Development of an automated design optimization workflow coupling deep-learning based tools with the existing Loci/CHEM suite for simulation of optimal aerospike nozzle design.

This contract is a sole-source requirement for the development of an automated design optimization workflow that integrates deep-learning tools with NASA’s existing Loci/CHEM simulation suite, specifically to advance the design of aerospike nozzles. The goal is to leverage machine learning for rapid, high-fidelity optimization of nozzle geometries, enhancing performance and efficiency in rocket propulsion systems. The project requires close alignment with Loci/CHEM’s computational fluid dynamics capabilities to ensure seamless coupling between AI-driven design suggestions and validated simulation outputs. The solicitation number is 80NSSC26939857Q, posted on July 28, 2026, with a strict response deadline of July 30, 2026. The work is classified under NAICS code 611310 and is managed by the NASA Shared Services Center on behalf of the National Aeronautics and Space Administration. Performance will occur at Stennis Space Center in Mississippi, where the primary point of contact is Shanna Patterson, reachable via email. This effort is critical to accelerating next-generation propulsion development through intelligent automation, and the sole-source nature indicates an exclusive focus on a vendor with pre-existing expertise in this specialized domain.