37 citations · 57 across the 27 of their papers we have counts for
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Physics-Infused Machine Learning Based Prediction of VTOL Aerodynamics with Sparse Datasets
Manaswin Oddiraju, Divyang Amin, Michael Piedmonte +1
Complex optimal design and control processes often require repeated evaluations of expensive objective functions and consist of large design spaces. Data-driven surrogates such as…
Conceptual Design of Cellular Auxetic Systems with Passive Adaptation to Loading
Joshua Prendergast, Manaswin Oddiraju, Mostafa Nouh +1
Auxetics refer to a class of engineered structures which exhibit an overall negative Poisson's ratio. These structures open up various potential opportunities in impact resistance,…
Efficient Training of Transfer Mapping in Physics-Infused Machine Learning Models of UAV Acoustic Field
Rayhaan Iqbal, Amir Behjat, Revant Adlakha +3
Physics-Infused Machine Learning (PIML) architectures aim at integrating machine learning with computationally-efficient, low-fidelity (partial) physics models, leading to improved…
Efficient Inverse Design of 2D Elastic Metamaterial Systems Using Invertible Neural Networks
Manaswin Oddiraju, Amir Behjat, Mostafa Nouh +1
Locally resonant elastic metamaterials (LREM) can be designed, by optimizing the geometry of the constituent self-repeating unit cells, to potentially damp out vibration in selecte…
Metamodel Based Forward and Inverse Design for Passive Vibration Suppression
Amir Behjat, Manaswin Oddiraju, Mohammad Ali Attarzadeh +2
Aperiodic metamaterials represent a class of structural systems that are composed of different building blocks (cells), instead of a self-repeating chain of the same unit cells. Op…