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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Optimization Routine for Generating Medical Kits for Spaceflight Using the Integrated Medical Model

The Integrated Medical Model (IMM) is a MATLAB model that provides probabilistic assessment of the medical risk associated with human spaceflight missions.Different simulations or profiles can be run in which input conditions regarding both mission characteristics and crew characteristics may vary. For each simulation, the IMM records the total medical events that occur and “treats” each event with resources drawn from import scripts. IMM outputs include Total Medical Events (TME), Crew Health Index (CHI), probability of Evacuation (pEVAC), and probability of Loss of Crew Life (pLOCL).The Crew Health Index is determined by the amount of quality time lost (QTL). Previously, an optimization code was implemented in order to efficiently generate medical kits. The kits were optimized to have the greatest benefit possible, given amass and/or volume constraint. A 6-crew, 14-day lunar mission was chosen for the simulation and run through the IMM for 100,000 trials. A built-in MATLAB solver, mixed-integer linear programming, was used for the optimization routine. Kits were generated in 10% increments ranging from 10%-100% of the benefit constraints. Conditions wheremass alone was minimized, volume alone was minimized, and where mass and volume were minimizedjointly were tested.

Medical Kit↗
NASA NTRS1988

Nonlinear 3-D evolution of bounded kinetic Alfven waves due to shear flow and collisionless tearing instability

The three-dimensional nonlinear simulation of the evolution of a kinetic Alfven wave is presented for simple boundary conditions that resemble those of a discrete auroral breakup arc. The model used is a variant of the reduced megnetohydrodynamic description that includes, in addition, the important dispersive effect of electron inertia. It is found that with a 'generator' boundary condition corresponding to a current generator and a fully conducting 'load' boundary, the wave evolves three-dimensionally through a combination of shear flow and collisionless tearing mode instability.

Seyler, Charles E., Jr.↗
NASA NTRS1996

A Computational Fluid Dynamic and Heat Transfer Model for Gaseous Core and Gas Cooled Space Power and Propulsion Reactors

A computational model based on the axisymmetric, thin-layer Navier-Stokes equations is developed to predict the convective, radiation and conductive heat transfer in high temperature space nuclear reactors. An implicit-explicit, finite volume, MacCormack method in conjunction with the Gauss-Seidel line iteration procedure is utilized to solve the thermal and fluid governing equations. Simulation of coolant and propellant flows in these reactors involves the subsonic and supersonic flows of hydrogen, helium and uranium tetrafluoride under variable boundary conditions. An enthalpy-rebalancing scheme is developed and implemented to enhance and accelerate the rate of convergence when a wall heat flux boundary condition is used. The model also incorporated the Baldwin and Lomax two-layer algebraic turbulence scheme for the calculation of the turbulent kinetic energy and eddy diffusivity of energy. The Rosseland diffusion approximation is used to simulate the radiative energy transfer in the optically thick environment of gas core reactors. The computational model is benchmarked with experimental data on flow separation angle and drag force acting on a suspended sphere in a cylindrical tube. The heat transfer is validated by comparing the computed results with the standard heat transfer correlations predictions. The model is used to simulate flow and heat transfer under a variety of design conditions. The effect of internal heat generation on the heat transfer in the gas core reactors is examined for a variety of power densities, 100 W/cc, 500 W/cc and 1000 W/cc. The maximum temperature, corresponding with the heat generation rates, are 2150 K, 2750 K and 3550 K, respectively. This analysis shows that the maximum temperature is strongly dependent on the value of heat generation rate. It also indicates that a heat generation rate higher than 1000 W/cc is necessary to maintain the gas temperature at about 3500 K, which is typical design temperature required to achieve high efficiency in the gas core reactors. The model is also used to predict the convective and radiation heat fluxes for the gas core reactors. The maximum value of heat flux occurs at the exit of the reactor core. Radiation heat flux increases with higher wall temperature. This behavior is due to the fact that the radiative heat flux is strongly dependent on wall temperature. This study also found that at temperature close to 3500 K the radiative heat flux is comparable with the convective heat flux in a uranium fluoride failed gas core reactor.

Anghaie, S.↗
NASA NTRS1992

Semi-coupled flow and thermal analysis of the field joint during rapid pressurization of the redesigned solid rocket motor

A transient, semi-coupled, multi-dimensional thermal and flow analysis methodology was developed to predict the thermal/gas dynamic conditions in the field joint region of the Redesigned Solid Rocket Motor (RSRM). Transient temperature response, pressure history, and combustion gas flow rate (within the field joint region), were of principle interest, in the course of this study. The thermal environment in the field joint was modeled using SINDA, a finite difference based thermal network analyzer. The combustion gas flow boundary condition was generated using the FLAP code; this code performs a transient, lumped-parameter, control volume analysis to solve the mass, momentum, and energy conservation equations. The FLAP computer code was modified to account for erosion of the NBR insulation material, following ignition. An independent grid sensitivity study was conducted to determine an appropriate grid distribution near the wall. The predicted results, obtained using an optimum grid distribution and computer generated flow boundary condition, were compared with subscale test data.

Ghaffarian, Benny↗
NASA NTRS1993

Controlled experiments in cosmological gravitational clustering

A systematic study is conducted of gravitational instability in 3D on the basis of power-law initial spectra with and without spectral cutoff, emphasizing nonlinear effects and measures of nonlinearity; effects due to short and long waves in the initial conditions are separated. The existence of second-general pancakes is confirmed, and it is noted that while these are inhomogeneous, they generate a visually strong signal of filamentarity. An explicit comparison of smoothed initial conditions with smoothed envelope models also reconfirms the need to smooth over a scale larger than any nonlinearity, in order to extrapolate directly by linear theory from Gaussian initial conditions.

Melott, Adrian L.↗
NASA NTRS2004

The use of NASA GEOS Global Analysis in MM5/WRF Initialization: Current Studies and Future Applications

An effort has been made at NASA/GSFC to use the Goddard Earth Observing system (GEOS) global analysis in generating the initial and boundary conditions for MM5/WRF simulation. This linkage between GEOS global analysis and MM5/WRF models has made possible for a few useful applications. As one of the sample studies, a series of MM5 simulations were conducted to test the sensitivity of initial and boundary conditions to MM5 simulated precipitation over the eastern; USA. Global analyses horn different operational centers (e.g., NCEP, ECMWF, I U ASA/GSFCj were used to provide first guess field and boundary conditions for MM5. Numerical simulations were performed for one- week period over the eastern coast areas of USA. the distribution and quantities of MM5 simulated precipitation were compared. Results will be presented in the workshop. In addition,other applications from recent and future studies will also be addressed.

Pu, Zhao-Xia↗
NASA NTRS1999

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

NASA Center ARC↗
NASA NTRS2010

LS-DYNA Analysis of a Full-Scale Helicopter Crash Test

A full-scale crash test of an MD-500 helicopter was conducted in December 2009 at NASA Langley's Landing and Impact Research facility (LandIR). The MD-500 helicopter was fitted with a composite honeycomb Deployable Energy Absorber (DEA) and tested under vertical and horizontal impact velocities of 26 ft/sec and 40 ft/sec, respectively. The objectives of the test were to evaluate the performance of the DEA concept under realistic crash conditions and to generate test data for validation of a system integrated LS-DYNA finite element model. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests was conducted to evaluate the impact performances of various components, including a new crush tube and the DEA blocks. Parameters defined within the system integrated finite element model were determined from these tests. The objective of this paper is to summarize the finite element models developed and analyses performed, beginning with pre-test and continuing through post test validation.

Annett, Martin S.↗
NASA NTRS2012

Physiological Based Simulator Fidelity Design Guidance

The evolution of the role of flight simulation has reinforced assumptions in aviation that the degree of realism in a simulation system directly correlates to the training benefit, i.e., more fidelity is always better. The construct of fidelity has several dimensions, including physical fidelity, functional fidelity, and cognitive fidelity. Interaction of different fidelity dimensions has an impact on trainee immersion, presence, and transfer of training. This paper discusses research results of a recent study that investigated if physiological-based methods could be used to determine the required level of simulator fidelity. Pilots performed a relatively complex flight task consisting of mission task elements of various levels of difficulty in a fixed base flight simulator and a real fighter jet trainer aircraft. Flight runs were performed using one forward visual channel of 40 deg. field of view for the lowest level of fidelity, 120 deg. field of view for the middle level of fidelity, and unrestricted field of view and full dynamic acceleration in the real airplane. Neuro-cognitive and physiological measures were collected under these conditions using the Cognitive Avionics Tool Set (CATS) and nonlinear closed form models for workload prediction were generated based on these data for the various mission task elements. One finding of the work described herein is that simple heart rate is a relatively good predictor of cognitive workload, even for short tasks with dynamic changes in cognitive loading. Additionally, we found that models that used a wide range of physiological and neuro-cognitive measures can further boost the accuracy of the workload prediction.

Schnell, Thomas↗
NASA NTRS2017

Comparisons of Mixed-Phase Icing Cloud Simulations with Experiments Conducted at the NASA Propulsion Systems Laboratory

This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines. Experimentally measured air temperature, humidity, total water content, liquid and ice water content, as well as cloud particle size, are compared with model predictions. The model showed good trend agreement with experimentally measured values, but often over-predicted aero-thermodynamic changes. This discrepancy is likely attributed to radial variations that this one-dimensional model does not address. One of the key findings of this work is that greater aero-thermodynamic changes occur when humidity conditions are low. In addition a range of mixed-phase clouds can be achieved by varying only the tunnel humidity conditions, but the range of humidities to generate a mixed-phase cloud becomes smaller when clouds are composed of smaller particles. In general, the model predicted melt fraction well, in particular with clouds composed of larger particle sizes.

Thermal model↗
NASA NTRS2017

The Impact of Anthropogenic Land Use and Land Cover Change on Regional Climate Extremes

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land useland cover change (LULCC) on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics.

Near-surface↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results and Analysis: Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally-cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results & Analysis - Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
DOE OSTI2026

Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗
NASA NTRS1989

Predeployment validation of fault-tolerant systems through software-implemented fault insertion

Fault injection-based automated testing (FIAT) environment, which can be used to experimentally characterize and evaluate distributed realtime systems under fault-free and faulted conditions is described. A survey is presented of validation methodologies. The need for fault insertion based on validation methodologies is demonstrated. The origins and models of faults, and motivation for the FIAT concept are reviewed. FIAT employs a validation methodology which builds confidence in the system through first providing a baseline of fault-free performance data and then characterizing the behavior of the system with faults present. Fault insertion is accomplished through software and allows faults or the manifestation of faults to be inserted by either seeding faults into memory or triggering error detection mechanisms. FIAT is capable of emulating a variety of fault-tolerant strategies and architectures, can monitor system activity, and can automatically orchestrate experiments involving insertion of faults. There is a common system interface which allows ease of use to decrease experiment development and run time. Fault models chosen for experiments on FIAT have generated system responses which parallel those observed in real systems under faulty conditions. These capabilities are shown by two example experiments each using a different fault-tolerance strategy.

Czeck, Edward W.↗
NASA NTRS2006

An Energy Balance Model to Predict Chemical Partitioning in a Photosynthetic Microbial Mat

Studies of biosignature formation in photosynthetic microbial mat communities offer potentially useful insights with regards to both solar and extrasolar astrobiology. Biosignature formation in such systems results from the chemical transformation of photosynthetically fixed carbon by accessory microorganisms. This fixed carbon represents a source not only of reducing power, but also energy, to these organisms, so that chemical and energy budgets should be coupled. We tested this hypothesis by applying an energy balance model to predict the fate of photosynthetic productivity under dark, anoxic conditions. Fermentation of photosynthetically fixed carbon is taken to be the only source of energy available to cyanobacteria in the absence of light and oxygen, and nitrogen fixation is the principal energy demand. The alternate fate for fixed carbon is to build cyanobacterial biomass with Redfield C:N ratio. The model predicts that, under completely nitrogen-limited conditions, growth is optimized when 78% of fixed carbon stores are directed into fermentative energy generation, with the remainder allocated to growth. These predictions were compared to measurements made on microbial mats that are known to be both nitrogen-limited and populated by actively nitrogen-fixing cyanobacteria. In these mats, under dark, anoxic conditions, 82% of fixed carbon stores were diverted into fermentation. The close agreement between these independent approaches suggests that energy balance models may provide a quantitative means of predicting chemical partitioning within such systems - an important step towards understanding how biological productivity is ultimately partitioned into biosignature compounds.

Hoehler, Tori M.↗
NASA NTRS1989

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗