Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves
An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by usi...
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ftnasantrs:oai:casi.ntrs.nasa.gov:20180001225 2023-05-15T18:30:05+02:00 Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves Wheeler, Lorien Tarano, Ana Mathias, Donovan Close, Sigrid Unclassified, Unlimited, Publicly available January 26, 2018 application/pdf http://hdl.handle.net/2060/20180001225 unknown Document ID: 20180001225 http://hdl.handle.net/2060/20180001225 Copyright, Public use permitted CASI Astronomy ARC-E-DAA-TN52016 Stanford Engineering Opportunity Job Fair Details for Students; 26 Jan. 2018; Stanford, CA; United States 2018 ftnasantrs 2019-07-20T23:19:42Z An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment. Other/Unknown Material Tagish NASA Technical Reports Server (NTRS) Canada Tagish ENVELOPE(-134.272,-134.272,60.313,60.313) Tagish Lake ENVELOPE(-134.233,-134.233,59.717,59.717) |
institution |
Open Polar |
collection |
NASA Technical Reports Server (NTRS) |
op_collection_id |
ftnasantrs |
language |
unknown |
topic |
Astronomy |
spellingShingle |
Astronomy Wheeler, Lorien Tarano, Ana Mathias, Donovan Close, Sigrid Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
topic_facet |
Astronomy |
description |
An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment. |
format |
Other/Unknown Material |
author |
Wheeler, Lorien Tarano, Ana Mathias, Donovan Close, Sigrid |
author_facet |
Wheeler, Lorien Tarano, Ana Mathias, Donovan Close, Sigrid |
author_sort |
Wheeler, Lorien |
title |
Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
title_short |
Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
title_full |
Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
title_fullStr |
Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
title_full_unstemmed |
Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves |
title_sort |
genetic algorithm-based optimization to match asteroid energy deposition curves |
publishDate |
2018 |
url |
http://hdl.handle.net/2060/20180001225 |
op_coverage |
Unclassified, Unlimited, Publicly available |
long_lat |
ENVELOPE(-134.272,-134.272,60.313,60.313) ENVELOPE(-134.233,-134.233,59.717,59.717) |
geographic |
Canada Tagish Tagish Lake |
geographic_facet |
Canada Tagish Tagish Lake |
genre |
Tagish |
genre_facet |
Tagish |
op_source |
CASI |
op_relation |
Document ID: 20180001225 http://hdl.handle.net/2060/20180001225 |
op_rights |
Copyright, Public use permitted |
_version_ |
1766213564905816064 |