Mathematical model for estimation of meteoroid dark flight trajectory

Vinnikov, Vladimir; Gritsevich, Maria; Turchak, L. I.

doi:10.1063/1.4965020

Cited by 5 publications

(6 citation statements)

References 11 publications

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“…Fireball observations can be also used to infer the individual trajectories of fragments resulting from atmospheric fragmentation. Together with modelling the dark flight, which constitutes the lower part of the trajectory following the termination of the luminous flight, this leads to a con-struction of a strewn field map showing where meteorites could be potentially recovered on the ground [1045,1046].…”

Section: Meteorsmentioning

confidence: 99%

Ultra-High-Energy Cosmic Rays: The Intersection of the Cosmic and Energy Frontiers

Coleman,

Eser,

Mayotte

et al. 2022

Preprint

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Pin down the shower energy observable to use μ as a composition-only Reduce hadronic uncertainties interaction model E threshold (TBD) Other messengers Galactic * μ / em separation † * depending on analysis progress † depending on detector configuration• At least one next-generation experiment needs to be able to make high-precision measurements to explore new particle physics and measure particle rigidity on an event-by-event basis. Of the planned next-generation experiments, GCOS is the best positioned to meet this recommendation.• As a complementary effort, experiments with sufficient exposure ( 5 × 10 5 km 2 sr yr) are needed to search for Lorentz-invariance violation (LIV), SHDM, and other BSM physics at the Cosmic and Energy Frontiers, and to identify UHECR sources at the highest energies.• Full-sky coverage with low cross-hemisphere systematic uncertainties is critical for astrophysical studies. To this end, next generation experiments should be space-based or multi-site. Common sites between experiments are encouraged.• Based on the productive results from inter-collaboration and inter-disciplinary work, we recommend the continued progress/formation of joint analyses between experiments and with other intersecting fields of research (e.g., magnetic fields).• The UHECR community should continue its efforts to advance diversity, equity, inclusion, and accessibility. It also needs to take steps to reduce its environmental impacts and improve open access to its data to reduce the scientific gap between countries.vi

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Section: Meteorsmentioning

confidence: 99%

Ultra-High-Energy Cosmic Rays: The Intersection of the Cosmic and Energy Frontiers

Coleman,

Eser,

Mayotte

et al. 2022

Preprint

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“…Furthermore we aim at introducing into the code a build-in recalculation for the realistic atmospheric conditions after Lyytinen & Gritsevich (2016) and see how these could improve the results. We will also calculate the dark-flight trajectory for events identified in the "likely fall" and "possible fall" regions with the algorithms presented in Vinnikov et al (2016), Moilanen et al (2021), andBoaca et al (2021). We plan to apply the algorithm to detections of the FRIPON in other countries.…”

Section: Discussionmentioning

confidence: 99%

Characterization of the Fireballs Detected by All-sky Cameras in Romania

Boacă

Gritsevich

Birlan

et al. 2022

ApJ

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Some of the fields of research that have captured the persistent interest of both scientists and the general public are meteor phenomena. The main goal in the study of meteoroid impacts into Earth’s atmosphere is the recovery of the remnant matter after the ablation in the form of meteorites. This is a complementary approach, yet cheap alternative, to a sample return mission. Meteoroids are messengers since the time of the formation of the solar system due to the fact that they have preserved the same composition. The study of meteorites provides information regarding the chemical composition from which the planets formed. The increasing number of all-sky camera networks in recent years has resulted in a large set of events available for study. Thus, it is very important to use a method that determines whether the meteoroid could produce a meteorite or not. In this paper we study the meteors detected by the FRIPON network in Romania with the use of all-sky cameras. We focus on the events with noticeable deceleration (V f /V 0 < 0.8). We determine the ballistic coefficient α and the mass-loss parameter β for the selected sample. Based on this analysis the events are classified in three categories: (1) meteoroids that are likely to produce meteorites; (2) meteoroids that can possibly produce meteorites; (3) meteoroids that are unlikely to produce meteorites. The entry and final mass are determined for each event. From the recorded fireballs, we identified one possible meteorite dropper, and we analyzed its dynamical evolution.

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“…One can also impose the further condition that the transition from bright to dark-flight must be smooth; most importantly, this means that the rate of change of acceleration should be smooth from bright to dark flight (see Ceplecha 1987). The DFN approach for the core procedure is monotonic; we assume that shape does not change during descent and that there is no fragmentation (see Vinnikov et al 2016). In reality, it is quite possible for fragmentation to occur during the dark flight, as seen in meteorites recovered with broken or missing fusion crust (Folinsbee & Bayrock 1961;Spurný et al 2012).…”

Section: Overviewmentioning

confidence: 99%

“…The shape may also vary during the bright-flight phase owing to ablation or fragmentation, although it is commonly assumed to be fixed during dark flight. (An exception is the dark-flight modeling of Vinnikov et al 2016. ) One approach, as taken by Ceplecha (1987) and similarly used for bright-flight modeling (Ceplecha et al 2000;Revelle 2002;Sansom et al 2015), is to combine these parameters of shape, density, and mass to generate a shape-density parameter (since none of these parameters can be independently constrained from observations) and then use values derived from bright flight as an input to dark-flight modeling.…”

Section: Complicating Factorsmentioning

confidence: 99%

“…The details of the drag coefficient behaviors chosen do not appear to be discussed in detail in dark-flight papers, with the notable exception of detailed modeling such as Vinnikov et al (2016). Apart from meteorite properties, drag coefficient is dependent on many conditions, such as the velocity, the Mach number, and the density of air, all of which vary in dark flight as one goes from the supersonic regime in low-density air to a subsonic regime in high-density turbulent air, close to the ground.…”

Section: Complicating Factorsmentioning

confidence: 99%

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Dark-flight Estimates of Meteorite Fall Positions: Issues and a Case Study Using the Murrili Meteorite Fall

Towner¹,

Jansen‐Sturgeon²,

Cupák³

et al. 2022

Planet. Sci. J.

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Fireball networks are used to recover meteorites, with the context of orbits. Observations from these networks cover the bright flight, where the meteoroid is luminescent, but to recover a fallen meteorite, these observations must often be predicted forward in time to the ground to estimate an impact position. This dark-flight modeling is deceptively simple, but there is hidden complexity covering the precise interactions between the meteorite and the (usually active) atmosphere. We describe the method and approach used by the Desert Fireball Network, detailing the issues we have addressed, and the impact that factors such as shape, mass, and density have on the predicted fall position. We illustrate this with a case study of Murrili meteorite fall that occurred into Lake Eyre-Kati Thanda in 2015. The fall was very well observed from multiple viewpoints, and the trajectory was steep, with a low-altitude endpoint, such that the dark flight was relatively short. Murrili is 1.68 kg with a typical ordinary chondrite density but with a somewhat flattened shape compared to a sphere, such that there are discrepancies between sphere-based predictions and the actual recovery location. It is notable that even in this relatively idealized dark-flight scenario, modeling using spherically shaped projectiles resulted in a significant distance between predicted fall position and recovered meteorite.

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Mathematical model for estimation of meteoroid dark flight trajectory

Cited by 5 publications

References 11 publications

Ultra-High-Energy Cosmic Rays: The Intersection of the Cosmic and Energy Frontiers

Ultra-High-Energy Cosmic Rays: The Intersection of the Cosmic and Energy Frontiers

Characterization of the Fireballs Detected by All-sky Cameras in Romania

Dark-flight Estimates of Meteorite Fall Positions: Issues and a Case Study Using the Murrili Meteorite Fall

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