District heating systems are considered a feasible heating alternative to replace natural gas to mitigate emissions in cities. However, urban transitions are very complex because energy systems often operate in densely populated areas, which gives rise to all kinds of interdependencies in cities. These interdependencies can result in unintended consequences which can indirectly help or hinder urban energy transitions. Understanding these influences the transition to climate neutrality. This research investigates the lessons learned from a project conducted in Rotterdam: a high-density city in the Netherlands which is expanding its district heating systems. We use qualitative system dynamics models to explore the underlying complexity and to recognize indirect consequences of policies. Our results cover both technologically oriented and policy-oriented insights, contributing to the literature on transition governance in cities. On the one hand, the national and urban strategies in the Netherlands activate mechanisms that support cities with district heating systems such as Rotterdam. On the other hand, the same strategies could also lead to a potential rivalry between energy efficiency and energy security, which are both crucial goals in urban transition governance. Participative modeling provides policy-makers with an analytical tool to detect systemic dependencies which can be used to identify synergies and barriers among different energy policy objectives. This helps avoiding potential unintended consequences including the use of carbon-heavy systems and displacing investments from energy efficiency and renewable heating systems.

Purpose: Patients who have medical metallic implants, e.g. orthopaedic implants and pacemakers, often cannot undergo an MRI exam. One of the largest risks is tissue heating due to the radio frequency (RF) fields. The RF safety assessment of implants is computationally demanding. This is due to the large dimensions of the transmit coil compared to the very detailed geometry of an implant. Methods: In this work, we explore a faster computational method for the RF safety assessment of implants that exploits the small geometry. The method requires the RF field without an implant as a basis and calculates the perturbation that the implant induces. The inputs for this method are the incident fields and a library matrix that contains the RF field response of every edge an implant can occupy. Through a low-rank inverse update, using the Sherman–Woodbury–Morrison matrix identity, the EM response of arbitrary implants can be computed within seconds. We compare the solution from full-wave simulations with the results from the presented method, for two implant geometries. Results: From the comparison, we found that the resulting electric and magnetic fields are numerically equivalent (maximum error of 1.35%). However, the computation was between 171 to 2478 times faster than the corresponding GPU accelerated full-wave simulation. Conclusions: The presented method enables for rapid and efficient evaluation of the RF fields near implants and might enable situation-specific scanning conditions.