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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Hydrodynamic Models of Line-Driven Accretion Disk Winds III: Local Ionization Equilibrium

We present time-dependent numerical hydrodynamic models of line-driven accretion disk winds in cataclysmic variable systems and calculate wind mass-loss rates and terminal velocities. The models are 2.5-dimensional, include an energy balance condition with radiative heating and cooling processes, and includes local ionization equilibrium introducing time dependence and spatial dependence on the line radiation force parameters. The radiation field is assumed to originate in an optically thick accretion disk. Wind ion populations are calculated under the assumption that local ionization equilibrium is determined by photoionization and radiative recombination, similar to a photoionized nebula. We find a steady wind flowing from the accretion disk. Radiative heating tends to maintain the temperature in the higher density wind regions near the disk surface, rather than cooling adiabatically. For a disk luminosity L (sub disk) = solar luminosity, white dwarf mass M(sub wd) = 0.6 solar mass, and white dwarf radii R(sub wd) = 0.01 solar radius, we obtain a wind mass-loss rate of M(sub wind) = 4 x 10(exp -12) solar mass yr(exp -1) and a terminal velocity of approximately 3000 km per second. These results confirm the general velocity and density structures found in our earlier constant ionization equilibrium adiabatic CV wind models. Further we establish here 2.5D numerical models that can be extended to QSO/AGN winds where the local ionization equilibrium will play a crucial role in the overall dynamics.

Pereyra, Nicolas Antonio↗
NASA NTRS1979

Flow friction of the turbulent coolant flow in cryogenic porous cables

Considered are cryogenic power transmission cables with porous cores. Calculations of the turbulent coolant flow with injection or suction through the porous wall are presented within the framework of a two-layer model. Universal velocity profiles were obtained for the viscous sublayer and flow core. Integrating the velocity profile, the law of flow friction in the pipe with injection has been derived for the case when there is a tangential injection velocity component. The effect of tangential velocity on the relative law of flow friction is analyzed. The applicability of the Prandtl model to the problem under study is discussed. It is shown that the error due to the acceptance of the model increases with the injection parameter and at lower Reynolds numbers; under these circumstances, the influence of convective terms in the turbulent energy equation on the mechanism of turbulent transport should be taken into account.

Hendricks, R. C.↗
NASA NTRS1990

Error analysis for pulsed maneuvers of a dual-spin spacecraft

The Galileo is a dual-spin interplanetary spacecraft which is scheduled for launch toward Jupiter in October of 1989. The spacecraft has twelve thrusters, located on the rotor, which can be operated in continuous or pulsed modes. In this paper probabilistic error models are presented for the pulsed maneuvers which are used to change the spacecraft's velocity. These models take into account all error sources which might affect the maneuver accuracies, such as wobble, nutation, plume impingement, thrust level variation and misalignment, gyro drift, burn timing errors and mass property uncertainties. The analytic models are sufficiently general so that they may be applied to all spin and dual-spin stabilized spacecraft. When these models are applied to the case of the Galileo spacecraft, the numerical results demonstrate that the spacecraft can achieve the maneuver accuracies required in order to successfully reach Jupiter and perform its scientific mission.

Longuski, James M.↗
DOE OSTI2020

Experimental and Kinetic Modeling Study of Laminar Burning Velocities of Cyclopentanone and Its Binary Mixtures with Ethanol and n-Propanol

Cyclopentanone is a promising biofuel that can enable more efficient engine operation and increase the fuel economy of the light duty fleet over current and planned technology developments. While the ignition of cyclopentanone has been investigated in detail, more studies on the laminar burning velocities of cyclopentanone are called for. In this work, the laminar burning velocities of cyclopentanone (C 5 H 8 O) have been measured using the heat flux and spherical flame methods at 1 atm, equivalence ratios from 0.7 to 1.6, and initial temperatures of 328, 353, and 428 K. To further investigate the relationship between the molecular structure and laminar burning velocity, identical experiments were also performed for binary mixtures of cyclopentanone with ethanol and n-propanol at 1:1 (mol). The consistency between the experimental data sets obtained in this work and literature data sets has been evaluated. Here, a recently published mechanism of cyclopentanone was used for simulation after adopting the submechanism of n-propanol. Good agreement has been seen between experimental and simulated results for all flames. To qualitatively explain the characteristics of the laminar burning velocity of cyclopentanone and the differences with those of ethanol and n-propanol, sensitivity analysis and reaction pathway analysis have been performed to compare the chemistry of the fuels under flame conditions, which revealed how the molecular structure of cyclopentanone could affect its laminar burning velocity. Compared to ethanol and n-propanol, cyclopentanone does not have primary carbon atoms in its molecule, leading to lower production of methyl radicals. Meanwhile, the carbonyl group in the cyclopentanone molecule is mostly released as CO in the decomposition of multiple intermediates accompanied by the production of unsaturated C 2 and C 4 species, especially C 2 H 4 and C 2 H 3 . Both features contribute to the high laminar burning velocity of cyclopentanone.

09 BIOMASS FUELS↗
NASA NTRS1984

Heat transfer distributions around nominal ice accretion shapes formed on a cylinder in the NASA Lewis Icing Research Tunnel

Local heat transfer coefficients were obtained on irregular cylindrical shapes which typify the accretion of ice on circular cylinders in cross flow. The shapes were 2, 5, and 15 min accumulations of glaze ice and 15 min accumulation of rime ice. These icing shapes were averaged axially to obtain a nominal shape of constant cross section for the heat transfer tests. Heat transfer coefficients were also measured around the cylinder with no ice accretion. The models were run in a 15.2 x 68.6 cm (6 x 27 in.) wind tunnel at several velocities. The models were also run with a turbulence producing grid which gave about 3.5 percent turbulence. The effect of roughness was also simulated with sand grains glued to the surface. Results are presented as Nusselt number versus angle from the stagnation line for the smooth and rough models for both high and low levels of free stream turbulence. Roughness of the surface in the region prior to flow separation plays a major role in determining the heat transfer distribution. Free stream turbulence does not affect the distribution of heat transfer in this region but raises the level by a nearly uniform amount. For the rime shape, roughness had a larger effect in the near wedge shaped region past the initial separation point.

Van Fossen, G. J.↗
DOE OSTI2026

Modeling Marangoni Convection using a Velocity-Time Relationship

The Waste Treatment and Immobilization Plant (WTP) at the U.S. Department of Energy’s (DOE’s) Handford site is designed to treat 56 million gallons of radioactive waste through vitrification. The melting vessels physical and chemical integrity is essential to maintain, as failure has a high safety and financial penalty. Monofrax® K-3 refractory, the material widely used for the melting vessel, undergoes significant corrosion over time, concentrated at the triple-point junction between the gaseous atmosphere, refractory, and glass melt, producing a characteristic neck-like profile that significantly limits refractory service life. Accurate prediction of the corrosion within the melter can be used to prevent this and extend the lifetime of the melters. A computational fluid dynamics (CFD) model was previously developed, and predicted subsurface refractory corrosion, but failed to predict the neck-line profile observed experimentally. To address this limitation, the glass-melt meniscus geometry at the glass-refractory interface was estimated from experimentally measured neck profiles and wettability experiments. A curve was fitted to the neck profile to identify the triple point location, and the meniscus shape was characterized by a contact angle of 1°. A velocity profile accounting for Marangoni convection-driven corrosion was derived from the estimated meniscus geometry. Surface tension measurements from LORPM14R1 glasses of varying composition were coupled with K-3 coupon dissolution rates to establish a surface tension–time relationship. This analytical velocity-time model was integrated into the existing CFD framework to improve prediction of the neck corrosion profile. Work was done in a computational setting with national collaboration, resulting in professional development through presentational and technical writing growth.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Realizability-preserving discontinuous Galerkin method for spectral two-moment radiation transport in special relativity

Here we present a realizability-preserving numerical method for solving a spectral two-moment model to simulate the transport of massless, neutral particles interacting with a steady background material moving with relativistic velocities. The model is obtained as the special relativistic limit of a four-momentum-conservative general relativistic two-moment model. Using a maximum-entropy closure, we solve for the Eulerian-frame energy and momentum. The proposed numerical method is designed to preserve moment realizability, which corresponds to moments defined by a nonnegative phase-space density. The realizability-preserving method is achieved with the following key components: (i) a discontinuous Galerkin phase-space discretization with specially constructed numerical fluxes in the spatial and energy dimensions; (ii) a strong stability-preserving implicit-explicit time-integration method; (iii) a realizability-preserving conserved to primitive moment solver; (iv) a realizability-preserving implicit collision solver; and (v) a realizability-enforcing limiter. Component (iii) is necessitated by the closure procedure, which closes higher order moments nonlinearly in terms of primitive moments. The nonlinear conserved to primitive and the implicit collision solves are formulated as fixed-point problems, which are solved with custom iterative solvers designed to preserve the realizability of each iterate. With a series of numerical tests, we demonstrate the accuracy and robustness of this discontinuous-Galerkin-implicit-explicit method.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

Predictions of the structure of turbulent, particle-laden, round jets

Models of gas and particle motion in turbulent, particle-laden, round jets were evaluated using existing measurements of flow structure. Three models were considered: (1) a locally homogeneous flow model, where velocities and turbulent mixing properties of both phases were assumed to be equal; (2) a deterministic separated flow model, where interphase slip was considered but effects of turbulent dispersion were ignored; and (3) a stochastic separated flow model where effects of interphase slip and turbulent dispersion were considered using random sampling techniques. In all three cases, mean and turbulent properties of the continuous phase were found with a well-calibrated k-epsilon model. The locally homogeneous flow and deterministic separated flow models over- and underestimated particle spread and flow development rates, respectively. The stochastic separated flow model, however, yielded satisfactory predictions of flow structure - except at high particle loadings. Uncertainties in initial conditions for the measurements and possible effects of turbulence modulation by the particles are proposed as the reason for these errors.

Shuen, J.-S.↗
NASA NTRS1998

Physics of Interplanetary Dust Collection with Aerogel

This report presents the results of research undertaken to study various problems associated with hypervelocity capture of dust particles in aerogel. The primary topics investigated were the properties of shocked aerogel and the requirements for reliable capture of particles on the STARDUST mission. In particular, the viscosity of shocked aerogel has been an open question. The results presented here suggest that the viscosity of aerogel at high impact velocities is negligible, although there remains some uncertainty about lower velocities. The model adopted for viscosity treats the mixture of polymeric silica and decomposition products and finds that, for particle velocities of 6-7 km/s, the viscosity is similar to that typical of light gasses at STP. Expressions for the Hugoniot of aerogel as a function of density were also obtained from the available data. All aerogels of interest for cosmic dust collectors have very similar shock velocity-particle velocity Hugoniot curves. The strength behavior of aerogel for low-speed penetration was measured, but further work is needed to study the proper way to apply this to the issue of terminal deceleration of a dust particle. Preliminary calculations designed to maximize the penetration depths were performed to determine the required density of aerogel to reliably stop a particle in a 3 cm thickness of aerogel (the path length expected for a normal impact into the STARDUST collector). In order to stop a particle of density rho(sub p) and diameter d(sub p), the mean density of the aerogel collector should be no less than that given by the expression bar rho(sub 0) = 1.085 X 10(exp -4 )rho(sub p)d(sub p), for densities measured in g/ cu cm and the particle diameter measured in micrometers.

Anderson, William W.↗
DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A realworld highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗
DOE OSTI2022

Joint Inversion of Body Wave Arrival Times, Surface Wave Dispersion Data and Receiver Functions: Method and Application to South China

In this work, we have developed a new joint inversion method that incorporates body wave arrival times, surface wave dispersion and receiver functions to simultaneously update earthquake locations and constrain three-dimensional P-wave (Vp) and S-wave velocity (Vs) models. Due to complementary sensitivities of the three types of data, the proposed joint inversion algorithm can reduce the intrinsic non-uniqueness of inversions using fewer types of data and better determine smooth velocity variations and velocity discontinuities. Synthetic tests demonstrate the advantages of this new joint inversion algorithm in resolving velocity structures, especially in constraining velocity gradients across the Moho interface. We have applied the proposed joint inversion algorithm to image the lithosphere velocity structure of south China. The inverted Vp and Vs models fit body wave arrival times, surface wave dispersion and receiver functions well. We further analyzed the distribution of Vs gradients across the Moho interface in detail, which helps us better understand tectonics in south China.

58 GEOSCIENCES↗
DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real- world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗
NASA NTRS1984

Advances in Multivalued-Velocity Theory of Turbulence

Developments reported in modeling of fluid turbulence as superposition of number of interpenetrating velocity fields. Multivalued-velocity model has practical implications in design of aircraft, turbines, nozzles, pumps, and other systems that involve turbulent flow. In both viscous and inviscid cases, equations made to predict stable regine of oscillations, both finite and independent of initial conditions as in case of real turbulence.

Zak, M. A.↗
NASA NTRS2012

Comparison of MSL RCS Jet Computations With Flow Visualization and Velocimetry

Numerical predictions of the Mars Science Laboratory (MSL) reaction control system (RCS) jets interacting with a Mach 10 hypersonic flow are compared to experimental nitric oxide (NO) planar laser-induced fluorescence (PLIF) data. The steady Reynolds Averaged Navier Stokes (RANS) equations using the Baldwin-Barth one-equation turbulence model were solved using the OVERFLOW code. The experimental PLIF data used for comparison consists of qualitative two-dimensional visualization images, qualitative reconstructed three-dimensional flow structures, and quantitative two-dimensional distributions of streamwise velocity. Through modeling of the PLIF signal equation, computational flow images (CFI) were produced and directly compared to the qualitative PLIF data. Post processing of the experimental and simulation data enabled the jet trajectory to be extracted for a more quantitative comparison. The two-dimensional velocity fields were reconstructed through interpolation of a series of single-component velocity profiles. Each distribution of single-component velocity was obtained using molecular tagging velocimetry (MTV). After validating the numerical model, the numerical solution was further examined to gain insight into hypersonic jet-in-crossflow interaction. Future NO-PLIF experiments are proposed based on this analysis.

Johansen, Craig T.↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
NASA NTRS1979

Aerodynamic and acoustic investigation of inverted velocity profile coannular exhaust nozzle models and development of aerodynamic and acoustic prediction procedures

Five co-annular nozzle models, covering a systematic variation of nozzle geometry, were tested statically over a range of exhaust conditions including inverted velocity profile (IVP) (fan to primary stream velocity ratio 1) and non IVP profiles. Fan nozzle pressure ratio (FNPR) was varied from 1.3 to 4.1 at primary nozzle pressure ratios (PNPR) of 1.53 and 2.0. Fan stream temperatures of 700 K (1260 deg R) and 1089 K(1960 deg R) were tested with primary stream temperatures of 700 K (1260 deg R), 811 K (1460 deg R), and 1089 K (1960 deg R). At fan and primary stream velocities of 610 and 427 m/sec (2000 and 1400 ft/sec), respectively, increasing fan radius ratio from 0.69 to 0.83 reduced peak perceived noise level (PNL) 3 dB, and an increase in primary radius ratio from 0 to 0.81 (fan radius ratio constant at 0.83) reduced peak PNL an additional 1.0 dB. There were no noise reductions at a fan stream velocity of 853 m/sec (2800 ft/sec). Increasing fan radius ratio from 0.69 to 0.83 reduced nozzle thrust coefficient 1.2 to 1.5% at a PNPR of 1.53, and 1.7 to 2.0% at a PNPR of 2.0. The developed acoustic prediction procedure collapsed the existing data with standard deviation varying from + or - 8 dB to + or - 7 dB. The aerodynamic performance prediction procedure collapsed thrust coefficient measurements to within + or - .004 at a FNPR of 4.0 and a PNPR of 2.0.

Larson, R. S.↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗