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Dian-Qing Li

Researcher at Wuhan University

Publications -  194
Citations -  6722

Dian-Qing Li is an academic researcher from Wuhan University. The author has contributed to research in topics: Slope stability & Reliability (statistics). The author has an hindex of 37, co-authored 186 publications receiving 4654 citations. Previous affiliations of Dian-Qing Li include Shanghai Jiao Tong University & Hong Kong University of Science and Technology.

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A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties

TL;DR: In this paper, a multiple response-surface method for slope reliability analysis considering spatially variable soil properties is proposed and the effect of theoretical autocorrelation functions (ACFs) on slope reliability is highlighted since the theoretical ACFs are often used to characterize the spatial variability of soil properties.
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Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method

TL;DR: In this paper, a non-intrusive stochastic finite element method for slope reliability analysis considering spatially variable shear strength parameters is proposed, which does not require the user to modify existing deterministic finite element codes, which provides a practical tool for analyzing slope reliability problems that require complex finite element analysis.
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Stochastic response surface method for reliability analysis of rock slopes involving correlated non-normal variables

TL;DR: In this paper, a stochastic response surface method for reliability analysis involving correlated non-normal random variables, in which the Nataf transformation is adopted to effectively transform the correlated nonnormal variables into independent standard normal variables, is presented.
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Efficient System Reliability Analysis of Slope Stability in Spatially Variable Soils Using Monte Carlo Simulation

TL;DR: In this paper, a Monte Carlo simulation (MCS) based approach for efficient evaluation of the system failure probability P f, s of slope stability in spatially variable soils is presented.
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Bayesian perspective on geotechnical variability and site characterization

TL;DR: In this paper, a Bayesian inverse analysis framework for direct quantification of the actual variability of various soil and rock properties is proposed, which is based on the mapping of inherent variability, statistical uncertainty, measurement errors, and transformation uncertainty.