| Recent advances in machine learning for fiber optic sensor applications A Venketeswaran, N Lalam, J Wuenschell, PR Ohodnicki Jr, M Badar, ... Advanced Intelligent Systems 4 (1), 2100067, 2022 | 113 | 2022 |
| Investigation of separation force for constrained-surface stereolithography process from mechanics perspective H Ye, A Venketeswaran, S Das, C Zhou Rapid Prototyping Journal 23 (4), 696-710, 2017 | 57 | 2017 |
| A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates P Sasikumar, A Venketeswaran, R Suresh, S Gupta Composite Structures 125, 212-227, 2015 | 42 | 2015 |
| Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser N Lalam, P Lu, A Venketeswaran, MP Buric Sensors 21 (6), 2078, 2021 | 14 | 2021 |
| Fusion of distributed fiber optic sensing, acoustic NDE, and artificial intelligence for infrastructure monitoring PR Ohodnicki, P Zhang, N Lalam, D Karki, A Venketeswaran, H Babaee, ... Optical Fiber Sensors, Tu1. 1, 2022 | 8 | 2022 |
| Feature extraction for pipeline defects inspection based upon distributed acoustic fiber optic sensing data P Zhang, A Venketeswaran, R Wright, K Denslow, H Babaee, ... Fiber Optic Sensors and Applications XVIII 12105, 14-29, 2022 | 8 | 2022 |
| Probabilistic deep neural network based signal processing for Brillouin gain and phase spectrums of vector BOTDA system N Lalam, A Venketeswaran, P Lu, M Buric Optical Interconnects XXI 11692, 169-175, 2021 | 7 | 2021 |
| Effective and efficient characterization of lubrication flow over soft coatings A Venketeswaran, S Das Meccanica 55 (6), 1193-1213, 2020 | 3 | 2020 |
| Computationally effective and efficient methods for interface characterization using cohesive zone model and lubrication theory A Venketeswaran State University of New York at Buffalo, 2019 | 3 | 2019 |
| A multi scale approach for uncertainty quantification of layered composite beams A Venketeswaran, P Sasikumar, S Gupta Int Conf Struct Safety Reliab, CRC Press, Columbia University, NY, 4849-4856, 2013 | 3 | 2013 |
| Raman-assisted BOTDA performance improvement with the differential pulse-width pair technique and an artificial neural network based fitting algorithm N Lalam, P Lu, A Venketeswaran, M Buric, PR Ohodnicki Autonomous Systems: Sensors, Processing, and Security for Vehicles and …, 2020 | 2 | 2020 |
| Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning A Venketeswaran, N Lalam, P Lu, SR Bukka, MP Buric, R Wright Sensors 23 (13), 6064, 2023 | 1 | 2023 |
| Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification P Zhang, A Venketeswaran, RF Wright, N Lalam, E Sarcinelli, ... Sensors 23 (12), 5410, 2023 | 1 | 2023 |
| Enhanced Signal Processing of Distributed Brillouin Fiber Sensors using a Decoupled Radial Basis Function Network A Venketeswaran, N Lalam, P Lu, PR Ohodnicki, KP Chen Optical Fiber Sensors, T3. 51, 2020 | 1 | 2020 |
| Machine learning data analytics based on distributed fiber sensors for pipeline feature detection P Zhang, A Venketeswaran, SR Bukka, E Sarcinelli, N Lalam, RF Wright, ... Optical Waveguide and Laser Sensors II 12532, 49-60, 2023 | | 2023 |
| Feature analysis acoustic signals for fiber-optic-sensing-based NDE for welded structures E Sarcinelli, P Zhang, A Venketeswaran, RM Meyer, R Wright, H Babaee, ... Optical Waveguide and Laser Sensors II 12532, 61-74, 2023 | | 2023 |
| Real-Time Pipe Structure Change Detection and Classification using Distributed Acoustic Fiber Sensors Based on Convolutional Neural Network (CNN) Models P Zhang, A Venketeswaran, RF Wright, N Lalam, E Sarcinelli, ... Preprints, 2023 | | 2023 |
| Integration of Simulated and Real Distributed Acoustic Sensor Measurements to Develop AI Enhanced Intelligent Sensing Operations A Venketeswaran, N Lalam, P Lu, R Wright, M Buric, P Chen National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV …, 2021 | | 2021 |
Nageswara LalamNational Energy Technology LaboratoryVerified email at netl.doe.gov
