Reliability Analysis of Repairable Systems Using Stochastic Point Processes

In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.

Developed mathematical technique for fractional stochastic point kinetics model in nuclear reactor dynamics

Fractional stochastic kinetics equations have proven to be valuable tools for the point reactor kinetics model, where the nuclear reactions are not fully described by deterministic relations. A fractional stochastic model for the point kinetics system with multi-group of precursors,including the effect of temperature feedback, has been developed and analyzed. A major mathematical and inflexible scheme to the point kinetics model is obtained by merging the fractional and stochastic technique. A novel split-step method including mathematical tools of the Laplace transforms, Mittage–Leffler function, eigenvalues of the coefficient matrix, and its corresponding eigenvectors have been used for the fractional stochastic matrix differential equation. The validity of the proposed technique has been demonstrated via calculations of the mean and standard deviation of neutrons and precursor populations for various reactivities: step, ramp, sinusoidal, and temperature reactivity feedback. The results of the proposed method agree well with the conventional one of the deterministic point kinetics equations.

A New Approach to Simulate Positional Error of Line Segment in GIS

To determine the distribution of positional error of a line segment, Monte Carlo approach is applied to simulate the probability density function of a line segment with the assumption that the error of endpoints in a line segment follows a two-dimensional normal distribution. For such purpose, a stochastic generator used for uncertain endpoints with the two-dimensional normal distribution is presented. This forms the basis of the generation of random line segment for the simulation of the error model of a whole line segment. The error models cover the cases where two endpoints are either independent or dependent to each other, also including a special case that the distance between two random endpoints in a line segment is close enough.

Existence of p-mean Almost Periodic Mild Solution for Fractional Stochastic Neutral Functional Differential Equation

A class of fractional stochastic neutral functional differential equation is analyzed in this paper.With the utilization of the fractional calculations,semigroup theory,fixed point technique and stochastic analysis theory,a sufficient condition of the existence for p-mean almost periodic solution is obtained,which are supported by two examples.

Adaptive merit function in SPGD algorithm for beam combining

The beam pointing is the most crucial issue for beam combining to achieve high energy laser output. In order to meet the turbulence situation, a beam pointing method that cooperates with the stochastic parallel gradient descent(SPGD) algorithm is proposed. The power-in-the-bucket(PIB) is chosen as the merit function, and its radius changes gradually during the correction process. The linear radius and the exponential radius are simulated. The results show that the exponential radius has great promise for beam pointing.