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Journal Articles

Model Parameter Calibration for Vibration Fatigue Analysis by Means of Bayesian Updating and Artificial Neural Network Based Surrogate Models

S. Maier, C. C. Saenz-Betancourt, F. Bachmann, R. Feldmann, B. Götz, F. Duddeck, T. Melz
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. September 2024, 9(3): 031001.
Paper No: VVUQ-23-1057
https://doi.org/10.1115/1.4065826
Published Online: July 13, 2024
View Article titled, Model Parameter Calibration for Vibration Fatigue Analysis by Means of Bayesian Updating and Artificial Neural Network Based Surrogate Models
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Topics: Artificial neural networks, Calibration, Vibration, Sensitivity analysis, Fatigue analysis, Stress, Damage
Journal Articles

Uncertainty Quantification of a Machine Learning Model for Identification of Isolated Nonlinearities With Conformal Prediction

David A. Najera-Flores, Justin Jacobs, D. Dane Quinn, Anthony Garland, Michael D. Todd
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021005.
Paper No: VVUQ-23-1054
https://doi.org/10.1115/1.4064777
Published Online: June 21, 2024
View Article titled, Uncertainty Quantification of a Machine Learning Model for Identification of Isolated Nonlinearities With Conformal Prediction
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Topics: Artificial neural networks, Damage, Machine learning, Noise (Sound), Uncertainty quantification
Journal Articles

Quantifying Uncertainty of Damage in Composites Using a Quasi Monte Carlo Technique

Emil J. Pitz, Kishore V. Pochiraju
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. March 2022, 7(1): 011004.
Paper No: VVUQ-21-1025
https://doi.org/10.1115/1.4052895
Published Online: December 14, 2021
View Article titled, Quantifying Uncertainty of Damage in Composites Using a Quasi Monte Carlo Technique
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Topics: Composite materials, Damage, Fracture (Materials), Simulation, Engineering simulation, Uncertainty, Failure
Journal Articles

Experimental and Modeling Uncertainty Considerations for Determining the First Item Ignited in a Compartment Using a Bayesian Method

J. M. Cabrera, R. D. Moser, O. A. Ezekoye
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. March 2022, 7(1): 011002.
Paper No: VVUQ-21-1015
https://doi.org/10.1115/1.4052796
Published Online: November 17, 2021
View Article titled, Experimental and Modeling Uncertainty Considerations for Determining the First Item Ignited in a Compartment Using a Bayesian Method
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Topics: Damage, Fire, Heat flux, Ignition, Risk, Sensors, Uncertainty, Dynamics (Mechanics), Heat
Journal Articles

Grid-Induced Numerical Errors for Shear Stresses and Essential Flow Variables in a Ventricular Assist Device: Crucial for Blood Damage Prediction?

Lucas Konnigk, Benjamin Torner, Sebastian Hallier, Matthias Witte, Frank-Hendrik Wurm
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. December 2018, 3(4): 041002.
Paper No: VVUQ-17-1037
https://doi.org/10.1115/1.4042989
Published Online: April 1, 2019
View Article titled, Grid-Induced Numerical Errors for Shear Stresses and Essential Flow Variables in a Ventricular Assist Device: Crucial for Blood Damage Prediction?
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Topics: Blood, Damage, Errors, Flow (Dynamics), Pumps, Shear stress, Uncertainty, Ventricular assist devices, Simulation, Computational fluid dynamics