Vasilis K. Dertimanis

Nonlinear modeling of a rotational MR damper via an enhanced Bouc–Wen model

The coupling of magnetorheological (MR) dampers with semi-active control schemes has proven to be an effective and failsafe approach for vibration mitigation of low-damped structures. However, due to the nonlinearities inherently relating to such damping devices, the characterization of the associated nonlinear phenomena is still a challenging task. Herein, an enhanced phenomenological modeling approach is proposed for the description of a rotational-type MR damper, which comprises a modified Bouc–Wen model coupled with an appropriately selected sigmoid function. In a first step, parameter optimization is performed on the basis of individual models in an effort to approximate the experimentally observed response for varying current levels and actuator force characteristics. In a second step, based on the previously identified parameters, a generalized best-fit model is proposed by performing a regression analysis. Finally, model validation is carried out via implementation on different sets of experimental data. The proposed model indeed renders an improved representation of the actually observed nonlinear behavior of the tested rotational MR damper.

Vibration-based experimental damage detection of a small-scale wind turbine blade

Structural health monitoring offers an attractive tool for condition assessment, fault prognosis and life-cycle management of wind turbine components. However, owing to the intense loading conditions, geometrical nonlinearities, complex material properties and the lack of real-time information on induced structural response, damage detection and characterization of structural components comprise a challenging task. This study is focused on the problem of damage detection for a small-scale wind turbine (Sonkyo Energy Windspot 3.5 kW) experimental blade. To this end, the blade is dynamically tested in both its nominal (healthy) condition and for artificially induced damage of varying types and intensities. The response is monitored via a set of accelerometers; the acquired signals serve for damage detection via the use of appropriate statistical and modal damage detection methods. The former rely on extraction of a characteristic statistical quantity and establishment of an associated statistical hypothesis test, while the latter rely on tracking of damage-sensitive variations of modal properties. The results indicate that statistical-based methods outperform modal-based ones, succeeding in the detection of induced damage, even at low levels.

On the feasibility of structural metamaterials for seismic-induced vibration mitigation

This paper summarizes recent efforts toward development of locally resonant metamaterial structures for seismic isolation purposes. The metamaterial structure forms a blind zone in the frequency domain, inhibiting the propagation of waves characterised by frequencies lying within this range. The feasibility of fashioning such systems in the [0.5, 5] Hz frequency band, linked to earthquake induced response, is here explored. An analytical and numerical investigation is undertaken relying on Blochs theory and classical vibration analysis. The analysed case-studies pertain to both one-dimensional and two-dimensional mass-in-mass lattice systems investigated for overlapping sub-bands. On the basis of the offered analysis, a basic unit cell design is proposed, and a parametric study is carried out revealing the critical influence of the external-to-internal stiffness ratios adopted for the unit cell design. A further discussion is offered with respect to limitations and extensions of the proposed designs.

Output-only schemes for joint input-state-parameter estimation of linear systems

The subject of predicting structural response, for control or fatigue assessment purposes, via output only vibration measurements is an emerging topic of Structural Health Monitoring. The subject of estimation of the states of a partially observed dynamic system within a stochastic framework has been studied by many scientists and there are well developed algorithms to manage both linear and nonlinear state-space models. Dealing with structural systems, the system states comprise the response displacements and velocities at the degrees of freedom of the structure. On one hand, in practical cases it is difficult or sometimes impossible to measure structural displacements and velocities for continuous monitoring purposes. On the other hand, recent developments in highly accurate low consumption wireless MEMS accelerometers permit continuous and accurate acceleration measurements when dealing with structural systems. Dealing with operational conditions the uncertainties stemming from the absence of information on the input force, model inaccuracy and measurement errors render the state estimation a challenging task, with research to achieve a robust solution still in progress. Eftekhar Azam et al. [1] have proposed a novel dual Kalman filter to accomplish the task of joint input-state estimation for linear time invariant systems. In this study, the extension of such a scheme is considered for the joint input-state and parameter estimation of linear systems.

Design of Metamaterials for Seismic Isolation

This study assesses the implementation of locally resonant metamaterials in seismic isolation applications, by investigating their potential feasibility in low frequency bands. To this end, via adoption of both Blochs Theorem and classical vibration analysis, both one-dimensional and two-dimensional mass-in-mass lattices are analyzed in overlapping subbands and corresponding relations for the structural parameters are derived. The lattices are first examined in an infinite setup, for determining the arrangement of the resulting band gaps. Subsequently finite lattice configurations are investigated in the frequency and time domain. In this work, previous results are corroborated and additionally expanded to the 2D case. The parametric study that was carried out reveals interesting properties, particularly for low external-to-internal stiffness ratios of the unit cells comprising the lattices. Further investigation is required for confirming the feasibility of application of the resulting setups in full scale.

On the Monitoring-Driven Assessment of Engineered Systems

The life-cycle management of structural systems operating under diverse loads involves the tasks of simulation (forward engineering), identification (inverse engineering) and maintenance/control actions. The efficient and successful implementation of these tasks is however non-trivial, due to the ever-changing nature of these systems, and the variability in their interactive environment. Two defining factors in understanding and interpreting such large-scale systems are nonlinear behavior and structural uncertainty. The former is related to the external dynamic loading that might shift the structural response from purely linear to nonlinear regimes, while the latter is related to erroneous modeling assumptions, imprecise sensory information, ageing effects, and lack of a priori knowledge of the system itself. This paper discusses implementation of methods and tools able to tackle the aforementioned challenges. Among other topics, the use of surrogate models and Bayesian-type filters for the reduced representation and identification of uncertain and nonlinear structural systems is discussed.

Fatigue Monitoring and Remaining Lifetime Prognosis Using Operational Vibration Measurements

A framework is presented for real-time monitoring of fatigue damage accumulation and prognosis of the remaining lifetime at hotspot locations of new or existing structures by combining output-only vibration measurements from a permanently installed, optimally located, sparse sensor network with the information build into high-fidelity computational mechanics models. To produce fatigue damage accumulation maps at component and/or system level, valid for the monitoring period, the framework integrates developments in (a) fatigue damage accumulation (FDA) and (b) stress time histories predictions under loading and structural modeling uncertainties based on monitoring information (Papadimitriou et al., Struct Control Health Monit 18(5):554–573, 2011). Methods and computational tools include, but are not limited to, the use of Kalman-type filters for state and stress response reconstruction based on the sensor information (Eftekhar Azam et al., Mech Syst Signal Process 60:866–886, 2015; Lourens et al., Mech Syst Signal Process 29:310–327, 2012), as well as stress cycle counting techniques, S-N curves and fatigue damage accumulation laws (Miner, Appl Mech Trans (ASME) 12(3):159–164, 1945; Palmgren, VDI-Z 68(14):339–341, 1924) to estimate fatigue from the reconstructed stress time histories at numerous hot spot locations. The FDA maps provide realistic fatigue estimates consistent with the actual operational conditions experienced by an individual structure. Combined with models of future loading events and their uncertainties, assumed or rationally estimated during the long-term monitoring period, the continuously updated FDA maps can be used to predict the remaining fatigue lifetime maps and associated uncertainties. Developments are valuable for planning cost-effective maintenance strategies, eventually reducing the life-cycle maintenance cost.

Optimal sensor placement methods and metrics – comparison and implementation on a timber frame structure

Abstract The current work aims at determining optimal sensor configurations for the modal identification of a post-tensioned timber frame structure. The objective is to maximise the information gained from the structural testing, while keeping the number of necessary sensors to a minimum. Three different and widely used optimal sensor placement (OSP) methods are investigated and evaluated based on appropriate metrics, namely the effective independence method, the modal kinetic energy method and the information entropy (IE) method. An enhanced IE variant is adopted, which resolves the problem of close positioning of sensors, which forms a common issue when sensor positions are selected from a dense grid. In terms of the adopted metrics, three different options are investigated, namely, the information entropy index, the Modal Assurance Criterion and a newly introduced metric, the relative dispersion index. For the quantification of trade-offs among the selected metrics a Pareto Front scheme is realised. The study indicates that the evaluation of different OSP configurations is strongly dependent on the employed metric. It is therefore of vital importance to select the appropriate metric when determining optimal sensor positions.

Structural health monitoring and fatigue damage estimation using vibration measurements and finite element model updating

In this work, a computational framework is proposed for fatigue damage estimation in structural systems by integrating operational experimental measurements in a high-fidelity, large-scale finite element model. The proposed method is applied in a linear steel substructure of a lignite grinder assembly at a Public Power Corporation power plant. A finite element model of the steel base is developed and updated to match the dynamic characteristics measured in real operating conditions. This is achieved through coupled use of numerical and experimental methods for identifying, updating, and optimizing a high-fidelity finite element model. The full stress time histories of the complex mechanical assembly are estimated, at critical locations, by imposing operational vibration measurements from a limited number of sensors in the updated finite element model. Fatigue damage and remaining lifetime is subsequently estimated via commonly adopted engineering approaches, such as Palmgren–Miner damage rule, S–N curves, and rainflow cycle counting. Incorporation of a numerical model of the structure in the response estimation procedure permits stress estimation at unmeasured locations, thereby enabling the drawing of a complete and substantially dense fatigue map consistent with the vibration measurements. Fatigue predictions via the proposed framework are highly correlated to experimental fatigue results, proving the efficiency and applicability of the framework.

Large scale metasurfaces for seismic waves control

Elastic metamaterials are artificial composites with subwavelength resonant particles hosted in a medium able to manipulate the propagation of elastic waves. When the resonant particles are placed at the free surface of the medium to form a resonant “metasurface,” the localization mechanism and the direction of surface waves can be fully controlled. In this talk, we discuss the use of resonant metasurfaces to control the propagation of vertically and horizontally polarized surface waves and their possible application for seismic waves mitigation. By combining analytical, numerical, and experimental studies, we describe the interaction of Rayleigh waves with a metasurface of vertical resonators and design large-scale resonant barriers to deviate damaging seismic Rayleigh waves into the medium bulk. Additionally, we investigate the effect of material stratification on the metasurface dynamics by analyzing the propagation of surface waves in unconsolidated granular media with depth-dependent stiffness profile. Finally, we describe the interaction of Love waves guided by a stratified medium with a metasurface of horizontal resonators and design large-scale resonant metalenses to redirect their propagation.