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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗
NASA NTRS1996

Development of a Computer Architecture to Support the Optical Plume Anomaly Detection (OPAD) System

The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.

Katsinis, Constantine↗
NASA NTRSDate not supplied

Reliability Growth Modeling and Testing

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗
NASA NTRSDate not supplied

Modeling Reliability Growth

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗
DOE OSTI2016

Simulation and fitting of complex reaction network TPR: The key is the objective function

In this research, a method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based on the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN-TPR, there is increased importance (relative to simple reaction network TPR) in resolving of peaks prior to fitting, as well as from weighting of experimental data points. Using an implicit ordinary differential equation solver was found to be inadequate for simulating CRN-TPR. Lastly, the method employed here was capable of attaining improved fits in simulation and fitting of CRN-TPR when starting with a postulated mechanism and physically realistic initial guesses for the kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The Bright and the Slow—GRBs 100724B and 160509A with High-energy Cutoffs at ≲100 MeV

Here, we analyze the prompt emission of GRB 100724B and GRB 160509A, two of the brightest gamma-ray bursts (GRBs) observed by Fermi at ≲ MeV energies but surprisingly faint at ≳100 MeV energies. Time-resolved spectroscopy reveals a sharp high-energy cutoff at energies E c ~ 20–60 MeV for GRB 100724B and E c ~ 80–150 MeV for GRB 160509A. We first characterize phenomenologically the cutoff and its time evolution. We then fit the data to two models where the high-energy cutoff arises from intrinsic opacity to pair production within the source (τ γγ ): (i) a Band spectrum with τ γγ from the internal-shocks-motivated model of Granot et al. (2008) and (ii) the photospheric model of Gill & Thompson (2014). Alternative explanations for the cutoff, such as an intrinsic cutoff in the emitting electron energy distribution, appear to be less natural. Both models provide a good fit to the data with very reasonable physical parameters, providing an estimate of bulk Lorentz factors in the range Γ ~ 100–400, on the lower end of what is generally observed in Fermi GRBs. Surprisingly, their lower cutoff energies E c compared to other Fermi/LAT GRBs arise not only predominantly from the lower Lorentz factors, but also at a comparable level from differences in variability time, luminosity, and high-energy photon index. Lastly, particularly low E c values may prevent detection by Fermi/LAT, thus introducing a bias in the Fermi/LAT GRB sample against GRBs with low Lorentz factors or variability times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Accretion flow properties of MAXI J1543-564 during 2011 outburst from the TCAF solution

We derive accretion flow properties of the transient black hole candidate (BHC) MAXI J1543–564 using the RXTE data. We use the two-component advective flow (TCAF) solution to fit the data of the initial rising phase of outburst (from 2011 May 10 to 15). The 2.5–25 keV spectra are fitted using the TCAF solution fits file as a local additive table model in XSPEC. We extract physical flow parameters such as the two-component (Keplerian disk and sub-Keplerian halo) accretion rates and size and the property of the Compton cloud (post-shock region close to a black hole). Similar to other classical transient BHCs, monotonic evolution of low-frequency quasi-periodic oscillations (QPOs) is observed during the rising phase of the outburst, which is fitted with the propagating oscillatory shock (POS) model, which describes how the Compton cloud properties change from day to day. From the nature of variations of TCAF model fitted physical flow parameters and QPOs, we only found hard-intermediate and soft-intermediate spectral states during this phase of the outburst under study. We also calculated the frequency of the dominating QPOs from the TCAF model fitted shock parameters and found that they roughly match with the observed and POS model fitted values. From our spectro-temporal study of the source with TCAF and POS models, the most probable mass of the BHC is found to be 12.6–14.0 M {sub ⊙}, or 13{sub −0.4}{sup +1.0} M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Fitting program for linear regressions according to Mahon (1996)

This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error propagation. This software should facilitate the proper fitting of measurements with a simple Interface.

Trappitsch, RetoG.↗
DOE OSTI2011

SAAF: SANS data Analysis using Analytical Functions

The recently completed Extended Q-Range Small Angle Scattering Diffractometer (EQ-SANS) has put the focus on its software needs with renewed urgency. In a series of efforts, we aim at providing a complete set of software solutions on the EQ-SANS instrument. These programs include initial data processing, data correction and reduction, analytical model fitting to the scattering data, Monte Carlo simulation for structure determination, and virtual instrument simulation for experiment planning. SAAF is one such program for analytical data modeling. It takes the reduced EQ-SANS data and allows users to fit the data to analytical models. These models are easy to write. They can either be user written, or from the pre-supplied model library.

Data Analysis↗
DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Plutonium Speciation and Oxidation State Distributions in the Presence of Citrate

We explored the speciation and kinetics of the Pu(VI)-citrate and Pu(III)-citrate systems (pH m = 2.5–11.0, I = 0.1 M NaCl, T = 23 °C, O 2 (g) < 2 ppm) using ultraviolet–visible–near-infrared (UV–vis–NIR) spectrophotometry, solvent extraction, and PHREEQC modeling. Formation constants were determined for PuO 2 (HcitH)(aq) (log K° 1,1 = 1.09 ± 0.05) and PuO 2 (HcitH)(citH) 3– (log K° 1,2 = -0.20 ± 0.07), and evidence for (PuO 2 ) m (citH –k ) n (OH) x 2m(3+k)n–x was identified under alkaline conditions. Pu(VI) species were found to be less stable in the presence of citrate than in the absence of citrate (t ≤ 168 days); the rate of reduction increased with increasing pH. Further, the direct reduction of Pu(VI) to Pu(IV) was required to fit experimental data in the presence of citrate but did not improve the fit for Pu in the absence of citrate. We also observed increased Pu(III) stability in the presence of citrate (t ≤ 293 days), with higher concentrations of Pu(III) favored at lower pH. Finally, we provide evidence of a radiolysis-driven mechanism for the citrate-mediated reduction of plutonium that involves electron transfer from the oxidative breakdown of citrate. Our work highlights the need to investigate the redox effect of organic ligands on plutonium oxidation states under repository-relevant conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Investigations into the shape-preserving interpolants using symbolic computation

Shape representation is a central issue in computer graphics and computer-aided geometric design. Many physical phenomena involve curves and surfaces that are monotone (in some directions) or are convex. The corresponding representation problem is given some monotone or convex data, and a monotone or convex interpolant is found. Standard interpolants need not be monotone or convex even though they may match monotone or convex data. Most of the methods of investigation of this problem involve the utilization of quadratic splines or Hermite polynomials. In this investigation, a similar approach is adopted. These methods require derivative information at the given data points. The key to the problem is the selection of the derivative values to be assigned to the given data points. Schemes for choosing derivatives were examined. Along the way, fitting given data points by a conic section has also been investigated as part of the effort to study shape-preserving quadratic splines.

Lam, Maria↗
NASA NTRS2000

Does UV CETI Suffer from the MAD Syndrome?

Data have been reduced and partially analyzed and models have been fitted. ASCA data indicate a metal-poor corona, with metals down by a factor of 3 or more relative to the photospheric values. EUVE data show a FIP effect, which is expected if the metals are enhanced rather than depleted. An absolute measure of the metal abundance has not yet been performed for the EUVE data. Either the FIP effect is in operation in the presence of a global depletion of metals, or the ASCA analysis is giving the wrong answer. The latter could be the case if the plasma models applied are incomplete. Further investigation into this is warranted prior to publication.

Drake, Jeremy↗
NASA NTRS2004

Stardust Dynamic Science at Wild 2: First Look

The Dynamic Science investigation on the STARDUST mission has been described previously. The data delivered by the STARDUST Project is multifold, but basically it consists of radio Doppler data from the Deep Space Network (DSN) and attitude control data (ACS) from the spacecraft. Doppler data were successfully recorded by JPL's Navigation System (closed-loop data) and also by its Radio Science System (open-loop data) at DSN stations DSS43 near Canberra Australia and at DSS14 at Goldstone California. Attitude control data were also successfully delivered to the Dynamic Science Team. Here we describe a preliminary analysis of the data. Beyond a closest approach distance of 150 km, a Doppler detection of a the Wild 2 nucleus mass was not expected. The current best estimate of the closest approach distance is 236.4 km, and as expected, any mass signal in the Doppler data is hopelessly buried in the noise. We have attempted to fit the data to a mass model with no success. However, analysis of the Doppler data and the ACS data for particle impacts on the spacecraft's Whipple shields is in progress, and will be reported at the meeting. The DSS43 closed-loop Doppler residuals are plotted as a function of time from the current best estimate of the time of Wild 2 closest approach, 2 January 2004, 19:43:11.7 UTC, Earth-receive time at the station.

Anderson, J. D.↗
NASA NTRS1999

Backus Effect on a Perpendicular Errors in Harmonic Models of Real vs. Synthetic Data

Measurements of geomagnetic scalar intensity on a thin spherical shell alone are not enough to separate internal from external source fields; moreover, such scalar data are not enough for accurate modeling of the vector field from internal sources because of unmodeled fields and small data errors. Spherical harmonic models of the geomagnetic potential fitted to scalar data alone therefore suffer from well-understood Backus effect and perpendicular errors. Curiously, errors in some models of simulated 'data' are very much less than those in models of real data. We analyze select Magsat vector and scalar measurements separately to illustrate Backus effect and perpendicular errors in models of real scalar data. By using a model to synthesize 'data' at the observation points, and by adding various types of 'noise', we illustrate such errors in models of synthetic 'data'. Perpendicular errors prove quite sensitive to the maximum degree in the spherical harmonic expansion of the potential field model fitted to the scalar data. Small errors in models of synthetic 'data' are found to be an artifact of matched truncation levels. For example, consider scalar synthetic 'data' computed from a degree 14 model. A degree 14 model fitted to such synthetic 'data' yields negligible error, but amplifies 4 nT (rmss) added noise into a 60 nT error (rmss); however, a degree 12 model fitted to the noisy 'data' suffers a 492 nT error (rmms through degree 12). Geomagnetic measurements remain unaware of model truncation, so the small errors indicated by some simulations cannot be realized in practice. Errors in models fitted to scalar data alone approach 1000 nT (rmss) and several thousand nT (maximum).

Voorhies, C. V.↗
NASA NTRS1997

Frozen-Flux Modelling for Epochs 1915 and 1980

The frozen-flux hypothesis for the Earth's liquid core assumes that convective terms dominate diffusive terms in the induction equation governing the behaviour of the magnetic field at the surface of the core. While highly plausible on the basis of estimates of physical parameters, the hypothesis has been questioned. To study this hypothesis, we improve the method which tests the consistency of magnetic observations with the hypothesis by constructing simple, flux-conserving core-field models fitting the data at pairs of epochs. We introduce a new approach that fixes the patch configurations at each of the two epochs before inversion, so that each configuration is consistent with its respective data set but possesses the same patch topology. We expand upon the inversion algorithm, using quadratic programming to maintain the proper flux sign within patches; the modelling calculations are also extended to include data types that depend non-linearly on the model. Every test of a hypothesis depends on the characterization of the observational uncertainties; we undertake a thorough review of this question. For main-field models, the primary source of uncertainty comes from the crustal field. We base our analysis on statistical models of the crustal magnetization, adjusted to bring it into better conformity with our data set. The noise model permits us to take into account the correlations between the measurements and requires that a different weighting be given to horizontal and vertical components. It also indicates that the observations should be fit more closely than has been the practice heretofore. We apply the revised method to Magsat data from 1980 and survey and observatory data from 1915.5, two data sets believed to be particularly difficult to reconcile with the frozen-flux hypothesis. We compute a pair of simple, flux-conserving models that fit the averaged data from each epoch. We therefore conclude that present knowledge of the geomagnetic fields of 1980 and 1915.5 is consistent with the frozen-flux hypothesis.

OBrien, Michael S.↗
DOE OSTI2014

Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Purpose: Monte Carlo simulations were performed with the goal of verifying previously published physical measurements characterizing scatter as a function of apparent thickness. A secondary goal was to provide a way of determining what effect tissue glandularity might have on the scatter characteristics of breast tissue. The overall reason for characterizing mammography scatter in this research is the application of these data to an image processing-based scatter-correction program. Methods: MCNPX was used to simulate scatter from an infinitesimal pencil beam using typical mammography geometries and techniques. The spreading of the pencil beam was characterized by two parameters: mean radial extent (MRE) and scatter fraction (SF). The SF and MRE were found as functions of target, filter, tube potential, phantom thickness, and the presence or absence of a grid. The SF was determined by separating scatter and primary by the angle of incidence on the detector, then finding the ratio of the measured scatter to the total number of detected events. The accuracy of the MRE was determined by placing ring-shaped tallies around the impulse and fitting those data to the point-spread function (PSF) equation using the value for MRE derived from the physical measurements. The goodness-of-fit was determined for each data set as a means of assessing the accuracy of the physical MRE data. The effect of breast glandularity on the SF, MRE, and apparent tissue thickness was also considered for a limited number of techniques. Results: The agreement between the physical measurements and the results of the Monte Carlo simulations was assessed. With a grid, the SFs ranged from 0.065 to 0.089, with absolute differences between the measured and simulated SFs averaging 0.02. Without a grid, the range was 0.28–0.51, with absolute differences averaging −0.01. The goodness-of-fit values comparing the Monte Carlo data to the PSF from the physical measurements ranged from 0.96 to 1.00 with a grid and 0.65 to 0.86 without a grid. Analysis of the data suggested that the nongrid data could be better described by a biexponential function than the single exponential used here. The simulations assessing the effect of breast composition on SF and MRE showed only a slight impact on these quantities. When compared to a mix of 50% glandular/50% adipose tissue, the impact of substituting adipose or glandular breast compositions on the apparent thickness of the tissue was about 5%. Conclusions: The findings show agreement between the physical measurements published previously and the Monte Carlo simulations presented here; the resulting data can therefore be used more confidently for an application such as image processing-based scatter correction. The findings also suggest that breast composition does not have a major impact on the scatter characteristics of breast tissue. Application of the scatter data to the development of a scatter-correction software program can be simplified by ignoring the variations in density among breast tissues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2000

Timing Noise in SGR 1806-20

We have phase connected a sequence of Rossi X-ray Timing Explorer Proportional Counter Array observations of SGR 1806-20 covering 178 days. We find a simple secular spin-down model does not adequately fit the data. The period derivative varies gradually during the observations between 8.1 and 11.7 x 10(exp -11) s/s (approx. 40% larger than the long term trend), while the average burst rate as seen with the Burst and Transient Source Experiment drops throughout the time interval. The phase residuals show no evidence for periodicity, but more closely resemble timing noise as seen ill radio pulsars. The magnitude of the timing noise., however, is large relative to the noise level typically found in radio pulsars (Delta(sub 8) = 4.8; frequency derivative average power approx. = 8 X 10(exp -20) Hz/sq s). Combined with the noise levels measured for some AXPs. we find all magnetar candidates have A8 values larger than those expected from a simple extrapolation of the correlation found in radio pulsars. We find the timing noise ill SGR 1806-20 is greater than or equal to the levels found in some accreting systems (e.g., Vela X-1, 4U 1538-52 and 4U 1626-67). Alternatively, an orbital model with a period P(sub orb) = 733 days provides a statistically acceptable fit to the data. If the phase residuals are created by Doppler shifts from a gravitationally bound companion. then the allowed parameter space for the mass function (small) and orbital separation (large) rule out the possibility of accretion from the companion sufficient to power the persistent emission from the SGR.

Woods, Peter M.↗