국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions.
저자	Spear, Ashley D.;; Priest, Amanda R.;; Veilleux, Michael G.;; Ingraffea, Anthony R.;; Hochhalter, Jacob D.
Keyword	CRACK PROPAGATION;; DAMAGE;; EDUCATION;; EXPERIMENT DESIGN;; FINITE ELEMENT METHOD;; FRACTURE MECHANICS;; FRACTURING;; NEURAL NETS;; REAL TIME OPERATION;; RESIDUAL STRENGTH;; SIMULATION;; TARGETS
URL	http://hdl.handle.net/2060/20110023793
보고서번호	NF1676L-11863
발행년도	2011
출처	NTRS (NASA Technical Report Server)
ABSTRACT	A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.