详情

Damage Prognosis Models for Space Vehicles and Structures

项目名称：	Damage Prognosis Models for Space Vehicles and Structures
摘要：	Structural health monitoring (SHM) and damage prognosis of space structures will be important components of future space vehicles and in future space operations. SHM entails the detection, through combined measurement and modeling, of material defects and damage that could compromise safety and survivability of the structure. Damage prognosis (DP) entails use of the SHM outcomes to model and predict the evolution of damage and the useful life of the structural component. The current status of these two elements of structural safety monitoring are at different stages of development: (1) theory and some methodologies of SHM for application to space vehicles are well developed, and the next major step will be development and deployment of sensing and integration hardware systems that utilize existing modeling and theory; and (2) DP is still in its infancy - it is recognized as a critical component of the overall structural health problem, but most substantive developments remain to be made. It is DP development that we will pursue in the proposed research. DP involves the development of predictive simulation methods that necessitate the modeling of a number of things: the future environment of the structure under study, the likely future loadings to which the structure will be subjected, the current location, type, and level of any damage (via SHM), macro and micro models of structural behavior, and models for growth/propagation of structural damage with time, and models that specify the useful life of structures as functions of states simulated via predictive simulation. Predictive simulation may require very large models (e.g., millions of DOF) that must be simulated on massively parallel platforms in order to produce reliable results. Such platforms are available to New Mexico researchers through the Encanto system. At the same time, real-time, onboard DP systems may need to use significantly smaller math models that can be solved with modest, onboard computing power. Thus, small models that capture the essence of the large models are also necessary.
状态：	Active
资金：	0.00
资助组织：	Federal Aviation Administration
项目负责人：	Davidian, Ken
执行机构：	New Mexico State University, Las Cruces
开始时间：	20120521
主题领域：	Aviation；Vehicles and Equipment