1-20 of 26
Uncertainty quantification
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles

Uncertainty Quantification in Fault and Degradation Analysis of Rolling Element Bearings

Available to Purchase
Accepted Manuscript
David O. Ajayi, Stephen Ekwaro-Osire, Olympio Belli, Nazir Laureano Gandur, Camilo Alberto Lopez-Salazar
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B.
Paper No: RISK-25-1003
https://doi.org/10.1115/1.4068540
Published Online: April 26, 2025
View Articletitled, Uncertainty Quantification in Fault and Degradation Analysis of Rolling Element Bearings
Open the PDF for Uncertainty Quantification in Fault and Degradation Analysis of Rolling Element Bearings in another window
Topics: Risk, Rolling bearings, Uncertainty quantification, Uncertainty, Entropy, Fault diagnosis, Ball bearings, Bearings, Density, Emission spectroscopy
Journal Articles

Balancing Interpretability and Uncertainty in Prognostic Models: A TOPSIS-Based Comparative Analysis of N-CMAPSS DS02 Methods

Free
Declan P. Mallamo, Helene P. Hoang, Michael H. Azarian, Michael G. Pecht
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. June 2025, 11(2): 021106.
Paper No: RISK-24-1094
https://doi.org/10.1115/1.4068151
Published Online: April 7, 2025
View Articletitled, Balancing Interpretability and Uncertainty in Prognostic Models: A TOPSIS-Based Comparative Analysis of N-CMAPSS DS02 Methods
Open the PDF for Balancing Interpretability and Uncertainty in Prognostic Models: A TOPSIS-Based Comparative Analysis of N-CMAPSS DS02 Methods in another window
Topics: Uncertainty, Uncertainty quantification, Physics, Tradeoffs
Journal Articles

Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications

Available to Purchase
Zheng Liu, Yanwen Xu, Yuan Jiang, Anabel Renteria, Parth Bansal, Chenlong Xu, Pingfeng Wang, Yumeng Li
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2025, 11(3): 031204.
Paper No: RISK-24-1031
https://doi.org/10.1115/1.4066933
Published Online: November 22, 2024
View Articletitled, Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications
Open the PDF for Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications in another window
Topics: Absorption, Additive manufacturing, Compression, Design, Simulation, Uncertainty, Uncertainty quantification, Modeling, Manufacturing, Reliability
Journal Articles

A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

Available to Purchase
Lars Bogaerts, Matthias G.R. Faes, David Moens
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2025, 11(3): 031201.
Paper No: RISK-24-1030
https://doi.org/10.1115/1.4066619
Published Online: November 4, 2024
View Articletitled, A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty
Open the PDF for A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty in another window
Topics: Artificial neural networks, Deep learning, Dimensions, Uncertainty, Welding, Pressure, Finite element model, Uncertainty quantification, Algorithms
Journal Articles

Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes

Available to Purchase
Nazir Laureano Gandur, Stephen Ekwaro-Osire
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2025, 11(3): 031202.
Paper No: RISK-24-1052
https://doi.org/10.1115/1.4066722
Published Online: November 4, 2024
View Articletitled, Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes
Open the PDF for Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes in another window
Topics: Batteries, Bearings, Failure, Failure mechanisms, Uncertainty, Service life (Equipment), Uncertainty quantification, Reliability
Journal Articles

Uncertainty Quantification and Sensitivity Analysis for the Self-Excited Vibration of a Spline-Shafting System

Available to Purchase
Xinxing Ma, Yucai Zhong, Peng Cao, Jie Yuan, Zhenguo Zhang
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. December 2023, 9(4): 041104.
Paper No: RISK-23-1030
https://doi.org/10.1115/1.4063069
Published Online: October 3, 2023
View Articletitled, Uncertainty Quantification and Sensitivity Analysis for the Self-Excited Vibration of a Spline-Shafting System
Open the PDF for Uncertainty Quantification and Sensitivity Analysis for the Self-Excited Vibration of a Spline-Shafting System in another window
Topics: Friction, Sensitivity analysis, Splines, Uncertainty, Vibration, Rotors, Uncertainty quantification, Polynomials, Torque, Displacement
Journal Articles

Special Section on Uncertainty Quantification and Management in Nonlinear Dynamical Systems in Aerospace and Mechanical Engineering

Free
Jie Yuan, Enora Denimal, Sifeng Bi, Jinglang Feng, Quan Hu, Alice Cicirello
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Guest Editorial
ASME J. Risk Uncertainty Part B. December 2023, 9(4): 040301.
Paper No: RISK-23-1072
https://doi.org/10.1115/1.4063301
Published Online: September 28, 2023
View Articletitled, Special Section on Uncertainty Quantification and Management in Nonlinear Dynamical Systems in Aerospace and Mechanical Engineering
Open the PDF for Special Section on Uncertainty Quantification and Management in Nonlinear Dynamical Systems in Aerospace and Mechanical Engineering in another window
Topics: Aerospace industry, Mechanical engineering, Nonlinear dynamical systems, Uncertainty, Uncertainty quantification
Journal Articles

Network Uncertainty Quantification for Analysis of Multi-Component Systems

Free
John Tencer, Edward Rojas, Benjamin B. Schroeder
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. June 2023, 9(2): 021203.
Paper No: RISK-22-1022
https://doi.org/10.1115/1.4055688
Published Online: October 26, 2022
View Articletitled, Network Uncertainty Quantification for Analysis of Multi-Component Systems
Open the PDF for Network Uncertainty Quantification for Analysis of Multi-Component Systems in another window
Topics: Boundary-value problems, Temperature, Uncertainty, Uncertainty quantification, Transients (Dynamics), Bombs, Simulation, Steady state
Journal Articles

Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances

Available to Purchase
Sankaran Mahadevan, Paromita Nath, Zhen Hu
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Review Articles
ASME J. Risk Uncertainty Part B. March 2022, 8(1): 010801.
Paper No: RISK-21-1065
https://doi.org/10.1115/1.4053184
Published Online: January 6, 2022
View Articletitled, Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances
Open the PDF for Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances in another window
Topics: Additive manufacturing, Calibration, Optimization, Physics, Uncertainty, Uncertainty quantification, Errors, Lasers, Manufacturing
Journal Articles

Special Issue on Uncertainty Quantification and Management in Additive Manufacturing

Free
Zhen Hu, Saideep Nannapaneni, Sankaran Mahadevan
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Guest Editorial
ASME J. Risk Uncertainty Part B. March 2022, 8(1): 010301.
Paper No: RISK-21-1089
https://doi.org/10.1115/1.4053183
Published Online: December 27, 2021
View Articletitled, Special Issue on Uncertainty Quantification and Management in Additive Manufacturing
Open the PDF for Special Issue on Uncertainty Quantification and Management in Additive Manufacturing in another window
Topics: Additive manufacturing, Uncertainty quantification, Uncertainty
Journal Articles

Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach

Free
Jiahui Ye, Mohamad Mahmoudi, Kubra Karayagiz, Luke Johnson, Raiyan Seede, Ibrahim Karaman, Raymundo Arroyave, Alaa Elwany
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. March 2022, 8(1): 011111.
Paper No: RISK-21-1012
https://doi.org/10.1115/1.4052270
Published Online: October 14, 2021
View Articletitled, Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach
Open the PDF for Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach in another window
Topics: Calibration, Simulation models, Alloys, Metals, Additive manufacturing, Uncertainty quantification, Lasers
Journal Articles

Application of Deep Transfer Learning and Uncertainty Quantification for Process Identification in Powder Bed Fusion

Available to Purchase
Piyush Pandita, Sayan Ghosh, Vipul K. Gupta, Andrey Meshkov, Liping Wang
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. March 2022, 8(1): 011106.
Paper No: RISK-21-1010
https://doi.org/10.1115/1.4051748
Published Online: August 9, 2021
View Articletitled, Application of Deep Transfer Learning and Uncertainty Quantification for Process Identification in Powder Bed Fusion
Open the PDF for Application of Deep Transfer Learning and Uncertainty Quantification for Process Identification in Powder Bed Fusion in another window
Topics: Additive manufacturing, Design, Modeling, Simulation, Uncertainty quantification, Lasers, Computers, Physics
Journal Articles

Uncertainty Quantification Analysis on Silicon Electrodeposition Process Via Numerical Simulation Methods

Free
Zhuoyuan Zheng, Pingfeng Wang
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. March 2022, 8(1): 011105.
Paper No: RISK-20-1111
https://doi.org/10.1115/1.4051700
Published Online: August 6, 2021
View Articletitled, Uncertainty Quantification Analysis on Silicon Electrodeposition Process Via Numerical Simulation Methods
Open the PDF for Uncertainty Quantification Analysis on Silicon Electrodeposition Process Via Numerical Simulation Methods in another window
Topics: Electrodeposition, Electrodes, Electrolytes, Finite element model, Silicon, Uncertainty quantification, Temperature, Anodes, Design, Simulation results
Journal Articles

Uncertainty Quantification for Fatigue Life of Offshore Wind Turbine Structure

Available to Purchase
Abraham Nispel, Stephen Ekwaro-Osire, João Paulo Dias, Americo Cunha, Jr.
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. December 2021, 7(4): 040901.
Paper No: RISK-20-1099
https://doi.org/10.1115/1.4051162
Published Online: July 12, 2021
View Articletitled, Uncertainty Quantification for Fatigue Life of Offshore Wind Turbine Structure
Open the PDF for Uncertainty Quantification for Fatigue Life of Offshore Wind Turbine Structure in another window
Topics: Fatigue life, Offshore wind turbines, Reliability, Uncertainty, Uncertainty quantification, Modeling, Sensitivity analysis, Fatigue, Probability, Physics
Journal Articles

Quantifying Uncertainty in the Residence Time of the Drug and Carrier Particles in a Dry Powder Inhaler

Available to Purchase
Antara Badhan, V. M. Krushnarao Kotteda, Samia Afrin, Vinod Kumar
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2021, 7(3): 031004.
Paper No: RISK-20-1107
https://doi.org/10.1115/1.4050250
Published Online: May 28, 2021
View Articletitled, Quantifying Uncertainty in the Residence Time of the Drug and Carrier Particles in a Dry Powder Inhaler
Open the PDF for Quantifying Uncertainty in the Residence Time of the Drug and Carrier Particles in a Dry Powder Inhaler in another window
Topics: Drugs, Particulate matter, Density, Uncertainty quantification, Flow (Dynamics)
Journal Articles

A Hyper-Ellipsoid Approach for Inverse Lack-of-Knowledge Uncertainty Quantification

Available to Purchase
Norbert Ludwig, Fabian Duddeck, Marco Daub
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. June 2021, 7(2): 020911.
Paper No: RISK-20-1085
https://doi.org/10.1115/1.4050162
Published Online: April 23, 2021
View Articletitled, A Hyper-Ellipsoid Approach for Inverse Lack-of-Knowledge Uncertainty Quantification
Open the PDF for A Hyper-Ellipsoid Approach for Inverse Lack-of-Knowledge Uncertainty Quantification in another window
Topics: Computation, Hull, Jet engines, Uncertainty, Uncertainty quantification, Optimization, Inverse problems
Journal Articles

Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating

Available to Purchase
Sifeng Bi, Michael Beer, Jingrui Zhang, Lechang Yang, Kui He
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. June 2021, 7(2): 020903.
Paper No: RISK-20-1070
https://doi.org/10.1115/1.4050168
Published Online: April 23, 2021
View Articletitled, Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating
Open the PDF for Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating in another window
Topics: Algorithms, Optimization, Uncertainty, Uncertainty quantification, Chain
Journal Articles

Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis

Free
Matthias G. R. Faes, David Moens, Michael Beer, Hao Zhang, Kok-Kwang Phoon
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Guest Editorial
ASME J. Risk Uncertainty Part B. June 2021, 7(2): 020301.
Paper No: RISK-21-1013
https://doi.org/10.1115/1.4050256
Published Online: March 19, 2021
View Articletitled, Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis
Open the PDF for Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis in another window
Topics: Event history analysis, Uncertainty quantification, Uncertainty
Journal Articles

Measurement Errors and Uncertainty Quantification of a Two-Dimensional-Particle Image Velocimetry Experimental Setup for Jet Flow Characterization

Available to Purchase
Flávia V. Barbosa, Carlos A. P. Costa, Senhorinha F. C. F. Teixeira, José C. F. Teixeira
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. December 2020, 6(4): 041007.
Paper No: RISK-20-1025
https://doi.org/10.1115/1.4047649
Published Online: July 17, 2020
View Articletitled, Measurement Errors and Uncertainty Quantification of a Two-Dimensional-Particle Image Velocimetry Experimental Setup for Jet Flow Characterization
Open the PDF for Measurement Errors and Uncertainty Quantification of a Two-Dimensional-Particle Image Velocimetry Experimental Setup for Jet Flow Characterization in another window
Topics: Errors, Flow (Dynamics), Particulate matter, Uncertainty, Reynolds number, Uncertainty quantification, Nozzles, Jets, Calibration
Journal Articles

Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications

Available to Purchase
D. J. Wagg, K. Worden, R. J. Barthorpe, P. Gardner
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2020, 6(3): 030901.
Paper No: RISK-19-1039
https://doi.org/10.1115/1.4046739
Published Online: May 12, 2020
View Articletitled, Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications
Open the PDF for Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications in another window
Topics: Dynamics (Mechanics), Modeling, Simulation, Workflow, Uncertainty, Physics, Uncertainty quantification, Design