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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Verification of a SEU model for advanced 1-micron CMOS structures using heavy ions

Modeling and test results are reported for 1 micron CMOS circuits. Analytical predictions are correlated with experimental data, and sensitivities to process and design variations are discussed. Unique features involved in predicting the SEU performance of these devices are described. The results show that the critical charge for upset exhibits a strong dependence on pulse width for very fast devices, and upset predictions must factor in the pulse shape. Acceptable SEU error rates can be achieved for a 1 micron bulk CMOS process. A thin retrograde well provides complete SEU immunity for N channel hits at normal incidence angle. Source interconnect resistance can be important parameter in determining upset rates, and Cf-252 testing can be a valuable tool for cost-effective SEU testing.

Cable, J. S.↗
NASA NTRS2013

Representation of Nucleation Mode Microphysics in a Global Aerosol Model with Sectional Microphysics

In models, nucleation mode (1 nm<Dp <10 nm) particle microphysics can be represented explicitly with aerosol microphysical processes or can be parameterized to obtain the growth and survival of nuclei to the model's lower size boundary. This study investigates how the representation of nucleation mode microphysics impacts aerosol number predictions in the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics model running with the GISS GCM II-prime by varying its lowest diameter boundary: 1 nm, 3 nm, and 10 nm. The model with the 1 nm boundary simulates the nucleation mode particles with fully resolved microphysical processes, while the model with the 10 nm and 3 nm boundaries uses a nucleation mode dynamics parameterization to account for the growth of nucleated particles to 10 nm and 3 nm, respectively.We also investigate the impact of the time step for aerosol microphysical processes (a 10 min versus a 1 h time step) to aerosol number predictions in the TOMAS models with explicit dynamics for the nucleation mode particles (i.e., 3 nm and 1 nm boundary). The model with the explicit microphysics (i.e., 1 nm boundary) with the 10 min time step is used as a numerical benchmark simulation to estimate biases caused by varying the lower size cutoff and the time step. Different representations of the nucleation mode have a significant effect on the formation rate of particles larger than 10 nm from nucleated particles (J10) and the burdens and lifetimes of ultrafinemode (10 nm≤Dp ≤70 nm) particles but have less impact on the burdens and lifetimes of CCN-sized particles. The models using parameterized microphysics (i.e., 10 nm and 3 nm boundaries) result in higher J10 and shorter coagulation lifetimes of ultrafine-mode particles than the model with explicit dynamics (i.e., 1 nm boundary). The spatial distributions of CN10 (Dp ≥10 nm) and CCN(0.2 %) (i.e., CCN concentrations at 0.2%supersaturation) are moderately affected, especially CN10 predictions above ∼700 hPa where nucleation contributes most strongly to CN10 concentrations. The lowermost-layer CN10 is substantially improved with the 3 nm boundary (compared to 10 nm) in most areas. The overprediction in CN10 with the 3 nm and 10 nm boundaries can be explained by the overprediction of J10 or J3 with the parameterized microphysics, possibly due to the instantaneous growth rate assumption in the survival and growth parameterization. The errors in CN10 predictions are sensitive to the choice of the lower size boundary but not to the choice of the time step applied to the microphysical processes. The spatial distribution of CCN(0.2 %) with the 3 nm boundary is almost identical to that with the 1 nm boundary, but that with the 10 nm boundary can differ more than 10-40% in some areas. We found that the deviation in the 10 nm simulations is partly due to the longer time step (i.e., 1 h time step used in the 10 nm simulations compared to 10 min time step used in the benchmark simulations), but, even with the same time step, the 10 nm cutoff showed noticeably higher errors than the 3 nm cutoff. In conclusion, we generally recommend using a lower diameter boundary of 3 nm for studies focused on aerosol indirect effects but down to 1 nm boundary for studies focused on CN10 predictions or nucleation.

microphysics↗
NASA NTRS2014

Influence of Triply-Charged Ions and Ionization Cross-Sections in a Hybrid-PIC Model of a Hall Thruster Discharge

The sensitivity of xenon ionization rates to collision cross-sections is studied within the framework of a hybrid-PIC model of a Hall thruster discharge. A revised curve fit based on the Drawin form is proposed and is shown to better reproduce the measured crosssections at high electron energies, with differences in the integrated rate coefficients being on the order of 10% for electron temperatures between 20 eV and 30 eV. The revised fit is implemented into HPHall and the updated model is used to simulate NASA's HiVHAc EDU2 Hall thruster at discharge voltages of 300, 400, and 500 V. For all three operating points, the revised cross-sections result in an increase in the predicted thrust and anode efficiency, reducing the error relative to experimental performance measurements. Electron temperature and ionization reaction rates are shown to follow the trends expected based on the integrated rate coefficients. The effects of triply-charged xenon are also assessed. The predicted thruster performance is found to have little or no dependence on the presence of triply-charged ions. The fraction of ion current carried by triply-charged ions is found to be on the order of 1% and increases slightly with increasing discharge voltage. The reaction rates for the 0→III, I→III, and II→III ionization reactions are found to be of similar order of magnitude and are about one order of magnitude smaller than the rate of 0→II ionization in the discharge channel.

Hall Thrusters↗
NASA NTRS1979

A maximum likelihood convolutional decoder model vs experimental data comparison

This article describes the comparison of a maximum likelihood convolutional decoder (MCD) prediction model and the actual performance of the MCD at the Madrid Deep Space Station. The MCD prediction model is used to develop a subroutine that has been utilized by the Telemetry Analysis Program (TAP) to compute the MCD bit error rate for a given signal-to-noise ratio. The results indicate that that the TAP can predict quite well compared to the experimental measurements. An optimal modulation index also can be found through TAP.

Chen, R. Y.↗
NASA NTRS1995

Impact of CMOS Scaling on Single-Event Hard Errors in Space Systems

Applications of highly scaled devices in space applications are shown to be limited by hard errors from cosmic rays. Hard errors were first observed in 0.8 (micro)m DRAMs. For feature sizes below 0.5 (micro)m, scaling theory predicts that low power devices will have much lower hard error rates than devices optimized for high speed.

CMOS Scaling↗
NASA NTRS2001

Laboratory characterization of silicon avalanche photodiodes (APD) for pulse position modulation (PPM) detection

Two commercially available large area silicon avalanche photodiodes (APD) were characterized in the laboratory. Specifically, the response of the APD’s to a sequence of 8-bit pulse position modulated (256-PPM) laser pulses, with and without background noise, was recorded and stored for post analysis. Empirical probability distribution functions (pdf) were constructed from the signal and noise slot data and compared to pdf’s predicted by an analytical model based on Webb/Gaussian statistics. The limited pulse sequence was also used to generate bit-error rate (BER) versus signal photons per pulse values, albeit with large error bars. These BER measurements were also compared to results predicted using the Gaussian and Webb/Gaussian models for APD channel statistics. While the measurements qualitatively reflect features predicted by theory, significant quantitative deviations are displayed between the measurements and theory. The source of these discrepancies is not currently well understood, but it is surmised that inaccurate knowledge of detector parameters such as gain and noise equivalent temperature models may explain the discrepancies.

Biswas, A.↗
NASA NTRS2001

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one-dimensional convection-diffusion-reaction (CDR) equations. First, accuracy, stability, conservation, and dense output are considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, N = 2, additive Runge-Kutta ARK2 methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms are of equal order to those of the elemental methods. Derived ARK2 methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z(exp [I]) goes to infinity, and retain high stability efficiency in the absence of stiffness, z(exp [I]) goes to zero. Extrapolation-type stage-value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK2 error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK2 methods while offering error control and stage-value predictors.

Kennedy, Christopher A.↗
NASA NTRS2002

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one- dimensional convection-diffusion-reaction (CDR) equations. Accuracy, stability, conservation, and dense-output are first considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, (N = 2), additive Runge-Kutta (ARK(sub 2)) methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms of the partitioned method are of equal order to those of the elemental methods. Derived ARK(sub 2) methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z['] yields -infinity, and retain high stability efficiency in the absence of stiffness, z['] yield 0. Extrapolation-type stage- value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK(sub 2) error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK(sub 2) methods.

Kennedy, Christopher A.↗
NASA NTRS1988

Measurement of the de Sitter precession of the moon - A relativistic three-body effect

Lunar laser-ranging data, accumulated between 1970 and 1986, are analyzed to estimate the deviation of the precession of the moon's orbit from the predictions of general relativity. No deviation from this predicted de Sitter precession rate of nearly 2 angular sec per century (sec/cy) is found, to within an estimated standard error of 0.04 sec/cy. This standard error, 2 percent of the predicted effect, incorporates an assessment of the likely contributions of systematic errors, and is about threefold larger than the statistical standard error.

Shapiro, I. I.↗
NASA NTRS1988

Characterization of Mode 1 and Mode 2 delamination growth and thresholds in graphite/peek composites

Composite materials often fail by delamination. The onset and growth of delamination in AS4/PEEK, a tough thermoplastic matrix composite, was characterized for mode 1 and mode 2 loadings, using the Double Cantilever Beam (DCB) and the End Notched Flexure (ENF) test specimens. Delamination growth per fatigue cycle, da/dN, was related to strain energy release rate, G, by means of a power law. However, the exponents of these power laws were too large for them to be adequately used as a life prediction tool. A small error in the estimated applied loads could lead to large errors in the delamination growth rates. Hence strain energy release rate thresholds, G sub th, below which no delamination would occur were also measured. Mode 1 and 2 threshold G values for no delamination growth were found by monitoring the number of cycles to delamination onset in the DCB and ENF specimens. The maximum applied G for which no delamination growth had occurred until at least 1,000,000 cycles was considered the threshold strain energy release rate. Comments are given on how testing effects, facial interference or delamination front damage, may invalidate the experimental determination of the constants in the expression.

Martin, Roderick H.↗
NASA NTRS1990

Characterization of Mode I and Mode II delamination growth and thresholds in AS4/PEEK composites

Composite materials often fail by delamination. The onset and growth of delamination in AS4/PEEK, a tough thermoplastic matrix composite, was characterized for mode 1 and mode 2 loadings, using the Double Cantilever Beam (DCB) and the End Notched Flexure (ENF) test specimens. Delamination growth per fatigue cycle, da/dN, was related to strain energy release rate, G, by means of a power law. However, the exponents of these power laws were too large for them to be adequately used as a life prediction tool. A small error in the estimated applied loads could lead to large errors in the delamination growth rates. Hence strain energy release rate thresholds, G sub th, below which no delamination would occur were also measured. Mode 1 and 2 threshold G values for no delamination growth were found by monitoring the number of cycles to delamination onset in the DCB and ENF specimens. The maximum applied G for which no delamination growth had occurred until at least 1,000,000 cycles was considered the threshold strain energy release rate. Comments are given on how testing effects, facial interference or delamination front damage, may invalidate the experimental determination of the constants in the expression.

Martin, Roderick H.↗
NASA NTRS2011

Delay and Disruption Tolerant Networking MACHETE Model

To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity, the ability to take advantage of scheduled and opportunistic connectivity, and late binding of names to addresses.

Segui, John S.↗
DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗
NASA NTRS2015

Optical PAyload for Lasercomm Science (OPALS) link validation

Recently several day and nighttime links under diverse atmospheric conditions were completed using the Optical Payload for Lasercomm Science (OPALS) flight system on-board the International Space Station (ISS). In this paper we compare measured optical power and its variance at either end of the link with predictions that include atmospheric propagation models. For the 976 nm laser beacon mean power transmitted from the ground to the ISS the predicted mean irradiance of 10's of microwatts per square meter close to zenith and its decrease with range and increased air mass shows good agreement with predictions. The irradiance fluctuations sampled at 100 Hz also follow the expected increase in scintillation with air mass representative of atmospheric coherence lengths at zenith at 500 nm in the 3-8 cm range. The downlink predicted power of 100's of nanowatts was also reconciled within the uncertainty of the atmospheric losses. Expected link performance with uncoded bit-error rates less than 1E-4 required for the Reed-Solomon code to correct errors for video, text and file transmission was verified. The results of predicted and measured powers and fluctuations suggest the need for further study and refinement.

ISS↗
DOE OSTI2024

On the Representativity of Electrode Microstructure Parameters and Their Electrochemical Response for Lithium Ion Batteries

Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the microstructure analysis. A microstructure scale electrochemical model was used to investigate lithium plating onset, material non-uniform utilization, and in-plane heterogeneities for an NMC-graphite full cell. To evaluate the representativeness, and thus relevance, of these model predictions, a coupled representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response. Electrode microstructure parameters representativeness has been first quantified using the representative volume element (RVE) methodology. The RVE major flaw is that ultimately it can only conclude if a FOV contains representative subvolumes of the FOV, but not if the FOV itself is representative of the electrode volume. Analysis can conclude negatively ('FOV is not representative'), but not positively ('FOV is representative'). One major contribution of this work was to quantify the convergence of the RVE size with the FOV, to actually investigate the FOV representativeness and thus partly remedy this intrinsic limitation. The analysis determined that performing a standard RVE calculation, without exploring its FOV convergence, is likely to strongly underestimate the actual RVE size. The new RVE methodology has been automated in the NREL open-source Microstructure Analysis Toolbox (MATBOX) and is available to the battery community. Representativeness of microstructure parameters is however only an intermediate step, as the end-results of an electrochemical model are performances predictions. Indeed, what is the practical consequence of a given deviation for a microstructure parameter? The microstructure parameter deviation propagations to the 3D microstructure scale electrochemical response have been then quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Such deviation propagation analysis is analogous to error propagation analysis and is necessary to determine the relevance of microstructure scale model predictions for macroscale predictions. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Therefore, we introduced the novel concept of electrochemical RVE (eRVE) that is a function of the operating conditions (thus defined as a dynamic RVE), with an increasing dependence with the C-rate. Representativity analysis of the investigated cell determined a FOV of 144.4 x 54.4 m2 is large enough to establish a convergence on the representative section areas for low to intermediate C-rate (=2.5C), but not large enough to conclude for higher rates. This work aims to emphasize the importance of representativity analysis for LIB electrode microstructures, as it is required to estimate the error, and thus the relevance, of microstructure parameters intended to be used in macroscale models. The methodology and results can help researchers to select the relevant imaging and associated FOV required to provide accurate enough microstructure parameters.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Human operator response to error-likely situations in complex engineering systems

The causes of human error in complex systems are examined. First, a conceptual framework is provided in which two broad categories of error are discussed: errors of action, or slips, and errors of intention, or mistakes. Conditions in which slips and mistakes might be expected to occur are identified, based on existing theories of human error. Regarding the role of workload, it is hypothesized that workload may act as a catalyst for error. Two experiments are presented in which humans' response to error-likely situations were examined. Subjects controlled PLANT under a variety of conditions and periodically provided subjective ratings of mental effort. A complex pattern of results was obtained, which was not consistent with predictions. Generally, the results of this research indicate that: (1) humans respond to conditions in which errors might be expected by attempting to reduce the possibility of error, and (2) adaptation to conditions is a potent influence on human behavior in discretionary situations. Subjects' explanations for changes in effort ratings are also explored.

Morris, Nancy M.↗
NASA NTRS1974

Progress and problems in erosion prediction

Methods for predicting erosion resulting from repeated localized impulsive loadings, such a impacts from droplets or in cavitation flow from microjets and bubbles, are examined. The parameters which determine the adequacy of a component to resist the loads put upon it are identified. The development of erosion rate models is discussed. The expected accuracy of the prediction and the sources of error are analyzed.

Heymann, F. J.↗