Design Space Exploration Methodology including AIrcraft Design, Economics and Industrial System Considerations

During high-level decisions for complex aerospace system designs, Top-Level Aircraft Requirements need to be implemented in a wide range of performance, industrial, and economic environments and under the same range of constraints. The trade-offs between the different range of environments are poorly reflected in traditional sequential design methods due to their nonlinear and interdisciplinary nature. In this paper, a Design Space Exploration methodology is discussed with an integration of Model-Based Systems Engineering and Multi-Disciplinary Analysis and Optimization. The goal is to identify, capture, and quantify key trade-offs across the constraint sets. The proposed framework allows rapid iteration in multiple design spaces with low- and medium-fidelity disciplinary models for aircraft performance, logistics modeling, and manufacturer economics. Surrogate modeling ensures traceability while supporting fast evaluation, and the methodology is validated on a derivative single-aisle commercial aircraft where multiple constraints in performance, logistics, and economics are analyzed. The approach demonstrates feasible design spaces, supports informed decision-making across stakeholders, and analyzes system-level feasibility early in the conceptual design phase using an interactive dashboard embedding metrics from performance, industrial, and economic domains.