Chetan S. Kulkarni

According to our database, Chetan S. Kulkarni authored at least 15 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Physics-guided recurrent neural network trained with approximate Bayesian computation: A case study on structural response prognostics.

Juan Fernández Salas, Juan Chiachío, José Barros, Manuel Chiachío, Chetan S. Kulkarni

Reliab. Eng. Syst. Saf., March, 2024

Training of physics-informed Bayesian neural networks with ABC-SS for prognostic of Li-ion batteries.

Juan Fernández Salas, Matteo Corbetta, Chetan S. Kulkarni, Juan Chiachío, Manuel Chiachío

Comput. Ind., February, 2024

Data-Driven RUL Prediction Using Performance Metrics (Short Paper).

Abel Díaz-González, Austin Coursey, Marcos Quiñones-Grueiro, Chetan S. Kulkarni, Gautam Biswas

Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

2023

ProgPy: Python Packages for Prognostics and Health Management of Engineering Systems.

Christopher Teubert, Katelyn J. Jarvis, Matteo Corbetta, Chetan S. Kulkarni, Matthew J. Daigle

J. Open Source Softw., 2023

2022

A prescriptive Dirichlet power allocation policy with deep reinforcement learning.

Yuan Tian, Minghao Han, Chetan S. Kulkarni, Olga Fink

Reliab. Eng. Syst. Saf., 2022

Fusing physics-based and deep learning models for prognostics.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

Reliab. Eng. Syst. Saf., 2022

Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction.

Luca Biggio, Tommaso Bendinelli, Chetan S. Kulkarni, Olga Fink

CoRR, 2022

2021

Exploring Architectures for Integrated Resilience Optimization.

Daniel E. Hulse, Arpan Biswas, Christopher Hoyle, Irem Y. Tumer, Chetan S. Kulkarni, Kai Goebel

J. Aerosp. Inf. Syst., October, 2021

Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

Data, 2021

2020

Real-Time Model Calibration with Deep Reinforcement Learning.

Yuan Tian, Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

CoRR, 2020

2019

Battery health management for small-size rotary-wing electric unmanned aerial vehicles: An efficient approach for constrained computing platforms.

Gina Sierra, Marcos E. Orchard, Kai Goebel, Chetan S. Kulkarni

Reliab. Eng. Syst. Saf., 2019

Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

CoRR, 2019

2018

Short-Term Transit Decision Support System Using Multi-task Deep Neural Networks.

Fangzhou Sun, Abhishek Dubey, Chinmaya Samal, Hiba Baroud, Chetan S. Kulkarni

Proceedings of the 2018 IEEE International Conference on Smart Computing, 2018

2015

A testbed for implementing prognostic methodologies on cryogenic propellant loading systems.

Chetan S. Kulkarni, George Gorospe, Matthew J. Daigle, Kai Goebel

IEEE Instrum. Meas. Mag., 2015

2012

Prognostics Health Management and Physics Based Failure Models for Electrolytic Capacitors.

Chetan S. Kulkarni, Jose Celaya, Gautam Biswas, Kai Goebel

Proceedings of the Infotech@Aerospace 2012, 2012