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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Pneumatic distortion compensation for aircraft surface pressure sensing devices

In this paper a technique of compensating for pneumatic distortion in aircraft surface pressure sensing devices is developed. The compensation allows conventional pressure sensing technology to obtain improved unsteady pressure measurements. Pressure distortion caused by frictional attenuation and pneumatic resonance within the sensing system makes obtaining unsteady pressure measurements by conventional sensors difficult. Typically, most of the distortion occurs within the pneumatic tubing used to transmit pressure impulses from the surface of the aircraft to the measurement transducer. This paper develops a second-order distortion model that accurately describes the behavior of the primary wave harmonic of the pneumatic tubing. The model is expressed in state-variable form and is coupled with standard results from minimum-variance estimation theory to develop an algorithm to compensate for the effects of pneumatic distortion. Both postflight and real-time algorithms are developed and evaluated using simulated and flight data. Covariance selection and filter-tuning examples are presented. Results presented verify that, given appropriate covariance magnitudes, the algorithms accurately reconstruct surface pressure values from remotely sensed pressure measurements.

Whitmore, Stephen A.↗
NASA NTRS1995

Colliding Winds and Tomography of O-Type Binaries

This grant was awarded in support of an observational study with the NASA IUE Observatory during the 15th episode (1992), and it subsequently also supported our continuing work in 16th (1994) and 18th (1995) episodes. The project involved the study of FUV spectra of massive spectroscopic binary systems containing hot stars of spectral type O. We applied a Doppler tomography algorithm to reconstruct the individual component UV spectra of stars in order to obtain improved estimates of the temperature, gravity, UV intensity ratio, and projected rotational velocity for stars in each system, and to make a preliminary survey for abundance anomalies through comparison with standard spectra. We also investigated the orbital phase-related variations in the UV stellar wind lines to probe the geometries of wind-wind collisions in these systems. The project directly supported two Ph.D. dissertations at Georgia State University (by Penny and Thaller), and we are grateful for this support. No inventions were made in the performance of this work. Detailed results are summarized in the abstracts listed in the following section.

Gies, Dougles R.↗
NASA NTRS2009

Spatial Modulation Improves Performance in CTIS

Suitably formulated spatial modulation of a scene imaged by a computed-tomography imaging spectrometer (CTIS) has been found to be useful as a means of improving the imaging performance of the CTIS. As used here, "spatial modulation" signifies the imposition of additional, artificial structure on a scene from within the CTIS optics. The basic principles of a CTIS were described in "Improvements in Computed- Tomography Imaging Spectrometry" (NPO-20561) NASA Tech Briefs, Vol. 24, No. 12 (December 2000), page 38 and "All-Reflective Computed-Tomography Imaging Spectrometers" (NPO-20836), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 7a. To recapitulate: A CTIS offers capabilities for imaging a scene with spatial, spectral, and temporal resolution. The spectral disperser in a CTIS is a two-dimensional diffraction grating. It is positioned between two relay lenses (or on one of two relay mirrors) in a video imaging system. If the disperser were removed, the system would produce ordinary images of the scene in its field of view. In the presence of the grating, the image on the focal plane of the system contains both spectral and spatial information because the multiple diffraction orders of the grating give rise to multiple, spectrally dispersed images of the scene. By use of algorithms adapted from computed tomography, the image on the focal plane can be processed into an image cube a three-dimensional collection of data on the image intensity as a function of the two spatial dimensions (x and y) in the scene and of wavelength (lambda). Thus, both spectrally and spatially resolved information on the scene at a given instant of time can be obtained, without scanning, from a single snapshot; this is what makes the CTIS such a potentially powerful tool for spatially, spectrally, and temporally resolved imaging. A CTIS performs poorly in imaging some types of scenes in particular, scenes that contain little spatial or spectral variation. The computed spectra of such scenes tend to approximate correct values to within acceptably small errors near the edges of the field of view but to be poor approximations away from the edges. The additional structure imposed on a scene according to the present method enables the CTIS algorithms to reconstruct acceptable approximations of the spectral data throughout the scene.

Bearman, Gregory H.↗
NASA NTRS2019

PERISCOPE: PERIapsis Subsurface Cave OPtical Explorer

In this NIAC report we present a new technique enabling a practical option for mapping these structures at a relatively low cost: Photon Time-of-Flight (PTOF) imaging. Consider a scene with a surface that is in a camera's line of sight, with unknown geometry beyond the line of sight. PTOF works by directing laser pulses onto the visible surface and detecting the returned light after it reflects off the visible surface, onto the hidden surfaces, and back to the detector. An algorithm then reconstructs a 3d model of the hidden surface. The information gained has a wide variety of applications across NASA, the scientific community, the burgeoning commercial space industry, and in commercial and industrial use here on Earth.

Exploration↗
NASA NTRS2019

Rapid Expansion of Northern Peatlands and Doubled Estimate of Carbon Storage

Northern peatlands are an integral part of the global carbon cycle—a strong sink of atmospheric carbon dioxide and source of methane. Increasing anthropogenic carbon dioxide and methane in the atmosphere are thought to strongly impact these environments, and yet, peatlands are not routinely included in Earth system models. Here we present a quantification of the sink and stock of northern peat carbon from the last glacial period through the pre-industrial period. Additional data and new algorithms for reconstructing the history of peat carbon accumulation and the timing of peatland initiation increased the estimate of total northern peat carbon stocks from 545 Gt to 1,055 Gt of carbon. Further, the post-glacial increases in peatland initiation rate and carbon accumulation rate are more abrupt than previously reported. Peatlands have been a strong carbon sink throughout the Holocene, but the atmospheric partial pressure of carbon dioxide has been relatively stable over this period. While processes such as permafrost thaw and coral reef development probably contributed some additional carbon to the atmosphere, we suggest that deep ocean upwelling was the most important mechanism for balancing the peatland sink and maintaining the observed stability.

Nichols, Jonathan E.↗
NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗
NASA NTRS1998

Forward Electromagnetic Scattering Models for Sea Ice

Recent advances in forward modeling of the electromagnetic scattering properties of sea ice are presented. The results have direct relevance to microwave remote sensing, and serve at the basis for inverse algorithms for reconstructing the physical properties of sea ice from scattering data.

Electromagnetic↗
NASA NTRSDate not supplied

Direct Reconstruction of Ablative Thermal Protection System Aeroheating Using A Green's Function Approach

A Green’s function inverse heat transfer (IHT) approach is used to reconstruct the surface heating conditions on ablative thermal protection system (TPS) materials from embedded heat flux sensor and temperature probe measurements. The approach models the temperature time-history at the measurement location as a discrete linear system, allowing for the heat flux boundary condition to be recovered directly without the need for time-marching schemes. The effects of material decomposition and pyrolysis gas transport are modeled using an energy source/sink analogue. The performance of the reconstruction approach is analyzed on a 1D test case representative of an atmospheric entry heating scenario. The approach can recover the TPS surface heat flux to within 4% of the input heating condition with a computation time of 2-3 seconds (>3 orders of magnitude faster than current time-marching IHT methods). As a byproduct of the surface heating reconstruction, the algorithm also captures the surface pyrolysis gas mass flux and solid decomposition at multiple through-thickness locations within the TPS.

Kenneth McAfee↗
DOE OSTI2021

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography *

Abstract Neutron computed tomography (NCT), a 3D non-destructive characterization technique, is carried out at nuclear reactor or spallation neutron source-based user facilities. Because neutrons are not severely attenuated by heavy elements and are sensitive to light elements like hydrogen, neutron radiography and computed tomography offer a complementary contrast to x-ray CT conducted at a synchrotron user facility. However, compared to synchrotron x-ray CT, the acquisition time for an NCT scan can be orders of magnitude higher due to lower source flux, low detector efficiency and the need to collect a large number of projection images for a high-quality reconstruction when using conventional algorithms. As a result of the long scan times for NCT, the number and type of experiments that can be conducted at a user facility is severely restricted. Recently, several deep convolutional neural network (DCNN) based algorithms have been introduced in the context of accelerating CT scans that can enable high quality reconstructions from sparse-view data. In this paper, we introduce DCNN algorithms to obtain high-quality reconstructions from sparse-view and low signal-to-noise ratio NCT data-sets thereby enabling accelerated scans. Our method is based on the supervised learning strategy of training a DCNN to map a low-quality reconstruction from sparse-view data to a higher quality reconstruction. Specifically, we evaluate the performance of two popular DCNN architectures—one based on using patches for training and the other on using the full images for training. We observe that both the DCNN architectures offer improvements in performance over classical multi-layer perceptron as well as conventional CT reconstruction algorithms. Our results illustrate that the DCNN can be a powerful tool to obtain high-quality NCT reconstructions from sparse-view data thereby enabling accelerated NCT scans for increasing user-facility throughput or enabling high-resolution time-resolved NCT scans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1998

Beta in Streamers

Streamers are generally described as regions of the corona in which the density is higher than in coronal holes because the plasma is trapped by closed loops of magnetic flux. In contrast, MHD models of the global corona show the plasma beta in streamers above siml.2R_S (heliocentric). There are three recent contributions to this topic. The first is that heating near the cusp further drives beta up and results in release of new slow solar wind plasma from the top of the streamer. The second is SOHO/UVCS observations, in combination with a potential field/source surface model of the magnetic field, that show beta above 1.2R_S in a streamer observed near solar sunspot minimum. The third is a magnetic field reconstruction technique that uses field deforming algorithms and is more versatile for local fields than potential field models . The field reconstruction algorithm was applied to an isolated active region (AR 7999) and to the Pneuman Kopp global MHD model (beta has never been published for their model). In the active region, beta becomes larger than unity at siml.2 R_S. In the Pneuman & Kopp model, beta at the base of the streamer and rises with increasing height, becoming 15-20 at 1.6R_S and 35- 50 at 1.7R_S. Global simulations go on to show that the reason streamers do not simply explode under such high beta conditions is that they are held down by pressure from the sides due to the magnetic fields (and low beta) in adjacent coronal holes. The main role of the closed magnetic loop near the cusp is to keep the steamer from continuously leaking plasma, as otherwise happens in a magnetic pinch which is similar but has no closed loops. Awareness of MHD physical conditions in streamers is causing us to focus more attention on the details of the heating. On obvious suggestion is that heating is at much lower heights in streamers than in coronal holes. Also, energy which is directly delivered as momentum in coronal holes might all be deposited as heat in streamers.

Suess, Steven T.↗
NASA NTRS1985

Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction

The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the space shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.

Whitmore, S. A.↗
NASA NTRS1985

Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction

The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the Space Shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.

Whitmore, S. A.↗
NASA NTRS1989

Application of adaptive least-squares algorithm to multi-element array signal reconstruction

Results are presented in terms of the performance improvement of a multi-feed array configuration over the usual single feed system when an adaptive least-squares algorithm is applied for the signal reconstruction. Two versions of the least-squares algorithm are presented, one of which is based on the maximization of the signal-to-noise ratio while the other is based on the deconvolution of received signal field. These algorithms were developed for the purpose of minimizing degradations arising from various sources, which can severely limit the performance (gain) of a single-feed system.

Kumar, R.↗
DOE OSTI2026

Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector

The particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on physics-motivated heuristics and assumptions that can be replaced by machine-learning (ML) models trained directly on simulated data and naturally suited to modern graphics processing units (GPUs). A state-of-the-art ML-based PF (MLPF) reconstruction algorithm, implemented within the CMS software framework, is presented. The MLPF algorithm performs a learnable full-event reconstruction on GPUs, generalizes across detector conditions and collision energies, and replaces multiple modular reconstruction steps with a single unified model. Physics performance comparable to standard PF reconstruction is achieved in both simulation and data, with improved jet energy resolution and inference time. In simulated top quark-antiquark events under LHC Run-3 (2023-2024) conditions, the jet energy resolution improves by 10-20% for jets with transverse momentum between 30-100 GeV. Inference time is evaluated using simulated multijet events, with a median of $20\,\hbox {ms}$ per event on an Nvidia L4 GPU, compared to approximately $110\,\hbox {ms}$ for the standard CMS PF reconstruction.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
DOE OSTI2020

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material e ects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filterbased methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall eciency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and oine reconstruction for the HL-LHC CMS tracker.

Cerati, Giuseppe↗
DOE OSTI2023

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm 0.6$% and 84.1$\pm 0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.

43 PARTICLE ACCELERATORS↗