ALBERT

Description: This study investigates the nonlinear dynamic response behavior of a rotating ring that forms an essential element of MEMS (Micro Electro Mechanical Systems) ring-based vibratory gyroscopes that utilize oscillatory nonlinear electrostatic forces. For this purpose, the dynamic behavior due to nonlinear system characteristics and nonlinear external forces was studied in detail. The partial differential equations that represent the ring dynamics are reduced to coupled nonlinear ordinary differential equations by suitable addition of nonlinear mode functions and application of Galerkin’s procedure. Understanding the effects of nonlinear actuator dynamics is essential for characterizing the dynamic behavior of such devices. For this purpose, a suitable theoretical model to generate a nonlinear electrostatic force acting on the MEMS ring structure is formulated. Nonlinear dynamic responses in the driving and sensing directions are examined via time response, phase diagram, and Poincare’s map when the input angular motion and nonlinear electrostatic force are considered simultaneously. The analysis is envisaged to aid ongoing research associated with the fabrication of this type of device and provide design improvements in MEMS ring-based gyroscopes.

Description: In this paper, we use the Monte Carlo simulation to study aeroelastic behavior caused by non-random uncertain free-stream velocity. For sampling, we use the interval process method. Each family of samples is defined by a correlation function and upper and lower bounds. By using this sampling method, there is no need for constructing precise probability distribution functions; therefore, this method is suitable for practical engineering applications. We studied the aeroelastic behavior of an airfoil and a high aspect-ratio wing.

Description: A recent blast design trend is to properly select cladding characteristics in order to limit blast consequences on its supporting structure. In this context, it is worth noting that cladding components may exhibit significant membrane action, and its effects may be decisive for the supporting structure. The main focus of the present study was to examine these effects through two-step dimensionless SDOF analyses, aimed at reaching conclusions that would be applicable to a large variety of cladding/supporting structure arrangements. The results of these analyses are presented by employing the dynamic load factor, representing the maximum supporting structure displacement. It was found that cladding membrane action has adverse effects over its supporting structure, as it does not allow for extensive plastic dissipation and leads to higher support reactions. On the contrary, insignificant membrane action leads to lower dynamic load factor for the supporting structure. Thus, membrane behavior should be activated only as a safety backup action in order to prevent cladding failure. A case study of a typical cladding/supporting structure is presented to demonstrate and verify the proposed two-step SDOF analyses and the obtained results.

Description: A quantitative procedure for the robustness and progressive collapse assessment of reinforced concrete (RC) frames under blast load scenarios is presented. This procedure is supported by multilevel numerical models, including nonlinear numerical analyses of the structural response of both local (i.e., response of the single structural element to the blast load) and global levels (i.e., response of the structural system to the blast-induced damage). Furthermore, the procedure is applied to a 2D RC frame structure. The novelty of the proposed procedure is that the global robustness is evaluated by the so-called “damage-presumption approach” where the considered damages are defined both in typology and extension depending on the blast scenario occurring at the local level. The dedicated local response analysis of a specified blast scenario leads to the proper definition of the so-called “blast-scenario dependent robustness curves”.

Description: The paper presents the analysis of the possibility of fatigue crack detection and monitoring its propagation process using fibre Bragg grating (FBG) sensors. The investigations were carried out on an aluminium alloy sample (a part of the Mi-2 helicopter rotor blade). During the fatigue test, the sample was equipped with FBG sensors applied for strain measurement and the vibration-based strain monitoring. It was observed that the strain curves determined by the FBG sensors agreed well with the fatigue force profile. However, the strain curves were almost insensitive to the crack propagation process, except in the last stage of the test, when the crack length was equal to 25 mm. The strain values and the natural frequencies of the sample that were determined experimentally were compared with the values achieved from the finite element method model, with both methods showing good agreement. Additionally, spectrogram-based analyses were performed, focused on the acoustic waves phenomena related to a crack propagation process. It was confirmed that the proposed signal processing method, based on spectrogram analyses, can be applied for the detection of fatigue crack development in metal structures.

Description: The linear control of a nonlinear response is investigated in this paper, and a nonlinear model of the system is developed and validated. The design of the control system has been constrained based on a suggested application, wherein mass and expense are parameters to be kept to a minimum. Through these restrictions, the array of potential applications for the control system is widened. The structure is envisioned as a robot manipulator link, and the control system utilises piezoelectric elements as both sensors and actuators. A nonlinear response is induced in the structure, and the control system is employed to attenuate these vibrations which would be considered a nuisance in practical applications. The nonlinear model is developed based on Euler–Bernoulli beam theory, where unknown parameters are obtained through optimisation based on a comparison with experimentally obtained data. This updated nonlinear model is then compared with the experimental results as a method of empirical validation. This research offers both a solution to unwanted nonlinear vibrations in a system, where weight and cost are driving design factors, and a method to model the response of a flexible link under conditions which yield a nonlinear response.

Description: The flutter phenomenon is a potentially destructive aeroelastic vibration studied for the design of aircraft structures as it limits the flight envelope of the aircraft. The aim of this work is to propose a heuristic design of a piezoelectric actuator-based controller for flutter vibration suppression in order to extend the allowable speed range of the structure. Based on the numerical model of a three degrees of freedom (3DOF) airfoil and taking into account the FEM model of a V-stack piezoelectric actuator, a filtered PID controller is tuned using the population decline swarm optimizer PDSO algorithm, and gain scheduling (GS) of the controller parameters is used to make the control adaptive in velocity. Numerical simulations are discussed to study the performance of the controller in the presence of external disturbances.

Description: Driving over rising and falling edges on roads and pavements, rails, manhole covers, or transverse joints can influence the driving impression regarding the driver’s perception of vibrations and acoustics. To be able to describe this, objective parameters are used to make the subjective ride comfort measurable and scalable. Previous studies have already contributed to the investigation of the subjective perception regarding the interaction of vibrations and acoustics. However, the results were individual. Aimed at improving the quality of objective analysis methods, driving maneuvers were performed in a real vehicle to investigate the interaction of vibrations and acoustics due to transient road excitations. For this purpose, a sound reproduction system was used, which could provide the acoustic environment for the driver to adapt to while driving. With this method, subjective ratings by varying vibrations and acoustics were collected and with reference to objective parameters statistically evaluated. The results showed that both tactile and audible vibrations under transient influences had no significant interactive effects on the driver’s perception.

Description: Various techniques have been developed to detect railway defects. One of the popular techniques is machine learning. This unprecedented study applies deep learning, which is a branch of machine learning techniques, to detect and evaluate the severity of rail combined defects. The combined defects in the study are settlement and dipped joint. Features used to detect and evaluate the severity of combined defects are axle box accelerations simulated using a verified rolling stock dynamic behavior simulation called D-Track. A total of 1650 simulations are run to generate numerical data. Deep learning techniques used in the study are deep neural network (DNN), convolutional neural network (CNN), and recurrent neural network (RNN). Simulated data are used in two ways: simplified data and raw data. Simplified data are used to develop the DNN model, while raw data are used to develop the CNN and RNN model. For simplified data, features are extracted from raw data, which are the weight of rolling stock, the speed of rolling stock, and three peak and bottom accelerations from two wheels of rolling stock. In total, there are 14 features used as simplified data for developing the DNN model. For raw data, time-domain accelerations are used directly to develop the CNN and RNN models without processing and data extraction. Hyperparameter tuning is performed to ensure that the performance of each model is optimized. Grid search is used for performing hyperparameter tuning. To detect the combined defects, the study proposes two approaches. The first approach uses one model to detect settlement and dipped joint, and the second approach uses two models to detect settlement and dipped joint separately. The results show that the CNN models of both approaches provide the same accuracy of 99%, so one model is good enough to detect settlement and dipped joint. To evaluate the severity of the combined defects, the study applies classification and regression concepts. Classification is used to evaluate the severity by categorizing defects into light, medium, and severe classes, and regression is used to estimate the size of defects. From the study, the CNN model is suitable for evaluating dipped joint severity with an accuracy of 84% and mean absolute error (MAE) of 1.25 mm, and the RNN model is suitable for evaluating settlement severity with an accuracy of 99% and mean absolute error (MAE) of 1.58 mm.

Description: Footbridges are generally slender and lightweight structures with low stiffness, designed to support dynamic loads generated by crowds. Therefore, these structures are exposed to vibration problems related to the resonance of human walking step frequencies and the lower vibration modes. To mitigate these problems, one of the most applied corrective strategies is the installation of tuned mass damper (TMD) systems that aim at the vibration reduction of the footbridge’s dominant mode. A fundamental matter in both the footbridge and the TMD design is the pedestrian load modelling, generally considered as a deterministically moving force or a biodynamic model. However, as human gait is a random process, the deterministic models can lead to non-realistic results, directly affecting the TMD system efficiency. In contrast, the use of probabilistic distributions to simulate the human walk randomness can lead to more reliable time series predictions. In this paper, a random walk (RW) algorithm is developed and applied to simulate different crowd scenarios using a simplified plane model of a coupled human-structure-TMD system. In each scenario, the TMD efficiency in reducing the vibration amplitudes is assessed. Results highlight the importance of considering the walking randomness and pedestrians’ dynamic properties in the TMD design.