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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Visualization of Unsteady Computational Fluid Dynamics

The current compute environment that most researchers are using for the calculation of 3D unsteady Computational Fluid Dynamic (CFD) results is a super-computer class machine. The Massively Parallel Processors (MPP's) such as the 160 node IBM SP2 at NAS and clusters of workstations acting as a single MPP (like NAS's SGI Power-Challenge array and the J90 cluster) provide the required computation bandwidth for CFD calculations of transient problems. If we follow the traditional computational analysis steps for CFD (and we wish to construct an interactive visualizer) we need to be aware of the following: (1) Disk space requirements. A single snap-shot must contain at least the values (primitive variables) stored at the appropriate locations within the mesh. For most simple 3D Euler solvers that means 5 floating point words. Navier-Stokes solutions with turbulence models may contain 7 state-variables. (2) Disk speed vs. Computational speeds. The time required to read the complete solution of a saved time frame from disk is now longer than the compute time for a set number of iterations from an explicit solver. Depending, on the hardware and solver an iteration of an implicit code may also take less time than reading the solution from disk. If one examines the performance improvements in the last decade or two, it is easy to see that depending on disk performance (vs. CPU improvement) may not be the best method for enhancing interactivity. (3) Cluster and Parallel Machine I/O problems. Disk access time is much worse within current parallel machines and cluster of workstations that are acting in concert to solve a single problem. In this case we are not trying to read the volume of data, but are running the solver and the solver outputs the solution. These traditional network interfaces must be used for the file system. (4) Numerics of particle traces. Most visualization tools can work upon a single snap shot of the data but some visualization tools for transient problems require dealing with time.

Haimes, Robert↗
DOE OSTI2023

Analysis of the rotationally-resolved infrared spectrum of CD 3 79 Br and CD 3 81 Br between 900 and 1400 cm -1

We report the infrared spectrum of CD 3 79 Br and CD 3 81 Br between 900 cm -1 and 1400 cm -1 has been analyzed at high resolution. In this region, two fundamental vibrational states, v 2 = 1 and v 5 = 1, an overtone state, v 3 = 2, and a combination state, v 3 = v 6 = 1, have been analyzed for both isotopologues. As found in other halomethane molecules, strong Coriolis resonances couple the v 2 = 1 state to the v 5 = 1 state, and similar resonances were also used to describe the coupling found between the v 5 = 1 state to the v 3 = 2 state. A new determination of the K-dependent constant A 0 was performed for each isotopologue through the use of perturbation-allowed transitions. The values for A 0 determined from the analysis are 2.6001898(26) and 2.6001905(27) for CD 3 79 Br and CD 3 81 Br, respectively. Ab initio calculations were performed to examine the efficacy of high-level theoretical calculations to accurately predict spectroscopic constants. The ab initio calculations had variable success with the largest errors associated with the prediction of the ΔB rotational constants of the interacting states

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

Automatic Processing of Reactive Polymers

A series of process modeling computer codes were examined. The codes use finite element techniques to determine the time-dependent process parameters operative during nonisothermal reactive flows such as can occur in reaction injection molding or composites fabrication. The use of these analytical codes to perform experimental control functions is examined; since the models can determine the state of all variables everywhere in the system, they can be used in a manner similar to currently available experimental probes. A small but well instrumented reaction vessel in which fiber-reinforced plaques are cured using computer control and data acquisition was used. The finite element codes were also extended to treat this particular process.

Roylance, D.↗
NASA NTRS1992

Dynamic rain fade compensation techniques for the advanced communications technology satellite

The dynamic and composite nature of propagation impairments that are incurred on earth-space communications links at frequencies in and above the 30/20 GHz Ka band necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) project by the implementation of optimal processing schemes derived through the use of the ACTS Rain Attenuation Prediction Model and nonlinear Markov filtering theory. The ACTS Rain Attenuation Prediction Model discerns climatological variations on the order of 0.5 deg in latitude and longitude in the continental U.S. The time-dependent portion of the model gives precise availability predictions for the 'spot beam' links of ACTS. However, the structure of the dynamic portion of the model, which yields performance parameters such as fade duration probabilities, is isomorphic to the state-variable approach of stochastic control theory and is amenable to the design of such statistical fade processing schemes which can be made specific to the particular climatological location at which they are employed.

Manning, Robert M.↗
NASA NTRS1993

LSENS, a general chemical kinetics and sensitivity analysis code for gas-phase reactions: User's guide

A general chemical kinetics and sensitivity analysis code for complex, homogeneous, gas-phase reactions is described. The main features of the code, LSENS, are its flexibility, efficiency and convenience in treating many different chemical reaction models. The models include static system, steady, one-dimensional, inviscid flow, shock initiated reaction, and a perfectly stirred reactor. In addition, equilibrium computations can be performed for several assigned states. An implicit numerical integration method, which works efficiently for the extremes of very fast and very slow reaction, is used for solving the 'stiff' differential equation systems that arise in chemical kinetics. For static reactions, sensitivity coefficients of all dependent variables and their temporal derivatives with respect to the initial values of dependent variables and/or the rate coefficient parameters can be computed. This paper presents descriptions of the code and its usage, and includes several illustrative example problems.

Radhakrishnan, Krishnan↗
NASA NTRS2015

Assessing Air-Sea Interaction in the Evolving NASA GEOS Model

In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.

Clayson, Carol Anne↗
NASA NTRS2019

Long and Short Term Geomagnetic Prediction (Chapter 19)

Prediction of geomagnetic variability depends on the accuracy of geomagnetic field modeling, dynamical modeling of source regions that contribute to geomagnetic signals, and advanced assimilation algorithms that combine effectively the results of geomagnetic field and dynamic models to make accurate estimates of the dynamic states of the sources and, therefore, accurate forecast of geomagnetic variations. In this chapter we provide an overview of recent research efforts in these three research areas, focusing primarily on geomagnetic variations from the dynamic outer core and from solar and lunar tidal effects, but also including a review of relevant research results and developments. Prediction of weak but periodic tidal phenomena, and of strong but chaotic secular variation (SV) showcases two very important new developments which will lead to new opportunities in geomagnetic research and application.

Weijia Kuang↗
DOE OSTI2022

Conceptual Design of Pulverized Coal Electricity Generating Units for Flexible Operation

This presentation was given by Marc Turner, NETL Support Contractor, at the International Center for Sustainable Carbon's "The Energy Transition - the Role for Sustainable Carbon" workshop held in Sardinia, Italy on November 16-18, 2022. The presentation addresses the NETL report titled "Conceptual Design of Pulverized Coal Electricity Generating Units for Flexible Operation" published on September 6, 2022. This study presents an independent conceptual assessment of the features, cost, and performance of pulverized coal power plants (without carbon dioxide capture) intended for flexible, rather than baseload, operation. The objective was to leverage the already substantial knowledge base about flexible operation and develop state-of-the-art pulverized coal power plant cases that are designed to accommodate flexible operation within an electric grid having a high level of renewable generation. This is of significant importance in coal-dependent regions of the world as variable renewable energy becomes more prevalent.

Turner, Marc↗
NASA NTRS2013

A Suzaku X-ray Observation of One Orbit of the Supergiant Fast X-ray Transient IGR J16479-4514

We report on a 250 ks long X-ray observation of the supergiant fast X-ray transient (SFXT) IGR J16479-4514 performed with Suzaku in 2012 February. During this observation, about 80% of the short orbital period (P(sub orb) approximates 3.32 days) was covered as continuously as possible for the first time. The source light curve displays variability of more than two orders of magnitude, starting with a very low emission state (10(exp −13) erg / sq cm/s; 1-10 keV) lasting the first 46 ks, consistent with being due to the X-ray eclipse by the supergiant companion. The transition to the uneclipsed X-ray emission is energy dependent. Outside the eclipse, the source spends most of the time at a level of 6-7X10)(exp−12) erg/sq. cm/s) punctuated by two structured faint flares with a duration of about 10 and 15 ks, respectively, reaching a peak flux of 3-4X10(exp −11) erg/sq. cm./S, separated by about 0.2 in orbital phase. Remarkably, the first faint flare occurs at a similar orbital phase of the bright flares previously observed in the system. This indicates the presence of a phase-locked large scale structure in the supergiant wind, driving a higher accretion rate onto the compact object. The average X-ray spectrum is hard and highly absorbed, with a column density, NH, of 10*exp 23)/sq cm, clearly in excess of the interstellar absorption. There is no evidence for variability of the absorbing column density, except that during the eclipse, where a less absorbed X-ray spectrum is observed. A narrow Fe K-alpha emission line at 6.4 keV is viewed along the whole orbit, with an intensity which correlates with the continuum emission above 7 keV. The scattered component visible during the X-ray eclipse allowed us to directly probe the wind density at the orbital separation, resulting in rho(sub w)=7X10(exp −14) g/cubic cm. Assuming a spherical geometry for the supergiant wind, the derived wind density translates into a ratio M(sub w)/v(sub infinity) = 7X10(exp −17) Solar M/km which, assuming terminal velocities in a large range 500-3000 km/s, implies an accretion luminosity two orders of magnitude higher than that observed. As a consequence, a mechanism should be at work reducing the mass accretion rate. Different possibilities are discussed.

J164794514↗
DOE OSTI2025

Data-Driven Closures and Assimilation for Stiff Multiscale Random Dynamics

Here, we introduce a data-driven and physics-informed framework for propagating uncertainty in stiff, multiscale random ordinary differential equations (RODEs) driven by correlated (colored) noise. Unlike systems subjected to Gaussian white noise, a deterministic equation for the joint probability density function (PDF) of RODE state variables does not exist in closed form. Moreover, such an equation would require as many phase-space variables as there are states in the RODE system. To alleviate this curse of dimensionality, we instead derive exact, albeit unclosed, reduced-order PDF (RoPDF) equations for low-dimensional observables/quantities of interest. The unclosed terms take the form of state-dependent conditional expectations, which are directly estimated from data at sparse observation times. However, for systems exhibiting stiff, multiscale dynamics, data sparsity introduces regression discrepancies that compound during RoPDF evolution. This is overcome by introducing a kinetic-like defect term to the RoPDF equation, which is learned by assimilating in sparse, low-fidelity RoPDF estimates. Two assimilation methods are considered, namely nudging and deep neural networks, which are successfully tested against Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

From S-N to the Paris Law with a New Mixed-Mode Cohesive Fatigue Model

The relationship between fatigue life and fatigue crack propagation rate is explored with a new cohesive damage model. The parameters of the model are obtained from idealizations of S-N diagrams used in engineering design. The model is based on the hypothesis that both stable tearing damage and damage due to cyclic loading are representations of a density of microcracks and, therefore, a single damage variable can describe the state of damage. This assumption implies that the quasi-static cohesive law that describes tearing is also the envelope of the fatigue damage. Fatigue damage within the cohesive envelope is assumed to accumulate at a rate that depends on the displacement jumps. The fatigue model was implemented as a UMAT subroutine for Abaqus cohesive elements by adding fatigue damage accumulation to a cohesive model based on the Turon mixed-mode cohesive laws. The analyses were conducted using a simplified cyclic loading procedure in which the maximum applied load is kept constant and the computational expense of cycling the load is avoided. The predicted propagation rates in mode I and mixed mode were compared to experimental results for IM7/8552 graphite/epoxy tape. Several aspects of the results were investigated, including the effect of R-curves, the stress ratio R, and the difference between displacement control and force control.

Davila, Carlos G.↗
NASA NTRS2018

A Cohesive Fatigue Model Based on the S-N Diagram

The relationship between fatigue life and fatigue crack propagation rate is explored with a new cohesive damage model. The parameters of the model are obtained from idealizations of S-N diagrams used in engineering design. The model is based on the hypothesis that both stable tearing damage and damage due to cyclic loading are representations of a density of microcracks and, therefore, a single damage variable can describe the state of damage. This assumption implies that the quasi-static cohesive law that describes tearing is also the envelope of the fatigue damage. Fatigue damage within the cohesive envelope is assumed to accumulate at a rate that depends on the displacement jumps. The fatigue model was implemented as a UMAT subroutine for Abaqus cohesive elements by adding fatigue damage accumulation to a cohesive model based on the Turon quasi-static cohesive law. The analyses were conducted using a simplified cyclic loading procedure in which the maximum applied load is kept constant and the computational expense of cycling the load is avoided. The predicted propagation rates for a double cantilever beam (DCB) specimen were compared to experimental results for IM7/8552 graphite/epoxy tape.

Dávila, Carlos G.↗
DOE OSTI2025

Orientation-dependent enhanced ionization in acetylene revealed by ultrafast cross-polarized pulse pairs

We investigate the orientation dependence of enhanced ionization (EI) during strong-field-driven nuclear motion in acetylene (C 2 ⁢H 2 ). Here, we both initiate and probe molecular dynamics in acetylene with intense 6-fs cross-polarized pulse pairs, separated by a variable delay. Following multiple ionization by the first pulse, acetylene undergoes simultaneous elongation of the carbon-carbon and carbon-hydrogen bonds, enabling further ionization by the second pulse and the formation of a very highly charged state, [C 2 ⁢H 2 ] 6+ . At small interpulse delays (< 20 fs), this enhancement occurs when the molecule is aligned to the probe pulse. Conversely, at large delays (> 40 fs), formation of [C 2 ⁢H 2 ] 6+ occurs when the molecule is aligned to the pump pulse. By analyzing the polarization and time dependence of sequentially ionized [C 2 ⁢H 2 ] 6+ , we resolve two transient alignments that both contribute to a large increase in the multiple ionization yield. In conclusion, this cross-polarized pulse pair scheme uniquely enables selective probing of deeply bound orbitals, providing new insights on orientation-dependent EI in highly charged hydrocarbons.

Atomic & molecular clusters↗
NASA NTRS2007

Uncertainty Analysis of Historical Hurricane Data

An analysis of variance (ANOVA) study was conducted for historical hurricane data dating back to 1851 that was obtained from the U. S. Department of Commerce National Oceanic and Atmospheric Administration (NOAA). The data set was chosen because it is a large, publicly available collection of information, exhibiting great variability which has made the forecasting of future states, from current and previous states, difficult. The availability of substantial, high-fidelity validation data, however, made for an excellent uncertainty assessment study. Several factors (independent variables) were identified from the data set, which could potentially influence the track and intensity of the storms. The values of these factors, along with the values of responses of interest (dependent variables) were extracted from the data base, and provided to a commercial software package for processing via the ANOVA technique. The primary goal of the study was to document the ANOVA modeling uncertainty and predictive errors in making predictions about hurricane location and intensity 24 to 120 hours beyond known conditions, as reported by the data set. A secondary goal was to expose the ANOVA technique to a broader community within NASA. The independent factors considered to have an influence on the hurricane track included the current and starting longitudes and latitudes (measured in degrees), and current and starting maximum sustained wind speeds (measured in knots), and the storm starting date, its current duration from its first appearance, and the current year fraction of each reading, all measured in years. The year fraction and starting date were included in order to attempt to account for long duration cyclic behaviors, such as seasonal weather patterns, and years in which the sea or atmosphere were unusually warm or cold. The effect of short duration weather patterns and ocean conditions could not be examined with the current data set. The responses analyzed were the storm latitude, longitude and intensity, as recorded in the data set, 24 or 120 hours beyond the current state. Several ANOVA modeling schemes were examined. Two forms of validation were used: 1) comparison with official hurricane prediction performance metrics and 2) cases studies conducted on hurricanes from the 2005 season, which were not included within the model construction and ANOVA assessment. In general, the ANOVA technique did not perform as well as the established official prediction performance metrics published by NOAA; still, the technique did remarkably well in this demonstration with a difficult data set and could probably be made to perform better with more knowledge of hurricane development and dynamics applied to the problem. The technique provides a repeatable prediction process that eliminates the need for judgment in the forecast.

Green, Lawrence L.↗
DOE OSTI2020

High-temperature and high-pressure NMR investigations of low viscous fluids confined in mesoporous systems

Abstract In this contribution, the relaxation and diffusional behaviors of low viscous fluids, water and methanol confined into mesoporous silica and controlled size pore glass were investigated. The engineered porous systems are relevant to geologically important subsurface energy materials. The engineered porous proxies were characterized by Brunauer–Emmett–Teller (BET) surface analyzer, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (EM) to determine surface area, pore-wall protonation and morphology of these materials, respectively. The confined behavior of the low viscous fluids was studied by varying pore diameter, fluid-to-solid ratio, temperature, and pressure, and then compared to bulk liquid state. Both relaxation and diffusion behaviors for the confined fluids showed increasing deviation from pure bulk fluids as the fluid-to-solid ratio was decreased, and surface-to-volume ratio ( S / V ) was varied. Variable pressure deuteron NMR relaxation of confined D 2 O and confined methanol, deuterated at the hydroxyl or methyl positions, were performed to exploit the sensitivity of the deuteron quadrupole moment to molecular rotation. The methanol results demonstrated greater pressure dependence than those for water only in bulk. The deviations from bulk liquid behavior arise from different reasons such as confinement and the interactions between confined fluid and the nano-pore wall. The results of the present report give insight into the behavior of low viscosity fluid in nano-confined geometries under different state conditions.

Chemistry↗
DOE OSTI2026

Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0–5, 0–10 cm) and rootzone (0–100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM–ecohydrology coupling, which varies strongly across models and depends on the reference dataset. Köppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil–plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil–plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

CMIP6↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗