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Leifur Leifsson
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Proceedings Papers

High-Dimensional Variance-Based Adaptive Sampling for Prediction of Aerodynamic Flows Using Non-Intrusive Reduced Order Models

Abhijnan Dikshit, Leifur Leifsson
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A036, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-140650
https://doi.org/10.1115/DETC2024-140650
View Paper titled, High-Dimensional Variance-Based Adaptive Sampling for Prediction of Aerodynamic Flows Using Non-Intrusive Reduced Order Models
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Topics: Aerodynamic flow, Modeling, Uncertainty, Errors, Aerodynamics, Algorithms, Construction, Engineering simulation, Pressure, Shock waves
Journal Articles

Global Sensitivity Analysis of Ultrasonic Testing Simulations of Slot-Like Defects With Multifidelity Modeling

Yen-Chen Liu, Roberto Miorelli, Leifur Leifsson, Christophe Reboud, Pierre Calmon
Journal: Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
Publisher: ASME
Article Type: Research Papers
ASME J Nondestructive Evaluation. February 2025, 8(1): 011002.
Paper No: NDE-23-1021
https://doi.org/10.1115/1.4065766
Published Online: July 26, 2024
View Articletitled, Global Sensitivity Analysis of Ultrasonic Testing Simulations of Slot-Like Defects With Multifidelity Modeling
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Topics: Metamodeling, Modeling, Sensitivity analysis, Simulation, Testing, Ultrasonic testing, Physics, Uncertainty
Proceedings Papers

Efficient Airfoil Geometric Uncertainty Quantification Using Neural Network Models and Sequential Sampling

Pavankumar Koratikere, Leifur Leifsson
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A046, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-114954
https://doi.org/10.1115/DETC2023-114954
View Paper titled, Efficient Airfoil Geometric Uncertainty Quantification Using Neural Network Models and Sequential Sampling
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Topics: Airfoils, Neural network models, Uncertainty quantification, Algorithms, Computational fluid dynamics, Uncertainty, Drag (Fluid dynamics), Engineering simulation, Optimization, Simulation
Proceedings Papers

Gradient-Enhanced Multifidelity Neural Networks for High-Dimensional Function Approximation

Jethro Nagawkar, Leifur Leifsson
Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A040, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-70502
https://doi.org/10.1115/DETC2021-70502
View Paper titled, Gradient-Enhanced Multifidelity Neural Networks for High-Dimensional Function Approximation
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Topics: Artificial neural networks, Function approximation, Algorithms, Construction, Machine learning
Journal Articles

Efficient Global Sensitivity Analysis of Model-Based Ultrasonic Nondestructive Testing Systems Using Machine Learning and Sobol’ Indices

Jethro Nagawkar, Leifur Leifsson
Journal: Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
Publisher: ASME
Article Type: Research Papers
ASME J Nondestructive Evaluation. November 2021, 4(4): 041008.
Paper No: NDE-20-1063
https://doi.org/10.1115/1.4051100
Published Online: June 7, 2021
View Articletitled, Efficient Global Sensitivity Analysis of Model-Based Ultrasonic Nondestructive Testing Systems Using Machine Learning and Sobol’ Indices
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Topics: Algorithms, Artificial neural networks, Machine learning, Nondestructive evaluation, Sensitivity analysis, Physics, Testing
Proceedings Papers

Applications of Polynomial Chaos-Based Cokriging to Simulation-Based Analysis and Design Under Uncertainty

Jethro Nagawkar, Leifur Leifsson
Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A046, August 17–19, 2020
Publisher: American Society of Mechanical Engineers
Paper No: DETC2020-22369
https://doi.org/10.1115/DETC2020-22369
View Paper titled, Applications of Polynomial Chaos-Based Cokriging to Simulation-Based Analysis and Design Under Uncertainty
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Topics: Chaos, Design under uncertainty, Polynomials, Simulation, Design, Drag (Fluid dynamics), Airfoils, Construction, Optimization, Sensitivity analysis
Journal Articles

Efficient Model-Assisted Probability of Detection and Sensitivity Analysis for Ultrasonic Testing Simulations Using Stochastic Metamodeling

Xiaosong Du, Leifur Leifsson, William Meeker, Praveen Gurrala, Jiming Song, Ronald Roberts
Journal: Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
Publisher: ASME
Article Type: Research Papers
ASME J Nondestructive Evaluation. November 2019, 2(4): 041002.
Paper No: NDE-19-1004
https://doi.org/10.1115/1.4044446
Published Online: September 23, 2019
View Articletitled, Efficient Model-Assisted Probability of Detection and Sensitivity Analysis for Ultrasonic Testing Simulations Using Stochastic Metamodeling
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Topics: Chaos, Physics, Polynomials, Probability, Sensitivity analysis, Ultrasonic testing, Nondestructive evaluation, Simulation, Interpolation, Inspection