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Neural Network-Based Regression for Local Adhesion Estimation (COF-UOS-02 Report)
11431
08/12/2021 12:42:21
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Ratesetter+: Report 1 - Platform and Station Passenger Flow Optimisation (COF-G22-01 Report)
11501
14/09/2021 08:20:07
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Understanding leaf effects on low adhesion (COF-ITR-03)
18778
24/10/2022 16:49:38
This is a co-sponsored studentship run by the Centre for Doctoral Training in Integrated Tribology (iT-CDT) at the University of Sheffield and University of Leeds
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Neural Network-Based Regression for Local Adhesion Estimation (COF-UOS-02)
18780
29/06/2022 09:26:02
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RateSetter+: the impact of social distancing on network performance (COF-G22-01)
18781
14/09/2021 07:39:21
As we welcome passengers back to the railway post-Covid-19, the impact of increasing numbers and social distance needs to be understood to better manage network performance
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Full-Scale Rig Test Specifications for Assessing Top-of-Rail Product Pick-up and Carry-down Performance (COF-G19-01 Report)
20004
31/01/2022 17:30:10
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Twin Disc Test Specifications for Assessing Top-of-Rail Product Performance, Creating Low Adhesion Layers, and Assessing Traction Gel Performance (COF-G19-01 Report)
20008
12/05/2022 09:48:40
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Sand consist changes for improved track circuit performance (COF-UOS-03)
26365
29/06/2022 09:19:52
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Sand consist changes for improved track circuit performance (COF-UOS-03 Report)
26366
08/12/2021 12:43:01
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Improving prediction of low adhesion friction considering transience (COF-UOS-05)
26478
24/10/2022 16:51:02
Low adhesion between wheel and rail can be caused by moisture on the rail mixing with the film produced by ‘leaves on the line’ or other contaminants, such as rust or grease
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