Agenda (pdf)


Contact:
 

  Prof. D. J. Inman
CIMSS, Virginia Tech
310 Durham Hall, MC 0261
Blacksburg, VA 24061
U.S.A.
Fax: +1 (540)231-2903
Tel: +1 (540)231-4709
Email: dinman@vt.edu

Sponsored by a grant from the US National Science Foundation in cooperation with the Engineering Sciences and Applications Division of Los Alamos National Laboratory.


 
 
 



Slides of Lectures

 
 

An introduction to damage prognosis (1.9 MB)
C. R. Farrar, LANL, USA

Modeling
Modeling damage evolution in materials: concepts, approaches and issues
(1.3 MB)
T. O. Williams and I. J. Beyerlein, LANL, USA

Boundary element fracture mechanics (2.4 MB)
P. Sollero, UNICAMP, Brazil

Overview of uncertainty quantification, model verification and validation (14.8 MB)
F. Hemez, LANL, USA

On friction induced non-linear and non-ideal vibrations: a source of fatigue (0.7 MB)
J. M. Balthazar, UNESP-RC, Brazil

Effect of damping in model updating (9.7 MB)
J. A. Pereira and R. M. Doi, UNESP-IS, Brazil

In situ observation of damage evolution and fracture toughness measurement using scanning electron microscopy (5.3 MB)
J. E. P. Ipiņa - UNC, A. A. Yawny - CAB, Argentina

Structural Health Monitoring
Model-based inverse problems in structural dynamics (0.9 MB)
D. A. Rade, UFU, Brazil

Structural health monitoring algorithms for smart structures (6.9 MB)
V. Lopes Jr., S. D. Silva, A. Tebaldi and R. M. Furtado, UNESP-IS, Brazil

Model-based inverse problems in structural dynamics (3.6 MB)
V. Steffen, UFU, Brazil

Improvement of damage assessment results using high-spatial density measurements (1.8 MB)
R. Pascual, Univ. Chile, Chile

Reliability analysis (0.9 MB)
A. N. Robertson, LANL, USA

Structural energy flow techniques (1.3 MB)
J. R. Arruda, UNICAMP, Brazil

Lamb-wave based structural health monitoring (2.3 MB)
C. E. S. Cesnik, Univ. Michigan, USA

Statistical pattern recognition paradigm for structural health monitoring (3.5 MB)
H. Sohn, LANL, USA

Smart materials for impedance based monitoring (10.3 MB)
D. J. Inman, VT, USA

Hardware Issues
Design of built-in structural health monitoring system (25.6 MB)
F.-K. Chang, Stanford Univ., USA

Optical-based sensing (19.6 MB)
M. Todd, UCSD, USA

Power harvesting for sensing (6.2 MB)
D. J. Inman, VT, USA

Applications
Composite wing applications (7.1 MB)
J. Kasmaka, UCSD, USA

Rotating machinery prognostics (5.3 MB)
M. Roemer, Impact Tech, USA

Application of simplified statistical models on hydro generating units health monitoring (6.6 MB)
G. Brito, ITAIPU, Brazil

Applications and challenges in structural diagnostics and prognostics (4.6 MB)
D. E. Adams, Purdue Univ., USA

Structural health monitoring applications to theme park rides (1.6 MB)
H. Sohn, A. N. Robertson and C. R. Farrar, LANL, USA

US Navy machinery diagnostics and prognostics (2.1 MB)
B. Marchall, NSWC, USA
 

Slides of Student Presentations

Introduction

Damage prognosis in commercial aircraft riveted lap joints (0.5 MB)
M. Robinson, S. Silva, I. Porto and A. Raghavan

Roller coaster damage detection and prognosis for safer operation (1.9 MB)
E. Castodeza, L. Martin, V. Meruane, T. Tippetts and J. Tarpani

Structural Health monitoring and damage prognosis in aircraft cargo doors (5.9 MB)
N. Flesher, C. Garibotti, B. Grisso, S. Heofel and J. Moura

Health monitoring and damage prognosis of unmanned air vehicles (1.0 MB)
R. Amaro, S. McCord, D. Santana, S. Souza and D. Peairs

Diagnosis and prognosis of a welded joint in a mining truck suspension (0.2 MB)
M. Abrantes, H. Kess, R. Marques, E. Menin and A. Tebaldi