Hyperloop is frequently proposed as a low-emission alternative for short-haul aviation, but to determine whether it is a viable substitute, the capacity of a hyperloop network must be assessed. Existing literature either analyzes small networks or does not model the full operations, leaving a gap in understanding system-level feasibility at European scale. In particular, it remains unclear which starter network best balances the two competing objectives of a first deployment: serving as much passenger demand as possible while requiring as little costly infrastructure as possible. This study investigates to what extent a simple first European hyperloop network can substitute short-haul air travel demand. The method used is three phased; first an cost-optimal European hyperloop network is defined using a multi-commodity flow problem, with short-haul air passenger travel demand between approximately 100 large European airports as input. The optimization produced a 19-station, 20-link starter network. The resulting straight-line links were then translated into infrastructure-realistic alignments by routing through OpenStreetMap rail and road geometry with curvature-based smoothing. This network and other operational parameters serve as input for a 24-hour SimPy discrete-event simulation, modeling hyperloop operations in detail, incorporating per-link vacuum headway, pod dwell, and bounded fleet size. The simulation is run under several input variations to show the performance of the hyperloop system under different circumstances. Results show that this first hyperloop network can deliver around 64 million passengers yearly under conditions of varying demand and disruptions, which is equivalent to 15.7% of total intra European air demand. These findings indicate that the proposed hyperloop network is a viable starting point for an eventually complete European hyperloop network. The recommendation is that the complete network should be planned and analyzed before implementation and construction, as bottlenecks and design parameters such as pod capacity and headway have large impacts on final system capacity. Therefore, choices like fleet and vehicle sizing should be determined jointly with the network topology.
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