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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

V/STOL model fan stage rig design report

A model single-stage fan with variable inlet guide vanes (VIGV) was designed to demonstrate efficient point operation while providing flow and pressure ratio modulation capability required for a V/STOL propulsion system. The fan stage incorporates a split-flap VIGV with an independently actuated ID flap to permit independent modulation of fan and core engine airstreams, a flow splitter integrally designed into the blade and vanes to completely segregate fan and core airstreams in order to maximize core stream supercharging for V/STOL operation, and an EGV with a variable leading edge fan flap for rig performance optimization. The stage was designed for a maximum flow size of 37.4 kg/s (82.3 lb/s) for compatibility with LeRC test facility requirements. Design values at maximum flow for blade tip velocity and stage pressure ratio are 472 m/s (1550 ft/s) and 1.68, respectively.

Cheatham, J. G.↗
DOE OSTI2017

On mechanical waves and Doppler shifts from moving boundaries

We investigate the propagation of infinitesimal harmonic mechanical waves emitted from a boundary with variable velocity and arriving at a stationary observer. In the classical Doppler effect, X s (t)=vt is the location of the source with constant velocity v. In the present work, however, we consider a source co-located with a moving boundary x=X s (t), where X s (t) can have an arbitrary functional form. For ‘slowly moving’ boundaries (i.e., ones for which the timescale set by the mechanical motion is large in comparison to the inverse of the frequency of the emitted wave), we present a multiple-scale asymptotic analysis of the moving boundary problem for the linear wave equation. Here, we obtain a closed-form leading-order (with respect to the latter small parameter) solution and show that the variable velocity of the boundary results not only in frequency modulation but also in amplitude modulation of the received signal. Consequently, our results extend the applicability of two basic tenets of the theory of a moving source on a stationary domain, specifically that (i) $.\atop{x}_s$ for non-uniform boundary motion can be inserted in place of the constant velocity v in the classical Doppler formula and (ii) that the non-uniform boundary motion introduces variability in the amplitude of the wave. The specific examples of decelerating and oscillatory boundary motion are worked out and illustrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1994

Evidence for X-ray flux and spectral modulation by absorption in NGC 6814. 1: The nature of the most rapid variability

The Seyfert 1 galaxy NGC 6814 was observed using the Japanese X-ray astronomy satellite Ginga in 1990 April and October. The rapid variability characteristically associated with this source was reconfirmed. Specifically, three dips were found in the April observation in which the flux dropped to nearly zero in approximately 300 s. The doubling timescale was approximately 50 s. A similar but separated drop and rise in flux was observed in the October data, different in that the flux did not decrease completely to zero. A detailed analysis of the data around the structures of most rapid variability found spectral variability and lags in flux between different energy bands. Lags were on the order of a few to tens of seconds for the April data, and on the order of tens to a couple of hundred seconds for the October data. The sense of the lags was such that during flux decreases the hard flux lagged, while during flux increases the soft flux lagged. Associated significant apparent hardening of the spectrum at low flux was observed in the April data. Apparent hardening of the spectrum also occurred in the October flux decrease, to a photon index of GAMMA = 0.85; however, the spectrum softened at lowest flux to the index of the predecrease level, GAMMA = 1.54. In the April dips, the line flux was found to decrease significantly. A marginal decrease in line flux was also observed in the October data. The variability of the line flux reconfirmed the result of Kunieda et al. (1990), who found that the line production region must be within approximately 300 light-seconds from the source. To explain the observational results, a variable-absorption model was proposed, in which the column density was assumed to vary as a function of time. Other physical processes, including intrinsic spectral changes and warm absorber models, which could account for the fastest variability, could be ruled out by the results of the data analysis. A primary constraint found for geometrical models is that the material which is doing the absorption must have relatively low ionization (xi less than 100). This result leads to severe constraints on a general orbiting cloud model, requiring high densities (n approximately 10(exp 16)/cu cm) and sheetlike geometry.

Leighly, Karen↗
NASA NTRS1999

Seasonal-to-Interannual Variability in Antarctic Sea-Ice Dynamics, and Its Impact on Surface Fluxes and Water Mass Production

Strong seasonal and interannual signals in Antarctic bottom-water outflow remain unexplained yet are highly correlated with anomalies in net sea-ice growth in coastal polynyas. The mechanisms responsible for driving salination and replenishment and rejuvenation of the dense shelf "source" waters likely also generate pulses of bottom water outflow. The objective of this research is to investigate time-scales of variability in the dynamics of sea-ice in the Southern Ocean in order to determine the primary sites for production of dense shelf waters. We are using a merged satellite/buoy sea-ice motion data set for the period 1978-present day to compute the dynamics of opening and closing of coastal polynyas over the continental shelf. The Ocean Circulation and Climate Advanced Model (OCCAM) ocean general circulation model with coupled sea-ice dynamics is presently forced using National Center for Environmental Prediction (NCEP) data to simulate fluxes and the salination impact of the ocean shelf regions. This work is relevant in the context of measuring the influence of polar sea-ice dynamics upon polar ocean characteristics, and thereby upon global thermohaline ocean circulation. Interannual variability in simulated net freezing rate in the Southern Weddell Sea is shown for the period 1986-1993. There is a pronounced maximum of ice production in 1988 and minimum in 1991 in response to anomalies in equatorward meridional wind velocity. This follows a similar approximate 8-year interannual cycle in Sea Surface Temperature (SST) and satellite-derived ice-edge anomalies reported elsewhere as the "Antarctic Circumpolar Wave." The amplitude of interannual fluctuations in annual net ice production are about 40% of the mean value, implying significant interannual variance in brine rejection and upper ocean heat loss. Southward anomalies in wind stress induce negative anomalies in open water production, which are observed in passive microwave satellite images. Thus, cycles of enhanced poleward wind stress reduce ice growth by compacting the ice along the coastline and closing open water in leads and polynyas. Model simulations confirm that years of low ice production, such as 1991, coincide with years of lower than normal bottom water outflow. Future plans include the assimilation of satellite ice concentrations and ice drift dynamics to more accurately constrain boundary conditions in the model.

Drinkwater, Mark R.↗
DOE OSTI2026

Schwinger-Keldysh effective action for hydrodynamics with approximate symmetries

We study hydrodynamic theories with approximate symmetries in the recently developed effective action approach on the Schwinger-Keldysh contour. We employ the method of spurious symmetry transformation for small explicit symmetry-breaking parameters to systematically constrain symmetry-breaking effects in the nonequilibrium effective action for hydrodynamics. We apply our method to the hydrodynamic theory of chiral symmetry in quantum chromodynamics at finite temperature and density and its explicit breaking by quark masses. We show that the spurious symmetry and the Kubo-Martin-Schwinger relation dictate that the Ward-Takahashi identity for the axial symmetry, i.e., the partial conservation of axial vector current (PCAC) relation, contains a relaxational term proportional to the axial chemical potential, whose kinetic coefficient is at least of the second order in the quark mass. In the phase where the chiral symmetry is spontaneously broken, and the pseudo-Nambu-Goldstone pions appear as hydrodynamic variables, this relaxation effect is subleading compared to the conventional pion mass term in the PCAC relation, which is of the first order in the quark mass. On the other hand, in the chiral symmetry restored phase, we show that our relaxation term, which is of the second order in the quark mass, becomes the leading contribution to the axial charge relaxation. Therefore, the leading axial charge relaxation mechanism is parametrically different in the quark mass across a chiral phase transition.

Goldstone bosons↗
DOE OSTI2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

Optimal engine operation during a transient driving cycle is the key to achieving greater fuel economy, engine efficiency, and reduced emissions. In order to achieve continuously optimal engine operation, engine calibration methods use a combination of static correlations obtained from dynamometer tests for steady-state operating points and road and/or track performance data. As the parameter space of control variables, design variable constraints, and objective functions increases, the cost and duration for optimal calibration become prohibitively large. In order to reduce the number of dynamometer tests required for calibrating modern engines, a large-scale simulation-driven machine learning approach is presented in this work. A parallel, fast, robust, physics-based reduced-order engine simulator is used to obtain performance and emission characteristics of engines over a wide range of control parameters under various transient driving conditions (drive cycles). We scale the simulation up to 3,906 nodes of the Theta supercomputer at the Argonne Leadership Computing Facility to generate data required to train a machine learning model. The trained model is then used to predict various engine parameters of interest, and the results are compared with those predicted by the engine simulator. Our results show that a deepneural-network-based surrogate model achieves high accuracy: Pearson product-moment correlation values larger than 0.99 and mean absolute percentage error within 1.07% for various engine parameters such as exhaust temperature, exhaust pressure, nitric oxide, and engine torque. Once trained, the deep-neural-network-based surrogate model is fast for inference: it requires about 16 mu s for predicting the engine performance and emissions for a single design configuration compared with about 0.5 s per configuration with the engine simulator. Moreover, we demonstrate that transfer learning and retraining can be leveraged to incrementally retrain the surrogate model to cope with new configurations that fall outside the training data space.

deep learning↗
NASA NTRS1991

Oceanographic data analysis with NASA's SEAPAK software

The paper presents a case study of the interannual variability of vertical Ekman transport (upwelling) observed in the North Atlantic during the CZCS data collection period in order to illustrate SEAPAK's ancillary data handling functions. The study begins at the entire basin-scale for the North Atlantic and proceeds to a regional scale where much of the observed upwelling variability occurs. The analysis utilizes a variety of output types, including images, horizontal contour plots, time series, cross sections, and vertical profiles, produced on the VAX directly or by commercially available PC software packages. The SEAPAK software can be used just as effectively for global or basin-scale studies as for regional studies.

Firestone, James K.↗
NASA NTRS1947

High-Altitude Flight Cooling Investigation of a Radial Air-Cooled Engine

An investigation of the cooling of an 18-cylinder, twin-row, radial, air-cooled engine in a high-performance pursuit airplane has been conducted for variable engine and flight conditions at altitudes ranging from 5000 to 35,000 feet in order to provide a basis for predicting high-altitude cooling performance from sea-level or low altitude experimental results. The engine cooling data obtained were analyzed by the usual NACA cooling-correlation method wherein cylinder-head and cylinder-barrel temperatures are related to the pertinent engine and cooling-air variables. A theoretical analysis was made of the effect on engine cooling of the change of density of the cooling air across the engine (the compressibility effect), which becomes of increasing importance as altitude is increased. Good agreement was obtained between the results of the theoretical analysis and the experimental data.

Manganiello, Eugene J↗
NASA NTRS1981

A variable vertical resolution weather model with an explicitly resolved planetary boundary layer

A version of the fourth order weather model incorporating surface wind stress data from SEASAT A scatterometer observations is presented. The Monin-Obukhov similarity theory is used to relate winds at the top of the surface layer to surface wind stress. A reasonable approximation of surface fluxes of heat, moisture, and momentum are obtainable using this method. A Richardson number adjustment scheme based on the ideas of Chang is used to allow for turbulence effects.

Helfand, H. M.↗
DOE OSTI2021

A surrogate-model-based approach for estimating the first and second-order moments of offshore wind power

Power curve, the functional relationship that governs the process of converting a set of weather variables experienced by a wind turbine into electric power, is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input, thus ignoring the secondary, yet possibly significant effects of other environmental factors, (ii) they largely overlook the complex marine environment in which offshore turbines operate, potentially compromising their value in offshore wind energy applications, and (ii) they solely focus on the first-order properties of wind power, with little (or null) information about the variation around the mean behavior, which is important for ensuring reliable grid integration, asset health monitoring, and energy storage, among others. In light of that, this study investigates the impact of several wind-and wave-related factors on offshore wind power variability, with the ultimate goal of accurately predicting its first two moments. Further, our approach couples OpenFAST—a multi-physics wind turbine simulator—with Gaussian Process (GP) regression to reveal the underlying relationships governing offshore weather-to-power conversion. We first find that a multi-input power curve which captures the combined impact of wind speed, direction, and air density, can provide double-digit improvements, in terms of prediction accuracy, relative to univariate methods which rely on wind speed as the sole explanatory variable (e.g. the standard method of bins). Wave-related variables are found not important for predicting the average power output, but interestingly, appear to be extremely relevant in describing the fluctuation of the offshore power around its mean. Tested on real-world data collected at the New York/New Jersey bight, our proposed multi-input models demonstrate a high explanatory power in predicting the first two moments of offshore wind generation, testifying their potential value to the offshore wind industry.

17 WIND ENERGY↗
NASA NTRS1976

Sensitivity of solar-cell performance to atmospheric variables. 2: Dissimilar cells at several locations

Several solar cells having dissimilar spectral response curves and cell construction were measured at various locations in the United States to determine sensitivity of cell performance to atmospheric water vapor and turbidity. The locations selected represent a broad range of summer atmospheric conditions, from clear and dry to turbid and humid. Cell short circuit current under direct normal incidence sunlight, the intensity, water vapor and turbidity were measured. Regression equations were developed from the limited data base in order to provide a single method of prediction of cell current sensitivity to the atmospheric variables.

Klucher, T. M.↗
DOE OSTI2019

Shape-Preserved Transformation of Biological Cells into Synthetic Hydrogel Microparticles

The synthesis of materials that can mimic the mechanical, and ultimately functional, properties of biological cells can broadly impact the development of biomimetic materials, as well as engineered tissues and therapeutics. Yet, it is challenging to synthesize, for example, microparticles that share both the anisotropic shapes and the elastic properties of living cells. Here in paper, a cell-directed route to replicate cellular structures into synthetic hydrogels such as polyethylene glycol (PEG) is described. First, the internal and external surfaces of chemically fixed cells are replicated in a conformal layer of silica using a sol–gel process. The template is subsequently removed to render shape-preserved, mesoporous silica replicas. Infiltration and cross-linking of PEG precursors and dissolution of the silica result in a soft hydrogel replica of the cellular template as demonstrated using erythrocytes, HeLa, and neuronal cultured cells. The elastic modulus can be tuned over an order of magnitude (≈10–100 kPa) though with a high degree of variability. Furthermore, synthesis without removing the biotemplate results in stimuli-responsive particles that swell/deswell in response to environmental cues. Overall, this work provides a foundation to develop soft particles with nearly limitless architectural complexity derived from dynamic biological templates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Identifying quenched jets in heavy ion collisions with machine learning

Measurements of jet substructure in ultra-relativistic heavy ion collisions suggest that the jet showering process is modified by the interaction with the quark-gluon plasma. Modifications of the hard substructure of jets can be explored with modern data-driven techniques. In this study, a machine learning approach to the identification of quenched jets is designed. Jet showering processes are simulated with a jet quenching model JEWEL and a non-quenching model PYTHIA 8. Sequential substructure variables are extracted from the jet clustering history following an angular-ordered sequence and are used in the training of a neural network built on top of a long short-term memory network. We show that this approach successfully identifies the quenching effect in the presence of the large uncorrelated background of soft particles created in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Bounded motion design in the Earth zonal problem using differential algebra based normal form methods

Establishing long-term relative bounded motion between orbits in perturbed dynamics is a key challenge in astrodynamics to enable cluster flight with minimum propellant expenditure. Herein, we present an approach that allows for the design of long-term relative bounded motion considering a zonal gravitational model. Entire sets of orbits are obtained via high-order Taylor expansions of Poincarè return maps about reference fixed points. The high-order normal form algorithm is used to determine a change in expansion variables of the map into normal form space, in which the phase space behavior is circular and can be easily parameterized by action–angle coordinates. The action–angle representation of the normal form coordinates is then used to parameterize the original Poincarè return map and average it over a full phase space revolution by a path integral along the angle parameterization. As a result, the averaged nodal period and drift in the ascending node are obtained, for which the bounded motion conditions are straightforwardly imposed. Sets of highly accurate bounded orbits are obtained, extending over several thousand kilometers, and valid for decades.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

On the Solvability of a Boundary-Value Problem for a Second-Order Singular Quasilinear Equation

We obtain solvability conditions for a two-point boundary-value problem for a second-order quasilinear equation. The equation is singular with respect to the independent variable. The result is based on the properties of the Green operator of the corresponding linear problem. In particular, we prove its boundedness and obtain an upper estimate of its norm. Conditions of existence of a solution of the original problem are obtained from the solvability condition of an auxiliary operator equation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A splitting Chebyshev collocation method for Schrödinger–Poisson system

We develop a splitting Chebyshev collocation (SCC) method for the time-dependent Schrödinger–Poisson (SP) system arising from theoretical analysis of quantum plasmas. By means of splitting technique in time, the time-dependant SP system is first reduced to uncoupled Schrödinger and Poisson equations at every time step. The space variables in Schrödinger and Poisson equations are next represented by high-order Chebyshev polynomials, and the resulting system are discretized by the spectral collocation method. Finally, matrix diagonalization technique is applied to solve the fully discretized system in one dimension, two dimensions and three dimensions, respectively. The newly proposed method not only achieves spectral accuracy in space but also reduces the computer-memory requirements and the computational time in comparison with conventional solver. Numerical results confirm the spectral accuracy and efficiency of this method, and indicate that the SCC method could be an efficient alternative method for simulating the dynamics of quantum plasmas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Acceleration of diffusive molecular dynamics simulations through mean field approximation and subcycling time integration

Highlights: • Two numerical methods are presented to accelerate DMD simulations. • The methods greatly reduce the computation time without much loss of accuracy. • The accelerated DMD model is capable of simulating long-term mass transport at atomistic length scales. • Demonstrated for the propagation of an atomically sharp phase boundary over 30 seconds. - Abstract: Diffusive Molecular Dynamics (DMD) is a class of recently developed computational models for the simulation of long-term diffusive mass transport at atomistic length scales. Compared to previous atomistic models, e.g., transition state theory based accelerated molecular dynamics, DMD allows the use of larger time-step sizes, but has a higher computational complexity at each time-step due to the need to solve a nonlinear optimization problem at every time-step. This paper presents two numerical methods to accelerate DMD based simulations. First, we show that when a many-body potential function, e.g., embedded atom method (EAM), is employed, the cost of DMD is dominated by the computation of the mean of the potential function and its derivatives, which are high-dimensional random variables. To reduce the cost, we explore both first- and second-order mean field approximations. Specifically, we show that the first-order approximation, which uses a point estimate to calculate the mean, can reduce the cost by two to three orders of magnitude, but may introduce relatively large error in the solution. We show that adding an approximate second-order correction term can significantly reduce the error without much increase in computational cost. Second, we show that DMD can be significantly accelerated through subcycling time integration, as the cost of integrating the empirical diffusion equation is much lower than that of the optimization solver. To assess the DMD model and the numerical approximation methods, we present two groups of numerical experiments that simulate the diffusion of hydrogen in palladium nanoparticles. In particular, we show that the computational framework is capable of capturing the propagation of an atomically sharp phase boundary over a time window of more than 30 seconds. The effects of the proposed numerical methods on solution accuracy and computation time are also assessed quantitatively.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A general metriplectic framework with application to dissipative extended magnetohydrodynamics

General equations for conservative yet dissipative (entropy producing) extended magnetohydrodynamics are derived from two-fluid theory. Keeping all terms generates unusual cross-effects, such as thermophoresis and a current viscosity that mixes with the usual velocity viscosity. While the Poisson bracket of the ideal version of this model has already been discovered, we determine its metriplectic counterpart that describes the dissipation. This is done using a new and general thermodynamic point of view to derive dissipative brackets, a means of derivation that is natural for understanding and creating dissipative dynamics without appealing to underlying kinetic theory orderings. Finally, the formalism is used to study dissipation in the Lagrangian variable picture where, in the context of extended magnetohydrodynamics, non-local dissipative brackets naturally emerge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗