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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Heat transfer measurements for Stirling machine cylinders

The primary purpose of this study was to measure the effects of inflow-produced heat turbulence on heat transfer in Stirling machine cylinders. A secondary purpose was to provide new experimental information on heat transfer in gas springs without inflow. The apparatus for the experiment consisted of a varying-volume piston-cylinder space connected to a fixed volume space by an orifice. The orifice size could be varied to adjust the level of inflow-produced turbulence, or the orifice plate could be removed completely so as to merge the two spaces into a single gas spring space. Speed, cycle mean pressure, overall volume ratio, and varying volume space clearance ratio could also be adjusted. Volume, pressure in both spaces, and local heat flux at two locations were measured. The pressure and volume measurements were used to calculate area averaged heat flux, heat transfer hysteresis loss, and other heat transfer-related effects. Experiments in the one space arrangement extended the range of previous gas spring tests to lower volume ratio and higher nondimensional speed. The tests corroborated previous results and showed that analytic models for heat transfer and loss based on volume ratio approaching 1 were valid for volume ratios ranging from 1 to 2, a range covering most gas springs in Stirling machines. Data from experiments in the two space arrangement were first analyzed based on lumping the two spaces together and examining total loss and averaged heat transfer as a function of overall nondimensional parameter. Heat transfer and loss were found to be significantly increased by inflow-produced turbulence. These increases could be modeled by appropriate adjustment of empirical coefficients in an existing semi-analytic model. An attempt was made to use an inverse, parameter optimization procedure to find the heat transfer in each of the two spaces. This procedure was successful in retrieving this information from simulated pressure-volume data with artificially generated noise, but it failed with the actual experimental data. This is evidence that the models used in the parameter optimization procedure (and to generate the simulated data) were not correct. Data from the surface heat flux sensors indicated that the primary shortcoming of these models was that they assumed turbulence levels to be constant over the cycle. Sensor data in the varying volume space showed a large increase in heat flux, probably due to turbulence, during the expansion stroke.

Kornhauser, Alan A.↗
NASA NTRS1996

Hypersonic Boundary-Layer Stability Experiments on a Flared-Cone Model at Angle of Attack in a Quiet Wind Tunnel

An experimental investigation of the effects of angle of attack on hypersonic boundary-layer stability on a flared-cone model was conducted in the low-disturbance Mach-6 Nozzle-Test Chamber Facility at NASA Langley Research Center. This unique facility provided a 'quiet' flow test environment which is well suited for stability experiments because the low levels of freestream 'noise' minimize artificial stimulation of flow-disturbance growth. Surface pressure and temperature measurements documented the adverse-pressure gradient and transition-onset location. Hot-wire anemometry diagnostics were applied to identify the instability mechanisms which lead to transition. In addition, the mean flow over the flared-cone geometry was modeled by laminar Navier-Stokes computations. Results show that the boundary layer becomes more stable on the windward ray and less stable on the leeward ray relative to the zero-degree angle-of-attack case. The second-mode instability dominates the transition process at a zero-degree angle of attack, however, on the windward ray at an angle of attack this mode was completely stabilized. The less-dominant first-mode instability was slightly destabilized on the windward ray. Non-linear mechanisms such as saturation and harmonic generation are identified from the flow-disturbance bispectra.

Doggett, Glen P.↗
NASA NTRS1995

Interdecadal Variations in the Alaska Gyre

Climatic dynamic topography variations in the Alaska gyre during the period 1968-1990 are described with an objective analysis of more than 12000 STD and XBT stations, and COADS wind stress data Interannual the dynamic height and SST variations were correlated and were consistent with recently described large-scale climatic shifts in the North Pacific. The gyre was centered more to the east, circulation appeared stronger, and SST was lower during the early to mid-1970s than during the 1980s. The Aleutian low (NP and PNA indices) intensified during the interim, but the response did not appear as a gyre spinup. Instead, the associated wind stress anomalies forced a slowly varying dynamic height anomaly across the eastern and northern part of the gyre through Ekman convergence, which had the effect of displacing the gyre's low somewhat to the WSW in the 1980s. The wind curl spectrum was white, and the slow oceanic response was modeled as stochastic-forced climate variability with a simple first-order Markov autoregression process. Forcing was assumed to be Ekman pumping of the pycnocline, and the damping coefficient was estimated from the data to be approx. 1 yr. A hindcast with observed winds gave estimated dynamic height patterns similar to those observed, with a canonical correlation of 0.79 at 99% confidence. This response was weak in the western half of the gyre, where slow baroclinic variability may have been influenced by long Rossby wave propagation. A simple autoregression simulation using artificial white noise forcing shows the evolution of decadal variations similar in nature to those observed. This result, along with the low frequency correlation between dynamic height and SST, suggests that the upper-ocean climatic variability in this region is primarily wind forced.

Lagerloef, Gary S.E.↗
DOE OSTI2023

Deconstructing magnetization noise: Degeneracies, phases, and mobile fractionalized excitations in tetris artificial spin ice

Direct detection of spontaneous spin fluctuations, or “magnetization noise,” is emerging as a powerful means of revealing and studying magnetic excitations in both natural and artificial frustrated magnets. Depending on the lattice and nature of the frustration, these excitations can often be described as fractionalized quasiparticles possessing an effective magnetic charge. Here, by combining ultrasensitive optical detection of thermodynamic magnetization noise with Monte Carlo simulations, we reveal emergent regimes of magnetic excitations in artificial “tetris ice.” A marked increase of the intrinsic noise at certain applied magnetic fields heralds the spontaneous proliferation of fractionalized excitations, which can diffuse independently, without cost in energy, along specific quasi-1D spin chains in the tetris ice lattice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2003

Jet Noise Physics and Modeling Using First-principles Simulations

An extensive analysis of our jet DNS database has provided for the first time the complex correlations that are the core of many statistical jet noise models, including MGBK. We have also for the first time explicitly computed the noise from different components of a commonly used noise source as proposed in many modeling approaches. Key findings are: (1) While two-point (space and time) velocity statistics are well-fitted by decaying exponentials, even for our low-Reynolds-number jet, spatially integrated fourth-order space/retarded-time correlations, which constitute the noise "source" in MGBK, are instead well-fitted by Gaussians. The width of these Gaussians depends (by a factor of 2) on which components are considered. This is counter to current modeling practice, (2) A standard decomposition of the Lighthill source is shown by direct evaluation to be somewhat artificial since the noise from these nominally separate components is in fact highly correlated. We anticipate that the same will be the case for the Lilley source, and (3) The far-field sound is computed in a way that explicitly includes all quadrupole cancellations, yet evaluating the Lighthill integral for only a small part of the jet yields a far-field noise far louder than that from the whole jet due to missing nonquadrupole cancellations. Details of this study are discussed in a draft of a paper included as appendix A.

Freund, Jonathan B.↗
NASA NTRS1990

AMPTE CCE observations of Pc 3-4 pulsations at L = 2-6

Magnetic field data acquired by the AMPTE CCE satellite from L = 2-6 are analyzed. A procedure was specially developed to reduce the artificial modulation and noise in magnetic field measurements, making it possible to detect Pc 3-4 pulsations with amplitudes only 1 nT or less, even for L values less than 3. A survey of 41 CCE passes in L = 2-6 and in the postnoon sector showed that the most commonly observed pulsations in this region were the east-west oscillations of magnetic field with clearly L-dependent frequencies; these are identified as the toroidal mode standing Alfven waves. A relationship was found between the pulsation frequency and plasma density, showing that the pulsation data can be used to estimate the plasma mass density in the inner magnetosphere.

Takahashi, Kazue↗
NASA NTRS2011

Evaluation of Pulse Counting for the Mars Organic Mass Analyzer (MOMA) Ion Trap Detection Scheme

The Mars Organic Mass Analyzer is being developed at Goddard Space Flight Center to identify organics and possible biological compounds on Mars. In the process of characterizing mass spectrometer size, weight, and power consumption, the use of pulse counting was considered for ion detection. Pulse counting has advantages over analog-mode amplification of the electron multiplier signal. Some advantages are reduced size of electronic components, low power consumption, ability to remotely characterize detector performance, and avoidance of analog circuit noise. The use of pulse counting as a detection method with ion trap instruments is relatively rare. However, with the recent development of high performance electrical components, this detection method is quite suitable and can demonstrate significant advantages over analog methods. Methods A prototype quadrupole ion trap mass spectrometer with an internal electron ionization source was used as a test setup to develop and evaluate the pulse-counting method. The anode signal from the electron multiplier was preamplified. The an1plified signal was fed into a fast comparator for pulse-level discrimination. The output of the comparator was fed directly into a Xilinx FPGA development board. Verilog HDL software was written to bin the counts at user-selectable intervals. This system was able to count pulses at rates in the GHz range. The stored ion count nun1ber per bin was transferred to custom ion trap control software. Pulse-counting mass spectra were compared with mass spectra obtained using the standard analog-mode ion detection. Prelin1inary Data Preliminary mass spectra have been obtained for both analog mode and pulse-counting mode under several sets of instrument operating conditions. Comparison of the spectra revealed better peak shapes for pulse-counting mode. Noise levels are as good as, or better than, analog-mode detection noise levels. To artificially force ion pile-up conditions, the ion trap was overfilled and ions were ejected at very high scan rates. Pile-up of ions was not significant for the ion trap under investigation even though the ions are ejected in so-called 'ion-micro packets'. It was found that pulse counting mode had higher dynamic range than analog mode, and that the first amplification stage in analog mode can distort mass peaks. The inherent speed of the pulse counting method also proved to be beneficial to ion trap operation and ion ejection characterization. Very high scan rates were possible with pulse counting since the digital circuitry response time is so much smaller than with the analog method. Careful investigation of the pulse-counting data also allowed observation of the applied resonant ejection frequency during mass analysis. Ejection of ion micro packets could be clearly observed in the binned data. A second oscillation frequency, much lower than the secular frequency, was also observed. Such an effect was earlier attributed to the oscillation of the total plasma cloud in the ion trap. While the components used to implement pulse counting are quite advanced, due to their prevalence in consumer electronics, the cost of this detection system is no more than that of an analog mode system. Total pulse-counting detection system electronics cost is under $250

Van Amerom, Friso H.↗
NASA NTRS1993

Noise levels from a model turbofan engine with simulated noise control measures applied

A study of estimated full-scale noise levels based on measured levels from the Advanced Ducted Propeller (ADP) sub-scale model is presented. Testing of this model was performed in the NASA Lewis Low Speed Anechoic Wind Tunnel at a simulated takeoff condition of Mach 0.2. Effective Perceived Noise Level (EPNL) estimates for the baseline configuration are documented, and also used as the control case in a study of the potential benefits of two categories of noise control. The effect of active noise control is evaluated by artificially removing various rotor-stator interaction tones. Passive noise control is simulated by applying a notch filter to the wind tunnel data. Cases with both techniques are included to evaluate hybrid active-passive noise control. The results for EPNL values are approximate because the original source data was limited in bandwidth and in sideline angular coverage. The main emphasis is on comparisons between the baseline and configurations with simulated noise control measures.

Hall, David G.↗
NASA NTRSDate not supplied

Developing and Testing a Physics Guided Machine Learning NeuralNetwork to Predict Tonal Noise Emitted by a Propeller

Artificial neural networks offer a highly nonlinear and adaptive model for predicting complex interactions between input-output parameters. However, these networks require large datasets which often exceed practical considerations in modeling experimental results. To alleviate the dataset size requirement, a method known as physics guided machine learning has been applied to construct several neural networks for predicting propeller tonal noise in the time domain over a broad range of flight conditions. Three space-filling designs, namely, Latin-Hypercube, Sphere-Packing, and Grid-Space, were used to distribute points throughout the input parameter space encompassing nondimensional flight conditions and observer geometry. Each neural network’s performance was validated by conditions outside of the training set and compared to the Propeller Analysis System tool from the NASA Aircraft Noise Prediction Program. Compared to the Grid-Space input design, the Latin-Hypercube and the Sphere-Packing designs provided a better representation of the domain for training. Regarding the network archetype, a fully connected perceptron was found to outperform the partially connected perceptron in their ability to predict tonal noise for small datasets. The black-box nature of these neural networks was also explored to understand how the networks constructed the waveform and understand why some network designs produce better models.

Propeller noise↗
DOE OSTI2023

Removing Numerical Pathologies in a Turbulence Parameterization Through Convergence Testing

Abstract Discretized numerical models of the atmosphere are usually intended to faithfully represent an underlying set of continuous equations, but this necessary condition is violated sometimes by subtle pathologies that have crept into the discretized equations. Such pathologies can introduce undesirable artifacts, such as sawtooth noise, into the model solutions. The presence of these pathologies can be detected by numerical convergence testing. This study employs convergence testing to verify the discretization of the Cloud Layers Unified By Binormals (CLUBB) model of clouds and turbulence. That convergence testing identifies two aspects of CLUBB's equation set that contribute to undesirable noise in the solutions. First, numerical limiters (i.e., clipping) used by CLUBB introduce discontinuities or slope discontinuities in model fields. Second, nonlinear artificial diffusion employed for improving numerical stability can introduce unintended small‐scale features into the solution of the model equations. Smoothing the limiters and using linear artificial diffusion reduces the noise and restores the expected first‐order convergence in CLUBB's solutions. These model reformulations enhance our confidence in the trustworthiness of solutions from CLUBB by eliminating the unphysical oscillations in high‐resolution simulations. The improvements in the results at coarser, near‐operational grid spacing and timestep are also seen in cumulus cloud and dry turbulence tests. In addition, convergence testing is proven to be a valuable tool for detecting pathologies, including unintended discontinuities and grid dependence, in the model equation set.

58 GEOSCIENCES↗
NASA NTRS1982

Rotating gravity gradiometer study

Two rotating gravity gradiometer (RGG) sensors, along with all the external electronics needed to operate them, and the fixtures and special test equipment needed to fill and align the bearings, were assembled in a laboratory, and inspected. The thermal noise threshold of the RGG can be lowered by replacing a damping resistor in the first stage electronics by an active artificial resistor that generates less random voltage noise per unit bandwidth than the Johnson noise from the resistor it replaces. The artificial resistor circuit consists of an operational amplifier, three resistors, and a small DC to DC floating power supply. These are small enough to be retrofitted to the present circuit boards inside the RGG rotor in place of the 3 Megohm resistor. Using the artificial resistor, the thermal noise of the RGG-2 sensor can be lowered from 0.3 Eotvos to 0.15 Eotvos for a 10 sec integration time.

Forward, R. L.↗
NASA NTRS2023

Blade-Wake Interaction Noise for Small Hovering Rotors, Part I: Characterization Study

This work illustrates the use of artificial neural network modeling to study and characterize broadband blade-wake interaction noise from hovering small unmanned aerial systems rotors subject to varying airfoil geometries, rotor geometries, and operating conditions. Design of experiments was used to create input feature spaces, and a high-fidelity strategy was implemented at the discrete data points defined by the input feature spaces to design airfoils and rotor blades, predict the unsteady rotor aerodynamics and aeroacoustics, and isolate the blade-wake interaction noise from the acoustic broadband noise. A metric for the blade-wake interaction noise was developed, and the ANOPP2 Artificial Neural Network Tool was used to identify an optimal prediction model for the nonlinear relationship between the input features and the metric for blade-wake interaction noise. This optimal artificial neural network was then validated over training/test data and exhibited prediction accuracy over 91% for data previously unseen by the model. A sensitivity analysis was conducted, which showed that input features that directly modify the thrust coefficient had a dominant effect over blade-wake interaction noise. The optimal prediction model along with aerodynamic simulations were used to further study the effect of varying input features on blade-wake interaction noise, and three types of blade-wake interaction noise were identified

Christopher S. Thurman↗
NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

A surrogate artificial neural network/machine learning model was developed to predict the acoustic interaction for a fixed-pitch rotor in proximity to a downstream cylindrical airframe typical of small Unmanned Aerial System (sUAS) platforms. The model was trained to predict the acoustic waveform under representative hover conditions as a function of rotational speed, airframe proximity, and observer angle. Training data were acquired in an anechoic chamber on both isolated rotors and rotor-airframe configurations. Acoustic amplitude and phase of the revolution-averaged interaction were predicted, which required up to 25 harmonics to capture the impulse event caused by the blade’s approach and departure from the airframe. Prediction performance showed, on average, that the models could estimate the acoustic amplitude and phase over the relevant harmonics for unseen conditions with 86% and 75% accuracy, respectively, enabling a time domain reconstruction of the waveform for the range of geometric and flow parameters tested.

acoustics↗
NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

A surrogate artificial neural network/machine learning model was developed to predict the acoustic interaction for a fixed-pitch rotor in proximity to a downstream cylindrical airframe typical of small Unmanned Aerial System (sUAS) platforms. The model was trained to predict the acoustic waveform under representative hover conditions as a function of rotational speed, airframe proximity, and observer angle. Training data were acquired in an anechoic chamber on both isolated rotors and rotor-airframe configurations. Acoustic amplitude and phase of the revolution-averaged interaction were predicted, which required up to 25 harmonics to capture the impulse event caused by the blade’s approach and departure from the airframe. Prediction performance showed, on average, that the models could estimate the acoustic amplitude and phase over the relevant harmonics for unseen conditions with 86% and 75% accuracy, respectively, enabling a time domain reconstruction of the waveform for the range of geometric and flow parameters tested.

acoustics↗
NASA NTRS2007

The Evolution of Modulated Wavetrains Into Turbulent Spots

Experiment are being carried out to study the process by which th almost periodic disturbance waves generated naturally by the freestream evolve into turbulence. The boundary layer on a flat plate has been used for this study. The novelty of the approach is in the form of artificial excitation that is used. In this work the flow is excited artificially by deterministic white noise. The weak T-S wave created develops down stream, becomes nonlinear and blows up locally onto a highly distorted flow. These large local distortions of the mean flow allow very high frequency disturbances to grow and form into small turbulent spots. The spots arise from the excitation, and if the same noise sequence is repeated a spot will form at the same position and time instant relative to the excitation.

Gaster, M.↗
NASA NTRS1984

Rotational Inversion from Global Solar Oscillations

The degree to which various sets of solar oscillations can resolve the solar internal rotation was investigated. Genuine observations were simulated by the following procedure; first an artificial angular velocity was invented, and from it the rotational splitting of a set of normal modes was calculated; to that was added some random noise. The result was treated as artificial data and an attempt to recover the rotation law by using the Backus-Gilbert optimal averaging procedure was made. Neither the original rotation law nor the amount of noise that had been added was known. The conclusion was compared with the actual artificial angular velocity.

Christensen-Dalsgaard, J.↗
NASA NTRS1990

The identification of helicopter noise using a neural network

Experiments were carried out to demonstrate the ability of an artificial neural network (ANN) system to distinguish between the noise of two helicopters. The ANN is taught to identify helicopters by using two types of features: one that is associated with the ratio of the main-rotor to tail-rotor blade passage frequency (BPF), and the ohter that describes the distribution of peaks in the main-rotor spectrum, which is independent of the tail-rotor. It is shown that the ability of the ANN to identify helicopters is comparable to that of a conventional recognition system using the ratio of the main-rotor BPF to the tail-rotor BPF (when both the main- and the tail-rotor noise are present), but the performoance of ANN exceeds the conventional-method performance when the tail-rotor noise is absent. In addition, the results of ANN can be obtained as a function of propagation distance.

Cabell, Randolph H.↗
NASA NTRS1995

Water vapor radiometer measurements of the tropospheric delay fluctuations at Goldstone over a full year

One year of near-continuous water vapor radiometer (WVR) measurements at DSS 13 has provided a database for characterizing the Goldstone tropospheric delay properties in a statistical sense. The results have been expressed in terms of the Allan standard deviation of delay and compared to a previous model for Goldstone fluctuations and the specifications of the Cassini Gravitational Wave Experiment (GWE). The new WVR data indicate that average fluctuation levels at hour time scales or less are approximately 30 percent lower than the earlier Goldstone model predictions. At greater than 1 h time scales, the WVR indicated fluctuation levels are in closer agreement with the model, although noise floor limitations may be artificially raising the average WVR-derived atmospheric fluctuation levels at the longer time scales. When scaled to two-way Doppler tracking at 20 deg elevation, as will occur for the GWE, these results indicate that Goldstone winter tropospheric delay fluctuations will typically be a factor of 10 larger than the GWE requirements at 1000 s and a factor of 4 larger at 10,000 s.

Keihm, S. J.↗