activity
20082022
most citedBridging Proper Orthogonal Decomposition methods and augmented Newton-Krylov algorithms: an adaptive model order reduction for highly nonlinear mechanical problems

165 citations · 208 across the 11 of their papers we have counts for

collaborators

11 papers

stat.ML2022★ 3 cited

Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems

Tapas Tripura, Aarya Sheetal Desai, Sondipon Adhikari +1

A framework for creating and updating digital twins for dynamical systems from a library of physics-based functions is proposed. The sparse Bayesian machine learning is used to upd…

physics.app-ph2021

Metadamping in inertially amplified metamaterials: Trade-off between spatial attenuation and temporal attenuation

Mahmoud I. Hussein, Ibrahim Patrick, Arnab Banerjee +1

Metadamping is the phenomenon of either enhanced or diminished intrinsic dissipation in a material stemming from the material's internal structural dynamics. It has been previously…

cs.CR2020

Analysis of IoT-Based Load Altering Attacks Against Power Grids Using the Theory of Second-Order Dynamical Systems

Subhash Lakshminarayana, Sondipon Adhikari, Carsten Maple

Recent research has shown that large-scale Internet of Things (IoT)-based load altering attacks can have a serious impact on power grid operations such as causing unsafe frequency…

stat.ML2020★ 1 cited

Machine learning based digital twin for dynamical systems with multiple time-scales

Souvik Chakraborty, Sondipon Adhikari

Digital twin technology has a huge potential for widespread applications in different industrial sectors such as infrastructure, aerospace, and automotive. However, practical adopt…

stat.ML2020

The role of surrogate models in the development of digital twins of dynamic systems

Souvik Chakraborty, Sondipon Adhikari, Ranjan Ganguli

Digital twin technology has significant promise, relevance and potential of widespread applicability in various industrial sectors such as aerospace, infrastructure and automotive.…

cs.AI2017

Fuzzy finite element model updating using metaheuristic optimization algorithms

I. Boulkaibet, T. Marwala, M. I. Friswell +2

In this paper, a non-probabilistic method based on fuzzy logic is used to update finite element models (FEMs). Model updating techniques use the measured data to improve the accura…