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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 1,711 records · Page 95

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NASA NTRS2007

ANOPP Landing Gear Noise Prediction Comparisons to Model-scale Data

The NASA Aircraft NOise Prediction Program (ANOPP) includes two methods for computing the noise from landing gear: the "Fink" method and the "Guo" method. Both methods have been predominately validated and used to predict full-scale landing gear noise. The two methods are compared, and their ability to predict the noise for model-scale landing gear is investigated. Predictions are made using both the Fink and Guo methods and compared to measured acoustic data obtained for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. A process is developed by which full-scale predictions can be scaled to compare with model-scale data. The measurements were obtained in the NASA Langley Quiet Flow Facility for a range of Mach numbers at a large number of observer polar (flyover) and azimuthal (sideline) observer angles. Spectra and contours of the measured sound pressure levels as a function of polar and azimuthal angle characterize the directivity of landing gear noise. Comparisons of predicted noise spectra and contours from each ANOPP method are made. Both methods predict comparable amplitudes and trends for the flyover locations, but deviate at the sideline locations. Neither method fully captures the measured noise directivity. The availability of these measured data provides the opportunity to further understand and advance noise prediction capabilities, particularly for noise directivity.

Burley, Casey L.↗

DOE OSTI2021

Large-scale dissolution of sintered Mo disks

Non-uranium production of 99 Mo via neutron capture or by photonuclear reaction using an electron accelerator is receiving considerable attention. For commercial production of 99 Mo, post-irradiation processes must incorporate a robust design for easy scale-up. Once developed, large-scale chemical processes must be optimized for hot-cell operations and potential automation. In this work, we present experimental results on the large-scale dissolution of sintered Mo disks using three 50% hydrogen peroxides from different suppliers. Dissolution rates obtained for 600-g Mo batches and potential reasons for different dissolution behaviors is discussed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

DOE OSTI2020

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Leaf-scale carbon assimilation simulated by the multi-assumption architecture & testbed for process sensitivity analysis

Raw and processed output from the Multi-Assumption Architecture & Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_walker2020; Walker et al., 2018). The dataset contains leaf-scale carbon assimilation data from three MAAT simulations and their post-processing and plotting scripts. Simulation 1, labelled "FvC_4proc_proc," is a four-process, process sensitivity analysis (Dai et al., 2017) of carbon assimilation based on the Farquhar et al. (1980) photosynthesis model, and its variant proposed by Collatz et al. (1991). Simulation 2, labelled "FvC_4proc_salt," is a 14 parameter sensitivity analysis (Saltelli et al., 2010) of carbon assimilation based on the Farquhar and Collatz photosynthesis models. Simulation 3, labelled "FvC," is a factorial combination of the alternative process representations and parameter values presented in those original papers across a factorial combination of incident photosynthetically active radiation (50-2000 µmol m-2 s-1, in increments of 50) and atmospheric CO2 concentration (50-1500 µmol m-2 s-1, in increments of 50). Additional scripts/functions for post-processing and plotting are part of the MAAT repository. These data were generated to evaluate and compare the Farquhar and Collatz models of leaf-scale photosynthesis across a range of CO2 and incident light conditions. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures; .RDS files, a binary format specific to R and read with the 'readRDS' function, to store raw MAAT output; R and bash scripts (.bs) that help to run a MAAT simulation, .XML files that are output from MAAT describing a run, and .csv files which contain the calculated sensitivity indexes published in Walker et al. (2020).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Structurally flexible cloud microphysics, observationally constrained at all scales via ML-accelerated Bayesian inference

We discuss the challenge of developing observationally informed parameterizations of microphysics for use at a hierarchy of modeling scales. Our proposed approach is applicable to any domain that suffers from a two-fold parameterization problem, where physical processes are not resolved at the model scale (the first problem), and those processes are uncertain at any scale (the second problem). For such problems, a physical approach facilitates modeling across scales, as well as systematic observational inference accelerated by machine learning (ML) surrogate models, and quantification of physical uncertainties.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗

DOE OSTI2020

2019 Project Peer Review Report

This document summarizes the evaluations provided by an independent external panel of experts at the 2019 U.S. Department of Energy Bioenergy Technologies Office's Peer Review meeting on March 4–7, 2019 in Denver, CO. BETO manages a diverse portfolio of technologies covering the full spectrum of bioenergy production, from the feedstock source to end use. BETO systematically prioritizes research and development (R&D) into technology opportunities across a range of emerging scientific breakthroughs and technology-readiness levels. This approach supports a diverse R&D portfolio while developing the most promising and widely applicable technologies, testing technologies as integrated processes, and verifying integrated processes at the engineering scale. These technologies will use a broad variety of currently underused domestic biomass and waste resources to produce increasing volumes of biofuels, bioproducts, and biopower. The biennial peer review process enables external stakeholders to provide feedback on the responsible use of taxpayer funding and develop recommendations for the most efficient and effective ways to accelerate the development of a bioenergy industry. BETO completed these reviews in 2019. This report includes the results of both the Project Peer Review meeting held in March 2019 and the Program Management Review meeting held in July 2019.

09 BIOMASS FUELS↗

NASA NTRS2013

Materials Manufactured from 3D Printed Synthetic Biology Arrays

Many complex, biologically-derived materials have extremely useful properties (think wood or silk), but are unsuitable for space-related applications due to production, manufacturing, or processing limitations. Large-scale ecosystem-based production, such as raising and harvesting trees for wood, is impractical in a self-contained habitat such as a space station or potential Mars colony. Manufacturing requirements, such as the specialized equipment needed to harvest and process cotton, add too much upmass for current launch technology. Cells in nature are already highly specialized for making complex biological materials on a micro scale. We envision combining these strengths with the recently emergent technologies of synthetic biology and 3D printing to create 3D-structured arrays of cells that are bioengineered to secrete different materials in a specified three-dimensional pattern.

Gentry, Diana↗

NASA NTRS1994

Gravitational collapse of small-scale structure as the origin of the Lyman-alpha forest

If gravitational clustering is a hierarchical process, the present large-scale structure of the galaxy distribution implies that structures on smaller scales must have formed at high redshift. We simulate the formation of small-scale structure (average cell mass: (delta) bar m(sub b) = 10(sup 4.2) solar mass) and the evolution of photoionized gas, in the specific case of the CDM + Lambda model. The photoionized gas has a natural minimal scale of collapse, the Jeans scale (m(sub b,J) is approximately equal to 10(exp 9) solar mass). We find that low column density (N(sub HI) is less than or equal to 10(exp 14)/sq cm) lines originate in regions resembling Zel'dovich pancakes, where gas with overdensities in the range 3-30 is enclosed by two shocks but is typically reexpanding at approximately the Hubble velocity. However, higher column density lines stem from more overdense regions where the shocked gas is cooling. We show that this model can probably account for the observed number of lines, their distribution in column density and b-parameters, as well as the cloud physical sizes as observed in gravitationally lensed quasars. We find a redshift evolution that is too steep; however, this may be due to insufficient dynamical range in the simulation or because the specific model is incorrect. The model predicts that high signal-to-noise observations should find systematic deviations from Voigt profiles, mainly in the form of broad wings in the line profiles, and that a fluctuating Gunn-Peterson effect will be detected, which can be modeled as a superposition of weak lines with a wide range of b-parameters.

Cen, Renyue↗

DOE OSTI2025

Disentangling the gap between pure and mixed-gas performance of thin film composite membranes through improved cell design and testing methods

Testing thin film composite (TFC) membrane coupons at low stage-cuts (≤5%) in a sweep-gas permeation system is a common practice to obtain mixed-gas separation properties for benchmarking performance and making scale-up decisions. However, even under these idealized conditions, mixed-gas permeance and selectivity can be more than 30% lower than their pure-gas values, partially due to concentration polarization, an effect that typically intensifies with increased membrane permeance. This study investigates the effect of cell design on mixed-gas testing using PolyActive TM TFC membranes with pure-gas CO 2 permeance of 1700 – 3100 gas permeance unit (GPU), covering the permeance range of most state-of-the-art CO 2 /N 2 separation membranes. Here, we designed and 3D-printed a counter-current permeation cell with enhanced feed and sweep flow efficiency, resulting in a 33 – 41% increase in mixed-gas CO 2 permeance compared to traditional permeation cells. Furthermore, we compared sweep-gas and vacuum permeation methods using traditional permeation cells, revealing that the latter delivers 41% higher mixed-gas CO 2 permeance, because vacuuming effectively minimizes the downstream concentration polarization. These findings highlight the importance of cell design and permeation apparatus selection in lab-scale mixed-gas testing, with strong implications for module design and process optimization at the industrial scale.

mixed gas performance↗

DOE OSTI2022

Evidence for a genetic basis in functional trait tradeoffs with microbial growth rate but not growth yield

Tradeoffs in microbial functional traits have been a focus of recently described ecological frameworks and of mathematical models of microbial community functioning. Tradeoffs in key traits such as growth rate, growth yield, resource acquisition, and stress tolerance may have either a genetic basis or a physiological basis, and the type of tradeoff can inform how traits are modeled and measured. Here we provide evidence that growth rate/decomposition and growth rate/stress tolerance tradeoffs have a primarily genetic basis in a phylogenetically diverse suite of ten leaf litter-inhabiting fungi. In contrast, growth yield tradeoffs with functional traits are more likely to have a physiological basis. Consideration of the type of tradeoff, genetic or physiological, should help to inform efforts to model microbial contributions to ecosystem processes, especially when considering different scales. Consideration of physiological tradeoffs may be important for understanding short-term variability (e.g., pulse events) and fine spatial scales, whereas genetic tradeoffs are likely to be useful for understanding regional- to continental-scale and medium- to long-term contributions of microbes to ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks

Large-scale multiphysics simulations are computationally challenging due to the coupling of multiple processes with widely disparate time scales. The advent of exascale computing systems exacerbates these challenges since these systems enable ever-increasing size and complexity. In recent years, there has been renewed interest in developing multirate methods as a means to handle the large range of time scales, as these methods may afford greater accuracy and efficiency than more traditional approaches of using implicit-explicit (IMEX) and low-order operator splitting schemes. However, to date there have been few performance studies that compare different classes of multirate integrators on complex application problems. In this work, we study the performance of several newly developed multirate infinitesimal (MRI) methods, implemented in the SUNDIALS solver package, on two reacting flow model problems built on structured mesh frameworks. The first model revisits prior work on a compressible reacting flow problem with complex chemistry that is implemented using BoxLib but where we now include comparisons between a new explicit MRI scheme with the multirate spectral deferred correction (SDC) methods in the original paper. The second problem uses the same complex chemistry as the first problem, combined with a simplified flow model, but runs at a large spatial scale where explicit methods become infeasible due to stability constraints. Two recently developed IMEX MRI multirate methods are tested. These methods rely on advanced features of the AMReX framework on which the model is built, such as multilevel grids and multilevel preconditioners. The results from these two problems show that MRI multirate methods can offer significant performance benefits on complex multiphysics application problems and that these methods may be combined with advanced spatial discretization to compound the advantages of both.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Ultrafast electron microscopy for probing magnetic dynamics

Abstract The spatial features of ultrafast changes in magnetic textures carry detailed information on microscopic couplings and energy transport mechanisms. Electrons excel in imaging such picosecond or shorter processes at nanometer length scales. We review the range of physical interactions that produce ultrafast magnetic contrast with electrons, and specifically highlight the recent emergence of ultrafast Lorentz transmission electron microscopy. From the fundamental processes involved in demagnetization at extremely short timescales to skyrmion-based devices, we show that ultrafast electron imaging will be a vital tool in solving pressing problems in magnetism and magnetic materials where nanoscale inhomogeneity, microscopic field measurement, non-equilibrium behavior or dynamics are involved. Graphic abstract

36 MATERIALS SCIENCE↗

NASA NTRS1999

Managing the Moon Program: Lessons Learned from Project Apollo

There have been many detailed historical studies of the process of deciding on and executing the Apollo lunar landing during the 1960s and early 1970s. From the announcement of President John F Kennedy on May 25, 1961, of his decision to land an American on the Moon by the end of the decade, through the first lunar landing on July 20, 1969, on to the last of six successful Moon landings with Apollo 17 in December 1972, NASA carried out Project Apollo with enthusiasm and aplomb. While there have been many studies recounting the history of Apollo, at the time of the 30th anniversary of the first lunar landing by Apollo 11, it seems appropriate to revisit the process of large-scale technological management as it related to the lunar mission. Consequently, the NASA History Office has chosen to publish this monograph containing the recollections of key partcipants in the management process. The collective oral history presented here was recorded in 1989 at the Johnson Space Center's Gilruth Recreation Center in Houston, Texas. It includes the recollections of key participants in Apollo's administration, addressing issues such as communication between field centers, the prioritization of technological goals, and the delegation of responsibility. The following people participated: George E. Muller, Owen W. Morris, Maxime A. Faget, Robert R. Gilruth, Christopher C. Kraft, and Howard W. (Bill) Tindall. The valuable perspectives of these individuals deepen and expand our understanding of this important historical event. This is the 14th in a series of special studies prepared by the NASA History Office. The Monographs in Aerospace History series is designed to provide a wide variety of investigations relative to the history of aeronautics and space. These publications are intended to be tightly focused in terms of subject, relatively short in length, and reproduced in an inexpensive format to allow timely and broad dissemination to researchers in aerospace history.

Source record↗

NASA NTRS2002

Self-Consistent Magnetosphere-Ionosphere Coupling and Associated Plasma Energization Processes

Magnetosphere-Ionosphere (MI) coupling and associated with this process electron and ion energization processes have interested scientists for decades and, in spite of experimental and theoretical research efforts, are still ones of the least well known dynamic processes in space plasma physics. The reason for this is that the numerous physical processes associated with MI coupling occur over multiple spatial lengths and temporal scales. One typical example of MI coupling is large scale ring current (RC) electrodynamic coupling that includes calculation of the magnetospheric electric field that is consistent with the ring current (RC) distribution. A general scheme for numerical simulation of such large-scale magnetosphere-ionosphere coupling processes has been presented earlier in many works. The mathematical formulation of these models are based on "modified frozen-in flux theorem" for an ensemble of adiabatically drifting particles in the magnetosphere. By tracking the flow of particles through the inner magnetosphere, the bounce-averaged phase space density of the hot ions and electrons can be reconstructed and the magnetospheric electric field can be calculated such that it is consistent with the particle distribution in the magnetosphere. The new a self-consistent ring current model has been developed that couples electron and ion magnetospheric dynamics with calculation of electric field. Two new features were taken into account in addition to the RC ions, we solve an electron kinetic equation in our model, self-consistently including these results in the solution. Second, using different analytical relationships, we calculate the height integrated ionospheric conductances as the function of precipitated high energy magnetospheric electrons and ions as produced by our model. This results in fundamental changes to the electric potential pattern in the inner magnetosphere, with a smaller Alfven boundary than previous potential formulations would predict but one consistent with recent satellite observations. This leads to deeper penetration of the plasma sheet ions and electrons into the inner magnetosphere and more effective ring current ions and electron energization.

Khazanov, G. V.↗

NASA NTRS2012

Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km×10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Landsat↗