A real-time train routing and platforming problem in complex railway stations

Author(s):  
Lijie Bai ◽  
Zhiming Yuan ◽  
Hongtao Zhao ◽  
Tao Zhang

This paper studies the real-time trains routing and platforming problem (RT-TRPP) in railway stations that arises from the unreliable arrival times of freight trains, flexible shunting operations and dynamic station layout caused by equipment failure. The feasibility of station timetable is checked before preparing a route for a train or after updating the station layout. If the station timetable is infeasible, the reassignment of trains is triggered. After introducing a problem formulation for the RT-TRPP, we propose an Integer Linear Program (ILP) that strives to minimize the number of conflicting trains. In resulting timetable, directions, arrival and leaving time remain the same with networks timetable to prevent traffic disturbance of neighboring territories. If the resulting timetable is still infeasible, conflicting trains are pointed out with the cause analysis. The method is tested on real-world complex station which receives always the overload of trains’ activities. The optimal full-day solution of 249 trains is obtained within 2 seconds. The efficiency of this method meets the time-critical nature of RT-TRPP.

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sherif M. Hanafy ◽  
Hussein Hoteit ◽  
Jing Li ◽  
Gerard T. Schuster

AbstractResults are presented for real-time seismic imaging of subsurface fluid flow by parsimonious refraction and surface-wave interferometry. Each subsurface velocity image inverted from time-lapse seismic data only requires several minutes of recording time, which is less than the time-scale of the fluid-induced changes in the rock properties. In this sense this is real-time imaging. The images are P-velocity tomograms inverted from the first-arrival times and the S-velocity tomograms inverted from dispersion curves. Compared to conventional seismic imaging, parsimonious interferometry reduces the recording time and increases the temporal resolution of time-lapse seismic images by more than an order-of-magnitude. In our seismic experiment, we recorded 90 sparse data sets over 4.5 h while injecting 12-tons of water into a sand dune. Results show that the percolation of water is mostly along layered boundaries down to a depth of a few meters, which is consistent with our 3D computational fluid flow simulations and laboratory experiments. The significance of parsimonious interferometry is that it provides more than an order-of-magnitude increase of temporal resolution in time-lapse seismic imaging. We believe that real-time seismic imaging will have important applications for non-destructive characterization in environmental, biomedical, and subsurface imaging.


Author(s):  
D Spallarossa ◽  
M Cattaneo ◽  
D Scafidi ◽  
M Michele ◽  
L Chiaraluce ◽  
...  

Summary The 2016–17 central Italy earthquake sequence began with the first mainshock near the town of Amatrice on August 24 (MW 6.0), and was followed by two subsequent large events near Visso on October 26 (MW 5.9) and Norcia on October 30 (MW 6.5), plus a cluster of 4 events with MW > 5.0 within few hours on January 18, 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450,000 events in the year following the first mainshock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hours on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84,401 to 450,000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ± 0.9km in epicentral location and ± 1.5km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting.


Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1881
Author(s):  
Jesús Lázaro ◽  
Armando Astarloa ◽  
Mikel Rodríguez ◽  
Unai Bidarte ◽  
Jaime Jiménez

Since the 1990s, the digitalization process has transformed the communication infrastructure within the electrical grid: proprietary infrastructures and protocols have been replaced by the IEC 61850 approach, which realizes interoperability among vendors. Furthermore, the latest networking solutions merge operational technologies (OTs) and informational technology (IT) traffics in the same media, such as time-sensitive networking (TSN)—standard, interoperable, deterministic, and Ethernet-based. It merges OT and IT worlds by defining three basic traffic types: scheduled, best-effort, and reserved traffic. However, TSN demands security against potential new cyberattacks, primarily, to protect real-time critical messages. Consequently, security in the smart grid has turned into a hot topic under regulation, standardization, and business. This survey collects vulnerabilities of the communication in the smart grid and reveals security mechanisms introduced by international electrotechnical commission (IEC) 62351-6 and how to apply them to time-sensitive networking.


2021 ◽  
Author(s):  
Phathompat Boonyasaknanon ◽  
Raymond Pols ◽  
Katja Schulze ◽  
Robert Rundle

Abstract An augmented reality (AR) system is presented which enhances the real-time collaboration of domain experts involved in the geologic modeling of complex reservoirs. An evaluation of traditional techniques is compared with this new approach. The objective of geologic modeling is to describe the subsurface as accurately and in as much detail as possible given the available data. This is necessarily an iterative process since as new wells are drilled more data becomes available which either validates current assumptions or forces a re-evaluation of the model. As the speed of reservoir development increases there is a need for expeditious updates of the subsurface model as working with an outdated model can lead to costly mistakes. Common practice is for a geologist to maintain the geologic model while working closely with other domain experts who are frequently not co-located with the geologist. Time-critical analysis can be hampered by the fact that reservoirs, which are inherently 3D objects, are traditionally viewed with 2D screens. The system presented here allows the geologic model to be rendered as a hologram in multiple locations to allow domain experts to collaborate and analyze the reservoir in real-time. Collaboration on 3D models has not changed significantly in a generation. For co-located personnel the approach is to gather around a 2D screen. For remote personnel the approach has been sharing a model through a 2D screen along with video chat. These approaches are not optimal for many reasons. Over the years various attempts have been tried to enhance the collaboration experience and have all fallen short. In particular virtual reality (VR) has been seen as a solution to this problem. However, we have found that augmented reality (AR) is a much better solution for many subtle reasons which are explored in the paper. AR has already acquired an impressive track record in various industries. AR will have applications in nearly all industries. For various historical reasons, the uptake for AR is much faster in some industries than others. It is too early to tell whether the use of augmented reality in geological applications will be transformative, however the results of this initial work are promising.


Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Adam Prater ◽  
Meredith Bowen ◽  
Emily Pavich ◽  
Thomas Loehfelm ◽  
Aaron M Anderson ◽  
...  

Background: Real-Time Location Systems (RTLS) utilize tracking tags and detectors to locate objects or people. This technology has been implemented in healthcare, chiefly to track hospital assets, and a few healthcare systems have applied this technology to track patients in the emergency department. This pilot study tested the feasibility of RTLS to monitor the acute stroke workflow in a large, urban hospital. Methods: An asset tracking RTLS was installed in a large, urban hospital. A series of 21 acute stroke patients were tracked throughout the workflow process by a human observer and via RTLS asset tag attached to the patient’s hospital equipment. A Wi-Fi detector documented initial patient arrival times in the ER Hallway, radiofrequency/infrared (RFID/IR) detectors documented ER CT scanner and ER patient room times. Patient Arrival and departure times in the emergency room (ER) and radiology CT scanner were measured. Time differences between human observer and RTLS were calculated. Results: A total of 21 patients were tracked with RTLS. The mean time difference, interquartile range and standard deviation in minutes are as follows: initial arrival (mean 106, IQR 112, SD 197); CT arrival ( mean 1, IQR 1, SD 0.86); CT departure (mean 2, IQR 2, SD 1.13); patient return to ED (mean 1, IQR 1, SD 0.94). Discussion: Our data demonstrate that RTLS can provide accurate, real-time patient location information, and has the potential to provide data for quality improvement. Combination RFID/IR detectors provided accurate time information while the Wi-Fi detector, proved unreliable for initial arrival times. Our preliminary data supports the development of an unique RTLS system specifically designed to allow for complete visualization of the stroke workflow from patient arrival to treatment along with a dashboard user interface to facilitate treatment team coordination.


2014 ◽  
Vol 4 (1) ◽  
pp. 27 ◽  
Author(s):  
Michael Vistein ◽  
Andreas Angerer ◽  
Alwin Hoffmann ◽  
Andreas Schierl ◽  
Wolfgang Reif

Sign in / Sign up

Export Citation Format

Share Document