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.
DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data
Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.
New approach to the design of Schottky barrier diodes for THz mixers
Near-ideal GaAs Schottky barrier diodes especially designed for mixing applications in the THz frequency range are presented. A diode fabrication process for submicron diodes with near-ideal electrical and noise characteristics is described. This process is based on the electrolytic pulse etching of GaAs in combination with an in-situ platinum plating for the formation of the Schottky contacts. Schottky barrier diodes with a diameter of 1 micron fabricated by the process have already shown excellent results in a 650 GHz waveguide mixer at room temperature. A conversion loss of 7.5 dB and a mixer noise temperature of less than 2000 K have been obtained at an intermediate frequency of 4 GHz. The optimization of the diode structure and the technology was possible due to the development of a generalized Schottky barrier diode model which is valid also at high current densities. The common diode design and optimization is discussed on the basis of the classical theory. However, the conventional fomulas are valid only in a limited forward bias range corresponding to currents much smaller than the operating currents under submillimeter mixing conditions. The generalized new model takes into account not only the phenomena occurring at the junction such as current dependent recombination and drift/diffusion velocities, but also mobility and electron temperature variations in the undepleted epi-layer. Calculated diode I/V and noise characteristics are in excellent agreement with the measured values. Thus, the model offers the possibility of optimizing the diode structure and predicting the diode performance under mixing conditions at THz frequencies.
Fluid dynamic aspects of jet noise generation
The propagation of sound waves inside a jet (single or multiple) was studied with particular attention to refraction of ray trajectories and distortion of wave profile due to nonlinear effects. An experimental method is used in studying this phenomenon which consists of injecting from outside the jet, at one or various points near the mixing zone, a set of pressure signals, and detecting them with one or more microphones placed inside the jet. The signals are detected in the presence of the background noise of the jet itself. Signal processing and instrumentation are discussed along with noise detection.
Improved Broadband Liner Optimization Applied to the Advanced Noise Control Fan
The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more desirable. This paper describes improvements to a previously established broadband acoustic liner optimization process using the Advanced Noise Control Fan rig as a demonstrator. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom designs are carried through design, fabrication, and testing to validate the efficacy of the design process. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of these liner designs. This study also provides an application for demonstrating the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.
AAFE man-made noise experiment project. Volume 2: Project and experiment discussions
An experiment for the acquisition and processing of man-made noise interference data on earth orbital altitudes is discussed. The objectives of the project are to confirm the results of analytical studies concerning radio frequency man-made noise in space. It is stated that the measurements of the amounts and types of noise in frequency bands of interest could allow the allocation and utilization of frequencies to be optimized and would also contribute to the engineering objective of optimizing flight receiving systems. A second objective of the project was to design and fabricate a noise measuring receiver which would demonstrate the feasibility of the experiment design under the project. The procedures for acquiring and processing the electromagnetic radiation data are discussed.
Characterization of contaminants in the Lyman-alpha forest auto-correlation with DESI
Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-α (Lyα) forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants to the Lyα forest which are mainly caused by correlated signals introduced by the spectroscopic data processing pipeline as well as astrophysical contaminants due to foreground absorption in the intergalactic medium. Notably, an excess signal caused by the sky background subtraction noise is present in the Lyα auto-correlation in the first line-of-sight separation bin. We use synthetic data to isolate this contribution, we also characterize the effect of spectro-photometric calibration noise, and propose a simple model to account for both effects in the analysis of the Lyα forest. We then measure the auto-correlation of the quasar flux transmission fraction of low redshift quasars, where there is no Lyα forest absorption but only its contaminants. We demonstrate that we can interpret the data with a two-component model: data processing noise and triply ionized Silicon and Carbon auto-correlations. This result can be used to improve the modeling of the Lyα auto-correlation function measured with DESI.
Reducing Centroid Error Through Model-Based Noise Reduction
A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.
Optimum linear filtering of an integrated signal in white noise.
Optimum linear filtering of integrated signal in white noise, deriving expression for minimum mean square error
Temporal Coarse Graining for Classical Stochastic Noise in Quantum Systems
Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for 1/f noise in solid-state quantum information processors. Here we present an approach for simulating Hamiltonian classical stochastic noise that performs temporal coarse-graining by effectively integrating out the high-frequency components of the noise. We focus on the case where the stochastic noise can be expressed as a sum of Ornstein-Uhlenbeck processes. Temporal coarse-graining is then achieved by conditioning the stochastic process on a coarse realization of the noise, expressing the conditioned stochastic process in terms of a sum of smooth, deterministic functions and bridge processes with boundaries fixed at zero, and performing the ensemble average over the bridge processes. For Ornstein-Uhlenbeck processes, the deterministic components capture all dependence on the coarse realization, and the stochastic bridge processes are not only independent but taken from the same distribution with correlators that can be expressed analytically, allowing the associated noise propagators to be precomputed once for all simulations. This combination of noise trajectories on a coarse time grid and ensemble averaging over bridge processes has practical advantages, such as a simple concatenation rule, that we highlight with numerical examples.
An analytical method for designing low noise helicopter transmissions
The development and experimental validation of a method for analytically modeling the noise mechanism in the helicopter geared power transmission systems is described. This method can be used within the design process to predict interior noise levels and to investigate the noise reducing potential of alternative transmission design details. Examples are discussed.
Perturbative model of noisy quantum signal processing
Recent progress in quantum signal processing (QSP) and its generalization, quantum singular value transformation, has led to a grand unification of quantum algorithms. However, inherent experimental noise in quantum devices severely limits the length of realizable QSP sequences. Here, we consider a model of QSP with generic perturbative noise in the signal processing basis and present a diagrammatic notation useful for analyzing such errors. To demonstrate our technique, we study a specific coherent error, that of under- or overrotation of the signal processing operator parametrized by ε<<1. For this coherent error model, it is shown that while Pauli Z errors are not recoverable without additional resources, Pauli X and Y errors can be arbitrarily suppressed by coherently appending a noisy recovery QSP without the use of additional resources or ancillas. Furthermore, through a careful accounting of errors using our diagrammatic tools, we provide an upper and lower bound on the length of this recovery QSP operator. We anticipate that the perturbative technique and the diagrammatic notation proposed here will facilitate future study of generic noise in QSP and quantum algorithms.
Modeling of Broadband Liners Applied to the Advanced Noise Control Fan
The broadband component of fan noise has grown in relevance with an increase in bypass ratio and incorporation of advanced fan designs. Therefore, while the attenuation of fan tones remains a major factor in engine nacelle acoustic liner design, the simultaneous reduction of broadband fan noise levels has received increased interest. As such, a previous investigation focused on improvements to an established broadband acoustic liner optimization process using the Advanced Noise Control Fan (ANCF) rig as a demonstrator. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom liner designs were carried through design, fabrication, and testing. This paper addresses a number of areas for further research identified in the initial assessment of the ANCF study. Specifically, incident source specification and uncertainty in some aspects of the predicted liner impedances are addressed. This information is incorporated in updated predictions of the liner performance and comparisons with measurement are greatly improved. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of various liner designs. This study also provides further confidence in the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.
Analysis of combustion acoustic phenomena in compression–ignition engines using large eddy simulation
As computational capabilities continue to grow, exploring the limits of computational fluid dynamics to capture complex and elusive phenomena, which are otherwise difficult to study by experimental techniques, is one of the main targets for the research community. This paper presents a detailed analysis of the physical processes that lead to combustion noise emissions in internal combustion engines. In particular, diesel combustion in a compression-ignition (CI) engine is studied in order to understand the singular behavior of the in-cylinder flow field responsible for the acoustic emissions. The main objective is, therefore, to improve the understanding of the phenomena involved in CI engine noise using large eddy simulations. Several visualization methods are employed to investigate the connection between combustion behavior and its effects on the pressure field. In addition, proper orthogonal decomposition is used to analyze the modal energy distribution among all the acoustic modes. The results show that the acoustic signature is fundamentally conditioned by the intensity of the premixed combustion rather than by the pressure oscillations generated by turbulent fluctuations in the flame surface established during the diffusion stage.
Remote Sensing Time Series Product Tool
The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.
Noise and Dynamical Pattern Selection in Solidification
The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.
Detection in fixed and random noise in foveal and parafoveal vision explained by template learning
Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.
Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for characterizing radiated noise from marine energy converters
Marine energy converters can generate electricity from energetic ocean waves and water currents. Because sound is extensively used by marine animals, the radiated noise from these systems is of regulatory interest. However, the energetic nature of these locations poses challenges for performing accurate passive acoustic measurements, particularly with stationary platforms. The Drifting Acoustic Instrumentation SYstem (DAISY) is a modular hydrophone recording system purpose-built for marine energy environments. Using a flow shield in currents and mass–spring–damper suspension system in waves, we demonstrate that DAISYs can effectively minimize the masking effect of flow noise at frequencies down to 10 Hz. In addition, we show that groups of DAISYs can utilize time-delay-of-arrival post-processing to attribute radiated noise to a specific source. Consequently, DAISYs can rapidly measure radiated noise at all frequencies of interest for prototype marine energy converters. Furthermore, the resulting information from future operational deployments should support regulatory decision-making and allow technology developers to make design adjustments that minimize the potential for acoustic impacts as their systems are scaled up for utility-scale power generation.