Modelling

The active or adjustable journal bearings are designed with unique mechanisms to reduce the rotor-bearing system lateral vibrations by adjusting their damping and stiffness. The article provides a comprehensive review of the literature, outlining the structure and findings of studies on active bearings. Over the years, various kinds of adjustable bearing designs have been developed with unique operational mechanisms. Such bearing designs include adjustable pad sectors, externally adjustable pads, active oil injection through pad openings, and flexible deformable sleeves. These modifications enhance the turbine shaft line’s performance by increasing the system’s overall stability. The detailed review in this paper highlights the characteristics of bearings, along with the key advantages, limitations, and potential offered by active control across different bearing types. The efficiency of any rotor system can be greatly enhanced by optimally selecting the adjustable bearing parameters. These adjustable bearings have demonstrated a unique capability to modify the hydrodynamic operation within the bearing clearances. Experimental studies and simulation approaches were also utilized to optimize bearing geometries, lubrication regimes, and control mechanisms. The use of advanced controllers like PID, LQG, and Deep Q networks further refined the stability. The concluding section of the article explores potential avenues for the future development of active bearings. Full article

In this article, we study a directed version of Douglas–Rachford splitting method in real Hilbert spaces. By using new, self-contained, and simplified techniques, we prove its weak convergence. The major innovation is that we exploit the firm non-expansiveness of the Douglas–Rachford operator for the first time to derive the best possible upper bounds on direction factors, assuming that the involved factors remain constant. We give a new rare feature selection model equipped with the TripAdvisor hotel-review dataset. Numerical results confirm the user-friendliness and efficiency of directed Douglas–Rachford splitting in solving this model. Full article

Unmanned surface vehicles (USVs) have great application prospects in defense, environmental surveillance and offshore energy due to their cost-effectiveness and long-duration mission ability. The structural safety issues induced by the prolonged cyclic wave loading on such small-sized marine structures, such as fatigue failure mechanism, represent an important research topic. In order to characterize the loading process, a piston-type numerical wave flume with wave absorption setting is constructed using the Arbitrary Lagrangian Eulerian (ALE) formulation, and the fluid–structure interaction (FSI) simulations are performed. Simulated wave profiles are measured and compared with corresponding analytical wave solutions to verify the accuracy of target waves. The wave absorption effect is verified by comparing the velocities of water particles in different water regions. Then, different impact scenarios are performed by applying a range of the applicable target waves. Simulated wave forms, impact scenes along with the computed wave load data are presented, and the impact process is analyzed. As a result, the FSI simulations demonstrate cyclic loading characteristics of small-sized floating structures subjected to wave impacts, and the constructed ALE numerical wave flume possesses the extensibility for the simulation of nonlinear water wave impact scenarios. Full article

Meso-scale combustors face persistent challenges in sustaining stable combustion and efficient heat transfer due to high surface-to-volume ratios and attendant heat losses. In contrast, larger outlet diameters exhibit weaker recirculation and more diffused temperature zones, resulting in reduced combustion efficiency and thermal confinement. The behavior of non-premixed flames in meso-scale combustor has been investigated through a comprehensive numerical study, utilizing computational fluid dynamics (CFD) under stoichiometric natural gas (methane)–air conditions; three outlet configurations (6 mm, 8 mm, and 10 mm) were analysed to evaluate their impact on temperature behaviour, vortex flow, swirl intensity, and central recirculation zone (CRZ) formation. Among the tested geometries, the 6 mm outlet produced the most robust central recirculation, intensifying reactant entrainment and mixing and yielding a sharply localised high-temperature core approaching 1880 K. The study highlights the critical role of geometric parameters in governing heat release distribution, with the 6 mm configuration achieving the highest exhaust temperature (920 K) and peak wall temperature (1020 K), making it particularly suitable for thermoelectric generator (TEG) integration. These findings underscore the interplay between combustor geometry, flow dynamics, and heat transfer mechanisms in meso-scale systems, providing valuable insights for optimizing portable power generation devices. Full article

Numerical simulation of metal forming processes is finding increasingly wide applications in advanced industry for the optimization of material processing conditions and prediction of process parameters, finally delivering a reduction of production costs. This work presents a comparison between simulation results of radial shear rolling (RSR) of VT3-1 titanium alloy (Ti-Al-Mo-Cr-Fe-Si) and results of experimental RSR at 1060 °C, 980 °C, and 900 °C in one, three, and five passes, respectively. The digital model (DM) demonstrates a high convergence of the calculation results (calculation error of less than 5%) with the actual geometric parameters of the experimental bars, their surface temperature, and rolling time during the experiment, which indicates a good potential for its application in the selection of deformation modes. Based on the simulation and experimental data, the conditions providing for the formation of differently sized grains in the bar cross-section have been identified. All of the as-rolled bars exhibit a gradient distribution of macrostructure grain size number (GSN), from the smallest one at the bar surface (2–4) to the greatest one in the center (4–6). The macrostructure GSN correlates with the workpiece temperature, which is the highest in the axial zone of the bars, and with the experimentally observed high plastic strain figures in the surface layers. It was found that, depending on the temperature conditions and reduction ratio per pass, any minor change in the values of process parameters can lead to the formation of macrostructures with different grain size numbers. Full article

The identification of interdependent edges plays a critical role in improving information propagation efficiency and enhancing network robustness in interdependent networks. However, existing methods exhibit significant limitations when identifying interdependent edges between networks with substantial differences in edge density. This paper proposes a greedy module matching-based method for sparse interdependent edge identification in similar-order heterogeneous networks. The method utilizes degree entropy and betweenness centrality as node characteristic values for sparse and dense networks, respectively. It first leverages structural differences between sparse and dense networks to determine the upper bound of interdependent edges. Then, a clustering algorithm is employed to identify modules in both networks that align with the estimated number of interdependent edges. Finally, a greedy algorithm is applied to infer interdependent edges between sparse and dense networks. The proposed method is validated using synthetic networks and power-communication networks, with network robustness and connection efficiency as evaluation metrics. Additionally, further validation is conducted through applications in problem–answer networks. Experimental results demonstrate that the proposed approach significantly improves the prediction of sparse interdependent relationships in heterogeneous complex networks and has broad applicability across multiple domains. Full article

Pile foundations are widely used to support offshore wind turbines. While the p-y curve method is adopted for analysis of pile–soil interactions in popular design specifications, including the American Petroleum Institute (API), its accuracy remains unassessed systematically and quantitatively. This study established a database by collecting 491 sets of pile p-y curves from multiple offshore wind turbine projects. The database was used to statistically evaluate the accuracy of the API p-y curve method for cohesionless soils. The model accuracy is represented by a model factor defined as the ratio of measured to predicted values of soil resistance around the pile. The results showed that accuracy assessment using the field data is significantly different from that using the laboratory model test data. On average, the API p-y curve method overestimates the true soil resistance in the field by about 30%, but underestimates that in the laboratory by about 8%. The dispersions in prediction accuracy of both cases are high. Correction terms are introduced to calibrate the current API p-y curves. The calibrated API methods were shown to be accurate in general and medium dispersive in prediction accuracy. Last, the model factors for the current and calibrated API methods were demonstrated to be lognormal random variables. Full article

We present a simple algorithm for synthesizing volumetric 3D puzzles from a 3D freeform geometric model represented volumetrically as trivariate NURBs functions, $\mathcal{M}$. The construction algorithm is based on the functional composition of puzzle elements, positioned in the domain of $\mathcal{M}$, with $\mathcal{M}$. The puzzle elements can be (heterogeneous) freeform polygonal models or freeform surface or trivariate functions and of arbitrary shape, and can include added joints to neighboring puzzle elements. The proposed approach is demonstrated via several examples of such volumetric puzzles, 3D printed and assembled. Full article

The solid electrolyte interphase (SEI) is a passive layer, typically a few hundred angstroms thick, that forms on the electrode surface in the first few battery cycles when the electrode is in contact with the electrolyte in lithium-metal batteries. Composed of a combination of lithium salts and organic compounds, the SEI plays a critical role in battery performance, serving as a channel for Li-ion shuttling. Its structure typically comprises an inorganic component-rich sublayer near the electrode and an outer organic component-rich sublayer. Understanding heat transport through the SEI is crucial for improving battery pack safety, particularly since the Li-ion diffusion coefficient exhibits an exponential temperature dependence. This study employs first-principles calculations to investigate phonon-mediated temperature-dependent lattice thermal conductivity across the inorganic components of the SEI, including, LiF, Li₂O, Li₂S, Li₂CO₃, and LiOH. This study is also extended to the dependence of the grain size on thermal conductivity, considering the mosaic-structured nature of the SEI. Full article

The Kolmogorov–Arnold network (KAN) is a regression model that is based on a representation of an arbitrary continuous multivariate function by a composition of functions of a single variable. Experimentally obtained datasets for regression models typically include uncertainties, which in some cases, cannot be neglected. The conventional way to account for the latter is to model confidence intervals of the systems’ outputs in addition to the expected values of the outputs. However, such information may be insufficient, and in some cases, researchers aim to obtain probability distributions of the outputs. The present paper proposes a method for estimating probability distributions of the outputs by constructing an ensemble of models. The suggested approach covers input-dependent probability distributions of the outputs and is capable of capturing the multi-modality, as well as the variation of the distribution type with the inputs. Although the method is applicable to any regression model, the present paper combines it with KANs, since their specific structure leads to the construction of computationally efficient models. The source codes are available online. Full article

A novel right-sidewall gas blowing method is proposed to improve the flow behavior in a single-strand tundish. Despite advances in tundish flow control, the impact of slag layers and sidewall gas injection on flow dynamics and tracer transport remains underexplored. This study combines 1:3.57 scale water model experiments and Compuational Fluid Dynamics (CFD) simulations to investigate the effects of gas injection heights (50 mm and 100 mm) on flow structure, mixing efficiency, and slag layer interactions. Particle Image Velocimetry (PIV) and the stimulus-response method are used for quantitative validation. Results show that sidewall gas blowing suppresses short-circuit flow, increases average residence time by up to 37%, and reduces dead zone volume by up to 19%. The 50 mm blowing height induces stronger surface turbulence, while the 100 mm height improves flow uniformity. The presence of a slag layer significantly dampens surface fluctuations and alters vortex formation. These findings fill a critical research gap in tundish metallurgy and offer a practical reference for optimizing gas blowing strategies in industrial applications. Full article

In this paper, a switched model for DC-DC boost converters with modeling uncertainty is considered. Based on the switched model, a continuous switching control law is first designed to guarantee the robust stability of the closed-loop system. Then, to reduce the data transmission amount and ease the communication burden, a sampled-data switching control law is explored, where the switching action is executed based on a state-dependent condition at each sampling time. The proposed control strategies can track a specific reference point and varying reference points in the presence of modeling uncertainty. Finally, the simulation results show that the proposed sampling switch control reduces steady-state errors and the transient response is significantly smoother. These results confirm the effectiveness and practical potential of the proposed approach. Full article

Traditional median filtering with a fixed window easily leads to edge blurring and adaptive median filtering requires manual presetting of the maximum window parameter and has insufficient retention of details when dealing with high-density salt-and-pepper noise. Aiming at these problems, this paper proposes a hybrid decision-making adaptive median filtering algorithm with dual-window detection in collaboration with particle swarm optimization (PSO). The algorithm quickly locates suspected noise points through a 3 × 3 small window and enhances noise identification accuracy by using a PSO dynamically optimized 5–35-pixel large window. Meanwhile, a hybrid decision-making mechanism based on local statistical properties was introduced to dynamically select median filtering, weighted average based on spatial distance, or pixel preservation strategy to balance noise suppression and detail preservation, and the PSO algorithm was used to automatically find the optimal parameters of the large window’s size to avoid the manual parameter-tuning process. Experiments were conducted on standard grayscale and color images and compared with four traditional methods and two more advanced methods. The experiments showed that the algorithm improved the peak signal-to-noise ratio (PSNR) value by 2–4 dB and the structural similarity index measure (SSIM) metric by 0.05–0.2 under high salt-and-pepper noise density compared with the traditional methods, which effectively improved the contradiction between noise suppression and detail retention in traditional filtering algorithms and provided a highly efficient and intelligent solution for image denoising in high-noise scenarios. Full article

In this paper, a predator–prey model with hunting cooperation and maturation delay is studied. Through theoretical analysis, we investigate the existence of multiple stability switches of the positive equilibrium. By applying Hopf bifurcation theory, the conditions for Hopf bifurcation are derived, indicating the emergence of periodic solutions as the maturation delay passes through critical values. Utilizing center manifold theory and normal form analysis, we determine the stability and direction of the bifurcating orbits. Numerical simulations are performed to validate the theoretical results. Furthermore, the simulations vividly demonstrate the appearance of period-doubling bifurcations, which is the onset of chaotic behavior. Bifurcation diagrams and phase portraits are employed to precisely characterize the transition processes from a stable equilibrium to periodic, period-doubling solutions and chaotic states under different maturation delay values. The study reveals the significant influence of maturation delay on the stability and complex dynamics of predator–prey systems with hunting cooperation. Full article

This study conducts numerical analysis of fatigue crack propagation in deck-rib welded joints of orthotropic steel decks (OSDs) using linear elastic fracture mechanics. The stress intensity factor for central surface cracks under constant range bending stress is calculated, and single and multi-crack propagation are simulated by a numerical integration method. The research results show that deck geometry critically influences crack propagation behavior. Wider decks accelerate propagation of cracks after the crack depth exceeds half the deck thickness, thicker decks exhibit linearly faster propagation rates yet retain larger residual section to bear loads, and increased weld penetration reduces fatigue life. Initial defects rapidly converge to a preferred propagation path, stabilizing near $a_f/c_f\approx 0.1$ ($a_f$ is the failure crack depth and $c_f$ is the half surface crack length) regardless of initial aspect ratio. For multi-crack scenarios, defect density dominates merging, doubling density increases final cracks by 45%. Merged cracks adhere closely to the single-crack path, while total section loss escalates with defect density and deck thickness but remains stress range independent. The identified convergence preferred propagation path enables depth estimation from surface-length measurements during real bridge inspections. Full article

In three-dimensional (3D) logistics environments, finding optimal paths for unmanned aerial vehicles (UAVs) is challenging due to positioning inaccuracies that require ground-based corrections. These inaccuracies are exacerbated in harsh environments, leading to a significant risk of correction failure. This research proposes a multi-objective mixed integer programming model (MILP) that transforms dynamic uncertainties into binary constraints, utilizing a hierarchical sequencing strategy in the Gurobi optimizer to efficiently identify optimal paths. Our simulations indicate that achieving an 80% mission success probability necessitates an optimal path of 104,946 m with nine corrections. For a 100% success rate, the path length increases to 105,874 m, with corrections remaining constant. These results validate the model’s effectiveness in navigating environments with probabilistic constraints, highlighting its potential for addressing complex logistical challenges. Full article

In weak carbonate rock masses, small-sized karst features ranging from greater than 2 cm to over 1 m in diameter can significantly compromise slope stability, yet they are often overlooked in traditional geotechnical models. This study employs the equivalent porous medium (EPM) approach to incorporate these small-sized voids into two-dimensional finite element slope stability analysis using RS2 software (Version 11.022). By treating the matrix of karst hollows as a porous continuum, we simulate the mechanical and hydraulic influence of their presence on pit slope performance. Results show that even small voids substantially reduce the factor of safety, with destabilization intensifying as void density and pore fluid infiltration increase. Distinct failure mechanisms—including circular sliding, localized subsidence due to cavity collapse, and rockfalls from intersecting shear planes—emerge from the simulations. The stress trajectories and yield elements highlight how minor voids influence the distribution and initiation of shear and tensile failures. These findings reveal that karst features previously considered negligible can be critical structural discontinuities that trigger failure. The EPM framework thus provides a computationally efficient and mechanistically sound means of modelling the cumulative impact of small-sized karst features, bridging a significant gap in geotechnical design for karst-prone weak rock slopes. Full article

This paper presents the study of the viscoelastic behavior of high-density polyethylene (HDPE) ASTM 4710 pipes under diametral loads. The experimental procedure consists of applying a displacement ramp followed by a stress relaxation stage on six ring specimens extracted from pipes with varying thickness-to-diameter ratios. The proposed methodology combines the Standard Linear Solid Model (SLSM) with beam theory, introduces adjustment equations for estimating SLSM parameters, and discusses the influence of residual stresses induced during pipe manufacturing and cooling. Finally, the paper shows the validation of the modeling approach based on the results of the mechanical response of an independent test case. Full article

This work investigates the effect of sealing grease on inhibiting the leakage of supercritical carbon dioxide (CO₂) using molecular dynamics simulation. Consideration is given to the effects of temperature, pressure, and leakage channel height. It is found that CO₂ primarily leaks by diffusing into the interface between the grease and the channel at low temperatures, but the leakage is dominated by interfacial diffusion and the bulk penetration of CO₂ across the greases at high temperatures. Moreover, the presence of a large amount of supercritical CO₂ at the interface weakens the interactions between the grease and the channel, resulting in the extrusion of greases at high temperatures. For the pressure effect, the leakage always happens through interfacial diffusion with a low or high pressure. The high pressure can cause the extrusion of greases, as CO₂ distributed in both the interface and the grease can enhance its fluidity and make it more likely to be extruded from the channel under high pressure. Finally, leakage primarily involves interfacial diffusion for a small channel height, but it is also dominated by such diffusion and bulk penetrations with a large height, which is due to the boundary effect on the fluidity of greases. Full article