DebrisTracer：超高速撞击快速成像中的可靠跟踪
DebrisTracer: Reliable Tracking in Hypervelocity Impact Fast Imaging
- CEA（法国原子能委员会）
- ENSTA（国立高等先进技术学校）
- CNRS（法国国家科学研究中心）
- Sorbonne University（索邦大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究超高速撞击快速成像中碎片跟踪问题，基于临界点提取和匹配扩展拓扑跟踪框架，纳入领域知识和物理假设，实现准确可靠跟踪，在物理验证上比现有工具精度更高，统计摘要可直观识别碎片状态。
AI中文摘要：
本文介绍了DebrisTracer，一个用于超高速撞击快速成像中碎片可靠跟踪的框架。这类有噪声且高度特定的数据集捕捉了超高速发射的射弹撞击目标材料后大量碎片的喷射情况。在航空航天应用中，可靠估计碎片质量和速度分布至关重要。文中记录了如何扩展基于临界点提取和匹配的现成拓扑跟踪框架，以纳入领域知识和物理假设。该方法能自动实现准确可靠的碎片跟踪，对这一复杂时空现象进行可解释的视觉分析。大量实验表明，该方法在物理验证方面比领域专家使用的现有工具在预测实验喷射质量和弹坑深度剖面方面有精度提升。还通过多个用例展示了该方法的实用性，其统计摘要能直观识别碎片群体中的不同状态，证实并完善了领域专家的先前预期。
英文摘要：
This application paper presents DebrisTracer, a framework for the reliable tracking of debris in hypervelocity impact fast imaging. These noisy and highly specific datasets capture the ejection of a large number of debris fragments after the impact of a projectile launched at hypervelocity into a target material. The reliable estimation of debris mass and speed distributions is of major importance in aerospace applications. We document how to extend an off-the-shelf topology tracking framework based on critical point extraction and matching, in order to incorporate domain knowledge and physical assumptions. Our approach automatically produces an accurate and reliable debris tracking, enabling an interpretable visual analysis of this complex space-time phenomenon. Extensive experiments demonstrate the accuracy improvements provided by our approach over established tools used by domain experts in terms of physical validation, specifically via the prediction of the experimental ejected mass and crater depth profiles. We illustrate the utility of our approach across several use cases (with varying impact angles and physics). We show that our statistical summaries enable the visual identification of distinct regimes within the debris population, corroborating and refining prior expectations of domain experts. Our database and our C++ implementation are available at this address: https://github.com/tloloum/DebrisTracer.
