Roberto Gorelli points our attention at a recently published meteor related paper:

Inferring Fireball Velocity Profiles and Characteristic Parameters of Meteoroids from Incomplete Datasets

This article has been submitted by Eloy Peña-Asensio and Maria Gritsevich.

Abstract: Extracting additional information from old or incomplete fireball datasets remains a challenge. To address missing point-by-point observations, we introduce a method for estimating atmospheric flight parameters of meteoroids using metaheuristic optimization techniques. Using a fireball catalog from the European Fireball Network (EN), we reconstruct velocity profiles, meteoroid bulk densities, mass loss rates, and ablation and ballistic coefficients, based on the initial and terminal points’ height, velocity, and mass with the purely dynamical α-β model. Additionally, the method’s performance is compared to the Meteorite Observation and Recovery Project (MORP) derived fits, confirming the robustness of the computed parameters for objects with asteroidal compositions. Our findings show that α-β model yields parameters consistent with the photometric and dynamic mass estimates in the EN catalog for PE type I events. However, in the implementation proposed here, α-β model encounters limitations in accurately representing the final deceleration of more fragile high-velocity meteoroids. This is likely due to challenges in representing complex fragmentation processes by fitting only two points, even when initial and terminal residuals are minimal. The retrieved α-β distribution differs from the one derived from MORP data, likely due to the imposed mass constraints, which strongly influence the results, especially the bulk density. The results suggest that PE constraints reduce fitting accuracy (from 90% to 44%), while flexibility and freedom from assumptions improve α-β performance. The method yields 26% of the events compatible with the catalog PE classification. Our approach is well-suited for interpreting historical or sparse datasets.

You can download this paper for free:  https://arxiv.org/pdf/2504.10715  (32 pages).

 

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