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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Performant Optimization Strategies for Multifidelity Stochastic Power Grid Models

This talk goes into the algorithmic work done under the Forest project in order to solve expensive power grid models. We explore multiple fidelities of models that balance accuracy and computational expense. We use bundling strategies and progressive hedging in order to parallelize large stochastic programs.

Alfant, Rachael May [Sandia National Laboratories ↗
NASA NTRS2011

Integration of Multifidelity Multidisciplinary Computer Codes for Design and Analysis of Supersonic Aircraft

This paper documents the development of a conceptual level integrated process for design and analysis of efficient and environmentally acceptable supersonic aircraft. To overcome the technical challenges to achieve this goal, a conceptual design capability which provides users with the ability to examine the integrated solution between all disciplines and facilitates the application of multidiscipline design, analysis, and optimization on a scale greater than previously achieved, is needed. The described capability is both an interactive design environment as well as a high powered optimization system with a unique blend of low, mixed and high-fidelity engineering tools combined together in the software integration framework, ModelCenter. The various modules are described and capabilities of the system are demonstrated. The current limitations and proposed future enhancements are also discussed.

Geiselhart, Karl A.↗
NASA NTRS2014

Design Environment for Multifidelity and Multidisciplinary Components

One of the greatest challenges when developing propulsion systems is predicting the interacting effects between the fluid loads, thermal loads, and structural deflection. The interactions between technical disciplines often are not fully analyzed, and the analysis in one discipline often uses a simplified representation of other disciplines as an input or boundary condition. For example, the fluid forces in an engine generate static and dynamic rotor deflection, but the forces themselves are dependent on the rotor position and its orbit. It is important to consider the interaction between the physical phenomena where the outcome of each analysis is heavily dependent on the inputs (e.g., changes in flow due to deflection, changes in deflection due to fluid forces). A rigid design process also lacks the flexibility to employ multiple levels of fidelity in the analysis of each of the components. This project developed and validated an innovative design environment that has the flexibility to simultaneously analyze multiple disciplines and multiple components with multiple levels of model fidelity. Using NASA's open-source multidisciplinary design analysis and optimization (OpenMDAO) framework, this multifaceted system will provide substantially superior capabilities to current design tools.

Platt, Michael↗
NASA NTRSDate not supplied

Strategies for Automation of Model Tuning in Multifidelity Trajectory Uncertainty Propagation

Multi-model Monte Carlo methods are efficient strategies to perform forward uncertainty quantification studies in entry, descent, and landing (EDL) applications. These multi-model methods are based on the classical Monte Carlo estimator, but fuse predictions from several low-fidelity models to obtain estimators with greater precision given a prescribed computational budget. The effectiveness of these approaches relies on the magnitudes of correlations between the low-fidelity models and the high-fidelity model, as well as the relative computational costs of all models. Identifying and exploiting the best trade-off between correlation and cost, which ultimately depends on the selection of hyperparameters in the low-fidelity models, is a task often performed by hand or simply inspired by the deterministic understanding available for a specific application. This work extends a preliminary effort,

Marten Thompson↗