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Uncertainty driven active learning of coarse grained free energy models
Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically...
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Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials
Efficiently creating a concise but comprehensive data set for training machine-learned interatomic potentials (MLIPs) is an under-explored problem....
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Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
Neural networks (NNs) often assign high confidence to their predictions, even for points far out of distribution, making uncertainty quantification...
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Uncertainty-aware particle segmentation for electron microscopy at varied length scales
Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder...
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A Process-Structure-Property Simulation Framework for Quantifying Uncertainty in Additive Manufacturing: Application to Fatigue in Ti-6Al-4V
Metal additive manufacturing (AM) processes produce heterogeneous microstructures, leading to significant uncertainty in mechanical behavior....
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Lamination curing method for silver nanoparticle inkjet printed flexible electronics: design, uncertainty and performance analysis
In this paper, we propose a fast, simple, low-cost and high-performance curing method, “lamination curing”, to activate silver nano-particle inkjet...
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Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC
Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and...
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Calibration after bootstrap for accurate uncertainty quantification in regression models
Obtaining accurate estimates of machine learning model uncertainties on newly predicted data is essential for understanding the accuracy of the model...
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Determination of Chlorine in Dusty Waste in Ferronickel Production: Analysis and Estimation of Uncertainty
AbstractA key stage in ferronickel production is sulfate-chlorination roasting after which and at subsequent stages (up to the final product is...
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Certain About Uncertainty
One hundred years ago the physics that would be necessary to understand how quantum computers work, much less how to build them, did not exist. In...
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Estimating the Uncertainty of the Torque Standard Machine at Vietnam Metrology Institute
This paper presents the estimation of the uncertainty of the torque standard machine manufactured and integrated at the Vietnam Metrology Institute....
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Estimation of Uncertainty of Measurement for Experimental Determination of Longitudinal Modulus for Carbon/Carbon Composites
Uncertainty of measurement is an important parameter for any experiment where measurements are involved. Several advanced materials are in use for...
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Reliability Evaluation of an NPP’s Emergency Power Supply System Considering Uncertainty, Sensitivity and Testing Interval Analyses
This paper proposes a reliability analysis methodology of an electrical power system (EPS) in a French nuclear power plant model based on the fault...
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Physics-Informed Machine Learning and Uncertainty Quantification for Mechanics of Heterogeneous Materials
A model based on the Physics-Informed Neural Networks (PINN) for solving elastic deformation of heterogeneous solids and associated Uncertainty...
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Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models
This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of...
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Multi-fidelity Modeling for Uncertainty Quantification in Laser Powder Bed Fusion Additive Manufacturing
Computer simulation of the additive manufacturing (AM) process involves multi-physics, multi-scale models. These sophisticated higher fidelity (HF)...
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Thermal Control and Uncertainty Evaluation for Characterising Aluminium Formability Under Hot Stam** Conditions
Material formability under hot stam** conditions can be characterised by using an innovative Gleeble-based biaxial testing method with cruciform...
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Application of approximate Bayesian computation for estimation of modified weibull distribution parameters for natural fiber strength with high uncertainty
Despite the unique advantages of natural fibers as a reinforcement in polymer composites, they have high natural variability in their mechanical...
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Uncertainty Quantification for DIC Displacement Measurements in Industrial Environments
Background: most methods of uncertainty quantification for digital image correlation are orientated towards the research environment and it remains...
