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RISS 인기검색어
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- 저자 : Dian Zhou (검색결과 13 건)
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System Reliability Analysis of Rock Slope Stability Involving Correlated Failure Modes
Dian-Qing Li,Shui-Hua Jiang,Yi-Feng Chen,Chuang-Bing Zhou 대한토목학회 2011 KSCE JOURNAL OF CIVIL ENGINEERING Vol.15 No.8
This paper aims to propose a systematic quantitative method for system reliability evaluation of rock slope with plane failure involving multiple correlated failure modes. A probabilistic fault tree approach is presented to model system reliability of rock slope. An n-dimensional equivalent reliability method is employed to perform the system reliability analysis of the slope involving multiple correlated failure modes. Reliability sensitivity analyses at three different levels, namely, the single limit state function level, single failure mode level, and system reliability level, are carried out to study the effect of variables on reliability. An example is presented to demonstrate the validity and capability of the proposed approach. The results indicate that the system reliability of rock slope involving multiple correlated failure modes can be evaluated efficiently using the proposed approach. The system probability of failure is overestimated if the correlations between different failure modes are ignored. The relative importance of different failure modes to the system reliability can differ considerably. The sensitivity coefficients of basic random variables strongly depend on the selected sensitivity analysis level. The system reliability is sensitive to the location of the tension crack and the percentage of the tension crack filled with water.
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Dian-Qing Li,Shui-Hua Jiang,Yong-Gang Cheng,Chuang-Bing Zhou 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
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Li, Dian-Qing,Jiang, Shui-Hua,Cheng, Yong-Gang,Zhou, Chuang-Bing Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
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Jiang, Shui-Hua,Li, Dian-Qing,Zhou, Chuang-Bing,Zhang, Li-Min Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
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Shui-Hua Jiang,Dian-Qing Li,Chuang-Bing Zhou,Li-Min Zhang 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
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Performance Analysis of Power Line Communication Network Model Based on Spider Web
Liu Xiao-sheng,Zhang Liang,ZHOU Yan,Xu Dian-guo 전력전자학회 2011 ICPE(ISPE)논문집 Vol.2011 No.5
To enhance the reliability of narrow band PLC (Power Line Communication) in low-voltage network, inspired by the structure and invulnerability of spider web, a new PLC network model is proposed in this paper. The characteristics of the model and the transformational process of low-voltage distribution network from physical topology to artificially spider web logical topology are thoroughly discussed. New networking algorithm and route-reconstruction algorithm are put forward. A two-state Markov model is used to simulate a terminal node and the time-delay characteristic of the new algorithm is analyzed by modeling. Based on Opnet14.5, simulation and comparison are conducted, which prove that the new network model has advantages in improving the communication reliability of PLC network.
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Senescence as A Consequence of Ginsenoside Rg<sub>1</sub> Response on K562 Human Leukemia Cell Line
Liu, Jun,Cai, Shi-Zhong,Zhou, Yue,Zhang, Xian-Ping,Liu, Dian-Feng,Jiang, Rong,Wang, Ya-Ping Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.12
Aims and Background: Traditional chemotherapy strategies for human leukemia commonly use drugs based on cytotoxicity to eradicate cancer cells. One predicament is that substantial damage to normal tissues is likely to occur in the course of standard treatments. Obviously, it is urgent to explore therapies that can effectively eliminate malignant cells without affecting normal cells. Our previous studies indicated that ginsenoside $Rg_1$ ($Rg_1$), a major active pharmacological ingredient of ginseng, could delay normal hematopoietic stem cell senescence. However, whether $Rg_1$ can induce cancer cell senescence is still unclear. Methods: In the current study, human leukemia K562 cells were subjected to $Rg_1$ exposure. The optimal drug concentration and duration with K562 cells was obtained by MTT colorimetric test. Effects of $Rg_1$ on cell cycle were analyzed using flow cytometry and by SA-${\beta}$-Gal staining. Colony-forming ability was measured by colony-assay. Telomere lengths were assessed by Southern blotting and expression of senescence-associated proteins P21, P16 and RB by Western blotting. Ultrastructural morphology changes were observed by transmission electron microscopy. Results: K562 cells demonstrated a maximum proliferation inhibition rate with an $Rg_1$ concentration of $20{\mu}\;mol{\cdot}L^{-1}$ for 48h, the cells exhibiting dramatic morphological alterations including an enlarged and flat cellular morphology, larger mitochondria and increased number of lysosomes. Senescence associated-${\beta}$-galactosidase (SA-${\beta}$-Gal) activity was increased. K562 cells also had decreased ability for colony formation, and shortened telomere length as well as reduction of proliferating potential and arrestin $G_2$/M phase after $Rg_1$ interaction. The senescence associated proteins P21, P16 and RB were significantly up-regulated. Conclusion: Ginsenoside $Rg_1$ can induce a state of senescence in human leukemia K562 cells, which is associated with p21-Rb and p16-Rb pathways.
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