Bivas Bhaumik

Orcid: 0000-0002-3168-2687

According to our database1, Bivas Bhaumik authored at least 10 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Mathematical and neural network analysis of peristaltic flow of a second-grade fractional hybrid nanofluid with variable viscosity in bifurcated arteries.
Math. Comput. Simul., 2026

Modeling and prediction of Carreau fluid flow with generalized thermal conductivity using hybrid artificial neural network and symbolic regression.
Eng. Appl. Artif. Intell., 2026

A refined physics-informed neural network framework for solving nonlinear partial differential equations and extracting analytical expressions via symbolic regression.
Comput. Math. Appl., 2026

Peristaltic transport of non-Newtonian hybrid nanofluid flow through an inclined porous tube under a magnetic field and thermal radiation in a fuzzy environment.
Comput. Math. Appl., 2026

2025
Gradient Enhanced Self-Training Physics-Informed Neural Network (gST-PINN) for Solving Nonlinear Partial Differential Equations.
CoRR, October, 2025

Physics-informed neural network with symbolic regression for deriving analytical approximate solutions to nonlinear partial differential equations.
Neural Comput. Appl., August, 2025

Thermal analysis of nanolayer interfaces and nanoparticle shape reactivity in EMHD micromagnetorotational ternary nanofluid flow within deceased bifurcated artery.
Math. Comput. Simul., 2025

2024
Deep learning based solution of nonlinear partial differential equations arising in the process of arterial blood flow.
Math. Comput. Simul., March, 2024

Nanoparticle aggregation and electro-osmotic propulsion in peristaltic transport of third-grade nanofluids through porous tube.
Comput. Biol. Medicine, 2024

2021
Physics-based smart model for prediction of viscosity of nanofluids containing nanoparticles using deep learning.
J. Comput. Des. Eng., 2021


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