MECH&AE Seminar
MECHANICAL
AND AEROSPACE ENGINEERING DEPARTMENTAL SEMINARS
STRUCTURAL
& SOLID MECHANICS SEMINAR SERIES
“A
Comparison of Three Different Methods for the
Identification of Hysterically Degrading Systems Using
BWBN Model”
Mohammad
Noori
Professor
California Polytechnic
State University, San Luis Obispo
Monday, June
5, 2017
38-138
Engineering IV
Time: 10:30
– 11:30AM
Abstract:
Structural
control and health monitoring schemes play key roles not
only in enhancing the safety and the reliability of
infrastructure systems, but also to optimally minimize the
life cycle cost and maximize the performance through the
full life cycle design under natural disasters. In this
paper, an effective strategy is proposed to identify general
hysteretic behavior of a typical shear structure subjected
to external excitations. First, the characteristics of the
early version of Bouc-Wen-Baber-Noori (BWBN) model and its
parametric physical implications are presented using a
single degree of system. BWBN model was developed in the
1980’s and given its versatility and mathematical
tractability, as well as its capability in reproducing a
large number of nonlinear hysteretic behaviors, over the
past decade it has received significant attention of the
research community in nonlinear mechanics and hysteretically
degrading systems. Subsequently, a time varying shear
structure system with BWBN restoring force characteristics
is presented for different case studies. By incorporating a
“Grey Box” strategy, an Intelligent Parameter Varying (IPV),
an Artificial Neural Network (ANN) technique developed by
the authors, is introduced to identify the hysteretic
behavior of the generalized hysteresis structure using
system identification modeling approach. Genetic algorithm
(GA) and Transitional Markov Chain Monte Carlo (TMCMC) based
Bayesian Updating framework are also developed to identify
this hysteretic structural system. Correlation analysis and
algorithm efficiency are further studied to compare and
evaluate the system identification results. It is demonstrated that
IPV method is a viable and effective tool for the system
identification of highly nonlinear systems and offers
promising opportunities for SHM applications.
Bio:
Mohammad Noori holds
a BS from the University of Illinois (1977), a MS from
Oklahoma State University (1980), and a Ph.D. from the
University of Virginia (1984), all of which are in Civil
Engineering with a concentration in Engineering Mechanics. Noori has supervised
over 85keynotee postdoctoral and graduate research projects,
has given over 120 keynote and invited lectures, and along
with his co-authors, has published over 250 journal and
conference proceeding papers.
He is the founding executive editor of the
International Journal of Sustainable Materials and
Structural Systems, and he has served in various other
editorial roles for a number of scientific journals. Noori
has been a member of several NSF delegation teams for
US-Japan and US-China Cooperative Research programs and was
the founding chair of the ASME Uncertainty and
Probabilistics Committee. In 2014, Noori served as the
Director of the Sensors Program in the CMMI Division at NSF.
Noori worked at WPI from 1984 to 1999 where he served as the
J.W. Higgins Professor and the Head of the Mechanical
Engineering department. From
1999 to 2005, Noori worked at NC State University as a
Reynolds Professor and the Head of the Mechanical and
Aerospace Engineering department. Noori has received over
$13 million in support of his research from NSF, ONR, NASA,
National Sea Grant and industry (excluding the NIA funding).
He also served as the NC State PI and one of 7 colleagues
from 6 major universities who prepared a winning proposal to
NASA that resulted in the establishment of the National
Institute of Aerospace, a unique multi-university research
center, in partnership with Langley Research Center; through
a 15-year, $390M
contract with NASA. In 2005 he joined Cal Poly as the Dean
of Engineering where he served until 2010, after which he
returned to his passion for teaching and research. Noori’s research in
modeling complex and nonlinear hysteretic behavior of
structural systems (Bouc-Wen-Baber-Noori Model) has been
widely cited and over the past two decades BWBN model has
been utilized in a wide range of engineering applications,
for constitutive modeling, analysis and response prediction
of hysteretic systems and devices. Since 1990 Noori and
his collaborators have carried out work in structural health
monitoring (SHM). This
work has included development of a number of artificial
intelligence methods, for damage detection in linear and
nonlinear systems, as well feature extraction. Their most recent work
is on uncertainty quantification issues in SHM. Noori is a co-author of
a two volume upcoming book on the Application of Fiber Optic
Sensors in Structural Health Monitoring and also serves as a
special advisor to the President of the International
Society for Structural Health Monitoring of Intelligent
Infrastructure (ISHMII). Noori
has received numerous awards for his teaching, research, and
professional service. The most recent one include the ASEE
Keating Award for Innovation and Leadership in Lifelong
Learning in Graduate Engineering Education. He is an ASME Fellow,
has received a JSPS Fellowship and is a member of Sigma Xi,
Pi Tau Sigma, Chi-Epsilon, and Sigma Mu Epsilon honorary
societies. Currently,
Noori is a professor of mechanical engineering at Cal Poly
in San Luis Obispo, CA, has held a visiting scholar position
at DPRI, Japan, and currently holds a distinguished visiting
chaired professorship at a major research institution in
China.
All faculty, researchers, students, and guests
are welcome to this event. (Refreshments will be served.)