DSS-14 subreflector actuator dynamics during the Landers earthquake [PDF]
The 28 Jun. 1992 Landers earthquake ground motion records at the Echo site (DSS-12 antenna) were adjusted to provide a better match with spectra from the measured Mars site (DSS-14 antenna) instrument tower response. A finite-element model of the antenna
Levy, R., Strain, D.
core +1 more source
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
THE OBSERVATION OF GROUND MOTION USING UNDERGROUND SEISMOMETERS AT SHINJUKU, TOKYO
Hiroyoshi Kobayashi+2 more
openalex +2 more sources
Author Correction: Widespread ground motion distribution caused by rupture directivity during the 2015 Gorkha, Nepal earthquake. [PDF]
Koketsu K+8 more
europepmc +1 more source
Deformation Behavior of La2O3‐Doped Copper during Equal Channel Angular Pressing
By additions of strengthening elements and/or structure optimization, the mechanical properties of copper can be increased while keeping favorable electric conductivity. By combining addition of La2O3 and processing by equal channel angular pressing, substructure development is achieved, leading to increase in microhardness to more than double the ...
Lenka Kunčická+2 more
wiley +1 more source
2018 Characteristics of Pseudo-Earthquake Ground Motion : Part 2(Structures)
Yutaka Inoue
openalex +2 more sources
Helicopter simulation technology: An Ames Research Center perspective [PDF]
The total experience for evidence regarding the levels of motion and visual cueing fidelity required for handling-qualities research in ground-based simulators is reviewed.
Bray, R. S.
core +1 more source
The Interface Between Empirical and Simulation-Based Ground-Motion Models. [PDF]
Atkinson GM.
europepmc +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani+4 more
wiley +1 more source
2016 A Method of Calculation of Ground Motion for Response Analysis(Structures)
Hiroyoshi Kobayashi
openalex +2 more sources