In order to achieve a more accurate finite element (FE) model for an as-built structure, experimental data collected from the actual structure can be used to update selected parameters of the FE model. The process is known as FE model updating. This research compares the performance of two frequency-domain model updating approaches. The first approach minimizes the difference between experimental and simulated modal properties, such as natural frequencies and mode shapes. The second approach minimizes modal dynamic residuals from the generalized eigenvalue equation involving stiffness and mass matrices. Both
model updating approaches are formulated as an optimization problem with selected updating parameters as optimization variables. This research also compares the performance of different optimization procedures, including a nonlinear least-square, an interior-point and an iterative linearization procedure. The comparison is conducted using a numerical example of a space frame structure. The modal dynamic residual approach shows better performance than
the modal property difference approach in updating model parameters of the space frame structure.
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Experimental Model Updating of a Full-Scale Concrete Frame Structure
In structural analysis, it is common practice to construct a finite element (FE) model of
an as-built structure using nominal material properties and idealized boundary
conditions. However, behaviors of the FE model generally differ from the as-built
structure in the field. To minimize the differences, selected parameters of the FE model
can be updated using experimental measurements from the as-built structure. This
paper investigates the FE model updating of a full-scale concrete frame structure with
over a thousand degrees-of-freedom. Given experimental measurements obtained
during a shaker test, frequency-domain modal properties of the concrete structure are
identified. A non-convex optimization problem is then formulated to update parameter
values of the FE model by minimizing the difference between the experimentally
identified modal properties and those generated from the FE model. The selected
optimization variables include concrete elastic moduli of the columns, beams and slabs.
Upon model updating, the modal properties of the FE model can match better with the
experimentally identified modal properties.
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- Award ID(s):
- 1634483
- NSF-PAR ID:
- 10181390
- Date Published:
- Journal Name:
- 14th International Workshop on Advanced Smart Materials and Smart Structures Technology
- Page Range / eLocation ID:
- 41-47
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This paper describes a MATLAB package for structural model updating, named SMU. The SMU package updates parameter values of a finite element model by solving optimization problems utilizing modal properties obtained from sensor measurements. In particular, the package offers three model updating formulations, namely, (1) the modal assurance criterion value approach, (2) the eigenvector difference approach, and (3) the modal dynamic residual formulation. The first two belong to the family of modal property difference formulations. For each formulation, the analytical Jacobian derivative of the objective function is derived and implemented in SMU. Since the formulated optimization problems are generally nonconvex, the global optimality of the solution cannot be guaranteed using off-the-shelf optimization algorithms. In order to increase the chance of finding a better local minimum, the SMU package can perform gradient search from randomly generated starting points. Several examples for the model updating of as-built structures are included in the GitHub package. This paper demonstrates the SMU functionality through model updating of an 18-DOF model and a concrete building frame model.
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Numerical modeling of actual structural systems is a very complex task mainly due to the lack of complete knowledge on the involved parameters. Simplified assumptions on the uncertain geometry, material properties and boundary conditions make the numerical model response differ from the actual structural response. Improvements of the finite element (FE) models to obtain accurate response predictions can be achieved by vibration based FE model updating which uses experimental measures to minimize the differences between the numerical and experimental modal features (i.e. natural frequencies and mode shapes). Within this context, probabilistic model updating procedures based on the Bayes’ theorem were recently proposed in the literature in order to take into account the uncertainties affecting the structural parameters and their influence on the structural response. In this paper, a novel framework to efficiently estimate the posterior marginal PDF of the selected model parameters is proposed. First, the main dynamic parameters to be used for model updating are identified by ambient vibration tests on an actual structural system. Second, a first numerical FE model is developed to perform initial sensitivity analysis. Third, a surrogate model based on polynomial chaos is calibrated on the initial FE model to significantly reduce computational costs. Finally, the posterior marginal PDFs of the chosen model parameters are estimated. The effectiveness of the proposed method is demonstrated using a FE numerical model describing a curved cable-stayed footbridge located in Terni (Umbria Region, Central Italy).more » « less
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Numerical modeling of actual structural systems is a very complex task mainly due to the lack of complete knowledge on the involved parameters. Simplified assumptions on the uncertain geometry, material properties and boundary conditions make the numerical model response differ from the actual structural response. Improvements of the finite element (FE) models to obtain accurate response predictions can be achieved by vibration based FE model updating which uses experimental measures to minimize the differences between the numerical and experimental modal features (i.e. natural frequencies and mode shapes). Within this context, probabilistic model updating procedures based on the Bayes’ theorem were recently proposed in the literature in order to take into account the uncertainties affecting the structural parameters and their influence on the structural response. In this paper, a novel framework to efficiently estimate the posterior marginal PDF of the selected model parameters is proposed. First, the main dynamic parameters to be used for model updating are identified by ambient vibration tests on an actual structural system. Second, a first numerical FE model is developed to perform initial sensitivity analysis. Third, a surrogate model based on polynomial chaos is calibrated on the initial FE model to significantly reduce computational costs. Finally, the posterior marginal PDFs of the chosen model parameters are estimated. The effectiveness of the proposed method is demonstrated using a FE numerical model describing a curved cable-stayed footbridge located in Terni (Umbria Region, Central Italy).more » « less
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Abstract Real-time model updating of active structures subject to unmodeled high-rate dynamic events require structural model updates on the timescale of 2 ms or less. Examples of active structures subjected to unmodeled high-rate dynamic events include hypersonic vehicles, active blast mitigation, and orbital infrastructure. Due to the unmodeled nature of the events of interest, the real-time model updating algorithm should circumvent any model pre-calculations. In this work, we present a methodology that updates the finite element analysis (FEA) model of a structure experiencing varying dynamics through online measurements. The algorithm is demonstrated for a testbed, comprised of a cantilever beam and a roller that serves as movable support. The structure’s state is updated (i.e. the position of the moving roller) by continuously updating the associated FEA model through an online adaptive meshing and search algorithm. The structure’s state is continuously estimated by comparing the measured signals with FEA models. New FEA models are built based on the enhanced estimate of the structure’s state through adaptive meshing for modal analysis and adaptive search space for the FEA model selection. The proposed methodology is verified experimentally in real-time using the testbed. It is demonstrated that the adaptive features can achieve accurate state estimations within the required 2 ms timescale.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.13133/9788893771146
