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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Radiant heat transfer between nongray directional surfaces.

Real surface property effects on local and overall heat transfer are studied for a simple system of interacting opaque surfaces. Wavelength, temperature and directional dependence of surface properties is included in the analysis for equal and unequal temperature specularly reflecting surfaces. Tungsten is employed as a representative metal and Roberts' model is used to describe the wavelength and temperature dependence of its optical parameters. The relationships of electromagnetic theory are employed to describe the directional dependence of spectral properties. Numerical results establish that gray direction independent property analysis adequately predicts the general trends of real surface analysis. The results also establish that spectral and temperature dependence of surface properties influences radiant heat transfer to a greater degree than does directional dependence of properties. Property models which adequately account for the nongray character of engineering surfaces while neglecting directional dependence of properties can provide heat transfer results of acceptable engineering accuracy.

Fischer, W. D.↗
DOE OSTI2022

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Initial On-Orbit Spectral Calibration of the PACE Ocean Color Instrument

The NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission Project Science Team has used Ocean Color Instrument (OCI) measurements of Fraunhofer lines in spectra of sunlight reflected by the solar diffuser and measurements of atmospheric absorption bands in cloudtop and ocean spectra to characterize the spectral calibration of OCI on orbit. Multiple lines have been analyzed for both the ultraviolet to visible (UVVIS, 340−607 nm) and visible to near-infrared (VISNIR, 597−897 nm) grating spectrographs. The spectrographs yield hyperspectral observations with 5 nm bandwidths and 0.625 nm sampling intervals. The on-orbit observations have been compared with the prelaunch spectral calibration of OCI performed by the Goddard Laser for Absolute Measurement of Radiance (GLAMR) during thermal vacuum testing to track any changes in the calibration since launch. The calibration analyzed the line positions and strengths for the Fraunhofer lines for each spectrograph by comparing the solar spectra measured by OCI with predicted solar spectra derived from the solar reference spectrum and the BRDF of the solar diffuser, convolved with the OCI relative spectral responses. The calibration also compared the line positions of the atmospheric absorption bands with the model transmissions used by the PACE Project. The line position comparisons show that the root mean square (RMS) spectral difference between the measured and predicted spectra is 0.15 nm, the average spectral shift is 0.062 nm, and the residual spectral dispersion over the wavelength range of the Fraunhofer lines is 0.17 nm. All three estimates of the spectral accuracy of OCI meet the instrument functional requirement of a spectral accuracy of 0.5 nm and are well within the 0.625 nm sampling interval of the data. The line strength comparisons between measured and predicted spectra are essentially the same. These results show that the spectral calibration of OCI on orbit has not drifted since the prelaunch calibration of OCI by GLAMR and that the on-orbit spectral calibration of OCI is stable over time. These results also provide a baseline for monitoring the future spectral performance of OCI on orbit.

Radiometric Calibration↗
DOE OSTI2024

Standard model Higgs inflation supplemented by minimal dark matter

Renormalization group analysis with the present measurements of the top quark mass m t = 172.69 ± 0.30 GeV [1] indicates that the Standard Model (SM) Higgs potential becomes unstable at energy scales ∼ 10 10 GeV . This may be interpreted as hinting at new particles at high energy. The minimal extension of the SM that can avoid this instability while leaving the SM Higgs as the sole scalar particle of the theory is obtained by adding suitable fermions to the SM. These fermions are good dark matter candidates and the model is known as the minimal dark matter model. We revisit the inflationary scenario based on the minimal dark matter model, taking into account updated parameter constraints and recent understanding of reheating dynamics. We explore the model with different values of the right-handed neutrino mass and find that the cosmological prediction is insensitive to such details. We obtained a spectral index of the cosmic microwave background n s = 0.9672 and a tensor-to-scalar ratio r = 0.0031 as a robust prediction of this scenario. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
NASA NTRS1990

Predictions of launch-induced, near-field acoustics of clustered rocket engines using a scaling approach

A scaling technique is proposed for the prediction of clustered rocket engine, near-field acoustics. Scaling equations predict the mean square pressures and power spectral density (PSD) of an unknown vehicle, using near-field measurements from a similar vehicle. Separation of nonhomogeneous Shuttle acoustics into Space Shuttle Main Engine (SSME) and Solid Rocket Booster (SRB) component acoustics forms the basis for verification of the proposed scaling equations. Three separate models, based on the total Shuttle PSD, a three-SSME vehicle PSD, and a two-SRB vehicle PSD, are recommended for the Advanced Launch System (ALS) near-field predictions. Acoustic efficiency, equivalent diameter of closely/widely spaced clustered engines, and the use of a distance-dependent spectra for scaling ALS vehicle near-field acoustics are briefly addressed.

Sepcenko, Valentin↗
NASA NTRS2008

Spectral Attenuation of Sound in Dilute Suspensions with Nonlinear Particle Relaxation

Previous studies on the sound attenuation in particle-laden flows under Stokesian drag and conduction-controlled heat transfer have been extended to accommodate the nonlinear drag and heat transfer. It has been shown that for large particle-to-fluid density ratio, the particle Reynolds number bears a cubic relationship with (omega(tau))(sub d) (where omega is the circular frequency and (tau)(sub d) the Stokesian particle relaxation time). This dependence leads to the existence of a peak value in the linear absorption coefficient occurring at a finite value of(omega(tau))(sub d). Comparison of the predictions with the test data for the spectral attenuation of sound with water injection in a perfectly expanded supersonic air jet shows a satisfactory trend of the theory accounting for nonlinear particle relaxation processes.

Kandula, Max↗
NASA NTRS2003

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

Kundu, Prasun K.↗
NASA NTRS2010

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗
DOE OSTI2025

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗
NASA NTRS1975

The GSFC 20 and 30 GHz millimeter wave propagation experiment

The Goddard Space Flight Center Millimeter Wave Experiment (MWE) aboard ATS-6, designed to evaluate the propagation characteristics of earth-space communications links at 20 and 30 GHz, is outlined, and the major results to date are presented. The 20 and 30 GHz transmitters operate through spot beam or continental coverage antenna systems. The transmitted signals consist of 9 tones spaced out to 1440 MHz. A communications link 6 GHz up and 20 or 30 GHz down is provided. Attenuation ratio measurements between the 20 and 30 GHz links indicate values higher than those predicted. Clear sky scintillations have been observed with spectral components up to about 50 Hz. Observations of rain depolarization indicate that attenuation effects predominate over depolarization effects in frequency re-use communications systems in the 20 GHz region. Various methods of predicting path attenuation are under investigation.

Ippolito, L. J.↗
NASA NTRS2008

Spectral Attenuation of Sound in Dilute Suspensions with Nonlinear Particle Relaxation

Theoretical studies on the dissipation and dispersion of sound in two-phase suspensions have been briefly reviewed. Previous studies on the sound attenuation in particle-laden flows under Stokesian drag and conduction-controlled heat transfer have been extended to accommodate the nonlinear drag and heat transfer. It has been shown that for large particle-to-fluid density ratio, the particle Reynolds number bears a cubic relationship with Omega Tau(sub d) (where Omega is the circular frequency and Tau(sub d) the Stokesian particle relaxation time). This dependence leads to the existence of a peak value in the linear absorption coefficient occurring at a finite value Omega Tau (sub d). Comparison of the predictions with the test data for the spectral attenuation of sound with water injection in a perfectly expanded supersonic air jet shows a satisfactory trend of the theory accounting for nonlinear particle relaxation processes.

Kandula, M.↗
DOE OSTI2020

Frequency Analysis of Solar PV Power to Enable Optimal Building Load Control

In this paper, we present a flexibility estimation mechanism for buildings’ thermostatically controlled loads (TCLs) to enable the distribution level consumption of the majority of solar photovoltaic (PV) generation by local building TCLs. The local consumption of PV generation provides several advantages to the grid operation as well as the consumers, such as reducing the stress on the distribution network, minimizing voltage fluctuations and two-way power flows in the distribution network, and reducing the required battery storage capacity for PV integration. This would result in increasing the solar PV generation penetration levels. The aims of this study are twofold. First, spectral (frequency) analyses of solar PV power generation together with the power consumption of multiple building TCLs (such as heating, ventilation, and air conditioning (HVAC) systems, water heaters, and refrigerators) are performed. These analyses define the bandwidth over which these TCLs can operate and also describe the PV generation frequency bandwidth. Such spectral analyses, in frequency domain, can help identify the flexible components of PV generation that can be consumed by the various TCLs through optimal building load utilization. Second, a quadratic optimization problem based on model predictive control is formulated to allow consuming most of the low and medium frequency content of the PV power locally by building TCLs, while maintaining occupants’ comfort and TCLs’ physical constraints. The solution to the proposed optimization problem is achieved using optimal control strategies. Numerical results show that most of the low and medium frequency content of the PV generation can be consumed locally by building TCLs. The remaining high-frequency content of the PV generation can then be stored/offset using energy storage systems.

14 SOLAR ENERGY↗
NASA NTRS1986

Environmental processes and spectral reflectance characteristics associated with soil erosion in desert fringe regions

Two Thematic Mapper (TM) scenes were acquired. A scene was acquired for the Bahariya, Egypt field area, and one was acquired covering the Okavango Delta site. Investigations at the northwest Botswana study sites have concentrated upon a system of large linear (alab) dunes possessing an average wavelength of 2 kilometers and an east-west orientation. These dunes exist to the north and west of the Okavango Swamp, the pseudodeltaic end-sink of the internal Okavango-Cubango-Cuito drainage network. One archival scene and two TM acquisitions are on order, but at present no TM data were acquired for the Tombouctou/Azaouad Dunes, Mali. The three areas taken together comprise an environmental series ranging from hyperarid to semi-arid, with desertization processes operational or incipient in each. The long range goal is to predict normal seasonal variations, so that aperiodic spectral changes resulting from soil erosion, vegetation damage, and associated surface processes would be distinguishable as departures from the norm.

Jacobberger, P. A.↗
NASA NTRS2021

Contact with Bennu! Flight Performance Versus Prediction of OSIRIS-REx TAG Sample Collection

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission collected a sample from the surface of the near-Earth asteroid (101955) Bennu in late 2020. Bennu challenged the team with a surface that was much rockier than expected, resulting in modifications to the prelaunch design of the Touch And Go (TAG) sequence. Following enhancements in onboard trajectory correction, ground-based navigation, and maneuver execution error modeling, the spacecraft was delivered to the chosen TAG site within 1 m of the target, and a sample was successfully collected on the first attempt. This paper provides a comprehensive description of all flight dynamics aspects of TAG trajectory planning and execution. It also describes hazard map generation and how that combined with error analysis results to predict the probability of safe contact before TAG and the onboard wave-off determination during TAG.

Kevin E Berry↗
DOE OSTI2026

Efficient Measurement-Driven Eigenenergy Estimation with Classical Shadows

Quantum algorithms exploiting real-time evolution under a target Hamiltonian have demonstrated remarkable efficiency in extracting key spectral information. However, the broader potential of these methods, particularly beyond ground-state calculations, is underexplored. In this work, we introduce the framework of multiobservable dynamic mode decomposition (MODMD), which combines the observable dynamic mode decomposition (DMD), a measurement-driven eigensolver tailored for near-term implementation, with classical shadow tomography. MODMD leverages random scrambling in the classical shadow technique to construct, with exponentially reduced resource requirements, a signal subspace that encodes rich spectral information. Notably, we replace typical Hadamard-test circuits with a protocol designed to predict low-rank observables, thereby broadening the use of classical shadow tomography for predicting many low-rank observables. We establish theoretical guarantees on the spectral approximation from MODMD, taking into account distinct sources of error. In the ideal case, we prove that the spectral error scales as exp (−Δ⁢𝐸⁢𝑡 max ), where Δ⁢𝐸 is the Hamiltonian spectral gap and 𝑡 max is the maximal simulation time. This analysis provides a rigorous justification of the rapid convergence observed across simulations. To demonstrate the utility of our framework, we consider its application to fundamental tasks, such as determining the low-lying, i.e., ground or excited, energies of representative many-body systems. Our work paves the path for efficient designs of measurement-driven algorithms on near-term and early fault-tolerant quantum devices.

quantum algorithms & computation↗
NASA NTRS1974

A filter spectrometer concept for facsimile cameras

A concept which utilizes interference filters and photodetector arrays to integrate spectrometry with the basic imagery function of a facsimile camera is described and analyzed. The analysis considers spectral resolution, instantaneous field of view, spectral range, and signal-to-noise ratio. Specific performance predictions for the Martian environment, the Viking facsimile camera design parameters, and a signal-to-noise ratio for each spectral band equal to or greater than 256 indicate the feasibility of obtaining a spectral resolution of 0.01 micrometers with an instantaneous field of view of about 0.1 deg in the 0.425 micrometers to 1.025 micrometers range using silicon photodetectors. A spectral resolution of 0.05 micrometers with an instantaneous field of view of about 0.6 deg in the 1.0 to 2.7 micrometers range using lead sulfide photodetectors is also feasible.

Jobson, D. J.↗
NASA NTRS1975

Experimental evaluation of trailing edge and incidence fluctuation noise theories

Tests were conducted to evaluate conflicting theories for trailing edge noise and for incidence fluctuation noise. A flat-plate airfoil with flush-mounted surface pressure transducers was tested in an anechoic wind tunnel at velocities from 31.5 to 177 m/sec and nominal 4 and 6% grid-generated turbulence levels. In one series of runs, the airfoil was faired into the tunnel nozzle and extended beyond the nozzle lip for studies of trailing edge noise without a leading edge and with flow on only one side. Such noise was found to vary with velocity to the fifth power and turbulence level squared as predicted by Ffowcs Williams and Hall (1970) and by Chase (1972). Power spectral density at high frequencies decayed approximately inversely with frequency to the 10/3 power as predicted by Chase. The data were poorly predicted by Hayden's correlation (1969, 1972).

Fink, M. R.↗
NASA NTRS2004

Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

Srivastava, Ashok N.↗