MétaCan
Menu
← Retour à la cohorte
Enregistrement W3096640497 · doi:10.5194/epsc2020-64

Classification of fireballs: upgrading the PE criterion

2020· article· en· W3096640497 sur OpenAlexaff
Manuel Moreno-Ibáñez, Maria Gritsevich, J. M. Trigo‐Rodríguez, Elizabeth A. Silber, Jouni Peltoniemi

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueAstro and Planetary Science
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésMeteor (satellite)MeteoroidValue (mathematics)Interpretation (philosophy)Computer scienceArtificial intelligenceOperations researchMeteorologyStatisticsMathematicsPhysicsMachine learningAstronomy

Résumé

récupéré en direct d'OpenAlex

The visual observation of meteors has gathered over the last century the interest of scientists and the fascination of public. As the meteor observational techniques were spread worldwide, the meteor research community was avid of reliable mathematical relationships to derive further clues on these events: their orbital origin, their hazardous potential, etc. For such purpose, the combination of the meteor event observed flight parameters seemed to comply with these goals. Moreover, this approach was little by little more feasible given the technology growth that gradually improved the accuracy of the observations. Amongst all the suggested flight parameter relationships available in the literature, the one introduced by Ceplecha and McCrosky [1] in the mid 70’s became timely and used in many studies as a ‘ground truth’. The empirical work of Ceplecha and McCrosky [1] was also mathematically supported by the single body Newtonian formulation that is still widely used to model the meteor trajectory [2]. Moreover, Ceplecha and McCrosky [1] expanded the use of this relationship to elaborate a meteor classification. The classification relies on the value of a criterion, called PE, which ranks the value of the correlation given by the parameters included in the relationship. Although the authors did not expect the classification to be extremely accurate, it allows quick interpretation of the event under study. Consequently, both the criterion and the classification have played a relevant role in the scientific publication over the decades.The PE criterion relates the meteor observed end height to its atmospheric entry velocity, mass and flight trajectory angle. To keep the PE calculation straightforward, and because it originally was used for decelerating events, the influence of the meteoroid mass loss (ablation and shape coefficient) was simplified and a mean value for all the meteors registered in the same database was assumed. In the recent years, several alternative formulations for the meteoroid atmospheric flight modelling have been proposed in order to reduce the required analysis-related assumptions and consequent results’ inaccuracies. Amongst them, a formulation based on scaling laws and dimensionless variables has obtained significant results when tackling with different common meteor related studies (see e.g. [3-9]). The main advantage of this methodology is that it provides relevant clues on the event under study removing the necessity of stating initial assumptions on the meteor parameters. Additionally, the accuracy of the outcome is, in most cases, directly linked to the quality of the observations. Interestingly, this new methodology quantifies the meteoroid mass loss in a unique and straightforward way by matching the meteor trajectory (observed height and velocity values) with two dimensionless parameters that are physically meaningful. On one hand, the ballistic coefficient, α, expresses the drag intensity suffered by the meteor body during its flight and it is proportional to the mass of the atmospheric column with the initial meteoroid cross section area along the trajectory divided by the meteoroid’s pre-atmospheric mass. On the other, the mass loss parameter, β, characterizes the mass loss rate of the meteoroid; it can be expressed as the fraction of the kinetic energy per mass unit of the body that is transferred to the body in the form of heat divided by the effective destruction enthalpy.Since these two parameters comprise all the meteoroid flight variables earlier included in the PE criterion, but avoid artificial assumptions, we have proposed and studied the hypothesis that there should exist a mathematical expression involving these two parameters which offers an improved classification criterion [2]. In this work, we verify this hypothesis. The results of our study show that: i) under the same original assumptions [1] the derived log(2αβ) which we advocate using leads to the exactly same PE formula obtained by Ceplecha and McCrosky [1]; ii) the newly offered possibility to include the individual event mass-loss effects in the criterion allows an accurate formulation that still remains simple to implement; iii) the improved criterion is scalable – it is suitable for expanding the classification beyond fully disintegrating fireballs to larger impactors, including meteorite-dropping fireballs. We use the Prairie Network meteor observations for comparative analysis, which demonstrates the effectiveness and reliability of the new formulation.References[1] Ceplecha Z., McCrosky R. E.,1976, JGR, 81, 6257. https://doi.org/10.1029/JB081i035p06257[2] Moreno-Ibáñez M., Gritsevich M., Trigo-Rodriguez J. M., Silber E. A., 2020, MNRAS, 494 (1), 316. https://doi.org/10.1093/mnras/staa646[3] Gritsevich M. I., 2009, Adv. Space Res., 44(3), 323. http://dx.doi.org/10.1016/j.asr.2009.03.030[4] Gritsevich M. I., Stulov V. P., Turchak L. I.,2012, Cosmic Res., 50(1), 56. http://dx.doi.org/10.1134/S0010952512010017[5] Bouquet A., Baratoux D., Vaubaillon J., et al. 2014, PSS, 103, 238. http://dx.doi.org/10.1016/j.pss.2014.09.001[6] Moreno-Ibáñez M., Gritsevich M., Trigo-Rodríguez J. M., 2015, Icarus, 250, 544. http://dx.doi.org/10.1016/j.icarus.2014.12.027[7] Trigo-Rodríguez J. M., Lyytinen E., Gritsevich M., et al., 2015, MNRAS,449 (2), 2119. http://dx.doi.org/10.1093/mnras/stv378[8] Lyytinen E., Gritsevich M., 2016, PSS, 120, 35. http://dx.doi.org/10.1016/j.pss.2015.10.012[9] Sansom E. K., Gritsevich M., Devillepoix H. A. R., et al., 2019, ApJ, 885 (2). https://doi.org/10.3847/1538-4357/ab4516

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,029
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,026

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,029
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0080,003
Études des sciences et des technologies0,0010,001
Communication savante0,0030,004
Science ouverte0,0020,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,238
Écart entre enseignants0,207 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même sujetAstro and Planetary Science→Travaux en français237 207→