Rail Track Maintenance Planning: An Assessment Model

2000 ◽  
Vol 1713 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Scott A. Simson ◽  
Luis Ferreira ◽  
Martin H. Murray
Keyword(s):  
Net Present Value ◽  
Assessment Model ◽  
Operating Costs ◽  
Railway Track ◽  
Base Case ◽  
Maintenance Planning ◽  
Track Maintenance ◽  
Track Condition ◽  
Train Operation ◽  
Maintenance Work

In Australian rail freight operations, railway track maintenance makes up between 25 and 35 percent of total train operating costs. Models have shown that track maintenance costs can be reduced by 5 to 10 percent through improved planning. The Track Maintenance Planning Model (TMPM) has been developed to deal with the track maintenance planning function in the medium to long term. In contrast to traditional models, which mainly use expert systems, TMPM simulates the impacts of railway track conditions and related maintenance work by using an existing track degradation model. Track condition data from that model are used to determine whether safety-related speed restrictions are needed and what immediate maintenance work may be required for safe train operation. TMPM outputs the net present value of the financial benefits of undertaking a given maintenance strategy compared with a base-case maintenance scenario. This approach has an advantage over current models in investigating what-if scenarios. The track engineer can assess the possible benefits of reduced operating costs from upgrading track infrastructure or from improving maintenance equipment. Track maintenance and train operating costs also can be simulated over time. The results of applying the model to a test track section using several different maintenance strategies are presented.

scholarly journals A Taxonomy of Railway Track Maintenance Planning and Scheduling: A Review and Research Trends

2021 ◽  
pp. 107827
Author(s):  
Mahdieh Sedghi ◽  
Osmo Kauppila ◽  
Bjarne Bergquist ◽  
Erik Vanhatalo ◽  
Murat Kulahci
Keyword(s):  
Research Trends ◽  
Railway Track ◽  
Maintenance Planning ◽  
Planning And Scheduling ◽  
Track Maintenance

scholarly journals Optimization of work performance of snow removal work trains on the basis of linear programming

2018 ◽  
Vol 239 ◽  
pp. 04001 ◽  
Author(s):  
Aleksey Manakov ◽  
Andrey Abramov ◽  
Andrey Ilinykh ◽  
Vladimir Aksenov
Keyword(s):  
Linear Programming ◽  
Work Performance ◽  
Railway Track ◽  
Rolling Stock ◽  
Snow Removal ◽  
Track Maintenance ◽  
Maintenance Work ◽  
Optimization Methodology ◽  
The Cost ◽  
Removal Equipment

The introduction of monitoring systems for the work performance of special rolling stock and monitoring the load of snow removal work trains revealed a number of shortcomings in the planning, organization, and recording of work performed by snow removal work trains. The elimination of the identified problems is possible on the basis of optimization of work performance, the implementation of which can be achieved on the basis of existing systems with appropriate additional functionality. For this purpose, in the framework of the theoretical studies presented in the paper, a methodology for optimization of work performance of snow removal work trains has been developed. Linear programming is adopted as a method of solving the optimization problem. On the basis of the algorithm for solving the transport problem, the problem of minimizing the cost of snow removal from various sections of the track by the existing park of work trains is formulated, for which a mathematical model is constructed that includes the objective function and the corresponding restrictions. The results of the study show that the widespread use of work planning on the basis of the presented optimization methodology will make it possible to make the most efficient use of snow removal equipment and, as a result, to reduce the cost of this type of railway track maintenance work.

scholarly journals A Roadmap for Sustainable Smart Track—Wireless Continuous Monitoring of Railway Track Condition

2021 ◽  
Vol 13 (13) ◽  
pp. 7456
Author(s):  
J. Riley Edwards ◽  
Kirill A. Mechitov ◽  
Ian Germoglio Barbosa ◽  
Arthur de O. Lima ◽  
Billie F. Spencer ◽  
...  
Keyword(s):  
Conceptual Design ◽  
Ieee 802.15.4 ◽  
Railway Track ◽  
Public And Private ◽  
Expert Opinions ◽  
Track Condition ◽  
Train Operation ◽  
Accident Data ◽  
Monitoring Technologies ◽  
4G Lte

Ensuring safe train operation, minimizing service interruptions, and optimizing maintenance procedures are primary railway industry focus areas. To support these goals, a multi-disciplinary team of researchers at the University of Illinois at Urbana-Champaign proposed a wireless, continuous, and accurate methodology to monitor track conditions. This project, referred to as “Smart Track”, included the development of a conceptual design plan for efficient and effective implementation of smart monitoring technologies. The project began by establishing guiding research questions, and revising those questions based on track-caused accident data obtained from the Federal Railroad Administration (FRA) and expert opinions from rail experts in the public and private sectors. Next, the research team combined these findings and developed metrics for assigning risk and priorities to various track assets and inspection needs. In parallel, the project team conducted a survey of available wireless technologies for intra-site and site-to-cloud communications. These capabilities were mapped to instrumentation types and requirements (e.g., strain gauges, accelerometers) to ensure compatibility in terms of energy consumption, bandwidth, and communications range. Results identified the rail, crosstie and support, ballast and sub-structure, bridge deck and support, and special trackwork as priority locations for instrumentation. Additionally, IEEE 802.15.4 was found to be the most appropriate cellular communication system within field sites and 4G LTE cellular was determined to be the wireless technology best suited for field site-to-cloud communication. The conceptual design presented in this paper is the first step in achieving the broader goal of Smart Track; to improve the rail industry’s ability to answer critical safety and maintenance-related questions related to the track infrastructure by monitoring and predicting track health.

scholarly journals Developing an Enhanced Short-Range Railroad Track Condition Prediction Model for Optimal Maintenance Scheduling

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Prediction Method ◽  
Maintenance Scheduling ◽  
Railroad Track ◽  
Track Geometry ◽  
Track Maintenance ◽  
Track Condition ◽  
Optimal Maintenance ◽  
Process Work

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

scholarly journals Random-Forest Machine Learning Approach for High-Speed Railway Track Slab Deformation Identification Using Track-Side Vibration Monitoring

2021 ◽  
Vol 11 (11) ◽  
pp. 4756
Author(s):  
Gaoran Guo ◽  
Xuhao Cui ◽  
Bowen Du
Keyword(s):  
Random Forest ◽  
High Speed ◽  
Recognition Rate ◽  
Operation Time ◽  
Deformation Monitoring ◽  
Vibration Monitoring ◽  
Railway Track ◽  
Ballastless Track ◽  
Train Operation ◽  
Track Slab

High-speed railways (HSRs) are established all over the world owing to their advantages of high speed, ride comfort, and low vibration and noise. A ballastless track slab is a crucial part of the HSR, and its working condition directly affects the safe operation of the train. With increasing train operation time, track slabs suffer from various defects such as track slab warping and arching as well as interlayer disengagement defect. These defects will eventually lead to the deformation of track slabs and thus jeopardize safe train operation. Therefore, it is important to monitor the condition of ballastless track slabs and identify their defects. This paper proposes a method for monitoring track slab deformation using fiber optic sensing technology and an intelligent method for identifying track slab deformation using the random-forest model. The results show that track-side monitoring can effectively capture the vibration signals caused by train vibration, track slab deformation, noise, and environmental vibration. The proposed intelligent algorithm can identify track slab deformation effectively, and the recognition rate can reach 96.09%. This paper provides new methods for track slab deformation monitoring and intelligent identification.

Undersaturated Hydrocarbon Reservoir Waterflooding: A simulation Approach to Performance Assessment

2021 ◽  
Author(s):  
Adekunle Tirimisiyu Adeniyi ◽  
Miracle Imwonsa Osatemple ◽  
Abdulwahab Giwa
Keyword(s):  
Oil Recovery ◽  
Net Present Value ◽  
Oil Production ◽  
Base Case ◽  
Present Value ◽  
Sweep Efficiency ◽  
Recovery Method ◽  
Solution Approach ◽  
Hydrocarbon Reservoir

Abstract There are a good numbers of brown hydrocarbon reservoirs, with a substantial amount of bypassed oil. These reservoirs are said to be brown, because a huge chunk of its recoverable oil have been produced. Since a significant number of prominent oil fields are matured and the number of new discoveries is declining, it is imperative to assess performances of waterflooding in such reservoirs; taking an undersaturated reservoir as a case study. It should be recalled that Waterflooding is widely accepted and used as a means of secondary oil recovery method, sometimes after depletion of primary energy sources. The effects of permeability distribution on flood performances is of concerns in this study. The presence of high permeability streaks could lead to an early water breakthrough at the producers, thus reducing the sweep efficiency in the field. A solution approach adopted in this study was reserve water injection. A reverse approach because, a producing well is converted to water injector while water injector well is converted to oil producing well. This optimization method was applied to a waterflood process carried out on a reservoir field developed by a two - spot recovery design in the Niger Delta area of Nigeria that is being used as a case study. Simulation runs were carried out with a commercial reservoir oil simulator. The result showed an increase in oil production with a significant reduction in water-cut. The Net Present Value, NPV, of the project was re-evaluated with present oil production. The results of the waterflood optimization revealed that an increase in the net present value of up to 20% and an increase in cumulative production of up to 27% from the base case was achieved. The cost of produced water treatment for re-injection and rated higher water pump had little impact on the overall project economy. Therefore, it can conclude that changes in well status in wells status in an heterogenous hydrocarbon reservoir will increase oil production.

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