Fuzzy uncertainty analysis and reliability assessment of aeroelastic aircraft wings

In the present study, fuzzy uncertainty and reliability analysis of aeroelastic aircraft wings are investigated. The uncertain air speed and structural parameters are represented by fuzzy triangular membership functions. These uncertainties are propagated through the wing model using a fuzzy interval approach, and the uncertain flutter speed is obtained as a fuzzy variable. Further, the reliability of the wing flutter is based on the interference area in the pyramid shape defined by the fuzzy flutter speed and air speed. The ratio between the safe region volume and the total volume of the pyramid gives the reliability value. Two different examples are considered—a typical wing section, and a clean wing—and the results are given for various wind speed conditions. The results show that the approach considered is a low-cost but suitable method to estimate the reliability of the wing flutter speed in the presence of uncertainties

On the Effects of Structural Coupling on Piezoelectric Energy Harvesting Systems Subject to Random Base Excitation

The current research investigates the novel approach of coupling separate energy harvesters in order to scavenge more power from a stochastic point of view. To this end, a multi-body system composed of two cantilever harvesters with two identical piezoelectric patches is considered. The beams are interconnected through a linear spring. Assuming a stochastic band limited white noise excitation of the base, the statistical properties of the mechanical response and those of the generated voltages are derived in closed form. Moreover, analytical models are derived for the expected value of the total harvested energy. In order to maximize the expected generated power, an optimization is performed to determine the optimum physical and geometrical characteristics of the system. It is observed that by properly tuning the harvester parameters, the energy harvesting performance of the structure is remarkably improved. Furthermore, using an optimized energy harvester model, this study shows that the coupling of the beams negatively affects the scavenged power, contrary to the effect previously demonstrated for harvesters under harmonic excitation. The qualitative and quantitative knowledge resulting from this analysis can be effectively employed for the realistic design and modelling of coupled multi-body structures under stochastic excitations

An ocean wave-based piezoelectric energy harvesting system using breaking wave force

Nowadays, in the case of the coastal structures, wave breaking and access to clean energy are two important issues, which can be addressed by combining breakwater and vibration-based energy harvesting systems. In this study, the mechanical energy which is produced when ocean wave breaks into a vertical face is converted into electrical energy. To accomplish this, a new low-volume piezoelectric beam-column energy harvesting system is proposed. To study the application of this system, a theoretical model is presented and studied analytically. The analytical model is updated using experimental data and it is shown that the analytical results were similar to the experimental results after updating. After validating the electromechanical model, an energy harvesting system is presented, which can produce energy from breaking ocean waves on a vertical face. Four possible conceptual designs for energy harvesting systems are considered and the so-called Perfection Rate (PR) is introduced to select the best model to maximize harvested energy whilst mitigating the deteriorating effects of large strain deformation

Nonlocal elasticity in plates using novel trial functions

This study presents the Ritz formulation, which is based on boundary characteristic orthogonal polynomials (BCOPs), for the two-phase integro-differential form of the Eringen nonlocal elasticity model. This approach is named the nonlocal Ritz method (NL-RM). This feature greatly reduces the computational cost compared to the nonlocal finite-element method (NL-FEM). Another advantage of this approach is that, unlike NL-FEM, the nonlocal mass and stiffness matrices are independent of the mesh distribution. Here, these formulations are applied to study the static-bending and free-dynamic analyses of the Kirchhoff plate model. In this paper, novel 2D BCOPs of the plate are derived as coordinate functions. These polynomials are generated using a modified Gram-Schmidt process and satisfy the given geometrical boundary conditions as well as the natural boundary conditions. The accuracy and convergence of the presented model, demonstrated through several numerical examples, are discussed. A concise argument on the advantages of NL-RM compared to NL-FEM is also provided

On the Efficiency Enhancement of an Actively Tunable MEMS Energy Harvesting Device

In this paper, we propose an active control method to adjust the resonance frequency of a capacitive energy harvester. To this end, the resonance frequency of the harvester is tuned using an electrostatic force, which is actively controlled by a voltage source. The spring softening effect of the electrostatic force is used to accommodate the dominant frequency of the ambient mechanical vibration within the bandwidth of the resonance region. A single degree of freedom is considered, and the nonlinear equation of motion is numerically integrated over time. Using a conventional proportional–integral–derivative (PID) control mechanism, the results demonstrated that our controller could shift the resonance frequency leftward on the frequency domain and, as a result, improve the efficiency of the energy harvester, provided that the excitation frequency is lower than the resonance frequency of the energy harvester. Application of the PID controller in the resonance zone resulted in pull-in instability, adversely affecting the harvester’s performance. To tackle this problem, we embedded a saturation mechanism in the path of the control signal to prevent a sudden change in motion amplitude. Outside the pull-in band, the saturation of the control signal resulted in the reduction of harvested power compared to the non-saturated signal; this is a promising improvement in the design and analysis of energy harvesting devices

The effect of preload and surface roughness quality on linear joint model parameters

The physical parameters of the contact interfaces, such as preload and surface roughness quality, significantly affect the stiffness of joints. Knowledge of the relationship between these interface parameters and the equivalent stiffness allows joints to be considered in the design stages of complex structures. Hence, this paper considers the effect of contact interface parameters on the identified equivalent stiffness parameters of joint models. First, a new generic joint model is proposed to model the contact interfaces. Then, the ability of three different joint models, including the new model proposed in this paper, to capture the linear effects of contact interfaces under different preloads and surface roughness qualities is investigated. Finally, it is concluded that the preload and surface roughness quality control the normal and shearing stiffness of the joint models respectively. Experimental investigations also reveal that a complex mechanism governs the energy dissipation in the contact interface

Experimental and numerical gust identification using deep learning models

Identifying gusts and turbulence events is of primary importance for designing future gust load alleviation systems, calculating airframe load, and analysing incidents. Due to the impossibility of their direct measurement, indirect methods are used and ad hoc experiments are necessary to validate the methodology. This paper employs Convolutional Neural Network and Long Short Term Memory (CNN-LSTM) as well as CNN models for in-flight gust identification. Two aeroelastic models, with different levels of fidelity, representative of a civil and commercial aircraft, are used to generate gust responses to train and test the Deep Learning (DL) models. The results highlight the capability of both LSTM-CNN and CNN models in reconstructing gusts across the entire flight envelope of a civil commercial aircraft. The CNN model demonstrated its ability to identify gusts and turbulence when they occur concurrently, similar to real-world scenarios, in a significantly shorter amount of time. Furthermore, its application to wind tunnel gust response measurements, where the inflow has previously been characterised, demonstrated the effectiveness of the proposed methodology for experimental measurements