Learning Event on the Rising Powers for DFID Advisors, April-May 2012

The Learning Event brought together colleagues from DFID, IDS, and the BRICS, and aimed to facilitate the sharing and learning of experiences in international development and policy, from and amongst the BRICS, and to set out a framework and broad parameters for engaging with the Rising Powers in the future. Presentations from DFID colleagues in the BRICS countries and London office showed that DFID policymakers are concerned with finding structures that allow the UK to address the challenges of working with new development actors – e.g. non-DAC donors and the BRICS countries – particularly in the post-Busan context, where the OECD Development Assistance Committee is seen to no longer hold the same sway. At the same time, DFID seeks to share its extensive experience and expertise as a donor and partner in technical development cooperation. How do we capitalise on the good relationships the UK has with other nations to implement development processes and action in a new and as yet undefined space? Two key points emerged during the week-long RPID workshop; and in particular during the DFID Learning Event: the need for the BRICS and other Rising Powers to manage inequality, and the need to systematise learning from their experiences in development and poverty reduction.DFI

Building Mutual Learning between the Rising Powers

This Evidence Report provides a summary account of the Mutual Learning research initiative at the Institute of Development Studies, carried out from 2012 to 2014 as part of the Rising Powers in International Development programme. It offers an explanation for the growing interest in mutual learning as a way of engaging with ‘rising powers’ – such as the BRICS – in international development cooperation, and showcases some of the work carried out under the Mutual Learning component, including the Senior International Associates fellowship programme. It synthesises the IDS approach to mutual learning, as well as some of the challenges and opportunities presented by mutual – or multidirectional – learning in an increasingly multipolar world. Finally, the report outlines recommendations for how to accelerate mutual learning about different countries’ development experiences

Estimating the Inner Ring Defect Size and Residual Service Life of Freight Railcar Bearings Using Vibration Signatures

There are currently two primary wayside detection systems for monitoring the health of freight railcar bearings in the railroad industry: The Trackside Acoustic Detection System (TADS™) and the wayside Hot-Box Detector (HBD). TADS™ uses wayside microphones to detect and alert the train operator of high-risk defects. However, many defective bearings may never be detected by TADS™ since a high-risk defect is a spall which spans about 90% of a bearing’s raceway, and there are less than 30 systems in operation throughout the United States and Canada. HBDs sit on the side of the rail-tracks and use non-contact infrared sensors to acquire temperatures of bearings as they roll over the detector. These wayside bearing detection systems are reactive in nature and often require emergency stops in order to replace the wheelset containing the identified defective bearing. Train stoppages are inefficient and can be very costly. Unnecessary train stoppages can be avoided if a proper maintenance schedule can be developed at the onset of a defect initiating within the bearing. Using a proactive approach, railcars with defective bearings could be allowed to remain in service operation safely until reaching scheduled maintenance. The University Transportation Center for Railway Safety (UTCRS) research group at the University of Texas Rio Grande Valley (UTRGV) has been working on developing a proactive bearing condition monitoring system which can reliably detect the onset of bearing failure. Unlike wayside detection systems, the onboard condition monitoring system can continuously assess the railcar bearing health and can provide accurate temperature and vibration profiles to alert of defect initiation. This system has been validated through rigorous laboratory testing at UTRGV and field testing at the Transportation Technology Center, Inc. (TTCI) in Pueblo, CO. The work presented here builds on previously published work that demonstrates the use of the onboard condition monitoring system to identify defective bearings as well as the correlations developed for spall growth rates of defective bearing outer rings (cups). The system first uses the root-mean-square (RMS) value of the bearing’s acceleration to assess its health. Then, an analysis of the frequency domain of the acquired vibration signature determines if the bearing has a defective inner ring (cone) and the RMS value is used to estimate the defect size. This estimated size is then used to predict the residual life of the bearing. The methodology proposed in this paper can assist railroads and railcar owners in the development of a proactive and cost-efficient maintenance cycle for their rolling stock

Prognostics Models for Railroad Tapered Roller Bearings with Spall Defects on Inner or Outer Rings

Rolling contact fatigue (RCF) is one of the major causes of failure in railroad bearings used in freight service. Subsurface inclusions resulting from impurities in the steel used to fabricate the bearings initiate subsurface fatigue cracks, which propagate upwards and cause spalling of the rolling surfaces. These spalls start small and propagate as continued operation induces additional crack formation and spalling. Studies have shown that the bearing temperature is not a good indicator of spall initiation. In many instances, the temperature of the bearing increases markedly only when the spall has spread across major portions of the raceway. In contrast, vibration signatures can be used to accurately detect spall initiation within a bearing and can track spall deterioration. No monitoring technique can indicate the growth rate of a spall or determine residual useful life. Hence, the main objective of this study is to develop reliable prognostic models for spall growth within railroad bearings that are based on actual service life testing rather than theoretical simulations. The data used to devise the models presented here were acquired from laboratory and field testing that started in 2010. Growth models are provided for spalls initiating on the bearing inner (cone) and outer (cup) rings. Coupling these prognostic models with a previously developed vibration-based bearing condition monitoring algorithm will provide the rail industry with an efficient tool that can be used to plan proactive maintenance schedules that will mitigate unnecessary and costly train stoppages and delays and will prevent catastrophic derailments