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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The “Who” and “How” of Microbial Control over Soil Carbon Dynamics: a Multi-omics, Stable Isotope Probing, and Modeling Approach

Soils are the largest repository of organic carbon (C) in the terrestrial biosphere and represent an important source of CO 2 to the atmosphere, releasing 60-75 Pg C annually through microbial decomposition of organic materials. Microbes are key drivers of C cycling, and exhibit a large range in C use efficiency (CUE). CUE is the substrate C incorporated into biomass per substrate assimilated. While small changes in CUE can have profound effects on soil CO 2 flux, our understanding of the intersection of genomic and abiotic factors driving soil CUE dynamics is still very limited. Our long-term goal is to better predict the fate of soil C by developing mathematical and ecosystem models of SOM decomposition that incorporate a genetic and physiological understanding of CUE. The goal of this work was to define genes, metabolic pathways, and phylogenetic signals associated with microbial CUE for terrestrial microorganisms (bacteria and fungi). Our specific objectives are to: (1) Define genomic markers that indicate how terrestrial bacteria and fungi change CUE in response to environmental drivers of microbial activity; (2) Determine how well genomic markers identified predict CUE in soils; and (3) Improve predictions of soil C by incorporating genomics-informed CUE into ecosystem C models based on genomic features defined in and validated for soil in the course of this work. We address these objectives by coupling multi-omics analyses (genomics, metatranscriptomics) with physiological assays (CUE, enzyme activities) across environmental drivers (substrate quantity/quality, temperature, moisture). We employ a hierarchical approach to incrementally scale from cells to ecosystems, starting with pure cultures of bacteria and fungi, then mock communities in artificial, organic matter-free soil, then finally field soil manipulated to elicit microbial communities differing in community composition and CUE. By focusing on microbial isolates and communities in a temperate forest (Harvard Forest), we leverage a rich context for validating data based on multiple ongoing field, lab and modeling studies of soil C cycling. This research couples two culture collections of fungi and bacteria isolated from the Harvard Forest, along with over a decade of field measurements of CUE and C cycling, and microbial community analyses using metagenomics and metatranscriptomics. Because microbial feedbacks to the environment are regulated at the organismic level, the foundation of this research is the physiology and genomics of CUE among isolates that we have determined to be either dominant in our soil system, sensitive to climate change factors, or both. A series of three experiments using artificial soil, lab incubation of field-collected soil, and a field manipulation is designed to validate potential omics-informed, novel genomic markers to be used as proxies for CUE in models. We test our new understanding of the genetic basis for CUE and its implications for soil C dynamics using the trait-based model DEMENT and the ecosystem models MIIMICS and SCAMPS. All models are modified to simulate SOM decomposition in mineral soils and validated with other temperate forest climate change manipulation studies. By developing mathematical and ecosystem models of SOM decomposition that incorporate a genetic and physiological understanding of CUE, we hope to facilitate more realistic models of SOM decomposition for C cycling in soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis

Accurate and timely forecasts of CO 2 plume distribution throughout the injection and post-injection phases are crucial for detecting plume migration, assessing leakage risks, and supporting operational decisions in geologic carbon storage (GCS). Current convolutional neural network-based approaches primarily focus on spatial information and overlook temporal dependencies in plume distributions, thus limiting their ability to capture dynamic movement effects and provide accurate predictions of plume migration. In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED)-ConvLSTM, each uniquely designed to capture both spatial and temporal features. We apply the proposed methods to forecast the dynamic distribution of CO 2 plumes based on 108 reservoir simulations over a 30-year injection and a 30-year post-injection period. The results indicate that the ED-ConvLSTM model outperforms the AE-LSTM model in accurately predicting the spatiotemporal dynamics of CO 2 plume migration, achieving R 2 values above 0.99. To provide a deeper understanding of these model predictions, we employ a gradient-based explanation method on the trained models. This approach provides insights into the influence of input variables on plume migration forecasts and uncovers the underlying prediction mechanisms of the proposed models. Furthermore, we introduce a transfer learning technique, enabling fast and accurate plume migration forecasting in the post-injection phase by leveraging the trained model during the injection phase. This reduces the necessity for extensive data collection or re-training. In conclusion, the methods proposed in our work enhances the performance and interpretability of CO 2 plume migration forecasts, thereby facilitating informed decision-making throughout the entire lifecycle of GCS applications.

58 GEOSCIENCES↗
NASA NTRS1985

Management behavior, group climate and performance appraisal at NASA

The relationships among manager behavior, group climate and managerial effectiveness are examined. Survey data were collected from 435 GM14-15 managers and their subordinates at NASA concerning management practices and perceptions of the group environment. Performance ratings of managers were obtained from their superiors. The results strongly supported a causal model in which subordinates' climate perceptions mediate the effects of manager behavior on performance. That is, the development of group climate provides the process through which the effects of manager practices may be understood. Analyses also revealed that the function performed by a manager and his group (e.g., research) influenced the specific nature of the causal dynamics. Some implications of the results for management training and development are discussed.

Manderlink, G.↗
NASA NTRS2002

Air Traffic Control Response to Delays: A System Study of Newark International Airport

Airport delays are a significant problem in the United States air transportation system. Between 1999 and 2000 the number of flights delayed increased by 20 percent despite only a 0.4% increase in total operations. Newark International Airport (EWR), one of New York City's primary airports, is one of the airports in the United States most impacted by delays. Newark had the highest percentage of operations delayed in 1999, and was second only to LaGuardia Airport in 2000. Nearly 85% of delays at Newark are caused by adverse weather impacting an airport that may be characterized as having limited capacity and a very full schedule. Although Newark is heavily impacted by weather, delays have not increased significantly since 1998. This indicates that the airlines, air traffic control (ATC), and the Port Authority of New York and New Jersey have successfully adapted. On June 29, 2000, a research team from MIT visited Newark airport to assess the effectiveness of any adaptations made, and to collect data on airline and ATC departure operations, and of the national and local weather affecting the airport. Airline and ATC personnel were also interviewed. Results of this study indicate that airspace capacity limitations downstream of the airport are a primary flow constraint at the airport, and that these constraints are the source of most surface delays. A number of tactical ATC responses to delays were examined, including the application of restrictions, re-routing with the help of the National Playbook, and the use of decision-aiding tools such as the Dynamic Spacing Program (DSP) and the Integrated Terminal Weather System (ITWS). Improved interfacility communications and further utilization of runway 11-29 were identified as other tactical responses to delays, whilst the formation of the Air Traffic Control System Command Center and the New York Airspace redesign were identified as thekey strategic ATC responses to delays. Particularly the New York airspace redesign has great potential to reduce delays at the airport. Because delays at Newark are caused by downstream flow constraints, the responses at the airport can be applied to other airports as delays from downstream constraints increase. Such an increase in delays system wide from downstream constraints is inevitable as the system becomes more congested.

Evans, Antony D.↗
NASA NTRS2010

Human Habitation in a Lunar Electric Rover During a 14-Day Field Trial

Various military and commercial entities, as well as the National Aeronautics and Space Administration (NASA), have conducted space cabin confinement studies. However, after an extensive literature search, only one study was found using a simulated lunar rover (LUNEX II), under laboratory conditions, with a crew of two for an eighteen day lunar mission. Forty-three years later, NASA human factors engineers conducted a similar study using the Lunar Electric Rover (LER) in a dynamic real-world lunar simulation at the Black Point Lava Flow in Arizona. The objective of the study was to obtain human-in-the-loop performance data on the vehicle s interior volume with respect to human-system interfaces, crew accommodations, and habitation over a 14-day mission. Though part of a larger study including 212 overall operational elements, this paper will discuss only the performance of fifty different daily habitational elements within the confines of the vehicle carried out by two male subjects. Objective timing data and subjective questionnaire data were collected. Results indicate, much like the LUNEX II study, the LER field study suggest that a crew of two was able to maintain a satisfactory performance of tasks throughout the 14-day field trail within a relative small vehicle volume.

Litaker, Harry, Jr.↗
NASA NTRS2011

Trajectory-Based Complexity (TBX): A Modified Aircraft Count to Predict Sector Complexity During Trajectory-Based Operations

In this paper we introduce a new complexity metric to predict -in real-time- sector complexity for trajectory-based operations (TBO). TBO will be implemented in the Next Generation Air Transportation System (NextGen). Trajectory-Based Complexity (TBX) is a modified aircraft count that can easily be computed and communicated in a TBO environment based upon predictions of aircraft and weather trajectories. TBX is scaled to aircraft count and represents an alternate and additional means to manage air traffic demand and capacity with more consideration of dynamic factors such as weather, aircraft equipage or predicted separation violations, as well as static factors such as sector size. We have developed and evaluated TBX in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center during human-in-the-loop studies of trajectory-based concepts since 2009. In this paper we will describe the TBX computation in detail and present the underlying algorithm. Next, we will describe the specific TBX used in an experiment at NASA's AOL. We will evaluate the performance of this metric using data collected during a controller-inthe- loop study on trajectory-based operations at different equipage levels. In this study controllers were prompted at regular intervals to rate their current workload on a numeric scale. When comparing this real-time workload rating to the TBX values predicted for these time periods we demonstrate that TBX is a better predictor of workload than aircraft count. Furthermore we demonstrate that TBX is well suited to be used for complexity management in TBO and can easily be adjusted to future operational concepts.

trajectories↗
NASA NTRS2016

Application of High Speed Digital Image Correlation in Rocket Engine Hot Fire Testing

Hot fire testing of rocket engine components and rocket engine systems is a critical aspect of the development process to understand performance, reliability and system interactions. Ground testing provides the opportunity for highly instrumented development testing to validate analytical model predictions and determine necessary design changes and process improvements. To properly obtain discrete measurements for model validation, instrumentation must survive in the highly dynamic and extreme temperature application of hot fire testing. Digital Image Correlation has been investigated and being evaluated as a technique to augment traditional instrumentation during component and engine testing providing further data for additional performance improvements and cost savings. The feasibility of digital image correlation techniques were demonstrated in subscale and full scale hotfire testing. This incorporated a pair of high speed cameras to measure three-dimensional, real-time displacements and strains installed and operated under the extreme environments present on the test stand. The development process, setup and calibrations, data collection, hotfire test data collection and post-test analysis and results are presented in this paper.

Gradl, Paul R.↗
DOE OSTI2019

Tracking Aerosol Convective Interactions Experiment (TRACER) Science Plan

Convective clouds play an important role in the Earth’s climate system as a driver of large-scale circulations and a primary mechanism for the transport of heat, moisture, aerosols, and momentum throughout the troposphere. Despite their climatic importance, multi-scale models continue to have persistent biases produced by insufficient representation of convective clouds. This is the result of an incomplete understanding of key processes such as convective initiation, updraft and downdraft dynamics, cloud and precipitation microphysics, and aerosol-convection interactions. The Aerosol-Cloud-Precipitation-Climate Initiative, an international research group dedicated to advancing understanding of aerosol impacts on clouds relevant to climate, has identified the Houston, Texas region as an optimal location for targeted studies of aerosol-convection interactions within frequently developing isolated deep convection. Houston lies within a humid subtropical climate regime, where onshore flow and sea-breeze convection interact with a range of aerosol conditions associated with Houston’s urban and industrial emissions. Pilot studies have suggested that convective clouds in this region are potentially significantly impacted by the varying aerosol conditions. To increase our understanding of convective cloud life cycles and aerosol-convection interactions, the Tracking Aerosol Convection Interactions Experiment (TRACER) aims to collect a comprehensive data set focused on the evolution of convective clouds and the environment (including aerosol, cloud, thermodynamics, and lightning) in which the clouds initiate, grow, and decay. A unique component of TRACER is that a large number of individual, isolated convective cells will be tracked and measured in high spatial and temporal resolution for the purposes of: (i) Characterizing and linking convective cloud kinematic and microphysical life cycles, (ii) Quantifying environmental thermodynamic and kinematic controls on convective life cycle properties, (iii) Isolating and quantifying the impacts of aerosol properties on convective cloud kinematic and microphysical evolution. TRACER includes a one-year deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first ARM Mobile Facility (AMF1) and second-generation C-Band Scanning ARM Precipitation Radar (CSAPR2) aimed at collecting statistical data sets of cloud, precipitation, atmospheric state, and aerosol under varying aerosol loading and local circulation (sea breeze and urban heat island) conditions. A four-month intensive operational period (IOP) from June through September will include deployment of an ancillary site with aerosol, atmospheric state, and precipitation measurements at a location rarely impacted by Houston’s anthropogenic emissions, which will be commonplace near the AMF1 site. Convective cell tracking by the CSAPR2 will provide high-resolution polarimetric and velocity observations under a range of environmental (including aerosol loading) conditions. High-frequency radiosonde launches will capture quickly evolving thermodynamic and kinematic conditions near convective cells, a requirement for isolating aerosol effects on clouds. TRACER will additionally leverage a lightning mapping array, surface meteorological networks, and air pollution networks, and proposals will be entered to deploy additional mobile radar and radiosonde assets during the IOP. This unique combination of cloud, precipitation, lightning, aerosol, and atmospheric state measurements associated with tracked convective cells will ultimately improve our understanding of the convective cloud life cycle and its interaction with individual environmental factors such that improved, next-generation cumulus, microphysics, turbulence, and aerosol parameterizations can be designed.

Convective clouds, aerosols, cloud life cycle, atm↗
DOE OSTI2017

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Transverse spin effects in hard semi-inclusive collisions

The nucleons (protons and neutrons) are by far the most abundant form of matter in our visible Universe; they are composite particles made of quarks and gluons, the fundamental quanta of Quantum Chromo Dynamics (QCD). The usual interpretation of the nucleon dynamics in high energy interactions is often limited to a simple one-dimensional picture of a fast moving nucleon as a collection of co-linearly moving quarks and gluons (partons), interacting accordingly to perturbative QCD rules. However, massive experimental evidence shows that, in particular when transverse spin dependent observables are involved, such a simple picture is not adequate. The intrinsic transverse motion of partons has to be taken into account; this opens the way to a new, truly 3-dimensional (3D) study of the nucleon structure. A review of the main experimental data, their interpretation and understanding in terms of new transverse momentum dependent partonic distributions, and the progress in building a 3D imaging of the nucleon is presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

A search for companions to brown dwarfs in the Taurus and Chamaeleon star-forming regions

We have used WFPC2 on board the Hubble Space Telescope to obtain images of 47 members of the Taurus and Chamaeleon I star-forming regions that have spectral types of M6-L0 (M ∼ 0.01-0.1 M {sub ☉}). An additional late-type member of Taurus, FU Tau (M7.25+M9.25), was also observed with adaptive optics at Keck Observatory. In these images, we have identified promising candidate companions to 2MASS J04414489+2301513 (ρ = 0.''105/15 AU), 2MASS J04221332+1934392 (ρ = 0.''05/7 AU), and ISO 217 (ρ = 0.''03/5 AU). We reported the first candidate in a previous study, showing that it has a similar proper motion as the primary in images from WFPC2 and Gemini adaptive optics. We have collected an additional epoch of data with Gemini that further supports that result. By combining our survey with previous high-resolution imaging in Taurus, Chamaeleon I, and Upper Sco (τ ∼ 10 Myr), we measure binary fractions of 14/93 = 0.15{sub −0.03}{sup +0.05} for M4-M6 (M ∼ 0.1-0.3 M {sub ☉}) and 4/108 = 0.04{sub −0.01}{sup +0.03} for >M6 (M ≲ 0.1 M {sub ☉}) at separations of >10 AU. Given the youth and low density of these regions, the lower binary fraction at later types is probably primordial rather than due to dynamical interactions among association members. The widest low-mass binaries (>100 AU) also appear to be more common in Taurus and Chamaeleon I than in the field, which suggests that the widest low-mass binaries are disrupted by dynamical interactions at >10 Myr, or that field brown dwarfs have been born predominantly in denser clusters where wide systems are disrupted or inhibited from forming.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Data from "A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans"

Processed LiDAR data and environmental covariates from 2015 and 2019 LiDAR scans in the Vicinity of Snodgrass Mountain (Western Colorado, USA), in a geographic subset used in primary analysis for the research paper.This package contains LiDAR-derived canopy height maps for 2015 and 2019, crown polygons derived from the height maps using a segmentation algorithm, and environmental covariates supporting the model of forest growth. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Colorado Hazard Mapping Program and the Colorado Water Conservation Board. Both datasets adhere to the USGS QL2 quality standard. The point cloud data were processed using the R package lidR to generate a canopy height model representing maximum vegetation height above the ground surface, using a pit-free algorithm.This dataset was compiled to assess how spatial patterns of tree growth in montane and subalpine forests are influenced by water and energy availability. Understanding these growth patterns can provide insight into forest dynamics in the Southern Rocky Mountains under changing climatic conditions.This dataset contains .tif, .csv, and .txt files. This dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

JSPEC: A Program for IBS and Electron Cooling Simulation

Intrabeam scattering is an important collective effect that can deteriorate the properties of a high-intensity beam, and electron cooling is a method to mitigate the IBS effect. JSPEC (JLab Simulation Package for Electron Cooling) is an open-source program developed at Jefferson Lab, which simulates the evolution of the ion beam under the IBS and/or the electron cooling effect. JSPEC has been benchmarked with BETACOOL and experimental data. In this report, we will introduce the features of JSPEC, including the friction force calculation, the IBS expansion rate and electron cooling rate calculation, and the beam-dynamic simulations for the electron cooling process; explain how to set up the simulations in JSPEC; and demonstrate the benchmarking results.

Zhang, He↗
DOE OSTI2022

What’s in My Toolkit? A Review of Technologies for Assessing Changes in Habitats Caused by Marine Energy Development

Marine energy devices are installed in highly dynamic environments and have the potential to affect the benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats, and selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Technologies and sampling methods that are designed for working efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2 ) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2 , decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Altimetry for the Future: Building on 25 Years of Progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.

Saleh Abdalla↗
NASA NTRSDate not supplied

Efficient Variable-Pitch Propeller Aerodynamic Model Development for Vectored-Thrust eVTOL Aircraft

This paper describes a variable-pitch propeller testing and aerodynamic modeling methodology for electric vertical takeoff and landing (eVTOL) aircraft using wind tunnel testing. Propellers used for eVTOL aircraft propulsion systems experience a wide range of operating conditions resulting in significant variation of axial thrust and torque, as well as off-axis forces and moments, across a typical flight envelope. An experimental design is developed to collect informative wind tunnel data in an efficient manner using response surface methods. System identification methods are then applied to isolated propeller wind tunnel data to develop a mathematical model of the propeller valid throughout the transition envelope of a vectored-thrust eVTOL aircraft. Multiple explanatory variable definitions are postulated and compared using modeling and prediction performance metrics. Modeling results validated against data withheld from the modeling process indicate good predictive capability and agree with theoretical expectations. All identified propeller models are provided, which allows the models to be used in future eVTOL aircraft flight dynamics simulations.

aerodynamic modeling↗

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