Results 21 to 30 of about 3,752,834 (199)

Geometry-Encoded Soft Strain Sensing via Liquid-Metal Transmission Lines. [PDF]

Adv Sci (Weinh)
This study presents a liquid‐metal transmission‐line strain sensor that achieves intrinsic decoupling by encoding axial elongation into propagation delay. The time‐domain readout remains stable under complex off‐axis. This enables reliable, repeatable, real‐time elongation measurement in dynamic, multiaxial loading environments for wearable electronics,
Liu Z, Jin F, Shi W, She M, Meng Z, Fang M, Zhang Y, Dong Q, Yang W, Shi L, Zhao X, Zhou F, Yao B.   +12 more
europepmc   +2 more sources

Advanced Elastic and Reservoir Properties Prediction through Generative Adversarial Network

Applied Sciences, 2023
The prediction of subsurface properties such as velocity, density, porosity, and water saturation has been the main focus of petroleum geosciences.
Muhammad Anwar Ishak, Abdul Halim Abdul Latiff, Eric Tatt Wei Ho, Muhammad Izzuljad Ahmad Fuad, Nian Wei Tan, Muhammad Sajid, Emad Elsebakhi   +6 more
doaj   +1 more source

Numerical simulations of pure quasi-P-waves in orthorhombic anisotropic media

Frontiers in Earth Science, 2023
The accurate simulation of anisotropic media is critical in seismic imaging and inversion. In recent years, some scholars have dedicated efforts to the study of precise elastic waves in anisotropic media; however, it is easy to separate P-wave and S-wave
Hao Wang, Jianping Huang, Jidong Yang, Yi Shen   +3 more
doaj   +1 more source

Inverse Design of Pre-Strain via a Predictive Electromechanical Model for Enhanced Strain Sensing. [PDF]

Adv Sci (Weinh)
An analytical electromechanical model rooted in microcrack evolution mechanics is globally calibrated from only eight pre‐strain datasets, enabling prediction of the complete sensing response at untested pre‐strain values within the calibrated design space (R2 > 0.99).
Shang JC, Wang R, Lu B, Song ML, Chen YY, Han K, Feng XJ, Sun B, Cao YG, Yan XY, Yang SC.   +10 more
europepmc   +2 more sources

Recent progress on full waveform inversion

地球与行星物理论评, 2023
Full waveform inversion is an acoustic/elastic/anelastic wave equation-based high accuracy seismic imaging method for studying the Earth's interior structure.
Hejun Zhu, Qinya Liu, Jidong Yang
doaj   +1 more source

Anisotropic anelastic seismic full waveform modeling and inversion: Application to North Sea offset VSP data

Georesursy, 2018
In sedimentary basin, elastic anisotropy can be described by a transverse isotropic medium and the attenuation in the seismic bandwidth can be approximated by a quasi-constant quality factor.
C. Barnes, M. Charara
doaj   +1 more source

Multiparameter Elastic Full Waveform Inversion With Facies Constraints [PDF]

, 2017
Full waveform inversion (FWI) aims fully benefit from all the data characteristics to estimate the parameters describing the assumed physics of the subsurface.
Naeini, Ehsan Zabihi, Zhang, Zhendong, Alkhalifah, Tariq Ali   +2 more
core   +1 more source

Case studies of ultrasonic full waveform inversion for inspecting concrete structures

e-Journal of Nondestructive Testing
The non-destructive evaluation of reinforced pre-stressed concrete structures is critical to prevent catastrophic failures of aging infrastructure. Conventional non-destructive inspection methods often rely on manual and subjective interpretation of the
David Sollberger, Chris Udell, Lion Krischer, Christian Boehm, Elmar Strobach, David Corbett   +5 more
doaj   +1 more source

Seismic Waveform Inversion Using the Finite-Difference Contrast Source Inversion Method

Journal of Applied Mathematics, 2014
This paper extends the finite-difference contrast source inversion method to reconstruct the mass density for two-dimensional elastic wave inversion in the framework of the full-waveform inversion.
Bo Han, Qinglong He, Yong Chen, Yixin Dou   +3 more
doaj   +1 more source

Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data

Geosciences, 2019
Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix.
Marwan Charara, Christophe Barnes
doaj   +1 more source