DON26BZ01-NV035 — Integrated Multidisciplinary Design, Analysis, and Optimization Framework for Hypersonic Boost-Glide Weapons

Award Maximum: $140,000 (Base) / $100,000 (Option) Period of Performance: 6 months (Base) + 6 months (Option) Phase Type: Phase I

OBJECTIVE: Develop and demonstrate an integrated multidisciplinary design, analysis, and optimization (MDAO) framework for hypersonic boost-glide weapons that enables concurrent optimization of vehicle geometry, mission trajectory, and control strategy by leveraging existing modeling tools, incorporating reduced-order models, applying artificial intelligence and machine learning (AI/ML) to accelerate design and reduce computational cost, and providing early insights into system cost estimation, manufacturability, and technology development roadmaps.

DESCRIPTION: The Department of the Navy (DON) requires advanced simulation and optimization capabilities to accelerate the conceptual design and mission planning of hypersonic boost-glide weapons. These systems must deliver long-range strike capabilities, survive extreme thermal and structural environments, and maintain maneuverability for terminal effectiveness against defended targets. Designing such vehicles is highly complex due to the strong coupling between aerodynamic heating, structural loading, control authority, system mass, and mission trajectory.

Conventional design approaches treat these disciplines in isolation and in sequence, often resulting in suboptimal performance, prolonged development timelines, and increased costs. MDAO methods offer a more integrated approach, enabling concurrent consideration of key factors and improved trade space exploration. However, coupling high-fidelity models across multiple domains creates significant computational challenges. Practical MDAO frameworks must incorporate reduced-order models, surrogate approximations, and robust optimization techniques that balance computational efficiency and modeling accuracy.

This SBIR topic seeks innovative tools and methods that support an integrated MDAO framework for the design and optimization of hypersonic boost-glide weapons. Proposals should demonstrate capabilities in the following areas: Aerodynamic and trimmed flight analysis; Aerothermal modeling; Structural analysis; Mass properties and internal system layout; Trajectory and control optimization; System-level integration into an existing or proposed MDAO architecture such as ADAPT or OpenMDAO; Uncertainty quantification and robust optimization; AI/ML methods to accelerate convergence, construct reduced-order models, support adaptive sampling, and enable data-driven design exploration.

PHASE I: Develop a prototype MDAO framework for hypersonic boost-glide weapons. Integrate key modules and demonstrate coupling with existing architectures such as ADAPT or OpenMDAO. Apply the framework to optimize a representative boost-glide vehicle, capturing control surface deflection effects and geometric deformations over a notional trajectory. Evaluate computational efficiency, model fidelity, and extensibility. Prepare a Phase II plan.

PHASE II: Develop a fully integrated MDAO framework that enables co-design of vehicle geometry, trajectory, and control strategies for hypersonic boost-glide weapons. Incorporate launch platform constraints and model in-flight geometric deformations, control surface deflections, and effects such as ablation. Demonstrate manufacturability and cost-informed design on a non-canonical configuration. Leverage AI/ML to accelerate optimization, support surrogate modeling, and enable adaptive, data-driven design exploration. Validate the framework on realistic scenarios and implement workflow automation.

PHASE III DUAL USE APPLICATIONS: Transition the MDAO framework and supporting modules to practical applications within the Department of War and commercial aerospace sectors. Conduct extensive validation and optimization across a broad range of hypersonic vehicle configurations and flight conditions. Support integration into existing design and analysis workflows. Collaborate with industry and DOW stakeholders to ensure compliance with deployment standards. Develop comprehensive training materials, user documentation, and technical support resources.

KEYWORDS: Hypersonics; Multidisciplinary Design, Analysis, and Optimization; MDAO; Computational Fluid Dynamics; Artificial Intelligence / Machine Learning; AI/ML; Software Tools; Aerodynamics