Results 101 to 110 of about 5,511 (234)

Insights Into Paint‐Bake Toughening of Resistance Spot Welds of a 2.0 GPa Warm‐Stamped Medium‐Mn Steel

steel research international, EarlyView.
Paint baking of resistance spot welded joints of 2.0 GPa warm‐stamped medium‐Mn steel activates low‐temperature tempering, forming fine cementite in the fusion zone and enhancing toughness. Crack propagation resistance increases, shifting the failure mode from partial interfacial to complete pullout, with peak load and energy absorption rising ...
Sunusi Marwana Manladan, Savyasachi Nellikode, YeoJin Jang, Sumin Lee, Dileep Chandran Ramachandran, Sung‐bo Heo, Jinyoung Lee, Young‐Kook Lee, Yeong‐Do Park   +8 more
wiley   +1 more source

Crash Behavior of DP800–DP1000 Advanced High‐Strength Steel’s Dissimilar Resistance Spot Welded Joints Under Quasi‐static and High Strain Rates

steel research international, EarlyView.
The high‐strain‐rate behavior of resistance spot‐welded DP800–DP1000 joints is investigated. Results show that microstructural gradients across BM–HAZ–FZ govern hardness, strain rate sensitivity, and failure modes. While strength increases with strain rate, energy absorption is controlled by ductility, with DP800–DP800 joints showing superior ...
Pankaj Shrivastava, Velaphi Msomi
wiley   +1 more source

Multi‐level fatigue reliability assessment of reinforced concrete railway bridges

Structural Concrete, EarlyView.
Abstract This paper presents a multi‐level reliability framework for assessing the fatigue life of reinforced concrete (RC) railway trough bridges subjected to cyclic loading. The framework incorporates increasing levels of analytical complexity and real‐world data in four steps. First, an analytical model applies S–N curves and the Palmgren–Miner rule
Silvia Sarmiento, Jaime Gonzalez‐Libreros, Chao Wang, Lennart Elfgren, Ola Enoksson, Tommy Höjsten, Lars‐Olof Andersson, Gabriel Sas   +7 more
wiley   +1 more source

Zero-Shot Texture Analysis and Regression-Based Deformation Recognition for Rail Anomaly Detection

IEEE Access
This paper presents a novel anomaly detection framework for rail systems, integrating zero-shot texture analysis and regression-based deformation recognition to monitor rail defects effectively.
Mikel Lainsa, Daeyoung Kim
doaj   +1 more source

A comprehensive heavy haul locomotive-track model and its application in assessing short-wavelength rail defects

, 2016
Cole, CR ORCiD: 0000-0001-8840-7136; Spiryagin, M ORCiD: 0000-0003-1197-898X; Wu, Q ORCiD: 0000-0001-9407-5617The feasibility of monitoring short-wavelength rail defects such as dipped joints has been theoretically investigated by simulating a locomotive-
Wu, Q, Cole, C, Qing Wu (9847022), Yan Sun (9838427), Colin Cole (9788021), Maksym Spiryagin (9836759), Sun, Y, Spiryagin, M   +7 more
core  

Do the public take action when a severe snow warning is issued?

Weather, EarlyView.
Extreme weather events pose significant risks to the population, making timely warnings essential for preparedness. The UK Met Office’s National Severe Weather Warning Service (NSWWS) has issued impact‐based alerts for over a decade, yet evaluations of their effectiveness remain limited.
Helen Dacre, Rachel McCloy, Joi Alon
wiley   +1 more source

Deep convolutional neural networks for detection of rail surface defects

, 2016
In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings.
Nunez, Alfredo (author), Babuska, R. (author), Alfredo Nunez, Robert Babuska, Faghih Roohi, S. (author), Shahrzad Faghih-Roohi, De Schutter, B.H.K. (author), Hajizadeh, S. (author), Siamak Hajizadeh, Bart De Schutter   +9 more
core   +2 more sources

Lightweight Convolutional Neural Networks Model and Data Augmentation‐Based Background Regression for Rail Surface Defect Detection

Artificial Intelligence for Engineering, EarlyView.
An ultra‐lightweight semantic segmentation network RailNet with only 0.905 M parameters is proposed for rail surface defect detection. Combined with a CDBM image enhancement and GAN‐based data augmentation, RailNet achieves superior segmentation accuracy and real‐time speed on edge devices.
Ziqing Wu, Weilong Niu, Xiaoguang Sun, Ting Qu, Yihui Zhu   +4 more
wiley   +1 more source

Deep Learning (Fast R-CNN)-Based Evaluation of Rail Surface Defects

Applied Sciences
In current railway rails, trains are propelled by the rolling contact between iron wheels and iron rails, and the high frequency of train repetition on rails results in a significant load exertion on a very small area where the wheel and rail come into ...
Jung-Youl Choi, Jae-Min Han
doaj   +1 more source

An Overview of High‐Temperature Superconducting Cables in DC Systems: Unlocking Potential for High‐Voltage DC Networks

High Voltage, EarlyView.
ABSTRACT This paper provides an overview of high‐temperature superconducting (HTS) cables in DC systems, with a focus on their deployment in high‐voltage DC (HVDC) networks. The assessment of HTS cable properties—such as extremely low electrical resistance, high current‐carrying capacity and a compact geometry—and their comparison with those of ...
Mohammad Hossein Mousavi, Hassan Moradi, Kumars Rouzbehi   +2 more
wiley   +1 more source