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Now showing items 3171-3180 of 3227
Optimization of Viscoelastic Metamaterials for Vibration Attenuation Properties
(
World Scientific
, 2020 , Article)
Metamaterials (MMs) are composites that are artificially engineered to have unconventional mechanical properties that stem from their microstructural geometry rather than from their chemical composition. Several studies ...
Reconstruction of Road Defects from Dynamic Vehicle Accelerations by Using the Artificial Neural Networks
(
Springer Science and Business Media B.V.
, 2023 , Conference Paper)
Monitoring of roads is considered the first step in establishing a successful road maintenance program, which includes scheduling adequate maintenance to a certain road section at the right time. Road monitoring assesses ...
Investigating the effect of using softer rail-pads on ground-borne vibration from underground railways
(
Taylor and Francis Ltd.
, 2023 , Article)
In this study, a series of vibration measurements were performed on a section of one of the lines of the Doha Metro to explore the effect of changing rail-pads from conventional higher stiffness under-rail pads to lower ...
Road Profile Estimation Using Full/Quarter-Car Model with Artificial Neural Networks
(
Springer Science and Business Media Deutschland GmbH
, 2024 , Conference Paper)
The monitoring of road roughness is one of the first and most critical steps in road maintenance. Road networks need constant maintenance to function properly and avoid any hazardous accidents or blockage of the traffic ...
A MEASUREMENT CAMPAIGN TO INVESTIGATE THE EFFECT OF USING SOFT RAILPADS ON GROUND-BORNE VIBRATIONS FROM UNDERGROUND RAILWAYS
(
Society of Acoustics
, 2023 , Conference Paper)
Railway networks may run through or beneath populated regions and significant landmarks. Hence, the ground-borne vibration caused by the trains might affect nearby buildings, residents, and the sensitive equipment within ...
Classification of Process Pipework Vibration Using Machine Learning
(
Springer Science and Business Media Deutschland GmbH
, 2024 , Conference Paper)
This paper aims to use a deep convolution neural network (CNN) to classify pipework vibrations. Vibration levels are a good indicator of the risk of vibration-induced fatigue failures (VIF). Vibrations in pipework are very ...
PREDICTING ROAD ROUGHNESS PROFILE USING DYNAMIC VEHICLE ACCELERATIONS AND ARTIFICIAL NEURAL NETWORKS
(
Society of Acoustics
, 2022 , Conference Paper)
Road roughness can cause ride discomfort and contribute to the emission of ground-borne noise and vibration. A robust monitoring regime of road roughness is essential for the efficient maintenance of a country's road ...
Fault classification using convolutional neural networks and color channels for time-frequency analysis of acoustic emissions
(
SAGE Publications Inc.
, 2023 , Article)
We present a novel method for real-time fault classification using the time history of acoustic emissions (AEs) recorded from a lab-scale gas turbine operating under normal and faulty conditions across multiple turbine ...
Using probabilistic neural networks for modeling metal fatigue and random vibration in process pipework
(
John Wiley and Sons Inc
, 2022 , Article)
Many experiments are usually needed to quantify probabilistic fatigue behavior in metals. Previous attempts used separate artificial neural network (ANN) to calculate different probabilistic ranges which can be computationally ...
A computational overview on phylogenetic characterization, pathogenic mutations, and drug targets for Ebola virus disease
(
Elsevier
, 2021 , Article)
The World Health Organization declared Ebola virus disease(EVD) as the major outbreak in the 20th century. EVD was firstidentified in 1976 in South Sudan and the Democratic Republicof the Congo. EVD was transmitted from ...