publications

2024

1. 

   Reinforcement Learning Based Persistent Surveillance on Graphs Under Energy Constraints

   Nishchal Hoysal G, Aravind S, Lalit Jayanti, and 1 more author

   In 2024 Tenth Indian Control Conference (ICC), 2024

   DOI Bib

   @inproceedings{10883706,
     author = {G, Nishchal Hoysal and S, Aravind and Jayanti, Lalit and Tallapragada, Pavankumar},
     booktitle = {2024 Tenth Indian Control Conference (ICC)},
     title = {Reinforcement Learning Based Persistent Surveillance on Graphs Under Energy Constraints},
     year = {2024},
     volume = {},
     number = {},
     pages = {532-537},
     keywords = {Learning systems;Integer programming;Q-learning;Surveillance;Computational modeling;Closed box;Routing;Entropy;IP networks;Optimization},
     doi = {10.1109/ICC64753.2024.10883706}
   }

2. Linear complementarity formulations for contact analysis and wear prediction in gears

   Mangesh Pathak, Lalit Jayanti, and Sourav Rakshit

   Mechanism and Machine Theory, 2024

   Abs DOI Bib

   This work presents linear complementarity based formulations for contact analysis and wear prediction in gear trains. Assuming steady motion of gears transmitting constant input torque without transmission errors, three sets of linear complementarity formulations are proposed, first for rigid gear teeth, second for gear teeth with skin compliance, and third for gear teeth with full compliance, the last two being new in linear complementarity literature. The developed formulations are used for contact analysis of two examples of gear trains, a pair of spur gears in mesh, and a planetary gear train. The accuracy of the method is tested by considering various time step sizes and stability of the formulations demonstrated for wide range of time steps. Contact forces between meshing teeth are calculated at a pre-defined set of points on the path of contact, and then wear is calculated on gear tooth flank using Archard’s wear equation. These wear calculations are compared with existing results in literature which demonstrate the applicability of the developed LC formulations. Future work is projected to include more state-of-art friction models and extension to 3D contact analysis in helical gear trains.

   @article{PATHAK2024105669,
     title = {Linear complementarity formulations for contact analysis and wear prediction in gears},
     journal = {Mechanism and Machine Theory},
     volume = {198},
     pages = {105669},
     year = {2024},
     issn = {0094-114X},
     doi = {https://doi.org/10.1016/j.mechmachtheory.2024.105669},
     url = {https://www.sciencedirect.com/science/article/pii/S0094114X2400096X},
     author = {Pathak, Mangesh and Jayanti, Lalit and Rakshit, Sourav},
     keywords = {Archard’s equation, Coulomb friction, Rigid body, Skin compliance, Tooth compliance}
   }