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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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NASA NTRS2005

Chemical Modeling for Studies of GeoTRACE Capabilities

Geostationary measurements of tropospheric pollutants with high spatial and temporal resolution will revolutionize the understanding and predictions of the chemically linked global pollutants aerosols and ozone. However, the capabilities of proposed geostationary instruments, particularly GeoTRACE, have not been thoroughly studied with model simulations. Such model simulations are important to answer the questions and allay the concerns that have been expressed in the atmospheric sciences community about the feasibility of such measurements. We proposed a suite of chemical transport model simulations using the EPA Models 3 chemical transport model, which obtains its meteorology from the MM-5 mesoscale model. The model output consists of gridded abundances of chemical pollutants and meteorological parameters every 30-60 minutes for cases that have occurred in the Eastern United States. This output was intended to be used to test the GeoTRACE capability to retrieve the tropospheric columns of these pollutants.

Source record↗

NASA NTRS1986

Progress towards a model to describe jet/aerodynamic-surface interference effects

A first generation model is presented which relates the pressure distribution on an aerodynamic surface to properties of the jet plume. The characteristics of a jet in a cross flow are of primary importance in determining the pressure distribution on the aerodynamic surface and are assumed to be (1) a pair of contrasting vortices associated with a jet in a crossflow, (2) entrainment of crossflow fluid into the jet plume, and (3) a wake region near the aerodynamic surface and extending downstream from the jet orifice. The model is applied to the configuration of a round jet exhausting perpendicularly through a flat plate into a uniform crossflow for a range of jet-to-crossflow velocity ratios from three to ten. It is demonstrated that the model is capable of describing the measured pressure distribution on the flat plate with model parameters that are compatable with the incomplete description of the vortex pair that is available. The fore and moments on one plate are presented as functions of jet-to-crossflow velocity ratios.

Fearn, R. L.↗

NASA NTRS2002

Estimating Single-Trial Responses in EEG

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Shah, A. S.↗

NASA NTRS2004

Modeling approach for the Terrestrial Planet Finder coronagraph mission

State of the art modeling for the Terrestrial Planet Finder Coronagraph mission are being developed that will combine thermal, structural, and optical modeling in one package. This tool is discussed as well as specific modeling results highlighting the capabilities of integrated modeling for TPF.

TPF Terrestrial Planet Finder coronagraph↗

NASA NTRS2011

Experimental and Numerical Investigation of Reduced Gravity Fluid Slosh Dynamics for the Characterization of Cryogenic Launch and Space Vehicle Propellants

As space programs increasingly investigate various options for long duration space missions the accurate prediction of propellant behavior over long periods of time in microgravity environment has become increasingly imperative. This has driven the development of a detailed, physics-based understanding of slosh behavior of cryogenic propellants over a range of conditions and environments that are relevant for rocket and space storage applications. Recent advancements in computational fluid dynamics (CFD) models and hardware capabilities have enabled the modeling of complex fluid behavior in microgravity environment. Historically, launch vehicles with moderate duration upper stage coast periods have contained very limited instrumentation to quantify propellant stratification and boil-off in these environments, thus the ability to benchmark these complex computational models is of great consequence. To benchmark enhanced CFD models, recent work focuses on establishing an extensive experimental database of liquid slosh under a wide range of relevant conditions. In addition, a mass gauging system specifically designed to provide high fidelity measurements for both liquid stratification and liquid/ullage position in a micro-gravity environment has been developed. This pUblication will summarize the various experimental programs established to produce this comprehensive database and unique flight measurement techniques.

Walls, Laurie K.↗

NASA NTRSDate not supplied

Considerations for Health and Performance During Surface Extravehicular Activities

BACKGROUND: NASA’s objectives for expanding human presence beyond low Earth orbit will require Extravehicular Activities (EVAs) on lunar and planetary surfaces. Given the physiological and functional demands of conducting surface EVAs in a pressurized spacesuit in reduced gravity environments, there is a possibility that crew injury and compromised physiological and/or functional performance may present. OVERVIEW: Many human health and performance knowledge gaps exist in regards to exploration EVA that require characterization to ensure safety, reliability, and mission success. To address knowledge gaps, EVA simulations in Earth-based analog environments and/or spacesuit simulators can be utilized to provide valuable insights into task-based physiologic and metabolic costs, cognitive loads, and associated operational limitations to inform future mission concepts. Physical workloads approaching 60% of maximum metabolic rates and 85% age-predicted heart rate maxima; core body temperatures approaching 100o F; and subjective responses indicating limited spare cognitive capacity via Bedford scale have been observed during ground-based exploration EVA simulations in the NASA Active Response Gravity Offload Simulator (ARGOS) and Neutral Buoyancy Lab (NBL) during simulated planetary EVAs in pressurized suits. Further, ground-based EVA analogs vary in their ability to simulate planetary EVA and resulting physical workloads. DISCUSSION: Metabolic costs, thermal burdens, functional strength, and cognitive impacts have been and must continue to be assessed in ground-based analogs to fully characterize operational demands and crew readiness levels for exploration EVA. Considerations should be given to enabling a new concept of high-tempo surface EVA operations and associated work-rest intervals, understanding human health and performance impacts of evolving commercial suit designs and capabilities, and predictive modeling and decision support capabilities to enable safe and successful EVA operations.

EVA↗

NASA NTRS2024

Considerations for Health and Performance during Surface Extravehicular Activities

BACKGROUND: NASA’s objectives for expanding human presence beyond low Earth orbit will require Extravehicular Activities (EVAs) on lunar and planetary surfaces. Given the physiological and functional demands of conducting surface EVAs in a pressurized spacesuit in reduced gravity environments, there is a possibility that crew injury and compromised physiological and/or functional performance may present. OVERVIEW: Many human health and performance knowledge gaps exist in regards to exploration EVA that require characterization to ensure safety, reliability, and mission success. To address knowledge gaps, EVA simulations in Earth-based analog environments and/or spacesuit simulators can be utilized to provide valuable insights into task-based physiologic and metabolic costs, cognitive loads, and associated operational limitations to inform future mission concepts. Physical workloads approaching 60% of maximum metabolic rates and 85% age-predicted heart rate maxima; core body temperatures approaching 100° F; and subjective responses indicating limited spare cognitive capacity via Bedford scale have been observed during ground-based exploration EVA simulations in the NASA Active Response Gravity Offload Simulator (ARGOS) and Neutral Buoyancy Lab (NBL) during simulated planetary EVAs in pressurized suits. Further, ground-based EVA analogs vary in their ability to simulate planetary EVA and resulting physical workloads. DISCUSSION: Metabolic costs, thermal burdens, functional strength, and cognitive impacts have been and must continue to be assessed in ground-based analogs to fully characterize operational demands and crew readiness levels for exploration EVA. Considerations should be given to enabling a new concept of high-tempo surface EVA operations and associated work-rest intervals, understanding human health and performance impacts of evolving commercial suit designs and capabilities, and predictive modeling and decision support capabilities to enable safe and successful EVA operations.

P Estep↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System

NASA↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model Based Engineering

Model Based Engineering↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model-Based Engineering (REV B)

The emergence of model-based engineering is transforming design and analysis methodologies. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses, GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System Safety Engineering for NASA if adequate modeling processes and environment are established.

NASA↗

NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗

NASA NTRS2022

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Timothy M. Lahmers↗

NASA NTRS1988

Cumulative fatigue damage models

The problem of calculating expected component life under fatigue loading conditions is complicated by the fact that component loading histories contain, in many cases, cyclic loads of widely varying amplitudes. In such a case a cumulative damage model is required, in addition to a fatigue damage criterion, or life relationship, in order to compute the expected fatigue life. The traditional cumulative damage model used in design is the linear damage rule. This model, while being simple to use, can yield grossly unconservative results under certain loading conditions. Research at the NASA Lewis Research Center has led to the development of a nonlinear cumulative damage model, named the double damage curve approach (DDCA), that has greatly improved predictive capability. This model, which considers the life (or loading) level dependence of damage evolution, was applied successfully to two polycrystalline materials, 316 stainless steel and Haynes 188. The cumulative fatigue behavior of the PWA 1480 single-crystal material is currently being measured to determine the applicability of the DDCA for this material.

Mcgaw, Michael A.↗

NASA NTRS2001

Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

Turner, Travis L.↗

NASA NTRS2016

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Gastellu-Etchegorry, Jean-Philippe↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33873-DND

NOAA's National Air Quality Forecasting Capability (NAQFC) model provides 48-hour forecast of surface ozone and other atmospheric constituents serving as the nation's key tool actively used by regulatory professionals in assessing air quality events and the issuance of public air quality alerts. NAQFC incorporates input meteorology from North American Mesoscale Model (NAM) at 12 km horizontal resolution that is coupled to the Community Multi-scale Air Quality Model (CMAQ) to predict emissions, tropospheric gas and aerosol chemistry, and related deposition and removal processes. The NAQFC forecast simulations contain 35 steps in altitude, with about one third of these in a typical afternoon daytime boundary layer (0-1.5 km). While several studies have been conducted comparing NAQFC predictions to surface observations, investigations comparing the vertical distribution to observations remain limited. Vertical comparisons are needed in order to fully assess forecast model behavior and atmospheric mixing conditions leading to the formation of ozone at the surface. The Tropospheric Ozone Lidar Network (TOLNet) instruments provide a unique observational capability in this regard, as ozone vertical measurements can be directly compared to models, such as NAQFC, and provide additional insight into atmospheric processes and enhance forecast capabilities. In this study, we utilize multiple TOLNet lidar observations obtained during the Ozone Water Land Environmental Transition Studies (OWLETS-2017 & OWLETS-2018) and the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) to compare with NAQFC vertical predictions of ozone. These campaigns took place at different coastal locations along the US East coast with each campaign having multiple TOLNet lidars present, providing a unique opportunity to examine vertical structure of ozone in regions with complex water-land boundaries. Preliminary comparison results will be presented on ozone temporal and vertical differences between NAQFC and the TOLNet lidars along with example case studies to illustrate insights into boundary layer and surface processes of trace gases.

Timothy Berkoff↗

NASA NTRS1988

Application of a Comprehensive Analytical Model of Rotor Aerodynamics and Dynamics (CAMRAD) to the McDonnell Douglas AH-64A helicopter

A model of the AH-64A helicopter was generated in a Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD) in an effort to validate its analytical capabilities for modeling a current advanced Army helicopter. The initial phase of the effort involved the generation of CAMRAD input files necessary for the complete aerodynamic, structural, and dynamic definition of the production AH-64A helicopter. The input files were checked by making comparisons of CAMRAD full helicopter trim and main rotor blade natural frequency predictions with those of full helicopter trim program, Blade Element Trim (BETRIM), and dynamic analysis code, Dynamic Analysis Research Tool (DART), respectively. The main thrust concerned the application of the AH-64A CAMRAD model thus developed and verified for main rotor blade structural loads predictions and comparison with DART analytical results. The investigation provided insight not only into the usefulness of CAMRAD for the AH-64A performance and dynamics prediction, but also into the limitations of the program for modeling advanced rotor and fuselage systems. The model development effort is discussed, the results of the CAMRAD correlation studies presented, and some general conclusions are offered on the applicability of CAMRAD for rotor aeroelastic loads prediction for current and future rotorcraft configurations.

Callahan, Cynthia B.↗

NASA NTRS1991

Recent improvements in atmospheric environment models for Space Station applications

The capability of empirical models of the earth's thermosphere must continually be updated if they are to keep pace with their many applications in the aerospace industry. This paper briefly summarizes the progress of several such efforts in support of the Space Station Program. The efforts consists of the development of data bases, analytical studies of the data, and evaluation and intercomparison of thermosphere models. A geomagnetic storm model of Slowey does not compare as well to the MSIS-86 model as does the Marshall Engineering Thermosphere (MET). LDEF orbit decay data is used to evaluate the performance of the MET and MSIS-86 during a period of high solar activity; equal to or exceeding the highest levels that existed during the time of the original data sets upon which these models are based.

Anderson, B. Jeffrey↗