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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

APPLE - An aeroelastic analysis system for turbomachines and propfans

This paper reviews aeroelastic analysis methods for propulsion elements (advanced propellers, compressors and turbines) being developed and used at NASA Lewis Research Center. These aeroelastic models include both structural and aerodynamic components. The structural models include the typical section model, the beam model with and without disk flexibility, and the finite element blade model with plate bending elements. The aerodynamic models are based on the solution of equations ranging from the two-dimensional linear potential equation for a cascade to the three-dimensional Euler equations for multi-blade configurations. Typical results are presented for each aeroelastic model. Suggestions for further research are indicated. All the available aeroelastic models and analysis methods are being incorporated into a unified computer program named APPLE (Aeroelasticity Program for Propulsion at LEwis).

Reddy, T. S. R.↗
NASA NTRS2005

The APPL "Learning Map"

Root Learning, a learning consulting organization with a background in strategic planning, recognizes the knowledge gap that frequently exists between a leadership team and the rest of an organization. Team members supposedly working toward the same goal don't always have the same vision as to where the organization is headed, and they may not understand how the piece they are accountable for fits into the big picture. To address these complex problems, Root Learning utilizes the age-old tools of sarcasm, metaphor and graphics (much in the same way that ASK uses a traditional storytelling format.) The company is best known for creating "Learning Maps" like this one: humorous drawings based on the inner workings of an organization. Their purpose is to put complex topics on the table, to stimulate discussion, and to ultimately give team members a common vision of where the organization is going and what role they personally play in getting there. APPL knows how effective it is to incorporate new and engaging techniques into its knowledge sharing programs. By collaborating with Root Learning, we were able to expand the knowledge of the organization and add one more of these techniques to our repertoire.

Source record↗
NASA NTRS2007

Solving the AI Planning Plus Scheduling Problem Using Model Checking via Automatic Translation from the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL)

This paper describes a translator from a new planning language named the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL) model checker. This translator has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project sponsored by the Exploration Technology Development Program, which is seeking to mature autonomy technology for the vehicles and operations centers of Project Constellation.

Butler, Ricky W.↗
DOE OSTI2017

Corrigendum to “The Schwarz alternating method in solid mechanics” [Comput. Methods Appl. Mech. Engrg. 319 (2017) 19–51]

This corrigendum clarifies the conditions under which the proof of convergence of Theorem 1 from the original article is valid. We erroneously stated as one of the conditions for the Schwarz alternating method to converge that the energy functional be strictly convex for the solid mechanics problem. Finally, we have relaxed that assumption and changed the corresponding parts of the text. None of the results or other parts of the original article are affected.

36 MATERIALS SCIENCE↗