Multi-scale location-specific fatigue life prediction for additive propulsion components

To enable NASA’s technology roadmap for robust and efficient modeling and design of Advanced Propulsion system materials and structures, QuesTek (QT) will develop and demonstrate a multi-scale process-structure-property-performance modeling framework for aero propulsion component lifing. QT will develop a state-of-the-art integrated computational materials engineering toolkit and implement it in the ICMD® software platform to enable NASA, the aerospace industry, and broader materials intensive industries to leverage accurate and predictive component scale lifing in an intuitive and collaborative cloud-based graphical user interface. Additive manufacturing (AM) is key technology enabler for NASA to improve aero propulsion system efficiency, however, components in these systems are exposed to complex fatigue loading conditions, and paired with the inherent complexity of AM microstructures, durability is difficult to predict. This lack of predictive power that currently exists for fatigue of AM aero propulsion components is a barrier to the broader adoption of the technology. QT will enable composition, process history, microstructure, and component geometry/loading conditions to be captured in a multi-scale PSPP framework to provide robust and efficient component lifing predictions. This will enable concurrent engineering of propulsion systems and alloys. The framework will use CALPHAD based modeling to link composition and process history with microstructure evolution, physics-based mean field analytical modeling to link microstructure with tensile properties, crystal plasticity finite element method to link tensile properties and microstructure with fatigue properties, and Ansys’ nCode DesignLife, a component scale finite element method software to link fatigue properties with component scale lifing. Machine learning will be used for reduced order surrogate modeling to enable uncertainty quantification and propagation through the model framework. The proposed innovation is an integrated multi-scale process-structure-property-performance (PSPP) framework to enable accurate and robust location-specific and component-specific fatigue lifing for additive aero propulsion components. The framework will combine CALPHAD, mean field analytical modeling, CPFEM, and component scale FEM for composition, process history, microstructure, and component geometry sensitive fatigue lifing. The framework will include machine learning based surrogate modeling for efficient uncertainty quantification and propagation. This level of detailed modeling is necessary to accurately predict fatigue in complex additively manufactured propulsion system materials. This approach leverages the state of the art in modeling across length scales to enable NASA’s 2040 vision of robust and efficient modeling and design for Advanced Propulsion system materials and structures. With this toolkit, which will be integrated in the ICMD® software platform, NASA can develop new highly efficient propulsion systems for sub sonic transport vehicle.

• Multi-scale predictive lifing of additive aero propulsion components. • Accelerated qualification and certification of fatigue critical additive components. • Concurrent design of propulsion systems and alloys enabling new highly efficient propulsion systems for sub sonic transport vehicle. • Sensitivity analysis and uncertainty quantification to help with specification development and troubleshooting for new materials and systems. • Materials optimization for other fatigue critical NASA applications beyond aero propulsion systems (e.g., rockets, landers, etc.) • Concurrent design of systems and materials for additively manufactured, fatigue critical components such as biomedical implants (e.g., hip replacements printed using Ti64, heart stents printed out of NiTi-based shape memory alloys). • Location specific fatigue lifing of traditionally manufactured wrought components such as automotive industry (e.g., gears typically made of wrought gear steel, chassis typically made of steel or aluminum alloys, etc.) and aerospace industry (e.g., airframe components). • Supply chain resilience for fatigue critical materials reliant OEMs who need to source materials globally and can use this predictive fatigue modeling framework to determine the microstructure effects from various suppliers on their end products (e.g., agricultural heavy industry, oil & gas, etc.)

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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