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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Multiwire thermocouples: Frequency response

Experimental measurements are made with a novel two wire thermocouple. Signals from two wires of unequal diameters are recorded from the thermocouple suspended in constant flow with a periodic temperature fluctuation. It is demonstrated that the reconstructed signal from the two wire thermocouple requires no compensation for omega less than or equal to 2 omega(sub 1) where omega is the natural frequency of the smaller wire. A compensation factor is recommended for larger frequencies omega greater than 2 omega(sub 1). Theory and experimental measurements are compared with a novel three wire thermocouple. Signals from three wires of unequal diameters are recorded from the thermocouple suspended in constant flow with a periodic temperature fluctuation. It is demonstrated that the reconstructed signal from the three wire thermocouple requires no compensation for omega less than or equal to 5 omega(sub 1) where omega (sub 1) is the natural frequency of the smaller wire. The latter result represents a significant improvement compared to previous work with two wire thermocouples. A correction factor has also been derived to account for wires of arbitrary diameter. Measurements are recorded for multiwire thermocouples consisting of either two or three wires of unequal diameters. Signals from the multiwire probe are recorded for a reversing gas flow with a periodic temperature fluctuation. It is demonstrated that the reconstructed signal from the multiwire thermocouple requires no compensation provided omega/omega(sub 1) is less than 2.3 for two wires or omega/omega(sub 1) is less than 3.6 for three wires where omega(sub 1) is the natural frequency of the smaller wire based on the maximum gas velocity. The latter results were possible provided Fourier transformed data were used and knowledge of the gas velocity is available.

Forney, L. J.↗
DOE OSTI2020

Reconstruction of signal amplitudes in the CMS electromagnetic calorimeter in the presence of overlapping proton-proton interactions

A template fitting technique for reconstructing the amplitude of signals produced by the lead tungstate crystals of the CMS electromagnetic calorimeter is described. This novel approach is designed to suppress the contribution to the signal of the increased number of out-of-time interactions per beam crossing following the reduction of the accelerator bunch spacing from 50 to 25 ns at the start of Run 2 of the LHC. Execution of the algorithm is sufficiently fast for it to be employed in the CMS high-level trigger. It is also used in the offline event reconstruction. Results obtained from simulations and from Run 2 collision data (2015–2018) demonstrate a substantial improvement in the energy resolution of the calorimeter over a range of energies extending from a few GeV to several tens of GeV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

ELECTRON SHOWER RECONSTRUCTION IN THE ICARUS EXPERIMENT

This dissertation presents a study in the field of neutrino physics. Neutrinos are fundamental particles that are electrically neutral and have extremely small mass, allowing them to traverse matter with very little interaction. Because of this property, neutrinos are exceptionally difficult to detect. Nevertheless, understanding their behavior is essential for addressing fundamental questions about the origin of the Universe and the properties of matter. This work focuses on the reconstruction of electron showers produced by interactions of electron neutrinos (𝜈𝑒) in the ICARUS experiment, located at the Fermi National Accelerator Laboratory in the United States. ICARUS employs a liquid argon time projection chamber detector, which is capable of recording with high precision the tracks left by particles produced in neutrino interactions. The main objective of this research is to improve the reconstruction algorithms and techniques used to identify and characterize these electron showers, enhancing metrics such as completeness, defined as the fraction of correctly reconstructed signals, and purity, which quantifies how much of the reconstructed signal truly belongs to the candidate event. These improvements are crucial for reducing false positives and increasing the accuracy of electron photon discrimination. Consequently, this work directly contributes to improved neutrino oscillation analyses and to a deeper understanding of neutrino properties.

Salmoria, Gabrieli [Parana Tech. Fed. U., Toledo]↗
NASA NTRS1972

Carrier synchronization and detection of polyphase signals.

Digital communication networks used for the distribution of high-speed digital information are currently the subject of design studies for many civil and military applications. This paper presents results that are useful in such studies as well as in network planning. In particular, the paper is concerned with the problems of carrier synchronization and noisy reference detection of polyphase signals. Reconstruction of coherent references for the detection of polyphase signals is considered and analyzed for three carrier reconstruction loops, namely, Nth power (multiply-and-divide) loops, generalized Costas (I-Q) loops, and extensions of data-aided (modulation wipeoff) loops. General expressions for the error probability are developed when the reconstructed reference signals are noisy.

Lindsey, W. C.↗
NASA NTRS1997

Real-Time Sensor Validation System Developed for Reusable Launch Vehicle Testbed

A real-time system for validating sensor health has been developed for the reusable launch vehicle (RLV) program. This system, which is part of the propulsion checkout and control system (PCCS), was designed for use in an integrated propulsion technology demonstrator testbed built by Rockwell International and located at the NASA Marshall Space Flight Center. Work on the sensor health validation system, a result of an industry-NASA partnership, was completed at the NASA Lewis Research Center, then delivered to Marshall for integration and testing. The sensor validation software performs three basic functions: it identifies failed sensors, it provides reconstructed signals for failed sensors, and it identifies off-nominal system transient behavior that cannot be attributed to a failed sensor. The code is initiated by host software before the start of a propulsion system test, and it is called by the host program every control cycle. The output is posted to global memory for use by other PCCS modules. Output includes a list indicating the status of each sensor (i.e., failed, healthy, or reconstructed) and a list of features that are not due to a sensor failure. If a sensor failure is found, the system modifies that sensor's data array by substituting a reconstructed signal, when possible, for use by other PCCS modules.

Jankovsky, Amy L.↗
DOE OSTI2018

Characterization of an Ionization Readout Tile for nEXO

Anewdesign for the anode of a time projection chamber, consisting of a charge-detecting "tile", is investigated for use in large scale liquid xenon detectors. The tile is produced by depositing 60 orthogonal metal charge-collecting strips, 3 mm wide, on a 10 cm 10 cm fused-silica wafer. These charge tiles may be employed by large detectors, such as the proposed tonne-scale nEXO experiment to search for neutrinoless double-beta decay. Modular by design, an array of tiles can cover a sizable area. The width of each strip is small compared to the size of the tile, so a Frisch grid is not required. A grid-less, tiled anode design is beneficial for an experiment such as nEXO, where a wire tensioning support structure and Frisch grid might contribute radioactive backgrounds and would have to be designed to accommodate cycling to cryogenic temperatures. The segmented anode also reduces some degeneracies in signal reconstruction that arise in large-area crossed-wire time projection chambers. A prototype tile was tested in a cell containing liquid xenon. Very good agreement is achieved between the measured ionization spectrum of a 207Bi source and simulations that include the microphysics of recombination in xenon and a detailed modeling of the electrostatic field of the detector. An energy resolution E=5.5% is observed at 570 keV, comparable to the best intrinsic ionization-only resolution reported in literature for liquid xenon at 936 V/cm.

Jewell, M J.↗
NASA NTRS1977

Digital filter for voiceband noise

Device operates over 300 to 3000 hertz range and contains 10 bit, 10 kilohertz converters and equally fast registers. Combination and weights of digital samples of analog signal are utilized by device to reconstruct signal with noise above 3000 hertz eliminated.

Edwards, T. R.↗
NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 3

The following subjects were covered: (1) ASM80 manual, (2) signal preprocessing as an aid to on-line EKG analysis, and (3) high speed evaluation of magnetic tape recordings of electrocardiograms. A description of the ASM80 symbolic assembly program for the INTEL 8080 microprocessor and a user's manual were presented. The capability of three redundancy reduction algorithms to produce adequate representations of electrocardiographic data was examined. A hardware device was constructed which carried out zero order interpolation on a signal. Examination of the zero order interpolators reconstructed signal indicated that this representation was adequate for analysis of rhythm. A system to analyze magnetic tapes of electrocardiograms recorded over 24 hour intervals was designed. The recordings are sampled 200 times per second using a Nova computer and a special interface system. This system was tested on several recordings of clinical data, containing over 75 premature ventricular contractions, each one of which was flagged.

Mark, R. G.↗
DOE OSTI2013

Gravity Gradiometry: A Novel Application for Compressed Sensing

During the past decade, compressed sensing (CS) has proven to be extremely useful for sparse signal reconstruction. Here the method of CS is applied to fast mass distribution determination based on cold atom gravity gradiometer measurements. Specifically we consider an array of M gradiometers placed around a 2D target area in order to determine the interior mass distribution in cases where the set of (M) sensor measurements under samples the distribution. This was done by assuming that the system’s sparsity comes from the mass distributions only having K non-zero masses, which led to a non-orthogonal basis dictionary. This lack of orthogonality caused interesting behaviors, including weakened noise performance, and breaking of the typical CS motivated logarithmic scaling of required M values for larger K values. However, for low K values M scaled as expected. Modifications to the gravity sensor model to promote orthogonality and test its impact on signal recovery postponed the onset of anomalous scaling; suggesting that lack of orthogonality is the primary cause. While CS works for this sparse, but intrinsically ill-posed problem, this sensor system displayed increased noise sensitivity and a smaller upper bound on the size of recoverable K sets. However, while these limitations decrease CS performance, significant improvements over traditional sensing approaches are still possible.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

BAYESIAN INFERENCE OF POLARIZED COSMIC MICROWAVE BACKGROUND POWER SPECTRA FROM INTERFEROMETRIC DATA

Detection of B-mode polarization of the cosmic microwave background (CMB) radiation is one of the frontiers of observational cosmology. Because they are an order of magnitude fainter than E-modes, it is quite a challenge to detect B-modes. Having more manageable systematics, interferometers prove to have a substantial advantage over imagers in detecting such faint signals. Here, we present a method for Bayesian inference of power spectra and signal reconstruction from interferometric data of the CMB polarization signal by using the technique of Gibbs sampling. We demonstrate the validity of the method in the flat-sky approximation for a simulation of an interferometric observation on a finite patch with incomplete uv-plane coverage, a finite beam size, and a realistic noise model. With a computational complexity of O(n {sup 3/2}), n being the data size, Gibbs sampling provides an efficient method for analyzing upcoming cosmology observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR values were found to increase with decreasing RMSE values of projection angular gaps with strong correlations (r ≈ −0.7) regardless of the reconstruction algorithm used. Conclusions: Based on the authors’ results, displacement-based binning methods, better reconstruction algorithms, and the acquisition of even projection angular views are the most important factors to consider for improving thoracic 4D-CBCT image quality. In view of the practical issues with displacement-based binning and the fact that projection angular spacing is not currently directly controllable, development of better reconstruction algorithms represents the most effective strategy for improving image quality in thoracic 4D-CBCT for IGRT applications at the current stage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

Classical problems in computational physics such as data-driven forecasting and signal reconstruction from sparse sensors have recently seen an explosion in deep neural network (DNN) based algorithmic approaches. However, most DNN models do not provide uncertainty estimates, which are crucial for establishing the trustworthiness of these techniques in downstream decision making tasks and scenarios. In recent years, ensemble-based methods have achieved significant success for the uncertainty quantification in DNNs on a number of benchmark problems. However, their performance on real-world applications remains under-explored. In this work, we present an automated approach to DNN discovery and demonstrate how this may also be utilized for ensemble-based uncertainty quantification. Specifically, we propose the use of a scalable neural and hyperparameter architecture search for discovering an ensemble of DNN models for complex dynamical systems. We highlight how the proposed method not only discovers high-performing neural network ensembles for our tasks, but also quantifies uncertainty seamlessly. This is achieved by using genetic algorithms and Bayesian optimization for sampling the search space of neural network architectures and hyperparameters. Subsequently, a model selection approach is used to identify candidate models for an ensemble set construction. Afterwards, a variance decomposition approach is used to estimate the uncertainty of the predictions from the ensemble. We demonstrate the feasibility of this framework for two tasks — forecasting from historical data and flow reconstruction from sparse sensors for the sea-surface temperature. In conclusion, we demonstrate superior performance from the ensemble in contrast with individual high-performing models and other benchmarks.

Deep ensembles↗
DOE OSTI2021

On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work (Daubechies et al., Pure Appl. Math. 57(11), 1413–1457, 2004), where the single vector signal can be infinite-dimensional, and (Fornasier and Rauhut, SIAM J. Numer. Anal. 46(2), 577613, 2008), which extends the aforementioned work to the joint sparse recovery of finite number of infinite-dimensional vectors. In our case, to take account of the joint sparsity and promote the coupling of nonvanishing components, we employ a convex relaxation approach with mixed norm penalty ℓ 2,1 . This paper discusses the computation of the solutions of linear inverse problems with such relaxation by a forward-backward splitting algorithm. However, since the solution matrix possesses infinitely many columns, the arguments of Daubechies et al. (Pure Appl. Math. 57(11), 1413–1457, 2004) no longer apply. As such, we establish new strong convergence results for the algorithm, in particular when the set of jointly sparse vectors is infinite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Reconstruction and initial calibration of silicon photomultipliers response in the DANSS experiment

The specific features of silicon photomultiplier (SiPM) signal reconstruction in the DANSS experiment are discussed. A technique for calibration of SiPM response using its noise spectrum parameters is described. The method allows one to calculate the number of detected photoelectrons. The results of practical application of the developed procedure to the adjustment of SiPM operating voltages are presented. It is shown that the achieved precision of such hardware calibration is better than 2%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2009

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

Christensen, Daniel↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
NASA NTRS1997

Wavelet Methods Developed to Detect and Control Compressor Stall

A "wavelet" is, by definition, an amplitude-varying, short waveform with a finite bandwidth (e.g., that shown in the first two graphs). Naturally, wavelets are more effective than the sinusoids of Fourier analysis for matching and reconstructing signal features. In wavelet transformation and inversion, all transient or periodic data features (as in compressor-inlet pressures) can be detected and reconstructed by stretching or contracting a single wavelet to generate the matching building blocks. Consequently, wavelet analysis provides many flexible and effective ways to reduce noise and extract signals which surpass classical techniques - making it very attractive for data analysis, modeling, and active control of stall and surge in high-speed turbojet compressors. Therefore, fast and practical wavelet methods are being developed in-house at the NASA Lewis Research Center to assist in these tasks. This includes establishing user-friendly links between some fundamental wavelet analysis ideas and the classical theories (or practices) of system identification, data analysis, and processing.

Le, Dzu K.↗