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Results for “input estimation”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mid- to long-wave infrared computational spectroscopy with a graphene metasurface modulator

In recent years there has been much interest concerning the development of modulators in the mid- to long-wave infrared, based on emerging materials such as graphene. These have been frequently pursued for optical communications, though also for other specialized applications such as infrared scene projectors. Here we investigate a new application for graphene modulators in the mid- to long-wave infrared. We demonstrate, for the first time, computational spectroscopy in the mid- to long-wave infrared using a graphene-based metasurface modulator. Furthermore, our metasurface device operates at low gate voltage. To demonstrate computational spectroscopy, we provide our algorithm with the measured reflection spectra of the modulator at different gate voltages. We also provide it with the measured reflected light power as a function of the gate voltage. The algorithm then estimates the input spectrum. We show that the reconstructed spectrum is in good agreement with that measured directly by a Fourier transform infrared spectrometer, with a normalized mean-absolute-error (NMAE) of 0.021.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measurement of the ionization response of amorphous selenium with 122 keV γ rays

In this work, we performed a measurement of the ionization response of 200 μm-thick amorphous selenium (aSe) layers under drift electric fields of up to 50 V/μm. The aSe target was exposed to ionizing radiation from a 57 Co radioactive source and the ionization pulses were recorded with high resolution. Using the spectral line from the photoabsorption of 122 keV γ rays, we measured the charge yield in aSe and the line width as a function of drift electric field. From a detailed microphysics simulation of charge generation and recombination in aSe, we conclude that the strong dependence of recombination on the ionization track density provides the dominant contribution to the energy resolution in aSe. These results provide valuable input to estimate the sensitivity of a proposed next-generation search for the neutrinoless ββ decay of 82 Se that aims to employ imaging sensors with an active layer of aSe. We estimate the RMS line width of the integrated ionization signal from neutrinoless ββ decay events (of deposited energy 3 MeV) to be 2.0% for a drift field of 50 V/μm. The energy resolution can be improved to 1% by correcting for the charge yield as a function of ionization density along the imaged electron tracks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Diverse Super-Resolution (diversity_SR) [SWR-21-60]

Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.

Glaws, Andrew↗
DOE OSTI2020

Distributed Generation Market Demand (dGen) model

The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sectors, locations, and customers for whom adopting DERs would have a high economic value, for generating forecasts as an input to estimate distribution hosting capacity analysis, integrated resource planning, and load forecasting, and for understanding the economic or policy conditions in which DER adoption becomes viable, and for illustrating sensitivity to market and policy changes such as retail electricity rate structures, net energy metering, and technology costs.

Array↗
DOE OSTI2024

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗
NASA NTRS1972

The global energy budget of the thermosphere.

Experimental neutral atmospheric density and temperature profiles can be used to calculate the energy content variations of a given region as a function of time, season and location for which the data are available. Such calculations may then be compared with estimated energy inputs and losses to determine what other mechanisms may be important. In the present paper a model based on both incoherent scatter data from Arecibo, Nancay, and Jicamarca and satellite density measurements is used to derive the global distributions of thermal energy content and losses in the thermosphere. The energy sources and transport mechanisms required for global thermal balance are then discussed.

Swartz, W. E.↗
NASA NTRS1974

Optimal space communications techniques

The encoding of video signals using the Song Adaptive Delta Modulator (Song ADM) is discussed. The video signals are characterized as a sequence of pulses having arbitrary height and width. Although the ADM is suited to tracking signals having fast rise times, it was found that the DM algorithm (which permits an exponential rise for estimating an input step) results in a large overshoot and an underdamped response to the step. An overshoot suppression algorithm which significantly reduces the ringing while not affecting the rise time is presented along with formuli for the rise time and the settling time. Channel errors and their effect on the DM encoded bit stream were investigated.

Schilling, D. L.↗
NASA NTRS1976

Data acquisition and path selection decision making for an autonomous roving vehicle

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.

Frederick, D. K.↗
NASA NTRS1977

Prediction of the bulk temperature in spur gears based on finite element temperature analysis

The temperature distribution in spur gears operating in a state of thermal equilibrium is solved by using a finite element method. The effects of various dimensionless parameters on bulk temperature are shown. A table is provided which can be used to predict the bulk temperature on gear teeth, once the heat transfer coefficients and frictional heat input is estimated. Theoretical results for estimating heat transfer coefficients and frictional heat are also summarized.

Patir, N.↗
NASA NTRS1980

Coronal heating by stochastic magnetic pumping

Recent observational data cast serious doubt on the widely held view that the Sun's corona is heated by traveling waves (acoustic or magnetohydrodynamic). It is proposed that the energy responsible for heating the corona is derived from the free energy of the coronal magnetic field derived from motion of the 'feet' of magnetic field lines in the photosphere. Stochastic motion of the feet of magnetic field lines leads, on the average, to a linear increase of magnetic free energy with time. This rate of energy input is calculated for a simple model of a single thin flux tube. The model appears to agree well with observational data if the magnetic flux originates in small regions of high magnetic field strength. On combining this energy input with estimates of energy loss by radiation and of energy redistribution by thermal conduction, we obtain scaling laws for density and temperature in terms of length and coronal magnetic field strength.

Sturrock, P. A.↗
NASA NTRS1981

Coronal heating by stochastic magnetic pumping

Recent observational data cast serious doubt on the widely held view that the sun's corona is heated by traveling waves (acoustic or magnetohydrodynamic). It is here proposed that the energy responsible for heating the corona is derived from the free energy of the coronal magnetic field derived from motion of the 'feet' of magnetic field lines in the photosphere. Stochastic motion of the feet of magnetic field lines leads, on the average, to a linear increase of magnetic free energy with time. This rate of energy input is calculated for a simple model of a single thin flux tube. The model appears to agree well with observational data if the magnetic flux originates in small regions of high magnetic field strength as proposed by Tarbell et al. (1979). On combining this energy input with estimates of energy loss by radiation and of energy redistribution by thermal conduction, scaling laws are obtained for density and temperature in terms of length and coronal magnetic field strength.

Sturrock, P. A.↗
NASA NTRS1984

Determination of rainfall and condensational heating in the South Pacific convergence zone during FGGE SOP-1

The role of cloud related diabatic processes in maintaining the structure of the South Pacific Convergence Zone is discussed. The method chosen to evaluate the condensational heating is a diagnostic cumulus mass flux technique which uses GOES digital IR data to characterize the cloud population. This method requires as input an estimate of time/area mean rainfall rate over the area in question. Since direct observation of rainfall in the South Pacific is not feasible, a technique using GOES IR data is being developed to estimate rainfall amounts for a 2.5 degree grid at 12h intervals.

Robertson, F. R.↗
NASA NTRS1986

The chemical control of soluble phosphorus in the Amazon estuary

The role of sediments in controlling concentrations of soluble phosphorous in the Amazon estuary is examined. The efflux of phosphorous through the estuary is calculated using data collected on field excursions in December 1982 and May 1983, and laboratory mixing experiments. It is observed that soluble phosphorus was released from bottom sediments at a rate of 0.2 micro-M/day, when in seawater and deionizd water mixtures. The relation between release rates and salinity and sediment concentrations is studied. A one-dimensional dispersion model was developed to estimate phosphate inputs to the estuary. The model predicted total fluxes of soluble inorganic phosphorous of 15 x 10 to the 6th mole/day for December 1982 and 27 x 10 to the 6th mole/day for May 1983; the predictions correlate with field observations. It is noted that phosphorous removal is between 0 and 4 ppt at a rate of 0.044 + or - 0.01 micron-M/ppt per day and the annual mean input of phophorous from Amazon to outer-estuary is 23 x 10 to the 6th moles/day.

Fox, L. E.↗
NASA NTRS1988

Extension of synthetic estimation filters for relative position measurements

The construction of synthetic estimation filters (SEF) for out-of-plane rotation is reported. When images corresponding to rotations between the angles which were used to construct the estimator were input to the simulator, the yaw measurement accuracy was a little better than one-half of a degree over the five degree range. If individual phase-only filters were used and the only criteria for yaw angle was 'best correlation', 11 filter would be required for the same range and accuracy. The technique proposed here is invariant to translation.

Monroe, Stanley E., Jr.↗
NASA NTRS1989

Two novel automatic frequency tracking loops

Two automatic-frequency-control (AFC) loops are introduced and analyzed in detail. The algorithms are generalizations of the well known cross-product AFC loop with improved performance. The first estimator uses running overlapping discrete Fourier transforms to create a discriminator curve proportional to the frequency estimation error, whereas the second one preprocesses the received data and then uses an extended Kalman filter to estimate the input frequency. The algorithms are tested by computer simulations in a highly dynamic environment at low carrier/noise ratio (CNR). The algorithms are suboptimum tracking schemes with a larger frequency-error variance compared to an optimum strategy, but they offer simplicity of mechanization and a CNR with a very low operating threshold.

Aguirre, Sergio↗