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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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Robot constructs map from experience. Topological model consists of nodes and arcs corresponding to distinctive places and local travel edges linking nearby distinctive places. Model created by linking places and edges. Enables accumulation of metrical information with reduced vulnerability to metrical errors. Applications include robotic sentires, robotic delivery trucks, robotic floor cleaners, and robotic lawnmowers.
A pair of electronic models has been developed of a Ferroelectric Field Effect transistor. These models can be used in standard electrical circuit simulation programs to simulate the main characteristics of the FFET. The models use the Schmitt trigger circuit as a basis for their design. One model uses bipolar junction transistors and one uses MOSFET's. Each model has the main characteristics of the FFET, which are the current hysterisis with different gate voltages and decay of the drain current when the gate voltage is off. The drain current from each model has similar values to an actual FFET that was measured experimentally. T'he input and o Output resistance in the models are also similar to that of the FFET. The models are valid for all frequencies below RF levels. No attempt was made to model the high frequency characteristics of the FFET. Each model can be used to design circuits using FFET's with standard electrical simulation packages. These circuits can be used in designing non-volatile memory circuits and logic circuits and is compatible with all SPICE based circuit analysis programs. The models consist of only standard electrical components, such as BJT's, MOSFET's, diodes, resistors, and capacitors. Each model is compared to the experimental data measured from an actual FFET.
This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing.
A small-scale tiltrotor model was tested in the 7-by 10-foot Wind Tunnel at NASA Ames Research Center, with the goal of better understanding Vortex Ring State (VRS) effects on tiltrotor aircraft. Test objectives were to obtain performance data of a tiltrotor model over a wide range of descent conditions, to explore the effects of sideslip at these descent conditions, and to investigate the validity of using a single-rotor with a physical image plane to simulate dual rotor performance characteristics. The model consisted of a pair of 2-bladed teetering rotors with untwisted, 11.125-inch diameter, rectangular planform blades. Model configuration variations included a dual-rotor, an isolated-rotor, and a single-rotor with a physical image plane. Rotor performance data were obtained for the dual-rotor configuration operating over a wide range of descent and sideslip conditions. Isolated-rotor and single-rotor with image plane configurations were tested over an abbreviated range of descent conditions. Results of this investigation are presented and show mean thrust reductions in the region of VRS for each model configuration. In comparison with the dual-rotor configuration, the isolated-rotor and single-rotor with image plane configurations produced thrust results similar in trend but different in magnitude.
Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.
A model for the chromospheric-coronal transition layer and lower corona has been constructed for the south polar region. EUV observations acquired by the Harvard OSO-4 experiment in the fall of 1967 were used in the analysis. The observations can be explained with a simple model consisting of two types of regions. One region has a temperature-density structure similar to that in models developed for typical equatorial quiet areas. The other region has a corona in which the temperature and density are a factor of about 2 lower and the chromospheric-coronal temperature gradient is less steep by a factor of 4.
It is broadly maintained that the secular variation (SV) of the large scale geomagnetic field contains information on the fluid dynamics of Earth's electrically conducting outer core. The electromagnetic theory appropriate to a simple Earth model has recently been combined with reduced geomagnetic data in order to extract some of this information and ascertain its significance. The simple Earth model consists of a rigid, electrically insulating mantle surrounding a spherical, inviscid, and perfectly conducting liquid outer core. This model was tested against seismology by using truncated spherical harmonic models of the observed geomagnetic field to locate Earth's core-mantle boundary, CMB. Further electromagnetic theory has been developed and applied to the problem of estimating the horizontal fluid motion just beneath CMB. Of particular geophysical interest are the hypotheses that these motions: (1) include appreciable surface divergence indicative of vertical motion at depth, and (2) are steady for time intervals of a decade or more. In addition to the extended testing of the basic Earth model, the proposed GRM provides a unique opportunity to test these dynamical hypotheses.
A multiple-vortex-ring model of the winds associated with a microburst is verified by matching the model-generated winds to those encountered at the Dallas-Ft. Worth (DFW) microburst. The basis of the model consists of time-invariant vortex ring filaments embedded in irrotational flow. Each ring's viscous core is modeled by distributing the vorticity over a small distance (relative to the ring diameter) radially from the filaments. Parameters such as the size and strength of the vortex rings are identified using a modified Newton-Raphson technique. The parameters identified from the analysis of the DFW microburst encounter indicate a large ring with a radius of 8500 ft and a smaller ring with a radius of 1700 ft.
The objective of this study is to develop a model of the cardiovascular system capable of simulating the short-term (< or = 5 min) transient and steady-state hemodynamic responses to head-up tilt and lower body negative pressure. The model consists of a closed-loop lumped-parameter representation of the circulation connected to set-point models of the arterial and cardiopulmonary baroreflexes. Model parameters are largely based on literature values. Model verification was performed by comparing the simulation output under baseline conditions and at different levels of orthostatic stress to sets of population-averaged hemodynamic data reported in the literature. On the basis of experimental evidence, we adjusted some model parameters to simulate experimental data. Orthostatic stress simulations are not statistically different from experimental data (two-sided test of significance with Bonferroni adjustment for multiple comparisons). Transient response characteristics of heart rate to tilt also compare well with reported data. A case study is presented on how the model is intended to be used in the future to investigate the effects of post-spaceflight orthostatic intolerance.
The postbuckling response and failure of multistringer stiffened panels is analyzed using models with three levels of approximation. The first model uses a relatively coarse mesh to capture the global postbuckling response of a five-stringer panel. The second model can predict the nonlinear response as well as the debonding and crippling failure mechanisms in a single stringer compression specimen (SSCS). The third model consists of a simplified version of the SSCS that is designed to minimize the computational effort. The simplified model is well-suited to perform sensitivity analyses for studying the phenomena that lead to structural collapse. In particular, the simplified model is used to obtain a deeper understanding of the role played by geometric and material modeling parameters such as mesh size, inter-laminar strength, fracture toughness, and fracture mode mixity. Finally, a global/local damage analysis method is proposed in which a detailed local model is used to scan the global model to identify the locations that are most critical for damage tolerance.
There is convincing observational evidence for an increasing cosmic-ray positron-to-electron ratio at energies larger than ~10 GeV, at odds with expectations from secondary positron production. The most recent AMS-02 data exhibit an interesting spectral feature consisting of a bump at an energy around 300 GeV followed by a drop around ~800 GeV. A possible explanation for the most recent data is that the excess positron flux originates from decaying dark matter. Here, we show that models consisting of two dark matter particle species contributing equally to the global cosmological dark matter density provide good fits to the data. The favored models, with a best-fit with χ 2 / d . o . f ~ 2, consist of a first species weighing 750 GeV decaying with a lifetime τ χ ~ 10 26 s to τ lepton pairs (or to a pair of vector bosons subsequently decaying to a τ pair each), and a second species with a mass around 2.3 TeV decaying to μ lepton pairs. We provide a few possible concrete realizations for this scenario.
Herein, modeling of the phase transitions anticipated in gas hydrate bearing sediments (GHBS) is critical for a proper understanding of time-dependent changes in states and volumes (e.g. the production of methane from this type of soils). We propose a new pseudo-kinetic approach to simulate the typical phase changes anticipated in GHBS, using published experimental results involving gas hydrate dissociation that are the basis of a widely used kinetic model. The proposed pseudo-kinetic model is formulated in the pressure-temperature (P-T) plane and assumes a rate of gas hydrate dissociation (or formation) proportional to the distance between the current state and the phase boundary. The model consists of only one parameter and is simple to implement in numerical simulators. A similar concept is used to model ice formation/thawing phenomena, but based on the ice/liquid-water phase boundary. We implemented the pseudo-kinetic model in a fully coupled thermo-hydro-chemo-mechanical (THCM) finite element code and validated it against experimental results performed on the dissociation of synthetic gas hydrate. We also evaluated the pseudo-kinetic model using synthetic cases covering several scenarios associated with gas hydrate formation/dissociation and ice formation/thawing. The model successfully reproduced the gas production test from a natural GHBS core from Korea (scaled gas venting experiment over 14 h), and also the formation of gas hydrate and ice in permafrost in Alaska (over 2 × 10 6 years). -The analyses show the versatility of the proposed pseudo-kinetic approach by applying it to model the different types of phase transitions typically encounter in GHBS. The simple formulation, easy implementation in numerical simulator, and reduced number of parameters (only one per phase change) make this model an attractive option for simulating phase transformations in problems involving GHBS.
Conceptual models of smectite hydration include planar (flat) clay layers that undergo stepwise expansion as successive monolayers of water molecules fill the interlayer regions. However, X-ray diffraction (XRD) studies indicate the presence of interstratified hydration states, suggesting non-uniform interlayer hydration in smectites. Additionally, recent theoretical studies have shown that clay layers can adopt bent configurations over nanometer-scale lateral dimensions with minimal effect on mechanical properties. Therefore, in this study we used molecular simulations to evaluate structural properties and water adsorption isotherms for montmorillonite models composed of bent clay layers in mixed hydration states. Results are compared with models consisting of planar clay layers with interstratified hydration states (e.g. 1W–2W). The small degree of bending in these models (up to 1.5 Å of vertical displacement over a 1.3 nm lateral dimension) had little or no effect on bond lengths and angle distributions within the clay layers. Except for models that included dry states, porosities and simulated water adsorption isotherms were nearly identical for bent or flat clay layers with the same averaged layer spacing. Similar agreement was seen with Na- and Ca-exchanged clays. In conclusion, while the small bent models did not retain their configurations during unconstrained molecular dynamics simulation with flexible clay layers, we show that bent structures are stable at much larger length scales by simulating a 41.6×7.1 nm 2 system that included dehydrated and hydrated regions in the same interlayer.
Big Bang nucleosynthesis provides the earliest probe of standard model physics, at a time when the universe was less than 1000 seconds old. It determines the abundances of the lightest nuclides, which give rise to the subsequent history of the visible matter in the universe. This work derives new 7 Be(n,p) 7 Li thermonuclear reaction rates based on all available experimental information. This reaction sensitively impacts the primordial abundances of 7 Be and 7 Li during big bang nucleosynthesis. We critically evaluate all available data and disregard experimental results that are questionable. For the nuclear model, we adopt an incoherent sum of single-level, two-channel, R -matrix approximation expressions, which are implemented into a hierarchical Bayesian model, to analyze the remaining six data sets we deem most reliable. In the fitting of the data, we consistently model all known sources of uncertainty, including discrepant absolute normalizations of different data sets, and also take the variation of the neutron and proton channel radii into account, hence providing less biased estimates of the 7 Be(n,p) 7 Li thermonuclear rates. From the resulting posteriors, we extract R -matrix parameters ($E_r, γ^2_n, γ^2_p$) and derive excitation energies and partial and total widths. Our fit is sensitive to the contributions of the first three levels above the neutron threshold. Reaction rates were computed by integrating 10,000 samples of the reduced cross section. Our 7 Be(n,p) 7 Li thermonuclear rates have uncertainties between 1.5% and 2.0% at temperatures of ≤1 GK. Finally, we compare our rates to previous results and find that the 7 Be(n,p) 7 Li rates most commonly used in big bang simulations have uncertainties that are too optimistic.
Results are reported for braod-band photometry of the BL Lac object AO 0235+164 carried out over the spectral range from 0.36 to 3.5 microns in December 1975 and in October and November 1976. It is found that the continuum of this object steepened at visible wavelengths between December 1975 and October 1976, but maintained a relatively constant slope in the near-IR despite a factor-of-ten decrease in flux from the maximum level. Visible-wavelength data are cited which appear to suggest that the steepening of the visible spectrum occurred in less than 300 days, while the near-IR level may have been nearly constant. It is shown that the observed change in the spectral shape of the visible-wavelength continuum cannot be explained in terms of a 'composite' model consisting of an unchanging galaxy and a varying nonthermal source with constant spectral index. Two other general classes of models are considered: intrinsic variability and extrinsic modulation.
A study of stable periodic solutions to a simple nonlinear model of the ocean-atmosphere-ice system is presented. The model has two dependent variables: ocean-atmosphere temperature and latitudinal extent of the ice cover. No explicit dependence on latitude is considered in the model. Hence all variables depend only on time and the model consists of a coupled set of nonlinear ordinary differential equations. The globally averaged ocean-atmosphere temperature in the model is governed by the radiation balance. The reflectivity to incoming solar radiation, i.e., the planetary albedo, includes separate contributions from sea ice and from continental ice sheets. The major physical mechanisms active in the model are (1) albedo-temperature feedback, (2) continental ice-sheet dynamics and (3) precipitation-rate variations. The model has three-equilibrium solutions, two of which are linearly unstable, while one is linearly stable. For some choices of parameters, the stability picture changes and sustained, finite-amplitude oscillations obtain around the previously stable equilibrium solution. The physical interpretation of these oscillations points to the possibility of internal mechanisms playing a role in glaciation cycles.
Relaxed memory consistency models tolerate increased memory access latency in both hardware and software distributed shared memory systems. In recoverable systems, relaxing consistency has the added benefit of reducing the number of checkpoints needed to avoid rollback propagation. In this paper, we introduce new checkpointing algorithms that take advantage of relaxed consistency to reduce the performance overhead of checkpointing. We also introduce a scheme based on lazy relaxed consistency, that reduces both checkpointing overhead and the overhead of avoiding error propagation in systems with error latency. We use multiprocessor address traces to evaluate the relaxed consistency approach to checkpointing with distributed shared memory.
An empirical model calibration approach is presented that aims to approximate missing biosphere processes in a global land surface model without the need for substantial model structural changes. The strategy is implemented here using the NASA Catchment‐CN land surface model and Moderate Resolution Imaging Spectroradiometer (MODIS) observations of the fraction of absorbed photosynthetically active radiation (FPAR). Existing plant functional types (PFTs) of the Catchment‐CN model are divided into three subtypes, based on the bias between the model‐simulated and MODIS‐observed FPAR. Separate sets of vegetation parameters for each subtype are then calibrated at a small number of grid cells with homogeneous, single‐PFT land cover, using MODIS FPAR reference observations from 2003 to 2009. The effectiveness of the empirical approach at improving the realism of modeled vegetation dynamics is investigated with two global model simulations for the period 2010–2016, one using the newly calibrated parameter values and the other using the original values. Globally, the calibrated parameters reduce the root mean square error (RMSE) of the modeled FPAR with respect to MODIS by 0.029 (∼10%) on average. In some regions, substantially larger RMSE reductions are achieved. RMSE reductions are primarily driven by model bias reductions, with neutral effects on the temporal correlation skill. While the empirical approach is suitable for achieving consistent model improvements, it is shown to be sensitive to the characteristics of the model error, specifically a dominance of the bias component in the case of Catchment‐CN. Ultimately, more fundamental model structural changes may be required to achieve better improvements.