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James Cassanelli – GEOL 2810 – April 6, 2015

Week 9 – Summary: Pierazzo et al. (2008) – Validation of Numerical Codes for Impact and Explosion Cratering: Impacts on Strengthless and Metal Targets

Broad objective: To compare, validate, and benchmark several widely used shock codes in planetary applications against laboratory scale experimental results.

SHORT TITLE HERE: A. B. Author and C. D. Author

Introduction: Impacts are a geological process of fundamental importance in planetary evolution. While these processes have played a critical role in shaping the terrestrial planets, the scale, and (at least current) rarity, of these events prevent direct observations and as a result are not fully understood. Significant advances in computational ability have allowed computer simulations to be adapted to model these processes which has led to great new insights. However, despite the wide use of these numerical codes in modeling planetary impact processes, little work has been done to validate and benchmark the codes against currently available laboratory and field data. The authors of this study implement several popular impact simulation codes to model simplified impact scenarios and compare the various model predictions to experimental results in order to validate and benchmark the numerical codes.

Figure 1. Experimental set-up implemented for shock code benchmarking.

Numerical Codes: The numerical shock codes tested in this study include: AUTODYN, SOVA, SPH, ZEUS-MP, iSALE, CTH, RAGE/SAGE, and ALE3D. While the ultimate goal of all of these models is the same, the numerical methods applied in each differ to at least some extent. The primary differences between the listed numerical codes are the treatment of the model space used to solve the conservation equations, and the constitutive relations applied to predict the behavior of materials involved in the model. These different numerical treatments lead to systematic differences in the predictions made by the models when applied to identical test problems.

Benchmarking and Validation: In order to validate the predictions of the numerical codes, the authors benchmark the models against two simulation scenarios: (1) an “early-time simulation” which focuses on the early stages of the impact process involving peak shock pressure, pressure decay, temperature evolution, and melting/vaporization. This simulation is carried out by comparing model predictions of an aluminum sphere impacting an aluminum impact to laboratory experimental results. (2) A “late time simulation” which focuses on processes that occur later in the impact event including excavation cessation, which relies on a properly defined material strength model. This simulation is carried out by comparing model predictions of a glass sphere impacting a water target to laboratory experimental results.

The benchmarking carried out in this study shows inter-code variability in shock pressure predictions generally within the range of ~10-20 %. More significant inter-code variability can result from improper code setup which demonstrates the need for care when implementing these shock physics codes.

The deviation of model predictions from experimental results obtained during benchmarking show generally good agreement, with deviations similar in magnitude to the inter-code variability, in the range of ~10-20%. Although interestingly, the shock codes appear to have a tendency to underestimate the crater radius. During the benchmarking procedues, more significant discrepancies were observed between the model predictions and the experimental results, however these were found to be due to problematic initial or boundary conditions. This further underscores the need for careful shock code implementation.

Discussion Questions:

1) Given the discrepancies between the model predictions and laboratory scale test results, what could be some of the issues that might arise when applying shock codes to basin-scale impact events?

2) It was shown in the paper that the accuracy of the model predictions can be heavily influenced by user input and application. When reading planetary literature that makes use of these shock codes, how can one tell if the authors have implemented the codes appropriately?

3) Based on the shock code benchmarking shown in this study, which aspects of the shock code models (e.g. crater radius, crater depth etc.) are likely to be the most reliable with respect to predicting basin-scale impacts processes? Which are least?

4) Could the small differences observed in modeling lab-scale impacts between the various shock codes result in significant differences between model predictions when applied to basin scale impact events?

5) In planetary applications, is there any reason to favor one shock code over another?

Figure 2. (A.) Peak shock pressure versus distance from impact center predicted by the various shock codes benchmarked in this study. (B.) Crater radius versus time predicted by the various shock codes benchmarked in this study.

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