Influence of Multi-component Failure on Mechanical Product Design Change

Design change is one of the most common activities in design and development of mechanical products, and the change will affected by the design and maintenance of the products. It is not uncommon that multiple components might run out of order simultaneously during the use of a product, which would have significant influences on the product performance. Such kind of multi-component failure must be considered early in the product design stage, therefore it is necessary to study multiple design changes incurred by multi-component failure. Existing studies on the design change only focus on single change and ignore multiple simultaneous changes. To address this problem, a change influence network model is establishes, and the propagation path of multiple changes on the change influence network is described according to the change propagation characteristics of mechanical products. By analyzing the degree of dependence between the nodes and the absorption situations of nodes to change propagation, the possible paths of change propagation on the change influence network are determined, and based on which, calculation of the change influence is carried out, which provides decision-making support for product designers. Finally, the feasibility of the proposed methodology is demonstrated by taking a household juicer for case study.

A Solute Pinning Approach to Solute Drag in Multi-Component Solid Solution Alloys

The Cahn, Lücke and Stüwe theory remains the backbone of more complex analysis dealing with solute drag, however, the mathematical treatment is rather involved. A new approach based on solute pinning the boundary has therefore recently been suggested, which has the main advantage of a simpler mathematical treatment. In the present paper this approach has been generalized to take into account the influence of different types of solute atoms in the high solute content/low driving force regime.

Statistical Inference of Stress-Strength Model for Exponentiated Pareto Model with Censored Data

The reliability of a system is discussed when the strength of the system and the stress imposed on it are independent and non-identical exponentiated Pareto distributed random variables with progressively censored scheme.Different interval estimations are proposed.The interval estimations obtained are exact,approximate and bootstrap confidence intervals.Different methods and the corresponding confidence intervals are compared using Monte-Carlo simulations.Simulation results show that the confidence intervals(CIs)of exact and approximate methods are really better than those of the bootstrap method.

Improved Discrete Interval-Valued Stress-Strength Interference Model Based on Extended Universal Generating Function

In practical engineering,sometimes the probability density functions( PDFs) of stress and strength can not be exactly determined,or only limited experiment data are available. In these cases,the traditional stress-strength interference( SSI) model based on classical probabilistic approach can not be used to evaluate reliabilities of components. To solve this issue, the traditional universal generating function( UGF) is introduced and then it is extended to represent the discrete interval-valued random variable.Based on the extended UGF,an improved discrete interval-valued SSI model is proposed, which has higher calculation precision compared with the existing methods. Finally,an illustrative case is given to demonstrate the validity of the proposed model.

Reliability Bounds based on Universal Generating Function and Discrete Stress-strength Interference Model

A method for estimating the component reliability is proposed when the probability density functions of stress and strength can not be exactly determined. For two groups of finite experimental data about the stress and strength, an interval statistics method is introduced. The processed results are formulated as two interval-valued random variables and are graphically represented component reliability are proposed based on the by using two histograms. The lower and upper bounds of universal generating function method and are calculated by solving two discrete stress-strength interference models. The graphical calculations of the proposed reliability bounds are presented through a numerical example and the confidence of the proposed reliability bounds is discussed to demonstrate the validity of the proposed method. It is showed that the proposed reliability bounds can undoubtedly bracket the real reliability value. The proposed method extends the exciting universal generating function method and can give an interval estimation of component reliability in the case of lake of sufficient experimental data. An application example is given to illustrate the proposed method

Reliability of a Multicomponent Stress-strength Model Based on a Bivariate Kumaraswamy Distribution with Censored Data

In this paper,we consider a system which has k statistically independent and identically distributed strength components and each component is constructed by a pair of statistically dependent elements with doubly type-II censored scheme.These elements(X1,Y1),(X2,Y2),…,(Xk,Yk)follow a bivariate Kumaraswamy distribution and each element is exposed to a common random stress T which follows a Kumaraswamy distribution.The system is regarded as operating only if at least s out of k(1≤s≤k)strength variables exceed the random stress.The multicomponent reliability of the system is given by Rs,k=P(at least s of the(Z1,…,Zk)exceed T)where Zi=min(Xi,Yi),i=1,…,k.The Bayes estimates of Rs,k have been developed by using the Markov Chain Monte Carlo methods due to the lack of explicit forms.The uniformly minimum variance unbiased and exact Bayes estimates of Rs,k are obtained analytically when the common second shape parameter is known.The asymptotic confidence interval and the highest probability density credible interval are constructed for Rs,k.The reliability estimators are compared by using the estimated risks through Monte Carlo simulations.

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis,the stress-strength model is often used to describe the life of a component which has a random strength(X)and is subjected to a random stress(Y).In this paper,we considered the problem of estimating the reliability𝑅𝑅=P[Y<X]when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution.The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample,ranked set sampling and median ranked set sampling methods.Four different reliability estimators under median ranked set sampling are derived.Two estimators are obtained when both strength and stress have an odd or an even set size.The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa.The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study.The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample.In general,the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.Keywords:Stress-Strength model,ranked set sampling,median ranked set sampling,maximum likelihood estimation,mean square error.corresponding estimates under ranked set sampling and simple random sample methods.

Multi-wave forward modeling of a reservoir and AVO analysis

In the process of accurate interpretation of multi-wave seismic data,we wanted to solve the problem of multi-wave information recognition.Based on techniques of elastic wave forwarding,targeting the geological model of a reservoir of an oil field exploration area,we used a high-order staggered-grid difference technology to simulate many shots of seismic records of nonzero offset shots,implemented multi-wave seismic data processing to acquire the CMP of P waves and converted waves,NMO traces of CCP pre stacks,including AVA information and superposition profiles.Based on the AVA calculation of the model,the layer parameters of the model and the forwarding wave field relations of the P-S wave,we also compared and studied the correspondence between P waves and converted waves.The results of our analysis show that the results from simulation and from the AVO analysis are consistent.Significant wave field differences between P waves and converted waves in the same reservoir were found,which are helpful in recognizing and interpreting the multi-wave information in this area.We made use of the multi-wave data to provide the important guidelines for reservoir prediction.

FATIGUE RELIABILITY CALCULATION MODEL FOR COMPONENT UNDER RANDOM LOADING

in reliability design of fatigue under random loading, the influence of loading se-quence must be considered. In order to avoid the uneertain hypothesis in the Miner's rule, ie. thatthe sum of damage equals one represents failure, this paper proposes the probabilistic relativeMine's rule. This paper also presents a new method for calculating reliability, ie. the syntheticmethod of Miner's rule and interference model. This model considers not only the influence ofstress concentration, dimension and surface, but also the influence of stress amplitude and se-quence.

Phase-Field Models for Multi-Component Fluid Flows

In this paper,we review the recent development of phase-field models and their numerical methods for multi-component fluid flows with interfacial phenomena.The models consist of a Navier-Stokes system coupled with a multi-component Cahn-Hilliard system through a phase-field dependent surface tension force,variable density and viscosity,and the advection term.The classical infinitely thin boundary of separation between two immiscible fluids is replaced by a transition region of a small but finite width,across which the composition of the mixture changes continuously.A constant level set of the phase-field is used to capture the interface between two immiscible fluids.Phase-field methods are capable of computing topological changes such as splitting andmerging,and thus have been applied successfully to multi-component fluid flows involving large interface deformations.Practical applications are provided to illustrate the usefulness of using a phase-field method.Computational results of various experiments show the accuracy and effectiveness of phase-field models.

A STOICHIOMETRIC DISPLACEMENT MODEL FOR RETENTION OF SOLUTE IN LIQUID CHROMATOGRAPHY WITH MULTI-COMPONENT SYSTEM

Considering all the kinds of interactions between solute and solvent, solute and stationary phase, solvent and stationary phase molecules as well as the competitional adsorption among various kinds of solvent molecules on the stationary phase, we present a stoichiometric displacement model of solute retention with four sets of parameters in liquid chromatography. This model was tested with data from both literature and experiments done by ourselves. These results show that this model may fit the experimental data for a liquid chromatography system with various kinds of mobile phases consisting of a complete range of multi-components and with different types of stationary phases.

Applicable models for multi-component adsorption of dyes:A review

Adsorption is one of the several techniques that has been successfully used for dyes removal.Since most industrial colored effluents contain several components including dyes,having a strong knowledge about the scope of competitive adsorption process is a powerful key to design an appropriate system.This is mainly because of the complexity brought about by the increasing number of parameters needed for process description which complicates not only the process modeling but also the experimental data collection.A multicomponent adsorption model should be based on fundamental soundness,speed,and simplicity of calculation.For such systems,competition will change the adsorbent-adsorbate attractions.Thus,there is major concern to develop an accurate and reliable method to predict dye adsorption behavior in multi-component systems.This article covers topics such as the theory of dyes adsorption in multi-component systems along with applicable models according to the consistent theories presented by researchers.

Improved multi-order parameter and multi-component model of polycrystalline solidification

In this paper, we present an improved multi-order parameter model for multi-component model of polycrystalline solidification. We introduce an interpolation function in the phase field dynamical equation to obtain controllable grain boundary energy at large undercooling. The same interpolation function is also employed in the kinetics coefficient to allow for better control of grain boundary migration. Temperature dependent phase field parameters and noise terms are consistently coupled into the dynamics of a binary system in a manner that allows for quantitative simulations in the thin interface limit. The model is applied to multi-phase solidification in Al-Cu alloy, where a parabolic fitting method is employed to model the free energy of Al-Cu phases and two-phase nucleation is demonstrated in directional solidification.

A blind separation method of overlapped multi-components based on time varying AR model

A method utilizing single channel recordings to blindly separate the multicomponents overlapped in time and frequency domains is proposed in this paper. Based on the time varying AR model, the instantaneous frequency and amplitude of each signal component are estimated respectively, thus the signal component separation is achieved. By using prolate spheroidal sequence as basis functions to expand the time varying parameters of the AR model, the method turns the problem of linear time varying parameters estimation to a linear time invariant parameter estimation problem, then the parameters are estimated by a recursive algorithm. The computation of this method is simple, and no prior knowledge of the signals is needed. Simulation results demonstrate validity and excellent performance of this method.

Multi-Component Model of Diesel Sprays Under High Injection Pressure

The combustion efficiency of a diesel engine depends not only on spray characteristics but also on fuel-air mixing characteristics. Based on the original spray model, a new spray model is established in this paper to accurately predict the diesel spray, and then a multi-component evaporation model is added into it. The model takes the influence of component concentration gradient and species on its evaporation rate in the liquid phase into account. This paper studies the spray characteristics(spray penetration, spray angle and spray morphology) and fuel-air mixing characteristics(spray area, spray volume and air entrainment mass) using the spray model, and the results are compared with the experimental results. The comparison shows that the simulated spray penetration and spray angle are close to the experimental results with the average deviations less than 3%. Moreover, this paper studies the spray area, spray volume and air entrainment using empirical formula under different conditions. And the maximum deviations of the spray volume, spray area and air entrainment mass are less than 5% as compared with the test values. Overall, this spray model can predict the diesel spray characteristics and fuel-air mixing characteristics under high injection pressure accurately.

Reliability Analysis of Systems with Common Cause Failure Based on Stress-Strength Interference Model

Many mechanical systems have the characteristics of multiple failure modes and complex failure mech- anisms. On the basis of stress-strength interference （SSI） model, this paper takes the mechanical system with common cause failure （CCF） as the research object. The relationship between the stress distribution and the strength distribution is studied, and the failures of components are independent of each other under the determin- istic stress. Then, the concept of conditional reliability is introduced to build the system reliability models under the action of one-stress and multi-stress for both series and parallel systems. Finally, the corresponding properties of the DrODosed methods are discussed to show their advantages.

Nonparametric Inference for the Stress-Strength Model under Right Censoring

The stress-strength model is widely applied in reliability. Observations are often subject to right censoring due to some practical limitations. In such circumstances, the statistical inference for the stress-strength model is demanding, although lacking. We propose a nonparametric method for the inference of the stress-strength model when the observations are subject to right censoring. The asymptotic properties are also established. The practical utility of the proposed method is assessed through both simulated and real data sets.

Wind Turbine Gearbox Reliability Analysis Based on the System Level Stress-Strength Model

In order to estimate the reliability of wind turbine gearbox based on the system level, a generalized stress-strength model is introduced. Considering that the system works properly under a variety of random stresses which affect every component, the total stress on the system is given by a known linear combination of the stresses of all components. Then the strength of the system can be viewed as a linear combination of the strengths of relative components. In this model, stress and strength are independent of each other. Reliability of the system is the probability that strength exceeds stress. Finally, the reliability of wind turbine gearbox is estimated by the multivariable reliability calculation method. The corresponding result is compared with the results of reliability in the extreme cases(completely dependent and completely independent) by the traditional evaluation method.

Expansion of Lie Algebra and Its Application

Firstly we expand a finite-dimensional Lie algebra into a higher-dimenslonal one. By making use of the later and its corresponding loop algebra, the expanding integrable model of the multi-component NLS-mKdV hierarchy is worked out.