Fully automated operational modal analysis using multi-stage clustering

The interest for robust automatic modal parameter extraction techniques has increased significantly over the last years, together with the rising demand for continuous health monitoring of critical infrastructure like bridges, buildings and wind turbine blades. In this study a novel, multi-stage clustering approach for Automated Operational Modal Analysis (AOMA) is introduced. In contrast to existing approaches, the procedure works without any user-provided thresholds, is applicable within large system order ranges, can be used with very small sensor numbers and does not place any limitations on the damping ratio or the complexity of the system under investigation. The approach works with any parametric system identification algorithm that uses the system order n as sole parameter. Here a data-driven Stochastic Subspace Identification (SSI) method is used. Measurements from a wind tunnel investigation with a composite cantilever equipped with Fiber Bragg Grating Sensors (FBGSs) and piezoelectric sensors are used to assess the performance of the algorithm with a highly damped structure and low signal to noise ratio conditions. The proposed method was able to identify all physical system modes in the investigated frequency range from over 1000 individual datasets using FBGSs under challenging signal to noise ratio conditions and under better signal conditions but from only two sensors

Operational Modal Analysis of a wing excited by transonic flow

Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed

A hybrid embedded cohesive element method for predicting matrix cracking in composites

The complex architecture of many fibre-reinforced composites makes the generation of finite element meshes a labour-intensive process. The embedded element method, which allows the matrix and fibre reinforcement to be meshed separately, offers a computationally efficient approach to reduce the time and cost of meshing. In this paper we present a new approach of introducing cohesive elements into the matrix domain to enable the prediction of matrix cracking using the embedded element method. To validate this approach, experiments were carried out using a modified Double Cantilever Beam with ply drops, with the results being compared with model predictions. Crack deflection was observed at the ply drop region, due to the differences in stiffness, strength and toughness at the bi-material interface. The new modelling technique yields accurate predictions of the failure process in composites, including fracture loads and crack deflection path

Dietary Modulation of Drosophila Sleep-Wake Behaviour

Background A complex relationship exists between diet and sleep but despite its impact on human health, this relationship remains uncharacterized and poorly understood. Drosophila melanogaster is an important model for the study of metabolism and behaviour, however the effect of diet upon Drosophila sleep remains largely unaddressed. Methodology/Principal Findings Using automated behavioural monitoring, a capillary feeding assay and pharmacological treatments, we examined the effect of dietary yeast and sucrose upon Drosophila sleep-wake behaviour for three consecutive days. We found that dietary yeast deconsolidated the sleep-wake behaviour of flies by promoting arousal from sleep in males and shortening periods of locomotor activity in females. We also demonstrate that arousal from nocturnal sleep exhibits a significant ultradian rhythmicity with a periodicity of 85 minutes. Increasing the dietary sucrose concentration from 5% to 35% had no effect on total sucrose ingestion per day nor any affect on arousal, however it did lengthen the time that males and females remained active. Higher dietary sucrose led to reduced total sleep by male but not female flies. Locomotor activity was reduced by feeding flies Metformin, a drug that inhibits oxidative phosphorylation, however Metformin did not affect any aspects of sleep. Conclusions We conclude that arousal from sleep is under ultradian control and regulated in a sex-dependent manner by dietary yeast and that dietary sucrose regulates the length of time that flies sustain periods of wakefulness. These findings highlight Drosophila as an important model with which to understand how diet impacts upon sleep and wakefulness in mammals and humans

A study on the uniaxial tension of FCC metals at nano level using MD

Molecular Dynamics (MD) are now having orthodox means for simulation of matter in nano-scale. It can be regarded as an accurate alternative for experimental work in nano-science. In this paper, Molecular Dynamics simulation of uniaxial tension of some face centered cubic (FCC) metals (namely Au, Ag, Cu and Ni) at nano-level have been carried out. Sutton-Chen potential functions and velocity Verlet formulation of Noise-Hoover dynamic as well as periodic boundary conditions were applied. MD simulations at different loading rates and temperatures were conducted, and it was concluded that by increasing the temperature, maximum engineering stress decreases while engineering strain at failure is increasing. On the other hand, by increasing the loading rate both maximum engineering stress and strain at failure are increasing

Durability of structural health monitoring systems under impact loading

This paper reports an experimental study on the degradation of Piezoelectric Wafer Active Sensors (PWAS) under impact loading. Carbon/epoxy laminates with surface bonded / embedded sensors were subjected to different levels of impact energy, and the performance of PWAS was monitored using impedance analysis. The effect of direct and indirect impact loading on the degradation of piezoelectric sensors was also examined. Using the force history data, a reduction in the flexural stiffness of the embedded specimens was identified. Examining the capacitance, output voltage and electromechanical impedance of PWAS, it was found that the degradation of the sensors under impact loading depends on the level of impact energy, location of the impactor as well as the number of impacts. Identification of the structural damage and sensor's degradation was verified using SEM micrographs

A hybrid averaging approach to predict overall properties of nanocomposites

A new method is proposed to consider the characterizations of the fillers in overall properties of heterogeneous media, and in particular, nanocomposites. According to this method, named 'Hybrid averaging,' the effective properties of a general nanocomposite containing several phases and orientations can be found using the results from a number of simple unidirectional two-phase nanocomposites. The results for the simple media might be obtained from any roots including analytical approaches, numerical simulations, and experimental analyses. In this article, M-T as the analytical and FE as the numerical approaches are combined with the proposed hybrid method. To perform FE analysis, RRVE with periodic boundary conditions is employed. In addition, the influential parameters consisting of RRVE size and mesh density on the numerical results are justified by satisfying certain criteria. Numerical investigations are then done for two case studies of nanocomposites in which boron nitride nanotubes, as fillers, are distributed using two different functions. Furthermore, comparisons are made between the results obtained from different approaches for these materials