Search Results (18)

This study investigates the practical value of angular-velocity measurements in the dynamic identification of pedestrian footbridges, addressing the need for reliable yet cost-effective diagnostics for slender civil structures. A comprehensive experimental campaign on a steel footbridge in Gdynia combined ambient vibration tests, forced excitation (light and heavy shakers), and controlled pedestrian loading. Synchronous translational accelerations and rotational velocities from MEMS sensors enabled evaluation of both bending and torsional responses. Three identification techniques—Peak Picking (PP), Frequency Domain Decomposition (FDD), and Stochastic Subspace Identification (SSI)—were applied and compared with a validated beam–shell FEM developed in SOFiSTiK. The results show that rotational data improve mode-shape interpretation and classification, notably resolving a coupled torsional–vertical mode (VT₂) that was ambiguous in acceleration-only analyses. The fundamental frequency of 3.1 Hz places the bridge in a resonance-prone range; field tests confirmed predominantly vertical response, with horizontal accelerations < 0.05 m/s² and peak vertical accelerations exceeding comfort class CL3 during synchronised walking of six pedestrians (≈2.55 m/s²) and jumping (up to 3.61 m/s²). Overall, the outcomes highlight that low-cost gyroscopic sensing offers substantial benefits for structural system identification and mode-shape characterization, enriching acceleration-based diagnostics and strengthening the basis for subsequent analyses. By reducing the financial and material demands of vibration testing, the proposed approach contributes to more sustainable assessment and maintenance of pedestrian bridges, aligning with resource-efficient monitoring strategies in civil infrastructure. Full article

Ensuring the purity of water sources is a paramount global challenge, necessitating the development of highly sensitive and rapid detection technologies. In this work, a novel Zeonex-based photonic crystal fiber (PCF) sensor is designed and numerically analyzed for the effective differentiation of pure and polluted water by identifying their unique fingerprints in the terahertz (THz) spectrum. The proposed structure features a rectangular core for analyte infiltration, surrounded by a unique hybrid cladding, meticulously engineered with four inner “mode-shaping” rectangular air holes and an outer “confinement” ring of elliptical air holes. This complex topology is strategically designed to maximize the core-power fraction while ensuring robust mode confinement, enabling the exceptional performance metrics observed. The guiding properties and sensing performance of the sensor are rigorously scrutinized using the Finite Element Method (FEM) over a broad frequency range of 0.5 to 3 THz, accommodating analytes with refractive indices from 1.33 to 1.46. This range is specifically chosen to cover the refractive index of pure water (≈1.33) and a broad spectrum of common chemical and biological pollutants. The simulation results demonstrate the exceptional performance of the sensor. For polluted water, the sensor achieves an ultra-high relative sensitivity of 99.6% with a negligible confinement loss of 1.4 × 10⁻¹¹ dB/m at an operating frequency of 3 THz. In contrast, pure water exhibits a high sensitivity of 96% and a confinement loss 9.4 × 10⁻⁶ of dB/m at the same frequency, showcasing a remarkable capability to distinguish between different water qualities. The superior sensitivity, extremely low loss, and structurally feasible design make the proposed PCF sensor an up-and-coming candidate for real-time water quality monitoring within the THz domain. Full article

In the context of complex operational environments and limited sensor configurations, modal identification of large-scale tower structures often faces challenges related to adaptive model order determination and modal aliasing. This study develops an algorithmic framework for automatic mode identification based on the corrected Akaike information criterion (AICC) and adaptive density-based clustering. First, unlike traditional singular entropy increment (SEI) methods where the determined model order is affected by cumulative thresholds, the AICC-based approach ensures that the adaptively determined model order remains stable. Furthermore, automatic model order selection using the AICC is integrated with adaptive density-based clustering, where the modal assurance criterion extended to a complex mode space (MACXP) is employed to define a modal distance metric. The proposed framework enhances automatic modal clustering and mode-shape discrimination under limited sensor conditions. Finally, a field application was carried out on A-shaped steel towers of integrated bridge–station structures in a high-speed railway station to identify and validate their dynamic characteristics. The results demonstrate that (i) AICC-based model order selection effectively overcomes the threshold dependence of SEI, ensuring improved stability and reliability; (ii) combining AICC-based order determination with density-based clustering enables stable and automated modal identification; and (iii) compared with the conventional MAC, MACXP exhibits superior mode shape discrimination capability under sparse measurement conditions and clearly reveals differences in the modal characteristics of complex structures. This study provides an effective approach for model order determination, mode discrimination, and automated modal identification of large-scale engineering structures under limited sensor deployments. Full article

This study investigated the acoustic modal characteristics of pump tower structures under fluid–structure coupling effects through a finite element analysis. Compared with the dry condition, filling the internal pipelines with liquid causes the first three natural frequencies to decrease by 17.12%, 16.80%, and 19.50%, respectively, while full external immersion (wet mode) further reduces them by 15.60%, 15.10%, and 5.30%. As the liquid level in the surrounding storage tank increases from 0% to 100%, the first-mode frequency falls from 6.07 Hz to 5.13 Hz (a 15.5% reduction), the second-mode from 14.71 Hz to 12.48 Hz (15.1%), and the third-mode from 19.69 Hz to 18.63 Hz (5.5%). Mode-shape distributions remain qualitatively similar across liquid levels, although local deformation magnitudes decrease by up to 21.0% for the first mode and 18.3% for the second mode. These quantitative findings provide a theoretical and technical basis for predicting dynamic responses of pump tower structures in complex fluid environments. Full article

The steady-state aerodynamics and the aeroelastic response have been analyzed in an oscillating linear transonic cascade at the KTH Royal Institute of Technology. The investigated operating points ($\mathrm{\Pi }=1.29$ and $1.25$) represent an open-source virtual compressor (VINK) operating at a part speed line. At these conditions, a shock-induced separation mechanism is present on the suction side. In the cascade, the central blade vibrates in its first natural modeshape with a 0.69 reduced frequency, and the reference measurement span is 85%. The numerical results are computed from the commercial software Ansys CFX with an SST turbulence model, including a reattachment modification (RM). Steady-state results consist of a Laser-2-Focus anemometer (L2F), pressure taps, and flow visualization. Steady-state numerical results indicate good agreement with experimental data, including the reattachment line length, at both operating points, while discrepancies are observed at low-momentum regions within the passage. Experimental unsteady pressure coefficients at the oscillating blade display a fast amplitude decrease downstream, while numerical results overpredict the amplitude response. Numerical results indicate that, at the measurement plane, for both operating points, the harmonic amplitude is dominated by the shock location. At midspan, there is an interaction between the shock and the separation onset, where large pressure gradients are located. Experimental and numerical responses at blades adjacent to the oscillating blade are in good agreement at both operating points. Full article

When it comes to modern design of turbomachinery, one of the most critical objectives is to achieve higher efficiency and performance by reducing weight, fuel consumption, and noise emissions. This implies the need for reducing the mass and number of the components, by designing thinner, lighter, and more loaded blades. These choices may lead to mechanical issues caused by the fluid–structure interaction, such as flutter and forced response. Due to the periodic aerodynamic loading in rotating components, preventing or predicting resonances is essential to avoid or limit the dangerous vibration of the blades; thus, simulation methods are crucial to study such conditions during the machine design. The purpose of this paper is to assess a numerical approach based on a topology optimization method for the innovative design of a compressor rotor. A fluid-structural optimization process has been applied to a rotor blisk which belongs to a one-and-a-half-stage aeronautical compressor including static and dynamic loads coming from blade rotation and fluid flow interaction. The fluid forcing is computed by some CFD TRAF code, and it is processed via time and space discrete Fourier transform to extract the pressure fluctuation components in a cyclic-symmetry environment. Finally, a topological optimization of the disk is performed, and the encouraging results are presented and discussed. The remarkable mass reduction in the component (≈32%), the mode-shape frequency shift from a fluid forcing frequency, and an overall relevant reduction in the dynamic response around Campbell’s crossing confirm the efficacy of the presented methodology. Full article

Torsional vibration is a critical phenomenon in rotor dynamics. It consists of an oscillating movement of the shaft and causes failures in multiple oscillating fields of application. This type of vibration is more difficult to measure than lateral vibration. Torsional vibrometers are generally invasive and require a complicated setup, as well as being inconvenient for field measurements. One of the most reliable, non-invasive, and transportable measuring techniques involves the laser torsional vibrometer. For this research, two laser heads with different measurement capabilities were utilized. An experimental test rig was used to perform a relative calibration of the two laser vibrometers. The frequency of the acting force and the rotation speed of the shaft vary in the same range, which is commonly found in rotating machines. Finally, experimental measurements of torsional vibrations using laser vibrometers were compared with numerical results from a 1D finite element model of the same test rig. The main outcome of this paper is the definition of a reliable measuring procedure to exploit two laser vibrometers for detecting torsional mode-shapes and natural frequencies on real machines. The relative calibration of two different measuring heads is described in detail, and the procedure was fundamental to properly correlate measuring signals in two machine sections. A good correspondence between the numerical and experimental results was found. Full article

The measurement of the meshing stiffness in gear pairs is a technological problem. Many studies have been conducted, but a few results are available. A tailored test bench was designed and realized to measure the Static Transmission Error in two mating gears to address this issue. The bench is capable of testing several kinds of gears, e.g., spur, helical, conical, and internal, and it measures the transmission error concerning the applied torque. The Static Transmission Error is due to the variable stiffness of the gear teeth during a mesh cycle. In this paper, a dynamical method for measuring gear mesh stiffness is presented. The tooth stiffness is estimated from the torsional modal behavior of the rotating parts of the test bench. The dynamics of the system are acquired using accelerometers and very precise encoders to measure the angular accelerations and displacements of rotating parts. The torsional mode shapes are identified; those that show a vibrational behavior of the gears that do not follow the transmission ratio’s sign of the mating kinematic condition are selected because they depend on the flexibility of the teeth. In such a way, the engagement stiffness is estimated from the natural frequencies of the selected mode-shapes and the known inertia of gears and shafts. The experimentally identified results are also compared with numerical values computed with a commercial software for mutual validation. Full article

In studies of structural mechanics, modal analysis, presented in this paper, is an important tool for analyzing the vibration of an object and its frequencies. In modal analysis, different modes of vibration and the frequencies that generate them are considered. The study covers the nondestructive identification of the elastic characteristics of materials, which involves stochastic algorithms and the application of reverse engineering (i.e., the comparison of reference eigenfrequencies with the results of mathematical models). Identification is achieved by minimizing the objective function—the smaller the value of the objective function, the higher the identification accuracy obtained. By changing the parameters of a material’s mathematical model during identification, certain (usually higher order) modes can change places in a natural frequency spectrum. This leads to the comparison of different order eigenfrequencies, slow convergence and poor accuracy of the identification process. The technique involved in this work is the mode-shape recognition of a specimen of material with an “incorrect” set of elastic properties. The results prove that the identification accuracy of a material’s elastic properties can be increased if an “incorrect” set of elastic properties is removed from the identification process. The research covers only numerical research, with a physical experiment simulation. Full article

We propose to study the nonlinear stroke and lower-order modal interactions of a clamped–clamped shallow-arch flexible micro-electrode. The flexible electrode is electrically actuated through an in-plane parallel-plates field superimposed over out-of-plane electrostatic fringing fields. The in-plane electrostatic fields result from a difference of potential between the initially curved flexible electrode and a lower stationary parallel-grounded electrode. Moreover, the out-of-plane fringing fields are mainly due to the out-of-plane asymmetry of the flexible shallow arch and two respective surrounding stationary side electrodes (left and right). A nonlinear beam model is first introduced, consisting of a nonlinear partial differential equation governing the flexible shallow-arch in-plane deflection. Then, a resultant reduced-order model (ROM) is derived assuming a Galerkin modal decomposition with mode-shapes of a clamped–clamped beam as basis functions. The ROM coupled modal equations are numerically solved to obtain the static deflection. The results indicate the possibility of mono-stable and bi-stable structural behaviors for this particular device, depending on the flexible electrode’s initial rise and the size of its stationary side electrodes. The eigenvalue problem is also derived and examined to estimate the variation of the first three lower natural frequencies of the device when the microbeam is electrostatically actuated. The proposed micro-device is tunable with the possibility of pull-in-free states in addition to modal interactions through linear coupled mode veering and crossover processes. Remarkably, the veering zone between the first and third modes can be electrostatically adjusted and reach $22.6$kHz for a particular set of design parameters. Full article

Designing an electrical motor is a complex process that needs to deal with the non-linearity phenomena caused by the saturation of the iron at high magnetic field strength, the multi-physical nature of the investigated system and with requirements that may come into conflict. This paper proposes to use geometric parametric models to evaluate the multi-physical performances of electrical machines and build a machine learning model that is able to predict multi-physical characteristics of electrical machines from input geometrical parameters. The focus of this work is to accurately estimate the electromagnetic characteristics, motor losses and stator natural frequencies, using the developed machine learning model, at the early-design stage of the electrical motor, when the information about the housing is not available and to include the model in optimisation loops, to speed-up the computational time. Three individual machine learning models are built for each physics analysed, a model for the torque and back electromotive force harmonic orders, one model for motor losses and another one for natural frequencies of the mode-shapes. The necessary data is obtained by varying the geometrical parameters of 2D electromagnetic and 3D structural motor parametric models. The accuracy of different machine learning regression algorithms are compared to obtain the best model for each physics involved. Ultimately, the developed multi-attribute model is integrated in an optimisation routine, to compare the computational time with the classical finite element analysis (FEA) optimisation approach. Full article

This paper presents a modal analysis of honeycomb and re-entrant lattice structures to understand the change in natural frequencies when multi-material configuration is implemented. For this purpose, parallel nylon ligaments within re-entrant and honeycomb lattice structures are replaced with chopped and continuous carbon fibre to constitute multi-material lattice configurations. For each set, the first five natural frequencies were compared using detailed finite element models. For each configuration, three different boundary conditions were considered, which are free–free and clamping at the two sides that are parallel and perpendicular to the vertical parts of the structure. The comparison of the natural frequencies was based on mode-shape matching using modal assurance criteria to identify the correct modes of different configurations. The results showed that the natural frequency of the multi-material configurations increases from 4% to 18% depending on the configuration and material. Full article

The present paper deals with the exact calculation of the Principal Elastic Reference System of R/C Cores, which have thin-walled open section. A new modified technique based on Vlasov torsion theory is developed that examines the warping phenomenon of cores. The exact position of the elastic center (or shear center) of a core and the orientation of the principal axes of elasticity, as well as the exact calculation of warping constant, are special parameters since, on the one hand it strongly affects the in plan stiffness distribution of the building members, and on the other hand it affects the values of the building eigen-frequencies and mode-shapes. These parameters are particularly critical in seismic design of asymmetric multistorey buildings. Based on Vlasov torsion theory of cores with thin-walled open sections, a repetitive mathematical procedure about the calculation of the location of the elastic center of core and the principal start point of the section is proposed. This new modified technique can be applied to cores of any shape. Afterwards, the exact diagram of sectorial coordinates of the section, as well as the warping constant, are calculated. All the above-mentioned parameters are very useful in the simulation of the cores in numerical models that are going to use in linear and nonlinear seismic analysis of the structures. Knowing all mentioned parameters, the numerical accuracy of the finite element method on cores can be checked. Finally, a numerical example, where the proposed new modified technique is applied on a fully asymmetric core, is presented. Full article

This paper describes a non-invasive inspection technique for the estimation of longitudinal stress in continuous welded rails (CWR) to infer the rail neutral temperature (RNT), i.e., the temperature at which the net longitudinal force in the rail is zero. The technique is based on the use of finite element method (FEM), vibration measurements, and machine learning (ML). FEM is used to model the relationship between the boundary conditions and the longitudinal stress of any given CWR to the vibration characteristics (mode shapes and frequencies) of the rail. The results of the numerical analysis are used to train a ML algorithm that is then tested using field data obtained by an array of accelerometers polled on the track of interest. In the study presented in this article, the proposed technique was proven in the field during an experimental campaign conducted in Colorado. A commercial FEM software was used to model the rail track as a short rail segment repeated indefinitely and under varying boundary conditions and stress. Three datasets were prepared and fed to ML models developed using hyperparameter search optimization techniques and k-fold cross validation to infer the stress or the RNT. The frequencies of vibration were extracted from the time waveforms obtained from two accelerometers temporarily attached to the rail. The results of the experiments demonstrated that the success of the technique is dependent on the accuracy of the model and the ability to properly identify the modeshapes. The results also proved that the ML was also able to predict successfully the neutral temperature of the tested rail by using only a limited number of experimental data for the training. Full article

The presence of a crack in a beam leads to changes in its dynamic characteristics and hence changes in its natural frequencies and mode shapes. In this paper, Alternative Admissible Functions (AAF) with penalties for extracting the dynamic characteristics of a Euler–Bernoulli Beam with a shallow crack is proposed and validated. The proposed method has two key advantages. First, the alternative admissible function choice is independent of the boundary conditions, which are modelled via boundary penalty terms. Second, the crack is treated as a penalty function to account for the local stiffness reduction while ensuring beam continuity. The approach is validated with different crack depth ratios and locations. The mass, stiffness, and penalty function matrices for Simply Supported (SS), Clamped–Clamped (CC), and Clamped–Free (CF) are developed and are used in the analysis of a beam with a shallow crack. The proposed method demonstrates results in good agreement with published literature for shallow cracks. A significant advantage of the proposed method is the ease of applicability, eliminating the need for remodeling with changes in boundary conditions or crack parameters. The results show that the crack introduces asymmetry to the beam and may require changing the boundary penalty values, depending on the location and depth of the crack. Full article