The role of machine learning for insight into the material behavior of lattices: A surrogate model based on data from finite element simulation

In-Plane Stiffness and Yield Strength of Periodic Metal Honeycombs

A.-J. Wang, David L. McDowell · Journal of Engineering Materials and Technology · 2004 · 433 citations

Materials Science, Diagonal Compression, Engineering +15

Review on lattice structures for energy absorption properties

Hanfeng Yin, Wenzheng Zhang, Liangcong Zhu et al. · Composite Structures · 2022 · 414 citations

Quantum Lattice System, Physics, Natural Sciences +3

A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability

Irfan Ullah, Kai Liu, Toshiyuki Yamamoto et al. · Energy & Environment · 2021 · 180 citations

Engineering, Machine Learning, Intelligent Energy System +16

Machine learning prediction of biocrude yields and higher heating values from hydrothermal liquefaction of wet biomass and wastes

Tossapon Katongtung, Thossaporn Onsree, Nakorn Tippayawong · Bioresource Technology · 2021 · 140 citations

Liquefaction, Hydrothermal Liquefaction, Biomass Conversion +11

On the out-of-plane ballistic performances of hexagonal, reentrant, square, triangular and circular honeycomb panels

Yuanlong Wang, Yi Yu, Chunyan Wang et al. · International Journal of Mechanical Sciences · 2020 · 104 citations

Engineering, Mechanical Engineering, Circular Honeycomb Panels +2