Meteorite Strewn Fields from Asteroid Airbursts
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Accurately assessing asteroid threats relies on knowledge of the asteroid’s pre-entry properties such as size, velocity, and mass. Directly measuring these properties can be infeasible due to the sparsity of events and the accuracy and fidelity of various sensors. Current analysis of an asteroid’s pre-entry properties involves modeling the asteroid’s entry into the Earth’s atmosphere. This process can be time consuming and can require manual adjustment of uncertain modeling specific parameters. NASA Ames has developed a genetic algorithm that can help automate asteroid modeling using the Fragment-Cloud Model (FCM). The algorithm generates realistic energy deposition curves based on actual energy deposition curves from real, observed asteroids. By using these synthetic, labeled energy deposition curves, we developed a one-dimensional convolutional neural network that can predict an asteroid’s pre-entry parameters.
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Blast overpressure is the predominant source of ground damage posed by potentially hazardous asteroid strikes. Estimates of the extent, severity, and likelihoods of potential blast damage regions will be one of the key metrics needed to mount civil defense or disaster response plans in the face of an impending impact. However, there are many inherent sources of uncertainty in evaluating the damage, both in characterizing the properties of the incoming object and in the approaches used to model the entry/impact and resulting damage, which make it difficult to produce a single ‘accurate’ or ‘best guess’ prediction of ground damage. The current 2021 PDC hypothetical impact scenario poses a particular challenge due to its short warning time. The need for rapid disaster response to prepare for an immanent impact, combined with lack of observational opportunities to refine basic knowledge about the object’s basic size and properties, make understanding the range and relative likelihood of consequences particularly critical. The potential damage caused by these blasts can be evaluated using a range of modeling and simulation approaches and levels of fidelity. Fast-running engineering-level models can be used to run large numbers of probabilistically sampled cases covering wide variations of uncertain properties or parameters. High-fidelity simulations, on the other hand, can capture more detailed/accurate blast physics, but can only be performed for a small selection of specific cases, requiring many assumptions to be made about the initial object and its unpredictable entry/breakup characteristics. In order to provide a more complete picture of the potential threat for effective disaster response, both types of analysis need to be employed together. In this approach, high-fidelity simulations are used to refine and anchor engineering models, and the probabilistic engineering models are used to evaluate broad parameters spaces and guide selection of the most pertinent simulation cases for a given scenario. This presentation expands upon the probabilistic asteroid impact risk assessments being performed as part of the 2021 PDC hypothetical impact exercise, focusing on key aspects of blast damage modeling uncertainties and sensitivities. We review the current modeling and simulation approaches employed in the current assessment, compare the relative levels of uncertainty stemming from each main element of the problem (i.e., knowledge of the asteroid properties, modeling of the atmospheric entry/breakup and airburst, and estimates of the ground damage from the resulting blasts waves), and highlight any notable trends and sensitivities for the current scenario case.
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This presentation provides an introductory overview of key factors involved in the asteroid impact threat assessment and risk modeling performed for the Planetary Defense Conference hypothetical impact exercises.
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Lessons from Analogs - Hurricanes - Forecasting in time to take action - Large scale evacuations - Risk tolerance - Nuclear Explosions - Effects of large blast waves - Shelters - Fatality rates Application to Asteroid Impacts - PDC 2021: small, little warning, poorly constrained - PDC 2023: large, well characterized
NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 PDC hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.
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