| Assessment of unsteady flow predictions using hybrid deep learning based reduced-order models SR Bukka, R Gupta, AR Magee, RK Jaiman Physics of Fluids 33 (1), 2021 | 100 | 2021 |
| Reduced Order Model for Unsteady Fluid Flows via Recurrent Neural Networks SB Reddy, AR Magee, RK Jaiman, J Liu, W Xu, A Choudhary, AA Hussain ASME 2019 38th International Conference on Ocean, Offshore and Arctic …, 2019 | 39 | 2019 |
| Stability analysis of passive suppression for vortex-induced vibration SR Bukka, AR Magee, RK Jaiman Journal of Fluid Mechanics 886, A12, 2020 | 32 | 2020 |
| Deep convolutional recurrent autoencoders for flow field prediction SR Bukka, AR Magee, RK Jaiman International conference on offshore mechanics and arctic engineering 84409 …, 2020 | 24 | 2020 |
| A data-driven approach for the stability analysis of vortex-induced vibration SB Reddy, AR Magee, RK Jaiman International Conference on Offshore Mechanics and Arctic Engineering 51210 …, 2018 | 8 | 2018 |
| Reduced order model for nonlinear multi-directional ocean wave propagation SR Bukka, YZ Law, H Santo, ES Chan Physics of Fluids 33 (11), 2021 | 7 | 2021 |
| Data-driven computing for the stability analysis and prediction of fluid-structure interaction SR Bukka PQDT-Global, 2019 | 6 | 2019 |
| Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks N Lalam, S Bukka, H Bhatta, M Buric, P Ohodnicki, R Wright Communications Engineering 3 (1), 121, 2024 | 2 | 2024 |
| 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 | 2 | 2023 |
| 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 | 2 | 2023 |
| Assessment of hybrid data-driven models to predict unsteady flows R Gupta, SR Bukka, R Jaiman APS division of fluid dynamics meeting abstracts, K09. 017, 2020 | 1 | 2020 |
| Advanced Distributed Optical Fiber Sensor Systems for Pipeline Integrity Monitoring N Lalam, M Brister, HD Bhatta, SR Bukka, AF Mitul, M Buric, R Wright National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV …, 2024 | | 2024 |
| Reduced Order Model for Guided Wave Propagation on Gas Pipelines to Enable Real-Time Simulation SR Bukka, N Lalam, P Zhang, R Wright, P Ohodnicki National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV …, 2024 | | 2024 |
| Investigation of data augmentation techniques for ultrasonic acoustic fiber sensing signals in guided wave-based pipeline damage detection P Zhang, K Naeem, E Sarcinelli, A Venketeswaran, SR Bukka, N Lalam, ... Optical Waveguide and Laser Sensors III 13044, 79-95, 2024 | | 2024 |
| Multi-parameter optical fiber sensing of humidity, CH4, CO2, and corrosion B Mainali, A Shumski, S Bukka, N Diemler, R Wright Optical Waveguide and Laser Sensors III 13044, 123-140, 2024 | | 2024 |
| Lab scale demonstration of pipeline third-party damage classification using convolutional neural networks SR Bukka, N Lalam, H Bhatta, R Wright Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII …, 2024 | | 2024 |
| Variation of Current Drag on Flotel in Side-By-Side Configuration with FPSO A Yenduri, SR Bukka, AR Magee, J Liu, AA Hussain Offshore Technology Conference Asia, D021S013R003, 2020 | | 2020 |
| Nonlinear Dynamics of Multi-Segment Mooring Systems SB Reddy, AR Magee, W Bai International Conference on Offshore Mechanics and Arctic Engineering 57632 …, 2017 | | 2017 |
| Enhancing Machine Learning Models for Guided Wave-Based Pipeline Monitoring: Integrating Experimental Noise Characteristics into Simulation Data for Improved Reliability and … P Zhang, K Naeem, E Sarcinelli, A Venketeswaran, SR Bukka, N Lalam, ... Available at SSRN 5129217, 0 | | |
Allan Ross MageeProfessor (Practice) Civil and Environmental Engineering, National University of SingaporeE-mailová adresa ověřena na: nus.edu.sg
