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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Protein crystal growth in microgravity: Temperature induced large scale crystallization of insulin

One of the major stumbling blocks that prevents rapid structure determination using x-ray crystallography is macro-molecular crystal growth. There are many examples where crystallization takes longer than structure determination. In some cases, it is impossible to grow useful crystals on earth. Recent experiments conducted in conjuction with NASA on various Space Shuttle missions have demonstrated that protein crystals often grow larger and display better internal molecular order than their earth-grown counterparts. This paper reports results from three Shuttle flights using the Protein Crystallization Facility (PCF). The PCF hardware produced large, high-quality insulin crystals by using a temperature change as the sole means to affect protein solubility and thus, crystallization. The facility consists of cylinders/containers with volumes of 500, 200, 100, and 50 ml. Data from the three Shuttle flights demonstrated that larger, higher resolution crystals (as evidenced by x-ray diffraction data) were obtained from the microgravity experiments when compared to earth-grown crystals.

Long, Marianna M.↗
NASA NTRS1999

Large-Scale Parallel Unstructured Mesh Computations for 3D High-Lift Analysis

A complete "geometry to drag-polar" analysis capability for three-dimensional high-lift configurations is described. The approach is based on the use of unstructured meshes in order to enable rapid turnaround for complicated geometries which arise in high-lift configurations. Special attention is devoted to creating a capability for enabling analyses on highly resolved grids. Unstructured meshes of several million vertices are initially generated on a work-station, and subsequently refined on a supercomputer. The flow is solved on these refined meshes on large parallel computers using an unstructured agglomeration multigrid algorithm. Good prediction of lift and drag throughout the range of incidences is demonstrated on a transport take-off configuration using up to 24.7 million grid points. The feasibility of using this approach in a production environment on existing parallel machines is demonstrated, as well as the scalability of the solver on machines using up to 1450 processors.

Mavriplis, D. J.↗
DOE OSTI2021

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗
NASA NTRS1999

Large-scale Parallel Unstructured Mesh Computations for 3D High-lift Analysis

A complete "geometry to drag-polar" analysis capability for the three-dimensional high-lift configurations is described. The approach is based on the use of unstructured meshes in order to enable rapid turnaround for complicated geometries that arise in high-lift configurations. Special attention is devoted to creating a capability for enabling analyses on highly resolved grids. Unstructured meshes of several million vertices are initially generated on a work-station, and subsequently refined on a supercomputer. The flow is solved on these refined meshes on large parallel computers using an unstructured agglomeration multigrid algorithm. Good prediction of lift and drag throughout the range of incidences is demonstrated on a transport take-off configuration using up to 24.7 million grid points. The feasibility of using this approach in a production environment on existing parallel machines is demonstrated, as well as the scalability of the solver on machines using up to 1450 processors.

Mavriplis, Dimitri J.↗
NASA NTRS1999

Large-Scale Parallel Unstructured Mesh Computations for 3D High-Lift Analysis

A complete "geometry to drag-polar" analysis capability for three-dimensional high-lift configurations is described. The approach is based on the use of unstructured meshes in order to enable rapid turnaround for complicated geometries which arise in high-lift con gurations. Special attention is devoted to creating a capability for enabling analyses on highly resolved grids. Unstructured meshes of several million vertices are initially generated on a work-station, and subsequently refined on a supercomputer. The flow is solved on these refined meshes on large parallel computers using an unstructured agglomeration multigrid algorithm. Good prediction of lift and drag throughout the range of incidences is demonstrated on a transport take-off configuration using up to 24.7 million grid points. The feasibility of using this approach in a production environment on existing parallel machines is demonstrated, as well as the scalability of the solver on machines using up to 1450 processors.

Mavriplis, D. J.↗
DOE OSTI2020

Computationally Efficient Learning of Large Scale Dynamical Systems: A Koopman Theoretic Approach

In recent years there has been a considerable drive towards data-driven analysis, discovery and control of dynamical systems. To this end, operator theoretic methods, namely, Koopman operator methods have gained a lot of interest. In general, the Koopman operator is obtained as a solution to a least-squares problem, and as such, the Koopman operator can be expressed as a closed-form solution that involves the computation of Moore-Penrose inverse of a matrix. For high dimensional systems and also if the size of the obtained data-set is large, the computation of the Moore-Penrose inverse becomes computationally challenging. In this paper, we provide an algorithm for computing the Koopman operator for high dimensional systems in a time-efficient manner. We further demonstrate the efficacy of the proposed approach on two different systems, namely a network of coupled oscillators (with state-space dimension up to 2500) and IEEE 68 bus system (with state-space dimension 204 and up to 24,000 time-points).

Sinha, Subhrajit↗
NASA NTRS1990

Large-scale wind tunnel studies of a jet-engined powered ejector-lift STOVL aircraft

A full-scale model of a supersonic STOVL single engine flighter aircraft employing an ejector to augment lift in hover and in low-speed flight was tested in the 40- by 80-ft and 80- by 120-ft test sections of the National Full-Scale Aerodynamics Complex located at the NASA Ames Research Center. The measured ejector augmentation ratio in hover met the design requirement of 1.6 and continued to provide the lift necessary in forward flight for good transition qualities. The up-and-away aerodynamics (ejector system stowed) were found to be conventional for this class of vehicle. The pitch control provided by the full-span blown flaps is sufficient to control the large pitching moments generated by ventral exhaust nozzle vectoring and propulsion induced aerodynamic effects such as the turning of the flow entrained into the ejectors.

Dudley, Michael R.↗
DOE OSTI2025

ThinCurr: An open-source 3D thin-wall eddy current modeling code for the analysis of large-scale systems of conducting structures

In this paper we present a new thin-wall eddy current modeling code, ThinCurr, for studying inductively-coupled currents in 3D conducting structures -- with primary application focused on the interaction between currents flowing in coils, plasma, and conducting structures of magnetically-confined plasma devices. The code utilizes a boundary finite element method on an unstructured, triangular grid to accurately capture device structures. The new code, part of the broader Open FUSION Toolkit, is open-source and designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components. Scalability to large models is enabled through use of hierarchical off-diagonal low-rank compression of the inductance matrix, which is otherwise dense. Ease of handling large models of complicated geometry is further supported by automatic determination of supplemental elements through a greedy homology approach. Here, a detailed description of the numerical methods of the code and verification of the implementation of those methods using cross-code comparisons against the VALEN code and Ansys commercial analysis software is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1979

Study of mean- and turbulent-velocity fields in a large-scale turbine-vane passage

Laser-Doppler velocimetry, and to a lesser extent hot-wire anemometry, were employed to measure three components of the mean velocity and the six turbulent stresses at four planes within the turbine inlet-guide-vane passage. One variation in the turbulent inlet boundary layer thickness and one variation in the blade aspect ratio (span/axial chord) were studied. A longitudinal vortex (passage vortex) was clearly identified in the exit plane of the passage for the three test cases. The maximum turbulence intensities within the longitudinal vortex were found to be on the order of 2 to 4 percent, with large regions appearing nonturbulent. Because a turbulent wall boundary layer was the source of vorticity that produced the passage vortex, these low turbulence levels were not anticipated. For the three test cases studied, the lateral velocity field extended significantly beyond the region of the longitudinal velocity defect. Changing the inlet boundary layer thickness produced a difference in the location, the strength, and the extent of the passage vortex. Changing the aspect ratio of the blade passage had a measurable but less significant effect. The experiment was performed in a 210 mm pitch, 272 mm axial chord model in low speed wind tunnel at an inlet Mach number of 0.07.

Bailey, D. A.↗
DOE OSTI2021

Functional capacities of microbial communities to carry out large scale geochemical processes are maintained during ex situ anaerobic incubation

Mechanisms controlling CO 2 and CH 4 production in wetlands are central to understanding carbon cycling and greenhouse gas exchange. However, the volatility of these respiration products complicates quantifying their rates of production in the field. Attempts to circumvent the challenges through closed system incubations, from which gases cannot escape, have been used to investigate bulk in situ geochemistry. Efforts towards mapping mechanistic linkages between geochemistry and microbiology have raised concern regarding sampling and incubation-induced perturbations. Microorganisms are impacted by oxygen exposure, increased temperatures and accumulation of metabolic products during handling, storage, and incubation. We probed the extent of these perturbations, and their influence on incubation results, using high-resolution geochemical and microbial gene-based community profiling of anaerobically incubated material from three wetland habitats across a permafrost peatland. We compared the original field samples to the material anaerobically incubated over 50 days. Bulk geochemistry and phylum-level microbiota in incubations largely reflected field observations, but divergence between field and incubations occurred in both geochemistry and lineage-level microbial composition when examined at closer resolution. Despite the changes in representative lineages over time, inferred metabolic function with regards to carbon cycling largely reproduced field results suggesting functional consistency. Habitat differences among the source materials remained the largest driver of variation in geochemical and microbial differences among the samples in both incubations and field results. While incubations may have limited usefulness for identifying specific mechanisms, they remain a viable tool for probing bulk-scale questions related to anaerobic C cycling, including CO 2 and CH 4 dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Large-Scale Boundary Layer Ingesting Propulsor Research

NASA’s Advanced Air Transport Technology (AATT) project is investigating boundary layer ingesting (BLI) propulsors for advanced subsonic commercial vehicle concepts to enable the reduction of fuel burn. A multidisciplinary team of researchers from NASA, United Technologies Research Center (UTRC), Virginia Polytechnic University, and the Air Force Arnold Engineering Development Complex developed and tested an embedded BLI inlet and distortion-tolerant fan (BLI2DTF) system in the NASA Glenn Research Center (GRC) 8- foot by 6-foot (8x6) transonic wind tunnel. The test demonstrated the component performance goals necessary for an overall fuel burn reduction of 3 to 5 percent on a large hybrid wing body (HWB) aircraft. Special test equipment, including a raised floor with flow effectors and a bleed system, was developed for use in the 8x6 to produce the appropriate incoming boundary layer representative of an HWB application. Detailed measurements were made to determine the inlet total pressure loss and distortion, fan stage efficiency, and aeromechanic performance including blade vibration stress and displacement response. Results from this test were used as input to a vehicle-level system study performed by the AATT project to assess the impact of BLI on an alternative advanced concept aircraft referred to as the NASA D8 (ND8), which is somewhat similar to the HWB in its integration of the propulsor. This paper will provide an overview of the project timeline, special test equipment needed in the wind tunnel to develop the appropriate incoming boundary layer, and the difficulties in designing a propulsor for the test. The paper will conclude with some representative aerodynamic and aeromechanic data from the test itself and conclude with how this data was used in the ND8 system study.

Aerodynamic performance↗
NASA NTRS2019

Large-Scale Boundary Layer Ingesting Propulsor Research

_NASA's Advanced Air Transport Technology (AATT) project is investigating boundary layer ingesting (BLI) propulsors for advanced subsonic commercial vehicle concepts to enable the reduction of fuel burn. A multidisciplinary team of researchers from NASA, United Technologies Research Center (UTRC), Virginia Polytechnic University, and the Air Force Arnold Engineering Development Complex developed and tested an embedded BLI inlet and distortion-tolerant fan (BLI2DTF) system in the NASA Glenn Research Center (GRC) 8-foot by 6-foot (8x6) transonic wind tunnel. The test demonstrated the component performance goals necessary for an overall fuel burn reduction of 3 to 5 percent on a large hybrid wing body (HWB) aircraft. Special test equipment, including a raised floor with flow effectors and a bleed system, was developed for use in the 8x6 to produce the appropriate incoming boundary layer representative of an HWB application. Detailed measurements were made to determine the inlet total pressure loss and distortion, fan stage efficiency, and aeromechanic performance including blade vibration stress and displacement response. Results from this test were used as input to a vehicle-level system study performed by the AATT project to assess the impact of BLI on an alternative advanced concept aircraft referred to as the NASA D8 (ND8), which is somewhat similar to the HWB in its integration of the propulsor. This paper will provide an overview of the project timeline, special test equipment needed in the wind tunnel to develop the appropriate incoming boundary layer, and the difficulties in designing a propulsor for the test. The paper will conclude with some representative aerodynamic and aeromechanic data from the test itself and conclude with how this data was used in the ND8 system study.

Celestina, Mark L.↗
DOE OSTI2022

Large Scale MD to Predict Epitope Regions in HIV Env [Slides]

Highly dense carbohydrates located on the surface of the HIV Env protein play a key role in immune evasion. Such evolutionary adaptation hampers any attempt to obtain a full mechanistic understanding of the role played by the glycans in protecting the virus against an effective immune response. Moreover, and due to their chemical variability, an accurate molecular understanding of the so called “glycan shield” is still limited by the lack of effective resolution of state-of-the-art experimental technics. Here, we have used extensive computational modelling in order to fill this gap, addressing the presence of a large glycan variability as observed experimentally. Based on an automated pipeline, we were able to assemble, set-up and simulate via Molecular dynamics hundreds of different glycosylated Env variants at nearly atomic resolution, recapitulating the glycosylation distributions observed experimentally. Results from these simulations were subjected to machine learning and very accurate prediction of simulation derived glycan shielding areas of each glycan as a function of static sequence features. Such predictive models of per-glycan shielding, incorporating both glycan dynamics and heterogeneity, were used to develop a novel sequence-based glycan shield mapping strategy. Parallel to these studies, we also developed an accurate machine learning approach to predict glycan heterogeneity data using sequence features and found good prediction accuracy.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Large-scale counterstreaming of H(+) and He(+) along plasmaspheric flux tubes

An interhemispheric plasma transport model is used to study the flow characteristics of H(+), He(+), and O(+) along closed geomagnetic field lines for solstice conditions. The model corresponds to a time-dependent solution of the coupled continuity, momentum, and energy equations for the ions and electrons. The equations are solved along an entire flux tube from 120 km in one hemisphere to 120 km in the other hemisphere. The calculations are carried out for noon conditions for the flux tube passsing through Millstone Hill, at L = 3.2. The main conclusion is that H(+)-He(+) counterstreaming can be expected along a large segment of a plasmaspheric flux tube at solstice. For both symmetric and asymmetric wind patterns, the He(+) flow is from the winter to the summer ionosphere not only in the steady state, but during flux tube refilling due to the winter helium bulge and the depletion of N2.

Richards, P. G.↗
DOE OSTI2025

Large-scale deep learning for metastasis detection in pathology reports

Objectives No existing algorithm can reliably identify metastasis from pathology reports across multiple cancer types and the entire US population. In this study, we develop a deep learning model that automatically detects patients with metastatic cancer by using pathology reports from many laboratories and of multiple cancer types. Materials and Methods We use 60 471 unstructured pathology reports from 4 Surveillance, Epidemiology, and End Results (SEER) registries. The reports were coded into 1 of 3 labels: metastasis negative, metastases positive, or metastasis undetermined. We utilize a task-specific deep neural network trained from scratch and compare its performance with a widely used large language model (LLM). Results Our deep learning architecture trained on task-specific data outperforms a general-purpose LLM, with a recall of 0.894 compared to 0.824. We quantified model uncertainty and used it to defer reports for human review. We found that retaining 72.9% of reports increased recall from 0.894 to 0.969. Discussion A smaller deep learning architecture trained on task-specific data outperforms a general LLM. Equally critical to model performance is the incorporation of uncertainty quantification, achieved here through an abstention mechanism. Conclusions This study’s finding demonstrate the feasibility of developing algorithms to automatically identify metastatic cancer cases from unstructured pathology reports.

machine learning↗
NASA NTRS1984

Large-scale Bubble Structure of the Intersteller Medium (ISM) and Properties of the Local Spiral Arm (LSA)

Bubbles which are very common structure units in the Galaxy and galaxies were examined. Collection of radio, optical, infrared and X-ray observations of the Cyg superbubble (CSB) region of the sky show that the CSB is not a single bubble object. Between 50 to 75 percent of its X-ray emission is ascribed to discrete sources. The other 25 to 50% X-ray emission, probably originates from bubbles around 8 OB associations of the region. All bubbles located within the spiral structure of Galaxy, M31 and M33 have diameter 300 pc. The large distance of stellar association from the galactic plane (GP) combined with picture of the gas distribution within the LSA shows that a Reyleigh-Taylor instability in the LSA can develop and give use to the formation of compact stellar clusters, such as the Cyg OB2 association. Development stages of the Reyleigh-Taylor instability, some peculiarities of the dust distribution and departures of the local structure from the galactic grand design suggest the absence of a spiral shockwave in the LSA.

Bochkarev, N. G.↗
DOE OSTI2024

Sparse-Stochastic Fragmented Exchange for Large-Scale Hybrid Time-Dependent Density Functional Theory Calculations

Here we extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state near-gap hybrid DFT to calculate absorption spectra within linear-response time-dependent generalized Kohn-Sham DFT (LR-GKS-TDDFT) for systems consisting of thousands of valence electrons within a grid-based/plane-wave representation. A mixed deterministic/fragmented-stochastic compression of the exchange kernel, here using long-range explicit exchange functionals, provides an efficient method for accurate optical spectra. Both real-time propagation as well as frequency-resolved Casida-equation-type approaches for spectra are presented, and the method is applied to large molecular dyes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of the Large-Scale and Regional Climatic Response Across North Africa to Natural Variability in Oceanic Modes and Terrestrial Vegetation Among the CMIP5 Models

Hydrologic variability is a serious threat to the poverty-stricken regions of North Africa. Meanwhile, the scientific community struggles to attribute these extreme climatic episodes to specific oceanic and land drivers. Prior modeling studies have not assessed simulated feedbacks over North Africa against an established observational benchmark, so their results are considered as untested, model-specific findings. The Coupled Model Intercomparison Project Phase Five (CMIP5) archive represents the state-of-the-art in climate projections, with most CMIP5 models now containing interactive vegetation phenology; however, there have been no studies to date of their simulated vegetation feedbacks. The capability of CMIP5 models at accurately simulating the forcing of both sea-surface temperature (SST) and regional leaf area index (LAI) anomalies on North African climate needs to be a key consideration in assessing the models’ overall credibility and determining appropriate model weighting for developing climate projections. The Generalized Equilibrium Feedback Assessment (GEFA) is a promising statistical method, which can be applied to either model output or observations, for isolating the local and remote impacts of individual oceanic or terrestrial forcings on regional climate. We performed a combined observational and modeling assessment of land-ocean-atmosphere interactions across the distinct ecological and moisture gradients of North Africa. We evaluated and demonstrated the reliability of the GEFA statistical method over North Africa using the Community Earth System Model (CESM), applied GEFA to observational data to quantify the observed forcing of ocean basin SST anomalies and regional LAI anomalies on North African climate, evaluated the CMIP5 models’ performance in terms of representing these key observed feedbacks, and formulated CMIP5 feedback performance metrics for weighting North African climate projections. Our study represented the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, the first systematic assessment and intercomparison of land-ocean-atmosphere feedbacks in CMIP5, and the first exploration of vegetation feedbacks among CMIP5 models. The following work was accomplished. (1) The team generated 14 scientific publications and 30 presentations based on the DOE-funded research. (2) A stepwise version of the GEFA statistical method was developed in which unimportant forcings were dropped to increase the reliability of the results. (3) SGEFA was successfully validated through experiments with CESM in terms of its ability to isolate the atmospheric responses to individual oceanic or land forcings. (4) Observational evidence was revealed for the Sahel’s positive vegetation-rainfall feedback on the seasonal to interannual time scale, and it was attributed to a moisture recycling mechanism rather than an albedo mechanism. (5) An approach with SGEFA was developed in which the individual contributions of soil moisture versus vegetation forcings could be separated, revealing that the former forcing outweighed the latter for sub-Saharan Africa. (6) Tropical ocean temperatures were found to be key regulators of pan-tropical vegetation variability, especially for arid and semi-arid regions, including sub-Saharan Africa. (7) The CMIP5 models largely underestimated the importance of land feedbacks across the Sahel. (8) The general consensus among CMIP5 models indicates, for the late 21st century, a diminished seasonal predictability of sub-Saharan African regional climate and an elevated role of the land surface compared to oceanic drivers in regulating regional climate variability. (9) Land-ocean-atmosphere interactions were demonstrated to be key contributors to the seasonal predictability of African wildfire activity. (10) The El Djouf was determined to be of greater importance than the Bodélé depression in terms of providing trans-Atlantic dust transport to the Americas.

54 ENVIRONMENTAL SCIENCES↗