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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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NASA NTRS2010

The Kepler Light Curve of V344 LYR: Constraining the Thermal-Viscous Limit Cycle Instability

We present time dependent modeling based on the accretion disk limit cycle model for a 90 d light curve of the short period SU UMa-type dwarf nova V344 Lyr taken by Kepler. The unprecedented precision and cadence (1 minute) far surpass that generally available for long term light curves. The data encompass a super outburst, preceded by three normal (i.e., short) outbursts and followed by two normal outbursts. The main decay of the super outburst is nearly perfectly exponential, decaying at a rate approx.12 d/mag, while the much more rapid decays of the normal outbursts exhibit a faster-than-exponential shape. We show that the standard limit cycle model can account for the light curve, without the need for either the thermal-tidal instability or enhanced mass transfer.

Cannizzo, J. K.↗
NASA NTRS2010

Real-Time Exponential Curve Fits Using Discrete Calculus

An improved solution for curve fitting data to an exponential equation (y = Ae(exp Bt) + C) has been developed. This improvement is in four areas -- speed, stability, determinant processing time, and the removal of limits. The solution presented avoids iterative techniques and their stability errors by using three mathematical ideas: discrete calculus, a special relationship (be tween exponential curves and the Mean Value Theorem for Derivatives), and a simple linear curve fit algorithm. This method can also be applied to fitting data to the general power law equation y = Ax(exp B) + C and the general geometric growth equation y = Ak(exp Bt) + C.

Rowe, Geoffrey↗
NASA NTRS2011

An Investigation of How a Meteor Light Curve is Modified by Meteor Shape and Atmospheric Density Perturbations

This is a preliminary investigation of how perturbations to meteoroid shape or atmospheric density affect a meteor light curve. A simple equation of motion and ablation are simultaneously solved numerically to give emitted light intensity as a function of height. It is found that changing the meteoroid shape, by changing the relationship between the cross-section area and the mass, changes the curvature and symmetry of the light curve, while making a periodic oscillation in atmospheric density gives a small periodic oscillation in the light curve.

Stokan, E.↗
NASA NTRS2012

Light Curve Observations of Upper Stages in the Low Earth Orbit Environment

Active debris removal (ADR) is a potential means to remediate the orbital debris environment in low Earth orbit (LEO). Massive intact objects, including spent upper stages and retired payloads, with high collision probabilities have been suggested as potential targets for ADR. The challenges to remove such objects on a routine basis are truly monumental. A key piece of information needed for any ADR operations is the tumble motion of the targets. Rapid tumble motion (in excess of one degree per second) of a multiple-ton intact object could be a major problem for proximity and docking operations. Therefore, there is a need to characterize the general tumble motion of the potential ADR targets for future ADR planning. The NASA Orbital Debris Program Office has initiated an effort to identify the global tumble behavior of potential ADR targets in LEO. The activities include optical light curve observations, imaging radar data collection, and laboratory light curve simulations and modeling. This paper provides a preliminary summary of light curve data of more than 100 upper stages collected by two telescope facilities in Colorado and New Mexico between 2011 and 2012. Analyses of the data and implications for the tumble motions of the objects are also discussed in the paper.

Liou, J.-C.↗
NASA NTRS2011

Gamma-Ray Pulsar Light Curves in Vacuum and Force-Free Geometry

Recent studies have shown that gamma-ray pulsar light curves are very sensitive to the geometry of the pulsar magnetic field. Pulsar magnetic field geometries, such as the retarded vacuum dipole and force-free magnetospheres have distorted polar caps that are offset from the magnetic axis in the direction opposite to rotation. Since this effect is due to the sweepback of field lines near the light cylinder, offset polar caps are a generic property of pulsar magnetospheres and their effects should be included in gamma-ray pulsar light curve modeling. In slot gap models (having two-pole caustic geometry), the offset polar caps cause a strong azimuthal asymmetry of the particle acceleration around the magnetic axis. We have studied the effect of the offset polar caps in both retarded vacuum dipole and force-free geometry on the model high-energy pulse profiles. We find that, compared to the profiles derived from symmetric caps, the flux in the pulse peaks, which are caustics formed along the trailing magnetic field lines, increases significantly relative to the off-peak emission, formed along leading field lines. The enhanced contrast produces improved slot gap model fits to Fermi pulsar light curves like Vela, with vacuum dipole fits being more favorable.

Harding, Alice K.↗
NASA NTRS2014

Modified Displacement Transfer Functions for Deformed Shape Predictions of Slender Curved Structures with Varying Curvatives

To eliminate the need to use finite-element modeling for structure shape predictions, a new method was invented. This method is to use the Displacement Transfer Functions to transform the measured surface strains into deflections for mapping out overall structural deformed shapes. The Displacement Transfer Functions are expressed in terms of rectilinearly distributed surface strains, and contain no material properties. This report is to apply the patented method to the shape predictions of non-symmetrically loaded slender curved structures with different curvatures up to a full circle. Because the measured surface strains are not available, finite-element analysis had to be used to analytically generate the surface strains. Previously formulated straight-beam Displacement Transfer Functions were modified by introducing the curvature-effect correction terms. Through single-point or dual-point collocations with finite-elementgenerated deflection curves, functional forms of the curvature-effect correction terms were empirically established. The resulting modified Displacement Transfer Functions can then provide quite accurate shape predictions. Also, the uniform straight-beam Displacement Transfer Function was applied to the shape predictions of a section-cut of a generic capsule (GC) outer curved sandwich wall. The resulting GC shape predictions are quite accurate in partial regions where the radius of curvature does not change sharply.

displacement transfer functions↗
NASA NTRS2015

CSI 2264: Characterizing Young Stars in NGC 2264 With Short-Duration Periodic Flux Dips in Their Light Curves

We identify nine young stellar objects (YSOs) in the NGC 2264 star-forming region with optical CoRoT light curves exhibiting short-duration, shallow, periodic flux dips. All of these stars have infrared (IR) excesses that are consistent with their having inner disk walls near the Keplerian corotation radius. The repeating photometric dips have FWHM generally less than one day, depths almost always less than 15%, and periods (3 < P < 11 days) consistent with dust near the Keplerian co-rotation period. The flux dips vary considerably in their depth from epoch to epoch, but usually persist for several weeks and, in two cases, were present in data collected on successive years. For several of these stars, we also measure the photospheric rotation period and find that the rotation and dip periods are the same, as predicted by standard \disk-locking" models. We attribute these flux dips to clumps of material in or near the inner disk wall, passing through our line of sight to the stellar photosphere. In some cases, these dips are also present in simultaneous Spitzer IRAC light curves at 3.6 and 4.5 microns. We characterize the properties of these dips, and compare the stars with light curves exhibiting this behavior to other classes of YSO in NGC 2264. A number of physical mechanisms could locally increase the dust scale height near the inner disk wall, and we discuss several of those mechanisms; the most plausible mechanisms are either a disk warp due to interaction with the stellar magnetic field or dust entrained in funnel- ow accretion columns arising near the inner disk wall.

CSI 2264↗
NASA NTRS2016

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

Howell, Lauren R.↗
NASA NTRS2016

Marginalizing Instrument Systematics in HST WFC3 Transit Light Curves

Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) infrared observations at 1.1-1.7 microns probe primarily the H2O absorption band at 1.4 microns, and have provided low-resolution transmission spectra for a wide range of exoplanets. We present the application of marginalization based on Gibson to analyze exoplanet transit light curves obtained from HST WFC3 to better determine important transit parameters such as "ramp" probability (R (sub p)) divided by "ramp" total (R (sub asterisk)), which are important for accurate detections of H2O. We approximate the evidence, often referred to as the marginal likelihood, for a grid of systematic models using the Akaike Information Criterion. We then calculate the evidence-based weight assigned to each systematic model and use the information from all tested models to calculate the final marginalized transit parameters for both the band-integrated and spectroscopic light curves to construct the transmission spectrum. We find that a majority of the highest weight models contain a correction for a linear trend in time as well as corrections related to HST orbital phase. We additionally test the dependence on the shift in spectral wavelength position over the course of the observations and find that spectroscopic wavelength shifts delta (sub lambda) times lambda) best describe the associated systematic in the spectroscopic light curves for most targets while fast scan rate observations of bright targets require an additional level of processing to produce a robust transmission spectrum. The use of marginalization allows for transparent interpretation and understanding of the instrument and the impact of each systematic evaluated statistically for each data set, expanding the ability to make true and comprehensive comparisons between exoplanet atmospheres.

Wakeford, H. R.↗
NASA NTRS2016

Gamma-Ray Pulsar Light Curves as Probes of Magnetospheric Structure

The large number of gamma-ray pulsars discovered by the Fermi Gamma-Ray Space Telescope since its launch in 2008 dwarfs the handful that were previously known. The variety of observed light curves makes possible a tomography of both the ensemble-averaged field structure and the high-energy emission regions of a pulsar magnetosphere. Fitting the gamma-ray pulsar light curves with model magnetospheres and emission models has revealed that most of the high-energy emission, and the particles acceleration, takes place near or beyond the light cylinder, near the current sheet. As pulsar magnetosphere models become more sophisticated, it is possible to probe magnetic field structure and emission that are self-consistently determined. Light curve modeling will continue to be a powerful tool for constraining the pulsar magnetosphere physics.

Harding, A. K.↗
NASA NTRS2016

Charon's Light Curves, as Observed by New Horizons' Ralph Color Camera (MVIC) on Approach to the Pluto System.

Light curves produced from color observations taken during New Horizons approach to the Pluto-system by its Multi-spectral Visible Imaging Camera (MVIC, part of the Ralph instrument) are analyzed. Fifty seven observations were analyzed, they were obtained between 9th April and 3rd July 2015, at a phase angle of 14.5 degrees to 15.1 degrees, sub-observer latitude of 51.2 degrees North to 51.5 degrees North, and a sub-solar latitude of 41.2 degrees North. MVIC has four color channels; all are discussed for completeness but only two were found to produce reliable light curves: Blue (400-550 nm) and Red (540-700 nm). The other two channels, Near Infrared (780-975 nm) and Methane-Band (860-910 nm), were found to be potentially erroneous and too noisy respectively. The Blue and Red light curves show that Charon's surface is neutral in color, but slightly brighter on its Pluto-facing hemisphere. This is consistent with previous studies made with the Johnson B and V bands, which are at shorter wavelengths than that of the MVIC Blue and Red channel respectively.

Howett, C. J. A.↗
NASA NTRS2019

Real-time Exponential Curve Fits Using Discrete Calculus

This paper presents an improved solution for curve fitting data to an exponential equation (Y = AeBt + C). This improvement is in four areas ? speed, stability, determinant processing time, and the removal of limits. The solution presented in this paper avoids iterative techniques and their stability errors by using three mathematical ideas ? discrete calculus, a special relationship (between exponential curves and the Mean Value Theorem for Derivatives), and a simple linear curve fit algorithm. This method can also be applied to fitting data to the general power law equation Y = AxB + C and the general geometric growth equation Y = AkBt + C.

Rowe, Geoffrey K.↗
NASA NTRS2021

Various Types of Defects Detection in Flat and Curved Laminated Composite Plates using Nonintrusive Lamb Wave System

Composite materials are widely used in aerospace industries due to their light weight, strength, and various other desired properties. However, they are susceptible to various defects occurring during the manufacturing process or in service. Typical defects include porosity, wrinkles, and delamination. Nondestructive means of detection of the defects at any stage are of great importance to ensure quality and safety of composite structures. A nonintrusive removeable Lamb wave system and accompanied methodology that is not material-dependent is presented in this paper to detect various types of typical defects in laminated composite plates, flat or curved. Through multidimensional data acquisition and processing, abnormality in waves caused by defects is captured and presented in inspection images. The methodologies are demonstrated in 2 cases: flat plate with wrinkles, and curved plate with delamination. Overall the results show that Lamb waves using the piezoelectric transducer and laser vibrometer system can be used for various types of defects inspection in flat or curved composite plates.

composite structures↗
NASA NTRS2019

The Berkeley Sample of Type II Supernovae: BVRI Light Curves and Spectroscopy of 55 SNe II

In this work, BVRI light curves of 55 Type II supernovae (SNe II) from the Lick Observatory Supernova Search programme obtained with the Katzman Automatic Imaging Telescope and the 1 m Nickel telescope from 2006 to 2018 are presented. Additionally, more than 150 spectra gathered with the 3 m Shane telescope are published. We conduct an analyse of the peak absolute magnitudes, decline rates, and time durations of different phases of the light and colour curves. Typically, our light curves are sampled with a median cadence of 5.5 d for a total of 5093 photometric points. In average, V-band plateau declines with a rate of 1.29 mag (100 d)(exp −1), which is consistent with previously published samples. For each band, the plateau slope correlates with the plateau length and the absolute peak magnitude: SNe II with steeper decline have shorter plateau duration and are brighter. A time-evolution analysis of spectral lines in term of velocities and pseudo-equivalent widths is also presented in this paper. Our spectroscopic sample ranges between 1 and 200 d post-explosion and has a median ejecta expansion velocity at 50 d post-explosion of 6500 km s(exp −1) (H α line) and a standard dispersion of 2000 km s(exp −1). Nebular spectra are in good agreement with theoretical models using a progenitor star having a mass <16M⨀. All the data are available to the community and will help to understand SN II diversity better, and therefore to improve their utility as cosmological distance indicators.

Photometric techniques↗
NASA NTRS2020

SN2020bvc: A Broad-line Type Ic Supernova with a Double-peaked Optical Light Curve and a Luminous X-Ray and Radio Counterpart

We present optical, radio, and X-ray observations of SN 2020bvc (=ASASSN-20bs, ZTF 20aalxlis), a nearby (z = 0.0252; d = 114Mpc) broad-line (BL) Type Ic supernova (SN) and the first double-peaked Ic-BL discovered without a gamma-ray burst (GRB) trigger. Our observations show that SN 2020bvc shares several properties in common with the Ic-BL SN 2006aj, which was associated with the low-luminosity gamma-ray burst (LLGRB) 060218. First, the 10 GHz radio luminosity (L(radio) ≈ 10^(37) erg/s) is brighter than ordinary core-collapse SNe but fainter than LLGRB SNe such as SN 1998bw (associated with LLGRB 980425). We model our VLA observations (spanning 13–43 days) as synchrotron emission from a mildly relativistic (v ≳ 0.3c) forward shock. Second, with Swift and Chandra, we detect X-ray emission (L(X) ≈ 10^(41) erg/s) that is not naturally explained as inverse Compton emission or part of the same synchrotron spectrum as the radio emission. Third, high-cadence (6 × per night) data from the Zwicky Transient Facility (ZTF) show a double-peaked optical light curve, the first peak from shock cooling of extended low-mass material (mass Me < 10^(-2) Mꙩ at radius Re > 10^(12) cm) and the second peak from the radioactive decay of 56Ni. SN 2020bvc is the first double-peaked Ic-BL SN discovered without a GRB trigger, so it is noteworthy that it shows X-ray and radio emission similar to LLGRB SNe. For four of the five other nearby (z ≲ 0.05) Ic-BL SNe with ZTF high-cadence data, we rule out a first peak like that seen in SN 2006aj and SN 2020bvc, i.e., that lasts ≈1 day and reaches a peak luminosity M ≈ −18. Follow-up X-ray and radio observations of Ic-BL SNe with well-sampled early optical light curves will establish whether double-peaked optical light curves are indeed predictive of LLGRB-like X-ray and radio emission.

Anna Y. Q. Ho↗
NASA NTRS2021

Identifying Planetary Transit Candidates in TESS Full-frame Image Light Curves via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite(TESS)mission measured light from stars in∼75% of the sky throughout its 2 yr primary mission, resulting in millions of TESS 30-minute-cadence light curves to analyze in the search for transiting exoplanets. To search this vast data trove for transit signals, we aim to provide an approach that both is computationally efficient and produces highly performant predictions. This approach minimizes the required human search effort. We present a convolutional neural network, which we train to identify planetary transit signals and dismiss false positives. To make a prediction for a given light curve, our network requires no prior transit parameters identified using other methods. Our network performs inference on a TESS 30-minute-cadence light curve in∼5 ms on a single GPU, enabling large-scale archival searches. We present 181 new planet candidates identified by our network, which pass subsequent human vetting designed to rule out false positives.Our neural network model is additionally provided as open-source code for public use and extension

Gregory Olmschenk↗
NASA NTRSDate not supplied

Material Property Estimation in Thin Battery Components Using Guided Wave Measurement, Experimental Dispersion Curve Extraction and Finite Element Modeling

At NASA, we are investigating nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques to detect precursors of thermal runaway failure in lithium metal based lithium ion batteries (LIB). The approach is centered on computational simulation models to guide inspection and aid in interpretation of results. Since lithium metal LIBs have combinations of solid and fluid-filled porous materials, obtaining accurate material properties is both challenging and critical for successful simulation of battery inspection. To this end, we investigated a multi-verification approach for material characterization of thin battery components. First, a laser Doppler vibrometer (LDV) was used to measure guided wave fields in thin (microns-thick) battery components subject to broadband excitation. The time-space wavefield data was converted to frequency-wave number data to extract guided wave dispersion curves. A data visualization and post processing graphics user interface (GUI) was developed at NASA to aid the data exploration and analysis. Due to the thinness of the samples, low frequency-thickness-product plate wave approximations allowed for the calculation of closed-form solutions for material elastic property estimation. These approximations were then verified by calculating the Lamb wave solutions using the previously obtained material properties. Finally, the estimated elastic material properties were implemented in a COMSOL simulation model, and dispersion curves were extracted from simulation results. The dispersion curves and derived material properties were then compared to the analysis results from the experimental data. These comparisons informed on the accuracy of the measured material properties and helped demonstrate the accuracy of the finite element analysis (FEA) computational models. This assessment will prove vital when we start simulating more complex multi-layer components and poroelastic media. This paper gives a brief background of the problem space, outlines the workflow for data analysis and verification, shows results from the workflow, and gives an overview of future plans for simulation of lithium metal LIB inspection.

Peter Juarez↗
NASA NTRS2024

Short–Period Variables in TESS Full–Frame Image Light Curves Identified via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ∼85% of the sky throughout its 2 yr primary mission, resulting in millions of TESS 30-minute-cadence light curves to analyze in the search for transiting exoplanets. To search this vast data set, we aim to provide an approach that is computationally efficient, produces accurate predictions, and minimizes the required human search effort. We present a convolutional neural network that we train to identify short-period variables. To make a prediction for a given light curve, our network requires no prior target parameters identified using other methods. Our network performs inference on a TESS 30-minute-cadence light curve in ∼5 ms on a single GPU, enabling large-scale archival searches. We present a collection of 14,156 short-period variables identified by our network. The majority of our identified variables fall into two prominent populations, one of close-orbit main-sequence binaries and another of δ Scuti stars. Our neural network model and related code are additionally provided as open-source code for public use and extension.

Convolutional neural networks↗