DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

Journal Article · · Physica. D, Nonlinear Phenomena

Not Available

Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
AC02-06CH11357
OSTI ID:
1995927
Journal Information:
Physica. D, Nonlinear Phenomena, Journal Name: Physica. D, Nonlinear Phenomena Journal Issue: C Vol. 454; ISSN 0167-2789
Publisher:
ElsevierCopyright Statement
Country of Publication:
Netherlands
Language:
English

References (58)

Data-driven sparse reconstruction of flow over a stalled aerofoil using experimental data journal January 2021
Regularized Evolution for Image Classifier Architecture Search journal July 2019
Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling journal August 2018
Robust flow reconstruction from limited measurements via sparse representation journal October 2019
Multi-fidelity information fusion with concatenated neural networks journal April 2022
Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations
  • Carlberg, Kevin; Bou-Mosleh, Charbel; Farhat, Charbel
  • International Journal for Numerical Methods in Engineering, Vol. 86, Issue 2 https://doi.org/10.1002/nme.3050
journal October 2010
Long Short-Term Memory journal November 1997
Probabilistic neural networks for fluid flow surrogate modeling and data recovery journal October 2020
Physically constrained data‐driven correction for reduced‐order modeling of fluid flows journal October 2018
Accelerating Markov Chain Monte Carlo with Active Subspaces journal January 2016
Karhunen–Loève procedure for gappy data journal January 1995
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models journal May 2022
Data-driven nonintrusive reduced order modeling for dynamical systems with moving boundaries using Gaussian process regression journal January 2021
Non-autoregressive time-series methods for stable parametric reduced-order models journal August 2020
Neural network representability of fully ionized plasma fluid model closures journal July 2020
Active flow control using machine learning: A brief review journal April 2020
Proper orthogonal decomposition closure models for turbulent flows: A numerical comparison journal September 2012
Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism journal June 2020
Supremizer stabilization of POD-Galerkin approximation of parametrized steady incompressible Navier-Stokes equations: SUPREMIZER STABILIZATION OF POD-GALERKIN APPROXIMATION OF NS EQUATIONS
  • Ballarin, Francesco; Manzoni, Andrea; Quarteroni, Alfio
  • International Journal for Numerical Methods in Engineering, Vol. 102, Issue 5 https://doi.org/10.1002/nme.4772
journal November 2014
Reduced order modeling for nonlinear structural analysis using Gaussian process regression journal November 2018
Dynamic Mode Decomposition with Control journal January 2016
Galerkin v. least-squares Petrov–Galerkin projection in nonlinear model reduction journal February 2017
Optimization and sensitivity analysis of active drag reduction of a square-back Ahmed body using machine learning control journal December 2020
Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem journal May 2019
Non-linear Petrov–Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods journal February 2013
Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil journal April 2020
Deep learning observables in computational fluid dynamics journal June 2020
On the stability and convergence of a Galerkin reduced order model (ROM) of compressible flow with solid wall and far-field boundary treatment journal August 2010
Optimal reduced space for Variational Data Assimilation journal February 2019
Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons journal March 2023
Optimal Model Management for Multifidelity Monte Carlo Estimation journal January 2016
CNN-LSTM based reduced order modeling of two-dimensional unsteady flows around a circular cylinder at different Reynolds numbers journal December 2020
Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies of various shapes journal May 2020
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead journal May 2019
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems journal July 2020
Principal interval decomposition framework for POD reduced-order modeling of convective Boussinesq flows: PRINCIPAL INTERVAL DECOMPOSITION MODEL REDUCTION FRAMEWORK journal February 2015
Machine learning strategies applied to the control of a fluidic pinball journal January 2020
A lower-dimensional approximation model of turbulent flame stretch and its related quantities with machine learning approaches journal November 2020
Stochastic estimation of organized turbulent structure: homogeneous shear flow journal May 1988
Transformers for modeling physical systems journal February 2022
Physics-constrained bayesian neural network for fluid flow reconstruction with sparse and noisy data journal March 2020
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data journal October 2019
Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments journal August 2021
Enhanced data efficiency using deep neural networks and Gaussian processes for aerodynamic design optimization journal April 2021
Multiresolution Dynamic Mode Decomposition journal January 2016
Non-linear Petrov–Galerkin methods for reduced order modelling of the Navier–Stokes equations using a mixed finite element pair journal March 2013
Space--Time Least-Squares Petrov--Galerkin Projection for Nonlinear Model Reduction journal January 2019
Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems journal February 2023
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression journal November 2022
Assessment of supervised machine learning methods for fluid flows journal February 2020
The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability journal August 2015
Machine learning for fluid flow reconstruction from limited measurements journal January 2022
Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems journal August 2013
A Reduced Order Deep Data Assimilation model journal November 2020
Modal Analysis of Fluid Flows: Applications and Outlook journal March 2020
Extreme learning machine for reduced order modeling of turbulent geophysical flows journal April 2018
Model Reduction for Flow Analysis and Control journal January 2017
An intrinsic stabilization scheme for proper orthogonal decomposition based low-dimensional models journal May 2007