[HTML][HTML] A comprehensive review of lunar-based manufacturing and construction

M Azami, Z Kazemi, S Moazen, M Dubé… - Progress in Aerospace …, 2024 - Elsevier
As humankind prepares to establish outposts and infrastructure on the Moon, the ability to
manufacture parts and buildings on-site is crucial. While transporting raw materials from …

[HTML][HTML] Machine learning applications on lunar meteorite minerals: From classification to mechanical properties prediction

E Peña-Asensio, JM Trigo-Rodríguez, J Sort… - International Journal of …, 2024 - Elsevier
Amid the scarcity of lunar meteorites and the imperative to preserve their scientific value,
non-destructive testing methods are essential. This translates into the application of …

Global mapping of fragmented rocks on the Moon with a neural network: Implications for the failure mode of rocks on airless surfaces

O Rüsch, VT Bickel - The Planetary Science Journal, 2023 - iopscience.iop.org
Failure modes of lunar boulders depend both on rheology and the erosion agents acting in
the lunar surface environment. Here, we address the failure modes of lunar boulders and …

Cone penetration test prediction based on random forest models and deep neural networks

VL Pacheco, L Bragagnolo, F Dalla Rosa… - Geotechnical and …, 2023 - Springer
The cone penetration test (CPT) is widely used in soil characterization and the determination
of physical parameters. The traditional interpretation of the results of CPTs relies on the …

Identification study of soil types based on feature factors of XRF spectrum combining with machine learning

Y Wang, T Gan, N Zhao, G Yin, Z Ye, R Sheng… - … Acta Part B: Atomic …, 2024 - Elsevier
Soil type significantly influences the detection accuracy of heavy metals using X-ray
fluorescence (XRF) technology. Rapid and accurate soil type identification is crucial for …

A laboratory open-set Martian rock classification method based on spectral signatures

J Yang, Z Kang, Z Yang, J Xie, B Xue… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Rocks are one of the major surface features of Mars. The accurate characterization of the
chemical and mineralogical composition of Martian rocks would yield significant …

Extracting mare-like cryptomare deposits in cryptomare regions based on CE-2 MRM data using SVM method

T Tang, Z Meng, Y Lian, Z Wei, X Dong, Y Wang… - Remote Sensing, 2023 - mdpi.com
A new kind of surface material is found and defined in the Balmer–Kapteyn (BK) cryptomare
region, Mare-like cryptomare deposits (MCD), representing highland debris mixed by mare …

Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review

VL Pacheco, L Bragagnolo, A Thomé - Engineering Computations, 2021 - emerald.com
Purpose The purpose of this article is to analyze the state-of-the art in a systematic way,
identifying the main research groups and their related topics. The types of studies found are …

High-resolution mapping of soil carbon stocks in the western Amazon

CM Moquedace, CGO Baldi, RG Siqueira… - Geoderma …, 2024 - Elsevier
Global soil carbon maps are essential to understanding the global carbon cycle and
supporting policy decisions, but their uncertainty in remote areas with limited data remains a …

Application of deep learning and spectral deconvolution for estimating mineral abundances of zeolite, Mg-sulfate and montmorillonite mixtures and its implications for …

GRL Kodikara, LJ McHenry, FD van der Meer - Planetary and Space …, 2022 - Elsevier
A technique for estimating clinoptilolite, montmorillonite, and epsomite mineral abundances
from a reflectance spectrum of mineral mixtures using spectral deconvolution and a deep …