adsabs/AstroCLIMB huggingface dataset:
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: Results of alternative k-means classification scheme using 1600 m baseline slope in addition to the multibaseline roughness. Left: roughness spectra of alternative k-means classes. Right: resulting distribution of alternative k-means classes as a function of 1600 m baseline slope. See Figures A28, A29, and A30 for examples of alternative k-means class 1, 6, and 2, respectively.
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: LROC NAC image M140550700L showing an example of low topographic slope class 1 terrain. The background image is 20 m pixel−1 topographic slope.
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: LROC NAC image M140007876R showing an example of low topographic slope class 3 terrain. The background image is 20 m pixel−1 topographic slope.
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: LROC NAC image M1157836519R overlaid on image pair M1164904395L/R showing an example of high topographic slope class 1 terrain on a north-facing slope near longitude 0°. M1157836519R has a subsolar longitude ∼270° (to approximate the illumination in Figure A28), and M1164904395L/R has a subsolar longitude ∼0°. High topographic slope class 1, as in this figure, tends to be significantly less cratered than low topographic slope class 1 (Figure A28) while exhibiting elephant-hide texture. The background image is 20 m pixel−1 topographic slope.
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: Same as Figure A24, but for 1600 m baseline slope (left) and 100 m baseline slope (right).
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: Same as Figure A24, but for plagioclase abundance (left), mean reflectance at 513–627 nm (middle), and mean reflectance at 1013–1164 nm (right).
Paper: A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)
Authors: Michael K. Barker, Erwan Mazarico, Gregory A. Neumann, David E. Smith, Maria T. Zuber, James W. Head, Xiaoli Sun
Figure caption: Same as Figure A24, but for nanophase iron abundance (left), olivine abundance (middle), and optical maturity (OMAT; right).
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption:  N(L) as a function of resolution and threshold, portraying the multifractality of Mars clouds. The legend indicates the threshold (T) and the fitted slopes (S1 and S2). S1 is represented by a solid line and S2 by a dotted line, highlighting the break in the slopes.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: Slopes calculated for each threshold are plotted against the thresholds. The error bars indicate the 95% confidence intervals for each slope. The nonoverlapping confidence intervals for the higher threshold slopes indicate that these slopes are significantly different from those of the lower thresholds, providing evidence for the multifractal nature of the cloud structures.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: The ice extinction optical depth, retrieved using data from the EXI instrument on board the EMM mission, against sol number (bottom) and LS (top).
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: MFS-processed frame 1 from sol 292. The left panel was generated using the red channel and right panel using the blue channel.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: Frame 1 from sol 292 generated by taking the ratio of the blue and red channel of the NavCam RGB image.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: Frame 1 from sol 292 generated using the green-only channel.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: Cloud survey image from sol 73, LS 35.7°.
Paper: Geometric Properties of Water-ice Clouds as Observed from Jezero Crater in the First 600 sols with the NavCam Instrument On Board the Mars2020 Rover, Perseverance
Authors: Priya Patel, Leslie Tamppari, Manuel de la Torre Juárez, Mark Lemmon, Andrew Coates, Michael Wolff, Daniel Toledo, Graziella Branduardi-Raymont, Geraint Jones, Charissa Campbell, John Moores, Justin Maki, Jacqueline Ryan
Figure caption: MCS water-ice profiles for sol 289 (left) and sol 291(right).
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: Each row depicts the size and separation of a TNO satellite relative to its primary body. Above the solid black line are shown 10 of the most-massive known binary systems, and 10 of the least massive are below, with all being ordered by primary mass. In general, larger TNO binaries present a larger size disparity between the components and tend to be on tighter orbits (in units of the primary radius, R primary). Less-massive binaries are more widely separated, with comparably sized components. This dichotomy implies two different formation mechanisms for the two observed populations of TNO binaries. For Pluto, only Charon is shown due to the very small sizes of the minor satellites. System masses, semimajor axes, and component diameters were retrieved from the Johnston Archive (http://www.johnstonsarchive.net/astro/astmoontable.html) and references therein.
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: Position of Eris from 2015 August 6 to 2016 January 29 UT, retrieved from JPL Horizons, with 15 day intervals marked. The background is the coadded DES r-band image with a scale of ∼1″ pixel−1. For comparison, the full field of view of the P60 facility camera is 12.′9 × 12.′9 (Cenko et al. 2006).
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: All panels show light curves folded at the orbital period of Dysnomia. Mean magnitudes and illumination-phase variation have been subtracted. The top panel shows the DES g and r bands (triangles), HST F606W data (squares), and the individual P60 V-band data (light cyan circles). The dashed line is the best-fit two-harmonic light curve, with 0.03 mag peak-to-peak amplitude. The blue circles are the P60 data binned into eight phase ranges. The magenta stars are the phase-binned Gaia G-band measures, which were not used to derive this light-curve fit. The central panel shows the DES i and z bands—the dotted curve is the best-fit light curve, and the data are clearly not consistent with even this best periodic model; we suspect there are uncorrected systematic errors in the iz photometry. The lower panel shows the HST magnitudes for Dysnomia. There is a clear variation of 0.3 mag, and they are plausibly fit by a double-peaked light curve from a fundamental and first-harmonic sinusoid, although there are only seven points, so this is certainly not conclusive.
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: Each panel shows the χ 2 per DOF of a fit of a sinusoidal light curve to the photometric data vs. frequency. Ticks above the plots give period in days. The upper panel uses the only the P60 data, revealing two strong minima, at periods of 16.1 and 14.4 days. The former is consistent with the orbital period of Dysnomia, ∼15.79 days, marked with the vertical dashed line. Aliases of these frequencies due to the sampling of once per sidereal day are also good fits; we plot only the range below the Nyquist frequency. The middle panel shows the χ 2/ DOF periodogram for the HST data, which are not subject to sidereal-day aliasing. The vertical lines mark the frequencies of synchronous rotation and all of its potential sidereal-day aliases with P > 5 hr. We can see that none of the possible f > 0.5/day aliases of the frequencies identified by the P60 data are good fits to a sinusoidal HST light curve. The lower panel shows the periodogram from joint consideration of the P60, HST, and DES g- and r-band data, after estimated systematic errors are applied to each and the light curve is allowed to have a harmonic. The data strongly select a photometric period consistent with Dysnomia’s orbital frequency.
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: Numerically integrated examples of potential evolution of Dysnomia’s (left) and Eris’s (right) rotation periods, based on the method described in Hastings et al. (2016). All examples assume an initial orbit at 3 × the Roche radius, with a Dysnomia density of 1.2 g cm−3 and nominal k and Q values. Different initial rotation periods are represented by colored dashed lines and correspond to 1, 2, 3, 5, 8, 10, 20, 30, 50, and 100 hr. The black solid curve represents the orbital period as a function of time in each plot. When a rotation period reaches the orbital period, it becomes locked, as indicated by the colored-circle endpoints. When both bodies synchronize, the orbital evolution halts. At this Dysnomia density, Dysnomia’s rotation and orbital periods synchronize in ∼1 Myr, and Eris’s rotation synchronizes within 4.5 Gyr for minimum initial periods ≳20 hr.
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: The model-fitting process for the HST exposures is shown for a random exposure, idl004icq. At left is the processed image from MAST, with CTE correction applied. At center are the residuals to a model of a PSF for Dysnomia (to the lower right of Eris in this image) and a disk-broadened PSF for Eris. At right, the residuals are re-plotted as the χ 2 per pixel using the pixel uncertainties reported by MAST. The residuals in the core of Eris are substantially larger than the statistical errors in the signal, due to the limitations of the PSF models. The residual fluxes can be compared to Eris’s total flux of ≈800 counts s−1.
Paper: Synchronous Rotation in the (136199) Eris–Dysnomia System
Authors: Gary M. Bernstein, Bryan J. Holler, Rosario Navarro-Escamilla, Pedro H. Bernardinelli, T. M. C. Abbott, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, J. Annis, D. Bacon, D. Brooks, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, P. Doel, A. Drlica-Wagner, S. Everett, I. Ferrero, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, J. L. Marshall, J. Mena-Fernández, R. Miquel, R. L. C. Ogando, A. Pieres, A. A. Plazas Malagón, M. Raveri, K. Reil, E. Sanchez, I. Sevilla-Noarbe, M. Smith, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, P. Wiseman
Figure caption: Time series of the P60 V-band measurements. The error bars are statistical only, and do not include calibration errors or systematics. The dotted curve is the model for synchronous rotation and the solar phase curve derived in Section 3.3. The periodicity is marginally visible in these unbinned data—see Figure 6 for phase-folded, binned versions. It is also clear that the phase variations produce a signal of comparable amplitude to the rotational light curve.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: Total wall-clock runtime as a function of aggregate shape for box-filling (a) and collapse (b) simulations run in serial. The blue bars (the left side of the histogram bar pairs) indicate total wall-clock simulation time with the improved search and sorting methods; the red bars (the right side of the pairs) indicate total wall-clock simulation time with the original brute-force search. Black bars indicate time spent in analogous free-sphere simulations, with no aggregate options compiled at runtime.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: A representative example of profiling results from the uniform gravity trials described in Section 3.3. The charts show the fractional simulation time spent on each of the three most computationally expensive sets of calculations both before (a) and after (b) the sort and search method enhancements. For uniform gravity tests like the one shown here, those categories are aggregate operations (blue), neighbor search operations (orange), and all other operations (green). Chart sectors are labeled accordingly. This example was taken from the set of box-filling simulations with N = 6400 member particles bound into a mix of different aggregate shapes and subjected to uniform lunar gravity. Notably, the percentage of simulation time spent in aggregates decreases from 84.6% to 2.1% with the new search and sort methods. The length of time spent on the neighbor search and “Other” functions is constant between panels (a) and (b), but the total simulation time decreases in panel (b) (see Figure 4) due to the decrease in time spent on aggregate operations.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: A representative example of profiling results from the interparticle gravity trials described in Section 3.3 both before (a) and after (b) the efficiency improvements were applied. This test included 20,000 member particles bound into a mix of different aggregate shapes. The set of tests this example was drawn from are described in greater detail in Section 3.3. The two panels are analogous to the ones shown in Figure 2. Note that the second-most computationally expensive protocol in this instance before modification is particle self-gravity, in contrast with the example shown in Figure 2.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: Images of the initial packing of a system of mixed aggregates (color-coded by shape) with a large intruder buried in the medium (a) and the intruder (red) emerging after repeated sinusoidal shaking of the medium (b). Panel (c) is a plot demonstrating the rise of the intruder particle and thus the nonspherical BNE. In panel (c), the red solid line demonstrates the height of the center of the intruder particle, the blue dashed line indicates the median height of the nonintruder particles in the medium, and the black dashed line indicates the initial height of the particle bed.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: Nonspherical constituents or “bonded aggregates” as implemented in pkdgrav. From left to right, a two-particle “dumbbell” shape, a four-particle planar diamond, a four-particle tetrahedron, a four-particle rod, a four-particle cube, and a 155-particle irregular aggregate.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: A grid of plots demonstrating the rise of the intruder particle surrounded by media of different symmetric aggregate shapes, each with the same curves and definitions as described in Figure 7(c). From left to right and top to bottom, the media around the intruders are composed of two-particle dumbbell shapes, four-particle tetrahedra, four-particle planar diamond shapes, four-particle rods, eight-particle cubes, and free spheres.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: A rubble-pile body composed of 5000 bonded aggregates (21,765 particles) before and after a tidal encounter. As in Figure 5, the aggregates are color-coded by shape.
Paper: An Efficient Numerical Approach to Modeling the Effects of Particle Shape on Rubble-pile Dynamics
Authors: Julian C. Marohnic, Joseph V. DeMartini, Derek C. Richardson, Yun Zhang, Kevin J. Walsh
Figure caption: A rubble pile composed of 5000 bonded aggregates (21,765 particles) shedding mass after being subjected to spin-up. Here we use a variety of regular shapes, including cubes, tetrahedra, and four-particle rods, among others. Aggregates are color-coded by shape.