Opportunity sizing for SNCF
Enhancing Traffic Flow for SNCF with Digital Twin Technology
Highlights
- SNCF explored using linear motor trains to ease congestion on a busy Paris rail segment.
- Piwwop created a digital twin and physical model to simulate traffic and assess train performance.
- Results showed significant capacity improvements and long-term economic benefits, supporting the modernization effort.
Challenge
SNCF, the French national railway company, faced challenges with traffic congestion on a specific rail segment in the Paris region. They sought to explore the potential of using linear motor trains to alleviate this bottleneck and increase traffic capacity. However, they needed to evaluate both the operational feasibility and the economic impact of this shift before making a decision.
Solution
Piwwop developed a digital twin of the rail segment, simulating the entire traffic flow. Alongside this, we built a simplified physical model of the linear motor trains to assess their performance under different conditions. By integrating both models, we were able to analyze how the introduction of linear motor trains would affect traffic throughput on this congested section. Our simulations provided insights into the technical feasibility, including how the trains could reduce congestion and increase overall capacity, while also delivering a comprehensive analysis of the economic impact of the solution.
Impact
Our digital twin simulations demonstrated that the adoption of linear motor trains could significantly increase traffic capacity on the congested segment, alleviating the bottleneck and improving overall network efficiency. The economic analysis showed that while initial infrastructure changes would require investment, the long-term benefits in terms of increased traffic, reduced delays, and energy efficiency would outweigh the costs, providing SNCF with a clear path toward modernization.
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