Details
| Original language | English |
|---|---|
| Title of host publication | Structural Health Monitoring 2019 |
| Subtitle of host publication | Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring |
| Editors | Fu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos |
| Pages | 909-917 |
| Number of pages | 9 |
| ISBN (electronic) | 9781605956015 |
| Publication status | Published - 2019 |
| Event | 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States Duration: 10 Sept 2019 → 12 Sept 2019 |
Abstract
With this work, we present the application of a damage distribution function to finite element (FE) model updating with the goal to detect, locate and quantify structural damage using a prestressed concrete tower as an example. The choice of design variables greatly influences the quality of the model updating procedure. Thereby, the parameterization connected to the design variables has to be able to model the structural damage with a high resolution. At the same time, the number of design variables should be as low as possible, since a high amount of design variables can result in an objective value space with many local minima, making numerical optimization unfeasible. A common approach consists of directly fitting the sectional stiffness of FEs to measured behavior. Thereby, the number of design variables increases linearly to the element count of the model. In order to reduce the number of design variables, they are commonly assigned to groups of FEs supposedly having similar mechanical properties. An additional method to even further reduce the amount of design variables is the determination of susceptible regions based on experience, prior knowledge or inspection findings. However, the position of damage is unknown in many applications. To alleviate this problem, we introduce a damage distribution function, which is described by few parameters. As these parameters represent the design variables of the optimization process, the proposed model updating procedure is independent of the FE mesh resolution as well as prior assumptions about the defect location. We demonstrate the application of the damage distribution function using a prestressed concrete tower as an example. First, we apply a three-parameter damage distribution function in order to detect, locate and quantify an artificially induced damage in a simple beam model of the considered tower. In this application, the defect location is determined along the height. Second, we extend the damage distribution function to a three-dimensional shell model of the concrete tower. This time, the location of the fictitious damage is also determined along the perimeter. The proposed parameterization keeps the amount of design variables low and enables a high numerical performance as well as stability, while maintaining the ability to detect, locate and quantify damage.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Health Professions(all)
- Health Information Management
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Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring. ed. / Fu-Kuo Chang; Alfredo Guemes; Fotis Kopsaftopoulos. 2019. p. 909-917.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Damage localization via model updating using a damage distribution function
AU - Bruns, Marlene
AU - Hofmeister, Benedikt
AU - Hübler, Clemens
AU - Rolfes, Raimund
PY - 2019
Y1 - 2019
N2 - With this work, we present the application of a damage distribution function to finite element (FE) model updating with the goal to detect, locate and quantify structural damage using a prestressed concrete tower as an example. The choice of design variables greatly influences the quality of the model updating procedure. Thereby, the parameterization connected to the design variables has to be able to model the structural damage with a high resolution. At the same time, the number of design variables should be as low as possible, since a high amount of design variables can result in an objective value space with many local minima, making numerical optimization unfeasible. A common approach consists of directly fitting the sectional stiffness of FEs to measured behavior. Thereby, the number of design variables increases linearly to the element count of the model. In order to reduce the number of design variables, they are commonly assigned to groups of FEs supposedly having similar mechanical properties. An additional method to even further reduce the amount of design variables is the determination of susceptible regions based on experience, prior knowledge or inspection findings. However, the position of damage is unknown in many applications. To alleviate this problem, we introduce a damage distribution function, which is described by few parameters. As these parameters represent the design variables of the optimization process, the proposed model updating procedure is independent of the FE mesh resolution as well as prior assumptions about the defect location. We demonstrate the application of the damage distribution function using a prestressed concrete tower as an example. First, we apply a three-parameter damage distribution function in order to detect, locate and quantify an artificially induced damage in a simple beam model of the considered tower. In this application, the defect location is determined along the height. Second, we extend the damage distribution function to a three-dimensional shell model of the concrete tower. This time, the location of the fictitious damage is also determined along the perimeter. The proposed parameterization keeps the amount of design variables low and enables a high numerical performance as well as stability, while maintaining the ability to detect, locate and quantify damage.
AB - With this work, we present the application of a damage distribution function to finite element (FE) model updating with the goal to detect, locate and quantify structural damage using a prestressed concrete tower as an example. The choice of design variables greatly influences the quality of the model updating procedure. Thereby, the parameterization connected to the design variables has to be able to model the structural damage with a high resolution. At the same time, the number of design variables should be as low as possible, since a high amount of design variables can result in an objective value space with many local minima, making numerical optimization unfeasible. A common approach consists of directly fitting the sectional stiffness of FEs to measured behavior. Thereby, the number of design variables increases linearly to the element count of the model. In order to reduce the number of design variables, they are commonly assigned to groups of FEs supposedly having similar mechanical properties. An additional method to even further reduce the amount of design variables is the determination of susceptible regions based on experience, prior knowledge or inspection findings. However, the position of damage is unknown in many applications. To alleviate this problem, we introduce a damage distribution function, which is described by few parameters. As these parameters represent the design variables of the optimization process, the proposed model updating procedure is independent of the FE mesh resolution as well as prior assumptions about the defect location. We demonstrate the application of the damage distribution function using a prestressed concrete tower as an example. First, we apply a three-parameter damage distribution function in order to detect, locate and quantify an artificially induced damage in a simple beam model of the considered tower. In this application, the defect location is determined along the height. Second, we extend the damage distribution function to a three-dimensional shell model of the concrete tower. This time, the location of the fictitious damage is also determined along the perimeter. The proposed parameterization keeps the amount of design variables low and enables a high numerical performance as well as stability, while maintaining the ability to detect, locate and quantify damage.
UR - http://www.scopus.com/inward/record.url?scp=85074392811&partnerID=8YFLogxK
U2 - 10.12783/shm2019/32202
DO - 10.12783/shm2019/32202
M3 - Conference contribution
AN - SCOPUS:85074392811
SP - 909
EP - 917
BT - Structural Health Monitoring 2019
A2 - Chang, Fu-Kuo
A2 - Guemes, Alfredo
A2 - Kopsaftopoulos, Fotis
T2 - 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
Y2 - 10 September 2019 through 12 September 2019
ER -