uam4x: A Python-based Framework for Multi-modal UAM Design Space Exploration

Urban Air Mobility (UAM) concepts require multidisciplinary analyses across multiple modes of operation and often involve discrete architectural differences such as propulsion type, rotor configuration, and mission context. Existing optimization and workflow frameworks support continuous design variables but provide limited mechanisms for handling discrete variants, multi-modal vehicle definitions, and vehicle management for UAM vehicles. This paper presents uam4x, an open-source Python framework that addresses these challenges through a structured problem definition representation, a plugin-based execution engine, integrated version control, and a function-based branching script mechanism for constructing analysis scenarios. The framework provides integration of existing tools including Open Vehicle Sketch Pad (OpenVSP), NASA Design and Analysis of Rotorcraft (NDARC), M4 Structures Studio (M4SS), and Intelligent Cross Section Generator (IXGEN) through unified plugin interfaces. Parameter sweeps, nested analyses, and optimization via OpenMDAO are supported within the same architecture. This paper also presents demonstrations that were created to illustrate the various capabilities and integration efforts of the framework.