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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 91 records · Page 5

Compression-ignition engine performance with undoped and doped fuel oils and alcohol mixtures

Several fuel oils, doped fuel oils, and mixtures of alcohol and fuel oil were tested in a high-speed, single-cylinder, compression-ignition engine to determine power output, fuel consumption, and ignition and combustion characteristics. Fuel oils or doped fuel oils of high octane number had shorter ignition lags, lower rates of pressure rise, and gave smoother engine operation than fuel oils or doped fuel oils of low octane number. Higher engine rotative speeds and boost pressures resulted in smoother engine operation and permitted the use of fuel oils of relatively low octane number. Although the addition of a dope to a fuel oil decreased the ignition lag and the rate of pressure rise, the ensuing rate of combustion was somewhat slower than for the undoped fuel oil so that the effectiveness of combustion was practically unchanged. Alcohol used as an auxiliary fuel, either as a mixture or by separate injection, increased the rates of pressure rise and induced roughness. In general, the power output decreased as the proportion of alcohol increased and, below maximum power, varied with the heating value of the total fuel charge.

Moore, Charles S↗

On DGS Relaxation: The Stokes Problem

Multigrid methods have proven to be efficient methods for solving partial differential equations (especially those of elliptic type). There is also growing experience with multigrid solvers for fluids problems, e.g., the Stokes and Navier-Stokes equations (using both finite element and finite difference discretizations). It is also well known that at the heart of any multigrid method is the smoother. In this work we look at a smoother introduced by Brandt and Dinar (DGS relaxation), and we examine some of its properties and consider some possible modifications to it. It is well known that multigrid performance using DGS relaxation is sensitive to the treatment of boundaries; this issue is addressed.

Meir, A. J.↗

Radiative Smoothing in Clouds at Transparent and Absorbing Wavelengths

For absorbing and transparent wavelengths, we discuss the effect of horizontal solar radiative fluxes in clouds on the accuracy of a conventional plane-parallel radiative transfer calculations for a single pixel, known as the Independent Pixel Approximation (IPA). We address the question of correlations between horizontal fluxes, IPA accuracies and radiative smoothing. By smoothing we understand a radiative transfer process whereby radiation does not follow the small-scale fluctuations of cloud structure, producing much smoother radiation fields. The scale eta that characterizes this process is called "radiative smoothing scale." We relate radiative smoothing to the photon's horizontal displacement that characterizes a "spot" of reflected light associated with a point source. We generalize the "spot-size" estimate derived for conservative scattering using the diffusion theory to the case of non-conservative scattering. For reflected light, theoretical results are confirmed with numerical simulations. The radiative smoothing scale eta is a critical value where IPA effectively breaks down; for scales smaller than TI, real radiation field are much smoother than their IPA counterparts for the same cloud structure. In addition to the estimate of il for absorbing wavelengths, we show that: (1) with more absorption, the scale break determined by eta in a log-log plot of wavenumber spectra moves towards smaller scales and (2) the smaller eta the flatter the small-scale slope which means less radiative smoothing, thus more accuracy in the IPA reflection.

Marshak, A.↗

Exploratory Investigation of Aerodynamic Characteristics of Helicopter Tail Boom Cross-Section Models with Passive Venting

Two large-scale, two-dimensional helicopter tail boom models were used to determine the effects of passive venting on boom down loads and side forces in hovering crosswind conditions. The models were oval shaped and trapezoidal shaped. Completely porous and solid configurations, partial venting in various symmetric and asymmetric configurations, and strakes were tested. Calculations were made to evaluate the trends of venting and strakes on power required when applied to a UH-60 class helicopter. Compared with the UH-60 baseline, passive venting reduced side force but increased down load at flow conditions representing right sideward flight. Selective asymmetric venting resulted in side force benefits close to the fully porous case. Calculated trends on the effects of venting on power required indicated that the high asymmetric oval configuration was the most effective venting configuration for side force reduction, and the high asymmetric with a single strake was the most effective for overall power reduction. Also, curves of side force versus flow angle were noticeable smoother for the vented configurations compared with the solid baseline configuration; this indicated a potential for smoother flight in low-speed crosswind conditions.

Banks, Daniel W.↗

The GEOS Retrospective Data Assimilation System: The 6-hour lag case

The fixed-lag Kalman smoother (FLKS) has been proposed as a framework to construct data assimilation procedures capable of producing high-quality climate research datasets. Fixed-lag Kalman smoother-based systems, referred to as retrospective data assimilation systems, are an extension to three-dimensional filtering procedures with the added capability of incorporating observations not only in the past and present time of the estimate, but also at future times. A variety of simplifications are necessary to render retrospective assimilation procedures practical. In this article, we present an FLKS-based retrospective data assimilation system implementation for the Goddard Earth Observing System (GOES) Data Assimilation System (DAS). The practicality of this implementation comes from the practicality of its underlying (filter) analysis system, i.e., the physical-space statistical analysis system (PSAS). The behavior of two schemes is studied here. The first retrospective analysis (RA) scheme is designed simply to update the regular PSAS analyses with observations available at times ahead of the regular analysis times. Although our GEOS DAS implementation is general, results are only presented for when observations 6-hours ahead of the analysis time are used to update the PSAS analyses and thereby to calculate the so-called lag-1 retrospective analyses. Consistency tests for this RA scheme show that the lag-1 retrospective analyses indeed have better 6-hour predictive skills than the predictions from the regular analyses. This motivates the introduction of the second retrospective analysis scheme which, at each analysis time, uses the 6-hour retrospective analysis to replace the first-guess normally used in the PSAS analysis, and therefore allows the calculation of a revised (filter) PSAS analysis. Since in this scheme the lag-1 retrospective analyses influence the filter results, this procedure is referred to as the retrospective-based iterative analysis (RIA) scheme. Results from the RIA scheme indicate its potential for improving the overall quality of the assimilation.

Zhu, Yan-Qiu↗

Small-scale Interstellar Structure Toward the Open Cluster Chi Persei; Program ID: BO29 (Cycle 2)

The primary objective of this program was to obtain FUSE observations of the interstellar H2 absorption toward six early-type stars in the core of the open star cluster Chi Persei. High resolution optical observations of the interstellar Na I absorption toward these stars and others in the core of Chi Per have revealed a rich variety of small-scale diffuse ISM structure in both the distant Perseus and more local Orion spiral arms. At the 1 arc minute angular scales typically probed by the separations of these stars, this structure corresponds to respective physical length scales of 0.6 and 0.15 pc in the Perseus and Orion arm gas. The principal scientific goal of the FUSE observations was to determine if this small-scale Na I structure toward the core of Chi Per was reflected in the abundance and/or excitation of interstellar H2. In September 2001, we obtained FUSE observations of the Chi Per stars BD +56 563, BD +56 571, BD +56 573, BD +56 574, BD +56 575, and BD +56 578 for this program. The data reveal that the Perseus arm gas exhibits significant small-scale variations in the strength of its molecular hydrogen absorption while the Orion arm H2 absorption is relatively uniform. We presented these results at the January 2003 American Astronomical Society meeting in Seattle, WA (points, Meyer, Lauroesch, Nguyen, and Friedman 2002, Bulletin of the American Astronomical Society, 34,1229). Since Na I is not a dominant ion in H I clouds, the variations detected in the Perseus arm Na I line profiles could be due to spatial differences in either the physical structure or the physical conditions in the gas. Although many of the H2 absorption profiles are too saturated or too weak to be definitive in this regard, it is clear that small-scale variations are present in H2 gas with excitation as high as the J=4 rotational level. In contrast, lower spatial resolution H I 21 cm studies of the Perseus arm gas across the face of the h and Chi Per double cluster have shown smoother, continuous variations on the larger scale. In order to investigate if the global velocity structure of H2 toward h and Chi Per more closely follows the chaotic structure seen in interstellar Na I absorption or the smoother, continuous H I structure, we have expanded our FUSE study with a Cycle 4 program (D902, PI: Points) to survey the H2 absorption toward a number of other stars across the face of the double cluster. We have obtained FUSE spectra of 14 additional h and Chi Per stars through this program and are now combining all of the data into a comprehensive study that will be submitted for publication next year.

Meyer, David M.↗

Gear Durability Shown To Be Improved by Superfinishing

Gears, bearings, and similar mechanical elements transmit loads through contacting surfaces. At the NASA Glenn Research Center at Lewis Field, we postulated that the fatigue lives of gears could be improved by providing smoother tooth surfaces. A superfinishing process was applied to a set of conventionally ground, aerospace-quality gears. This process produced a highly polished, mirrorlike surface as shown in the preceding photograph. The surface fatigue lives of both superfinished and conventionally ground gears were measured by experiments. The superfinished gears survived about four times longer than the conventionally ground gears. These superfinished gears were produced from conventionally ground, aerospace-quality gears whose geometry had been inspected. The gears were superfinished by placing them in a vibrating bath consisting of water, detergent, abrasive powder, and small pieces of zinc. Upon removal from the bath, the surfaces were highly polished, as depicted in the preceding photograph. The gears were again inspected, and dimensional measurements made before and after the superfinishing operation were compared. Superfinishing removed the peaks of the grinding marks and left a much smoother surface. Profile and spacing checks proved that the overall gear tooth shape was not affected in any harmful way. Superfinishing uniformly removed approximately 2.5 microns from each surface.

Krautz, Timothy L.↗

Thermostatic Valves Containing Silicone-Oil Actuators

Flow-splitting and flow-mixing thermally actuated spool valves have been developed for controlling flows of a heat-transfer fluid in a temperature-regulation system aboard the Mars Science Laboratory (MSL) rover. Valves like these could also be useful in terrestrial temperature-regulation systems, including automobile air-conditioning systems and general refrigeration systems. These valves are required to provide smoother actuation over a wider temperature range than the flow-splitting, thermally actuated spool valves used in the Mars Explorer Rover (MER). Also, whereas the MER valves are unstable (tending to oscillate) in certain transition temperature ranges, these valves are required not to oscillate. The MER valves are actuated by thermal expansion of a wax against spring-loaded piston rods (as in common automotive thermostats). The MSL valves contain similar actuators that utilize thermal expansion of a silicone oil, because silicone-oil actuators were found to afford greater and more nearly linear displacements, needed for smoother actuation, over the required wider temperature range. The MSL valves also feature improved spool designs that reflect greater understanding of fluid dynamics, consideration of pressure drops in valves, and a requirement for balancing of pressures in different flow branches.

Bhandari, Pradeep↗

The Effect of Composition on the Surface Finish of PS400: A New High Temperature Solid Lubricant Coating

A new composite, multi-constituent, solid lubricant coating, NASA PS400, developed for high temperature tribological applications, exhibits a smoother surface finish after grinding and polishing than its predecessors PS200 and PS300. In this paper, the baseline composition of PS400 is modified to investigate each individual constituent s role on the achievable surface finish through a series of coating deposition, grinding, and polishing experiments. Furthermore, to explore the limits of compositional tailoring for improved tribological performance, several PS400 coatings were doped with additional solid lubricants (graphite, MoS2 and BN) and tribologically tested. The test results clearly showed that, compared to PS300 coatings, PS400 achieves a smoother surface finish via a reduced lubricant content. Coatings prepared with higher than the baseline level (10 wt%) of lubricants exhibited higher final surface roughness than the earlier generation PS300 coatings. Reducing or eliminating the one or both lubricants (fluorides or silver) did not further improve the surface finish suggesting that the current composition of PS400 is near optimal with respect to surface finish. Lastly, attempts to improve the poor initial room temperature tribological behavior of PS400 via the addition of traditional solid lubricants were unsuccessful. Based upon this work and earlier results it is expected that future research will concentrate on developing methods to produce a lubricious glaze on the rubbing surface during break in to ensure that low friction and wear are rapidly achieved.

DellaCorte, Christopher↗

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Orbit Determination↗

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗

Multigrid Preconditioning for a Space-Time Spectral-Element Discontinuous-Galerkin Solver

In this work we examine a multigrid preconditioning approach in the context of a high- order tensor-product discontinuous-Galerkin spectral-element solver. We couple multigrid ideas together with memory lean and efficient tensor-product preconditioned matrix-free smoothers. Block ILU(0)-preconditioned GMRES smoothers are employed on the coarsest spaces. The performance is evaluated on nonlinear problems arising from unsteady scale- resolving solutions of the Navier-Stokes equations: separated low-Mach unsteady ow over an airfoil from laminar to turbulent ow. A reduction in the number of ne space iterations is observed, which proves the efficiency of the approach in terms of preconditioning the linear systems, however this gain was not reflected in the CPU time. Finally, the preconditioner is successfully applied to problems characterized by stiff source terms such as the set of RANS equations, where the simple tensor product preconditioner fails. Theoretical justification about the findings is reported and future work is outlined.

Franciolini, Matteo↗

Is There A Relationship Between Cornered-Hat Methods and A Residual Approach to Estimate System Uncertainty?

Recently a relationship has been established between a now traditional residual diagnostic used to estimate observation, background and analysis error covariances of interest to data assimilation and the three-cornered hat (3CH) method. An existing extension of the traditional residual diagnostic uses residuals from a fixed lag-1 Kalman smoother to retrieve system (model) error covariance. It is thus natural to ask if an additional relationship can be established between this extended residual method and some form of cornered--hat method. The answer might seem straightforward. Unlike in the standard residual estimation case, attempting to estimate model error amounts to estimating the statistics of a residual quantity itself. As shown in this presentation, in such cases the 3CH method becomes trivial: the sought out uncertainty can be derived directly from the covariance of the residual quantity at hand. In the particular case of estimating model error, one of the corners would have to be composed of vectors providing estimates of model error; these are not typically available in practice. Therefore, at first glance the present work finds no relationship between the lag-1 smoother residual diagnostic for system error estimation and cornered--hat methods. However, the work suggests that a two-tiered 3CH might be all that is necessary for system uncertainty to be obtained with 3CH.

Ricardo Todling↗

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

Parallel Element-based Algebraic Multigrid for H (c url ) and H (div) Problems Using the ParELAG Library

This paper presents the use of element-based algebraic multigrid (AMGe) hierarchies, implemented in the ParELAG (Parallel Element Agglomeration Algebraic Multigrid Upscaling and Solvers) library, to produce multilevel preconditioners and solvers for H (c url ) and H (div) formulations. ParELAG constructs hierarchies of compatible nested spaces, forming an exact de Rham sequence on each level. This allows the application of hybrid smoothers on all levels and AMS (Auxiliary-space Maxwell Solver) or ADS (Auxiliary-space Divergence Solver) on the coarsest levels, obtaining complete multigrid cycles. Numerical results are presented, showing the parallel performance of the proposed methods. As a part of the exposition, this paper demonstrates some of the capabilities of ParELAG and outlines some of the components and procedures within the library.

97 MATHEMATICS AND COMPUTING↗

On ParELAG's Parallel Element-based Algebraic Multigrid and its MFEM Miniapps for H(curl) and H(div) Problems: a report including lowest and next to the lowest order numerical results

This paper presents the utilization of element-based algebraic multigrid (AMGe) hierarchies, implemented in the ParELAG (Parallel Element Agglomeration Algebraic Multigrid Upscaling and Solvers) library, to produce multilevel preconditioners and solvers for H(curl) and H(div) formulations. This involves the construction of hierarchies of compatible nested spaces, forming an exact de Rham sequence on each level. This allows the application of hybrid smoothers on all levels and AMS (Auxiliary-space Maxwell Solver) or ADS (Auxiliary-space Divergence Solver) on the coarsest levels, obtaining complete multigrid cycles. Numerical results are presented, showing the parallel performance of the proposed methods. As a part of the exposition, this paper demonstrates some of the capabilities of ParELAG and outlines some of the components and procedures within the library.

97 MATHEMATICS AND COMPUTING↗

Reanalysis Surface Mass Balance of the Greenland Ice Sheet along K-transect (2000-2014)

Accurate estimates of surface mass balance over the Greenland ice sheet (GrIS) would contribute to understanding the cause of recent changes and would help to better estimate the future contribution of the GrIS to sea-level rise. Given the limitations of in-situ measurement, modeling, and remote sensing, it is critical to explore the opportunity to merge the available data to better characterize the spatial and temporal variation of the GrIS surface mass balance (SMB). This work utilizes a particle batch smoother data assimilation technique that yields SMB estimates that benefit from the snow model Crocus and a 16-day albedo product derived from satellite remote sensing data. Comparison of the results against in-situ SMB measurements shows that the assimilation of the albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB by 51% and reduces bias by 95%.

Greenland Ice Sheet↗