Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process noise”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A parallel domain decomposition-based implicit method for the Cahn–Hilliard–Cook phase-field equation in 3D

We present a numerical algorithm for simulating the spinodal decomposition described by the three dimensional Cahn–Hilliard–Cook (CHC) equation, which is a fourth-order stochastic partial differential equation with a noise term. The equation is discretized in space and time based on a fully implicit, cell-centered finite difference scheme, with an adaptive time-stepping strategy designed to accelerate the progress to equilibrium. At each time step, a parallel Newton–Krylov–Schwarz algorithm is used to solve the nonlinear system. We discuss various numerical and computational challenges associated with the method. The numerical scheme is validated by a comparison with an explicit scheme of high accuracy (and unreasonably high cost). We present steady state solutions of the CHC equation in two and three dimensions. The effect of the thermal fluctuation on the spinodal decomposition process is studied. We show that the existence of the thermal fluctuation accelerates the spinodal decomposition process and that the final steady morphology is sensitive to the stochastic noise. We also show the evolution of the energies and statistical moments. In terms of the parallel performance, it is found that the implicit domain decomposition approach scales well on supercomputers with a large number of processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Flux-pumped impedance-engineered broadband Josephson parametric amplifier

Broadband quantum-limited amplifiers play a critical role in the single-shot readout of superconducting qubits, but a popular implementation, the traveling wave parametric amplifier, involves a complex design and fabrication process. Here, we present a simple design for a Josephson parametric amplifier, using a lumped element resonator comprising a superconducting quantum interference device whose useful bandwidth is enhanced with an on-chip impedance-matching circuit. Additionally, we demonstrate a flux-coupling geometry that maximizes the coupling to the Josepson loop and minimizes spurious excitation of the amplifier resonant circuit. The amplifier, which operates in a flux-pumped mode, is demonstrated with a power gain of more than 20dB over a bandwidth of about 300MHz, where approximate noise measurements indicate quantum-limited pehrformance. A procedure is given for optimizing the bandwidth for this kind of amplifier, using a linearized circuit simulation while minimizing non-linearities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1973

Analysis of noise produced by an orderly structure of turbulent jets

The orderly structure which has been observed recently by numerous researchers within the transition region of subsonic turbulent jets is analyzed to reveal its noise-producing potential. For a circular jet, this structure is molded as a train of toroidal vortex rings which are formed near the jet exit and propagate downstream. The noise produced by the model is evaluated from a reformulation of Lighthill's expression for the far-field acoustic density, which emphasizes the importance of the vorticity within the turbulent flow field. It is shown that the noise production occurs mainly close to the jet exit and depends primarily upon temporal changes in the toroidal radii. The analysis suggests that the process of formation of this regular structure may also be an important contribution of the high-frequency jet noise. These results may be helpful in the understanding of jet-noise generation and in new approaches to jet-noise suppression.

Hardin, J. C.↗
NASA NTRS1989

Estimating laser transit anemometry noise performance capabilities

A Monte Carlo based LTA (laser transit anemometry) simulation system has been used to perform a detailed evaluation of a set of processing algorithms proposed by Mayo and Smart (1984) for the extraction of two-dimensional flow parameters from LTA data sets collected in a plane normal to the optical axis of the system. The present evaluation includes data ensembles containing 0.0, 5.0, 10.0, and 20.0 percent background noise levels in the constituent correlograms. The results of these evaluations indicate that for turbulence levels of up to 10.0 percent the processing system is able to extract the necessary flow parameters accurately from the LTA data sets. Mean velocity magnitude and flow angle are measurable to within 2.0 percent for turbulence intensity levels of up to 14.0 percent. Standard deviations are measureable to within 10.0 percent over a turbulence range of 3.0-10.0 percent at the same noise levels. These results indicate that the algorithms described have applications in fluid flow surveys.

Humphreys, William M., Jr.↗
DOE OSTI2016

High-Field Stress, Low-Frequency Noise, and Long-Term Reliability of AlGaN/GaN HEMTs

A small degradation of threshold voltage and a significant reduction in dc and RF transconductance are observed for AlGaN/GaN high-electron-mobility transistors fabricated via three different process techniques and subjected to high voltage stress in the semi-ON bias condition. Low-frequency noise measurements as a function of temperature show peaks at ~0.2, ~0.5, ~0.7, and/or ~0.8 eV that increase with the magnitude and duration of high-field stress. The dehydrogenation of passivated Fe and O impurity defects and/or N antisite defects leads to increased charge trapping, noise, and transconductance degradation. Density functional theory calculations show that Ga vacancy motion and dehydrogenation of substitutional Fe complexes in the GaN buffer layer also contribute significantly to the poststress degradation of these devices. At higher stress voltages, these defects also likely contribute to device failure.

1/f noise↗
DOE OSTI2016

Noise power spectrum of the fixed pattern noise in digital radiography detectors

Purpose: The fixed pattern noise in radiography image detectors is caused by various sources. Multiple readout circuits with gate drivers and charge amplifiers are used to efficiently acquire the pixel voltage signals. However, the multiple circuits are not identical and thus yield nonuniform system gains. Nonuniform sensitivities are also produced from local variations in the charge collection elements. Furthermore, in phosphor-based detectors, the optical scattering at the top surface of the columnar CsI growth, the grain boundaries, and the disorder structure causes spatial sensitivity variations. These nonuniform gains or sensitivities cause fixed pattern noise and degrade the detector performance, even though the noise problem can be partially alleviated by using gain correction techniques. Hence, in order to develop good detectors, comparative analysis of the energy spectrum of the fixed pattern noise is important. Methods: In order to observe the energy spectrum of the fixed pattern noise, a normalized noise power spectrum (NNPS) of the fixed pattern noise is considered in this paper. Since the fixed pattern noise is mainly caused by the nonuniform gains, we call the spectrum the gain NNPS. We first asymptotically observe the gain NNPS and then formulate two relationships to calculate the gain NNPS based on a nonuniform-gain model. Since the gain NNPS values are quite low compared to the usual NNPS, measuring such a low NNPS value is difficult. By using the average of the uniform exposure images, a robust measuring method for the gain NNPS is proposed in this paper. Results: By using the proposed measuring method, the gain NNPS curves of several prototypes of general radiography and mammography detectors were measured to analyze their fixed pattern noise properties. We notice that a direct detector, which is based on the a-Se photoconductor, showed lower gain NNPS than the indirect-detector case, which is based on the CsI scintillator. By comparing the gain NNPS curves of the indirect detectors, we could analyze the scintillator properties depending on the techniques for the scintillator surface processing. Conclusions: A robust measuring method for the NNPS of the fixed pattern noise of a radiography detector is proposed in this paper. The method can measure a stable gain NNPS curve, even though the fixed pattern noise level is quite low. From the measured gain NNPS curves, we can compare and analyze the detector properties in terms of producing the fixed pattern noise.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Sound Generation in the Presence of Moving Surfaces with Application to Internally Generated Aircraft Engine Noise

In many cases of technological interest solid boundaries play a direct role in the aerodynamic sound generation process and their presence often results in a large increase in the acoustic radiation. A generalized treatment of the emission of sound from moving boundaries is presented. The approach is similar to that of Ffowcs Williams and Hawkings (1969) but the effect of the surrounding mean flow is explicitly accounted for. The results are used to develop a rational framework for the prediction of internally generated aero-engine noise. The final formulas suggest some new noise sources that may be of practical significance.

Goldstein, Marvin E.↗
NASA NTRS2016

Toward Reduced Aircraft Community Noise Impact Via a Perception-Influenced Design Approach

This is an exciting time for aircraft design. New configurations, including small multi-rotor uncrewed aerial systems, fixed- and tilt-wing distributed electric propulsion aircraft, high-speed rotorcraft, hybrid-electric commercial transports, and low-boom supersonic transports, are being made possible through a host of propulsion and airframe technology developments. The resulting noise signatures may be radically different, both spectrally and temporally, than those of the current fleet. Noise certification metrics currently used in aircraft design do not necessarily reflect these characteristics and therefore may not correlate well with human response. Further, as operations and missions become less airport-centric, e.g., those associated with on-demand mobility or package delivery, vehicles may operate in closer proximity to the population than ever before. Fortunately, a new set of tools are available for assessing human perception during the design process in order to affect the final design in a positive manner. The tool chain utilizes system noise prediction methods coupled with auralization and psychoacoustic testing, making possible the inclusion of human response to noise, along with performance criteria and certification requirements, into the aircraft design process. Several case studies are considered to illustrate how this approach could be used to influence the design of future aircraft.

Rizzi, Stephen A.↗
DOE OSTI2017

A Monte Carlo method for the simulation of coagulation and nucleation based on weighted particles and the concepts of stochastic resolution and merging

Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named ‘stochastic resolution’ in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope of a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named ‘random removal’ in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Ultra-Low Noise Germanium Neutrino Detection system (ULGeN).

Monitoring nuclear power plant operation by measuring the antineutrino flux has become an active research field for safeguards and non-proliferation. We describe various efforts to demonstrate the feasibility of reactor monitoring based on the detection of the Coherent Neutrino Nucleus Scattering (CNNS) process with High Purity Germanium (HPGe) technology. CNNS detection for reactor antineutrino energies requires lowering the electronic noise in low-capacitance kg-scale HPGe detectors below 100 eV as well as stringent reduction in other particle backgrounds. Existing state- of-the-art detectors are limited to an electronic noise of 95 eV-FWHM. In this work, we employed an ultra-low capacitance point-contact detector with a commercial integrated circuit preamplifier- on-a-chip in an ultra-low vibration mechanically cooled cryostat to achieve an electronic noise of 39 eV-FWHM at 43 K. We also present the results of a background measurement campaign at the Spallation Neutron Source to select the area with sufficient low background to allow a successful first-time measurement of the CNNS process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multiqubit noise deconvolution and characterization

We present a noise deconvolution technique for obtaining noiseless expectation values of noisy observables at the output of multiqubit quantum channels. For any number of qubits or in the presence of correlations, our protocol applies to any mathematically invertible noise model, even when its inverse map is not physically implementable, i.e., when it is neither completely positive nor trace preserving. For a generic observable affected by Pauli noise it provides a quadratic speedup, always producing a rescaling of its Pauli basis components. We show that it is still possible to achieve the deconvolution while experimentally estimating the noise parameters, whenever these are unknown (bypassing resource-heavy techniques such as quantum process tomography). We provide a simulation, with examples for both Pauli and non-Pauli channels.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1982

Role of empirical methods

There are different levels of helicopter noise prediction which may be appropriate at various stages in the design process. In the early preliminary design stages, when available information is usually limited to parameters such as gross weight, tip speed, forward speed, rotor radius, and possibly number of blades, one is limited to purely empirically based methodology. As the design progresses, and airfoil blade planforms and twists are defined, predictions of airloads, vortex paths, and compressibility effects may permit application of more analytically based sound pressure level prediction methods. At the present stage of development of first principle prediction methodology, however, the designer may still find it necessary to supplement such analyses with modifications based on empirical experience. Various causes and parameters of helicopter noise were identified and discussed from the standpoint of prediction. Rotational noise, blade-vortex interaction noise, thickness noise, broadband noise, and flyover noise were considered. A modular computer program for helicopter noise prediction (HELNOP) was described briefly. Wind tunnel models as useful tools in predicting full scale helicopter noise were also discussed.

Sternfeld, H.↗
NASA NTRS1978

On-board data processing for the IRAS telescope system

Onboard data processing has been developed for the Infrared Astronomical Satellite (IRAS) telescope system to effectively utilize the RF bandwidth and minimize the ground-data processing costs. Use of filtering techniques, data deglitching circuits, and data encoding algorithms are combined with a microprocessor-controlled telescope system to achieve a system dynamic range of 100,000 with a noise equivalent flux density of no less than 10 to the minus 19th W/sq cm. Extraneous data, e.g., noise due to radiation hits, will be removed prior to transmission, thereby optimizing ground-data processing for the highest sensitivity and reliability. Simulation results are presented which demonstrate the advantages gained through the use of onboard data processing and illustrate the possible merging of these techniques with an array for the future evolution of 'smart' sensors.

Lum, H.↗
NASA NTRS1995

Transient Structure Current Generated by the Activation of a Squib Device

Experimental measurements of the currents in pyro-activation circuits show that a structure current is generated during the pyro-activation process. This current is a transient current and is an intense source of electromagnetic interference. Analysis has indicated that the noise voltage induced on candidate victim circuits is sufficient to cause circuit upset and/or latchup. A survey of flight anomaly records has also correlated the occurrence of anomalies with the pyro-activation process. Detailed analyses, taking the spacecraft cabling configuration and circuit sensitivities into account, have shown that the structure current induced noise voltage could definitely be the cause of the anomalies. The threat of the structure current due to pyro-activation can be alleviated by isolating the pyro-activation circuit from ground and by proper arrangement of the cables in sensitive circuits.

pyrotechnic↗
DOE OSTI2022

Process prediction and detection of faults using probabilistic bidirectional recurrent neural networks on real plant data

Attaining Industry 4.0 for manufacturing operations requires advanced monitoring systems and real-time data analytics of plant data, among other topics. We propose a Probabilistic Bidirectional Recurrent Network (PBRN) for industrial process monitoring for the early detection of faults. The model is based on a Gated Recurrent Unit (GRU) neural network that allows the model to retain long-term dependencies between sensor data along a time horizon, hence learning the dynamic behavior of the process. To reduce the false-positive detection rate of the model, we compel the model to learn from a highly noisy sensor reading while outputting noise-free sensor outputs. The performance of the proposed model is compared to other data-driven statistical process monitoring schemes using real plant data from an industrial Air Separations Unit (ASU) containing noisy sensor readings. We show that the model can learn from noisy data without reducing its performance. Using two different fault cases, we demonstrate the model’s ability to carry out early fault detection with average false-positive rates of 2.9% and 4.9% for both fault cases. The missed detection rates are 0.1% and 0.2%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

Design and Stress Analysis of Low-Noise Adjusted Bearing Contact Spiral Bevel Gears

An integrated computerized approach for design and stress analysis of low-noise spiral bevel gear drives with adjusted bearing contact is proposed. The procedure of computations is an iterative process that requires four separate procedures and provide: (a) a parabolic function of transmission errors that is able to reduce the effect of errors of alignment on noise and vibration, and (b) reduction of the shift of bearing contact caused by misalignment. Application of finite element analysis enables us to determine the contact and bending stresses and investigate the formation of the bearing contact. The design of finite element models and boundary conditions is automated and does not require intermediate CAD computer programs for application of general purpose computer program for finite element analysis.

Fuentes, A.↗
NASA NTRS1971

Bayesian recursive image estimation.

A procedure for recursively estimating images that are characterized statistically by the mean and correlation functions associated with the random process representing the brightness level is proposed for the case where the images are corrupted by additive noise. First, a dynamic model is developed with a response characteristic which matches that of the scanner output (the input of the estimator is the output of a horizontal line scanner) in a statistical sense. Such models have the form of an ordinary differential or difference equation with white noise input. An insignificant approximation is introduced by using a constant-coefficient model. The appropriate model is a vector valued difference equation with the solution representing a vector Markov process. The next step is to obtain the minimum mean square estimate of the image by using a Kalman filter. Since the image estimation is an interpolation problem, two successive runs over the observation are performed in opposite directions and the resultant estimates are averaged. Examples are included for illustration.

Nahi, N. E.↗