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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

New Short Constraint Length, Rate 1/N Convolutional Codes which Minimize Required E Sub B/n Sub o for Given Bit Error Rate

Instead of using the criterion of maximum free distance, (df) or the maximum (df) with minimizing a few first distance profiles, short constraint length rate 1/N convolution codes were searched using a criterion of minimizing required bit energy-to-noise density ratio, E(b)/N(o), for a given value of desired bit error rate (BER), for the goodness of a code. The considered channel was binary antipodal signaling over additive white Gaussian noise and no quantization at the channel output. For the BER calculations, the transfer function bounding technique was used. Partial searches were performed using some known facts and a very useful idea that "good codes generate good codes.'' That is, for a given constraint length K, good rate 1/(N + 1) codes can be found by extending the code generator matrices of good rate 1/N codes. The code search results are tabulated for 3 or = K or = 7 and 2 or = N or = 8. For many pairs of K and N, the new codes are shown to save 0.1 to 0.4 dB in the required E(b)/N(o) compared to previously reported codes. Additionally, the benefits of coding bandwidth expansion are confirmed with the new codes.

Lee, P. J.↗
NASA NTRS1992

Learning and tuning fuzzy logic controllers through reinforcements

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Berenji, Hamid R.↗
NASA NTRS1993

Three Alternative Symbol-Lock Detectors

Three symbol-lock detectors proposed as alternatives in advanced receivers processing non-return-to-zero binary data signals. Two perform operations similar to those of older square-law and absolute-value types. However, integrals computed during nonoverlapping symbol periods and, therefore, only one integrator needed in each such detector. Proposed detectors simpler, but performances worse because noises in overlapping samples correlated, whereas noises in nonoverlapping samples not correlated. Third detector is signal-power-estimator type. Signal integrated during successive half symbol cycles, and therefore only one integrator needed. Half-cycle integrals multiplied to eliminate effect of symbol polarity, and products accumulated during M-cycle observation period to smooth out estimate of signal power. If estimated signal power exceeds threshold, delta, then lock declared.

Shihabi, Mazen M.↗
NASA NTRS1992

Learning and tuning fuzzy logic controllers through reinforcements

This paper presents a new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system. In particular, our generalized approximate reasoning-based intelligent control (GARIC) architecture (1) learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward neural network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto et al. (1983) to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Berenji, Hamid R.↗
NASA NTRS1995

Nonperiodic variations in astrophysical systems: Investigating frequency evolution

We present a method related to the wavelet transform, the Gabor transform, for investigating astronomical time series containing nonconsistent frequencies. Instances in which such data sets may arise include variable star light curves, numerical studies of the gravitational three-body problem, X-ray binaries, and signals from more exotic objects such as planets around pulsars and mass infall from accretion structures onto compact objects. As an illustration of its power, we apply the technique to a numerical data set of a gravitational three-body interaction and to photometry of the rapidly oscillating peculiar A star HD 60435. In the three-body example, the method provides an insightful shorthand that allows for the determination of episodes where the system behaves as two nearly Keplerian orbits. For HD 60435, the power in the main frequency exhibits unusual evolution over the duration of the observation.

Boyd, Patricia T.↗
NASA NTRS1995

Joint Synchronization Of Viterbi And Reed-Solomon Decoders

Synchronization times reduced to reduce loss of data. Scheme for decoding received doubly encoded binary-data signal provides for joint synchronization of two decoders. Applies to concatenated error-correcting channel coding communication system in which, at transmitter, data first encoded by interleaved Reed-Solomon code (block code), then by convolutional code.

Statman, Joseph I.↗
DOE OSTI2025

Design of Experiments for Dynamic Test Runs in Solvent-Based CO 2 Capture Pilot Plants

Test runs in the pilot plants consume significant resources, and therefore, the learning from test runs should be maximized. Test runs conducted in the pilot plants are often steady state. It takes several hours for reaching steady-state in the pilot plants, and thus, the duration of the test runs needs to be long even for collecting few steady-state data points. On the other hand, a large number of measurements can be collected through dynamic test runs in a short span of time. This paper presents a systematic design of dynamic experiments (DoDEs) for identifiability of model parameters, which is achieved by persistently exciting the inputs signals. A pseudorandom binary sequence (PRBS) is designed as the input signal for DoDE due to its efficiency in obtaining sufficient spectral content. However, due to the long sequence size of the PRBS signal, a Schroeder-phase input signal, which is a multisine signal, is also designed. Tests for both types of signals are run in the Pilot Solvent Test Unit (PSTU) at the National Carbon Capture Center in Wilsonville, Alabama. The transient data are used to solve dynamic data reconciliation and parameter estimation problem. The estimated parameters are found to be not only superior to those estimated from using data collected from hundreds of steady-state test runs in a nonreactive (air–water) system, but the parameters could be estimated by using the dynamic data collected for about 24 h from the pilot plant for the MEA-H 2 O–CO 2 system.

CO2 capture↗
NASA NTRS1965

Coded noncoherent communications.

Binary digits encoding into orthogonal signals with white Gaussian noise for noncoherent communications over Rician channel

DIGITAL COMMUNICATIONS SYSTEM↗
DOE OSTI2022

Constraining ΛCDM cosmological parameters with Einstein Telescope mock data

ABSTRACT We investigate the capability of Einstein Telescope to constrain the cosmological parameters of the non-flat ΛCDM cosmological model. Two types of mock data sets are considered depending on whether or not a short gamma-ray burst is detected, and associated with the gravitational wave emitted by binary neutron stars merger, using the THESEUS satellite. Depending on the mock data set, two statistical estimators are applied: one assumes that the redshift is known, while the other marginalizes over it assuming a specific redshift prior distribution. We demonstrate that (i) using mock catalogues collecting gravitational wave signals emitted by binary neutron stars systems to which a short gamma-ray burst has been associated, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.40$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.09$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.07$; while (ii) using mock catalogues collecting all gravitational wave signals emitted by binary neutron stars systems for which an electromagnetic counterpart has not been detected, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.04$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.01$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.01$, once the redshift probability distribution of GW events is known from from population synthesis simulations and/or the measure of the tidal deformability parameter. These results show an improvement of a factor 2–75 with respect to earlier results using complementary data sets.

Califano, Matteo↗
DOE OSTI2024

Periodicity significance testing with null-signal templates: reassessment of PTF’s SMBH binary candidates

Periodograms are widely employed for identifying periodicity in time series data, yet they often struggle to accurately quantify the statistical significance of detected periodic signals when the data complexity precludes reliable simulations. We develop a data-driven approach to address this challenge by introducing a null-signal template (NST). The NST is created by carefully randomizing the period of each cycle in the periodogram template, rendering it non-periodic. It has the same frequentist properties as a periodic signal template, and we show with simulations that the distribution of false positives is the same as with the original periodic template, regardless of the underlying data. Thus, performing a periodicity search with the NST acts as an effective simulation of the null (no-signal) hypothesis, without having to simulate the noise properties of the data. We apply the NST method to the supermassive black hole binaries (SMBHB) search in the Palomar Transient Factory (PTF), where Charisi et al. had previously proposed 33 high signal-to-noise candidates utilizing simulations to quantify their significance. Our approach reveals that these simulations do not capture the complexity of the real data. There are no statistically significant periodic signal detections above the non-periodic background. To improve the search sensitivity, we introduce a Gaussian quadrature based algorithm for the Bayes Factor with correlated noise as a test statistic. We show with simulations that this improves sensitivity to true signals by more than an order of magnitude. However, the Bayes Factor approach also results in no statistically significant detections in the PTF data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Long-lived neutron-star remnants from asymmetric binary neutron star mergers: element formation, kilonova signals and gravitational waves

We present 3D general-relativistic neutrino-radiation hydrodynamics simulations of two asymmetric binary neutron star mergers producing long-lived neutron stars remnants and spanning a fraction of their cooling time scale. The mergers are characterized by significant tidal disruption with neutron rich material forming a massive disc around the remnant. The latter develops one-armed dynamics that is imprinted in the emitted kilo-Hertz gravitational waves. Angular momentum transport to the disc is initially driven by spiral-density waves and enhanced by turbulent viscosity and neutrino heating on longer timescales. The mass outflows are composed by neutron-rich dynamical ejecta of mass ∼10 −3 –10 −2 M ⊙ followed by a persistent spiral-wave/neutrino-driven wind of ≳ 10 −2 M ⊙ with material spanning a wide range of electron fractions, ∼0.1–0.55. Dynamical ejecta (winds) have fast velocity tails up to ∼0.8 (∼0.4) c. The outflows are further evolved to days timescale using 2D ray-by-ray radiation-hydrodynamics simulations that include an online nuclear network. We find complete r-process yields and identify the production of 56 Ni and the subsequent decay chain to 56 Co and 56 Fe. Synthetic kilonova light curves predict an extended (near-) infrared peak a few days postmerger originating from r-process in the neutron-rich/high-opacity ejecta and UV/optical peaks at a few hours (ten minutes) postmerger originating from weak r-process (free-neutron decay) in the faster ejecta components. Additionally, the fast tail of tidal origin generates kilonova afterglows potentially detectable in radio and X band on a few to ten years time scale. Quantitative effects originating from the tidal disruption merger dynamics are reflected in the multimessenger emissions.

abundances↗
NASA NTRS1972

Binary single-sideband phase-modulated communication systems.

Single-sideband phase modulation (SSBPM), in which a signal is simultaneously phase- and amplitude-modulated by a signal and its Hilbert transform, is shown to be suboptimum for binary signaling in white Gaussian noise. An alternative single-sideband technique based on the properties of binary suppressed-carrier phase modulation is proposed and shown to give performance equivalent to the double-sideband version.

Chadwick, H. D.↗
NASA NTRS2019

Search for Intermediate Mass Black Hole Binaries in the First and Second Observing Runs of the Advanced LIGO and VIRGO Network

Gravitational-wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar-mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational-wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event is detected in this search. Consequently, we place upper limits on the merger rate density for a family of intermediate mass black hole binaries. In particular, we choose sources with total masses 𝑀=𝑚1+𝑚2∈[120,800] 𝑀⊙ and mass ratios 𝑞=𝑚2/𝑚1∈[0.1,1.0]. For the first time, this calculation is done using numerical relativity waveforms (which include higher modes) as models of the real emitted signal. We place a most stringent upper limit of 0.20 Gpc−3 yr−1 (in comoving units at the 90% confidence level) for equal-mass binaries with individual masses 𝑚1,2=100 𝑀⊙ and dimensionless spins 𝜒1,2=0.8 aligned with the orbital angular momentum of the binary. This improves by a factor of ∼5 that reported after Advanced LIGO’s first observing run.

B. P. Abbott↗
NASA NTRS1986

Adaptive Quantizer for Burst Synthetic-Aperture Radar

Adaptive quantizer for burst-mode synthetic-aperture radar reduces data rate of return signal. Device, called block floating-point quantizer (BFPQ) basically analog-to-digital converter that covers wide dynamic range and discards appropriate lower order bits. BFPQ is, in effect, digital approximator with automatic gain control. Moves floatingpoint marker binary representation of signal data in accordance with perceived dynamic range. Available step sizes thus limited to multiples of underlying smallest quantization step (represented by lowest order bit). Retains only first K most significant bits of signal; (L,K) BFPQ is one that does K-bit quantization of signal originally quantized to L bits. Quantization error simply difference between actual signal level and its binary approximation. Other potential applications for BFPQ include speech compression and picture data compression.

Joo, T. H.↗
DOE OSTI2021

Deep Learning with Quantized Neural Networks for Gravitational-wave Forecasting of Eccentric Compact Binary Coalescence

We present the first application of deep learning forecasting for binary neutron stars, neutron star–black hole systems, and binary black hole mergers that span an eccentricity range e ≤ 0.9. In this work, we train neural networks that describe these astrophysical populations, and then test their performance by injecting simulated eccentric signals in advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) noise available at the Gravitational Wave Open Science Center to (1) quantify how fast neural networks identify these signals before the binary components merge; (2) quantify how accurately neural networks estimate the time to merger once gravitational waves are identified; and (3) estimate the time-dependent sky localization of these events from early detection to merger. Our findings show that deep learning can identify eccentric signals from a few seconds (for binary black holes) up to tens of seconds (for binary neutron stars) prior to merger. A quantized version of our neural networks achieves 4× reduction in model size, and up to 2.5× inference speedup. These novel algorithms may be used to facilitate time-sensitive multimessenger astrophysics observations of compact binaries in dense stellar environments.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Performance Of The Split-Symbol Moments Estimator

Report presents analysis of performance of Split-Symbol Moments Estimator (SSME) algorithm. Designed to estimate symbol signal-to-noise ratio of radio signal modulated by binary data pulses of period T and received in presence of additive white Gaussian noise. Incoming signal and noise first filtered, then sampled Ns - T/Ts times per symbol period. This study focuses on performance of SSME in case in which frequency width limited by digital filter and inter-symbol interference is thereby generated.

Shah, Biren N.↗
NASA NTRS1995

Symbol lock detection implemented with nonoverlapping integration intervals

A symbol lock detector is introduced for an incoming coherent digital communication signal which utilizes a subcarrier modulated with binary symbol data, d(sub k), and known symbol interval T by integrating binary values of the signal over nonoverlapping first and second intervals selected to be T/2, delaying the first integral an interval T/2, and either summing or multiplying the second integral with the first one that preceded it to form a value X(sub k). That value is then averaged over a number M of symbol intervals to produce a static value Y. A symbol lock decision can then be made when the static value Y exceeds a threshold level delta.

Shihabi, Mazen M.↗