Comment on "Stiffness Matrix Adjustment Using Mode Data"

Fuh, Jon-Shen; Berman, Alex

doi:10.2514/3.48699

Cited by 6 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The element [Δ ] in (10) can be defined as (14) using the interaction formulas of (12) and (13) [27]:…”

Section: Direct Matrix Updating Methods (Dmum)mentioning

confidence: 99%

An Experimental Study of Structural Identification of Bridges Using the Kinetic Energy Optimization Technique and the Direct Matrix Updating Method

Heo¹,

Jeon

2016

Shock and Vibration

View full text Add to dashboard Cite

This paper aims to develop an SI (structural identification) technique using the KEOT and the DMUM to decide on optimal location of sensors and to update FE model, respectively, which ultimately contributes to a composition of more effective SHM. Owing to the characteristic structural flexing behavior of cable bridges (e.g., cable-stayed bridges and suspension bridges), which makes them vulnerable to any vibration, systematic and continuous structural health monitoring (SHM) is pivotal for them. Since it is necessary to select optimal measurement locations with the fewest possible measurements and also to accurately assess the structural state of a bridge for the development of an effective SHM, an SI technique is as much important to accurately determine the modal parameters of the current structure based on the data optimally obtained. In this study, the kinetic energy optimization technique (KEOT) was utilized to determine the optimal measurement locations, while the direct matrix updating method (DMUM) was utilized for FE model updating. As a result of experiment, the required number of measurement locations derived from KEOT based on the target mode was reduced by approximately 80% compared to the initial number of measurement locations. Moreover, compared to the eigenvalue of the modal experiment, an improved FE model with a margin of error of less than 1% was derived from DMUM. Thus, the SI technique for cable-stayed bridges proposed in this study, which utilizes both KEOT and DMUM, is proven effective in minimizing the number of sensors while accurately determining the structural dynamic characteristics.

show abstract

“…The element [Δ ] in (10) can be defined as (14) using the interaction formulas of (12) and (13) [27]:…”

Section: Direct Matrix Updating Methods (Dmum)mentioning

confidence: 99%

An Experimental Study of Structural Identification of Bridges Using the Kinetic Energy Optimization Technique and the Direct Matrix Updating Method

Heo¹,

Jeon

2016

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…As mentioned in Sec. IV.B, J T = [3,18,19). Further, J M = [3J, J c = JT, Jc, = Jc^ = Jc, g = JT-Now, we can draw the following conclusions.…”

Section: Correlation In Torsionmentioning

confidence: 98%

“…Modes 3, 18, 19 are torsional modes with respect to the z axis. In fact, admixture coefficients reveal that JB = {1, 2, 8, 9, 12, 13, 15, 16) and7 r = [3,18,19), J M =(l} 9 J C =J B , •/c, =«/*•••, Jc, 2 = JB, Jc 3 = JT, • • -* ^c 19 = JT-Now, we can draw the following conclusions: 1) Changes in correlation measures by a factor 1.5 are handled accurately by RESTRUCT.…”

Section: B Offshore Tower Modelmentioning

confidence: 99%

See 1 more Smart Citation

Structural model correlation using large admissible perturbations incognate space

Bernitsas

Tawekal

1991

AIAA Journal

View full text Add to dashboard Cite

A nonlinear perturbation method is developed to solve the problem of correlating a finite element model (FEM) to a structure for which an incomplete set of natural frequencies and mode shapes and/or some static deflections have been measured. The solution algorithm can handle differences between FEM and structure, in design variables and response, as large as 100-300%, depending on the scale of the structure and correlation measures. This is achieved incrementally by making inadmissible predictions, identifying the modal cognate space relevant to the correlation measures, and making admissible corrections in the cognate space. The developed computer code postprocesses results of the FEM modal and/or static analyses of the initial model only. No additional finite element analysis is required. Lagrange multipliers reveal the dominant correlation requirements and the active admissible cognate subspace. Depending on the number of correlation variables and measures, an optimal, a unique, or an inadmissible minimal error solution may be produced. Beam and offshore tower examples are used to test the algorithm and investigate conflicting requirements, definition of admissible cognate space, limits of allowable differences between FEM and structure, accuracy, and cost of the nonlinear perturbation method.

show abstract

“…        (9)         (10) 이때, 식 (9)에서의  는 식 (11) 및 식 (12)의 관계식을 이용하여 식 (13)과 같이 정의된다 (24) . (22) .…”

Section: 또한 대상 구조물의 응답(계측값)을 기준으로 해 당시점의 구조적 상태를 대변하는 Fe 모델을 구성 하고 unclassified

Structural Identification for Structural Health Monitoring of Long-span Bridge - Focusing on Optimal Sensing and FE Model Updating -

Heo¹,

Jeon²

2015

Transactions of the Korean Society for Noise and Vibration Engi

View full text Add to dashboard Cite

This paper aims to develop a SI(structural identification) technique using the kinetic energy optimization technique(KEOT) and the direct matrix updating method(DMUM) to decide on optimal location of sensors and to update FE model respectively, which ultimately contributes to a composition of more effective SHM. Owing to the characteristic structural flexing behavior of cable bridges, which makes them vulnerable to any vibration, systematic and continuous structural health monitoring (SHM) is pivotal for them. Since it is necessary to select optimal measurement locations with the fewest possible measurements and also to accurately assess the structural state of a bridge for the development of an effective SHM, a SI technique is as much important to accurately determine the modal parameters of the current structure based on the data optimally obtained. In this study, the KEOT was utilized to determine the optimal measurement locations, while the DMUM was utilized for FE model updating. As a result of experiment, the required number of measurement locations derived from KEOT based on the target mode was reduced by approximately 80 % compared to the initial number of measurement locations. Moreover, compared to the eigenvalue of the modal experiment, an improved FE model with a margin of error of less than 1 % was derived from DMUM.Finally, the SI technique for long-span bridges proposed in this study, which utilizes both KEOT and DMUM, is proven effective in minimizing the number of sensors while accurately determining the structural dynamic characteristics.

show abstract

Comment on "Stiffness Matrix Adjustment Using Mode Data"

Cited by 6 publications

References 10 publications

An Experimental Study of Structural Identification of Bridges Using the Kinetic Energy Optimization Technique and the Direct Matrix Updating Method

An Experimental Study of Structural Identification of Bridges Using the Kinetic Energy Optimization Technique and the Direct Matrix Updating Method

Structural model correlation using large admissible perturbations incognate space

Structural Identification for Structural Health Monitoring of Long-span Bridge - Focusing on Optimal Sensing and FE Model Updating -

Contact Info

Product

Resources

About