The objective of structural model updating is to reduce inherent modeling errors in Finite Element (FE) models due to simplifications, idealized connections, and uncertainties of material properties. ...Updated FE models, which have less discrepancies with real structures, give more precise predictions of dynamic behaviors for future analyses. However, model updating becomes more difficult when applied to civil structures with a large number of structural components and complicated connections. In this paper, a full-scale FE model of a major long-span bridge has been updated for improved consistency with real measured data. Two methods are applied to improve the model updating process. The first method focuses on improving the agreement of the updated mode shapes with the measured data. A nonlinear inequality constraint equation is used to an optimization procedure, providing the capability to regulate updated mode shapes to remain within reasonable agreements with those observed. An interior point algorithm deals with nonlinearity in the objective function and constraints. The second method finds very efficient updating parameters in a more systematic way. The selection of updating parameters in FE models is essential to have a successful updating result because the parameters are directly related to the modal properties of dynamic systems. An in-depth sensitivity analysis is carried out in an effort to precisely understand the effects of physical parameters in the FE model on natural frequencies. Based on the sensitivity analysis, cluster analysis is conducted to find a very efficient set of updating parameters.
•A full-scale FE model of a major long-span bridge is updated to match with identified modal properties from real measured data.•A nonlinear inequality constraint equation is used to improve the agreement between identified mode shapes and ones computed from an FE model.•The sensitivity-based clustering analysis is applied to find efficient updating parameters which lead to a better updating result.
Despite advances in instrumentation and measurement techniques, it is still necessary to update numerical models to simulate or predict some structural responses, for example. Thus, this work ...proposes a metaheuristic framework based on hybrid agents, an approach within the Artificial Intelligence (AI) topics for updating Finite Element (FE) numerical models. This framework aims to provide flexible non-deterministic strategies to guide the updating process, ranging from simple local search procedures to complex learning processes. Two case studies are presented: (i) a free–free aluminium beam tested under laboratory conditions and; (ii) a catamaran tested during a sea trial under real operating conditions. The updating process aimed to optimize the stiffness matrix while maintaining the mass matrix unchanged. The objective function seeks to minimize the differences between numerical and experimental modal parameters, namely, natural frequencies and vibration modes. Results from the digital twin framework showed that the difference in natural frequencies significantly decreased, for example, 9% to 1% for the free–free aluminium beam and 15% to 4% for the catamaran’s main deck, when comparing the experimental with the updated FE model. As for the updated FE vibration modes, the Modal Assurance Criteria (MAC) values decreased slightly in both cases but within the acceptable MAC values (above 0.9), thus showing good consistency with the experimental vibration modes. In the end, the proposed framework was able to update the FE model directly using its respective reduced model, circumventing the”black box” of commercial packages.
This study proposes a method for updating the finite element model of crooked members in grid structures based on 3D scanning data. The crooked member is modeled using the multi-beam methodology, and ...two function curves are established to simulate different types of member deformation. Two parameters, section stiffness correction factor and initial stress, are introduced to account for changes in section and stress state. An experiment is carried out on a grid structure with crooked members, and the deformation of the member is obtained using 3D laser scanning technology. The bending deformation of the member is modified in the case of mild structural damage, whereas in the case of severe structural damage, the properties of the new crooked members are modified, along with the pre-set crooked member. The resulting modifications agree well with the measured results. The load-displacement curve calculated using the finite element method matches the actual loading process. Therefore, the results of this study can be utilized in the safety evaluation of grid structures with crooked members.
•Effects of modeling errors on damage identification (ID) results are studied.•Models validity within the frequency domain is non-uniform.•A likelihood function is proposed for damage ID without ...calibrating a reference model.•Optimal subset of modes are selected though a Bayesian model class selection approach.•Bayesian model averaging technique is used to account for different weight factors.
Validity and accuracy of model based identification techniques such as linear finite element (FE) model updating are sensitive to modeling errors. Models used for the design and performance assessment of civil structures often contain large modeling errors for certain frequency ranges of response. In other words, modeling errors have unequal effects on different vibration modes of structures. Therefore, the performance of FE model updating for damage identification is sensitive to the type and the subset of data used and to the residual weight factors. This study proposes a process to mitigate the effects of modeling errors by selecting the optimal subset of modes and the optimal modal residual weights. Multiple model updating classes are defined based on different subsets of modes and different weight factors. Structural damage is then identified using Bayesian model class selection and model averaging techniques over the results of all the considered model updating classes. In addition, a new likelihood function is defined to allow damage identification without the need for calibrating a reference FE model. Performance of the proposed damage identification process and the new likelihood function is evaluated numerically at multiple levels of modeling errors and structural damage on the SAC 9-story steel moment frame. It is shown that the structural damages can be identified with negligible bias when the proposed likelihood and updating process is implemented.
The continuous development of new materials and larger and/or more complex structures drives the need for the development of more robust, accurate, and sensitive Structural Health Monitoring (SHM) ...techniques. In the present work, a novel vibration-based damage-detection method that contributes into the SHM field is presented using Metaheuristic algorithms coupled with optimal Finite Element Models that can effectively localize damage. The proposed damage-detection framework can be applied in any kind of detailed structural FE model, while requiring only the output information of the dynamic response of the structure. It can effectively localize damage in a structure by highlighting not only the affected part of the structure but also the specific damaged area inside the part. First, the optimal FE model of the healthy structure is developed using appropriate FE model updating techniques and experimental vibration measurements, simulating the undamaged condition. Next, the main goal of the proposed method is to create a damaged FE model that approximates the dynamic response of the damaged structure. To achieve this, a parametric area is inserted into the FE model, changing stiffness and mass to simulate the effect of the physical damage. This area is controlled by the metaheuristic optimization algorithm, which is embedded in the proposed damage-detection framework. On this specific implementation of the framework, the Particle Swarm Optimization (PSO) algorithm is selected which has been used for a wide variety of optimization problems in the past. On the PSO’s search space, two parameters control the stiffness and mass of the damaged area while additional location parameters control the exact position of the damaged area through the FE model. For effective damage localization, the Transmittance Functions from acceleration measurements are used which have been shown to be sensitive to structural damage while requiring output-only information. Finally, with proper selection of the objective function, the error that arises from modeling a physical damage with a linear damaged FE model can be minimized, thus creating a more accurate prediction for the damaged location. The effectiveness of the proposed SHM method is demonstrated via two illustrative examples: a simulated small-scale model of a laboratory-tested vehicle-like structure and a real experimental CFRP composite beam structure. In order to check the robustness of the proposed method, two small damage scenarios are examined for each validation model and combined with random excitations.
The NVH design of cavities in aircraft, cars and other transportation equipment are mainly based on use of vibro-acoustic FE models to analyze low frequency structural vibration and interior noise. ...In order to improve the accuracy and reliability of these vibro-acoustic models, uncertainties associated with modeling of boundary conditions, joints, damping and acoustic absorption properties of cavity surfaces in acoustic domain, must be taken into account. Finite element (FE) model updating is now recognized as an effective approach to reduce modeling inaccuracies present in an FE model. This paper presents experimental studies in updating of FE model of vibro-acoustic cavity. Two experimental studies are presented. The first experimental study is about updating of structural FE model of the cavity incorporating acoustic loading using modal data based on an inverse eigen-sensitivity approach. The second study involves updating of structural and acoustic parameters of the vibro-acoustic model using frequency response functions based on a constrained optimization based approach. Thus, FE model and experimental coupled modal data and FRF data are integrated to obtain a more accurate vibro-acoustic model. Experimental example of a 3D rectangular-box cavity with a flexible plate is presented. The studies demonstrate that the improvement of the vibro-acoustic FE models through FE model updating can be an effective approach to obtain more accurate vibro-acoustic predictions.
•Optimum Design of filament wound CFRP tubes.•Optimal lamina mechanical properties.•Numerical - experimental validation.•FE Model Updating of systems with material or structural nonlinearities.
The ...complexity of fiber patterns within the layers of a Carbon Fiber Reinforced Polymer (CFRP) composite made with the filament winding technique has an active effect on the mechanical properties of the layer and respectively of the whole structure. While the approximation of mechanical properties in classic laminated composites is a relatively well-researched subject, there is a lack of information on filament wound cylindrical composites. Due to its material variability, filament wound CFRPs require certification results through numerical - experimental validation. Thus, in this work, an optimal modeling procedure of filament wound CFRP tubes is presented. The main goal is to acquire the lamina mechanical properties that could reliably be used in further finite element analyses with implications in critical practical applications with linear and nonlinear characteristics. At first, a homogenization method is applied to obtain the nominal values of layer properties. Next, a simple tensile test, conforming to ASTM 3039 standards, was repeatedly carried out using a representative sample of CFRP specimens, measuring experimental strain data. A stochastic state-of-the-art single objective optimization algorithm coupled to a robust finite element analysis solver is employed in order to finely tune the lamina material parameters minimizing the residual between experimental measurements and numerical predictions. Lastly, three tensile-based validation tests of stepwise difficulty and varying layer orientation, thickness, internal diameter, width and loading conditions are carried out, efficiently confirming the reliability of the characterized lamina material properties. Comparison of experimentally measured and optimal model’s numerically predicted strain response time histories in both linear elastic deformations as well as in nonlinear large deformations under progressive failure response strongly supported the efficacy and effectiveness of the proposed methodology.
•Geometrically complex brick masonry vaults have been analysed to assess their structural safety.•Operational Modal Analysis technique is used to dynamically characterise masonry vaults.•Genetic ...algorithms are used for numerical models updating.•Updated FE model is used to perform a nonlinear analysis.
This paper addresses the structural safety assessment of the Chapel of the Würzburg Residence (Germany), one of the most important churches of the Central European Baroque. It was declared as World Heritage Site by UNESCO in 1981, one of its most unique and distinctive characteristics is the geometry of its complex vaults. Intersections between vaults are warped and vaults surfaces were built using only one layer of brick masonry. In this work, a nonlinear finite elements (FE) model has been developed and used to assess the structural safety of the building. In order to update the model by identifying the dynamic response of the building, experimental ambient vibration tests have been previously subsequently carried out. Operational Modal Analysis (OMA) has been used to experimentally identify both modal displacements and natural frequencies. The numerical FE model is them adjusted using genetic algorithms until its dynamic response resembles that experimentally observed, thus providing a valid model to further analyse the structural behaviour of the building. After briefly descripting the Chapel, the methodology followed to update the numerical model and the obtained results from a non-linear analysis on this over-complex vaulted structure are the main goals of the paper.
This paper investigates the effects of different factors on the performance of nonlinear model updating for a seven-story shear wall building model. The accuracy of calibrated models using different ...data features and modeling assumptions is studied by comparing the time and frequency responses of the models with the exact simulated ones. Simplified nonlinear finite element models of the shear wall building are calibrated so that the misfit between the considered response data features of the models and the structure is minimized. A refined FE model of the test structure, which was calibrated manually to match the shake table test data, is used instead of the real structure for this performance evaluation study. The simplified parsimonious FE models are composed of simple nonlinear beam-column fiber elements with nonlinearity infused in them by assigning generated hysteretic nonlinear material behaviors to uniaxial stress–strain relationship of the fibers. Four different types of data features and their combinations are used for model calibration: (1) time-varying instantaneous modal parameters, (2) displacement time histories, (3) acceleration time histories, and (4) dissipated hysteretic energy. It has been observed that the calibrated simplified FE models can accurately predict the nonlinear structural response in the absence of significant modeling errors. In the last part of this study, the physics-based models are further simplified for casting into state-space formulation and a real-time identification is performed using an Unscented Kalman filter. It has been shown that the performance of calibrated state-space models can be satisfactory when reasonable modeling assumptions are used.
•Nonlinear models of a shear wall structure are identified.•Effects of modeling errors and data features used in the identification are studied.•Certain data features provide better identification results.•For large modeling errors, addition of data does not significantly improve the results.
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