운(Dawn An),최주호(Jooho Choi),원준호(Junho Won) 대한기계학회 2008 대한기계학회 춘추학술대회 Vol.2008 No.5

Bayesian approach for the structural reliability analysis is proposed, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional reliability analysis mostly dealt with the aleatory uncertainty in which the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing methods less useful. In the Bayesian approach, the probability itself is a random variable conditioned by the observed data, and is represented by a PDF, which is obtained by conducting a double loop of reliability analyses. KDRM is employed for the efficient implementation of the reliability analysis, which can construct the PDF of the limit state function with favorable accuracy under a small number of analyses Mathematical examples are used to verify the proposed method. A reliability problem of a side load spring is solved as an example for practical application.

Reliability analysis of reinforced concrete haunched beams shear capacity based on stochastic nonlinear FE analysis

Hasan M. Albegmprli,AbdulkadirÇevik,M. ErenGülşan,AhmetEminKurtoglu 사단법인 한국계산역학회 2015 Computers and Concrete, An International Journal Vol.15 No.2

The lack of experimental studies on the mechanical behavior of reinforced concrete (RC) haunched beams leads to difficulties in statistical and reliability analyses. This study performs stochastic and reliability analyses of the ultimate shear capacity of RC haunched beams based on nonlinear finite element analysis. The main aim of this study is to investigate the influence of uncertainty in material properties and geometry parameters on the mechanical performance and shear capacity of RC haunched beams. Firstly, 65 experimentally tested RC haunched beams and prismatic beams are analyzed via deterministic nonlinear finite element method by a special program (ATENA) to verify the efficiency of utilized numerical models, the shear capacity and the crack pattern. The accuracy of nonlinear finite element analyses is verified by comparing the results of nonlinear finite element and experiments and both results are found to be in a good agreement. Afterwards, stochastic analyses are performed for each beam where the RC material properties and geometry parameters are assigned to take probabilistic values using an advanced simulating procedure. As a result of stochastic analysis, statistical parameters are determined. The statistical parameters are obtained for resistance bias factor and the coefficient of variation which were found to be equal to 1.053 and 0.137 respectively. Finally, reliability analyses are accomplished using the limit state functions of ACI-318 and ASCE-7 depending on the calculated statistical parameters. The results show that the RC haunched beams have higher sensitivity and riskiness than the RC prismatic beams.

L.E.O. Satellite Power Subsystem Reliability Analysis

Zahran M.,Tawfik S.,Dyakov Gennady The Korean Institute of Power Electronics 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.2

Satellites have provided the impetus for the orderly development of reliability engineering research and analysis because they tend to have complex systems and hence acute problems. They were instrumental in developing mathematical models for reliability, as well as design techniques to permit quantitative specification, prediction and measurement of reliability. Reliability engineering is based on implementing measures which insure an item will perform its mission successfully. The discipline of reliability engineering consists of two fundamental aspects; $(1^{st})$ paying attention to details, and $(2^{nd})$ handling uncertainties. This paper uses some of the basic concepts, formulas and examples of reliability theory in application. This paper emphasizes the practical reliability analysis of a Low Earth Orbit (LEO) Micro-satellite power subsystem. Approaches for specifying and allocating the reliability of each element of the power system so as to meet the overall power system reliability requirements, as well as to give detailed modeling and predicting of equipment/system reliability are introduced. The results are handled and analyzed to form the final reliability results for the satellite power system. The results show that the Electric Power Subsystem (EPS) reliability meets the requirements with quad microcontrollers (MC), two boards working as main and cold redundant while each board contains two MCs in a hot redundant.

Reliability analysis of laminated composite shells by response surface method based on HSDT

Sandipan N. Thakur,Subrata Chakraborty,Chaitali Ray 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.72 No.2

Reliability analysis of composite structures considering random variation of involved parameters is quite important as composite materials revealed large statistical variations in their mechanical properties. The reliability analysis of such structures by the first order reliability method (FORM) and Monte Carlo Simulation (MCS) based approach involves repetitive evaluations of performance function. The response surface method (RSM) based metamodeling technique has emerged as an effective solution to such problems. In the application of metamodeling for uncertainty quantification and reliability analysis of composite structures; the finite element model is usually formulated by either classical laminate theory or first order shear deformation theory. But such theories show significant error in calculating the structural responses of composite structures. The present study attempted to apply the RSM based MCS for reliability analysis of composite shell structures where the surrogate model is constructed using higher order shear deformation theory (HSDT) of composite structures considering the uncertainties in the material properties, load, ply thickness and radius of curvature of the shell structure. The sensitivity of responses of the shell is also obtained by RSM and finite element method based direct approach to elucidate the advantages of RSM for response sensitivity analysis. The reliability results obtained by the proposed RSM based MCS and FORM are compared with the accurate reliability analysis results obtained by the direct MCS by considering two numerical examples.

구조손상 및 확률변수 간의 공간적 상관관계를 고려한 트러스 구조물의 신뢰성 해석

조성록,이진학 한국방재학회 2019 한국방재학회논문집 Vol.19 No.2

본 연구에서는 트러스 교량을 대상으로 부재 제원 및 작용 하중에 포함되어 있는 불확실성, 구조손상 및 확률변수 간의 공간적 상관관계를 고려한 신뢰성 해석을 수행하였다. 한계상태로는 허용처짐을 기준으로 한 사용성 한계상태와 부재의 허용응력을 기준으로 한 응력한계상태를 고려하였으며, 신뢰성 해석을 위하여 모멘트 방법으로 알려져 있는 Level II 방법과 추출법 기반의 Level III 방법을 적용하였다. 이 연구에서는 이러한 신뢰성 해석 방법을 이용하여 (1) 부재에 존재하는 구조손상이 신뢰도 지수에 미치는 영향과 (2) 확률변수 간의 공간적 상관관계에 따른 신뢰성 해석 결과를 분석하였다. 신뢰성 해석 결과 한계상태에 따라 신뢰도 지수 및 파괴확률에 대한 구조손상의 영향이 손상부재에 따라 다름을 알 수 있었다. 또한 공간적 상관관계의 경우, 확률변수 간의 상관관계가 커질수록 파괴확률이 증가하는 것을 알 수 있었다. 따라서 확률론적 방법을 통한 신뢰성 해석을 할 때에는 한계상태 및 고려하는 확률변수의 분포 형태, 평균, 표준편차 외에도 구조손상 및 확률변수 간의 상관관계를 합리적으로 고려하여야 함을 알 수 있다. In this study, a reliability analysis is performed for a truss bridge considering uncertainties in structural properties and applied loads, structural damage, and spatial correlation between random variables. Two limit states are considered: a serviceability limit state based on allowable deflection and a stress limit state based on allowable stress. The Level II reliability analysis method, which is known as one of the moment methods, and the Level III method based on sampling techniques are used in the reliability analysis. In this study, the effects of structural damage and spatial correlation between random variables on the reliability index are intensively investigated. Results of the reliability analysis showed that structural damage has different effects on the reliability index and probability of failure in terms of the limit state and damaged member. With respect to spatial correlation, the probability of failure increases as the spatial correlation coefficient between random variables increases. Therefore, it can be concluded that structural damage and the spatial correlation between random variables should be reasonably considered to achieve a more rational reliability analysis.

베이지안 이론을 이용한 타입강관말뚝의 신뢰성 평가

박재현,김동욱,곽기석,정문경,김준영,정충기 한국지반공학회 2010 한국지반공학회논문집 Vol.26 No.7

For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was obrained based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability indices of driven steel pipe piles by adding more proof pile load test results, even not conducted to failure, to the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. The empirical method proposed by Meyerhof is used to calculate the predicted pile resistance. Reliability analyses were performed using the updated distribution of pile resistance ratio. The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian updates are most effective when limited data are available for reliability analysis.

Reliability Improvement of Machine Tool changing Servo Motor

Sung, Baek-Ju,Lee, Jong-Bae The Korean Institute of Electrical Engineers 2011 The Journal of International Council on Electrical Vol.1 No.1

First of all, it is the most important to know the cause and effect of major failures to increase the reliability of servo motor. All reliability parameters can be achieved after analysis of them and experiments based on the analysis data. So, we firstly made out the failure analysis data of servo motor such as FMMA, FMECA, FTA, and 2-stage QFD considering the reference materials, field failure data, and the opinion of experts of servo motor. And the test items were decided which are needed to evaluate the performance characteristics of servo motor as analysis results of failure analysis data. And then, the major reliability parameters are deduced by experiments and MINITAB analysis. In addition, according to prove a major failure mode of servo motor by above analysis results, we produced FEA (Finite Element Analysis) model about shape of stator and rotor of servo motor to find out the reducing method of cogging torque. This paper presents the useful major reliability parameters, detailed failure mode analysis data, experimental results using 3 samples, and a cogging torque reducing method of servo motor, and also verified the validity of the deduced parameters and analysis data.