Nelder–Mead Optimization of Elastic Metamaterials via Machine-Learning-Aided Surrogate Modeling

Analysis of wave band gaps in mechanical metamaterial based on Nelder–Mead method

(2019) Jiaqi Dong et al.   ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

(2018) Liang Liang et al.   Journal of the Royal Society Interface

Error modeling for surrogates of dynamical systems using machine learning

(2017) Sumeet Trehan et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Solving the quantum many-body problem with artificial neural networks

(2017) Giuseppe Carleo et al.   SCIENCE

On the mechanism of bandgap formation in locally resonant finite elastic metamaterials

(2016) Christopher Sugino et al.   JOURNAL OF APPLIED PHYSICS

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Multi-flexural band gaps in an Euler–Bernoulli beam with lateral local resonators

(2016) Ting Wang et al.   PHYSICS LETTERS A

A chiral elastic metamaterial beam for broadband vibration suppression

(2014) R. Zhu et al.   JOURNAL OF SOUND AND VIBRATION

On three-dimensional dilational elastic metamaterials

(2014) Tiemo Bückmann et al.   NEW JOURNAL OF PHYSICS

Hybrid elastic solids

(2011) Yun Lai et al.   NATURE MATERIALS

Implementing the Nelder-Mead simplex algorithm with adaptive parameters

(2010) Fuchang Gao et al.   COMPUTATIONAL OPTIMIZATION AND APPLICATIONS

Two-dimensional phononic crystals: Examples and applications

(2010) Yan Pennec et al.   SURFACE SCIENCE REPORTS

Phononic properties of hexagonal chiral lattices

(2009) Alessandro Spadoni et al.   WAVE MOTION