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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
DOE OSTI2022

Flow Loop Study of ECT-Based Volume Fraction Monitoring in Oil–Water Two-Phase Flows

Measurement of phase volume fractions in water-containing multiphase flows is necessary for the optimization of a host of industrial flow processes. Many water-containing multiphase flows can be classified as either water-dispersed or water-continuous mixtures. A recently developed approach based on Hanai’s mixture formula and utilizing electrical capacitance tomography (ECT) sensors have shown good potential for obtaining water volume fraction estimates in two-phase water-containing flows with different water salinity levels. However, the proposed approach was investigated via controlled experiments restricted to static configurations while, in practice, multiphase flows can be dynamic and unpredictable. In this work, we perform a flow loop study of the proposed ECT-based method for volume fraction estimation in oil–water two-phase flows. Here, we evaluate the performance of the proposed method in both water-dispersed and water-continuous flow regimes by employing different types of capacitive sensors in cylindrical arrangements and parallel-plate rectangular arrangements.

02 PETROLEUM↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
NASA NTRS1976

The effects of an ion-thruster exhaust plume on S-band carrier transmission

The study reported here was undertaken (1) to develop models of the effects of an ion-thruster exhaust plume on S-band signals, and (2) to measure the effects. The results show that an S-band signal passing through an ion-thruster plume is reduced in amplitude and advanced in phase. The mathematical models gave reasonable estimates of the average signal attenuation and phase shift. Negligible fluctuations in the signal amplitude and phase were measured during steady-state thruster operation. However, large jumps in phase occurred when changes were made in the thruster operating state. This study confirms that the thruster plume can have a significant effect on S-band communication link performance; hence the plume effects must be considered in S-band link calculations when electric thrusters are used for spacecraft propulsion.

Ackerknecht, W. E.↗
NASA NTRS1988

Advanced Receiver tracking of Voyager 2 near solar conjunction

The Advanced Receiver (ARX) was used to track the Voyager 2 spacecraft at low Sun-Earth-Probe (SEP) angles near solar conjunction in December of 1987. The received carrier signal exhibited strong fluctuations in both phase and amplitude. The ARX used spectral estimation and mathematical modeling of the phase and receiver noise processes to set an optimum carrier tracking bandwidth. This minimized the mean square phase error in tracking carrier phase and thus minimized the loss in the telemetry signal-to-noise ratio due to the carrier loop. Recovered symbol SNRs and errors in decoded engineering data for the ARX are compared with those for the current Block 3 telemetry stream. Optimum bandwidths are plotted against SEP angle. Measurements of the power spectral density of the solar phase and amplitude fluctuations are also given.

Brown, D. H.↗
NASA NTRS2010

Phase and Pupil Amplitude Recovery for JWST Space-Optics Control

This slide presentation reviews the phase and pupil amplitude recovery for the James Webb Space Telescope (JWST) Near Infrared Camera (NIRCam). It includes views of the Integrated Science Instrument Module (ISIM), the NIRCam, examples of Phase Retrieval Data, Ghost Irradiance, Pupil Amplitude Estimation, Amplitude Retrieval, Initial Plate Scale Estimation using the Modulation Transfer Function (MTF), Pupil Amplitude Estimation vs lambda, Pupil Amplitude Estimation vs. number of Images, Pupil Amplitude Estimation vs Rotation (clocking), and Typical Phase Retrieval Results Also included is information about the phase retrieval approach, Non-Linear Optimization (NLO) Optimized Diversity Functions, and Least Square Error vs. Starting Pupil Amplitude.

Dean, B. H.↗
DOE OSTI2022

Earthquake Phase Association Using a Bayesian Gaussian Mixture Model

Earthquake phase association algorithms aggregate picked seismic phases from a network of seismometers into individual seismic events and play an important role in earthquake monitoring and research. Dense seismic networks and improved phase picking methods produce massive seismic phase datasets, particularly for earthquake swarms and aftershocks occurring closely in time and space, making phase association a challenging problem. Here, we present a new association method, the Gaussian Mixture Model Association (GaMMA), that combines the Gaussian mixture model with earthquake location, origin time, and magnitude estimation. We treat earthquake phase association as an unsupervised clustering problem in a probabilistic framework, where each earthquake corresponds to a cluster of P and S phases with a hyperbolic moveout of arrival times and a decay of amplitude with distance. We use the multivariate Gaussian distribution to model the collection of phase picks of an event; and the mean of the multivariate Gaussian distribution is given by the predicted arrival time and amplitude from the causative event. We carry out the pick assignment to each earthquake and determine earthquake source parameters (i.e., earthquake location, origin time, and magnitude) under the maximum likelihood criterion using the Expectation-Maximization algorithm. The GaMMA method does not require typical association steps of other algorithms, such as grid-search or supervised training. The results for both synthetic tests and for the 2019 Ridgecrest earthquake sequence show that GaMMA effectively associates phases from a temporally and spatially dense earthquake sequence while producing useful estimates of earthquake location and magnitude.

58 GEOSCIENCES↗
NASA NTRS1974

Modeling the evolution of Sm and Eu abundances during lunar igneous differentiation

The current work presents models for the evolution of europium and samarium abundances during lunar igneous processes. The effect of probable variations in lunar temperature and oxygen fugacity, mineral-liquid distribution coefficients, and the crystallization or melting progression are considered in the model calculations. Changes in the proportions of crystallizing phases strongly influence the evolution of trace element abundances during fractional crystallization, and models must include realistic estimates of the major phase equilibria during crystallization. The results are applied to evaluating the possibility of generating KREEP-rich materials by lunar igneous processes.

Weill, D. F.↗
NASA NTRS1990

Phase noise effects on turbulent weather radar spectrum parameter estimation

Accurate weather spectrum moment estimation is important in the use of weather radar for hazardous windshear detection. The effect of the stable local oscillator (STALO) instability (jitter) on the spectrum moment estimation algorithm is investigated. Uncertainty in the stable local oscillator will affect both the transmitted signal and the received signal since the STALO provides transmitted and reference carriers. The proposed approach models STALO phase jitter as it affects the complex autocorrelation of the radar return. The results can therefore by interpreted in terms of any source of system phase jitter for which the model is appropriate and, in particular, may be considered as a cumulative effect of all radar system sources.

Lee, Jonggil↗
DOE OSTI2024

Sand Thermal Energy Storage Pilot Design (Final Report)

This report summarizes work done on developing a 10-MWhe pilot of the sand-based thermal energy storage (SandTES) technology at Alabama Power’s Plant Gaston Unit 5, an operating, supercritical coal power unit. The system will be integrated to the unit, obtaining steam to heat the sand through an air-blown fluidized-bed heat exchanger, then storing the water to be reused during discharging to produce steam that will then be vented. An electrical particle heater will also be included to provide part of the heat to the sand to provide data and learnings for commercial systems that will be fully electrically heated. Hot sand is contained in one bunker, while cold sand is housed in the other bunker, and standard solids handling equipment moves the sand around. This pilot would advance the SandTES technology to Technology Readiness Level 6 and position it for commercial readiness by 2030. This work was done in two phases: Phase I performed a conceptual study that provided Association for the Advancement of Cost Engineering (AACE) Class 5 costs and estimated performance, and then Phase II, which also involved a design update, performed a more detailed pre-front-end engineering and design study that elicited AACE Class 4 costs. Work was also done to provide estimated costs for commercial applications of the technology, assess its gaps, create its technology maturation and commercialization plans, and finally perform an Environmental Information Volume for the pilot site as a first step in the National Environmental Policy Act process.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1989

Operations and support cost modeling using Markov chains

Systems for future missions will be selected with life cycle costs (LCC) as a primary evaluation criterion. This reflects the current realization that only systems which are considered affordable will be built in the future due to the national budget constaints. Such an environment calls for innovative cost modeling techniques which address all of the phases a space system goes through during its life cycle, namely: design and development, fabrication, operations and support; and retirement. A significant portion of the LCC for reusable systems are generated during the operations and support phase (OS). Typically, OS costs can account for 60 to 80 percent of the total LCC. Clearly, OS costs are wholly determined or at least strongly influenced by decisions made during the design and development phases of the project. As a result OS costs need to be considered and estimated early in the conceptual phase. To be effective, an OS cost estimating model needs to account for actual instead of ideal processes by associating cost elements with probabilities. One approach that may be suitable for OS cost modeling is the use of the Markov Chain Process. Markov chains are an important method of probabilistic analysis for operations research analysts but they are rarely used for life cycle cost analysis. This research effort evaluates the use of Markov Chains in LCC analysis by developing OS cost model for a hypothetical reusable space transportation vehicle (HSTV) and suggests further uses of the Markov Chain process as a design-aid tool.

Unal, Resit↗
NASA NTRSDate not supplied

NASA Hybrid Thermally Efficient Core (HyTEC) Project Overview

The HyTEC Project goal is to mature compact core aircraft engine technologies as part of the NASA-led Sustainable Flight National Partnership (SFNP) that contributes to the United States Aviation Climate Action Plan goal for aviation net zero carbon emissions by 2050. Individual technologies were proposed and defined by industry partners, and then selected technology maturation activities are cost shared. Phase 1 contracts were awarded in 2021, and since then, the project has matured numerous technologies to TRL 4-5. Some of the Phase 1 efforts have been completed with successful results. An initial systems analysis study has been completed to estimate the impact of Phase 1 technologies against project performance metrics, with results indicating significant progress is being made toward meeting those metrics. HyTEC will culminate with an engine core demonstration that will integrate many of the Phase 1 technologies into a large-scale integrated ground demonstration that will achieve TRL 6 to enable industry to transition the technologies into the next single-aisle engine architecture. The goal of the demonstration is to fully meet the project performance metrics that define a compact engine core with substantial improvements in efficiency, durability, performance, hybridization, and sustainability over the baseline established in the year 2020. HyTEC will also incorporate hybrid electric technology into the engine core with the intention to bring the first electrified turbofan engines into production. The core demonstration has been awarded with a cost-share partnership and is planned to occur by the end of 2028.

Anthony L Nerone↗
NASA NTRS2003

Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

Taylor, Jaime↗
DOE OSTI2021

Influence of Heave Plate Topology on Reaction Force

In this study, we explore the role of heave plate topology on fluid reaction forces using three, representative shapes: a hexagonal flat plate, a hexagonal conic with an open top, and the same with a closed top that encloses a fluid mass. We force each test article sinusoidally in a quiescent tank and decompose the reaction force using forms of the Morison equation for phase-invariant and phase-dependent parameterizations. We find that a flat plate generates 5.3 % more fluid reaction force than the open conic topology, and 21.4% more than the enclosed conic. Asymmetric topologies generate asymmetric reaction forces, but the magnitude of asymmetry is limited by nearly symmetric fluid inertia forces, which dominate over drag for these test articles. Additionally, we observe asymmetric vortex dynamics for the flat plate when the Keulegan-Carpenter number is between 1 and 2, accompanied by a shift in the phase of the peak force by of the oscillation period. As a consequence of this shift, the hydrodynamic coefficients estimated from the phase-dependent Morison equation decomposition are asymmetric, suggesting that phase-dependent representations may not provide physical insight in some hydrodynamic regimes.

added mass↗
DOE OSTI2026

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗
DOE OSTI2024

GalaxyFlow: upsampling hydrodynamical simulations for realistic mock stellar catalogues

ABSTRACT Cosmological N-body simulations of galaxies operate at the level of ‘star particles’ with a mass resolution on the scale of thousands of solar masses. Turning these simulations into stellar mock catalogues requires ‘upsampling’ the star particles into individual stars following the same phase-space density. In this paper, we introduce two new upsampling methods. First, we describe GalaxyFlow, a sophisticated upsampling method that utilizes normalizing flows to both estimate the stellar phase-space density and sample from it. Secondly, we improve on existing upsamplers based on adaptive kernel density estimation (KDE), using maximum likelihood estimation to fine-tune the bandwidth for such algorithms in a way that improves both the density estimation accuracy and upsampling results. We demonstrate our upsampling techniques on a neighbourhood of the Solar location in two simulated galaxies: Auriga 6 and h277. Both yield smooth stellar distributions that closely resemble the stellar densities seen in the Gaia DR3 catalogue. Furthermore, we introduce a novel multimodel classifier test to compare the accuracy of different upsampling methods quantitatively. This test confirms that GalaxyFlow more accurately estimates the density of the underlying star particles than methods based on KDE, at the cost of being more computationally intensive.

Lim, Sung Hak (ORCID:0000000330981092)↗
NASA NTRS2012

Formation of Minor Phases in a Nickel-Based Disk Superalloy

The minor phases of powder metallurgy disk superalloy LSHR were studied. Samples were consistently heat treated at three different temperatures for long times to approximate equilibrium. Additional heat treatments were also performed for shorter times, to then assess non-equilibrium conditions. Minor phases including MC carbides, M23C6 carbides, M3B2 borides, and sigma were identified. Their transformation temperatures, lattice parameters, compositions, average sizes and total area fractions were determined, and compared to estimates of an existing phase prediction software package. Parameters measured at equilibrium sometimes agreed reasonably well with software model estimates, with potential for further improvements. Results for shorter times representing non-equilibrium indicated significant potential for further extension of the software to such conditions, which are more commonly observed during heat treatments and service at high temperatures for disk applications.

Gabb, T. P.↗
NASA NTRS1987

Optimized tracking of RF carriers with phase noise, including Pioneer 10 results

The ability to track very weak signals from distant spacecraft is limited by the phase instabilities of the received signal and of the local oscillator employed by the receiver. These instabilities ultimately limit the minimum loop bandwidth that can be used in a phase-coherent receiver, and hence limit the ratio of received carrier power to noise spectral density which can be tracked phase coherently. A method is presented for near real time estimation of the received carrier phase and additive noise spectrum, and optimization of the phase locked loop bandwidth. The method was used with the breadboard Deep Space Network (DSN) Advanced Receiver to optimize tracking of very weak signals from the Pioneer 10 spacecraft, which is now more distant that the edge of the solar system. Tracking with bandwidths of 0.1 Hz to 1.0 Hz reduces tracking signal threshold and increases carrier loop signal to noise ratio (SNR) by 5 dB to 15 dB compared to the 3 Hz bandwidth of the receivers now used operationally in the DSN. This will enable the DSN to track Pioneer 10 until its power sources fails near the end of the century.

Vilnrotter, V. A.↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗