1-3 of 3
Anabel Renteria
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 of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications

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 Article titled, 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
Proceedings Papers

Sensor Network Design for Permanent Magnet Synchronous Motor Fault Diagnosis

Sara Kohtz, Junhan Zhao, Anabel Renteria, Anand Vikas Lalwani, Xiaolong Zhang, Kiruba Sivasubramaniam Haran, Debbie Senesky, Pingfeng Wang
Proc. ASME. IDETC-CIE2023, Volume 3A: 49th Design Automation Conference (DAC), V03AT03A050, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116972
https://doi.org/10.1115/DETC2023-116972
View Paper titled, Sensor Network Design for Permanent Magnet Synchronous Motor Fault Diagnosis
Open the PDF for Sensor Network Design for Permanent Magnet Synchronous Motor Fault Diagnosis in another window
Topics: Design, Engines, Fault diagnosis, Flaw detection, Genetic algorithms, Motors, Permanent magnets, Sensor networks, Sensor placement
Proceedings Papers

Data-Driven Design of High Electron Mobility Transistor Devices Using Physics-Informed Gaussian Process Modeling

Anabel Renteria, Yanwen Xu, Bayan Hamdan, Zhou Li, Sergio Cordero, Debbie G. Senesky, Pingfeng Wang
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A014, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-117200
https://doi.org/10.1115/DETC2023-117200
View Paper titled, Data-Driven Design of High Electron Mobility Transistor Devices Using Physics-Informed Gaussian Process Modeling
Open the PDF for Data-Driven Design of High Electron Mobility Transistor Devices Using Physics-Informed Gaussian Process Modeling in another window
Topics: Data-driven design, Design, High-electron-mobility transistors, Modeling, Optimization, Physics, Simulation