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116 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Atmospheric Energy Deposition Modeling and Inference for Varied Meteoroid Structures

Asteroids populations are highly diverse, ranging from coherent monoliths to loosely-bound rubble piles with a broad range of material and compositional properties. These different structures and properties could significantly affect how an asteroid breaks up and deposits energy in the atmosphere, and how much ground damage may occur from resulting blast waves. We have previously developed a fragment-cloud model (FCM) for assessing the atmospheric breakup and energy deposition of asteroids striking Earth. The approach represents ranges of breakup characteristics by combining progressive fragmentation with releases of variable fractions of debris and larger discrete fragments. In this work, we have extended the FCM to also represent asteroids with varied initial structures, such as rubble piles or fractured bodies. We have used the extended FCM to model the Chelyabinsk, Benesov, Kosice, and Tagish Lake meteors, and have obtained excellent matches to energy deposition profiles derived from their light curves. These matches provide validation for the FCM approach, help guide further model refinements, and enable inferences about pre-entry structure and breakup behavior. Results highlight differences in the amount of small debris vs. discrete fragments in matching the various flare characteristics of each meteor. The Chelyabinsk flares were best represented using relatively high debris fractions, while Kosice and Benesov cases were more notably driven by their discrete fragmentation characteristics, perhaps indicating more cohesive initial structures. Tagish Lake exhibited a combination of these characteristics, with lower-debris fragmentation at high altitudes followed by sudden disintegration into small debris in the lower flares. Results from all cases also suggest that lower ablation coefficients and debris spread rates may be more appropriate for the way in which debris clouds are represented in FCM, offering an avenue for future model refinement.

Deposition↗
NASA NTRS2003

Chemical Analysis of Primitive Objects Using a Slitless Ultraviolet Meteor Spectrometer (CAPO-SUMS)

Measure the elemental composition in both random meteors and in the bolides forming specific meteor streams (these are traceable to specific small bodies in the solar system). These will yield the average chemical composition and degree of chemical variability in a statistically significant number of planetesimals. CAPO-SUMS is functionally equivalent to a series of multiple, small-body sample analysis missions, but provides much more analytical capability than is possible on any orbital or flyby mission due to the vaporization, ionization and ultraviolet emission from the ablating bolide as it enters the atmosphere. CAPO-SUMS will provide a chemical context from which the detailed analytical studies provided by a cometary or asteroidal lander mission can be interpreted.

Nuth, J. A.↗
NASA NTRS2017

Simultaneous Optical and Meteor Head Echo Measurements Using the Middle Atmosphere Alomar Radar System (MAARSY)

We describe a two year campaign of simultaneous automated meteor optical and head echo radar measurements conducted with the Middle Atmosphere Alomar Radar System (MAARSY). This campaign was established with the following goals: Compare trajectories as measured by MAARSY and the two optical stations for a range of meteoroid masses. Compare photometric and dynamic mass measured optically with radar-derived masses (inter-calibration of mass scales). Use the best observed simultaneous events to fuse all metric, photometric and ionization estimates together and apply different ablation models to self-consistently model these highest quality events.

Cooke, W. J.↗
NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗
NASA NTRS2018

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 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.

Depositio↗
NASA NTRS2000

Comparison of 1998 and 1999 Leonid Light Curve Morphology and Meteoroid Structure

Photometric low-light level video observations of 1999 Leonid storm meteors have been obtained from airborne platforms during the Leonid multi-instrument aircraft campaign (Leonid MAC). The 1999 Leonid light curves tend to be skewed towards the end point of the trajectory, while the 1998 Leonid light curves were not. The variation in the light curves from 1998 and 1999 can be explained as an overall reduction in the mass distribution index, alpha from approximately 1.95 in 1998 to approximately 1.75 in 1999. We have interpreted this behavior as being either indicative of a gradual loss of the "glue" that keeps the grains together, or the fact that the meteoroids sampled in 1998 had a different morphological structure to those sampled in 1999. The early fragmentation of a dustball meteoroid results in a light curve that peaks sooner than that predicted by classical single body ablation theory.

Murray, Ian S.↗
NASA NTRS2016

Asteroid Fragmentation Approaches for Modeling Atmospheric Energy Deposition

During asteroid entry, energy is deposited in the atmosphere through thermal ablation and momentum-loss due to aerodynamic drag. Analytic models of asteroid entry and breakup physics are used to compute the energy deposition, which can then be compared against measured light curves and used to estimate ground damage due to airburst events. This work assesses and compares energy deposition results from four existing approaches to asteroid breakup modeling, and presents a new model that combines key elements of those approaches. The existing approaches considered include a liquid drop or "pancake" model where the object is treated as a single deforming body, and a set of discrete fragment models where the object breaks progressively into individual fragments. The new model incorporates both independent fragments and aggregate debris clouds to represent a broader range of fragmentation behaviors and reproduce more detailed light curve features. All five models are used to estimate the energy deposition rate versus altitude for the Chelyabinsk meteor impact, and results are compared with an observationally derived energy deposition curve. Comparisons show that four of the five approaches are able to match the overall observed energy deposition profile, but the features of the combined model are needed to better replicate both the primary and secondary peaks of the Chelyabinsk curve.

Modeling↗
NASA NTRSDate not supplied

Recent Advances in the U.S. in Ablative TPS for In-situ Exploration of Giant Planets

The Decadal Survey report released [1] prioritizes Uranus as the highest priority Flagship class mission to be explored with an orbiter and a probe and it also recommended Saturn Probe under New Frontiers mission class. Thermal protection system (TPS) is essential for Uranus and Saturn probe missions. The two cardinal requirements are that it must be fail-safe and yet be mass efficient. The Decadal Survey report also pointed out the readiness of heatshield for extreme entry environment technology (HEEET) at TRL 6 for probe missions at Gas Giants. HEEET relies on 3-D weaving and is shown to be a robust and mass efficient TPS through ground testing and analysis. HEEET was matured to TRL 6 in 2019. HEEET was reported at the Ice Giant Workshop in 2019 at Marseille. Since 2019, significant advances have been made primarily because of Mars Sample Return (MSR) mission. MSR baselined 3-D Woven TPS as its heatshield for the earth entry system. MSR earth entry system (EES) requirements and the resulting heatshield/TPS requirements are most stringent of all entry missions. This is a result of backward contamination protection which classifies MSR as a “restricted class 5” mission to safeguard the accidental release of potentially hazardous Mars Sample into Earth’s atmosphere. Complex requirements for the heatshield start with micro-meteor impact tolerance followed by the requirement for steep entry to minimize the size of the impact footprint which results in extreme heating. The heatshield is part of the impact attenuation system. The EES architecture does not use a parachute and is designed to tolerate impact loads. Hence heatshield TPS selection and design becomes one of the key challenges. After completion of the HEEET technology maturation in 2019, IRAD efforts focused on assessing the 3-D Woven family of TPS to MSR EES. After nearly two years of evaluation of alternate TPS such as carbon phenolic, C-C hot structure, PICA, and 3-D woven family of TPS, a single layer 3-D woven TPS derived from the dual-layer HEEET was down selected and is currently the baseline. A new loom capable of weaving the single-layer 3-D woven preform at 80” wide has been designed, assembled and is currently on the verge of weaving the MSR EES TPS. During the HEEET maturation and the follow-on development, the single-layer TPS has been tested at extreme heating conditions. As a result, single layer TPS was recommended and evaluated during the Planetary Mission Concept Studies funded by NASA in preparation for the Decadal committee. In addition, in anticipation of Saturn mission proposals, single layer was evaluated as well. Aerocapture can reduce the trip time, also allow bigger payload fraction and in addition, it allows for the possibility of probe delivery once the spacecraft is in orbit. This can lead to obtaining both in-situ data as well as data from orbit simultaneously. Since Aerocapture depletes energy/velocity, probe delivery from orbit reduces the demand on TPS. Aerocapture was mentioned in the Decadal Study report as ready for implementation, but due to perceived risk it is not adopted by the mission designers. Establishing TPS readiness for aerocapture missions will be addressed. Going one step beyond aerocapture is aerogravity assist if fast return is the goal. Recent studies [4] looked at aerogravity assist and the TPS readiness. This talk will highlight both aerocapture and aerogravity assist from a TPS perspective. The main objective of this proposed talk is to present a comprehensive picture of the SOA TPS technology including recent developments. The talk will highlight advances in manufacturing, results from the Decadal White Papers, PMCS and other studies, and aerocapture and aerogravity assist that could play a role in the near or far term in-situ exploration.

E. Venkatapathy↗