Active learning accelerated Monte-Carlo simulation based on the modified K-nearest neighbors algorithm and its application to reliability estimations

This paper proposes an active learning accelerated Monte-Carlo simulation method based on the modified K-nearest neighbors algorithm.The core idea of the proposed method is to judge whether or not the output of a random input point can be postulated through a classifier implemented through the modified K-nearest neighbors algorithm.Compared to other active learning methods resorting to experimental designs,the proposed method is characterized by employing Monte-Carlo simulation for sampling inputs and saving a large portion of the actual evaluations of outputs through an accurate classification,which is applicable for most structural reliability estimation problems.Moreover,the validity,efficiency,and accuracy of the proposed method are demonstrated numerically.In addition,the optimal value of K that maximizes the computational efficiency is studied.Finally,the proposed method is applied to the reliability estimation of the carbon fiber reinforced silicon carbide composite specimens subjected to random displacements,which further validates its practicability.

QUICK ASSESSMENT METHODOLOGY FOR RELIABILITY OF SOLDER JOINTS IN BALL GRID ARRAY(BGA)ASSEMBLY——PART Ⅱ:RELIABILITY EXPERIMENT AND NUMERICAL SIMULATION

In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found that the MDS not only quickly assesses the long-term reliability of solder joints within days,but can also mimic similar failure mechanisms in accelerated thermal cycling (ATC) tests. Based on the MDS and ATC reliability experiments,the acceleration factors (AF) were obtained for different reliability testing conditions.Furthermore,by using the creep constitutive relation and fatigue life model developed in part I,a numerical approach was established for the purpose of virtual life prediction of solder joints. The simulation results were found to be in good agreement with the test results from the MDS.As a result,a new reliability assessment methodology was established as an alternative to ATC for the evaluation of long-term reliability of plastic BGA assembly.

Assessment of Multiple Working Condition System Reliability with Agent-Based Simulation Method

The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the characters of system reliability under the complex mission profile.In order to solve the problem,an agentbased simulation method was used to assess reliability for complex systems with various random working conditions.A multi-working condition simulation agent(MA)was designed and used to simulate the random transferring process of working conditions of system,and it cooperated with system simulation agents(SAs)and unit simulation agents(UAs)to realize system mission reliability(MR)simulation.Through simulation experiments,effect of multiple working conditions mission on the reliability of system was analyzed by comparing with the basic reliability condition.Feasibility and efficiency of the method were proved through simulation experiments of the case system.The research result provides a viable and useful method and a solution for MR analysis and assessment of complex systems in multi-working conditions,which can help to evaluate the reliability of operating system orienting to the practical mission and environment,and it is meaningful for the reliability analysis and the design of complex systems.

Perturbation Methods of Stability Analysis for Parallel Real-Time Digital Simulation Models

In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For two classes of systems of test equations, we construct the parallel simulation models and prove that they have the stability behaviour which is similar to the original continuous systems.

Digital simulation studies on long transmission line protection based on balance of energy

The protection based balance of energy is a new technique specially proposed for long transmission lines. This technique depends upon the calculation of net energy into the transmission line by two independent methods and comparing them to indicate healthy and faulty conditions. In order to study the performance and feasibility of the protection based on balance of energy, the new protection has been extensively tested by using EMTP on a long transmission line with various configurations and operating conditions (including single pole line, double circuit lines and two phase operation). The results calculated by EMTP show that under any condition of a power system, the proposed technique has excellent performance,the viability even for high resistance ground faults and a short operation time.

A DIGITAL SIMULATION TECHNIQUE FOR DRYDEN ATMOSPHERIC TURBULENCE MODEL

Dryden model is usually used in studying the response of flight vehicle to atmospheric turbulence.For a modern flight simulator,it is necessary to generate random winds ( in Dryden model or sometimesothers) with a digital computer.In this paper,a theoretically strict new method to meet this purpose isproposed.By this method,we can acquire a three-dimensional atmospheric turbulence which containsthree components of wind velocity and three components of wind velocity gradient.The reliability of thismethod is checked by comparing the obtained autocorrelation value with the theoretical one.A numericalexample has shown a satisfactory result.Finally,some proposals about how to use this mathematicalmodel in flight simulator are given.

Dynamic Reliability Assessment of Heavy Vehicle Crossing a Prototype Bridge Deck by Using Simulation Technology and Health Monitoring Data

Overloads of vehicle may cause damage to bridge structures,and how to assess the safety influence of heavy vehicles crossing the prototype bridge is one of the challenges.In this report,using a large amount of monitored data collected from the structural health monitoring system(SHMS)in service of the prototype bridge,of which the bridge type is large-span continuous rigid frame bridge,and adopting FEM simulation technique,we suggested a dynamic reliability assessment method in the report to assess the safety impact of heavy vehicles on the prototype bridge during operation.In the first place,by using the health monitored strain data,of which the selected monitored data time range is before the opening of traffic,the quasi dynamic reliability around the embedded sensor with no traffic load effects is obtained;then,with FEM technology,the FEM simulation model of one main span of the prototype bridge is built by using ANSYS software and then the dynamic reliability when the heavy vehicles crossing the prototype bridge corresponding to the middle-span web plate is comprehensively analyzed and discussed.At last,assuming that the main beam stress state change is in the stage of approximately linear elasticity under heavy vehicle loads impact,the authors got the impact level of heavy vehicles effects on the dynamic reliability of the prototype bridge.Based on a large number of field measured data,the dynamic reliability value calculated by our proposed methodology is more accurate.The method suggested in the paper can do good for not only the traffic management but also the damage analysis of bridges.

Simulation Evaluation Study of System Reliability Based on Improved BayesBootstrap Method

For the disadvantages of analyzing system reliability using common Bayes method,an evaluation method based on improved Bayes-Bootstrap method is presented.Firstly,the data obliteration problem existing in traditional Bayes method is analyzed,then an improved sampling arithmetic is proposed on the foundation of an experience function.Finally,effectiveness of this method is proved by an example.The simulating result shows that this method is more accurate than common Bayes method.

Slope reliability analysis based on Monte Carlo simulation and sparse grid method

In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.

Sensitivity of Sample for Simulation-Based Reliability Analysis Methods

In structural reliability analysis,simulation methods are widely used.The statistical characteristics of failure probability estimate of these methods have been well investigated.In this study,the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample,called‘contribution indexes’,are proposed to measure the contribution of sample.The contribution indexes in four widely simulation methods,i.e.,Monte Carlo simulation(MCS),importance sampling(IS),line sampling(LS)and subset simulation(SS)are derived and analyzed.The proposed contribution indexes of sample can provide valuable information understanding the methods deeply,and enlighten potential improvement of methods.It is found that the main differences between these investigated methods lie in the contribution indexes of the safety samples,which are the main factors to the efficiency of the methods.Moreover,numerical examples are used to validate these findings.

Simulation Assessment of Reliability for k/N Redundancy System Considering Failure Correlativity of Components

The reliability assessment model of k /N system is built based on Copula function theory considering the failure correlativity existing among components,and then a simulation strategy is presented on the foundation of agent technique.The components and equipment entity model are designed according to the modeling technique above to describe the operation relationship during the mission phase,and then the simulation system for the assessment of product reliability is completed.And at last,an example is given with different material support programs.The research result has shown that the relevance existing in components has effect on the confirmation and optimization of maintenance strategy.

Matlab Code to Assess the Reliability of the Smart Power Distribution System Using Monte Carlo Simulation

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. In this work, we develop a MATLAB code to examine the effect of the smart grid applications in improving the reliability of the power distribution networks via Monte Carlo Simulation approach. The system used in this paper is the IEEE 34 test feeder. The objective is to measure the installations of the Automatic Reclosers (ARs) as well as the Distributed Generators (DGs) on the reliability indices, SAIDI, SAIFI, CAIDI and EUE, and make comparisons with results from a previous study done by the authors using another approach. The MATLAB code should provide close results to the output of the previous research to verify its effectiveness.

Component-based software reliability process simulation considering imperfect debugging

In view of the flaws of component-based software(CBS) reliability modeling and analysis,the low recognition degree of debugging process,too many assumptions and difficulties in obtaining the solution,a CBS reliability simulation process is presented incorporating the imperfect debugging and the limitation of debugging resources.Considering the effect of imperfect debugging on fault detection and correction process,a CBS integration testing model is sketched by multi-queue multichannel and finite server queuing model(MMFSQM).Compared with the analytical method based on parameters and other nonparametric approaches,the simulation approach can relax more of the usual reliability modeling assumptions and effectively expound integration testing process of CBS.Then,CBS reliability process simulation procedure is developed accordingly.The proposed simulation approach is validated to be sound and effective by simulation experiment studies and analysis.

Probabilistic Methods for Reliability Assessment of Floating Structures Based on Extreme Wave Simulation

With the increasing application of floating platforms in deep waters and harsh environments,a proper assessment of the reliability of floating structures is important to ensure that these structures can operate safely during their design lives.This study outlines a practical methodology for reliability analysis of a semi-submersible platform based estimating the probability distribution of the extreme response in rough sea conditions(survival conditions).The Constrained NewWave(CNW)theory combined with Monte Carlo simulations was first applied to simulate the random wave surface elevation process in the time domain.A Gumbel distribution was the best fitting to describe the dynamically sensitive extreme response statistics under extreme waves(drift and mooring tension).The derived probability distribution of the extreme response was subsequently used in estimation of the associated limit state func-tion,and a reliability analysis of the floating structure was conducted using the Monte Carlo method.A semi-submersible platform in a water depth of 1500 m subjected to extreme wave loads was used to demonstrate the efficiency of the proposed methodology.The probability of failure of the semi-submersible when considering mooring lines tension is greater than considering drift.

A Dynamic Model and a Simulation Method for Structural Reliability

This paper introduces a dynaniic model for structural reliability. This modelorsanically combines a niatheniatical niodel with a physical cause method. Asimulation method for the estimation of structural reliability is put forward. Itsbasic principle is that the eetimation of the general reliability of structure maybe obtained by simulating the test of structural life to get the samples ofstructural life. Therefore a basis is provided to evaluate dyna.niic strticrurereliability completely.

USING SYSTEM SIMULATION METHOD AND CAD TECHNIQUE TO SOLVE THE MINING ENGINEERING RELIABILITY IN SURFACE MINES

Subjected to various stochastic factors, surface mining engineering reliability is difficult to solve by using general reliability mathematical method.The concept of reliability measurement is introduced; And the authors have combined system simulation method with CAD technique and developed an interactive color character graphic design system for evaluating and solving the mining engineering reliability in surface mines under the given constraints.

Study on the random simulation times of mining engineering reliability

The theory of Monte-Carlo simulation method is that the event happened probability was estimated by happened frequency in the experiments. So it is very im-portant to ascertain the times of simulation. The probability and statistic theory are used to determine the optimal simulation times through strict mathematic reasoning. The study of two cases is made to show the availability of the presented method, and some relative problems were discussed.

Reduced Expanding Load Method for Simulation-Based Structural System Reliability Analysis

The current situation and difficulties of the structural system reliability analysis are mentioned. Then on the basis of Monte Carlo method and computer simulation, a new analysis method reduced expanding load method (RELM) is presented, which can be used to solve structural reliability problems effectively and conveniently. In this method, the uncertainties of loads, structural material properties and dimensions can be fully considered. If the statistic parameters of stochastic variables are known, by using this method, the probability of failure can be estimated rather accurately. In contrast with traditional approaches,RELM method gives a much better understanding of structural failure frequency and its reliability index β is more meaningful.To illustrate this new idea, a specific example is given.

An Overview of Recently Developed Coupled Simulation Optimization Approaches for Reliability Based Minimum Cost Design of Water Retaining Structures

This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.

Capacitated stochastic coloured Petri net-based approach for computing two-terminal reliability of multi-state network

Classical network reliability problems assume both net- works and components have only binary states, fully working or fully failed states. But many actual networks are multi-state, such as communication networks and transportation networks. The nodes and arcs in the networks may be in intermediate states which are not fully working either fully failed. A simulation ap- proach for computing the two-terminal reliability of a multi-state network is described. Two-terminal reliability is defined as the probability that d units of demand can be supplied from the source to sink nodes under the time threshold T. The capacities of arcs may be in a stochastic state following any discrete or continuous distribution. The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and de- mand. To solve this problem, a capacitated stochastic coloured Petri net is proposed for modelling the system behaviour. Places and transitions respectively stand for the nodes and arcs of a net- work. Capacitated transition and self-modified token colour with route information are defined to describe the multi-state network. By the simulation, the two-terminal reliability and node importance can be estimated and the optimal route whose reliability is highest can also be given. Finally, two examples of different kinds of multi- state networks are given.