Browsing by Author "Civera, Marco"

Now showing 1 - 13 of 13
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    The accuracy and computational efficiency of the Loewner framework for the system identification of mechanical systems
    (MDPI, 2023-06-20) Dessena, Gabriele; Civera, Marco; Ignatyev, Dmitry; Whidborne, James F.; Zanotti Fragonara, Luca; Chiaia, Bernardino
    The Loewner framework has recently been proposed for the system identification of mechanical systems, mitigating the limitations of current frequency domain fitting processes for the extraction of modal parameters. In this work, the Loewner framework computational performance, in terms of the elapsed time till identification, is assessed. This is investigated on a hybrid, numerical and experimental dataset against two well-established system identification methods (least-squares complex exponential, LSCE, and subspace state space system identification, N4SID). Good results are achieved, in terms of better accuracy than LSCE and better computational performance than N4SID.
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    A comparative analysis of optimization algorithms for finite element model updating on numerical and experimental benchmarks
    (MDPI, 2023-12-01) Raviolo, Davide; Civera, Marco; Zanotti Fragonara, Luca
    Finite Element Model Updating (FEMU) is a common approach to model-based Non-Destructive Evaluation (NDE) and Structural Health Monitoring (SHM) of civil structures and infrastructures. Its application can be further utilized to produce effective digital twins of a permanently monitored structure. The FEMU concept, simple yet effective, involves calibrating and/or updating a numerical model based on the recorded dynamic response of the target system. This enables to indirectly estimate its material parameters, thus providing insight into its mass and stiffness distribution. In turn, this can be used to localize structural changes that may be induced by damage occurrence. However, several algorithms exist in the scientific literature for FEMU purposes. This study benchmarks three well-established global optimization techniques—namely, Generalized Pattern Search, Simulated Annealing, and a Genetic Algorithm application—against a proposed Bayesian sampling optimization algorithm. Although Bayesian optimization is a powerful yet efficient global optimization technique, especially suitable for expensive functions, it is seldom applied to model updating problems. The comparison is performed on numerical and experimental datasets based on one metallic truss structure built in the facilities of Cranfield University. The Bayesian sampling procedure showed high computational accuracy and efficiency, with a runtime of approximately half that of the alternative optimization strategies.
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    Experimental modal analysis of structural systems by using the fast relaxed vector fitting method
    (Wiley, 2021-01-06) Civera, Marco; Calamai, Giulia; Zanotti Fragonara, Luca
    System identification (SI) techniques can be used to identify the dynamic parameters of mechanical systems and civil infrastructures. The aim is to rapidly and consistently model the object of interest, in a quantitative and principled manner. This is also useful in establishing the capacity of a structure to serve its purpose, thus as a tool for structural health monitoring (SHM). In this context, input–output SI techniques allow precise and robust identification regardless of the actual input. However, one of the most popular and widely used approaches, the Rational Fraction Polynomial (RFP) method, has several drawbacks. The fitting problem is nonlinear and generally non‐convex, with many local minima; even if linearised via weighting, it can become severely ill‐conditioned. Here, a novel proposal for the broadband macro‐modelling of structures in the frequency domain with several output and/or input channels is presented. A variant of the vector fitting approach, the Fast Relaxed Vector Fitting (FRVF), applied so far in the literature only for the identification of electrical circuits, is translated and adapted to serve as a technique for structural SI and compared with other traditional techniques. A study about the robustness of the FRVF method with respect to noise is carried out on a numerical system. Finally, the method is applied to two experimental case studies: a scaled model of a high‐aspect‐ratio (HAR) wing and the well known benchmark problem of the three‐storey frame of Los Alamos laboratories. Promising results were achieved in terms of accuracy and computational performance.
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    An experimental study of the feasibility of phase‐based video magnification for damage detection and localisation in operational deflection shapes
    (Wiley, 2019-01-08) Civera, Marco; Zanotti Fragonara, Luca; Surace, Cecilia
    Optical measurements from high‐speed, high‐definition video recordings can be used to define the full‐field dynamics of a structure. By comparing the dynamic responses resulting from both damaged and undamaged elements, structural health monitoring can be carried out, similarly as with mounted transducers. Unlike the physical sensors, which provide point‐wise measurements and a limited number of output channels, high‐quality video recording allows very spatially dense information. Moreover, video acquisition is a noncontact technique. This guarantees that any anomaly in the dynamic behaviour can be more easily correlated to damage and not to added mass or stiffness due to the installed sensors. However, in real‐life scenarios, the vibrations due to environmental input are often so small that they are indistinguishable from measurement noise if conventional image‐based techniques are applied. In order to improve the signal‐to‐noise ratio in low‐amplitude measurements, phase‐based motion magnification has been recently proposed. This study intends to show that model‐based structural health monitoring can be performed on modal data and time histories processed with phase‐based motion magnification, whereas unamplified vibrations would be too small for being successfully exploited. All the experiments were performed on a multidamaged box beam with different damage sizes and angles.
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    A generalised power-law formulation for the modelling of damping and stiffness nonlinearities
    (Elsevier, 2020-12-26) Civera, Marco; Grivet-Talocia, Stefano; Surace, Cecilia; Zanotti Fragonara, Luca
    In this paper, a single-degree-of-freedom dynamic model is described, with displacement- and velocity-dependent nonlinearities represented by power laws. The model is intended to support the dynamic identification of structural components subjected to harmonic excitation. In comparison to other analytical expressions, the data-driven estimation of the nonlinear exponents provides a large versatility, making the generalised model adaptable for a wide number of different nonlinearities in both stiffness and damping. For instance, the proposed damping formulation can naturally accommodate air drag (quadratic) damping as well as dry friction. Differently to purely data-driven methods (e.g. black boxes), the obtained model is fully inspectable. The proposed formulation is here applied to the large oscillations of a prototype highly flexible wing and fitted on its steady state response in the frequency domain. These large-amplitude flap-wise bending oscillations are known to be affected by nonlinearities in both the stiffness (nonlinear hardening) and the velocity-dependent damping terms. The model is validated against experiments for different structural configurations and input amplitudes, as both these nonlinearities are energy-dependent.
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    A Loewner-based system identification and structural health monitoring approach for mechanical systems
    (Wiley, 2023-04-18) Dessena, Gabriele; Civera, Marco; Zanotti Fragonara, Luca; Ignatyev, Dmitry; Whidborne, James F.
    Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identifcation (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks. This paper proposes using an input-output system identifcation technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identification techniques. Promising results are achieved in terms of accuracy and reliability.
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    A multi‐objective genetic algorithm strategy for robust optimal sensor placement
    (Wiley, 2021-02-17) Civera, Marco; Pecorelli, Marica Leonarda; Ceravolo, Rosario; Surace, Cecilia; Fragonara, Luca Zanotti
    The performance of a monitoring system for civil buildings and infrastructures or mechanical systems depends mainly on the position of the deployed sensors. At the current state, this arrangement is chosen through optimal sensor placement (OSP) techniques that consider only the initial conditions of the structure. The effects of the potential damage are usually completely neglected during its design. Consequently, this sensor pattern is not guaranteed to remain optimal during the whole lifetime of the structure, especially for complex masonry buildings in high seismic hazard zones. In this paper, a novel approach based on multi‐objective optimization (MO) and genetic algorithms (GAs) is proposed for a damage scenario driven OSP strategy. The aim is to improve the robustness of the sensor configuration for damage detection after a potentially catastrophic event. The performance of this strategy is tested on the case study of the bell tower of the Santa Maria and San Giovenale Cathedral in Fossano (Italy) and compared to other classic OSP strategies and a standard GA approach with a single objective function.
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    Noise-robust modal parameter identification and damage assessment for aero-structures
    (Emerald, 2024-12-16) Dessena, Gabriele; Civera, Marco; Pontillo, Alessandro; Ignatyev, Dmitry I.; Whidborne, James F.; Zanotti Fragonara, Luca
    Purpose Ground vibration testing is critical for aircraft design and certification. Fast relaxed vector fitting (FRVF) and Loewner framework (LF), recently extended to modal parameter extraction in mechanical systems to address the computational challenges of time and frequency domain techniques, are applied for damage detection on aeronautically relevant structures. Design/methodology/approach FRVF and LF are applied to numerical datasets to assess noise robustness and performance for damage detection. Computational efficiency is also evaluated. In addition, they are applied to a novel damage detection benchmark of a high aspect ratio wing, comparing their performance with the state-of-the-art method N4SID. Findings FRVF and LF detect structural changes effectively; LF exhibits better noise robustness, while FRVF is more computationally efficient. Practical implications LF is recommended for noisy measurements. Originality/value To the best of the authors’ knowledge, this is the first study in which the LF and FRVF are applied for the extraction of the modal parameters in aeronautically relevant structures. In addition, a novel damage detection benchmark of a high-aspect-ratio wing is introduced.
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    Recursive partitioning and Gaussian process regression for the detection and localization of damages in pultruded glass fiber reinforced polymer material
    (Wiley, 2021-06-16) Boscato, Giosuè; Civera, Marco; Zanotti Fragonara, Luca
    In this paper, a methodology for the detection and localization of damages in composite pultruded members is proposed. This is particularly relevant to thin-walled pultruded members, which are typically characterized by orthotropic behavior, anisotropic along the fibers and isotropic in the cross section. Hence, a method to detect and localize damage, and the influence these might have on the performance of thin-walled Glass Fiber Reinforced Polymer (GFRP) members, is proposed and applied to both numerical and experimental data. Specifically, the numerical and experimental modal shapes of a narrow flange pultruded profile are analyzed. The reliability of the proposed semiparametric statistical method, which is based on Gaussian Processes Regression and Bayesian-based Recursive Partitioning, is analyzed on a narrow flange profile, artificially affected by sawed notches with incremental depth. The numerical investigation is carried out via finite element models (FEMs) of the cracked beam, where the dynamic parameters and the modal shapes are computed. In total, three different crack sizes are investigated, to compare the results with the experimental ones. Finally, the proposed approach is further extended and validated on numerically simulated frame structures.
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    System identification via fast relaxed vector fitting for the structural health monitoring of masonry bridges
    (Elsevier, 2021-01-23) Civera, Marco; Calamai, Giulia; Zanotti Fragonara, Luca
    The increasingly request for the maintenance of the architectural heritage has led in the last decades to the extensive use of System Identification (SI) techniques for Structural Health Monitoring (SHM) purposes. These proved to be useful tools for assessing the state of conservation of the built environment and its behaviour in operating conditions. In particular, historical masonry structures and infrastructures present several compelling difficulties. Masonry is non-linear and its mechanical properties are uncertain due to the presence of local irregularities and its internal texture. Moreover, centuries-old buildings are severely affected by deterioration, eventual restoration interventions, and exposure to weather conditions. In this work, the Fast Relaxed Vector Fitting (FRVF) approach is proposed as a rapid, efficient, and reliable instrument for the vibration-based SI of such structures. The method is preliminarily validated on simple numerical examples and a multi-damaged cantilevered box beam, then tested on a true 1:2 scaled model of a masonry two-span arch bridge. The results match well the estimations from other well-established SI techniques, such as the Eigensystem Realization Algorithm (ERA), and can be utilised for damage assessment (with all the standard advantages and limitations of modal-based outlier detection). Stabilisation diagrams and frequency-damping plots are also proposed for FRVF.
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    Treed gaussian process for manufacturing imperfection identification of pultruded GFRP thin-walled profile
    (Elsevier, 2020-08-28) Civera, Marco; Boscato, Giosuè; Fragonara, Luca Zanotti
    The process of manufacturing pultruded FRP (Fiber Reinforced Polymers) profiles involves unavoidable imperfections that affect their structural performances. This is is even more relevant for the stability of axially loaded slender elements, due to the importance of imperfections and notches to initiate the buckling phenomenon. Thus, they become a predominant factor for the design of lightweight FRP beam-like structures. A Bayesian approach is proposed to estimate the presence and location of manufacturing imperfections in pultruded GFRPs (Glass Fiber Reinforced Polymers) profiles. Specifically, the Treed Gaussian Process (TGP) procedure is applied. This approach combines regression Gaussian Processes (GP) and Bayesian-based Recursive Partitioning. The experimental and numerical modal shapes of wide flange pultruded profile were investigated. The experimental data were compared with the numerical results of several Finite Element Models (FEM) characterised by different crack sizes
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    Using video processing for the full-field identification of backbone curves in case of large vibrations
    (MDPI, 2019-05-21) Civera, Marco; Fragonara, Luca Zanotti; Surace, Cecilia
    Nonlinear modal analysis is a demanding yet imperative task to rigorously address real-life situations where the dynamics involved clearly exceed the limits of linear approximation. The specific case of geometric nonlinearities, where the effects induced by the second and higher-order terms in the strain–displacement relationship cannot be neglected, is of great significance for structural engineering in most of its fields of application—aerospace, civil construction, mechanical systems, and so on. However, this nonlinear behaviour is strongly affected by even small changes in stiffness or mass, e.g., by applying physically-attached sensors to the structure of interest. Indeed, the sensors placement introduces a certain amount of geometric hardening and mass variation, which becomes relevant for very flexible structures. The effects of mass loading, while highly recognised to be much larger in the nonlinear domain than in its linear counterpart, have seldom been explored experimentally. In this context, the aim of this paper is to perform a noncontact, full-field nonlinear investigation of the very light and very flexible XB-1 air wing prototype aluminum spar, applying the well-known resonance decay method. Video processing in general, and a high-speed, optical target tracking technique in particular, are proposed for this purpose; the methodology can be easily extended to any slender beam-like or plate-like element. Obtained results have been used to describe the first nonlinear normal mode of the spar in both unloaded and sensors-loaded conditions by means of their respective backbone curves. Noticeable changes were encountered between the two conditions when the structure undergoes large-amplitude flexural vibrations.
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    Video processing techniques for the contactless investigation of large oscillations
    (Institute of Physics, 2019-08-01) Civera, Marco; Zanotti Fragonara, Luca; Surace, Cecilia
    The experimental acquisition of large vibrations presents various technical difficulties. Especially in the case of geometric nonlinearities, dealing with very flexible, very light structures causes minimal variations in mass or stiffness to affect severely the dynamical response. Thus, sensors' added masses change the behaviour of the structure with respect to the unloaded condition. Moreover, the most common tools regularly employed for acquisition in vibration analysis - that is to say, laser vibrometers and accelerometers - are often designed with small amplitudes in mind. Their recordings are known to lack accuracy when the investigated structure undergoes large or very large motions, due to geometrical reasons. Image-based measurement techniques offer a valid solution to this problem. Here, an ensemble of three video processing techniques are benchmarked against each other and tested as viable options for the non-contact dynamic characterisation of slender beam-like structures. The methods have been applied to the case study of an aluminium spar for a highly-flexible airwing prototype and compared to the measurements recorded by a laser velocimeter and several Raspberry PI Inertial Measurement Units (IMUs), which also proved to be minimally invasive.