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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Development of Closed-Loop Simulation Methods for a Next-Generation Terminal Area Automation System

A next-generation air traffic decision support tool, known as the Active Final Approach Spacing Tool (aFAST), will generate heading, speed and altitude commands to achieve more precise separation of aircraft in the terminal area. The techniques used to analyze the performance of earlier generation decision support tools are not adequate to analyze the performance of aFAST. This paper summarizes the development of a new and innovative fully closed-loop testing method for aFAST. This method, called trajectory feedback testing, closes each aircraft's control loop inside of the aFAST scheduling algorithm. Validation of trajectory feedback testing by examination of the variation of aircraft time-of-arrival predictions between schedule updates and the variation of aircraft excess separation distances between simulation runs is presented.

Robinson, John E., III↗
NASA NTRS2005

Weak-signal Phase Calibration Strategies for Large DSN Arrays

The NASA Deep Space Network (DSN) is studying arrays of large numbers of small, mass-produced radio antennas as a cost-effective way to increase downlink sensitivity and data rates for future missions. An important issue for the operation of large arrays is the accuracy with which signals from hundreds of small antennas can be combined. This is particularly true at Ka band (32 GHz) where atmospheric phase variations can be large and rapidly changing. A number of algorithms exist to correct the phases of signals from individual antennas in the case where a spacecraft signal provides a useful signal-to-noise ratio (SNR) on time scales shorter than the atmospheric coherence time. However, for very weak spacecraft signals it will be necessary to rely on background natural radio sources to maintain array phasing. Very weak signals could result from a spacecraft emergency or by design, such as direct-to-Earth data transmissions from distant planetary atmospheric or surface probes using only low gain antennas. This paper considers the parameter space where external real-time phase calibration will be necessary, and what this requires in terms of array configuration and signal processing. The inherent limitations of this technique are also discussed.

interferometry↗
NASA NTRS2016

Coupled Retrieval of Aerosol Properties and Surface Reflection Using the Airborne Multi-Angle SpectroPolarimetric Imager (AirMSPI)

The Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 10 km and is observed from 9 view angles between ±67° off of nadir. We have developed an efficient and flexible code that uses the information content of AirMSPI data for a coupled retrieval of aerosol properties and surface reflection. The retrieval was built based on the multi-pixel optimization concept, with the use of a hybrid radiative transfer model that combines the Markov Chain and adding/doubling methods. The convergence and robustness of our algorithm is ensured by applying constraints on (a) the spectral variation of the Bidirectional Polarization Distribution Function (BPDF) and angular shape of the Bidirectional Reflectance Distribution Function (BRDF); (b) the spectral variation of aerosol optical properties; and (c) the spatial variation of aerosol parameters across neighboring image pixels. Our retrieval approach has been tested using over 20 AirMSPI datasets having low to moderately high aerosol loadings (~0.02<AOD550-nm<~0.45) and acquired during several field campaigns. Results are compared with AERONET aerosol reference data. We also explore the benefits of AirMSPI’s ultraviolet and polarimetric bands as well as the use of multiple view angles.

Xu, Feng↗
NASA NTRS1975

Fixed-range optimum trajectories for short-haul aircraft

An algorithm, based on the energy-state method, is derived for calculating optimum trajectories with a range constraint. The basis of the algorithm is the assumption that optimum trajectories consist of, at most, three segments: an increasing energy segment (climb); a constant energy segment (cruise); and a decreasing energy segment (descent). This assumption allows energy to be used as the independent variable in the increasing and decreasing energy segments, thereby eliminating the integration of a separate adjoint differential equation and simplifying the calculus of variations problem to one requiring only pointwise extremization of algebraic functions. The algorithm is used to compute minimum fuel, minimum time, and minimum direct-operating-cost trajectories, with range as a parameter, for an in-service CTOL aircraft and for an advanced STOL aircraft. For the CTOL aircraft and the minimum-fuel performance function, the optimum controls, consisting of air-speed and engine power setting, are continuous functions of the energy in both climb and descent as well as near the maximum or cruise energy. This is also true for the STOL aircraft except in the descent where at one energy level a nearly constant energy dive segment occurs, yielding a discontinuity in the airspeed at that energy. The reason for this segment appears to be the relatively high fuel flow at idle power of the engines used by this STOL aircraft. Use of a simplified trajectory which eliminates the dive increases the fuel consumption of the total descent trajectory by about 10 percent and the time to fly the descent by about 19 percent compared to the optimum.

Erzberger, H.↗
DOE OSTI2020

K-Spin Hamiltonian for Quantum-Resolvable Markov Decision Processes

The Markov decision process is the mathematical formalization underlying the modern field of reinforcement learning when transition and reward functions are unknown. We derive a pseudo-Boolean cost function that is equivalent to a K-spin Hamiltonian representation of the discrete, finite, discounted Markov decision process with infinite horizon. This K-spin Hamiltonian furnishes a starting point from which to solve for an optimal policy using heuristic quantum algorithms such as adiabatic quantum annealing and the quantum approximate optimization algorithm on near-term quantum hardware. In arguing that the variational minimization of our Hamiltonian is approximately equivalent to the Bellman optimality condition for a prevalent class of environments we establish an interesting analogy with classical field theory. Along with proof-of-concept calculations to corroborate our formulation by simulated and quantum annealing against classical Q-Learning, we analyze the scaling of physical resources required to solve our Hamiltonian on quantum hardware.

Hamiltonian↗
DOE OSTI2021

Developing High-Resolution Constrained Variational Analysis of Vertical Velocity and Advective Tendencies within the Range of ARM Scanning Radars at the SGP

Research progress has been made in two areas. One is about the incorporation of the ARM variationally constrained objective analysis method into the WRF GSI data assimilation system. The other is the development of high resolution ARM data and its applications. Specially, we developed a new data assimilation algorithm by adding dynamical constraints to the WRF GSI data assimilation system using hybrid ensemble variational system to derive 3-D fields of atmospheric dynamics and thermodynamics over the ARM SGP sites. We also developed 4x4 km high-resolution constrained variational analysis data over the SGP during the PECAN and made them available to the community. Details are in the attached report.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Temporal and spatial variability of the tropical radiation budget from ERBS measurements (March 1985 to February 1986)

The diurnal and regional variations of the top-of-atmosphere radiation budget in the tropics are examined and the relative importance of these variations are assessed. The variations of the radiation components with scene type and the radiative effects of clouds are investigated. The LW emission shows the strongest diurnal variation over clear desert and land scenes, with domain-averaged diurnal ranges of approximately 50 W/sq m and 35 W/sq m, respectively. The LW emission over clear and tropical oceans show a small diurnal range of less than 1 W/sq m. A bias in the ERBE scene ID algorithm against clear tropical scenes at night is evident in the LW diurnal variation results for clear scenes. The effect of tropical water vapor resulting in low LW emission to space is diagnosed as the principal source of uncertainty in scene identification at night. Regional cloud forcing results show a strong dependence of net forcing on cloud type. While high cirrus clouds largely contribute to a small positive net forcing, low stratiform clouds primarily account for a large negative net forcing.

Chang, T. Y.↗
DOE OSTI2024

Sensitivity of modelled passive margin stratigraphy to variations in sea level, sediment supply and subsidence

Abstract We produced a 10 Myr synthetic stratigraphic section using a forward stratigraphic model that generates marine deltaic stratigraphy over geological timescales. We recursively fit the model using a Bayesian inversion algorithm to test: (1) if it could be accurately reconstructed; (2) if the parameters used to create it could be recovered; and (3) the sensitivity of the model output to given model parameters and the attendant physical processes. The original synthetic stratigraphic section was produced with cyclical sea‐level variations of 40 and 30 m with 2.4 and 10 Myr periods respectively. Sediment was also supplied cyclically, in 2.4 and 10 Myr cycles with amplitudes of 30 and 80 tons/100 kyr, respectively, varying from a mean of 232 tons/100 kyr. Parameter values were sampled to fit the model using a Markov chain Monte Carlo algorithm, resulting in a ±5 m (1σ) variation between the experimental output and the original. Sea level varied by ±7 m (1σ) within the posterior distribution of parameters. As a result, both the 10 Myr and 2.4 Myr sea‐level cycles could be extracted from the original output. The variation in sediment supply was approximately ±38 tons/100 kyr (1σ) and, as a result, only the larger long‐term supply variations could be accurately recovered in refitting the model. The variation in thermal, flexural and total subsidence across those parameter sets is less than ±10 m (1σ). The original section experienced 150 m of total subsidence at the depocentre. Our results demonstrate the distinct and interpretable imprint of sea level and subsidence on continental margin stratigraphy can be quantified. Moreover, we conclude that sea‐level change produces a defined effect on the geometries of stratigraphic architecture, and that techniques applied for the purpose of delineating sea‐level variation from continental margin strata have a well‐founded conceptual basis.

Schmelz, William J.↗
DOE OSTI2021

Optimization-based algorithms for nonlinear mechanics and frictional contact

An optimization-based strategy for solving nonlinear mechanics problems is proposed. In contrast to typical nonlinear equation solver algorithms that aim to find zeros in the residual force function, we minimize an energy (or energy-like) function to encourage solutions which are locally stable equilibria. These smooth and potentially non-convex objective functions are minimized using a preconditioned conjugate-gradient trust-region algorithm. Contact is formulated as an inequality constrained minimization problem, and is solved with an augmented Lagrangian algorithm. Friction is included in the approach via a regularized quasi-potential energy, and other dissipative behavior is included through the use of variational constitutive updates. Finally, to accelerate convergence rates for the Lagrange multipliers, we propose a novel multiplier update algorithm utilizing the Fischer-Burmeister function, and demonstrate super-linear solver convergence for some applications.

42 ENGINEERING↗
DOE OSTI2024

Adaptive Quantum Generative Training using an Unbounded Loss Function

We propose a generative quantum learning algorithm using the Adaptive Derivative-Assembled Problem Tailored ansatz (ADAPT) framework in which the loss function to be minimized is the maximal quantum Rényi divergence of order two, an unbounded function that mitigates barren plateaus which inhibit training variational circuits. We benchmark this method against other state-of-the-art adaptive algorithms by learning random two-local thermal states. We perform numerical experiments of up to 12 qubits comparing our method learning algorithms that use linear objective functions and show that Rényi-ADAPT is capable of constructing shallow quantum circuits competitive with existing methods, while the gradients remain favorable resulting from the maximal Rényi divergence loss function.

quantum algorithms, quantum machine learning, quan↗
DOE OSTI2025

Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems

Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Structure optimization with stochastic density functional theory

Linear-scaling techniques for Kohn–Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden–Fletcher–Goldfarb–Shanno algorithm. In conclusion, we further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

An attitude reorientation algorithm for the Galileo spacecraft

This paper presents an onboard closed loop attitude reorientation algorithm for a dual-spin spacecraft, Galileo. The basic concept for the design uses the despun stator as a reference and fires a sequence of fixed duration thruster pulses to precess the angular momentum vector to its commanded orientation. The error signals used to despin the stator and to perform the turn are derived from the stator error quaternion which is computed using gyro outputs. Constraints considered in the design include gyro rate saturation, plume impingement effects, system parameter variations, as well as software reliability and flexibility. The performance of the algorithm was predicted by analysis and confirmed by computer simulation results. It was concluded that a reorientation accuracy of better than 1 milliradian with a nutation angle of less than 1 degree during the turn can be achieved.

Lin, H.-S.↗
NASA NTRS1988

Patched-grid computations of high-speed inlet flows

Two implicit algorithms for the compressible Navier-Stokes equations are applied to the computation of high-speed inlet flows typical of those which are encountered on propulsion systems of advanced hypersonic vehicles. A patched grid formulation is used to treat accurately the blunt cowl interaction with the forebody compression field and efficiently treat variations in inlet geometry downstream of the inlet entrance. Results from the two algorithms, each based on an upwind-biased spatial differencing approach for the convective and pressure terms within a flux-difference-splitting framework, are compared with experimental results for both inlets, and reasonable agreement is found.

Thomas, J. L.↗
NASA NTRS1983

Investigation of radiometric properties of the LANDSAT-4 multispectral scanner

The radiometric data quality of the LANDSAT 4 multispectral scanner (MSS) was examined using several LANDSAT 4 frames. It was found that LANDSAT 4 MSS produces high-quality data of the caliber experienced with previous LANDSATS. For example, the detector equalization procedure worked well, leaving a residual banding effect of about 0.3 digital counts RMS, close to the theoretical minimum value of quantization error. Nevertheless, artifacts of the data were found, two of which were not experienced in previous MSS data. A low-level coherent noise effect was observed in all bands, with a magnitude of about 0.5 digital counts and a frequency of approximately 28 KHz (representing a wavelength of about 3.6 pixels); a substantial increase in processing complexity would be required to reduce this artifact in the data. Also, a substantial scan-length variation (of up to six pixels) was noted in MSS data when the TM sensor was operating; the LANDSAT 4 correction algorithms being applied routinely by the EROS Data Center to produce a p-type data should remove most of this variation. Between-satellite calibrations were examined in paired LANDSAT 3 and LANDSAT 4 MSS data sets, which were closely matched in acquisition time and place. Radiometric comparisons showed that all bands were highly linear in digital counts, and a well-determined linear transformation between the MSS's was established.

Malila, W. A.↗
NASA NTRS2011

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Davis, Bruce↗
NASA NTRS2012

Greenhouse Gas Concentration Data Recovery Algorithm for a Low Cost, Laser Heterodyne Radiometer

The goal of a coordinated effort between groups at GWU and NASA GSFC is the development of a low-cost, global, surface instrument network that continuously monitors three key carbon cycle gases in the atmospheric column: carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), as well as oxygen (O2) for atmospheric pressure profiles. The network will implement a low-cost, miniaturized, laser heterodyne radiometer (mini-LHR) that has recently been developed at NASA Goddard Space Flight Center. This mini-LHR is designed to operate in tandem with the passive aerosol sensor currently used in AERONET (a well established network of more than 450 ground aerosol monitoring instruments worldwide), and could be rapidly deployed into this established global network. Laser heterodyne radiometry is a well-established technique for detecting weak signals that was adapted from radio receiver technology. Here, a weak light signal, that has undergone absorption by atmospheric components, is mixed with light from a distributed feedback (DFB) telecommunications laser on a single-mode optical fiber. The RF component of the signal is detected on a fast photoreceiver. Scanning the laser through an absorption feature in the infrared, results in a scanned heterodyne signal io the RF. Deconvolution of this signal through the retrieval algorithm allows for the extraction of altitude contributions to the column signal. The retrieval algorithm is based on a spectral simulation program, SpecSyn, developed at GWU for high-resolution infrared spectroscopies. Variations io pressure, temperature, composition, and refractive index through the atmosphere; that are all functions of latitude, longitude, time of day, altitude, etc.; are modeled using algorithms developed in the MODTRAN program developed in part by the US Air Force Research Laboratory. In these calculations the atmosphere is modeled as a series of spherically symmetric shells with boundaries specified at defined altitudes. Temperature, pressure, and species mixing ratios are defined at these boundaries. Between the boundaries, temperature is assumed to vary linearly with altitude while pressure (and thus gas density) vary exponentially. The observed spectrum at the LHR instrument will be the integration of the contributions along this light path. For any absorption measurement the signal at a particular spectral frequency is a linear combination of spectral line contributions from several species. For each species that might absorb in a spectral region, we have pre-calculated its contribution as a function of temperature and pressure. The integrated path absorption spectrum can then by calculated using the initial sun angle (from location, date, and time) and assumptions about pressure and temperature profiles from an atmospheric model. The modeled spectrum is iterated to match the experimental observation using standard multilinear regression techniques. In addition to the layer concentrations, the numerical technique also provides uncertainty estimates for these quantities as well as dependencies on assumptions inherent in the atmospheric models.

Miller, J. Houston↗
NASA NTRS1978

Investigation of new techniques for aircraft navigation using the omega navigation

An OMEGA navigation receiver with a microprocessor as the computational component was investigated. A version of the INTEL 4004 microprocessor macroassembler suitable for use on the CDC-6600 system and development of a FORTRAN IV simulator program for the microprocessor was developed. Supporting studies included development and evaluation of navigation algorithms to generate relative position information from OMEGA VLF phase measurements. Simulation studies were used to evaluate assumptions made in developing a navigation equation in OMEGA Line of Position (LOP) coordinates. Included in the navigation algorithms was a procedure for calculating a position in latitude/longitude given an OMEGA LOP fix. Implementation of a digital phase locked loop (DPLL) was evaluated on the basic of phase response characteristics over a range of input phase variations. Included also is an analytical evaluation on the basis of error probability of an algorithm for automatic time synchronization of the receiver to the OMEGA broadcast format. The use of actual OMEGA phase data and published propagation prediction corrections to determine phase velocity estimates was discussed.

Baxa, E. G., Jr.↗