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Michael D. Shields
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Cited by
Year
The generalization of Latin hypercube sampling
MD Shields, J Zhang
Reliability Engineering & System Safety 148, 96-108, 2016
3802016
A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process
MD Shields, G Deodatis, P Bocchini
Probabilistic Engineering Mechanics 26 (4), 511-519, 2011
1782011
Refined stratified sampling for efficient Monte Carlo based uncertainty quantification
MD Shields, K Teferra, A Hapij, RP Daddazio
Reliability Engineering and System Safety 142, 310-325, 2015
1282015
On the quantification and efficient propagation of imprecise probabilities resulting from small datasets
J Zhang, MD Shields
Mechanical Systems and Signal Processing 98, 465-483, 2018
932018
Modeling strongly non-Gaussian non-stationary stochastic processes using the Iterative Translation Approximation Method and Karhunen–Loève expansion
H Kim, MD Shields
Computers & Structures 161, 31-42, 2015
862015
A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic vector process by a translation process with applications in wind velocity simulation
MD Shields, G Deodatis
Probabilistic Engineering Mechanics 31, 19-29, 2013
802013
Bayesian neural networks for uncertainty quantification in data-driven materials modeling
A Olivier, MD Shields, L Graham-Brady
Computer Methods in Applied Mechanics and Engineering 386, 114079, 2021
682021
Estimation of evolutionary spectra for simulation of non-stationary and non-Gaussian stochastic processes
MD Shields, G Deodatis
Computers & Structures 126, 149-163, 2013
642013
UQpy: A general purpose Python package and development environment for uncertainty quantification
A Olivier, D Giovanis, BS Aakash, M Chauhan, L Vandanapu, MD Shields
Journal of Computational Science 47, 101204, 2020
632020
Cohesive zone modeling and calibration for mode I tearing of large ductile plates
PB Woelke, MD Shields, JW Hutchinson
Engineering Fracture Mechanics 147, 293-305, 2015
612015
Simulations of ductile fracture in an idealized ship grounding scenario using phenomenological damage and cohesive zone models
PB Woelke, MD Shields, NN Abboud, JW Hutchinson
Computational Materials Science 80, 79-95, 2013
582013
Surrogate-enhanced stochastic search algorithms to identify implicitly defined functions for reliability analysis
VS Sundar, MD Shields
Structural Safety 62, 1-11, 2016
502016
Coarse graining atomistic simulations of plastically deforming amorphous solids
AR Hinkle, CH Rycroft, MD Shields, ML Falk
Physical Review E 95 (5), 053001, 2017
492017
Topology optimization for linear stationary stochastic dynamics: Applications to frame structures
M Zhu, Y Yang, JK Guest, MD Shields
Structural Safety 67, 116-131, 2017
422017
Simulation of spatially correlated nonstationary response spectrum–compatible ground motion time histories
MD Shields
Journal of Engineering Mechanics 141 (6), 04014161, 2015
412015
Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold
DG Giovanis, MD Shields
Computer Methods in Applied Mechanics and Engineering 370, 113269, 2020
382020
Reliability analysis using adaptive kriging surrogates with multimodel inference
VS Sundar, MD Shields
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A …, 2019
372019
The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets
J Zhang, MD Shields
Computer Methods in Applied Mechanics and Engineering 334, 483-506, 2018
372018
Deep transfer operator learning for partial differential equations under conditional shift
S Goswami, K Kontolati, MD Shields, GE Karniadakis
Nature Machine Intelligence 4 (12), 1155-1164, 2022
362022
Adaptive Monte Carlo analysis for strongly nonlinear stochastic systems
MD Shields
Reliability Engineering & System Safety 175, 207-224, 2018
342018
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