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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China 2004-2013

Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

satellite remote sensing↗
NASA NTRS2018

Regional Replay: A Unique Reanalysis-Based Tool for Addressing Model Error

Understanding and correcting errors in general circulation and climate models has long been part intuition and part trial and error. Efforts to diagnose the errors and provide some guidance to developers have been of some value, though such efforts, with few exceptions, have been more successful in identifying and documenting the errors in the model simulations rather than the model deficiencies that produced them. Modern atmospheric reanalyses such as MERRA-2 provide much-improved estimates of our climate system at hourly to interannual and longer time scales and have become an important tool for assessing model performance. Here we use MERRA-2 to address biases in the NASA/GMAO GEOS model by employing a "regional replay" approach developed in the GMAO. The regional replay approach constrains the model to remain close to the reanalysis over arbitrary regions and selected model variables, thus allowing us to examine how model error generated over one area is spatially translated across the globe. Several examples are given including an assessment of the global impact of errors produced over the Tibet region.

Tibet Region↗
NASA NTRS2016

Creating Systems Engineering Products with Executable Models in a Model-Based Engineering Environment

Applying systems engineering across the life-cycle results in a number of products built from interdependent sources of information using different kinds of system level analysis. This paper focuses on leveraging the Executable System Engineering Method (ESEM) which automates requirements verification (e.g. power and mass budget margins and duration analysis of operational modes) using executable SysML models. The particular value proposition is to integrate requirements, and executable behavior and performance models for certain types of system level analysis. The models are created with modeling patterns that involve structural, behavioral and parametric diagrams, and are managed by an open source Model Based Engineering Environment (named OpenMBEE). This paper demonstrates how the ESEM is applied in conjunction with OpenMBEE to create key engineering products (e.g. operational concept document) for the Alignment and Phasing System (APS) within the Thirty Meter Telescope (TMT) project, which is under development by the TMT International Observatory (TIO).

MBSE↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗
NASA NTRSDate not supplied

Instrumentation for Measuring Entry Radiative Heating - Past, Present, and Future

Radiative heating can be a significant contributor to the total heat load during atmospheric entry, especially for large vehicles with high entry velocties. For example, the stagnation region heat load derived from thermocouples embedded in the thermal protection system (TPS)of the Mars Science Laboratory (MSL) heatshield did not match the unmargined pre-flight predictions. This was at least partially attributed to the fact that radiative heating was not accounted for in the unmargined pre-flight predictions [2].Since MSL, significant work has been done to update radiative heating models and test how the models perform compared to ground-based test facilities such as shock tubes. The models and ground-based tests have shown that radiative heating can be significant for entry into the atmospheres of Venus, Earth, Mars, and Titan, among other planetary bodies. However, there are still discrepancies between the models and the test data, which is where the desire for flight data comes in to play. Missions that have had or are currently planned to have instrumentation to measure radiative heating during atmospheric entry are listed in Table 1.

R A Miller↗
NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation andits impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after exposure to stress, which may be expected based in part on rodent responses found afterexposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperilmission accomplishment. If mission-relevant animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗
NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation and its impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after expo-sure to stress, which may be expected based in part on rodent responses found after exposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperil mission accomplishment. If mission-relevant yet animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗
NASA NTRSDate not supplied

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗
NASA NTRS2021

The Case for a 50+ Year Radioisotope Power System

The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is leading the NASA funded Interstellar Probe study to explore the “Very Local” interstellar medium. To perform this exploration the mission will be required to last at least 50 years in regions of space where solar power is no longer practical. Additionally, several new studies for the National Academies’ Planetary Science and Astrobiology Decadal Survey are planning missions lasting 20-35 years. The Decadal Survey is used to build consensus on priority of national science goals. These proposed missions are inconsistent with the NASA’s current Radioisotope Power Systems (RPS) life requirement of 14 years (flight). Paramount to these proposed long-duration missions are questions about the longevity of such a mission. Evidence exists that space-borne Radioisotope Power Systems can indeed last a long time. LES-9, Voyager I, and Voyager II are over 40 years old, LES-8, Pioneer 10, and Pioneer 11 lasted 28, 30, and 22 years, respectively, and New Horizons is still active 15 years after launch. This paper explores the need for RPS designs that are intended to last much longer than the current requirement of 14 years (17 years after fueling) and explores the historical record for actual vs design lifetimes to show the feasibility of building long lasting RPS. We also exercise a current RTG performance model of the General-Purpose Heat Source RTG using the JPL Lifetime Performance Prediction (LPP) tool to make top-level inferences about power output at end-of-mission, and discusses how reliability engineering and testing methods can be brought to bear to increase confidence in delivering sufficient power at end-of-mission.

Phan, Brian↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).

Brett Raczka↗
NASA NTRSDate not supplied

Impact of Technology and Mission Variations on Aircraft Designed for Advanced Air Mobiity

NASA is conducting investigations in Advanced Air Mobility (AAM) aircraft and operations, including the development of Urban Air Mobility (UAM) aircraft designs that can be used to focus and guide research activities in support of AAM. This report is an investigation of the impact of technology and mission variations on several of the NASA AAM concept aircraft: quadrotor, quiet single main rotor, side-by-side, and tiltrotor configurations, with turboshaft and electric propulsion variants for each. First, the mission and aircraft models of the baseline designs were reassessed and updated, including rotor geometry optimization, update of the rotor performance models, and disk loading optimization. For these eight designs, technology and mission excursions were performed. Relative to the calibration cases that can be considered examples of good design practice, the impact of the weight technology factors is significant. For the electric aircraft, there is a very large impact of battery specific energy (Wh/kg), and correspondingly a very large impact of mission range. The vision of Advanced Air Mobility is driven by missions that will enable new transportation capabilities. Hence it is appropriate to compare Concept Vehicles of different lift and propulsive architectures, all designed to accomplish the same UAM mission. It is also useful however to consider specific missions that can take advantage of the strengths of individual aircraft configurations. So alternate designs were also developed for the concept vehicles: for turboshaft aircraft, longer unrefueled range, including faster cruise speed for the tiltrotor; for electric aircraft, shorter range and more realistic battery weight.

Technology↗
NASA NTRS1999

Aftbody Closure Model Design: Lessons Learned

An Aftbody Closure Test Program is necessary in order to provide aftbody drag increments that can be added to the drag polars produced by testing the performance models (models 2a and 2b). These models had a truncated fuselage, thus, drag was measured for an incomplete configuration. In addition, trim characteristics cannot be determined with a model with a truncated fuselage. The stability and control tests were conducted with a model (model 20) having a flared aftbody. This type aftbody was needed in order to provide additional clearance between the base of the model and the sting. This was necessary because the high loads imposed on the model for stability and control tests result in large model deflections. For this case, the aftbody model will be used to validate stability and control performance.

Capone, Francis J.↗
NASA NTRS2009

Development of an On-board Failure Diagnostics and Prognostics System for Solid Rocket Booster

We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.

Smelyanskiy, Vadim N.↗
NASA NTRS1992

Cold flow testing of the Space Shuttle Main Engine alternate turbopump development high pressure fuel turbine model

NASA's Marshall Space Flight Center has established a cold airflow turbine test program to experimentally determine the performance of liquid rocket engine turbopump drive turbines. Testing of the SSME alternate turbopump development (ATD) fuel turbine was conducted for back-to-back comparisons with the baseline SSME fuel turbine results obtained in the first quarter of 1991. Turbine performance, Reynolds number effects, and turbine diagnostics, such as stage reactions and exit swirl angles, were investigated at the turbine design point and at off-design conditions. The test data showed that the ATD fuel turbine test article was approximately 1.4 percent higher in efficiency and flowed 5.3 percent more than the baseline fuel turbine test article. This paper describes the method and results used to validate the ATD fuel turbine aerodynamic design. The results are being used to determine the ATD high pressure fuel turbopump (HPFTP) turbine performance over its operating range, anchor the SSME ATD steady-state performance model, and validate various prediction and design analyses.

Gaddis, Stephen W.↗
NASA NTRS1998

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗