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A Coupled Approach to Developing Damage Prognosis Solutions

机译：发育损伤预后解决方案的耦合方法

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摘要

An approach to developing damage prognosis (DP) solution that is being developed at Los Alamos National Laboratory (LANL) is summarized in this paper. This approach integrates advanced sensing technology, data interrogation procedures for state awareness, novel model validation and uncertainty quantification techniques, and reliability-based decision-making algorithms in an effort to transition the concept of damage prognosis to actual practice. In parallel with this development, experimental efforts are underway to deliver a proof-of-principle technology demonstration. This demonstration will assess impact damage and predict the subsequent fatigue damage accumulation in a composite plate. Although the project focus will be DP for composite materials, most of this technology can generalize to many other applications. The unique aspects of this approach discussed herein include: 1) multi-length scale damage models analyzed on tera-scale computer platforms that discretize composites on an individual lamina level, 2) integration of advanced sensors with Los Alamos's flight-hardened data acquisition system, 3) damage detection based on a statistical pattern recognition approach, and 4) reliability-based metamodels with quantified uncertainty that can be deployed on microprocessors integrated with the sensing system for autonomous damage prognosis.
机译：本文总结了在LOS Alamos国家实验室（LANL）开发的损害预后（DP）解决方案的方法。这种方法集成了先进的传感技术，数据询问程序，以实现国家意识，新颖的模型验证和不确定量化技术，以及基于可靠性的决策算法，以便将损伤预后的概念转变为实际实践。与此开发平行，正在进行实验努力来提供原则上的证据技术示范。该示范将评估抗冲击损伤并预测随后的复合板中的疲劳损伤积累。虽然项目焦点将是复合材料的DP，但大多数技术都可以推广到许多其他应用程序。本文讨论的这种方法的独特方面包括：1）在Tera级计算机平台上分析的多长度尺度损伤模型，使得单独的Lamina等级上的复合材料，2）与LOS Alamos的飞行 - 硬化数据采集系统集成了高级传感器的集成， 3）基于统计模式识别方法的损伤检测，以及4）基于可靠性的元典，具有量化的不确定性，可以部署在与自主损伤预后的传感系统集成的微处理器上。

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