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At least 217 records · Page 12

Large Adaptive Optics Survey for Substellar Objects around Young, Nearby, Low-mass Stars with Robo-AO

We present results from the Large Adaptive optics Survey for Substellar Objects, where the goal is to directly image new substellar companions (<70 M {sub Jup}) at wide orbital separations (≳50 au) around young (≲300 Myr), nearby (<100 pc), low-mass (≈0.1–0.8 M{sub ⊙}) stars. We report on 427 young stars imaged in the visible (i') and near-infrared (J or H ) simultaneously with Robo-AO on the Kitt Peak 2.1 m telescope and later the Maunakea University of Hawaii 2.2 m telescope. To undertake the observations, we commissioned a new infrared camera for Robo-AO that uses a low-noise high-speed SAPHIRA avalanche photodiode detector. We detected 121 companion candidates around 111 stars, of which 62 companions are physically associated based on Gaia DR2 parallaxes and proper motions, another 45 require follow-up observations to confirm physical association, and 14 are background objects. The companion separations range from 2 to 1101 au and reach contrast ratios of 7.7 mag in the near-infrared compared to the primary. The majority of confirmed and pending candidates are stellar companions, with ~5 being potentially substellar and requiring follow-up observations for confirmation. We also detected a 43 ± 9 M {sub Jup} and an 81 ± 5 M {sub Jup} companion that were previously reported. We found 34 of our targets have acceleration measurements detected using Hipparcos–Gaia proper motions. Of those, 58{sub -14}{sup +12}% of the 12 stars with imaged companion candidates have significant accelerations (χ{sup 2}>11.8), while only 23{sub -6}{sup +11}% of the remaining 22 stars with no detected companion have significant accelerations. The significance of the acceleration decreases with increasing companion separation. These young accelerating low-mass stars with companions will eventually yield dynamical masses with future orbit monitoring.

47 OTHER INSTRUMENTATION↗

PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events

We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times (tE > 120 days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~ 85% by selecting events with both tE > 120 days and a microlensing parallax of πE < 0.08. Unfortunately, such a selection criterion cannot be applied during the event as πE requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of O(100 - 1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions

79 ASTRONOMY AND ASTROPHYSICS↗

The Encounter of the Parker Solar Probe and a Comet-like Object Near the Sun: Model Predictions and Measurements

The Parker Solar Probe (PSP) aims to explore the nascent solar wind close to the Sun. Meanwhile, PSP is also expected to encounter small objects like comets and asteroids. Here, we survey the ephemerides to find the chance of a recent encounter and then model the interaction between released dusty plasmas and solar wind plasmas. On 2019 September 2, a comet-like object, the 322P/Solar and Heliosphere Observatory, just passed its perihelion flying to a heliocentric distance of 0.12 au and swept by PSP at a relative distance as close as 0.025 au. We present the dynamics of the dust particles released from 322P, forming a curved dust tail. Along the path of PSP in the simulated inner heliosphere, the states of plasma and magnetic field are sampled and illustrated, with the magnetic field sequences from simulation results being compared directly with the in situ measurements from PSP. Through the comparison, we suggest that 322P might be at a deficient activity level releasing limited dusty plasmas on its way to becoming a "rock comet." We also present images of solar wind streamers as recorded by the Wide-field Imager for Solar Probe Plus, showing an indication of dust bombardment for the images superposed with messy trails. We observe from the Large Angle and Spectrometric Coronagraph that 322P was transiting from a dimming region to a relatively bright streamer during its perihelion passage, and perform a simulation to confirm that 322P was flying from relatively faster to slower solar wind streams, modifying the local plasma states of the streams.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N

We report the characterization of 28 low-mass (0.02 M ⊙ ≤ M 2 ≤ 0.25 M ⊙ ) companions to Kepler objects of interest (KOIs), eight of which were previously designated confirmed planets. These objects were detected as transiting companions to Sunlike stars (G and F dwarfs) by the Kepler mission and are confirmed as single-lined spectroscopic binaries in the current work using the northern multiplexed Apache Point Observatory Galactic Evolution Experiment near-infrared spectrograph (APOGEE-N) as part of the third and fourth Sloan Digital Sky Surveys. We have observed hundreds of KOIs using APOGEE-N and collected a total of 43,175 spectra with a median of 19 visits and a median baseline of ~1.9 yr per target. We jointly model the Kepler photometry and APOGEE-N radial velocities to derive fundamental parameters for this subset of 28 transiting companions. The radii for most of these low-mass companions are overinflated (by ~10%) when compared to theoretical models. Tidally locked M dwarfs on short-period orbits show the largest amount of inflation, but inflation is also evident for companions that are well separated from the host star. We demonstrate that APOGEE-N data provide reliable radial velocities when compared to precise high-resolution spectrographs that enable detailed characterization of individual systems and the inference of orbital elements for faint (H > 12) KOIs. The data from the entire APOGEE-KOI program are public and present an opportunity to characterize an extensive subset of the binary population observed by Kepler.

79 ASTRONOMY AND ASTROPHYSICS↗

No Evidence for Orbital Clustering in the Extreme Trans-Neptunian Objects

The apparent clustering in longitude of perihelion piv and ascending node Ω of extreme trans-Neptunian objects (ETNOs) has been attributed to the gravitational effects of an unseen 5–10 Earth-mass planet in the outer solar system. To investigate how selection bias may contribute to this clustering, we consider 14 ETNOs discovered by the Dark Energy Survey, the Outer Solar System Origins Survey, and the survey of Sheppard and Trujillo. Using each survey's published pointing history, depth, and TNO tracking selections, we calculate the joint probability that these objects are consistent with an underlying parent population with uniform distributions in $\bar{w}$ and Ω. We find that the mean scaled longitude of perihelion and orbital poles of the detected ETNOs are consistent with a uniform population at a level between 17% and 94% and thus conclude that this sample provides no evidence for angular clustering.

79 ASTRONOMY AND ASTROPHYSICS↗

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗

Legacy Survey of Space and Time Data Preview 1: dia_object dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the dia_object dataset type. These are derived properties for transient and variable objects. This release contains 25 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 1: dia_object_forced_source dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the dia_object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all DIA objects. This release contains 597 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 1: object_forced_source dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all objects. This release contains 636 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 1: ss_object dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the ss_object dataset type. These are derived parameters for moving objects. This release contains 1 dataset of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 2: dia_object dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the dia_object dataset type. These are derived properties for transient and variable objects. This release contains 2,112 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 2: dia_object_forced_source dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the dia_object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all DIA objects. This release contains 183,169 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 2: object_forced_source dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all objects. This release contains 192,147 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 2: ss_object dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the ss_object dataset type. These are derived parameters for moving objects. This release contains 1 dataset of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 2: object_shear_all dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the object_shear_all dataset type. These are descriptions of shear objects detected and measured on coadds with metadetection. This release contains 1,699 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Studying the effects of overlapping objects in dark energy

Observing the clustering of galaxies allows us to calculate cosmological parameters necessary for understanding dark energy. However, as the density of observed objects increases, the probability of these objects blending likewise increases, causing multiple galaxies to be observed as one. This affects the inferred values of parameters such as the galaxy bias (b) and the matter energy density (ΩM). To see whether the bias from incorrectly inferring the galaxy count is significant, we compare the correlation functions in simulated data for “true” and “observed” data sets with one-to-one and multiple-to-one correspondences, respectively. For each data set, we create two correlation functions: one “measured” function directly relying on the galaxies’ positions using the TreeCorr python library, and one “model” derived mathematically from the galaxies’ power spectrum using the Cosmological Core Library (CCL). By minimizing the residual between these two functions, we compute the ideal values for b and ΩM across the various possible redshifts that position the galaxies in three dimensional space. This minimization is done with an Markov chain Monte Carlo (MCMC) estimate that finds one value of ΩM and ten values for b corresponding to the ten redshift bins ranging from z = 0.2 to z = 1.2. We find that neither b nor ΩM is particularly affected by inclusion of blended galaxies. Though there is room for improvement, the data suggests that the fluctuations we found are a result of noise or limitations on the modeling rather than blending explicitly.

79 ASTRONOMY AND ASTROPHYSICS↗

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗

Hybrid Curve Fitting For Reducing Motion Commands In Object Construction

Existing slicing software for additive manufacturing typically requires a triangulated mesh as its input. Triangulated meshes are approximate representations of exact CAD models. Despite the loss in dimensional accuracy, triangulated meshes are used because they are computationally easier to cross-section and offset than the exact geometry in CAD format. When a triangulated object is prepared, the resulting machine instructions include only linear motion commands. Numerous modern motion controllers can move in arc and spline motions; however, the absence of slicing software that supports curvature prevents these commands from being leveraged. To address this limitation, this paper presents a method for the hybrid reconstruction of arcs and splines as a post-processing step to traditional slicing. This method can greatly reduce the number of motion commands required to construct an object by printing smooth curved surfaces. This concise representation of tool-pathing allows for more even extrusion and is computed without a major impact on slicing time.

Wade, Charles↗