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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Process and quality verification controls for solid propellant manufacturing

It is pointed out that in-process tests to verify quality and detect discrepant propellant which could compromise motor performance are essential elements of the solid composite propellant manufacturing process. The successful performance of the 260SL-1 and 260SL-2 motors aptly verified the controls used for manufacturing the propellant. The present investigation is concerned with the selected control parameters, and their relationships to composition and final propellant properties. Control performance is evaluated by comparison with processing data experienced in the manufacture of the propellant for the 260SL-1 motor. It is found that the in-process quality verification controls utilized in the propellant manufacturing process for the 260-in. diameter motor contributed significantly to the confidence of successful and predictable motor performance.

Rogers, C. J.↗
NASA NTRS1984

Analysis of a transport fuselage section drop test

Transport fuselage section drop tests provided useful information about the crash behavior of metal aircraft in preparation for a full-scale Boeing 720 controlled impact demonstration (CID). The fuselage sections have also provided an operational test environment for the data acquisition system designed for the CID test, and data for analysis and correlation with the DYCAST nonlinear finite-element program. The correlation of the DYCAST section model predictions was quite good for the total fuselage crushing deflection (22 to 24 inches predicted versus 24 to 26 inches measured), floor deformation, and accelerations for the floor and fuselage. The DYCAST seat and occupant model was adequate to approximate dynamic loading to the floor, but a more sophisticated model would be required for good correlation with dummy accelerations. Although a full-section model using only finite elements for the subfloor was desirable, constraints of time and computer resources limited the finite-element subfloor model to a two-frame model. Results from the two-frame model indicate that DYCAST can provide excellent correlation with experimental crash behavior of fuselage structure with a minimum of empirical force-deflection data representing structure in the analytical model.

E. L. Fasanella↗
NASA NTRS1985

Flat-plate transition

A new research effort was undertaken to build a boundary-layer transition tunnel. This facility only recently became operational. The data obtained so far are merely qualitative. The main goal is to predict heat transfer given any combination of factors such as pressure gradient, turbulence level, Reynolds number, or intermittency factor. The boundary-layer transition tunnel is a closed-loop tunnel that controls the turbulence level, velocity and temperature of the air within it. Problems associated with the operation of this tunnel are examined.

Ercegovic, B. A.↗
NASA NTRS1989

A cell-vertex multigrid method for the Navier-Stokes equations

A cell-vertex scheme for the Navier-Stokes equations, which is based on central difference approximations and Runge-Kutta time stepping, is described. Using local time stepping, implicit residual smoothing, a multigrid method, and carefully controlled artificial dissipative terms, very good convergence rates are obtained for a wide range of two- and three-dimensional flows over airfoils and wings. The accuracy of the code is examined by grid refinement studies and comparison with experimental data. For an accurate prediction of turbulent flows with strong separations, a modified version of the nonequilibrium turbulence model of Johnson and King is introduced, which is well suited for an implementation into three-dimensional Navier-Stokes codes. It is shown that the solutions for three-dimensional flows with strong separations can be dramatically improved, when a nonequilibrium model of turbulence is used.

Radespiel, R.↗
NASA NTRS1990

An overview of selected NASP aeroelastic studies at the NASA Langley Research Center

Following an initial discussion of the NASP flight environment, the results of recent aeroelastic testing of NASP-type highly swept delta-wing models in Langley's Transonic Dynamics Tunnel (TDT) are summarized. Subsonic and transonic flutter characteristics of a variety of these models are described, and several analytical codes used to predict flutter of these models are evaluated. These codes generally provide good, but conservative predictions of subsonic and transonic flutter. Also, test results are presented on a nonlinear transonic phenomena known as aileron buzz which occurred in the wind tunnel on highly swept delta wings with full-span ailerons. An analytical procedure which assesses the effects of hypersonic heating on aeroelastic instabilities (aerothermoelasticity) is also described. This procedure accurately predicted flutter of a heated aluminum wing on which experimental data exists. Results are presented on the application of this method to calculate the flutter characteristics of a fine-element model of a generic NASP configuration. Finally, it is demonstrated analytically that active controls can be employed to improve the aeroelastic stability and ride quality of a generic NASP vehicle flying at hypersonic speeds.

Spain, Charles V.↗
NASA NTRS1992

System of Experts for Intelligent Data Management (SEIDAM)

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗
NASA NTRS1993

System of experts for intelligent data management (SEIDAM)

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗
NASA NTRS2000

An Overview of the NCC Spray/Monte-Carlo-PDF Computations

This paper advances the state-of-the-art in spray computations with some of our recent contributions involving scalar Monte Carlo PDF (Probability Density Function), unstructured grids and parallel computing. It provides a complete overview of the scalar Monte Carlo PDF and Lagrangian spray computer codes developed for application with unstructured grids and parallel computing. Detailed comparisons for the case of a reacting non-swirling spray clearly highlight the important role that chemistry/turbulence interactions play in the modeling of reacting sprays. The results from the PDF and non-PDF methods were found to be markedly different and the PDF solution is closer to the reported experimental data. The PDF computations predict that some of the combustion occurs in a predominantly premixed-flame environment and the rest in a predominantly diffusion-flame environment. However, the non-PDF solution predicts wrongly for the combustion to occur in a vaporization-controlled regime. Near the premixed flame, the Monte Carlo particle temperature distribution shows two distinct peaks: one centered around the flame temperature and the other around the surrounding-gas temperature. Near the diffusion flame, the Monte Carlo particle temperature distribution shows a single peak. In both cases, the computed PDF's shape and strength are found to vary substantially depending upon the proximity to the flame surface. The results bring to the fore some of the deficiencies associated with the use of assumed-shape PDF methods in spray computations. Finally, we end the paper by demonstrating the computational viability of the present solution procedure for its use in 3D combustor calculations by summarizing the results of a 3D test case with periodic boundary conditions. For the 3D case, the parallel performance of all the three solvers (CFD, PDF, and spray) has been found to be good when the computations were performed on a 24-processor SGI Origin work-station.

Raju, M. S.↗
NASA NTRS2002

Advanced Nacelle Acoustic Lining Concepts Development

The work reported in this document consisted of six distinct liner technology development subtasks: 1) Analysis of Model Scale ADP Fan Duct Lining Data (Boeing): An evaluation of an AST Milestone experiment to demonstrate 1995 liner technology superiority relative to that of 1992 was performed on 1:5.9 scale model fan rig (Advanced Ducted Propeller) test data acquired in the NASA Glenn 9 x 15 foot wind tunnel. The goal of 50% improvement was deemed satisfied. 2) Bias Flow Liner Investigation (Boeing, VCES): The ability to control liner impedance by low velocity bias flow through liner was demonstrated. An impedance prediction model to include bias flow was developed. 3) Grazing Flow Impedance Testing (Boeing): Grazing flow impedance tests were conducted for comparison with results achieved at four different laboratories. 4) Micro-Perforate Acoustic Liner Technology (BFG, HAE, NG): Proof of concept testing of a "linear liner." 5) Extended Reaction Liners (Boeing, NG): Bandwidth improvements for non-locally reacting liner were investigated with porous honeycomb core test liners. 6) Development of a Hybrid Active/Passive Lining Concept (HAE): Synergism between active and passive attenuation of noise radiated by a model inlet was demonstrated.

Bielak, G.↗
NASA NTRS2009

Assessment of Nutrient Stability in Space Foods

Maintaining an intact nutrient supply in the food system flown on spacecraft is a critical issue for mission success and crew health and safety. Early polar expeditions and exploration expeditions by sailing vessels have taught us that a deficiency, or excess, of even a single vitamin in the food supply can be catastrophic. Evidence from ground-based research indicates that some vitamins are destroyed and fatty acids are oxidized (and therefore rendered dangerous or useless) by different types of radiation and by conditions of long-term storage. We hypothesize that radiation and long-term storage in the space-flight environment will affect the stability of vitamins, amino acids, and fatty acids in the space food system. The research objectives of our ongoing stability studies are to determine the stability of water- and fat-soluble vitamins, fatty acids, and amino acids in the space food supply before and after space flight on the International Space Station (ISS). Foods were analyzed after 2 weeks (a flight control), 11, 19, and 28 months of flight. Along with the space-flown foods, ground-based controls matched for time, light, and temperature are analyzed. The flight studies complement planned ground-based studies of the effects of radiation on vitamins, amino acids, and fatty acids. Flight studies are needed because a model based on ground-based data cannot predict all of the effects of the space-flight environment. Flight studies provide a more accurate test system to determine the effects on these nutrients of the temperature, and radiation conditions in the space-flight environment. Ground studies are required to evaluate longer missions and higher radiation levels expected outside low-Earth orbit. In addition to providing information about nutrient stability in space, the results of these studies will help NASA determine if a need exists to develop special packaging that can ensure stability of foods and nutrients in space, or if further studies of nutrient metabolism or nutrient requirements are needed.

Zwart, S. R.↗
NASA NTRS2019

Physically Based and Stochastic Models for Greenland Moulin Formation, Longevity, and Spatial Distribution

Nearly all proglacial water discharge from the Greenland Ice Sheet is routed englacially, from the surface to the bed, via moulins. Identification of moulins in high-resolution imagery is a frequent topic of study, but the processes controlling how and where moulins form remain poorly understood. We seek to leverage information gained from the development of a physical model of moulin formation, remotely sensed ice-sheet data products, and an analytic model of ice-flow perturbations to develop a predictive stochastic model of moulin distribution across Greenland. Here we present initial results from the physical model of moulin formation and characterize the sensitivity of moulin geometry to a range of model parameters. This parameterization of moulin formation is the first step in developing a stochastic model that will be a predictive, computationally efficient representation of the englacial hydrologic system.

Andrews, Lauren C.↗
NASA NTRS2019

Spatiotemporal Monitoring of Hydrilla [Hydrilla verticillata (L. f.) Royle] to Aid Management Actions

Hydrilla is an invasive aquatic plant that has rapidly spread through many inland water bodies across the globe by outcompeting native aquatic plants. Drinking water supply, power generation, and recreational use of lakes are threatened by the spread of this invasive species. Moreover, hydrilla serves as a host for an epiphytic, toxic cyanobacteria known to be the causative agent of the neurodegenerative disease called avian vacuolar myelinopathy, which affects waterfowl, raptors, and amphibians. The early detection of hydrilla infestation is very important to reduce the costs associated with control and removal efforts of this invasive species. Therefore, this study was aimed at developing a rapid, frequent, and large-scale tool for monitoring and predicting spatial extent of hydrilla habitat. This was achieved by integrating in situ and Landsat 8 OLI satellite data for Lake J. Strom Thurmond, the largest US Army Corps of Engineers Lake east of the Mississippi River located on the Georgia/South Caroline border. The predictive model incorporated remote sensing reflectance, Secchi disk depth (SDD), light attenuation coefficient (Kd), maximum depth of colonization (Zc), and percentage of light available through water column (PLW). The model predicted ideal habitat for hydrilla featuring high SDD, low values of Kd, high Zc and PLW. Final analysis showed that hydrilla starts growing in April, reaches peak around October, begins retreating in the following months, and disappears in February. Additionally, physical meteorological factors were analyzed and were found to be closely associated with hydrilla extent. Management agencies can use these results to not only to plan future removal efforts, but also evaluate and adapt their current mitigation efforts.

Percentage of light available through the water co↗
DOE OSTI2021

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗
NASA NTRS2011

Urinary Acid Excretion Can Predict Changes in Bone Metabolism During Space Flight

Mitigating space flight-induced bone loss is critical for space exploration, and a dietary countermeasure would be ideal. We present here preliminary data from a study where we examined the role of dietary intake patterns as one factor that can influence bone mineral loss in astronauts during space flight. Crewmembers (n=5) were asked to consume a prescribed diet with either a low (0.3-0.6) or high (1.0-1.3) ratio of animal protein to potassium (APro:K) before and during space flight for 4-d periods. Diets were controlled for energy, total protein, calcium, and sodium. 24-h urine samples were collected on the last day of each of the 4-d controlled diet sessions. 24-h urinary acid excretion, which was predicted by dietary potential renal acid load, was correlated with urinary n-telopeptide (NTX, Pearson R = 0.99 and 0.80 for the high and low APro:K sessions, respectively, p<0.001). The amount of protein when expressed as the percentage of total energy (but not as total grams) was also correlated with urinary NTX (R = 0.66, p<0.01). These results, from healthy individuals in a unique environment, will be important to better understand diet and bone interrelationships during space flight as well as on Earth. The study was funded by the NASA Human Research Program.

Zwart, Sara R.↗
DOE OSTI2025

15-minute Parker River gap-filled tide height and salinity data, PIE LTER, Plum Island Sound, MA (2014–2023), for ELM PFLOTRAN modeling

This dataset contains 15-minute tide height and salinity data from the Typha site along the Parker River, part of the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site in Plum Island Sound, Massachusetts (MA) 2014-2023. Tide height (in NAVD88) was compiled from measurements conducted at the mouth of Plum Island Sound and corrected for time lags. Gap-filling of missing periods were done by fitting tidal constituents to the time series. Salinity was measured (and is stored on ESS DIVE ) in 2022 and 2023 using HOBO U24-002 conductivity loggers. River discharge is the most important control on tidal river water salinity at the location (Vallino & Hopkinson, 1998). An artificial neural network was trained to predict river water salinity at the location using Parker River discharge (USGS station 01101000, Parker River at Byfield, MA) and gap-filled salinity observations from a long-term monitoring station ca. 3km downstream from the Typha site (LTER station ‘Middle Road’) as input variables to create continuous time series information. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024). Metadata files ELMPFLOTRAN_tide_salinity_dd.csv and ELMPFLOTRAN_tide_salinity_flmd.csv provide details on site location, data variables, and QA/QC methods .

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

Presented here is a preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. The authors show that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Ashrafi, S.↗
NASA NTRS2014

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the re-adapation phase following a return to an earth-gravitational environment. These alterations may disrupt the ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from space flight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual space flight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures that include: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; 3) genotype markers for genetic polymorphisms in Catechol-O-Methyl Transferase, Dopamine Receptor D2, Brain-derived neurotrophic factor and genetic polymorphism of alpha2-adrenergic receptor that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration space flight and an analog bed rest environment. We will be conducting a retrospective study leveraging data already collected from relevant ongoing/completed bed rest and space flight studies. These data will be combined with predictor metrics that will be collected prospectively - behavioral, brain imaging and genomic measures; from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions against decrements in post-mission adaptive capability. This ability will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗
NASA NTRS1991

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

A preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity is presented. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. It is shown that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Ashrafi, S.↗