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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1961

Effects of Control-Feel Configuration on Airplane Longitudinal Control Response

A general study of longitudinal control feel was made with a transonic fighter-type airplane equipped with a control-feel system which 4 was adjustable in flight. The control-feel system provided a feel component with individual gain control in proportion to each of five quantities: stick deflection, stick rate, airplane normal acceleration, pitching acceleration, and pitching velocity. A number of feel configurations were investigated in flight and analytically. These feel configurations had feel components in various amounts from various combinations of these five sources. The results contained herein are all for an airplane center-of-gravity position at approximately 25 percent of the mean aerodynamic chord, a Mach number of 0.85, and an altitude of 28,000 feet. Results are presented as time histories, as plots of the variation of peak force per g with input duration, and as frequency-response plots. A number of frequency-response plots are included to illustrate the effects of choice of feel sources and gains. The results illustrate the desirability of balancing a normal-acceleration feel component with a pitching-acceleration feel component. Pitching-velocity feel is shown to be useful for shaping control-system frequency response. The results suggest the desirability of designing a control-feel system to a large extent by means of frequency-response analysis in order to keep the shapes of the frequency-response curves within desirable limits.

Crane, Harold L.↗
DOE OSTI2021

Assessment of DFT methods for the prediction of detachment energies and electronic structures of complex and multiply charged anions

Here, in this work, we assess the ability of different density functional theory methods to reproduce the vertical/adiabatic detachment energies (VDEs/ADEs) of a series of 40 anions, including monoanion versus multiply charged anions (MCAs) and covalent versus noncovalent interaction. The statistical analysis of errors is firstly performed by comparing the theoretical values with the experimental benchmark data obtained from the negative ion photoelectron spectroscopy (NIPES). The proposed optimally tuned range-separated (OTRS) functionals are proved to not only well reproduce the experimental VDEs/ADEs, but also simulate experimental NIPES. The result implies a more serious issue of delocalization error for MCAs and a balanced description of electron-rich/- deficient region of anions is necessary. The radius of the spherically symmetric average electron localization function (ELF) region is demonstrated as a useful descriptor for the characterization of electronic structure of anionic systems and a quasilinear fitting model is proposed to efficiently obtain their OTRS parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Abstract Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Addressing the sensitivity of signals from solid/liquid ambient pressure XPS (APXPS) measurement

Ambient pressure XPS has demonstrated its great potential in probing the solid/liquid interface, which is a central piece in electrocatalytic, corrosion, and energy storage systems. Additionally, despite the advantage of ambient pressure XPS being a surface sensitive characterization technique, the ability of differentiating the surface adsorbed species (~Å scale) and bulk electrolyte (~10 nm scale) in the spectrum depends on the delicate balance between bulk solution concentration (C), surface coverage (θ), bulk liquid layer thickness (L), and inelastic mean free path (λ) as a function of photon energy. By investigating a model system of gold dissolving in a bromide solution, the connection between theoretical prediction at the atomic resolution and macroscopic observable spectrum is established.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Sensitivity Analysis Applied to Atomic Data Used for X-ray Spectrum Synthesis

A great deal of work has been devoted to the accumulation of accurate quantities describing atomic processes for use in analysis of astrophysical spectra. But in many situations of interest the interpretation of a quantity which is observed, such as a line flux, depends on the results of a modeling- or spectrum synthesis code. The results of such a code depends in turn on many atomic rates or cross sections, and the sensitivity of the observable quantity on the various rates and cross sections may be non-linear and if so cannot easily be derived analytically. In such cases the most practical approach to understanding the sensitivity of observables to atomic cross sections is to perform numerical experiments, by calculating models with various rates perturbed by random (but known) factors. In addition, it is useful to compare the results of such experiments with some sample observations, in order to focus attention on the rates which are of the greatest relevance to real observations. In this paper I will present some attempts to carry out this program, focussing on two sample datasets taken with the Chandra HETG. I will discuss the sensitivity of synthetic spectra to atomic data affecting ionization balance, temperature, and line opacity or emissivity, and discuss the implications for the ultimate goal of inferring astrophysical parameters.

Kallman, Tim↗
NASA NTRS2006

Sensitivity Analysis Applied to Atomic Data Used for X-ray Spectrum Synthesis

A great deal of work has been devoted to the accumulation of accurate quantities describing atomic processes for use in analysis of astrophysical spectra. But in many situations of interest the interpretation of a quantity which is observed, such as a line flux, depends on the results of a modeling- or spectrum synthesis code. The results of such a code depends in turn 011 many atomic rates or cross sections, and the sensitivity of the observable quantity on the various rates and cross sections may be non-linear and if so cannot easily be derived analytically. In such cases the most practical approach to understanding the sensitivity of observables to atomic cross sections is to perform numerical experiments, by calculating models with various rates perturbed by random (but known) factors. In addition, it is useful to compare the results of such experiments with some sample observations, in order to focus attention on the rates which are of the greatest relevance to real observations. In this paper I will present some attempts to carry out this program, focussing on two sample datasets taken with the Chandra HETG. I will discuss the sensitivity of synthetic spectra to atomic data affecting ionization balance, temperature, and line opacity or emissivity, and discuss the implications for the ultimate goal of inferring astrophysical parameters.

Kallman, Tim↗
NASA NTRS2008

Testing Photoionization Calculations Using Chandra X-ray Spectra

A great deal of work has been devoted to the accumulation of accurate quantities describing atomic processes for use in analysis of astrophysical spectra. But in many situations of interest the interpretation of a quantity which is observed, such as a line flux, depends on the results of a modeling- or spectrum synthesis code. The results of such a code depends in turn on many atomic rates or cross sections, and the sensitivity of the observable quantity on the various rates and cross sections may be non-linear and if so cannot easily be derived analytically. In such cases the most practical approach to understanding the sensitivity of observables to atomic cross sections is to perform numerical experiments, by calculating models with various rates perturbed by random (but known) factors. In addition, it is useful to compare the results of such experiments with some sample observations, in order to focus attention on the rates which are of the greatest relevance to real observations. In this paper I will present some attempts to carry out this program, focussing on two sample datasets taken with the Chandra HETG. I will discuss the sensitivity of synthetic spectra to atomic data affecting ionization balance, temperature, and line opacity or emissivity, and discuss the implications for the ultimate goal of inferring astrophysical parameters.

Kallman, Tim↗
DOE OSTI2020

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Abstract Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model. This severely limits the practical application of these models in systems with dynamics governed by important rare events, such as chemical reactions and diffusion. We present an adaptive Bayesian inference method for automating the training of interpretable, low-dimensional, and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations. Within an active learning framework, the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model. The method is applied to a range of single- and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency, while requiring a minimal amount of ab initio training data. We provide a fully open-source implementation of our method, as well as a procedure to map trained models to computationally efficient tabulated force fields.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Free-standing membrane incorporating single-atom catalysts for ultrafast electroreduction of low-concentration nitrate

The release of wastewaters containing relatively low levels of nitrate (NO 3 ⁻) results in sufficient contamination to induce harmful algal blooms and to elevate drinking water NO 3 ⁻ concentrations to potentially hazardous levels. In particular, the facile triggering of algal blooms by ultra-low concentrations of NO 3 ⁻ necessitates the development of efficient methods for NO 3 ⁻ destruction. However, promising electrochemical methods suffer from weak mass transport under low reactant concentrations, resulting in long treatment times (on the order of hours) for complete NO 3 ⁻ destruction. In this study, we present flow-through electrofiltration via an electrified membrane incorporating nonprecious metal single-atom catalysts for NO 3 ⁻ reduction activity enhancement and selectivity modification, achieving near-complete removal of ultra-low concentration NO 3 ⁻ (10 mg-N L -1 ) with a residence time of only a few seconds (10 s). By anchoring Cu single atoms supported on N-doped carbon in a carbon nanotube interwoven framework, we fabricate a free-standing carbonaceous membrane featuring high conductivity, permeability, and flexibility. The membrane achieves over 97% NO 3 ⁻ removal with high N 2 selectivity of 86% in a single-pass electrofiltration, which is a significant improvement over flow-by operation (30% NO 3 ⁻ removal with 7% N 2 selectivity). This high NO 3 ⁻ reduction performance is attributed to the greater adsorption and transport of nitric oxide under high molecular collision frequency coupled with a balanced supply of atomic hydrogen through H 2 dissociation during electrofiltration. Overall, our findings provide a paradigm of applying a flow-through electrified membrane incorporating single-atom catalysts to improve the rate and selectivity of NO 3 ⁻ reduction for efficient water purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗
DOE OSTI2021

Advances and challenges in CO2 foam technologies for enhanced oil recovery in carbonate reservoirs

Utilization of surfactants for generating foam has the potential for fluid-mobility control during CO2 flooding processes, leading to improved oil recovery. This manuscript is a review of the most important aspects for the design of CO2-foams with mobility control in carbonate reservoirs, including recent advances in novel surfactants and analytical techniques for analysis of surfactant adsorption on carbonate minerals and their thermal stability. Several key parameters and properties regarding foam transport in porous media are reviewed such as, the minimum pressure gradient required for foam generation, the effects of the partition coefficient of a CO2-soluble surfactant on foam transport in rock cores, visualization of foam flow by either microfluidic or PET/CT imaging processes in heterogeneous or fractured systems and the effect of oil on foam transport under reservoir conditions. Also are discussed the most recent advances of two major foam modeling methods, including the semi-empirical STARS foam model and the population balance model, as well as CO2 foam pilot tests and the factors governing their successes.

Jian, Guoqing↗
DOE OSTI2023

Understanding the mechanisms of anisotropic dissolution in metal oxides by applying radiolysis simulations to liquid-phase TEM

Iron-based redox-active minerals are ubiquitous in soils, sediments, and aquatic systems. Their dissolution is of great importance for microbial impacts on carbon cycling and the biogeochemistry of the lithosphere and hydrosphere. Despite its widespread significance and extensive prior study, the atomic-to-nanoscale mechanisms of dissolution remain poorly understood, particularly the interplay between acidic and reductive processes. Here, we use in situ liquid-phase-transmission electron microscopy (LP-TEM) and simulations of radiolysis to probe and control acidic versus reductive dissolution of akaganeite (β–FeOOH) nanorods. Informed by crystal structure and surface chemistry, the balance between acidic dissolution at rod tips and reductive dissolution at rod sides was systematically varied using pH buffers, background chloride anions, and electron beam dose. We find that buffers, such as bis-tris, effectively inhibited dissolution by consuming radiolytic acidic and reducing species such as superoxides and aqueous electrons. In contrast, chloride anions simultaneously suppressed dissolution at rod tips by stabilizing structural elements while promoting dissolution at rod sides through surface complexation. Dissolution behaviors were systematically varied by shifting the balance between acidic and reductive attacks. The findings show LP-TEM combined with simulations of radiolysis effects can provide a unique and versatile platform for quantitatively investigating dissolution mechanisms, with implications for understanding metal cycling in natural environments and the development of tailored nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Feedback between radiation and transport in photovoltaics

By building on the generalized Hovel model, this work develops an analytical solution to unify photon recycling, light trapping, and carrier transport in solar cells. Enhanced transport due to photon recycling diffusion is considered. While photon recycling diffusion is often negligible, it can significantly support transport in cases where charge diffusion is low but radiative efficiency is high. Next, the diffusion equation is solved to determine carrier collection for planar and textured cells. Results elucidate novel features in the external quantum efficiency (EQE) curve that occur for textured cells with high absorption and limited transport. Then, the effect of limited transport on the radiative recombination of solar cells is investigated in detail. While the traditional treatment of detailed balance uses the applied voltage to calculate a cell's radiative recombination, the present approach uses the spatially resolved quasi-Fermi-level splitting (QFLS). Further, the discrepancy between the models is shown to be inconsequential to performance for cells with low radiative recombination (Si) or with high mobilities (lowly doped GaAs). However, for cells with high radiative recombination and low mobility (highly doped GaAs, polycrystalline CdTe, and thin-film perovskites), incorporating variation in QFLS in the determination of radiative recombination can become necessary for accurate photovoltaic modeling.

14 SOLAR ENERGY↗
DOE OSTI2024

2024 Standard Scenarios: A U.S. Electricity Sector Outlook

This data corresponds to the 2024 Standard Scenarios report, which contains a suite of forward-looking scenarios of the possible evolution of the U.S. electricity sector through 2050. These files contain modeled projections of the future. Although we strive to capture relevant phenomena as comprehensively as possible, the models used to create this data are unavoidably imperfect, and the future is highly uncertain. Consequentially, this data should not be the sole basis for making decisions. In addition to drawing from multiple scenarios within this set, we encourage analysts to also draw on projections from other sources, to benefit from diverse analytical frameworks and perspectives when forming their conclusions about the future of the power sector. For further discussions about the limitations of the models underlying this data, see section 1.4 of the "ReEDS Documentation" linked below. For scenario descriptions, input assumptions, and metric definitions for the data in these files, see the "2024 Standard Scenarios Report" linked below.

2050↗
NASA NTRS1971

Wind tunnel balance system for determination of wind-induced vibrations of a rigid shuttle model in the launch configuration

A wind tunnel balance system was designed to determine the wind-induced vibrations of a space shuttle model. The balance utilizes a flexible sting mounting in conjunction with a geometrically scaled rigid model. Bending and torsional displacements are determined through strain-gauge-instrumented spring bar mechanisms. The natural frequency of the string-model system can be varied continuously throughout the expected scaled frequency range of the shuttle vehicle while a test is in progress by the use of moveable riders on the spring bar mechanism. Through the use of a frequency analyzer, the output can be used to determine troublesome vibrational frequencies. A dimensional analysis of the wind-induced vibration problem is also presented which suggests a test procedure. In addition a computer program for analytical studies of the forced vibration problem is presented.

Source record↗
NASA NTRS2001

A New Look at Self-Similarity in Strained Plane Wakes

In early experiments, A. J. Reynolds and J. F. Keffer sought to determine whether plane wakes of circular cylinders, when strained by a wind tunnel of varying cross-section, evolved in accordance with an analytically derived self-similar solution. As pointed out by Reynolds, for the strain geometry considered this self-similar solution indicated exponential growth of the viscous term in the mean momentum equation, a result which he interpreted as suggesting that such wakes would eventually relaminarize. The experimental results were found not to agree with the similarity theory and recent direct numerical simulations confirm this. However, a more general self-similar analysis of the kind suggested by W. K. George is found to lead to families of possible similarity solutions, some of which do indeed describe the observed flaw behavior. These equilibrium similarity solutions result from creating a balance in the governing equations by grouping certain terms. For these solutions the viscous terms can be retained in the analysis.

Rogers, Michael M.↗
DOE OSTI2023

(NH 4 ) 2 [UO 2 Cl 4 ]·2H 2 O, a new uranyl tetrachloride with ammonium charge-balancing cations

A new uranyl tetrachloride salt with chemical formula, (NH 4 ) 2 [UO 2 Cl 4 ]·2H 2 O, namely, diammonium uranyl tetrachloride dihydrate, 1 , was prepared and crystallized via slow evaporation from a solution of 2 M hydrochloric acid. As confirmed by powder X-ray diffraction, the title compound crystallizes with an ammonium chloride impurity that formed as a result of the breakdown of a triazine precursor. The (UO 2 Cl 4 ) 2− dianion is charge balanced by ammonium cations, while an extensive hydrogen-bond network donated from structural water molecules stabilize the overall assembly. Compound 1 adds to the extensive collection of actinyl tetrachloride salts, but it represents the first without an alkali cation for purely inorganic compounds. Diffuse reflectance and luminescence spectra show typical absorption and emission behavior, respectively, of uranyl materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗