This paper focuses on the vibration analysis of three-layered curved sandwich beams with elastic face layers and viscoelastic core. First, the equations of motion that govern the free vibrations of the curved beams together with the boundary conditions are derived by using the principle of virtual work, in the most general form. Then, these equations are solved by using the generalized differential quadrature method in the frequency domain, for the first time to the best of the authors’ knowledge. Verification of the proposed beam model and the generalized differential quadrature solution is carried out via comparison with the results that already exist in literature and the ANSYS finite element solution combined with the modal strain energy method. The effect of system parameters, i.e. layer thicknesses, the lamination angle of layers and the curvature on the vibration and damping characteristics of a curved sandwich beam with laminated composite face layers and a frequency dependent viscoelastic core is investigated in detail.

In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5‐DOF quarter‐rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h) of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.

This study examined automobile vibrations by using a half vehicle model, and its vertical and angular vibrations were suppressed by means of the nonlinear adaptive control of a magneto-rheological damper. The control method was designed in such a way that it did not need to measure the road input to suppress the vibrations by the use of adaptive road observers. Therefore, disadvantages such as measurement difficulty and cost were also eliminated. Instead of completely experimental test rigs, the hardware-in-the-loop simulation which is a hybrid method was preferred due to it being easier to set up, cheaper, and also it had a close response to the full experimental system. The experimental responses obtained by the proposed adaptive control method with adaptive road observers and the nonlinear adaptive control method in which the road disturbances were measured were compared in the time and frequency domains. Finally, the effectiveness of the proposed method was shown using some figures, root mean square values, and performance indices.

Purpose: In this study, a railway superstructure is modeled with a new approach called locally continuous supporting, and its behavior under the effect of moving load is analyzed by using analytical and numerical techniques. The purpose of the study is to demonstrate the success of the new modeling technique. Design/methodology/approach: In the railway superstructure, the support zones are not modeled with discrete spring-damping elements. Instead of this, it is considered to be a continuous viscoelastic structure in the local areas. To model this approach, the governing partial differential equations are derived by Hamilton’s principle and spatially discretized by the Galerkin’s method, and the time integration of the resulting ordinary differential equation system is carried out by the Newmark–Beta method. Findings: Both the proposed model and the solution technique are verified against conventional one-dimensional and three-dimensional finite element models for a specific case, and a very good agreement between the results is observed. The effects of geometric, structural, and loading parameters such as rail-pad length, rail-pad stiffness, rail-pad damping ratio, the gap between rail pads and vehicle speed on the dynamic response of railway superstructure are investigated in detail. Originality/value: There are mainly two approaches to the modeling of rail pads. The first approach considers them as a single spring-damper connected in parallel located at the centroid of the rail pad. The second one divides the rail pad into several parts, with each of part represented by an equivalent spring-damper system. To obtain realistic results with minimum CPU time for the dynamic response of railway superstructure, the rail pads are modeled as continuous linearly viscoelastic local supports. The mechanical model of viscoelastic material is considered as a spring and damper connected in parallel.

This study aims to determine the stiffness values of under sleeper pad (USP) and rail pad (RP) components to reduce the high-amplitude vibrations that occur in the transition zones of some specific structures such as viaducts in ballasted railways. The conventional method of simulating USPs and RPs as spring–dashpot elements in the Kelvin–Voigt model is inadequate due to the absence of frequency and temperature dependencies in the model. The study proposes a new analytical model that considers USPs and RPs as viscoelastic (VE) materials and integrates them into the ballasted railway superstructure model by adding unit masses avoiding mathematical singularity. The process includes material testing, field measurements, and validation of the proposed model with finite element model analysis. The effect of ambient temperature and material modelling on the superstructure’s dynamic response in the frequency domain is analysed in detail. To account for VE behaviours of the resilient elements, the generalised Maxwell model (GMM) is chosen via unit mass implementation compared to other VE models. The obtained results show that the dynamic response of the railway superstructure is 8–10 times sensitive to temperature variation. This demonstrates how important it is to include the temperature-dependent dynamics of the elastomer material in the model. According to the other results that were obtained, the use of USP in transition zones does not solve the vibration problem radically. Bridge dynamic responses are also sensitive to the mass of the bridge rather than its stiffness.

This study has developed a novel measurement-based computational method that accurately determines the vertical and lateral wheel–rail contact forces transmitted from railway vehicles to the rails. A major contribution—and the first in the literature—is the analytical distribution of the total lateral wheelset force into its outer-wheel and inner-wheel components, thereby enabling precise individual evaluation of derailment risk on each wheel in curved tracks. Analytical equations derived from Newton’s second law were first formulated to express both vertical forces and total axle lateral force directly from bogie/axle-box accelerations and suspension reactions. To eliminate the deviations caused by conventional simplifying assumptions (neglect of creep effects, wheel diameter variation, and constant contact geometry), surrogate functions and distribution equations sensitive to curve radius, vehicle speed, and cant deficiency were introduced for the first time and seamlessly integrated into the equations. Validation was performed using the Istanbul Tramway multibody model in SIMPACK 2024x.2, with the equations implemented in MATLAB/Simulink R2024b. Excellent agreement with SIMPACK reference results was achieved on straight tracks and curves, after regression-based calibration of the surrogate functions. Although the method requires an initial regression calibration within a simulation environment, it relies exclusively on measurable parameters, ensuring low cost, full compatibility with existing vehicle sensors, and genuine suitability for real-time monitoring. Consequently, it supports predictive maintenance and proactive safety management while overcoming the practical limitations of instrumented wheelsets and offering a robust, fleet-scalable alternative for the railway industry.