A review of machine learning methods applied to structural dynamics and vibroacoustic

BZ Cunha, C Droz, AM Zine, S Foulard… - Mechanical Systems and …, 2023 - Elsevier
Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …

Research on the sound insulation performance of composite rubber reinforced with hollow glass microsphere based on acoustic finite element simulation

X Yang, S Tang, X Shen, W Peng - Polymers, 2023 - mdpi.com
The composite rubber reinforced with hollow glass microsphere (HGM) was a promising
composite material for noise reduction, and its sound insulation mechanism was studied …

A parametric physics-informed deep learning method for probabilistic design of thermal protection systems

R Zhang, N Xu, K Zhang, L Wang, G Lu - Energies, 2023 - mdpi.com
Precise and efficient calculations are necessary to accurately assess the effects of thermal
protection system (TPS) uncertainties on aerospacecrafts. This paper presents a …

Interpretable and physics-supported machine learning model for sound transmission loss analysis

BZ Cunha, M Ichchou, C Droz, A Zine… - ISMA 2022-International …, 2022 - hal.science
Lately, there has been a growing interest in applying Machine Learning and Digital Twins for
the speed-up of acoustic simulations. However, the lack of interpretability and physics …

An Automation Innovation of Gearbox Vehicle Control by Using Machine Learning Based Robotic Operation

MM Ramakrishna, NR Atyam… - 2023 International …, 2023 - ieeexplore.ieee.org
There are many vehicle exchanges around the world are using the manual transmission and
automatic transmission are the most popular. At this time, many popular manufacturers have …

[CITATA][C] Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction

HK Sreekumar - 2024 - … Universität Braunschweig, 2024