Simulation of the airwave caused by the Chelyabinsk superbolide

Avramenko, M.; Glazyrin, I. V.; Ionov, G.V.; Karpeev, Artem

doi:10.1002/2013jd021028

Cited by 30 publications

(42 citation statements)

References 13 publications

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“…This extent of blast damage is very consistent with 3D numerical simulations of blastwave propogation using an energy deposition model similar to the cylindrical line‐source approach employed here (Avramenko et al. ; Aftosmis et al. ).…”

Section: Resultssupporting

confidence: 86%

“…Fragmentation is commonly assumed to occur when the ram pressure in front of the meteoroid (the local air density times the meteoroid velocity squared), exceeds the meteoroid's strength. Beyond the fragmentation point, an additional equation is required to describe the increase in cross-sectional area of the disrupted rock mass as it deforms in response to aerodynamic stresses, decelerates, and penetrates denser air (e.g., Chyba et al 1993;Hills and Goda 1993;Avramenko et al 2014).…”

Section: Pancake Model Of Meteoroid Disruption In the Atmospherementioning

confidence: 99%

“…In this case, meteoroid spreading ceases when the ram pressure in front of the meteoroid drops below the strength of the meteoroid. Another, more recent meteoroid disruption model (Avramenko et al 2014) derives an alternative spreading rate using dimensional analysis and a chainreaction analogy for the cascading disruption of meteoroid fragments. Like the fragment cloud model, spreading is arrested when the ram pressure drops below the fragments' strength; however, in this case, the strength of the fragments is assumed to increase with time as fragment size decreases.…”

Section: Pancake Model Of Meteoroid Disruption In the Atmospherementioning

confidence: 99%

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A numerical assessment of simple airblast models of impact airbursts

Collins

Lynch

McAdam

et al. 2017

Meteorit & Planetary Scien

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Abstract-Asteroids and comets 10-100 m in size that collide with Earth disrupt dramatically in the atmosphere with an explosive transfer of energy, caused by extreme air drag. Such airbursts produce a strong blastwave that radiates from the meteoroid's trajectory and can cause damage on the surface. An established technique for predicting airburst blastwave damage is to treat the airburst as a static source of energy and to extrapolate empirical results of nuclear explosion tests using an energy-based scaling approach. Here we compare this approach to two more complex models using the iSALE shock physics code. We consider a moving-source airburst model where the meteoroid's energy is partitioned as twothirds internal energy and one-third kinetic energy at the burst altitude, and a model in which energy is deposited into the atmosphere along the meteoroid's trajectory based on the pancake model of meteoroid disruption. To justify use of the pancake model, we show that it provides a good fit to the inferred energy release of the 2013 Chelyabinsk fireball. Predicted overpressures from all three models are broadly consistent at radial distances from ground zero that exceed three times the burst height. At smaller radial distances, the moving-source model predicts overpressures two times greater than the static-source model, whereas the cylindrical line-source model based on the pancake model predicts overpressures two times lower than the static-source model. Given other uncertainties associated with airblast damage predictions, the static-source approach provides an adequate approximation of the azimuthally averaged airblast for probabilistic hazard assessment.

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Section: Resultssupporting

confidence: 86%

Section: Pancake Model Of Meteoroid Disruption In the Atmospherementioning

confidence: 99%

Section: Pancake Model Of Meteoroid Disruption In the Atmospherementioning

confidence: 99%

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A numerical assessment of simple airblast models of impact airbursts

Collins

Lynch

McAdam

et al. 2017

Meteorit & Planetary Scien

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“…Assuming that the earthquake was mainly caused by the shock wave pressure loaded on an area of no more than 30 km radius, and combining this assumption with the single‐force model obtained above, we estimate the average pressure to have been 0.36 kPa. In contrast, the pressures on central Chelyabinsk provided by most researchers (e.g., Emel'yanenko et al, ; Brown et al, 2013; Chernogor and Rozumenko, ; Avramenko et al, ) range from 0.7 kPa to 3.8 kPa. Apparently, our estimation of the average pressure is smaller than the value of the previously determined pressure at central Chelyabinsk.…”

Section: Discussionmentioning

confidence: 93%

“…Nevertheless, it is extremely difficult to accurately estimate the yield of a bolide because of uncertainties in the meteoroid trajectory, atmosphere structure, wind speed, and air‐ground coupling. Several investigators published yield estimates for this bolide explosion, but the results vary from a few kilotons to 58 megatons (Mt) (e.g., Seleznev et al, ; Avramenko et al, ; Chernogor and Rozumenko, ; Krasnov et al, ; Lobanovsky, ). Based on the extent of window breakage in Chelyabinsk, Emel'yanenko et al () calculated the corresponding overpressure to estimate the explosive energy of the bolide and obtained yield estimates between 300 and 500 kilotons (kt).…”

Section: Introductionmentioning

confidence: 99%

Seismic characteristics of the 15 February 2013 bolide explosion in Chelyabinsk, Russia

Wei

Zhao

Xie

et al. 2018

Earth and Planetary Physics

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The seismological characteristics of the 15 February 2013 Chelyabinsk bolide explosion are investigated based on seismograms recorded at 50 stations with epicentral distances ranging from 229 to 4324 km. By using 8–25 s vertical‐component Rayleigh waveforms, we obtain a surface‐wave magnitude of 4.17±0.31 for this event. According to the relationship among the Rayleigh‐wave magnitude, burst height and explosive yield, the explosion yield is estimated to be 686 kt. Using a single‐force source to fit the observed Rayleigh waveforms, we obtain a single force of 1.03×1012 N, which is equivalent to the impact from the shock wave generated by the bolide explosion.

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Uncertainty quantification in continuous fragmentation airburst models

McMullan

Collins

2019

Icarus

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As evidenced by the Chelyabinsk and Tunguska airburst events in Russia, decameterscale Near-Earth Objects (NEOs) can pose a hazard to human life and infrastructure from the energy they deposit in the atmosphere as they break up.To understand the potential damage these small NEOs can cause on Earth's surface, it is imperative to be able to model their atmospheric entry quickly and accurately. Here we compare three semi-analytical models of asteroid airbursts that differ in their descriptions of fragment separation and spreading.Each model can be calibrated to produce a good fit to the energy deposition curve inferred from Chelyabinsk observations, but in each case the implied initial meteoroid strength is different and when the calibrated models are upscaled to Tunguska, the results diverge. This introduces an inter-model uncertainty that compounds the large range of uncertain physical and model parameters that influence probabilistic hazard assessment. Uncertainty quantification of airburst energy deposition was performed for a theoretical impacting object with H-magnitude 27, assuming no prior knowledge of any other impactor or model parameter. Each of the three models produces a different distribution of airburst outcomes, however, the variation attributable to physical parameter uncertainty is far larger than the inter-model differences. To constrain the initial conditions of the Tunguska event, the same uncertainty quantification was performed for an H-magnitude 24 event. Among the scenarios consistent with Tunguska observations (5-10 km burst altitude, 10-60 • trajectory angle, 3-50

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Simulation of the airwave caused by the Chelyabinsk superbolide

Cited by 30 publications

References 13 publications

A numerical assessment of simple airblast models of impact airbursts

A numerical assessment of simple airblast models of impact airbursts

Seismic characteristics of the 15 February 2013 bolide explosion in Chelyabinsk, Russia

Uncertainty quantification in continuous fragmentation airburst models

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