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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Error field measurements and correction on MUSE permanent magnet stellarator

The magnetic field topology and error fields are measured in the MUSE permanent magnet stellarator with an electron beam and fluorescent rod. The effective magnetization of the magnets is determined by measuring rational flux surface locations. Electron magnetic drift effects must be considered self-consistently due to the small magnetic shear on MUSE. Error fields are characterized by flux surface shape deviation and magnetic island chain width and phase. Error fields are then corrected by adjusting the permanent magnet (PM) holders as rigid bodies. Resonant error fields are on the order of or smaller than 3 x 10 -6 of the toroidal field after correction and surface shape matches well with the design. Resonant components of the quasi-symmetry deviation are estimated, using a novel magnetic drift measurement, to be in the 10 −4 range. The PM approach is validated as a low-cost and precise way to build optimized stellarators.

electron beam mapping↗
NASA NTRS2003

Characterization of the Crab Pulsar's Timing Noise

We present a power spectral analysis of the Crab pulsar's timing noise, mainly using radio measurements from Jodrell Bank taken over the period 1982-1989, an interval bounded by sparse data sampling and a large glitch. The power spectral analysis is complicated by nonuniform data sampling and the presence of a steep red power spectrum that can distort power spectra measurement by causing severe power 'leakage'. We develop a simple windowing method for computing red noise power spectra of uniformly sampled data sets and test it on Monte Carlo generated sample realizations of red power-law noise. We generalize time-domain methods of generating power-law red noise with even integer spectral indices to the case of noninteger spectral indices. The Jodrell Bank pulse phase residuals are dense and smooth enough that an interpolation onto a uniform time series is possible. A windowed power spectrum is computed revealing a periodic or nearly periodic component with a period of 568 +/- 10 days and a l/f(exp 3) power-law noise component in pulse phase with a noise strength S(sub infinity)=(1.24 +/- 0.067) x 10(exp 16) cycles(exp 2)/sec(exp 2) over the analysis frequency range f=0.003- 0.1 cycles/day. This result deviates from past analyses which characterized the pulse phase timing residuals as either l/f(sub 4) power-law noise or a quasiperiodic process. The analysis was checked using the Deeter polynomial method of power spectrum estimation that was developed for the case of nonuniform sampling, but has lower spectral resolution. The timing noise is consistent with a torque noise spectrum rising with analysis frequency as f implying blue torque noise, a result not predicted by current models of pulsar timing noise. If the periodic or nearly periodic component is due to a binary companion, we find a mass function f(M) = (6.8 +/- 2.4) x 10(exp -16) solar mass and a companion mass, M(sub c) is greater than or equal to 3.2 solar mass assuming a Crab pulsar mass of 1.4 solar mass.

Scott, D. M.↗
DOE OSTI2026

Time-of-Flight energy measurements with BPMs

The energy of a bunched non-relativistic ion beam can be deduced from measuring the beam phases in neighboring Beam Position Monitors (BPMs). This report presents estimations on implementation of such a procedure at PIP-II H- linac being constructed at Fermilab. In part, the case when the flight time between BPMs is larger than the period of BPM frequency is considered in detail. When the absolute BPM phase calibration is not available, the BPM phase information can be used to trace deviations of the beam energy from the desired value. Such “energy deviation” parameter is operationally implemented at the transfer line between 400 MeV Linac and the Booster, and its analog is expected to be used in the transfer line from PIP-II as well.

Shemyakin, Alexander [Fermilab] (ORCID:00000001501↗
DOE OSTI2025

Time-of-Flight Energy Measurements With BPMs

The energy of a bunched non-relativistic ion beam can be deduced from measuring the beam phases in neighbouring Beam Position Monitors (BPMs). This report discusses implementation of such a procedure at the PIP-II H- linac being constructed at Fermilab. The case when the flight time between BPMs is longer than the period of BPM frequency is considered in more detail. When absolute BPM phase calibration is not available, the BPM phase information can be used to track deviations of the beam energy from the de-sired value. Such energy deviation parameter is operationally implemented at the transfer line between 400 MeV Linac and the Booster, and its analog is expected to be used in the transfer line from PIP-II as well.

Shemyakin, Alexander V. [Fermilab] (ORCID:00000001↗
NASA NTRS1976

Recurrent brief X-ray bursts from the globular cluster NGC 6624

Observational data are presented on ten brief X-ray bursts, recurrent at nearly equal time intervals, recorded during a two-day observation of 3U 1820-30 in the globular cluster NGC 6624 with the wide-field modulation collimator detectors on the SAS-3 X-ray observatory. The occurrence times were fitted by least squares to a linear sequence with an rms deviation of 621 sec, corresponding to a phase jitter of 3.9%. The bursts were observed in two energy channels. For a sequence of five of the most clearly observed bursts, the 2-6 keV rate rose to its peak value in about 1 sec and then decayed to preburst level in about 10 sec. The 6-11 keV rate rose more slowly and decayed similarly. The smooth decay of their averaged light curve suggests the temporal evolution may have a geometrical origin, where Compton scattering in a surrounding cloud of hot plasma stretches the pulse out and causes a progressive hardening of the spectrum.

Clark, G. W.↗
NASA NTRS1990

Modeling of collision and coalescence of droplets during microgravity processing of Zn-Bi immiscible alloys

A population balance model is presented for the coarsening of the dispersed phase of liquid-liquid two-phase mixtures in microgravity due to gravity sedimentation and Marangoni migration, which lead to the collision and coalescence of droplets. The model is used to predict the evolution of the size distribution of the dispersed phase in a liquid-phase miscibility gap system, Zn-Bi, which has been used in a number of experimental microgravity processing studies in which significant phase segregation has been observed. The analysis shows that increasing the temperature gradient, gravity level, volume fraction of the dispersed phase, initial average drop radius, initial standard deviation of droplet radii, or the temperature coefficient of the interfacial tension leads to an increase in the rate of droplet growth due to collision and coalescence. Comparison of the distribution evolutions for unimodal and bimodal initial distributions shows that the latter yield significantly more rapid droplet growth. Finally, it is shown that droplet growth can be dramatically reduced with antiparallel orientation of the gravity vector and the temperature gradient, provided that the relative magnitude of these two vectors is properly chosen.

Davis, R. H.↗
NASA NTRS2002

Global Landing Site Access Using Atmospheric Skip Trajectories

Mars direct entry, without going into orbit, does not provide global access to all landing site latitudes. Latitudes accessible via direct entry trajectories consist of a ring around the backside of the planet, centered about V infinity. Landing sites outside this ring can be achieved using a modified approach trajectory entering the atmosphere over the South Pole "aerocapture fashion" that will skip out to an altitude above the atmosphere and then re-enter the atmosphere a second time and continue to toward the North Pole. The first aerocapture maneuver is aligned to provide an exit orbit that contains the desired landing site with an apoapsis computed to provide proper ranging for the second entry. A powered maneuver is utilized during the exoatmospheric phase to remove altitude and flight path deviations due to uncertainties in the atmosphere occurring during the first entry. Three guidance schemes are required for global landing site access analysis. Aerocapture guidance was used for the first atmospheric entry, Shuttle Powered Explicit Guidance was used for the exoatmospheric maneuver, and Apollo Derived Entry Guidance was used for the second atmospheric entry. An altimeter to update the onboard navigation state after the first atmospheric entry, was required to remove accumulated deadreckoning navigation errors and achieve reasonable range errors at chute deploy.

Bryant, Lee↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities withinthe same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, validation of AD models through real-world sensor data is important for their application in nuclear facilities. In this paper, we propose an Autoencoder (AE)— a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD) — as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We also validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Phase noise in pulsed Doppler lidar and limitations on achievable single-shot velocity accuracy

The smaller sampling volumes afforded by Doppler lidars compared to radars allows for spatial resolutions at and below some sheer and turbulence wind structure scale sizes. This has brought new emphasis on achieving the optimum product of wind velocity and range resolutions. Several recent studies have considered the effects of amplitude noise, reduction algorithms, and possible hardware related signal artifacts on obtainable velocity accuracy. We discuss here the limitation on this accuracy resulting from the incoherent nature and finite temporal extent of backscatter from aerosols. For a lidar return from a hard (or slab) target, the phase of the intermediate frequency (IF) signal is random and the total return energy fluctuates from shot to shot due to speckle; however, the offset from the transmitted frequency is determinable with an accuracy subject only to instrumental effects and the signal to noise ratio (SNR), the noise being determined by the LO power in the shot noise limited regime. This is not the case for a return from a media extending over a range on the order of or greater than the spatial extent of the transmitted pulse, such as from atmospheric aerosols. In this case, the phase of the IF signal will exhibit a temporal random walk like behavior. It will be uncorrelated over times greater than the pulse duration as the transmitted pulse samples non-overlapping volumes of scattering centers. Frequency analysis of the IF signal in a window similar to the transmitted pulse envelope will therefore show shot-to-shot frequency deviations on the order of the inverse pulse duration reflecting the random phase rate variations. Like speckle, these deviations arise from the incoherent nature of the scattering process and diminish if the IF signal is averaged over times greater than a single range resolution cell (here the pulse duration). Apart from limiting the high SNR performance of a Doppler lidar, this shot-to-shot variance in velocity estimates has a practical impact on lidar design parameters. In high SNR operation, for example, a lidar's efficiency in obtaining mean wind measurements is determined by its repetition rate and not pulse energy or average power. In addition, this variance puts a practical limit on the shot-to-shot hard target performance required of a lidar.

Mcnicholl, P.↗
DOE OSTI2021

Magnetic field induced phase transitions of the triangular spin model

In this work, motivated by a recent inelastic neutron scattering experiment on YbMgGaO 4 , I study the homogeneous spin model on the triangular lattice using the cluster mean-field theory and exact diagonalization. Phase diagrams with and without magnetic field are computed. The results show that the magnetic field can induce the phase transition from the spin liquid state (or the stripe state) to the 120 ° antiferromagnetic state. These phase transitions are suppressed by the next-nearest-neighbor exchange interaction J 2 / J 1 and vanish as J 2 / J 1 > 0.11 . I analyze a parameter space at J 2 / J 1 = 0.1 , where a field induced phase transition can occur, and find that the deviation of the theoretical spin excitation energy from the experimental data is only about 0.054. These results imply that an effective homogeneous spin model still applies to YbMgGaO 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1994

Numerical Analysis of an Impinging Jet Reactor for the CVD and Gas-Phase Nucleation of Titania

We model a cold-wall atmospheric pressure impinging jet reactor to study the CVD and gas-phase nucleation of TiO2 from a titanium tetra-iso-propoxide (TTIP)/oxygen dilute source gas mixture in nitrogen. The mathematical model uses the computational code FIDAP and complements our recent asymptotic theory for high activation energy gas-phase reactions in thin chemically reacting sublayers. The numerical predictions highlight deviations from ideality in various regions inside the experimental reactor. Model predictions of deposition rates and the onset of gas-phase nucleation compare favorably with experiments. Although variable property effects on deposition rates are not significant (approximately 11 percent at 1000 K), the reduction rates due to Soret transport is substantial (approximately 75 percent at 1000 K).

Gokoglu, Suleyman A.↗
NASA NTRS1978

Performance evaluation of integrated guidance and navigation systems

The method of linear covariance analysis is applied to the study of an aerospace vehicle integrated guidance-and-navigation system. This requires that the rms trajectory deviations of the vehicle be computed along with the rms errors of the navigation system. The technique is used to examine the performance of the shuttle orbiter vehicle's guidance-and-navigation system during the terminal phase of the landing. Essentially the same rms trajectory deviations were obtained from a single covariance run as from a 30-sample Monte-Carlo run set. Of particular interest in the study was the result that rms trajectory deviations for the integrated-system were generally significantly larger than the rms navigation errors.

Tao, Y. C.↗
DOE OSTI2021

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗
NASA NTRS2007

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0 - 30 N and 0 - 30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Atmospheric Infrared Sounder↗
NASA NTRS2007

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0-30 N and 0-30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Atmospheric Infrared Sounder (AIRS)↗
DOE OSTI2023

Solubility behavior and thermodynamic modeling of sodium monosulfoaluminate (“U‐phase”) in cementitious systems

Abstract The “U‐phase,” a sodium‐containing (alumino‐ferrite‐monosubstituent) AFm phase, has been observed to form in sodium‐enriched highly alkaline cementitious systems, for example, of relevance to nuclear waste, and saline industrial brine management. But, minimal information is available of the U‐phase's (e.g., solubility or thermodynamic properties) due to its limited stability and its tendency to transform into ettringite or monosulfoaluminate. Herein, the U‐phase was systematically synthesized at four temperatures (5, 15, 25, and 50°C) and fully characterized in terms of its thermochemical properties. The average composition of the synthesized U‐phase (4CaO·Al 2 O 3 ·1.85SO 3 ·0.85Na 2 O·12H 2 O) deviates slightly from typical disclosures in the literature. The solubility product of the U‐phase formation was measured from conditions of oversaturation. The measured thermodynamic data accurately predicted experimental observations of U‐phase formation in cementitious environments. In general, it was noted that the U‐phase forms and persists (i.e., remains stable) at pH > 13.7 and [Na + ] concentrations superior to 1 mol/L.

Materials Science↗