This paper examines thick mapping as a design-driven research method applied in the educational setting of an international architectural design workshop. The workshop brings together 45 students at different levels and fields of education, academics, and practitioners in a collaborative exercise to co-create new knowledge about mobility at railway stations. Participants reinterpret stations as architectures of interchanges through three thematic lenses of investigation: articulation (flows), light & safety (perception), and interfaces (interaction with users). By combining mixed-media drawings with thick mapping practices, the workshop explores the visible and invisible relationships between mobility infrastructure, architectural space, and human perceptions in stations. The contribution of this paper is threefold: 1- to demonstrate how thick mapping can reveal new spatial narratives, creative potentials, and constraints that define mobility architecture and its experience; 2- to illustrate how it provides a deeper understanding of stations by visualising interactions between multiple scales, systems, modalities, agents, and flows; 3- to show how it supports co-design across different disciplines. Thick mapping thus emerges as a critical collaborative method of production linking research, learning, and design in addressing the complexities of mobility architecture.

Urban air mobility operations, such as flying Uncrewed Aerial Vehicles (UAVs) and small passenger aircraft in and around cities, will be inherently susceptible to the turbulent wind conditions in urban environments. Therefore, understanding UAM aircraft performance under microscale wind disturbances is critical. Gaining such insight is non-trivial due to the lack of sufficient UAM aircraft operational data and the complexities involved in flight testing UAM aircraft. A viable solution to overcome this hindrance is through simulation-based flight testing, data collection, and performance assessment. To support this effort, the present paper establishes a custom Stochastic microscale Wind Model (SWM) capable of efficiently generating high-resolution, spatio-temporally varying urban wind fields. The SWM is validated against wind tunnel test data, and subsequently, the findings are employed to guide targeted refinements of urban wake simulation. Furthermore, to incorporate realistic atmospheric conditions and demonstrate the ability to generate location-specific wind fields, the SWM is coupled with the mesoscale Weather Research and Forecasting (WRF) model. This integrated approach is demonstrated through a case study focused on a potential vertiport site in Milan, Italy, illustrating its utility for assessing operational area-specific UAM aircraft performance and vertiport emplacement.