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Predicting laser weld reliability with stochastic reduced‐order models
7 references·4 citing·27 second hop
Predicting laser weld reliability with stochastic reduced‐order models (2015)Predicting laser weld reliability with st…On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems (2015)On the efficacy of stochastic…Stochastic reduced order models for random vectors: Application to random eigenvalue problems (2012)Stochastic reduced order mode…A method for solving stochastic equations by reduced order models and local approximations (2012)A method for solving stochast…A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)A Sparse Grid Stochastic Coll…Reduced order models for random functions. Application to stochastic problems (2007)Reduced order models for rand…A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A Stochastic Collocation Meth…Applied non-Gaussian processes : examples, theory, simulation, linear random vibration, and MATLAB solutions (1995)Applied non-Gaussian processe…Modeling strength and failure variability due to porosity in additively manufactured metals (2020)Modeling strength and failure…Bayesian modeling of inconsistent plastic response due to material variability (2019)Bayesian modeling of inconsis…Stochastic Reduced Order Models with Python (SROMPy) (2018)Stochastic Reduced Order Mode…Bayesian methods for characterizing unknown parameters of material models (2016)Bayesian methods for characte…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis (2009)Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization (2018)Numerical Methods for Stochastic Computations: A Spectral Method Approach (2010)Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates (2013)Stochastic reduced order models for inverse problems under uncertainty (2014)Hybrid uncertain natural frequency analysis for structures with random and interval fields (2017)Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)Response Statistics for Random Heterogeneous Microstructures (2014)Optimization of PDEs with Uncertain Inputs (2018)Stochastic Finite Elements: A Spectral Approach (1991)Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations (2004)Uncertainty Quantification of Crosstalk Using Stochastic Reduced Order Models (2016)UQpy: A general purpose Python package and development environment for uncertainty quantification (2020)Stochastic Differential Equations (2003)Multiscale simulation of spatially correlated microstructure via a latent space representation (2024)STATISTICS FOR SPATIAL DATA (1992)Uncertainty Quantification of Microstructures: A Perspective on Forward and Inverse Problems for Mechanical Properties of Aerospace Materials (2024)Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)Translation models revisited (2017)Adaptive method for indirect identification of the statistical properties of random fields in a Bayesian framework (2019)Probabilistic engineering mechanics (1993)Computational stochastic mechanics – recent advances (2001)Simulation of second-order processes using Karhunen–Loeve expansion (2002)On the performance evaluation of stochastic finite elements in linear and nonlinear problems (2020)
this work references cited by second hop

References

  • 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data1,396 cited
  • 2008A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data942 cited
  • 1995Applied non-Gaussian processes : examples, theory, simulation, linear random vibration, and MATLAB solutions288 cited
  • 2007Reduced order models for random functions. Application to stochastic problems94 cited
  • 2012Stochastic reduced order models for random vectors: Application to random eigenvalue problems52 cited
  • 2015On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems35 cited
  • 2012A method for solving stochastic equations by reduced order models and local approximations29 cited

Cited by

  • 2020Modeling strength and failure variability due to porosity in additively manufactured metals23 cited
  • 2016Bayesian methods for characterizing unknown parameters of material models17 cited
  • 2019Bayesian modeling of inconsistent plastic response due to material variability15 cited
  • 2018Stochastic Reduced Order Models with Python (SROMPy)8 cited

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