41 citations · 45 across the 5 of their papers we have counts for
5 papers
Waveformer for modelling dynamical systems
N Navaneeth, Souvik Chakraborty
Neural operators have gained recognition as potent tools for learning solutions of a family of partial differential equations. The state-of-the-art neural operators excel at approx…
Enhanced multi-fidelity modelling for digital twin and uncertainty quantification
AS Desai, Navaneeth N, S Adhikari +1
The increasing significance of digital twin technology across engineering and industrial domains, such as aerospace, infrastructure, and automotive, is undeniable. However, the lac…
Physics informed WNO
Navaneeth N, Tapas Tripura, Souvik Chakraborty
Deep neural operators are recognized as an effective tool for learning solution operators of complex partial differential equations (PDEs). As compared to laborious analytical and…
Koopman operator for time-dependent reliability analysis
Navaneeth N., Souvik Chakraborty
Time-dependent structural reliability analysis of nonlinear dynamical systems is non-trivial; subsequently, scope of most of the structural reliability analysis methods is limited…
Surrogate assisted active subspace and active subspace assisted surrogate -- A new paradigm for high dimensional structural reliability analysis
Navaneeth N., Souvik Chakraborty
Performing reliability analysis on complex systems is often computationally expensive. In particular, when dealing with systems having high input dimensionality, reliability estima…