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Xianzhen Huang
Northeastern University
29Publications
7H-index
185Citations
Publications 22
Newest
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Louis J. M. Aslett (Durham University)H-Index: 6
Last.Frank P. A. Coolen (Durham University)H-Index: 24
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Abstract It is often difficult for a phased mission system (PMS) to be highly reliable, because this entails achieving high reliability in every phase of operation. Consequently, reliability analysis of such systems is of critical importance. However, efficient and interpretable analysis of PMSs enabling general component lifetime distributions, arbitrary structures, and the possibility that components skip phases has been an open problem. In this paper, we show that the survival signature can b...
1 CitationsSource
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Frank P. A. Coolen (Durham University)H-Index: 24
Last.Tahani Coolen-Maturi (Durham University)H-Index: 9
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In recent research, the major focus on reliability-redundancy allocation problems has been on the possibility of using more efficient and effective algorithms to improve convergence speed and solution accuracy of the optimization model. But the model of reliability-redundancy allocation itself has not been investigated further. In this paper, we try to simplify the optimization model of the reliability-redundancy allocation problem by using the theory of survival signature. To achieve this, the ...
1 CitationsSource
Reliability importance which serves to quantify the influence of each component (or each type of components) in each phase on the reliability of a phased mission system (PMS) plays an important role in security assessment and risk management. In this paper, we present a new and efficient method for reliability importance analysis of PMSs using the theory of survival signature. A new kind of survival signature is applied to assess the reliability of PMS with multiple types of components. A closed...
Source
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Sujun Jin (NU: Northeastern University)H-Index: 1
Last.David He (NU: Northeastern University)H-Index: 29
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In reality, a system and its components, apart from internal failures, are often exposed to external shocks as well. Since external shocks have significant effects on the performance of the system, neglecting their effects during reliability analysis of the system leads to large prediction errors and even misleading conclusions. In this paper, we present a new method for reliability analysis of coherent systems subject to internal failures and random external shocks. The cumulative probability o...
6 CitationsSource
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Frank P. A. Coolen (Durham University)H-Index: 24
The reliability sensitivity can be used to rank distribution parameters of system components concerning their impacts on the system’s reliability. Such information is essential to purposes such as component prioritization, reliability improvement, and risk reduction of a system. In this article, we present an efficient method for reliability sensitivity analysis of coherent systems using survival signature. The survival signature is applied to calculate the reliability of coherent systems. The...
2 CitationsSource
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Yuxiong Li (NU: Northeastern University)H-Index: 1
Last.Xufang Zhang (NU: Northeastern University)H-Index: 5
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Abstract In the second-order reliability method, the limit state function in arbitrarily distributed random variables is approximated by a quadratic polynomial of standard normal variables. The fitted quadratic polynomial is then used to calculate the probability of failure of the limit state. However, a closed-form solution for the probability of failure of a general quadratic polynomial surface is not available. As such, in this paper, a new second-order reliability method for reliability anal...
14 CitationsSource
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Fangjun Jia (NU: Northeastern University)
Last.Jinhua Lian (Taiyuan Heavy Industry Co., Ltd.)
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Abstract. Machining accuracy of a milled surface is influenced by process dynamics. Surface location error (SLE) in milling determines final dimensional accuracy of the finished surface. Therefore, it is critical to predict, control, and minimize SLE. In traditional methods, the effects of uncertain factors are usually ignored during prediction of SLE, and this would tend to generate estimation errors. In order to solve this problem, this paper presents methods for probabilistic analysis of SLE ...
Source
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Mingwei Hu (NU: Northeastern University)H-Index: 1
Last.Yimin Zhang (NU: Northeastern University)H-Index: 11
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Regenerative chatter in turning can cause serious tool wear or breakage, along with poor surface finish on the machined workpiece. Consequently, it is critical to avoid the occurrence of chatter in turning process. In this paper, dynamic model of regenerative chatter in turning process is established to predict the limited cutting width and derive the stability lobe diagram. This study addresses the influences of uncertain factors on the turning process, and a reliability based optimization mode...
Source
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Yang Liu (NU: Northeastern University)H-Index: 1
Last.Xufang Zhang (NU: Northeastern University)H-Index: 5
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Stochastic response surface method (SRSM) is a technique used for reliability analysis of complex structural systems having implicit or time consuming limit state functions. The main aspects of the SRSM are the collection of sample points, the approximation of response surface and the estimation of the probability of failure. In this paper, sample points are selected close to the most probable point of failure and the actual limit state surface (LSS). The response surface is fitted using the wei...
7 CitationsSource
#1Xianzhen Huang (NU: Northeastern University)H-Index: 7
#2Mingwei Hu (NU: Northeastern University)H-Index: 1
Last.Chunmei Lv (NU: Northeastern University)H-Index: 5
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In practical engineering, randomness of the parameters (mass, stiffness, and cutting coefficients) significantly impacts the stability of turning processes. In this study, the method involving the probabilistic analysis of the regenerative chatter stability in turning is comprehensively investigated. Considering the influences of random factors, the probability characteristic of the regenerative chatter stability in turning is studied using the Monte Carlo simulation (MCS) method and advanced fi...
7 CitationsSource
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