Discrete Element Modeling Of Railroad Ballast Under Simulated Train Loading

Ballasted tracks have been widely used in many countries around the world. Ballast layer is the main element in ballasted track. After service, ballast aggregates degrade and deform. Periodical maintenance for ballast layer is required; which is a cost and time expensive activity. Researchers used numerical approaches to understand the behavior of railroad ballast that leads to efficient design and maintenance. The Discrete Element Method (DEM) has been used increasingly to understand the mechanical behavior of railroad ballast, more frequently through box test. Most researches in the literature simulate the train loading as a pure continuous sinusoid based on train speed and axle spacing; unlike the actual loading induced by trains. This study aims to show the influence of simulated train loadings on ballast mechanical behavior using DEM via box test. The study utilizes the theory of Beam on Elastic Foundation to simulate a more realistic train load. The results from the more realistic simulated train load are compared with those from a sinusoidal load. The compared results highlight the influence of the simulated train load on the mechanical behavior of railroad ballast.Author: " I would like to acknowledge Qatar Rail for their sponsorship to this research under a project entitled “Framework for Research on Railway Engineering” with a grant reference number: QUEX-CENG-Rail 17/18.

Comparison of the Mechanical Behavior of Railroad Ballast in a Box Test under Sinusoidal and Realistic Train Loadings Using Discrete Element Method

A ballasted track is a popular type of railway track and its use is increasing all over the world. A ballasted track consists of different structural elements like rails, fasteners, sleepers, ballast layer, sub-ballast layer and subgrade. A ballast layer is considered as the main structural element of ballasted tracks; it has a significant contribution to track stability and alignment. After service, periodical maintenance of ballast layer is required to maintain its functionality. Ballast maintenance is a cost and time expensive operation. Better understanding of ballast mechanical behavior leads to better ballast design and efficient maintenance. Discrete Element Method has been used extensively in the literature to understand the mechanical behavior of railroad ballast in a box test. Nevertheless, in the literature most of the studies simulate train loading as pure continuous sinusoidal loading unlike the real train loading. This paper aims to investigate the influence of the simulated train loading on the mechanical behavior of railroad ballast after 1000 loading cycles. There are two simulated train-loading cases used in this study for comparison purposes; continuous sinusoidal loading and a more realistic train loading utilizing the Beam on Elastic Foundation theory. The results show a difference of ballast vertical settlement up to 14% between the two simulated train-loading cases

Geomechanical Modelling of Railroad Ballast: A Review

Traditional ballasted tracks have been used intensively around the world with ballast as the main material for tracks. Ballast has a significant contribution to the track alignment, stability and sustainability. After service, ballast deforms and degrades. Periodic ballast maintenance is needed which is a time and cost expensive activity. Understanding the mechanical behaviour of railroad ballast leads to better design and efficient maintenance. From the literature, there are two main approaches used to understand the mechanical behaviour of railroad ballast; large scale experimental and modelling. This paper aims to review the state of the art of literature on the modelling approaches used to understand ballast mechanical behaviour. It discusses the key findings from each modelling approach in understanding ballast mechanical behavior. It presents the main concerns and limitations of each modelling approach from different perspectives related to ballast modelling. It summarizes the limitations, gaps and gaps' developments of the researches used to understand ballast behaviour via modelling approach.Open Access funding provided by the Qatar National Library. This work has been carried out under a research project entitled "Framework for Research on Railway Engineering" which is supported by a grant sponsored by Qatar Rail with a grant reference number: QUEX-CENG-Rail 17/18.Scopu

New Technique for Flood Risk Assessment of Sub-Networks in Large Networks Using InfoWorks ICM: A Case Study of Qatar's Full Storm Water Network

The elements of the storm water network are made to safely drain most water during a heavy rainstorm. Flood risk modelling (mathematical modelling) with hydraulic software is a good way to check the network's level of service, especially now that technology has changed. Flood risk modelling is an essential method for checking the network sufficiency and adequacy for different kinds of rain. Modelling flood risk should be done for the whole network to ensure that flows are connected and get accurate results. In this study, one-dimensional flood risk modelling is needed for a sub-network that is part of Qatar's full storm water network. The flood risk modelling is conducted using InfoWorks ICM software. Running the whole model takes a lot of computational data processing. Splitting the entire stormwater network to the concerned sub-network without considering the hydraulic effects of upstream and downstream flows at the boundary conditions of the sub-network will lead to erroneous conclusions. In this research, a new method for hydraulically dividing the network into sub-networks is presented, taking into account the characteristics of the boundaries. This method increases the efficiency and viability of hydraulic modelling for sub-networks in big networks. For purposes of validation, the results of the reduced model in terms of flood depths and volumes are compared with those of the full model. The results of the split model are in good agreement with the entire model

Investigating the behavior of railroad ballast in a box test under sinusoidal & simulated train loading

The use of railway transportation systems has been increased throughout the years. Conventional ballasted tracks have been widely used in many countries around the world. Ballast material is the basic element in ballasted track, it degrades and deforms after service. Therefore, periodical ballast maintenance is required which is a cost and time expensive activity. Understanding of ballast behavior leads to efficient design and maintenance. From the literature, Discrete Element Method is used extensively to understand the behavior of railroad ballast through box test. However, most researches in the literature simulate the train loading as a pure continuous sinusoid unlike the actual loading induced by the trains. This paper aims to show the influence of simulated loading of moving train on the dynamic behavior of railroad ballast using box test via DEM. The paper utilizes the theory of Beam on Elastic Foundation to simulate a more realistic loading on railroad ballast. The results from the simulated train load are compared with those from a sinusoidal load. The results show a difference up to 6.89% between simulated train and sinusoidal loading. Copyright 2019 COMPDYN Proceedings. All rights reserved.This work has been carried out under a research project entitled "Framework for Research on Railway Engineering" which is supported by a grant sponsored by Qatar Rail with a grant reference number: QUEX-CENG-Rail 17/18.Scopu

Large-scale triaxial and box testing on railroad ballast: a review

The use of railway transportation systems has been increased throughout the years. The conventional ballasted tracks have been used widely in many countries around the world. Ballast material is the basic element of ballasted tracks. Ballast degrades and deforms after service. Therefore, periodical ballast maintenance is needed which is a cost and time expensive activity. Understanding ballast mechanical behavior leads to better design and efficient maintenance. From the literature, experimental approach is used to understand the mechanical behavior of railroad ballast. Traditional experimental tests provide inaccurate results due to the large ballast particle size with relative to sample size. Researchers used large scale triaxial and box tests extensively to understand the mechanical behavior of railroad ballast. The target of this paper is to present a concise review of the extensive literature presented on the mechanical behavior of railroad ballast using large scale triaxial and box testing. It discusses the various aspects of large-scale equipment such as apparatus’ set-up, size, material and shape, simulated load condition and test purpose. It presents the key findings of the large-scale triaxial and box tests in understanding ballast mechanical behavior.Other Information Published in: SN Applied Sciences License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s42452-019-1459-3</p

Geomechanical Modelling of Railroad Ballast: A Review

Traditional ballasted tracks have been used intensively around the world with ballast as the main material for tracks. Ballast has a significant contribution to the track alignment, stability and sustainability. After service, ballast deforms and degrades. Periodic ballast maintenance is needed which is a time and cost expensive activity. Understanding the mechanical behaviour of railroad ballast leads to better design and efficient maintenance. From the literature, there are two main approaches used to understand the mechanical behaviour of railroad ballast; large scale experimental and modelling. This paper aims to review the state of the art of literature on the modelling approaches used to understand ballast mechanical behaviour. It discusses the key findings from each modelling approach in understanding ballast mechanical behavior. It presents the main concerns and limitations of each modelling approach from different perspectives related to ballast modelling. It summarizes the limitations, gaps and gaps’ developments of the researches used to understand ballast behaviour via modelling approach.Other Information Published in: Archives of Computational Methods in Engineering License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s11831-019-09390-4</p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population