武器装备体系作战能力评估中的耦合风险研究

武器装备体系的耦合程度是衡量武器装备体系整体作战能力的一个重要指标。通过识别武器装备体系耦合风险源,求取了武器装备体系的耦合风险因子,探讨了武器装备体系作战能力的表达式。算例表明,研究武器装备体系的耦合风险对提高武器装备体系作战能力是有效的。

基于Monte Carlo法与GA算法的复杂系统可靠度求解

复杂系统可靠性问题是可靠性工程中丞待解决的问题。提出了基于可靠性框图的复杂系统蒙特.卡罗仿真方法,给出了各种基本可靠性模型系统与其组成单元的失效时间关系,解决了含有旁联模型的复杂系统仿真问题。以可靠性仿真数据为寿命样本,待估计参数的置信区间为编码空间,以经验分布与所求分布误差倒数为适应度函数,建立了基于遗传算法的寿命分布参数点估计模型,求得了复杂系统可靠度函数。最后以两个实例表明该方法比传统方法具有更高的精度。

Method of Jamming C/A Code GPS Receiver

The schemes and effects of electronically jamming GPS’s C/A code receivers are studied by using CW as the narrow band jamming signal and BPSK signal modulated by Gold code which is incoherent to that adopted by GPS as the wide band one. By simulating with Monte Carlo method and programming in Matlab language, the various jamming results in terms of bit error rate under several jamming scenarios are obtained. Through analyzing the simulation results and quantitative dependences of jamming effects on the distance from jammer to GPS receiver and the jammer’s height over ground, it is concluded that jamming with wide band jammer is much more effective than that with narrow band one.

Effects of tissue absorption on calculation of mean photon path length using modified Beer-Lambert law

The mean path length(MPL)of photons is a critical parameter to calculate tissue absorption coefficient as well as blood oxygenation using modified Beer-Lambert law,where in the differential path factor(DPF)is often assumed as constant over range of tissue absorption.By utilizing the Monte Carlo(MC)simulation of photon migrations in the leg,this study used four approaches to estimate MPL,and compared them with that determined by the MPL definition.The simulation results indicate that the DPF is remarkably affected by tissue absorption,at approximate 10% variation.A linear model is suggested to calculate MPL for measurements of tissue absorption as well as blood oxygenation using modified Beer-Lambert law.

Random Model and Simulation for Nucleation Stage of Emulsion Polymerization

The method of mathematical model and further computer simulation is an effective way to the theoretical study of emulsion polymerization and the scale-up of the reactors. In this work, Monte Carlo method has been used to simulate the nucleation of emulsion polymerization. The effects of emulsifier concentration [S] and initiator concentration [I] on various parameters such as the number of the particles (N p), the average diameter of the latex particles (D p), monomer conversion (x) and average radical number per particle (n) have been studied. The quantitative equations between [S], [I] and N p are in accord absolutely with the classical theory of Smith-Ewart.

A novel SMC-PHD filter based on particle compensation

As a typical implementation of the probability hypothesis density(PHD) filter, sequential Monte Carlo PHD(SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduced by the resampling step, together with the high computational burden problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this work, a novel SMC-PHD filter based on particle compensation is proposed to solve above problems. Firstly, according to a comprehensive analysis on the particle impoverishment problem, a new particle generating mechanism is developed to compensate the particles. Then, all the particles are integrated into the SMC-PHD filter framework. Simulation results demonstrate that, in comparison with the SMC-PHD filter, proposed PC-SMC-PHD filter is capable of overcoming the particle impoverishment problem, as well as improving the processing rate for a certain tracking accuracy in different scenarios.

Robustness analysis of underground powerhouse construction simulation based on Markov Chain Monte Carlo method

Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual construction, which may lead to discrepancies between the actual and planned schedules and increase the risk of total duration delay. Therefore, developing a robust construction scheduling technique is of vital importance for mitigating disturbance and improving completion probability. In the present study, the authors propose a robustness analysis method that involves underground powerhouse construction simulation based on the Markov Chain Monte Carlo(MCMC) method. Specifically, the MCMC method samples construction disturbances by considering the interrelationship between the states of parameters through a Markov state transition probability matrix, which is more robust and efficient than traditional sampling methods such as the Monte Carlo(MC) method. Additionally, a hierarchical simulation model coupling critical path method(CPM) and a cycle operation network(CYCLONE) is built, using which construction duration and robustness criteria can be calculated. Furthermore, a detailed measurement method is presented to quantize the robustness of underground powerhouse construction, and the setting model of the time buffer is proposed based on the MCMC method. The application of this methodology not only considers duration but also robustness, providing scientific guidance for engineering decision making. We analyzed a case study project to demonstrate the effectiveness and superiority of the proposed methodology.

Study of methods for evaluating the probability of multiple site damage occurrences

Two methods currently available for evaluating the probability of Multiple Site Damage(MSD)occurrence were studied in this paper.One of the methods is a probabilistic analysis approach based on the statistical theory and fatigue characteristics of each structural detail,and the other is an approach which defines the initial damage scenario by means of Monte-Carlo simulation,and multiple initial crack scenarios are randomly generated.A modified method based on the Monte-Carlo simulation was proposed in this paper,in which the random fluctuation of the stress was considered to give more accurate evaluation results.In the presented method,the probability of MSD occurrence in a structural element containing multiple details was calculated based on the Monte-Carlo simulation and the p-S-N curve of a single structural detail.Fatigue tests were accomplished using specimens containing 21-similar-details to obtain the fatigue life corresponding to MSD occurrence.Tests on single-detail specimens and static calibration tests were also conducted to get the basic fatigue properties of the material and the degree of stress fluctuation.The aforementioned three methods were compared and validated via the test results.The influence of the stress random fluctuation degree on the probability of MSD occurrence and influence of the distribution types on evaluating the MSD occurrence probability were discussed.