Radiative Heat Transfer Analysis of Railroad Bearings for Wayside Hot-Box Detector Optimization

The railroad industry utilizes wayside detection systems to monitor the temperature of freight railcar bearings in service. The wayside hot-box detector (HBD) is a device that sits on the side of the tracks and uses a non-contact infrared sensor to determine the temperature of the train bearings as they roll over the detector. Various factors can affect the temperature measurements of these wayside detection systems. The class of the railroad bearing and its position on the axle relative to the position of the wayside detector can affect the temperature measurement. That is, the location on the bearing cup where the wayside infrared sensor reads the temperature varies depending on the bearing class (e.g., class K, F, G, E). Furthermore, environmental factors can also affect these temperature readings. The abovementioned factors can lead to measured temperatures that are significantly different than the actual operating temperatures of the bearings. In some cases, temperature readings collected by wayside detection systems did not indicate potential problems with some bearings, which led to costly derailments. Attempts by certain railroads to optimize the use of the temperature data acquired by these wayside detection systems has led to removal of bearings that were not problematic (about 40% of bearings removed were non-verified), resulting in costly delays and inefficiencies. To this end, the study presented here aims to investigate the efficacy of the wayside detection systems in measuring the railroad bearing operating temperature in order to optimize the use of these detection systems. A specialized single bearing dynamic test rig with a configuration that closely simulates the operating conditions of railroad bearings in service was designed and built by the University Transportation Center for Railway Safety (UTCRS) research team at the University of Texas Rio Grande Valley (UTRGV) for the purpose of this study. The test rig is equipped with a system that closely mimics the wayside detection system functionality and compares the infrared sensor temperature reading to contact thermocouple and bayonet temperature sensors fixed to the outside surface of the bearing cup. This direct comparison of the temperature data will provide a better understanding of the correlation between these temperatures under various loading levels, operating speeds, and bearing conditions (i.e. healthy versus defective), which will allow for an optimization of the wayside detectors. The impact on railway safety will be realized through optimized usage of current wayside detection systems and fewer nonverified bearings removed from service, which translates into fewer costly train stoppages and delays

Remote source document verification in two national clinical trials networks: a pilot study.

OBJECTIVE: Barriers to executing large-scale randomized controlled trials include costs, complexity, and regulatory requirements. We hypothesized that source document verification (SDV) via remote electronic monitoring is feasible. METHODS: Five hospitals from two NIH sponsored networks provided remote electronic access to study monitors. We evaluated pre-visit remote SDV compared to traditional on-site SDV using a randomized convenience sample of all study subjects due for a monitoring visit. The number of data values verified and the time to perform remote and on-site SDV was collected. RESULTS: Thirty-two study subjects were randomized to either remote SDV (N=16) or traditional on-site SDV (N=16). Technical capabilities, remote access policies and regulatory requirements varied widely across sites. In the adult network, only 14 of 2965 data values (0.47%) could not be located remotely. In the traditional on-site SDV arm, 3 of 2608 data values (0.12%) required coordinator help. In the pediatric network, all 198 data values in the remote SDV arm and all 183 data values in the on-site SDV arm were located. Although not statistically significant there was a consistent trend for more time consumed per data value (minutes +/- SD): Adult 0.50 +/- 0.17 min vs. 0.39 +/- 0.10 min (two-tailed t-test p=0.11); Pediatric 0.99 +/- 1.07 min vs. 0.56 +/- 0.61 min (p=0.37) and time per case report form: Adult: 4.60 +/- 1.42 min vs. 3.60 +/- 0.96 min (p=0.10); Pediatric: 11.64 +/- 7.54 min vs. 6.07 +/- 3.18 min (p=0.10) using remote SDV. CONCLUSIONS: Because each site had different policies, requirements, and technologies, a common approach to assimilating monitors into the access management system could not be implemented. Despite substantial technology differences, more than 99% of data values were successfully monitored remotely. This pilot study demonstrates the feasibility of remote monitoring and the need to develop consistent access policies for remote study monitoring