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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Process Systems Engineering Perspective on the Design of Materials and Molecules

This paper aims to provide an overview of the current state of the art in molecule and material design and a perspective on open questions. First, we discuss the interplay between process design and the design of molecules and materials and then present the basic trade-offs and interdependencies that need to be considered in this integrated design problem. Second, we introduce methods and open questions in the area of processing materials, with special emphasis placed on heterogeneous catalysts due to their importance in the chemical industry. Finally, we discuss materials for photovoltaic cells as one example of a chemical product that is likely to help supply sustainable energy and address climate change concerns. This information presented here is based on presentations and discussions during the FIPSE-4 meeting in June 2018 (https://www.fi-in-pse.org/fipse-4- 2018).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unraveling Anion-Specific Inhibition and Structural Modulation of Gibbsite Crystallization: Implications for Aluminum Mobility in Natural and Engineered Systems

Gibbsite (α-Al(OH) 3 , sometimes designated as γ-Al(OH) 3 ) plays a crucial role in the chemistry of aluminum in the environment and industry, yet its crystallization behavior under multianionic conditions is not well understood. Here, in this study, we investigate how six common anions─fluoride (F – ), chloride (Cl – ), bromide (Br – ), nitrate (NO 3 – ), sulfate (SO 4 2– ), and phosphate (PO 4 3– )─influence the mineralization, structure, and morphology of gibbsite at room temperature. The results show that PO 4 3– , SO 4 2– , and F – strongly inhibit gibbsite formation, stabilizing amorphous or alternative crystalline phases such as nordstrandite and cryolite. On the contrary, Cl – , Br – , and NO 3 – allow partial to complete crystallization of gibbsite without significant morphological changes. Solid-state 27 Al magic angle spinning nuclear magnetic resonance provides crucial insight into aluminum coordination environments in both crystalline and amorphous phases, distinguishing between octahedral, pentahedral, and tetrahedral Al species. The density functional theory calculations reveal a direct correlation between the Al–X bond strength and the inhibition of crystallization, following the order: PO 4 3– > SO 4 2– > F – > NO 3 – > Cl – > Br – . These findings offer molecular-scale insights into anion-specific effects on aluminum hydroxide nucleation and transformation, improving the understanding of gibbsite formation and aluminum cycling in soils, phosphate retention, contaminant immobilization, and waste treatment strategies in nuclear and industrial settings. These insights can also guide the controlled synthesis of aluminum hydroxide materials with tailored crystallinity and morphology via liquid-assisted methods.

Anions effect↗
DOE OSTI2019

Chapter 7: Systems Engineering and Optimization of Wind Turbines and Power Plants

In this chapter, wind turbine optimization has been demonstrated as an effective approach to exploring complex design decisions. However, it is not a push-button solution and effective use requires a multidisciplinary design team and expertise in optimization algorithms. Common techniques include using reduced-order models for computationally intensive portions of the analysis, taking advantage of gradients to solve large problems, and more recently to include UQ to allow for robust design decisions. Current efforts continue to push for increased model fidelity, more comprehensive disciplinary coverage, and incorporation of uncertainty.

17 WIND ENERGY↗
DOE OSTI2016

DEPRECATED Turbine_CostSE (Turbine Cost Systems Engineering Model) [SWR-13-30]

DEPRECATED This repository has been archived by the owner since Jun 19, 2020. It is now read-only. Turbine_CostsSE is a DEPRECATED set of models for assessing the costs of a wind turbine. The first model is a new version of NREL's turbine Cost and Scaling Model that uses 2015 survey data to compute component mass properties from key turbine parameters such as rotor diameter, rated power and hub height. A second model is a new mass-to-cost model which takes the individual component masses as inputs to estimate each component costs with additional cost factors for assembly, overhead, and profits.

Dykes, Katherine↗
DOE OSTI2017

WindSE: Wind Systems Engineering [SWR-17-03]

WindSE is a tool for modeling atmospheric fluid flow within a wind plant and performing optimization of the turbine positions or operating settings. WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization.

King, Ryan↗
DOE OSTI2016

Parameter Estimator for Engineering Systems

This software model generates vehicle parameter sets for downstream modeling applications using real-world data. Value to users is provided through improvements to modeling activities as a result of decreases in time taken during model development and validation. Currently configured for transportation modeling activities, the software provides initial estimates for multiple fundamental vehicle parameters including mass, coefficient of drag, and tire rolling resistance using real-world drive and duty cycle information as inputs.

Source record↗
DOE OSTI2023

WindSE: Wind Systems Engineering [SWR-17-03]

WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization. Documentation can be found at: https://windse.readthedocs.io/en/latest/

King, Ryan↗
DOE OSTI2016

PEES (Parameter Estimator for Engineering Systems) [SWR-16-38]

This software model generates vehicle parameter sets for downstream modeling applications using real-world data. Value to users is provided through improvements to modeling activities as a result of decreases in time taken during model development and validation. Currently configured for transportation modeling activities, the software provides initial estimates for multiple fundamental vehicle parameters including mass, coefficient of drag, and tire rolling resistance using real-world drive and duty cycle information as inputs.

Miller, Eric↗