Hardness Variation in Driven Rivets for Bridge Evaluation

2018 ◽  
Vol 30 (10) ◽  
pp. 04018246 ◽  
Author(s):  
Matthew H. Hebdon ◽  
Ryan J. Sherman ◽  
Robert J. Connor
Keyword(s):  
Hardness Variation ◽  
Bridge Evaluation

scholarly journals Review of annual progress of bridge engineering in 2019

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Renda Zhao ◽  
Yuan Yuan ◽  
Xing Wei ◽  
Ruili Shen ◽  
Kaifeng Zheng ◽  
...  
Keyword(s):  
High Performance ◽  
Concrete Bridges ◽  
Bridge Engineering ◽  
Research Progress ◽  
Steel Bridge ◽  
Wind Resistance ◽  
Main Research ◽  
Bridge Model ◽  
Bridge Evaluation ◽  
Bridge Structures

AbstractBridge construction is one of the cores of traffic infrastructure construction. To better develop relevant bridge science, this paper introduces the main research progress in China and abroad in 2019 from 13 aspects, including concrete bridges and the high-performance materials, the latest research on steel-concrete composite girders, advances in box girder and cable-supported bridge analysis theories, advance in steel bridges, the theory of bridge evaluation and reinforcement, bridge model tests and new testing techniques, steel bridge fatigue, wind resistance of bridges, vehicle-bridge interactions, progress in seismic design of bridges, bridge hydrodynamics, bridge informatization and intelligent bridge and prefabricated concrete bridge structures.

Microstructure and hardness variation of additively manufactured Ti–Ni–C functionally graded composites

2021 ◽  
Vol 865 ◽  
pp. 158976
Author(s):  
Jianshen Wang ◽  
Daniel East ◽  
Evgeny V. Morozov ◽  
Aaron Seeber ◽  
Juan P. Escobedo-Diaz
Keyword(s):  
Functionally Graded ◽  
Functionally Graded Composites ◽  
Hardness Variation

Practical identification of favorable time windows for infrared thermography for concrete bridge evaluation

2015 ◽  
Vol 101 ◽  
pp. 1016-1030 ◽  
Author(s):  
Azusa Watase ◽  
Recep Birgul ◽  
Shuhei Hiasa ◽  
Masato Matsumoto ◽  
Koji Mitani ◽  
...  
Keyword(s):  
Infrared Thermography ◽  
Time Windows ◽  
Concrete Bridge ◽  
Bridge Evaluation

Concrete Bridge Evaluation and Rating

2014 ◽  
pp. 381-442
Author(s):  
Murugesu Vinayagamoorthy ◽  
Richard Tsang
Keyword(s):  
Concrete Bridge ◽  
Bridge Evaluation

Audio-Based Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

2018 ◽  
Author(s):  
Achyuth Kothuru ◽  
Sai Prasad Nooka ◽  
Rui Liu
Keyword(s):  
Neural Networks ◽  
Support Vector Machines ◽  
Tool Wear ◽  
Support Vector ◽  
Workpiece Material ◽  
Artificial Intelligent ◽  
Tool Condition ◽  
Hardness Variation ◽  
Vector Machines ◽  
Audible Sound

Machining industry has been evolving towards implementation of automation into the process for higher productivity and efficiency. Although many studies have been conducted in the past to develop intelligent monitoring systems in various application scenarios of machining processes, most of them just focused on cutting tools without considering the influence due to the non-uniform hardness of workpiece material. This study develops a compact, reliable, and cost-effective intelligent Tool Condition Monitoring (TCM) model to detect the cutting tool wear in machining of the workpiece material with hardness variation. The generated audible sound signals during the machining process will be analyzed by state of the art artificial intelligent techniques, Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs), to predict the tool condition and the hardness variation of the workpiece. A four-level classification model is developed for the system to detect the tool wear condition based on the width of the flank wear land and hardness variation of the workpiece. The study also involves comparative analysis between two employed artificial intelligent techniques to evaluate the performance of models in predicting the tool wear level condition and workpiece hardness variation. The proposed intelligent models have shown a significant prediction accuracy in detecting the tool wear and from the audible sound into the proposed multi-classification wear class in the end-milling process of non-uniform hardened workpiece.

Research on Railway Bridge Evaluation Index

2013 ◽  
Vol 838-841 ◽  
pp. 1126-1129
Author(s):  
Zhao Lan Wei ◽  
Guo Jun Liu ◽  
Zu Yin Zou
Keyword(s):  
High Speed ◽  
Evaluation Index ◽  
Railway Bridge ◽  
High Speed Railway ◽  
Railway Bridges ◽  
Bridge Evaluation ◽  
Normal Speed ◽  
The Difference

Each related index was compared in three specifications, including Fundamental code for design on railway bridge and culvert, Code for rating existing railway bridges, and Code for design of high speed railway. The reasons of the difference existed in indexes was revealed, especially between high speed railway bridge and normal speed railway bridge.

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