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RISS 인기검색어
- 검색키워드
- 저자 : Xiao-ya Bian (검색결과 3 건)
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Reliability Analysis for Serviceability Limit State of Pile Groups Foundation
Xiao-ya Bian,Jun-jie Zheng,Rong-Jun Zhang,Zhi-jun Xu 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.1
The aim of this paper is to present an approach for the assessment of the Serviceability Limit State (SLS) reliability of pile groups foundation combining the Ultimate Limit State (ULS) reliability method of pile groups. To this end, the linear relationship between the ULS and SLS reliability indices is presented using the formulas for calculating the ULS and SLS reliability indices of single piles. Meanwhile, the influence of system effects, correlation coefficient between pile group efficiency and system effects (ρζ,χ), and limiting tolerable settlement (Slt) on the SLS reliability analysis of pile groups foundation is studied using pile load test data compiled for illustration. The results indicate that both the ULS reliability index (βG-uls) and the SLS reliability index (βG-sls) of pile groups foundation decrease with ρζ,χ, that powerful system effects can enhance the ULS and SLS reliability of pile groups foundation, and that βG-sls increases with Slt. the reliability level estimated by pile load test data is equivalent to that incorporating the SLS requirements with a certain value of Slt between 15 mm and 25 mm. For Slt larger than this value, Reliability-based Design (RBD) of pile groups foundation will depend on the ULS requirements, but, conversely, RBD will depend on the SLS requirements.
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Xiao-ya Bian,Jun-jie Zheng,Zhi-jun Xu 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.4
This study develops a novel reliability-based approach for the analysis and design of piles by incorporating Serviceability Limit State (SLS) requirements into Load and Resistance Factor Design (LRFD) for Ultimate Limit States (ULS). Three methods for reliability-based analysis and design, namely the Mean Value First Order Second Moment (MVFOSM) method, the Advanced First Order Second Moment (AFOSM) method, and the Monte Carlo Simulation (MCS) method, are employed for comparison. In order to expediently quantify model uncertainties for SLS and incorporate them into the process of reliability-based analysis and design of piles, the SLS model factor (or bias factor) is established based on a two-parameter, hyperbolic curve-fitting equation describing the load-settlement relation. Herein, the limiting tolerable foundation settlement (slt) is treated as a random variable. Four load test databases from South Africa presented by Dithinde et al. (2011) are compiled again to conduct reliability analysis and calculate resistance factors. The case studies illustrate that the AFOSM method has the higher accuracy than the MVFOSM method as verified using the MCS method. This study recommends the AFOSM method to perform reliability analysis and determine resistance factors for Reliability-Based Design (RBD).
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Cloning and functional characterization of two GsSnRK1 gene promoters from wild soybean
Chen Jun,Li Qiang,Zhang Pengmin,Lu Haoran,Bian Ya,Jian Yi,Wang Yizhu,Ding Xiaodong,Xiao Jialei 한국식물생명공학회 2021 Plant biotechnology reports Vol.15 No.5
Sucrose non-fermenting-related protein kinase 1 (SnRK1) belongs to a plant serine/threonine protein kinase family, and is part of a large interactive network of signaling pathways in plants to regulate many aspects of growth and development, and its gene expressions are highly responsive to multiple external stimuli. To functionally characterize the role of different SnRK1 members in wild soybean and identify the expression patterns of novel SnRK1 promoters for transgenic research, in this study, we performed an in silico analysis of the SnRK1 gene family in wild soybean and found GsSnRK1.1 and GsSnRK1.2 are main SnRK1 isoforms in wild soybean. The promoter fragments of both GsSnRK1.1 and GsSnRK1.2 were isolated, and a series of 5′-deletion and the full-length versions of both GsSnRK1.1 and GsSnRK1.2 promoters were fused with GUS reporter gene to generate expression vectors. The GUS activities in different tissues of seedling and adult growth stages of transgenic Arabidopsis plants were determined, and the GUS activities in transgenic Arabidopsis plants under NaCl, NaHCO3, PEG, ABA, MeJA and SA were also analyzed. The results showed that GsSnRK1.1 and GsSnRK1.2 genes have different expression patterns and both promoters may contain enhancers and silencers. In addition, NaCl, NaHCO3, ABA, MeJA, and PEG treatments enhanced, whereas SA treatment decreased the GUS activity under the control of both GsSnRK1.1 and GsSnRK1.2 promoters, which may be due to the distributions of various cis-elements in both GsSnRK1.1 and GsSnRK1.2 promoter regions. These results will contribute to a better understanding of the underlying mechanisms of GsSnRK1 genes in response to various abiotic stresses, and as stress-inducible promoters, GsSnRK1.1 and GsSnRK1.2 promoters can be candidates for practical application in agriculture.
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