Seasonal Effect on the Optimization of Rail Defect Inspection Frequency

2013 ◽  
Author(s):  
Xiang Liu ◽  
C. Tyler Dick ◽  
Alexander Lovett ◽  
Mohd Rapik Saat ◽  
Christopher P. L. Barkan
Keyword(s):  
Seasonal Variation ◽  
Ultrasonic Inspection ◽  
Transportation Safety ◽  
Seasonal Effect ◽  
Infrastructure Management ◽  
Defect Inspection ◽  
Railroad Industry ◽  
Railway Infrastructure ◽  
Rail Inspection ◽  
Non Destructive

Broken rails are the most common cause of severe freight-train derailments on American railroads. Reducing the occurrence of broken-rail-caused derailments is an important safety objective for the railroad industry. The current practice is to periodically inspect rails using non-destructive technologies such as ultrasonic inspection. Determining the optimal rail defect inspection frequency is a critical decision in railway infrastructure management. There is a seasonal variation in the occurrence of broken rails that result in train derailments. This paper quantifies the effect of this seasonal variation on the risk-based optimization of rail inspection frequency. This research can be incorporated into a larger framework of broken rail risk management to improve railroad transportation safety.

Failure Analysis and Defect Inspection of Electronic Devices by High-Resolution Cathodoluminescence

2017 ◽  
Author(s):  
C. Monachon ◽  
M.S. Zielinski ◽  
D. Gachet ◽  
S. Sonderegger ◽  
S. Muckenhirn ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Electronic Materials ◽  
Electronic Devices ◽  
Optical Emission ◽  
Large Field ◽  
Nanometer Scale ◽  
Defect Analysis ◽  
Defect Inspection ◽  
Spectrally Resolved ◽  
Non Destructive

Abstract Quantitative cathodoluminescence (CL) microscopy is a new optical spectroscopy technique that measures electron beam-induced optical emission over large field of view with a spatial resolution close to that of a scanning electron microscope (SEM). Correlation of surface morphology (SE contrast) with spectrally resolved and highly material composition sensitive CL emission opens a new pathway in non-destructive failure and defect analysis at the nanometer scale. Here we present application of a modern CL microscope in defect and homogeneity metrology, as well as failure analysis in semiconducting electronic materials

Ultrasonic Tomography for Rail Flaw Imaging

2014 ◽  
Author(s):  
Robert Phillips ◽  
Francesco Lanza di Scalea ◽  
Claudio Nucera ◽  
Piervincenzo Rizzo ◽  
Leith Al-Nazer
Keyword(s):  
Human Error ◽  
Ultrasonic Inspection ◽  
Quantitative Information ◽  
Inspection Time ◽  
Practical Implementation ◽  
Ultrasonic Tomography ◽  
Railroad Industry ◽  
Knowledge Based ◽  
Portable System ◽  
High Resolution Images

There is a need in the railroad industry to have quantitative information on internal rail flaws, including flaw size and orientation. Such information can lead to knowledge-based decision making on any remedial action, and ultimately increase the safety of train operations by preventing derailments. Current ultrasonic inspection methods leave such sizing determinations to the inspector, and there can be significant variability from one inspector to another depending on experience and other factors. However, this quantitative information can be obtained accurately by 3-D imaging of the rail flaws. It is the goal of this project to develop a portable system that will improve defect classification in rails and ultimately improve public safety. This paper will present a method for 3-D imaging of internal rail flaws based on Ultrasonic Tomography. The proposed technique combines elements of ultrasonic testing with those of radar and sonar imaging to obtain high-resolution images of the flaws using a stationary array of ultrasonic transducers. The array is operated in a “full matrix capture” scheme that minimizes the number of ultrasonic transmitters, hence simplifying the practical implementation and reducing the inspection time. In this method, a full 3D image of the rail volume identifies the location, size and orientation of the defect. This will help to eliminate human error involved with a typical manual inspection using a single transducer probe inspection. The results of advanced numerical simulations, carried out on a rail profile, will be presented. The simulations show the effectiveness of the technique to image a 5% Head Area Transverse Defect in the railhead. Current efforts are aimed at developing an experimental prototype based on this technology, whose design status is also discussed in this paper.

Non-destructive technologies for sustainable assessment and monitoring of railway infrastructure: a focus on GPR and InSAR methods

2021 ◽  
Vol 80 (24) ◽  
Author(s):  
Chiara Ferrante ◽  
Luca Bianchini Ciampoli ◽  
Andrea Benedetto ◽  
Amir M. Alani ◽  
Fabio Tosti
Keyword(s):  
Railway Infrastructure ◽  
Assessment And Monitoring ◽  
Non Destructive

scholarly journals Seasonal Variation Analysis Method of GHG at Municipal Solid Waste Incinerator

2020 ◽  
Vol 12 (18) ◽  
pp. 7425
Author(s):  
Seongmin Kang ◽  
Joonyoung Roh ◽  
Eui-chan Jeon
Keyword(s):  
Seasonal Variation ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Ghg Emissions ◽  
Co2 Concentration ◽  
Waste Incineration ◽  
Seasonal Effect ◽  
Waste Incinerator ◽  
Waste Composition

The greenhouse gas emissions of the waste incineration sector account for approximately 43% of the total GHG emissions and represent the majority of the CO2 emissions from waste in Korea. Improving the reliability of the GHG inventory of the waste incineration sector is an important aspect for the examination of global GHG emission management according to the Paris Agreement. In this study, we introduced a statistical approach to analyze seasonal changes through analysis of waste composition and CO2 concentration in Municipal Solid Waste incinerators and applied the methodology to one case study facility. The analysis results in the case study showed that there was no seasonal variation in waste composition and CO2 concentrations, except for wood. Wood is classified as biomass, and the GHG emissions caused by biomass incineration are reported separately, indicating that the effect of an MSW incinerator on GHG emissions is not significant. Therefore, the seasonal effect of CO2 concentration or waste composition may not be an impact when calculating GHG emissions from case study facilities’ MSW incinerators. This study proposed an approach for analyzing factors that affect the GHG inventory reliability by analyzing seasonal characteristics and variation through the statistical analysis, which are used for the calculation of the GHG emissions of an MSW incinerator.

scholarly journals Inspection of the Composite Materials

2021 ◽  
Vol 10 (3) ◽  
pp. 146
Author(s):  
Yaser A. Jasim ◽  
Senan Thabet ◽  
Thabit H. Thabit
Keyword(s):  
Composite Materials ◽  
Visual Inspection ◽  
Magnetic Particle ◽  
Phased Array ◽  
Ultrasonic Inspection ◽  
Test Method ◽  
Main Method ◽  
Destructive Test ◽  
Eddy Current Inspection ◽  
Non Destructive

<p><em>A non-destructive test method is the main method to examine most of the materials, composite materials in particular. There are too many </em><em>Non-Destructive Test (</em><em>NDT) methods to inspect the materials such as, Visual Inspection, Liquid Penetrate Inspection, Eddy-Current Inspection, Phased Array Inspection, Magnetic Particle Inspection and Ultrasonic Inspection</em><em>.</em></p><p><em>This paper aims to creat a unified methodology for engineers depending on reaserch onion to study the inspection of the composite materials.</em></p><p><em>The researchers concluded that NDT method is the most suitable method for testing any materials and the composite materials. They also recommended to choose the most suitable NDT method as every materials and composite materials have its own properties as well as the inspection methods had its own capabilities and limitations. </em></p>

Development of Selective Seam Weld Corrosion Test Method

2014 ◽  
Author(s):  
J. A. Beavers ◽  
C. S. Brossia ◽  
R. A. Denzine
Keyword(s):  
Base Metal ◽  
Field Testing ◽  
Test Method ◽  
Transportation Safety ◽  
Seam Weld ◽  
Corrosion Kinetics ◽  
Pipeline Failures ◽  
Weld Corrosion ◽  
Pipeline Safety ◽  
Non Destructive

Selective seam weld corrosion (SSWC) of electric resistance welded (ERW) pipelines has been identified as a potential risk to pipeline safety. Due to recent pipeline failures, where seam weld defects may have played a significant role, the National Transportation Safety Board called upon the Pipeline and Hazardous Materials Safety Administration (PHMSA) to conduct a comprehensive study to identify actions that can be used by operators to eliminate catastrophic longitudinal seam failures in pipelines. Battelle contracted Kiefner and Associates, Inc. and Det Norse Veritas (U.S.A.) Inc. (DNV GL) with the objective to assist PHMSA in addressing this issue. The objective of one of the tasks performed by DNV GL was to develop a reliable, rapid, non-destructive, field-deployable test method that can quantify SSWC susceptibility on operating pipelines containing ERW seams. For this effort, two different, field deployable, non-destructive methods were evaluated in laboratory testing. The methods were validated using a standard destructive test for assessing SSWC susceptibility. One method was based on measurement of the local potential difference between the seam weld and the adjacent base metal while the second was based on differences in the corrosion kinetics between the seam weld and the base metal. The method that is based on corrosion kinetics was found to be most effective in identifying SSWC susceptible pipe steels. It utilizes a barnacle cell to conduct linear polarization resistance measurements on small, selected areas of the pipe (e.g., the weldment or base metal). Additional laboratory as well as field-testing is planned to further validate the test method.

scholarly journals Machine learning at the interface of structural health monitoring and non-destructive evaluation

2020 ◽  
Vol 378 (2182) ◽  
pp. 20190581
Author(s):  
P. Gardner ◽  
R. Fuentes ◽  
N. Dervilis ◽  
C. Mineo ◽  
S.G. Pierce ◽  
...  
Keyword(s):  
Machine Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ultrasonic Inspection ◽  
Guided Wave ◽  
Structural Health ◽  
Non Destructive Evaluation ◽  
Ultrasonic Guided Wave ◽  
Detection And Identification ◽  
Non Destructive

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

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