Postdoc: Validating a Digital Twin for Evaluating Emission Reduction Strategies for Inland Shipping

Descrizione

Postdoc: Validating a Digital Twin for Evaluating Emission Reduction Strategies for Inland Shipping Sintesi in italiano (traduzione automatica): L'organizzazione internazionale cerca un ricercatore post-dottorato per il progetto NWO 'PATH2ZERO', finalizzato a sviluppare strategie per la riduzione delle emissioni nel trasporto fluviale. La sede del lavoro è in un contesto di ricerca interdisciplinare, dove il candidato utilizzerà dati reali delle navi e tecnologie di digital twin per valutare l'efficacia delle politiche e delle tecnologie proposte. È richiesta una laurea di dottorato in Trasporti, Logistica, Ingegneria Civile, Ingegneria Meccanica, Ingegneria Marittima o campi affini. Le mansioni principali includono la modellazione agent-based e l'analisi di grandi dataset, con un forte focus sulla collaborazione con stakeholder e ricercatori. Il candidato ideale deve possedere competenze avanzate in modellazione e analisi dei dati, oltre a una predisposizione per l'apprendimento di nuove tecnologie. Use real-world vessel data, agent-based modelling and digital twin technology to accelerate the transition toward zero-emission inland shipping. Job description The postdoctoral research is part of the NWO project “PAving THe way towards Zero-Emission and RObust inland shipping (PATH2ZERO)”, which aims to develop breakthrough action perspectives and sustainable business models for all parties in the inland shipping chain, contributing to the transition to emission-free inland shipping. The main objective of the project is the evaluation of zero-emission strategies, the effectiveness of policies and technologies, and the assessment of the consequences of their implementation on the inland shipping system. One aim of the PATH2ZERO project is to translate research outcomes into practice, so that end users can make better-informed decisions. For this purpose, PATH2ZERO aims to develop a digital twin. The main goal of this data-driven virtual representation of the inland waterway transport system is to assess the efficiency of proposed solutions for emissions reduction in inland waterway transport. Three main aspects are regarded as vital components of the digital twin: the individual vessels, fleet and its operations, and the infrastructure. As these components require a detailed representation within a large-scale transport system, a meso-scale agent-based approach has been selected as a suitable basis for the digital twin. This enables the assessment of potential interventions, ranging from the application of new technologies to individual vessels to policy measures that are implemented for an entire shipping corridor, or various bunker infrastructure strategies in the network. In addition, the impact of the feasible interventions can be evaluated, ranging from the individual ship level and its emissions to the network level and the aggregated emissions in an entire area, or the impact on the logistics chain. For validating the digital twin, real-world data sources (AIS data, hydrodynamic data, infrastructure data, etc.) will be used in combination with already existing tools for maritime traffic simulation (e.g., OpenTNSim, which is being developed at TU Delft), energy consumption estimates, and emission algorithms. The relevant processes at the individual vessel level can be modelled in detail, and their performance can be tracked in time and space. Corridor scale effects will be simulated by aggregating the results of multiple vessels that together represent the corridor's traffic. Three regions will be modelled as areas of interest: the Rotterdam – Basel corridor (an open waterway, that is vulnerable to high and low discharge events), the Rotterdam – Antwerp / Gent corridor (a closed waterway that includes various locks and short-sea shipping), and the larger Port of Rotterdam region (a region that includes both sea-going and inland vessels in an area subject to currents and tides). While the scope of this research focuses on validating a digital twin using operational data from inland vessels, it is expected to involve close collaboration with project stakeholders and researchers within the project. This collaboration will contribute to the quantitative assessment of emission reduction strategies, paving the way toward zero-emission inland shipping. Job requirements We are looking for a candidate with an interdisciplinary track record who is able to integrate engineering, environmental, and social science knowledge into a new framework for zero-emission inland shipping. This position requires outstanding skills in modelling and working with big datasets. In addition, the applicants should have: PhD diploma in Transportation, Logistics, Civil Engineering, Mechanical Engineering, Maritime Engineering, or any other related field. Experience with agent-based modelling is essential. Experience with big data analytics, Python, and an affinity for acquiring new skills in this area. Ability to collaborate with both