Integration of Multiphysics Methods in Aerospace System Design: Selected Case Studies

This paper presents a concise analytical review of selected case studies on the integration of multiphysics methods in aerospace structural design, with emphasis on rocket and high-speed vehicle applications. The review synthesizes peer-reviewed publications (2022–2025) indexed in Web of Science and Scopus that address coupled Computational Fluid Dynamics—Finite Element Method (CFD–FEM) analyses, fluid–structure interaction (FSI), conjugate heat transfer (CHT), ablation and thermal protection modeling, and multidisciplinary design optimization (MDO) incorporating surrogate and machine-learning accelerants. Source selection and evaluation prioritized methodological transparency, relevance to structural design tasks, and applicability of results to engineering practice. The surveyed studies indicate that fully coupled CFD–FEM and FSI formulations are capable of reproducing key interactions among aerodynamic, thermal and structural fields, while posing significant numerical and computational demands related to mesh compatibility, stiffness of governing equations and temporal integration. CHT approaches yield improved estimates of interfacial heat fluxes for nozzles and TPS elements when turbulent flow models are combined with wall conduction models. Multidimensional ablation models provide mechanistic insight into material removal processes but require careful treatment of thermochemical coupling and validation against experimental data. Recent developments in multifidelity optimization and gradient-enhanced surrogate models demonstrate potential to reduce computational cost in MDO workflows without discarding essential physics. Given the limited scope inherent to a concise analytical review, conclusions are presented as informed recommendations rather than exhaustive generalizations. Recommended practical measures for engineering application include: explicit consistency of boundary and initial conditions across disciplinary solvers; use of adaptive local mesh refinement in regions of strong gradients; adoption of hybrid coupling strategies (e.g., weak/iterative coupling, multiscale and multifidelity frameworks) to balance accuracy and cost; and integration of surrogate or data-driven models into optimization loops with rigorous uncertainty quantification and targeted validation for TPS, nozzle and thin-walled components. These recommendations aim to support practitioners and researchers seeking to improve predictive capability and computational...<p></p>