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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 15087

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Special Issue Editors

Dr. Pedro Aires Montenegro

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Guest Editor

CONSTRUCT-LESE, Faculty of Engineering, University of Porto, Porto, Portugal
Interests: railway infrastructures; railway engineering; bridge dynamics; vehicle dynamics; train-bridge interaction; fatigue of railway bridges; structural engineering
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Prof. Dr. Diogo Ribeiro

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Guest Editor

Department of Civil Engineering, School of Engineering, Polytechnic of Porto, 4200-072 Porto, Portugal
Interests: railway infrastructures; dynamic testing; damage identification; remote inspection; data science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the 21st century, with globalization playing an increasingly important and influential role in societies and markets, the development of new transport infrastructures that allow the efficient movement of passengers and goods is of the utmost importance. Railway transport has been playing a key role in this context, contributing to the sustainable development of countries in terms of both economic growth and social development. This type of transport has several advantages over others, mostly related to the lower transportation costs involved, lower environmental impacts, and improved safety. Additionally, the reduction in travel time due to the increase in speed and improvement in passenger comfort also contribute to the greater competitiveness of rail transport.

In recent years, important investments have been made in the construction of new railway infrastructures, as well as in the rehabilitation and upgrading of existing lines. Many of these lines include a significant number of critical infrastructure elements, such as bridges, viaducts, and embankments, whose operational and safety conditions have to be preserved by infrastructure managers during their life cycle. Recent scientific and technological advancements have enabled the more efficient structural condition assessment of railway infrastructures, mainly through the implementation of intelligent strategies for inspection, monitoring, maintenance, and risk management. Moreover, the investment in the development of faster and lighter trains also poses important challenges in terms of the energy efficiency of this type of vehicle. Hence, within the framework outlined above, this Special Issue invites the submission of innovative research, reviews, case studies, and successful applications of solutions that aim to contribute to a more sustainable railway system. Theoretical, experimental, and computational investigations (or a combination of these) are welcome. Papers should cover various topics related (but not limited) to: structural integrity; sustainability in the construction of railway infrastructure; sustainable rolling stock; vehicle dynamics; structural condition assessment; digital twins; model calibration and validation; structural health monitoring; new sensors and technologies (photogrammetry, laser scanning, drones, wireless); computer vision techniques; automated damage identification; remote inspection strategies; BrIM (Bridges Information Modelling); big data; artificial intelligence (supervised and unsupervised learning); augmented reality; virtual reality; disaster risk reduction; emergency management; and intelligent asset management.

Dr. Pedro Aires Montenegro
Prof. Dr. Diogo Ribeiro
Guest Editors

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Keywords

railway transportation
railway engineering
railway infrastructure
bridges
rolling stock
sustainable transportation
smart condition assessment
structural health monitoring

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Published Papers (7 papers)

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Research

24 pages, 3776 KiB

Open AccessArticle

Modelling and Dynamic Analysis of Adaptive Neuro-Fuzzy Inference System-Based Intelligent Control Suspension System for Passenger Rail Vehicles Using Magnetorheological Damper for Improving Ride Index

by Sunil Kumar Sharma, Rakesh Chandmal Sharma, Yeongil Choi and Jaesun Lee

Sustainability 2023, 15(16), 12529; https://doi.org/10.3390/su151612529 - 18 Aug 2023

Cited by 11 | Viewed by 1326

Abstract

The ride comfort and safety of passenger rail vehicles depend on the performance of the suspension system in attenuating vibrations induced by track irregularities. This paper investigates the effectiveness of an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based semi-active controlled suspension system using a magnetorheological fluid damper in reducing nonlinear lateral vibrations of a passenger rail vehicle. A complete rail vehicle model is developed, including the carbody, front and rear bogies, and the passive suspension system’s nonlinear stiffness and damping characteristics are considered from experimental data. The passive suspension model is validated through experiments, and an ANFIS-based controller is incorporated with the secondary vertical suspension system to improve ride behavior. Three semi-active suspension strategies are considered under varying speeds and track irregularities, and their effectiveness is compared to the nonlinear passive suspension system in terms of rms acceleration, rms displacement, ride quality, and comfort. The results shows that the ANFIS-based semi-active suspension system with a magnetorheological fluid damper outperforms the passive suspension system and semi-active strategies in all tested conditions. There is a reduction in rms acceleration by approximately 11.11% to 23.64% and rms displacement by about 5.36% to 32.06%. Moreover, it significantly improves ride quality (9.20% to 31.02%) and comfort (9.96% to 31.50%). The rms acceleration and displacement are reduced, and the Sperling ride index and Percentage Reduction Index values demonstrate that the ANFIS-based semi-active suspension effectively minimizes the impact of rail irregularities and vibrations, resulting in a significant gain in ride quality and passenger comfort. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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15 pages, 1864 KiB

Open AccessArticle

Life Cycle Assessment of Current Portuguese Railway and Future Decarbonization Scenarios

by Tiago Ramos da Silva, Bruna Moura and Helena Monteiro

Sustainability 2023, 15(14), 11355; https://doi.org/10.3390/su151411355 - 21 Jul 2023

Cited by 4 | Viewed by 2119

Abstract

Given the current EU decarbonization targets, the railway transport is a key player to boost mobility toward more sustainable transportation, as it is currently the cleanest high-volume mode of locomotion available. However, a study analyzing the life cycle environmental impact of the existing conventional Portuguese railway has never been performed. Aiming to address this research gap, this paper presents an attributional life cycle assessment (LCA) to quantify the environmental impacts of the Portuguese railway infrastructure and rolling stock, using the Douro line case study. Through the LCA methodology, the current setting (using electric and diesel rolling stock) and three scenarios of full-line electrification (considering 2019, 2030, and 2050 electricity mixes) were analyzed for hotspot identification and an outlook on EU-aligned long-term sustainability prospects. In the current scenario, railway operation accounts for 74% of the total carbon footprint, mostly due to the fuel use of diesel trains and the expended electricity of electric train and infrastructure operation. The total electrification of the line and rolling stock can reduce carbon emissions by 38%, 56%, and 63%, if the 2019, 2030, and 2050 electricity mixes are considered, respectively. Further reductions could also be achieved with on-site renewable energy generation and through future low-carbon construction work strategies. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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20 pages, 3634 KiB

Open AccessArticle

Investigation of Dynamic Processes of Rolling Stock–Track Interaction: Experimental Realization

by Iryna Bondarenko, Vaidas Lukoševičius, Robertas Keršys and Larysa Neduzha

Sustainability 2023, 15(6), 5356; https://doi.org/10.3390/su15065356 - 17 Mar 2023

Cited by 9 | Viewed by 1628

Abstract

The dynamic process of the railway track–rolling stock interaction is characterized by time-dependent dynamics that are determined by both the varying characteristics of the interaction objects and the varying climatic conditions. This study investigated the effect of different groups of influence on the dynamic process, with a view towards the reduction of the cases of randomness during the registration of the process in experiments and an expansion of the understanding of the processes happening during the assessment of the registered data. The static nature of the rolling stock has been demonstrated to be not uniform and to influence the scattering of dynamic values under the variation of vertical and horizontal forces due to the characteristics of a rolling stock. The position of the rolling stock truck relative to the track axis during the movement of the rolling stock has been shown to enhance static non-uniformity. The results of the longitudinal force measurements under the three-point and Schlumpf methods have suggested that it is necessary to investigate the process of rail warping under the action of the rolling stock wheels. To enhance the output of the experiments, it is proposed to consider not only the stiffness of the basis of the oscillatory processes that imitate the physical process of oscillation of the system elements by means of the oscillation amplitude, but also the time of response to the oscillation process by using and assessing the triggering time rather than the frequencies of the oscillation processes. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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19 pages, 6698 KiB

Open AccessArticle

Optimization Study on the Design Parameters of Sand Barriers along the Hami-Lop Nor Railway Line

by Fei Li, Weiqiang Zheng, Liping Zhang, Haifeng Wang and Zehui Wang

Sustainability 2023, 15(6), 5297; https://doi.org/10.3390/su15065297 - 16 Mar 2023

Cited by 3 | Viewed by 1403

Abstract

In order to solve the current problems of the single effect of traditional sand control measures, the high cost of cleaning and maintenance, and the inability to provide long-term sustainable protection, this paper proposes a new type of sand barrier with the dual effect of sand conduction and sand blocking. Through field research of wind and sand disasters along the Hami-Lop Nor Railway, wind tunnel testing and numerical simulation of the new sand barrier, the wind velocity flow field, wind speed variation curve, wind protection effectiveness and sand barrier retention rate of the new sand barrier under different design parameters were studied. The results show that the sand barrier with 10H spacing (H is the height of the sand barrier) has the worst sand guiding and blocking effect. The sand barriers with 6H and 8H spacing have less difference in sand guiding and sand blocking effects. Both of them are better than the sand barrier with 10H spacing. The sand blocking effect of the new sand barrier was proportional to the angle (α). The sand guide effect was the opposite. When the angle is certain, the greater the wind speed and the better the sand guide effect. The results show that the new sand barrier is different from the traditional sand barrier in that it has both sand guiding and sand blocking functions, which provides a new method and scientific basis for sand damage control of Hami-Lop Nor Railway. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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17 pages, 4720 KiB

Open AccessArticle

Evolution of Rail Contact Fatigue on Crossing Nose Rail Based on Long Short-Term Memory

by Lei Kou, Mykola Sysyn, Jianxing Liu, Olga Nabochenko, Yue Han, Dai Peng and Szabolcs Fischer

Sustainability 2022, 14(24), 16565; https://doi.org/10.3390/su142416565 - 10 Dec 2022

Cited by 2 | Viewed by 1933

Abstract

The share of rail transport in world transport continues to rise. As the number of trains increases, so does the load on the railway. The rails are in direct contact with the loaded wheels. Therefore, it is more easily damaged. In recent years, domestic and foreign scholars have conducted in-depth research on railway damage detection. As the weakest part of the track system, switches are more prone to damage. Assessing and predicting rail surface damage can improve the safety of rail operations and allow for proper planning and maintenance to reduce capital expenditure and increase operational efficiency. Under the premise that functional safety is paramount, predicting the service life of rails, especially turnouts, can significantly reduce costs and ensure the safety of railway transportation. This paper understands the evolution of contact fatigue on crossing noses through long-term observation and sampling of crossing noses in turnouts. The authors get images from new to damaged. After image preprocessing, MPI (Magnetic Particle Imaging) is divided into blocks containing local crack information. The obtained local texture information is used for regression prediction using machine-supervised learning and LSTM network (Long Short-Term Memory) methods. Finally, a technique capable of thoroughly evaluating the wear process of crossing noses is proposed. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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26 pages, 7163 KiB

Open AccessArticle

Feasibility of Applying Mel-Frequency Cepstral Coefficients in a Drive-by Damage Detection Methodology for High-Speed Railway Bridges

by Edson Florentino de Souza, Túlio Nogueira Bittencourt, Diogo Ribeiro and Hermes Carvalho

Sustainability 2022, 14(20), 13290; https://doi.org/10.3390/su142013290 - 16 Oct 2022

Cited by 7 | Viewed by 2395

Abstract

In this paper, a drive-by damage detection methodology for high-speed railway (HSR) bridges is addressed, to appraise the application of Mel-frequency cepstral coefficients (MFCC) to extract the Damage Index (DI). A finite element (FEM) 2D VTBI model that incorporates the train, ballasted track and bridge behavior is presented. The formulation includes track irregularities and a damaged condition induced in a specified structure region. The feasibility of applying cepstrum analysis components to the indirect damage detection in HSR by on-board sensors is evaluated by numerical simulations, in which dynamic analyses are performed through a code implemented in MATLAB. Different damage scenarios are simulated, as well as external excitations such as measurement noises and different levels of track irregularities. The results show that MFCC-based DI are highly sensitive regarding damage detection, and robust to the noise. Bridge stiffness can be recognized satisfactorily at high speeds and under different levels of track irregularities. Moreover, the magnitude of DI extracted from MFCC is related to the relative severity of the damage. The results presented in this study should be seen as a first attempt to link cepstrum-based features in an HSR drive-by damage detection approach. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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31 pages, 12945 KiB

Open AccessArticle

Experimental Validation of a Double-Deck Track-Bridge System under Railway Traffic

by Gabriel Saramago, Pedro Aires Montenegro, Diogo Ribeiro, Artur Silva, Sergio Santos and Rui Calçada

Sustainability 2022, 14(10), 5794; https://doi.org/10.3390/su14105794 - 10 May 2022

Cited by 15 | Viewed by 2467

Abstract

This article describes the experimental and numerical evaluation of the dynamic behaviour of the Cascalheira bridge, located on the Northern Line of the Portuguese railway network. The bridge has a short span formed by two filler-beam half-decks, each one accommodating a railway track. The study includes the development of a finite element numerical model in ANSYS^® software, as well as in situ dynamic characterization tests of the structure, namely ambient vibration tests, for the estimation of natural frequencies, modes shapes and damping coefficients, and a dynamic test under railway traffic, particularly for the passage of the Alfa Pendular train. The damping coefficients’ estimation was performed based on the Prony method, which proved effective in situations where the classical methods (e.g., decrement logarithm) tend to fail, particularly in the case of mode shapes with closed natural frequencies, as typically happens with the first vertical bending and torsion modes. The updating of the numerical model of the bridge was carried out using an iterative methodology based on a genetic algorithm, allowing an upgrade of the agreement between the numerical and experimental modal parameters. Particular attention was given to the characterization of the ballast degradation over the longitudinal joint between the two half-decks, given its influence in the global dynamic behavior of this type of double-deck bridges. Finally, the validation of the numerical model was performed by comparing the acceleration response of the structure under traffic actions, by means of numerical dynamic analyses considering vehicle-bridge interaction and including track irregularities, with the ones obtained by the dynamic test under traffic actions. The results of the calibrated numerical model showed a better agreement with the experimental results based on the accelerations evaluated in several measurement points located in both half-decks. In the validation process the vertical stiffness of the supports, as well as the degradation of the ballast located over the longitudinal joint between half-decks, was demonstrated to be relevant for the accuracy and effectiveness of the numerical models. Full article

(This article belongs to the Special Issue Sustainable Railway Infrastructure and Rolling Stock)

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