Impact of Symmetric Vertical Sinusoid Alignments on Infrastructure Construction Costs: Optimizing Energy Consumption in
- PDF / 1,318,306 Bytes
- 12 Pages / 595.276 x 790.866 pts Page_size
- 71 Downloads / 163 Views
http://www.urt.cn/
ORIGINAL RESEARCH PAPERS
Impact of Symmetric Vertical Sinusoid Alignments on Infrastructure Construction Costs: Optimizing Energy Consumption in Metropolitan Railway Lines Using Artificial Neural Networks J Pineda-Jaramillo1 R. Insa-Franco2
•
P. Salvador-Zuriaga2 • P. Martı´nez-Ferna´ndez2
•
Received: 11 March 2019 / Revised: 20 December 2019 / Accepted: 1 June 2020 The Author(s) 2020
Abstract Minimizing energy consumption is a key issue from both an environmental and economic perspectives for railways systems; however, it is also important to reduce infrastructure construction costs. In the present work, an artificial neural network (ANN) was trained to estimate the energy consumption of a metropolitan railway line. This ANN was used to test hypothetical vertical alignments scenarios, proving that symmetric vertical sinusoid alignments (SVSA) can reduce energy consumption by up to 18.4% compared with a flat alignment. Finally, we analyzed the impact of SVSA application on infrastructure construction costs, considering different scenarios based on top–down excavation methods. When balancing reduction in energy consumption against infrastructure construction costs between SVSA and flat alignment, the extra construction costs due to SVSA have a return period of 25–300 years compared with a flat alignment, depending on the soil type and construction method used. Symmetric vertical sinusoid alignment layouts are thus suitable for scattered or soft soils, up to compacted intermediate geomaterials. Keywords Infrastructure construction costs on railways Symmetric vertical sinusoid alignments Optimization of energy consumption Artificial neural networks (ANN)
& J Pineda-Jaramillo [email protected] 1
Planning Department Office, Government of Antioquia, Medellı´n, Colombia
2
Department of Transport Infrastructure and Engineering, Universitat Polite`cnica de Vale`ncia, Valencia, Spain
1 Introduction The International Energy Agency reported up to 9555 million tonnes of oil equivalent (Mtoe) of energy consumption in the world in 2016. The transport sector consumes 28.8% of that energy, hence demonstrating its significant impact on global energy consumption [1]. Railways are more efficient in terms of energy consumption than road transport for both passengers and freight [2–4]. For example, despite carrying about 8% and 17% of passengers and freight across Europe, respectively (EU-28), European railways only represent about 2% of the energy consumed by the transportation sector [5]. However, it is necessary to continue reducing railways energy consumption so as to improve its competitiveness. For this reason, many strategies have been implemented to improve railways efficiency, focused on aspects as diverse as track geometry, rolling stock, driving schemes, or line operation. The most common strategy is to focus on driving schemes because these allow higher rates of efficiency [6–8]. Previous studies have tried to reduce energy consumption focusing on manually driven trains [9, 10] and o
Data Loading...
