Machine learning and deep learning in phononic crystals and metamaterials–A review

J Kennedy, CW Lim - Materials Today Communications, 2022 - Elsevier
Abstract Machine learning (ML), as a component of artificial intelligence, encourages
structural design exploration which leads to new technological advancements. By …

The boundary element method in acoustics: A survey

S Kirkup - Applied Sciences, 2019 - mdpi.com
The boundary element method (BEM) in the context of acoustics or Helmholtz problems is
reviewed in this paper. The basis of the BEM is initially developed for Laplace's equation …

DNoiseNet: Deep learning-based feedback active noise control in various noisy environments

YJ Cha, A Mostafavi, SS Benipal - Engineering Applications of Artificial …, 2023 - Elsevier
The use of active noise control/cancelation (ANC) has increased because of the availability
of efficient circuits and computational power. However, most ANC systems are based on …

Multi-frequency acoustic topology optimization of sound-absorption materials with isogeometric boundary element methods accelerated by frequency-decoupling and …

LL Chen, H Lian, S Natarajan, W Zhao, XY Chen… - Computer Methods in …, 2022 - Elsevier
The paper presents a novel approach for multi-frequency acoustic topology optimization of
sound-absorption materials. In this work, the isogeometric boundary element method based …

A BEM broadband topology optimization strategy based on Taylor expansion and SOAR method—Application to 2D acoustic scattering problems

L Chen, J Zhao, H Lian, B Yu… - … Journal for Numerical …, 2023 - Wiley Online Library
In this article, an innovative method is proposed for broadband topology optimization of
sound‐absorbing materials adhering to the surface of a sound barrier structure. Helmholtz …

A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic–vibration interaction problems

L Chen, R Cheng, S Li, H Lian, C Zheng… - Computer Methods in …, 2022 - Elsevier
We propose an efficient Monte Carlo simulation method to address the multivariate
uncertainties in acoustic–vibration interaction systems. The deep neural network acts as a …

Acoustic topology optimization of sound absorbing materials directly from subdivision surfaces with isogeometric boundary element methods

L Chen, C Lu, H Lian, Z Liu, W Zhao, S Li… - Computer Methods in …, 2020 - Elsevier
This paper presents an acoustic topology optimization approach using isogeometric
boundary element methods based on subdivision surfaces to optimize the distribution of …

A review of finite-element methods for time-harmonic acoustics

LL Thompson - The Journal of the Acoustical Society of America, 2006 - pubs.aip.org
State-of-the-art finite-element methods for time-harmonic acoustics governed by the
Helmholtz equation are reviewed. Four major current challenges in the field are specifically …

Bi-material topology optimization for fully coupled structural-acoustic systems with isogeometric FEM–BEM

LL Chen, H Lian, Z Liu, Y Gong, CJ Zheng… - … Analysis with Boundary …, 2022 - Elsevier
This paper presents a novel method for topology optimization of vibrating structures
interacted with acoustic wave for the purpose of minimizing radiated sound power level. We …

[HTML][HTML] A review of sensory interactions between autonomous vehicles and drivers

J Lu, Z Peng, S Yang, Y Ma, R Wang, Z Pang… - Journal of Systems …, 2023 - Elsevier
Nowadays, human-oriented has already become the direction of the development of the
intelligent vehicle, among which, the cabin, in constant contact with drivers, is getting more …