The present research aims at providing a numerical fluid flow prediction of the less explored T-shaped lid-driven cavity problem. It is solved two ways, first using a finite-difference-method-based vorticity-stream function formulation that is applied to the two-dimensional incompressible Navier-Stokes equations and then by using the SIMPLE algorithm implemented in the finite-volume-method-based OpenFOAM system. Firstly, a numerical in-house code is developed for a classical lid-driven square cavity problem, and successively verified by comparing it with results from the literature. Once the code’s credibility is established, the fluid flow characteristics are thoroughly investigated considering three different wall motions: single-sided, double-sided with co-directional wall motion, and double-sided with counter-directional motion. The investigation also focuses on how the fluid flow characteristics are influenced by both the Reynolds number of the flow and the aspect ratio of the domain. Through numerical simulations, the centerline velocity profiles are plotted, and also the structure and formation of vortices in a T-shaped cavity are compared between both finite difference and finite volume schemes. As the Reynolds number of the domain rises, many recirculation zones are formed, the fluid is shown to flow faster in the wall-driven enclosures. As the aspect ratio increases the strength of the vortices diminishes at the walls of the computational domain.
Operating characteristics (e.g., working area, kinematic and dynamic responses) of hydraulic excavators equipped with standard buckets is inherently defined by the dimensions of links, the corresponding characteristics of driving cylinders, and working conditions. For dredging construction, it is often necessary to integrate additional equipment into the original hydraulic excavator. Excavators mounted on pontoons and equipped with drum cutters are commonly employed for this purpose. Investigating the working performance of these devices is essential for integrating replacement equipment into excavators to meet specific design criteria, technical requirements, and operational spaces. The installation of an extended boom and the modification of the working attachment to meet dredging requirements have resulted in fundamental changes in the kinematic and dynamic characteristics of the working mechanism. Specifically, the addition of a long dynamic link and the presence of resistive forces that vary continuously due to the cutter teeth alternately entering and exiting the cutting zone represent key differences compared to the original machine. This study introduces an innovative configuration for a standard excavator by incorporating a long-reach arm and substituting the bucket with a drum cutter. This modification aims to enhance the excavator’s effectiveness in dredging tasks. In addition to extending the reachable working area to more than twice that of the original configuration, the translational velocity of the drum cutter can exceed that of the actuating cylinder by over 30 times. From a dynamic response perspective, the cutting layer thickness is shown to have a pronounced influence on the variation of resistive force components, driving forces, and joint reaction forces, with the coefficient of variation (CV) reaching values of up to 38.02 %. When the cutting depth is increased by a factor of 1.5, the CV of the force components decreases by the same ratio; however, the magnitudes of these force components may increase by more than four times. Through a comprehensive kinematic and dynamic analysis, the modified working area and operating characteristics of the backhoe dredger are evaluated to ensure safe, efficient, and structurally optimized operations. The proposed design and the findings of the present research offer valuable insights and practical solutions for the manufacturing and improvement of dredging equipment.
This research addresses the uncertainty quantification of time-dependent partial differential equations (PDEs) with random parameters. The stochastic Galerkin method, a sampling-free intrusive approach, is employed instead of sampling- or quadrature-based methods to overcome the slow convergence and high computational cost associated with high-resolution models. An acoustic wave propagation problem with a log-normal random field approximation for wave speed is illustrated. The stochastic partial differential equation with the inputs and outputs expanded using polynomial chaos expansion (PCE) is transformed into a set of coupled deterministic PDEs and discretized to yield a system of linear equations. To handle the increased memory requirements with increasing mesh size, time step and number of random parameters, domain decomposition-based (DD-based) solvers are utilized. A conjugate gradient iterative solver with a two-level Neumann-Neumann preconditioner is applied to the symmetric positive definite system matrix showing their efficient scalability. This combination of the stochastic Galerkin method and DD-based solvers enables large-scale real-time applications involving acoustic waves.
This study presents a surrogate-assisted multi-objective framework for a GE 1.5XLE horizontal-axis wind turbine (HAWT) blade based on a one-way fluid-structure interaction (FSI) analysis. The objective is to identify optimal trade-offs between structural weight reduction and dynamic performance by simultaneously minimizing blade mass and maximizing the fundamental natural frequency. Aerodynamic loads are first computed using computational fluid dynamics (CFD) and subsequently transferred to a structural finite element analysis (FEA) model through a one-way FSI coupling. To reduce the computational cost associated with repeated high-fidelity simulations, a Kriging metamodel is constructed using a latin hypercube sampling (LHS) design of experiments. The resulting surrogate model demonstrated high predictive accuracy, with a maximum prediction error below 0.4 %. A multi-objective genetic algorithm (MOGA) is then employed to generate the Pareto optimal set of solutions and to identify the best compromise designs under stress and deformation constraints. The optimal design achieves an approximately 10% reduction in total mass and a 9.1% increase in fundamental frequency compared with the baseline blade, while satisfying all structural requirements. Independent high-fidelity numerical verification confirms the reliability of the proposed framework, with deviations of less than 0.2 %. The proposed FSI-Kriging-MOGA methodology provides an efficient and reliable computational tool for the aeroelastic optimization of wind turbine blades and can be extended to other complex fluid-structure interaction systems.
Bevel gears play a crucial role in mechanical systems, particularly in power transmission applications where changes in shaft orientation are required. Early fault detection and diagnosis in gearboxes are essential for ensuring operational efficiency and preventing costly failures. This study evaluates and compares the effectiveness of logistic regression (LR) and support vector machine (SVM) classification methods in identifying gear faults, focusing on data-driven condition monitoring rather than predictive maintenance. To enhance the performance of these models, hyperparameter tuning was performed using grid search cross-validation. These techniques are essential for improving model performance, reducing overfitting and increasing classification accuracy. Gear fault classification was carried out using vibration data from a test bench under different speeds, loads, and measurement directions. While LR initially achieved higher accuracy (64.10 %) compared to SVM (38.46 %), hyperparameter tuning significantly improved SVM performance, allowing it to reach an accuracy of 92.31 % compared to 82.05 % in the case of LR. These findings underscore the capability of the optimized SVM model to provide more sensitive and precise fault diagnosis, highlighting its suitability for robust data-driven diagnostics of gear conditions.
Rescue and military helicopters are sometimes exposed to extraordinary operating conditions. Such loading can cause non-standard fatigue defects with very specific types of failure. Failure of a turbocompressor blade during a flight results in an inoperative power unit, leading to a very probable catastrophic scenario. This paper deals with fatigue microcracks of one of the widely used nickel alloys, ZS6K, operated in helicopter turboshaft power units. Despite its widespread use, fracture mechanics and the crack growth rate data are not well known. This knowledge gap exists for historical reasons, as early design practices were based largely on extensive ground and flight testing. Fatigue microcracks observed on turbocompressor blades of a turboshaft engine, made of ZS6K substrate material covered with a protective aluminum layer, after operation under high load, have not been described yet. The novelty of this article is to gather and describe the newly observed initiated fatigue cracks of turboshaft engines and their specific conditions under which they occur. This is the first important step for further research focused on an in-depth description of fracture mechanics, experimental investigation of short crack growth, and mathematical modeling of crack growth in this specific material composition under high-load spectrum. The obtained results fill a gap in operational and material data necessary for the durability and damage tolerance assessment. This paper ultimately contributes to the broader goal of increasing the operational safety of turboshaft power units.
The dynamic behaviour of a rotating Timoshenko functionally graded (FG) beam is investigated, with material properties varying along the height of the beam according to a power-law distribution. The study investigates how key parameters such as the power-law index, rotational speed, slenderness ratio, and various functionally graded material (FGM) compositions affect the dynamic response of the beam. The governing equations, which incorporate shear deformation and rotary inertia effects, are formulated and solved using the B-spline collocation method. The results provide critical insights into how these parameters affect the natural properties of FG beams, contributing to optimization and development for the design of advanced rotating structures in engineering applications.
The free vibration behavior of spinning nanoshafts is critically examined through the framework of nonlocal elasticity. Combining the Euler-Bernoulli beam model with the Eringen’s nonlocal theory, this work formulates a scale-dependent mathematical model. Hamilton’s principle is employed to derive the nonlocal governing equations andassociated boundary conditions. The generalized differential quadrature method (GDQM) is utilized to discretize and solve the resulting eigenvalue problem. Numerical results systematically quantify how the small-scale parameter, angular velocity, and various boundary conditions affect the system’s fundamental and second mode forward and backward frequencies. Additionally, the impact of geometrical properties, such as the aspect ratio and thickness-to-diameter ratio, on the instability thresholds is investigated. The findings of this study offer valuable guidelines for enhancing the performance and stability of advanced rotating nano-electromechanical systems (NEMS).
In this study, a Panasonic 18650 lithium-ion battery module consisting of 24 cells with multiple vents was studied and the design was optimized through numerical simulation. Compared to previous studies showing that the cooling model layout using 1 inlet and 1 outlet was improved, the cooling model with multiple vents improved the temperature difference and the maximum temperature in the cells. Specifically, the effects of multiple directions and the number of inlet/outlet cooling air were analyzed in the study, and finally the appropriate inlet velocity was discovered to be applied on the proposed model. The results showed that the arrangement of 2 inlets air holes at the center of the two ends of the battery module and 1 outlet hole at the center of the bottom surface produced the best cooling effect compared to the first model and other models. The maximum temperature (Tmax) and maximum temperature difference (∆Tmax ) were reduced by 312.62 K (14 %) and 6.74 K (88 %), respectively compared to the first model. Furthermore, with the 2 inlets – 1 outlet model being the optimal cooling model for the selected model, consideration of the velocity input value to bring the model to operate in the appropriate temperature range was then carried out. The results showed that with the battery cell operating at a discharge current of 3 C, velocity higher than 2 m s−1 was sufficient for the battery module to operate at the maximum temperature (Tmax) and maximum temperature difference (∆Tmax ) of 306.69 K and 4.84 K, respectively without consuming much fan power.
This paper explores the application of first integrals in constructing Lyapunov functions for stability analysis of dynamical systems in stochastic domains. A key advantage of using first integrals is their ability to embed system-specific structural and physical information, distinguishing the resulting Lyapunov functions from generic positive definite functions with no intrinsic connection to the system. However, since first integrals do not inherently satisfy Lyapunov conditions, additional constraints—often with direct physical interpretations—must be introduced to ensure positive definiteness and suitable monotonic behavior. The method is demonstrated on three mechanical systems subjected to parametric noise: a nonlinear aeroelastic single-degree-of-freedom oscillator, a spherical pendulum with two first integrals, and a gyroscope with three first integrals.
Flutter, a self-excited oscillation due to energy transfer from the flow to the structure, can cause catastrophic failures in many aerospace structures if uncontrolled. Mostly, predictions of flutter states rely on model-based evaluations under restrictive conditions, such as constant Mach numbers and altitude, which are challenging to replicate outside laboratories. To counter this problem, we investigated flutter prediction using artificial intelligence, specifically long short-term memory (LSTM) neural networks on dynamically varied operational data to simulate real-world conditions. A novel test rig of wing model in a closed circular wind tunnel with controlled airflow velocity was used for flutter simulations under variable conditions. Hundreds of vibration records, captured at critical trigger levels, formed a robust dataset for flutter classification and prediction. Average divergence and Lyapunov largest exponent methods were used to classify stability and chaos in the system, which provided valuable input data for training artificial intelligence. Analysis of results demonstrated the efficacy of neural networks in rapidly identifying flutter onset, which could contribute to advancements in flutter monitoring airborne structures under diverse operational conditions.
We present an open-source Python library for simulating two-dimensional incompressible Kelvin-Helmholtz instabilities in stratified shear flows. The solver employs a fractional-step projection method with spectral Poisson solution via Fast Sine Transform, achieving second-order spatial accuracy. Implementation leverages NumPy, SciPy, and Numba JIT compilation for efficient computation. Four canonical test cases explore Reynolds numbers 1000–5000 and Richardson numbers 0.1–0.3: classical shear layer, double shear configuration, rotating flow, and forced turbulence. Statistical analysis using Shannon entropy and complexity indices reveals that double shear layers achieve 2.8× higher mixing rates than forced turbulence despite lower Reynolds numbers. The solver runs efficiently on standard desktop hardware, with 384×192 grid simulations completing in approximately 31 minutes. Results demonstrate that mixing efficiency depends on instability generation pathways rather than intensity measures alone, challenging Richardson number-based parameterizations and suggesting refinements for subgrid-scale representation in climate models.
In this paper, we present a three-dimensional multiphase fluid lattice Boltzmann model based on the phase-field theory. The conservative Allen-Cahn equation was used to describe the interface dynamics between two different fluids. The proposed model extends the model proposed in [Fakhari et al., Physical Review E 96 (2017) No. 053301] to three space dimensions and we show how to improve the accuracy of the model at high density ratios by computing gradients more accurately. We also propose an accurate method for implementing the three-phase contact angle on curved boundaries. Several benchmark test cases have been performed with realistic parameters for a water-air system to demonstrate the improvement in accuracy of our model, compared to existing methods. Specifically, flow in a cylindrical capillary has been simulated and the results have been compared to previous methods and analytical solutions.
In European railways, the use of UIC draw gear and side buffers to connect individual railway vehicles within a train is still established. The buffers ensure the transmission of longitudinal compressive forces between the adjacent vehicles; longitudinal tensile forces are transmitted by means of the UIC draw gear, a drawbar hook and a screw coupling. Therefore, the stiffness characteristics of the draw and buffing gear are important from the point of view of longitudinal train dynamics, as well as running safety. This paper deals with the stiffness characteristics of railway buffers. The basic requirements for suspension elements used in the buffers are summarised. The solution of tasks in the field of modelling of dynamic phenomena during train running requires knowledge of the dynamic stiffness characteristics of these elements, which, however, are not determined by default. Therefore, experimental measurements of these characteristics were made on the dynamic test stand of the Faculty of Transport Engineering of the University of Pardubice. The experience from the evaluation of these measurements is summarised in the paper. Furthermore, attention is paid to the development of a new computational model of the buffers for use in multibody simulations, considering the results of the physical tests
Understanding crack propagation in heterogeneous materials is crucial for predicting the reliability and durability of structural components. In this study, we investigate the influence of material heterogeneity on mode III crack growth using a phase-field model. The phase-field method offers a powerful computational framework for simulating crack initiation, propagation, and branching without explicitly tracking the crack surface. By incorporating material heterogeneity into the phase-field model, we aim to analyze how variations in material properties affect the material’s strength and crack path behavior. The numerical simulations will explore complex interactions between cracks and microstructural features, providing insights into how heterogeneity influences fracture mechanics at different length scales. Through this research, we seek to enhance the understanding of crack growth in realistic materials and contribute to developing strategies for optimizing the performance and reliability of engineering structures subjected to mechanical loading. In this study, we utilize the Weibull distribution function to generate heterogeneous materials and calculate the crack propagation problem using the adaptive finite element method. The adaptive mesh method provides precise results and can significantly reduce computation time.
In the current paper, we investigate the effect of spin slip conditions for the Couette-Poiseuille flow of a couple stress fluid between two parallel plates. In the study, the motion of the fluid is considered to be steady, incompressible and unidirectional. At the interface between the fluid and the plates (both the upper and lower), we consider the non-zero tangential and couple stress spin slip relationships as boundary conditions. We present analytical expressions for the velocity profile, volume flow rate, vorticity, and couple stresses. This paper discusses the numerical influence of the spin slip parameter, velocity slip parameter, couple stress parameter, and pressure gradient on the velocity, vorticity, couple stresses, and volume flow rate. Our results show that the presence of the spin slip parameter reduces the velocity, couple stress and volume flow rate of the fluid, while it enhances the vorticity. The limiting cases for each problem align well with previously published results regarding the vanishing of couple stresses at the boundaries. This research helps both researchers and engineers in understanding how to control the conditions to achieve an efficient fluid flow, particularly in applications involving couple stress effects, such as microfluidics systems, lubrication technology, and polymeric suspensions.
Detached eddy simulation (DES), delayed DES (DDES) and improved DDES (IDDES) hybrid RANS-LES turbulence models based on the Menter's Shear Stress Transport (SST) model as well as the DES variant of the Kok's Turbulent/Non-Turbulent model (TNT), Extra-Large Eddy Simulation (X-LES), and its newly proposed delayed and improved delayed variants (DX-LES and IDX-LES) along with the base RANS methods are compared in this paper. The comparison is made on a flow around tandem cylinders, on which mainly hybrid methods based on the one-equation Spalart-Almaras model were previously tested. The proposed models show DDES and IDDES with a different approach from the SST-based two-equation methods, which potentially improves the results and, in the case of the TNT-based DDES variant, only the blending function is dependent of the distance from the wall.
The prime goal of the study is to investigate the relevance of torsional surface wave propagation in a thermally conducting heterogeneous (functionally graded) semi-infinite medium. The closed form of the dispersion equation for the propagation of torsional waves in heterogeneous elastic media has been established by assuming equations of motion in the temperature field with proper boundary conditions. One particular case where torsional vibration generates wave propagation in homogeneous materials has been addressed, and therefore, dispersion equation has been developed. The phase velocity and attenuation coefficient in both homogeneous and heterogeneous half-space have been computed to demonstrate the wave properties. In order to investigate the functionally graded parameter associated with the elastic medium, the effects of heat flow components related to thermodynamic forces, and the coupling coefficient related to the deformation and temperature fields, numerical calculations with graphical interpretation have been performed separately for phase velocity and attenuation coefficient.
Quantifying the reliability indices of structures under earthquake loading is traditionally considered to be challenging, especially when the nonlinear structural behaviour needs to be considered. With the increasing popularity of high-performance computer clusters, it is feasible to use detailed numerical procedures to quantify seismic safety margins of steel moment resisting frame (SMRF) structures under various sources of uncertainties. Two seismic reliability methods are used to examine the interaction of uncertainty from ground motions and intensity. One is a numerical integration procedure for the traditional method. The other is the Monte Carlo simulation. These methods produce cumulative probability distribution curves that can retain the accuracy of results from nonlinear dynamic analysis. These methods are applied to two SMRF structures to investigate their probabilistic behaviour with their uncertainties from earthquake loads and seismic weights. The global reliability indices of the structures are found to be between 2.5 and 2.1 under the maximum considered earthquake (MCE). When an MCE occurs, the conditional reliability indices of the structures range between 1.4 and 1.0. The results indicate that both methods can be used to accurately quantify the reliability of SMRF structures. The results also show that some conditional probability distributions may not be well-represented by simple equations with their parameters calibrated from data-fitting techniques. The results also prove that the discussed methods and numerical procedures can be further used to accurately quantify probabilistic seismic behaviour of other structures toward the community resilience.
The present study unveils research that examines the laminar motion of water-infused nanofluid comprised of nanoparticles of TiO2 (titanium dioxide), Ag (silver), and Cu (copper) over a stretching sheet. The flow undergoes a novel slip condition based on Thomson and Troian to model complex fluid behavior near solid walls and incorporate the Darcy-Forchheimer model to comprehensively analyze the influence of a porous medium on flow behavior. Moreover, a heat source/sink and radiation are included to ensure the outcome of the energy equation will resemble most actual-world applications. Partial differential equations (PDEs) of higher order, originally used to describe the system are then reformulated into higher-order non-linear ordinary differential equations (ODEs) by taking symmetry variables that are chosen thoughtfully. The resulting boundary layer equations are then turned into a set of ODEs by implementing relevant similarity transformations, which can be solved using the M ATLAB function bvp4c. Through graphs, the variations in the velocity, Nusselt number, temperature, and skin friction coefficient were displayed. The outcome showed that the incorporation of silver nanoparticles (0.01–0.03) enhanced the skin friction coefficient by ≈ 1.68 % and the Nusselt number reduced up to ≈ 5 %. The Forchheimer number also reported a 6.5% enhancement and 1.5% reduction in the skin friction coefficient and the Nusselt number, respectively. The velocity slip parameter γ1 correlates with an upswing in temperature and skin friction coefficient for the ternary nanofluid while observing a decline in the velocity and Nusselt number.
