Award Abstract # 1634483
A New Interval Finite Element Approach for Structural System Identification and Damage Detection under Uncertainty

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: GEORGIA TECH RESEARCH CORP
Initial Amendment Date: July 31, 2016
Latest Amendment Date: July 31, 2016
Award Number: 1634483
Award Instrument: Standard Grant
Program Manager: Caglar Oskay
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: August 1, 2016
End Date: July 31, 2020 (Estimated)
Total Intended Award Amount: $455,747.00
Total Awarded Amount to Date: $455,747.00
Funds Obligated to Date: FY 2016 = $455,747.00
History of Investigator:
  • Rafi Muhanna (Principal Investigator)
    rafi.muhanna@gatech.edu
  • Francesco Fedele (Co-Principal Investigator)
  • Yang Wang (Co-Principal Investigator)
Recipient Sponsored Research Office: Georgia Tech Research Corporation
926 DALNEY ST NW
ATLANTA
GA  US  30318-6395
(404)894-4819
Sponsor Congressional District: 05
Primary Place of Performance: Georgia Institute of Technology
225 North avenue
Atlanta
GA  US  30332-0420
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): EMW9FC8J3HN4
Parent UEI: EMW9FC8J3HN4
NSF Program(s): Structural and Architectural E
Primary Program Source: 01001617DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 036E, 039E, 040E
Program Element Code(s): 163700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Identifying material properties of existing structural systems is crucial for monitoring their performance and ensuring their safety. Knowledge about these properties allows the determination of the magnitudes and the locations of any deterioration occurring in the system. Such knowledge will allow the proper required actions to avoid any failures. The identification procedures require a significant amount of measured data that typically are associated with uncertainty. Accounting for uncertainty due to different factors is one of the most challenging tasks in structural system identification and damage detection. In this project, uncertainty in measurements due to device tolerances and field conditions will be treated in terms of possible values expressed as intervals, without any prior assumptions on their nature. The rigorous consideration of uncertainty in system identification will lead to a more reliable and dependable predictions of their behavior. Such reliable and dependable predictions are crucial for the safety of civil infrastructure systems, and will contribute to the reduction of life endangering failures and disasters. The research team will offer research opportunities to high school students through summer camps.

While interval-based methods and system identification are both very powerful and well-developed techniques within their respective fields, thus far they have scarcely been used together in the context of inverse problems under uncertainty. By investigating the best ways of analytically, numerically and computationally handling these two methodologies in conjunction with each other, we shall develop a powerful class of techniques not only for the problem at hand, but for a vast number of other inverse problems with partial differential equation (PDE) constraints. In this research an emphasis will be placed on the use of Interval Finite Element Methods (IFEM) in the context of optimization to solve for inverse problems that arise in structural system identification and damage detection under uncertainty without prior assumptions on its nature. This is therefore expected to be the first step of a long lasting research program which will be both broad in its scope of applications across many fields and at the same time remain coherently focused in its underlying computational and mathematical methodologies.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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3. Xiao, Naijia and Fedele, Francesco and Muhanna, Rafi "Interval-Based Parameter Identification for Structural Static Problems" Reliable computing , v.23 , 2016 Citation Details
DONG, Xinjun and WANG, Yang "A Comparative Study of Frequency-domain Finite Element Updating Approaches Using Different Optimization Procedures" EWSHM , 2016 Citation Details
Liu, Xi and Dong, Xinjun and wang, Yang and Muhanna, Rafi and Fedele, Francesco "Experimental Model Updating of a Full-Scale Concrete Frame Structure" 14th International Workshop on Advanced Smart Materials and Smart Structures Technology , 2019 10.13133/9788893771146 Citation Details
Muhanna, Rafi and Shahi, Shahrokh "Uncertainty in Boundary Conditions---An Interval Finite Element Approach" Decision Making under Constraints , 2020 10.1007/978-3-030-40814-5_20 Citation Details
Xiao, Naijia and Fedele, Francesco and Muhanna, Rafi ", Structural Dynamic Problems in Time Domain under Uncertainty - An Interval Finite Element Approach" International journal of reliability and safety , v.12 , 2018 https://doi.org/10.1504/IJRS.2018.092516 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Identifying material properties of existing structural systems is crucial for monitoring their performance and ensuring their safety. The knowledge about these properties allows the determination of the magnitudes and the locations of any occurring deterioration in the system. Such knowledge will allow the proper required actions to avoid any failures. The identification procedures require a significant amount of measured data that typically are associated with uncertainty. Accounting for uncertainty due to different factors is one of the most challenging tasks in structural system identification and damage detection. In this project, uncertainty in measurements due to device tolerances and field conditions has been treated in terms of possible values expressed as intervals, without any prior assumptions on their nature.  The rigorous consideration of uncertainty in system identification will lead to a more reliable and dependable predictions of their behavior. Such reliable and dependable predictions are crucial for the safety of civil infrastructure systems, and will contribute to the reduction of life endangering failures and disasters.

During the period of the project the conducted research has investigated, validated, and optimized an innovative class of interval-based computational algorithms for structural parameter identification and damage evaluation under uncertainty. We have combined mathematical and computational methodologies that have matured largely in isolation from each other within different engineering disciplines. Interval Finite Element Methods (IFEM) have been employed in the context of new interval optimization to solve for inverse problems that arise in structural system identification and damage detection under uncertainty.

We have developed fundamental theoretical solutions for the problem under consideration in addition to a new set of computational "interval-tools" that allowed us to pass directly from uncertain raw measurements to sharp and guaranteed bounds estimates of the unknown parameters leading to the prediction of local stiffness and enabling damage identification. Uncertainties in measurement due to device tolerances and field conditions have been treated in terms of possible values expressed as intervals, without any prior assumptions on their nature.

 


Last Modified: 11/30/2020
Modified by: Rafi L Muhanna

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