The Netherlands has an internationally leading position regarding logistics and is renowned for its advanced multimodal logistics infrastructure and extensive network of corridors and hubs. However, the performance and reliability of corridors heavily depend on inland shipping, which are under pressure due to climate change and a variety of disruptions. Disruptive events (e.g., drought, flooding and infrastructure failure/downtime) reveal vulnerabilities of corridors and bring negative cascading effects on their performance. Changing the ecological system and physical infrastructure is costly and time consuming (due to consultation and public participation procedures). However, the logistics system can be redesigned to create resilient and climate adaptive corridors.
Digital Twinning (DT) of different urban assets and systems has gained significant popularity in recent years. In this practice, a living and dynamic model of the asset is developed to reflects current status of the asset through the use of (near) real-time data. An accurate DT of a physical asset allows for: (1) assessing the performance of the physical asset using available information such as environmental and operational actions (e.g., ambient temperature/radiation, precipitation, water level) and the structural system’s response to the actions (e.g., soil saturation, water excess/deficiency), and (2) simulating likely scenarios negatively affecting the system, such as floods, draughts, failures of locks, and finding solutions for a quick recovery or adaptiveness of the system (Negi et al. 2023).
In addition to the physical aspects of the envisioned DT, it will serve the purpose of optimizing the logistics in multimodal corridors and supply chains. Policy makers will utilize the DT for decision making regarding investments in physical infrastructure. This way, the DT will become a multi-purpose DT of a multi-modal corridor. Such DT can be deployed for a variety of use cases, applications, scenarios, which come from different perspectives. This activity focuses on the development of a multi-purpose DT.
To the best of our knowledge, no operational DT exists for multimodal logistics corridors. Therefore, The aim of the Engineering Doctorate (EngD) candidate is to develop a robust DT that is integrated with appropriate simulation techniques.
The following questions will be addressed:
- What inputs (e.g., geometry data, material properties, logistics information) are needed to create a multi-purpose DT?
- What are the main modules, components and interfaces of the DT?
- Which models are best suited to support simulation, analysis and optimization?