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Modeling Complex Crater Collapse. Gareth Collins and Zibi Turtle Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ 85721, USA. Motivation. To summarize the current state of numerical modeling of complex crater formation.
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Modeling Complex Crater Collapse Gareth Collins and Zibi Turtle Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ 85721, USA
Motivation • To summarize the current state of numerical modeling of complex crater formation. • To highlight the major avenues for further research, both observational and in modeling.
Overview • Why model impact crater collapse? • The fundamentals of modeling collapse • Dynamic rock strength during an impact • Major results from modeling collapse • Where to go from here?
Why model crater collapse? Why model crater collapse? • No direct observation of crater collapse. • Laboratory and nuclear test experiments of limited use to study of crater collapse. • Means of studying dynamics of large crater collapse. • Best instrumented experiment.
Fundamentals of Modeling Importance of the initial conditions • Late stage impact cratering is a very different process to the contact-early excavation stage – sensible to model separately. • Z-model with static starting conditions is an approximation: not appropriate in all cases. • Late stages controlled by gravity and strength – need to model strength differences. • Final crater-transient crater scaling laws not always appropriate either.
Fundamentals of Modeling Importance of the Constitutive Model • Crater collapse is controlled by the competition between gravity and the strength of the target. • The constitutive model describes the response of a material to deformation. • It combines the concepts of: • Elasticity (strain proportional to stress) • Plasticity (elastic until yield stress) • Fluid flow (strain rate a function of stress)
Target Rheology Constitutive Model Used in Impact Simulations • The most commonly used constitutive model for rock material is elastic-plastic. • Yield strength is a function of pressure: • Damage: • and internal energy (temperature):
Target Rheology Coulomb-Von Mises model Yield strength D = 0 D = 1 Cohesion Pressure
Target Rheology Current strength models do not allow sufficient collapse • For standard strength models of rock materials, the transient crater is stable in a gravity field. • First determined using analytical modeling by Dent (1973), then by Melosh (1977) and McKinnon (1978). • All numerical modeling work echos this result.
Target Rheology Standard Strength Model Movie courtesy of Boris Ivanov
Target Rheology Target Weakening Facilitates Crater Collapse Movie courtesy of Boris Ivanov
Target Rheology Something is missing from current strength models • Some form of temporary target weakening is required to facilitate collapse. • Candidates include: • Fragmentation (during shock release or deformation) • Heat (shock or friction melting, thermal softening) • Pressure vibrations (remnant from passing shock) • Dynamic weakening (bulking, strain localization)
Target Rheology Modeling has constrained the required weakening effects • The target’s strength must be reduced by an order of magnitude or more. • A volume of material at least equivalent to the transient crater volume must be weakened. • The weakened material must be mobile enough to overshoot the target surface (<109 Pa-sec, for largest terrestrial crater).
Target Rheology Modeling has constrained the required weakening effects • For external ring formation in multi-ring basins there is an additional constraint. • There must be a weak, mobile layer at depth (Melosh and McKinnon, 1978). • Supported by numerical modeling (Turtle, 1998) and analogue modeling (Allemand and Thomas, 1999).
Results Major recent results • Melosh and Ivanov, 1999 • O'Keefe et al., 2001 • Collins et al., 2002 • Ivanov and Artemieva, 2002 • Shuvalov et al., 2002 • Turtle, 1998 • Allemand and Thomas, 1999
Results Model for Peak-Ring Formation
Results Model for Peak-Ring Formation
Results Model for Peak-Ring Formation
Results Model for Peak-Ring Formation
Results Model for Peak-Ring Formation
Results Model for Peak-Ring Formation
Peak ring identified as a topographic high at ~40km radius, reaching a max. height ~500m. Comparison with observations Peak-Ring Formation Model Supported by Seismic Data Peak ring • Peak ring overlies the base of the slump blocks Weak reflector • Weak, shallow-dipping reflector beneath peak-ring slump blocks
Peak-ring formation due to the collision between the two regimes: Comparison with observations Peak-Ring Formation Model Supported by Seismic Data Outward collapse of central uplift • Inwardly collapsing crater rim Inward collapse of transient crater • Outwardly collapsing central uplift.
Results Subsurface Structure Model for Generic Peak Ring Crater
Results Fate of the Melt? Simulations by Boris Ivanov
Results Fate of the Melt?
Results Chicxulub Formation Model(Courtesy of Dugan O’Keefe)
Results Chicxulub Formation Model
Results Chicxulub Formation Model
Results Summary
Results Key Results • Collapse requires temporary weakening: • Order of magnitude reduction in strength. • Volume of weakened material > Vtc • Material mobile enough to overshoot surface. • External rings also require mobile sub-surface layer • Significant central structural uplift ~ 0.1D • Modeling suggests “over-thrusting” model for peak-ring formation. • Majority of melt lies within the peak ring.
Further Work What is the weakening mechanism? • Current state of modeling cannot distinguish between weakening mechanisms. • How can one distinguish between these mechanisms in the field? • More experimental work needs to be done to understand dynamic rock strength!
Further Work How can we test the models? • Best test is still morphometry. • Need to test peak-ring and structural-uplift models with geological, geophysical and drill core data. • Test predictions of damaged region dimensions. • Test predictions of melt volume and distribution.
Further Work How can we test the models? • Need for code benchmarking. • Test problem comparison for early-stage calculations. • Compare strength models in late-stage codes.