29 citations · 34 across the 8 of their papers we have counts for
8 papers
A multi-objective optimization framework for reducing the impact of ship noise on marine mammals
Akash Venkateshwaran, Indu Kant Deo, Jasmin Jelovica +1
The underwater radiated noise (URN) emanating from ships presents a significant threat to marine mammals, given their heavy reliance on hearing for essential life activities. The i…
Optimizing sandwich panels with graded tubular cell core for enhanced sound transmission loss
Mohammad M. Keleshteri, Jasmin Jelovica
In this research a theoretical approach is proposed to evaluate sound transmission loss (STL) of a sandwich panel with tubular cells core (TCC) in the in-plane orientation. Afterwa…
Stress and frequency optimization of prismatic sandwich beams with joints: Performance improvements through topology optimization
Shengyu Yan, Jasmin Jelovica
Prismatic sandwich panels fabricated from metals offer a compelling alternative to more traditional panels across diverse industries, primarily due to their superior strength-to-we…
Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading
Yuecheng Cai, Jasmin Jelovica
Machine learning (ML) and deep learning (DL) techniques have gained significant attention as reduced order models (ROMs) to computationally expensive structural analysis methods, s…
A parametric level set method with convolutional encoder-decoder network for shape optimization with fluid flow
Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica
In this article, we present a new data-driven shape optimization approach for implicit hydrofoil morphing via a polynomial perturbation of parametric level set representation. With…
Assessment of convolutional recurrent autoencoder network for learning wave propagation
Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica
It is challenging to construct generalized physical models of wave propagation in nature owing to their complex physics as well as widely varying environmental parameters and dynam…
Deep convolutional neural network for shape optimization using level-set approach
Wrik Mallik, Neil Farvolden, Jasmin Jelovica +1
This article presents a reduced-order modeling methodology via deep convolutional neural networks (CNNs) for shape optimization applications. The CNN provides a nonlinear mapping b…
Kinematically consistent recurrent neural networks for learning inverse problems in wave propagation
Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica
Although machine learning (ML) is increasingly employed recently for mechanistic problems, the black-box nature of conventional ML architectures lacks the physical knowledge to inf…