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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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Based on the idea of separation of variables, a spectral theory for the three-dimensional, stationary, isotropic transport operator in a vector space of complex-valued Borel functions results in continuous sets of regular and generalized eigenfunctions.
Rocketsonde instrumentation noise separation from stratospheric variability, discussing paired soundings based large scale discrepancies in temperature and wind observations
The method of separation of variables is shown to make turbulent correlation equations of Karman-Howarth type tractable for shear turbulence as well under the condition of neglected triple correlation. The separated dependent variable obeys an Orr-Sommerfeld equation. A new analytical method is developed using a scaling law different from the classical one due to Heisenberg and Lin and more appropriate for wall turbulent profiles. A dispersion relationship between the wave number and the separation constant which has the dimension of a frequency is derived in support of experimental observations of wave or coherent structure of wall turbulence.
A cooperative research project was initiated in 1982 to study differences in thematic mapper spectral characteristics caused by variable tillage and crop residue practices. Initial evaluations of radiometric data suggest that spectral separability of variably tilled soils can be confounded by moisture and weathering effects. Separability of bare tilled soils from those with significant amounts of corn residue is enhanced by wet conditions, but still possible under dry conditions when recent tillage operations have occurred. In addition, thematic mapper data may provide an alternative method to study the radiant energy balance at the soil surface in conjunction with variable tillage systems.
A review of acoustic fill effect was conducted using vibroacoustic models of the NASA Space Launch System Block 1B 8.4-meter Payload Fairing. Fill effect is the term used to describe how sound pressure levels (SPLs) inside of a launch vehicle’s payload cavity change when a payload is present, compared to that of an unfilled cavity. Several vibroacoustic models with various payload shapes were developed and the deviation in output from an unfilled cavity model were compared to an analytical fill effect calculation. The analytical expression for the fill effect correction factor, known as the fill factor, is published in NASA-STD-7001B. The development and validation of the NASA fill factor is discussed to provide context for this study and define important variables including the volume fill percentage and the fairing-payload separation gap. The fill factor is reviewed from two perspectives; a global perspective which defines the volume ratio with respect to the entire fairing cavity, and a local perspective which defines the volume ratio with respect to a zone of interest dependent on the payload’s height. The global perspective was considered because it allows a decoupling of the volume ratio and fairing-payload separation gap variables. Both the global and local fill factor methods have difficulty capturing low frequency SPL because of a breakdown in the underlying assumptions of a diffuse acoustic field. Spatial variation in the pressure field at low frequency showed that axially oriented standing waves may be of concern for sensitive payload components; radial variation in SPL was found to be less significant. Further, a novel secondary derivation of the theoretical fill factor is posed for future work in which the absorption characteristics of the payload and fairing surfaces are considered. This work is supported by the NASA Glenn Research Center and the Space Launch System Payload Fairing Working Group.
An approach for the analysis of atomically resolved scanning transmission electron microscopy data with multiple ferroic variants in the presence of imaging non-idealities and chemical variabilities based on a rotationally invariant variational autoencoder (rVAE) is presented. We show that an optimal local descriptor for the analysis is a sub-image centered at specific atomic units, since materials and microscope distortions preclude the use of an ideal lattice as a reference point. The applicability of unsupervised clustering and dimensionality reduction methods is explored and is shown to produce clusters dominated by chemical and microscope effects, with a large number of classes required to establish the presence of rotational variants. Comparatively, the rVAE allows extraction of the angle corresponding to the orientation of ferroic variants explicitly, enabling straightforward identification of the ferroic variants as regions with constant or smoothly changing latent variables and sharp orientational changes. This approach allows further exploration of the chemical variability by separating the rotational degrees of freedom via rVAE and searching for remaining variability in the system. The code used in this article is available at https://github.com/saimani5/ferroelectric_domains_rVAE.
The Southern Great Plains (SGP) carbon dioxide flux (CO2 flux) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), and sensible heat. The fluxes are obtained by the eddy covariance technique, which computes the flux as the mean product of the vertical wind component with CO2 and H2O densities, or estimated virtual temperature. A three-dimensional sonic anemometer is used to obtain the orthogonal wind components and the virtual (sonic) temperature. An infrared gas analyzer is used to obtain the CO2 and H2O densities. A separate sub-system also collects half-hour average measures of meteorological and soil variables from separate 4-m towers.
The paper describes a continuous variable-temperature U-shaped cold trap which can both purify vacuum-line combustion products for subsequent stable isotopic analysis and isolate the methane and ethane constituents of natural gases. The canister containing the trap is submerged in liquid nitrogen, and, as the gas cools, the gas mixture components condense sequentially according to their relative vapor pressures. After the about 12 min required for the bottom of the trap to reach the liquid-nitrogen temperature, passage of electric current through the resistance wire wrapped around the tubing covering the U-trap permits distillation of successive gas components at optimal temperatures. Data on the separation achieved for two mixtures, the first being typical vacuum-line combustion products of geochemical samples such as rocks and the second being natural gas, are presented, and the thermal behavior and power consumption are reported.
Projection micro stereolithography (PµSL) is an additive manufacturing tool that offers multiple advantages, including unparalleled resolution and throughput, but the ability to print high viscosity resin for large-scale parts is limited. One of the key challenges in PµSL is to separate a newly polymerized layer from the vat floor without damaging the part. Since the separation force scales with the printing area, the risk of damaging the part increases significantly with larger-scale systems and must be addressed. In this paper, a novel roll-to-roll, variable tensioning system is proposed to reduce the separation force during printing. A mathematical model is proposed to predict the separation force for different 2D geometries, and a set of experiments is conducted on an experimental prototype to validate the model. Finally, the effects of different separation parameters including peel rate and peel angle are discussed in detail. The results show that the proposed tensioning system reduces the separation force significantly.
The observation of photon-assisted resonant tunneling in a multiple quantum well structure composed of doped quantum wells separated by variably space superlattice energy filters is reported. Electrons confined in the quantum wells are excited to the second quantized state by intersubband absorption of incident infrared radiation and are subsequently emitted through the filters under appropriate bias conditions. This is manifested by a distinct peak, with an associated negative differential photoconductance, in the photocurrent versus bias voltage characteristic at low temperatures.
Optimization of tilt-rotor systems requires the consideration of performance at multiple design points. In the current study, an adjoint-based optimization of a tilt-rotor blade is considered. The optimization seeks to simultaneously maximize the rotorcraft figure of merit in hover and the propulsive efficiency in airplane-mode for a tilt-rotor system. The design is subject to minimum thrust constraints imposed at each design point. The rotor flowfields at each design point are cast as steady-state problems in a noninertial reference frame. Geometric design variables used in the study to control blade shape include: thickness, camber, twist, and taper represented by as many as 123 separate design variables. Performance weighting of each operational mode is considered in the formulation of the composite objective function, and a build up of increasing geometric degrees of freedom is used to isolate the impact of selected design variables. In all cases considered, the resulting designs successfully increase both the hover figure of merit and the airplane-mode propulsive efficiency for a rotor designed with classical techniques.
Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.
To examine the long-period variability of the Gulf Stream, sea level residuals relative to a 2-year mean sea level in the Gulf Stream downstream of Cape Hatteras (between 75 deg W and 60 deg W longitude) are used. Residuals, as derived from Geosat altimetry between November 1986 and December 1988, were gridded in space and time at a temporal resolution of 10 days and spatial resolution of 1/4 deg. Complex empirical orthogonal function (CEOF) analysis was applied to the data set to extract the spatially correlated signal with the original data subsampled to 1/2 deg. In addition to determining the space-time scales and propagation characterisitics of the different modes, wavenumber-frequency spectral techniques were used to separate the variability into propagating and stationary components. The CEOF technique applied to the data set indicated that the first four CEOF modes accounted for 60% of the variability and were found to be above the noise leve 99% of the time. CEOF 1 was associated with westward propagation at 5 km/d at a wavelength of 2000 km and eastward propagation at 1-2 km/d centered at a 500-km wavelength. This first CEOF is in good agreement with thin-jet equivalent barotropic models which predict westward propagation for wavelengths greater than 1130 km. A deflection of the wavelike pattern at 65 deg W also indicates a possible topographic effect. A simple scaling of the effect of topography indicates that for length scales longer than the internal Rossby radius of deformation, the topographic term is at least of the same order of magnitude as the beta effect. The second CEOF was more broadbanded in wavenumber space, with eastward propagation occurring in a wavenumber-frequency band between 300 and 1400 km and 0.5 and 2.0 cycles/yr. The third CEOF is similar in structure to the first, but with less energy. CEOF 4 was clearly identifiable with higher frequencies than the first three with westward propagation at 4 km/d. The spatial location of this mode along with the westward propagation indicates possible influences from eddy-stream interactions. Thus topography, Rossby wave dynamics and eddy-stream interactions all appear to have a significant role in determining the space-time scales and propagation properties of the long-period response of sea level in the Gulf Stream.
Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited 10by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective 15 self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.
Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving partial differential equations (PDEs) in scientific computing. While PINNs typically use multilayer perceptrons (MLPs) as their underlying architecture, recent advancements have explored alternative neural network structures. One such innovation is the Kolmogorov–Arnold Network (KAN), which has demonstrated benefits over traditional MLPs, including faster neural scaling and better interpretability. The application of KANs to physics-informed learning has led to the development of Physics-Informed KANs (PIKANs), enabling the use of KANs to solve PDEs. However, despite their advantages, KANs often suffer from slower training speeds, particularly in higher-dimensional problems where the number of collocation points grows exponentially with the dimensionality of the system. To address this challenge, we introduce Separable Physics-Informed Kolmogorov–Arnold Networks (SPIKANs). This novel architecture applies the principle of separation of variables to PIKANs, decomposing the problem such that each dimension is handled by an individual KAN. This approach drastically reduces the computational complexity of training without sacrificing accuracy, facilitating their application to higher-dimensional PDEs. Through a series of benchmark problems, we demonstrate the effectiveness of SPIKANs, showcasing their superior scalability and performance compared to PIKANs and highlighting their potential for solving complex, high-dimensional PDEs in scientific computing.
A high order finite difference method with improved accuracy and stability properties for computational aeroacoustics (CAA) at low Mach numbers is proposed. The Euler equations are split into a conservative and a symmetric non- conservative portion to allow the derivation of a generalized energy estimate. Since the symmetrization is based on entropy variables, that splitting of the flux derivatives is referred to as entropy splitting. Its discretization by high order central differences was found to need less numerical dissipation than conventional conservative schemes. Owing to the large disparity of acoustic and stagnation quantities in low Mach number aeroacoustics, the split Euler equations are formulated in perturbation form. The unknowns are the small changes of the conservative variables with respect to their large stagnation values. All nonlinearities and the conservation form of the conservative portion of the split flux derivatives can be retained, while cancellation errors are avoided with its discretization opposed to the conventional conservative form. The finite difference method is third-order accurate at the boundary and the conventional central sixth-order accurate stencil in the interior. The difference operator satisfies the summation by parts property analogous to the integration by parts in the continuous energy estimate. Thus, strict stability of the difference method follows automatically. Spurious high frequency oscillations are suppressed by a characteristic-based filter similar to but without limiter. The time derivative is approximated by a 4-stage low-storage second-order explicit Runge-Kutta method. The method has been applied to simulate vortex sound at low Mach numbers. We consider the Kirchhoff vortex, which is an elliptical patch of constant vorticity rotating with constant angular frequency in irrotational flow. The acoustic pressure generated by the Kirchhoff vortex is governed by the 2D Helmholtz equation, which can be solved analytically using separation of variables.
Thermal-fatigue crack-growth characteristics of notched- and unnotched-disk specimens of A-286, Discaloy, hot-cold worked 16-25-6, and overaged 16-25-6 were experimentally studied. Separately controlled variables were total strain range (0.0043 to 0.0079 in./in.), maximum cycle temperature (1300 and 1100 F), and hold time at maximum temperature (O and 5 min). A limited number of mechanical, push-pull, constant-strain cycle tests at room temperature were made using notched and un-notched bars of the same materials. In these tests the number of cycles to failure as well as the variation of load change with accumulated cycles was measured, and the effects of mean stress were observed. Constant-strain-range mechanical-fatigue tests at room temperature revealed notched-bar fatigue life to be strongly influenced by mean stress. For a specific strain range, the longest fatigue life was always found to be associated with the least-tensile (or most compressive) mean stress. By defining thermal-fatigue life as the number of cycles required to produce a crack area of 6000 square mils, the relative thermal-fatigue resistances of the test materials were established. Notched-disk specimens of A-286 and Discaloy steels exhibited longer fatigue lives than either hot-cold worked or overaged 16-25-6. On the other hand, unnotched-disk specimens of Discaloy and hot-cold worked 16-25-6 had longer lives than A-286 and overaged 16-25-6. Separation of the crack-growth data into microstage and macrostage periods revealed that the macrostage period accounted for the greatest part of the difference among materials when tested in the notched configuration, while the microstage was largely responsible for the differences encountered in unnotched disks.
Proper generalized decomposition (PGD) can be described as a numerical extension of separation of variables and thus be employed as a solution technique for multi-dimensional problems, where dimensions should be understood in the phase-space context of the governing law at hand. This paper presents a PGD approach on efficiently solving problems involving multigroup neutron diffusion. Two PGD approaches are described: space-only and space-energy decompositions. Numerical results include 2-D and 3-D examples with two-, seven-, and 145-group structures. The PGD solutions are compared against traditional multi-dimensional finite element discretization. For few-group problems, both PGD approaches prove effective for mildly heterogeneous geometries, but showed reduced performance with increasing heterogeneity. The space-energy representation was found to be slower than the space-only approach for two-group problems, but proved more effective for seven-group problems. For even larger numbers of groups, the space-energy PGD decomposition was very effective at reducing the computational time.