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

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This topic was temporarily posted by the Department of War SBIR Program on March 2nd 2026 and removed the following day.
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Funding Amount:

Est. $240,000

Deadline to Apply:

Est. April 29th, 2026.

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 [Refs 1, 3, 4].

This SBIR topic seeks innovative tools and methods that support an integrated MDAO framework for the design and optimization of hypersonic boost-glide weapons. Solutions should enable concurrent optimization of vehicle geometry, mission trajectory, and control strategies while accounting for launch platform constraints such as volume, mass, interface requirements, and environmental loads. The framework should also address internal system considerations such as payload integration, guidance and control subsystems, and thermal protection. The capability should support conceptual-level design and deliver outputs that inform system cost estimation, manufacturability, technology development roadmaps, and risk reduction strategies.

Proposals should demonstrate capabilities in the following areas:

Aerodynamic and trimmed flight analysis to predict forces and moments over a broad range of Mach numbers, including control surface deflection effects and geometric deformation. Integration with existing computational fluid dynamics tools is encouraged.

Aerothermal modeling to estimate heating loads and surface temperatures, including convective and radiative heat transfer and thermal protection system behavior.

Structural analysis to evaluate stresses, strains, and deformation under combined aerodynamic and thermal loads, with support for high-temperature materials and composite structures.

Mass properties and internal system layout to optimize placement of payloads, sensors, power systems, and thermal subsystems while maintaining center-of-gravity control and packaging feasibility.

Trajectory and control optimization to evaluate and enhance flight performance while meeting constraints on range, maneuverability, survivability, and terminal accuracy.

System-level integration into an existing or proposed MDAO architecture such as ADAPT [Ref 2] or OpenMDAO, with support for geometry parameterization, solver coupling, multi-objective optimization, and design variable management.

Uncertainty quantification and robust optimization to evaluate sensitivity to variations in input parameters, models, or environmental conditions, and to ensure resilient design outcomes.

AI/ML methods to accelerate convergence, construct reduced-order models, support adaptive sampling, and enable data-driven design exploration. Solutions may also include optimizing the objective function itself by learning weighting factors for multi-objective problems, generating surrogate models for expensive simulations, discovering improved formulations via symbolic regression, or adaptively refining the objective function as new information becomes available.

Proposed solutions should leverage existing tools, frameworks, and prior government investments wherever feasible. The resulting toolset should support traceability between design inputs and mission-level measures of effectiveness, helping guide early-phase trade studies and enabling faster transition to detailed design and development.

Who will win?

If you can achieve the objective above better than any other company on the market, you have a very high-likelihood of success and should apply.

Who is eligible to apply?

Any company that meets the following criteria:

• For-profit company

• U.S.-owned and controlled.

• 500 or fewer employees (including affiliates)

How Can BW&CO Help?

1) End-to-end support including, strategy, writing of the full proposal, and administrative & compliance support.

2) Proposal strategy and review.

3) Administrative & compliance support.

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