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Armen Der Kiureghian
Researcher at University of California, Berkeley
Publications - 161
Citations - 14983
Armen Der Kiureghian is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Reliability (statistics) & Finite element method. The author has an hindex of 60, co-authored 160 publications receiving 12381 citations. Previous affiliations of Armen Der Kiureghian include University of British Columbia & University of Southern California.
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Aleatory or epistemic? Does it matter?
TL;DR: In this article, the sources and characters of uncertainties in engineering modeling for risk and reliability analyses are discussed, and they are generally categorized as either aleatory or epistemic, if the modeler sees a possibility to reduce them by gathering more data or by refining models.
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Structural reliability under incomplete probability information
TL;DR: In this paper, a comprehensive framework for the analysis of structural reliability under incomplete probability information is presented, consistent with the philosophy of Ditlevsen's generalized reliability index and complements existing second-moment and full-distribution structural reliability theories.
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Optimization algorithms for structural reliability
TL;DR: In this paper, several optimization algorithms are evaluated for application in structural reliability, where the minimum distance from the origin to the limit-state surface in the standard normal space is required, and the objective is to determine the suitability of the algorithms for application to linear and nonlinear finite element reliability problems.
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Standard penetration test-based probabilistic and deterministic assessment of seismic soil liquefaction potential
K. Onder Cetin,Raymond B. Seed,Armen Der Kiureghian,Kohji Tokimatsu,Leslie F. Harder,Robert E. Kayen,Robert E. S. Moss +6 more
TL;DR: In this paper, the authors present new correlations for assessment of the likelihood of initiation (or triggering) of soil liquefaction, which eliminate several sources of bias intrinsic to previous, similar correlations, and provide greatly reduced overall uncertainty and variance.
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Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns based on Experimental Observations
TL;DR: In this article, a methodology to construct probabilistic capacity models of structural components is developed, which properly accounts for aleatory and epistemic uncertainties, and is used to estimate the fragility of a typical bridge column in terms of maximum deformation and shear demands.