Results 71 to 80 of about 1,182 (196)

A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials

open access: yesAdvanced Science, Volume 13, Issue 26, 8 May 2026.
This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu   +13 more
wiley   +1 more source

Total Variation Regularized GRACE(‐FO) Inversion

open access: yesJournal of Geophysical Research: Solid Earth, Volume 131, Issue 5, May 2026.
Abstract Gravity estimation from satellite‐satellite tracking missions such as GRACE(‐FO) is an ill‐posed inverse problem. The conventional approach to regularized inversion of GRACE(‐FO) measurements uses L2 ${L}_{2}$‐Tikhonov regularization with a heuristic constraint matrix derived based on knowledge of spatiotemporal distribution of the signal ...
G. Jacob   +4 more
wiley   +1 more source

Enhancing seismic image resolution using Brownian diffusion bridge model [PDF]

open access: yes
Seismic images often lack the high resolution needed for proper identification of subsurface structures and potential hydrocarbon reservoirs, and that is due to factors such as limited data acquisition and the attenuation of seismic waves as they travel ...
Sun, Bingbing   +2 more
core   +1 more source

A Physics-Informed Neural Network Framework for Seismic Signal Denoising Based on Time–Frequency Adaptive Decomposition

open access: yesApplied Sciences
Seismic signal denoising stands as a vital process that enables precise seismic data analysis because noise interference blocks the detection of weak but valuable seismic signals.
Qinghua Zhang   +4 more
doaj   +1 more source

Fault Volume Digital Twin to Reproduce the Full Slip Spectrum, Scaling, and Statistical Laws

open access: yesJournal of Geophysical Research: Solid Earth, Volume 131, Issue 5, May 2026.
Abstract Seismological and geodetic observations of fault zones reveal diverse slip dynamics, scaling, and statistical laws. Existing mechanisms explain some but not all of these behaviors. We show that incorporating an off‐fault damage zone—characterized by distributed fractures surrounding a main fault—can reproduce many key features observed in ...
M. Almakari   +9 more
wiley   +1 more source

Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data [PDF]

open access: yes, 2017
We have determined an approach for simultaneous reconstruction and denoising of 3D seismic data with randomly missing traces. The core in simultaneous reconstruction and denoising of 3D seismic data is the choice of constraint method.
Yatong Zhou   +5 more
core   +1 more source

Deep Earth: Leveraging neural networks for seismic exploration objectives [PDF]

open access: yes, 2022
Machine learning has already made many inroads in developments related to acquisition, processing, imaging, inverting, and interpreting seismic data. In spite of the many success stories, its commercial use has been limited as the challenges mount. These
Ovcharenko, Oleg   +9 more
core   +1 more source

Investigating the Detectability of Body Wave Phases From Tidal Ice Cracking Events on Titan With the Dragonfly Short‐Period Seismometer

open access: yesJournal of Geophysical Research: Planets, Volume 131, Issue 4, April 2026.
Abstract Detecting seismic activity on Saturn's icy moon Titan during the Dragonfly mission could provide crucial information on its internal structure. The geological complexity of the moon's surface suggests significant cyclic tidal deformation, likely leading to the fracturing of the ice shell.
L. Delaroque   +9 more
wiley   +1 more source

FocoNet: Transformer‐Based Focal‐Mechanism Determination

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Traditional focal‐mechanism determination primarily relies on fitting the first‐motion polarities with grid‐search algorithms. We developed a machine‐learning model, FocoNet, to include more seismic information into focal mechanism determination.
Xiaohan Song   +3 more
wiley   +1 more source

GeoFWI: A Large Velocity Model Data Set for Benchmarking Full Waveform Inversion Using Deep Learning

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Full waveform inversion (FWI) plays an increasingly important role in the field of seismic imaging due to its strong ability to estimate subsurface properties. Specifically, data‐driven FWI (DDFWI) establishes a straightforward mapping relationship between seismic data and the corresponding velocity model, yielding promising results.
Chao Li   +5 more
wiley   +1 more source

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