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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Analysis of Near Simultaneous Jimsphere and AMPS High Resolution Wind Profiles

The high-resolution wind profile of the Automated Meteorological Profiling System (HRAMPS) is the proposed replacement for the Jimsphere measurement system used to support NASA Shuttle launches from the Eastern Test Range (ETR). Samples of twenty-six ETR near simultaneous Jimsphere and HRAMPS wind profiles were obtained for Shuttle program HRAMPS certification studies. Shuttle systems engineering certification is to ensure that spacecraft and launch vehicle systems performance and safety evaluations for each launch (derived from flight simulations with Jimsphere wind profile data bases) retain their validity when HRAMPS profiles are used on day-of-launch (DOL) in trajectory and loads simulations to support the commit-to-launch decision. This paper describes a statistical analysis of the near simultaneous profiles. In principle the differences between a Jimsphere profile and an HRAMPS profile should be attributed to tracking technology (radar versus GPS tracking of a Jimsphere flight element) and the method for derivation of wind vectors from the raw tracking data. In reality, it is not technically feasible to track the same Jimsphere balloon with the two systems. The aluminized Mylar surface of the standard Jimsphere flight element facilitates radar tracking, but it interferes with HRAMPS during simultaneous tracking. Suspending a radar reflector from an HRAMPS flight element (Jimsphere without aluminized coating) does not produce satisfactory Jimsphere profiles because of intermittent radar returns. Thus, differences between the Jimsphere and HRAMPS profiles are also attributed to differences in the trajectories of separate flight elements. Because of small sample size and a test period limited to one winter season, test measurements during extreme high winds aloft could not have been expected and did not occur. It is during the highest winds that the largest differences between Jimsphere and HRAMPS would occur because the distance between flight elements would be larger. Jimsphere radar tracking noise increases as a function of balloon displacement downrange. The Jimsphere data processing compensates for tracking signal/noise degradation by increasing the smoothing interval. The Jimsphere wind profile effective resolution is a function of downrange distance and altitude, whereas the effective resolution of the HRAMPS should be independent of those variables. The procedure used for editing Jimsphere spikes in Shuttle DOL profiles was not implemented for the Jimsphere profile measurements during the AMPS field tests. For this analysis a code was developed that essentially mimics DOL Jimsphere spike editing. Jimsphere profiles have somewhat more noise in the wavelength range less than 200m defined as the noise floor. No differences between Jimsphere and HRAMPS wind profile pairs have been found that would support denial of HRAMPS certification for application in Shuttle DOL applications. The reliability of the HRAMPS system, which is an important certification issue, is not addressed in this study.

Adelfang, S. I.↗
NASA NTRS1978

A sequential method for spline approximation with variable knots

In this paper we describe a method for approximating a waveform by a spline. The method is quite efficient, as the data are processed sequentially. The basis of the approach is to view the approximation problem as a question of estimation of a polynomial in noise, with the possibility of abrupt changes in the highest derivative. This allows us to bring several powerful statistical signal processing tools into play. We also present some initial results on the application of our technique to the processing of electrocardiograms, where the knot locations themselves may be some of the most important pieces of diagnostic information.

Mier Muth, A. M.↗
NASA NTRS1992

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗
NASA NTRS1993

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks.

Chien, Steve↗
NASA NTRS1990

Method for providing a polarization filter for processing synthetic aperture radar image data

A polarization filter can maximize the signal-to-noise ratio of a polarimetric synthetic aperture radar (SAR) and help discriminate between targets or enhance image features, e.g., enhance contrast between different types of target. The method disclosed is based on the Stokes matrix/ Stokes vector representation, so the targets of interest can be extended targets, and the method can also be applied to the case of bistatic polarimetric radars.

Dubois, Pascale C.↗
NASA NTRS1991

Method for providing a polarization filter for processing synthetic aperture radar image data

A polarization filter can maximize the signal-to-noise ratio of a polarimetric SAR and help discriminate between targets or enhance image features, e.g., enhance contract between different types of target. The method disclosed is based on the Stokes matrix/Stokes vector representation, so the targets of interest can be extended targets, and the method can also be applied to the case of bistatic polarimetric radars.

Dubois, Pascale C.↗
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.↗
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 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.↗