Search Results (686)

In the literature, there is a scarcity of studies examining the combined effects of vortex-induced vibrations (VIV) and surface roughness on a bluff body. This paper contributes to the limited studies and literature on VIV by highlighting the pronounced influence of roughness on the vortex formation modes of a circular cylinder forced to oscillate with respect to the freestream. The numerical approach utilizes a purely Lagrangian description through the discrete vortex method with a roughness model. Recent results obtained by our research group have shown that a two-dimensional roughness model is more sensitive than a simple turbulence model in capturing nonlinear multi-physics phenomena with a variety of applications in different engineering areas. In particular, the control of drag force and vortex shedding frequency can be studied based on the expected physics of viscous flow. In the present paper, the dimensionless oscillation amplitude is fixed at A/D = 0.13 (D is the outer cylinder diameter), and the cylinder forcing frequency varies in the range of 0.04 ≤ f_o ≤ 0.80 at a high Reynolds number value of Re = 1.0 × 10⁵. Three relative roughness sizes are chosen, i.e., ε/D = 0.001, 0.0045, and 0.007 (ε is the average roughness). The test cases without roughness effects are compared to experimental visualizations to capture two basic anti-symmetrical modes, namely the A-I and A-IV modes, the symmetric S-I (Type-I) mode, and the Chaotic mode categorized as C-I. Our strategy to identify these wake modes verifies the synchronization between the vortex shedding frequency f_CD, interpreted from temporal history of the drag force on an oscillating cylinder, and the body forcing frequency. In the test cases using the roughness model, it is possible to identify a desynchronization between the frequencies f₀ and f_CD as well as significant variations in the drag force. The roughness effect also provokes a regime of vortex formation, here classified as “A-IV mode with coalescence”. Full article

Ice accretion alters the airfoil profile of the unmanned aerial vehicle (UAV), degrading the aerodynamic performance and potentially triggering safety incidents. The computation of droplet impingement characteristics is the primary task for ice accretion analysis and the design of anti-icing/de-icing systems for UAVs. To address the disadvantages of the conventional Eulerian method and the Lagrangian method, a streamline-based Eulerian method is established to obtain the droplet impingement characteristics. It only solves the momentum equation to derive the velocity field, eliminating the computational load of the droplet continuity equation. Droplet streamlines are generated via backward integration in the droplet velocity field, allowing impingement characteristics to be calculated. In this scheme, the droplet collection efficiency is computed without the predetermination of droplet release locations or tracking a large number of droplet trajectories. The proposed method is applied to obtain the droplet collection efficiencies in the cases of an NACA0012 airfoil, a two-dimensional (2D) cylinder, an MS (1)-0317 airfoil, and an RG-15 airfoil. The results show good agreement with the data in the literature; therefore, the feasibility and effectiveness of this streamline-based Eulerian method are confirmed. This work can provide a reference for ice accretion analysis and anti-icing/de-icing system design for UAVs. Full article

This paper presents a roughness surface model for Lagrangian simulations that interacts with both temperature and vorticity fields. The chosen problem is the uniform flow around a rough circular cylinder heated with constant temperature under mixed convection. The methodology used is the Temperature Particles Method (TPM), in which both vorticity and temperature fields are discretized in particles to simulate the real flow in a purely Lagrangian form. The simulation is computationally extensive due to the application of the Biot–Savart law for the two fields and the calculation of buoyancy forces, which is alleviated by the use of parallel programming with OpenMP. The simulation of roughness effects for both fields is obtained using a Large Eddy Simulation (LES) model for vorticity, based on the second-order velocity structure function, which is correlated with the thermal diffusivity through the turbulent Prandtl number. In general, the results indicate that roughness increases the drag coefficient, while an increase in the Richardson number reduces this coefficient. Full article

Sediment erosion is a persistent problem that leads to the deterioration of hydro-turbines over time, ultimately causing blade failure. This paper analyzes the dynamics of sediment in water and its effects on a small Kaplan turbine. Flow data is obtained independently and transferred to a separate Lagrangian-based finite element code, which tracks particles throughout the computational domain to determine local impacts and erosion rates. This solver uses a random walk approach, along with statistical descriptions of particle sizes, numbers, and release positions. The turbine runner features significantly twisted blades with rounded corners, and complex three-dimensional (3-d) flow related to leakage and secondary flows. The results indicate that flow quality, particle size, concentration, and the relative position of the blades against the vanes significantly influence the distribution of impacts and erosion intensity, subsequently the local eroded mass is cumulated for each element face and averaged across one pitch of blades. At the highest concentration of 2500 mg/m³, the results show a substantial erosion rate from the rotor blades, quantified at 4.6784 × 10⁻³ mg/h and 9.4269 × 10⁻³ mg/h for the nominal and maximum power operating points, respectively. Extreme erosion is observed at the leading edge (LE) of the blades and along the front part of the pressure side (PS), as well as at the trailing edge (TE) near the hub corner. The distributor vanes also experience erosion, particularly at the LE on both sides, although the erosion rates in these areas are less pronounced. These findings provide essential insights into the specific regions where protective coatings should be applied, thereby extending the operational lifespan and enhancing overall resilience against sediment-induced wear. Full article

We investigate the potential of extreme mass ratio inspirals (EMRIs) as probes of strongly interacting dark matter (SIDM) spikes around supermassive black holes. Based on Lagrangian formulations of dark matter self-interactions, we analyze the effects of number changing processes, such as $2\to 0$ annihilation and $3\to 2$ scattering, on the inner density profiles, and propose a generalized definition of the dissolution radius, including its dependence on the central black hole mass. Building on this framework, we construct dark matter spike models suitable for phase shift calculations and study the gravitational waves of EMRIs under the circular orbit adiabatic approximation. Our analysis shows that different interaction mechanisms produce distinct dark matter density distributions, resulting in characteristic phase differences in the gravitational waveforms. The magnitudes of these phase shifts are well above the resolution threshold of space-based detectors. We conclude that future missions, such as LISA, will be able to distinguish different SIDM interaction channels through precise waveform measurements, thereby opening a new avenue for probing the microphysics of dark matter in extreme astrophysical environments. Full article

The material point method (MPM) has shown significant potential for simulating problems involving large deformations. However, many implicit MPM formulations based on the traditional Updated Lagrangian (UL) scheme still face challenges in terms of computational stability. In this study, we propose a novel Lagrangian equilibrium formulation for an implicit MPM that is tailored to large-deformation problems. (1) The previously converged state is utilized to simplify stiffness matrix computations, thereby improving the stability of the algorithm. (2) The framework supports a variety of high-order interpolation functions, which effectively mitigate numerical artifacts such as cell-crossing errors. (3) The B-bar technique is further incorporated to suppress spurious stress oscillations in the incompressible limit. The proposed method is validated through two classical benchmark tests, the simple shear of a single element and the cantilever beam problem, by comparing the simulation results with analytical solutions and alternative numerical approaches. Finally, its capability is demonstrated in slope stability and strip footing analyses, confirming the superior accuracy, stability, and robustness of the method for large-deformation elastoplastic problems. Full article

In offshore jack-up operations, it is common to reinstall spudcans close to existing footprints, which could result in asymmetric soil distribution and potential instability risks. This study investigates the mechanical behavior and stability of spudcans during reinstallation, focusing on the influence of footprint geometry, spudcan type, and offset distance. The coupled Eulerian–Lagrangian (CEL) method in ABAQUS is utilized together with soil strength reduction to assess stability. Both single-factor and orthogonal experimental designs are employed to systematically evaluate parameter effects. Results show that the footprint diameter has a greater impact than the depth, increasing the peak horizontal force by 33.4% and the moment by 10.9% due to enhanced soil asymmetry. Rectangular spudcans with tapered bases generate twice the vertical resistance and exhibit 8.8% smaller lateral displacements compared to circular spudcans. Offset distance significantly affects reinstallation performance, with adverse conditions occurring at 0.5 times the diameter of the spudcan. Orthogonal analysis further confirms that the offset distance has the greatest influence among the factors studied. These findings emphasize the necessity of considering footprint geometry, spudcan design and positioning to ensure safe and stable reinstallation, and provide guidance for engineering design and risk assessment of repeated spudcan operations. Full article

The guest room and aisle of electric high-speed maglev train must be shielded from leakage magnetic flux produced by superconducting strong magnetic field. To reduce magnetic leakage, the superconducting magnetic levitation system structure is obtained by extended lagrangian optimization method. The optimized superconducting coil structure has the advantages of reducing magnetic leakage, improving magnetic field utilization, reducing the weight of the magnetic isolation plate and the weight of the maglev train, and enhancing the load-bearing capacity of the maglev train. Based on optimized superconducting coil parameters for high-speed maglev, the magnetic shielding effect at the aisle and the guest room, the magnetic flux density distribution at the magnetic shielding is calculated and analyzed through analytical calculation. The relevant conclusions indicate that the magnetic suspension structure has the advantages of reducing end coil leakage flux and the weight of the high-speed maglev train. Full article

Suction embedded plate anchors are widely used in deepwater mooring systems, which can withstand significant vertical loading. During the installation, the mooring chain is tensioned and causes the anchor to rotate, which is known as keying. With a large deformation finite element approach of the coupled Eulerian–Lagrangian method, the chain effects are incorporated into the keying of suction embedded plate anchors. The effectiveness of the proposed method is verified by numerical results and centrifuge tests. The numerical study reveals that the installation angle of the chain has a significant effect on the loss of embedment, especially combined with the effects of load eccentricity and soil strength. The losses of embedment are 0.024~0.273 and 0.217~1.755 anchor width for the installation angles of 15° and 90°, respectively. The ultimate bearing capacity factor decreases with the increasing of load eccentricity and soil strength, because a cavity is formed at the anchor back. Empirical formulae are finally developed for engineers to rapidly estimate the embedment loss and ultimate pullout capacity of suction embedded plate anchors. Full article

Lagrangian Relaxation (LR) is an effective method for solving spatial optimization problems in geospatial analysis and GIS. Among others, it has been used to solve the classic p-median problem that served as a unified local model in GIS since the 1990s. Despite its efficiency, the LR algorithm has seen limited usage in practice and is not as widely used as off-the-shelf solvers such as OPL/CPLEX or GPLK. This is primarily because of the high cost of development, which includes (i) the cost of developing a full gradient descent algorithm for each optimization model with various tricks and modifications to improve the speed, (ii) the computational cost can be high for large problem instances, (iii) the need to test and choose from different relaxation schemes, and (iv) the need to derive and compute the gradients in a programming language. In this study, we aim to solve the first three issues by utilizing the computational power of GPGPU and existing facilities of modern deep learning (DL) frameworks such as PyTorch. Based on an analysis of the commonalities and differences between DL and general optimization, we adapt DL libraries for solving LR problems. As a result, we can choose from the many gradient descent strategies (known as “optimizers”) in DL libraries rather than reinventing them from scratch. Experiments show that implementing LR in DL libraries is not only feasible but also convenient. Gradient vectors are automatically tracked and computed. Furthermore, the computational power of GPGPU is automatically used to parallelize the optimization algorithm (a long-term difficulty in operations research). Experiments with the classic p-median problem show that we can solve much larger problem instances (of more than 15,000 nodes) optimally or nearly optimally using the GPU-based LR algorithm. Such capabilities allow for a more fine-grained analysis in GIS. Comparisons with the OPL solver and CPU version of the algorithm show that the GPU version achieves speedups of 104 and 12.5, respectively. The GPU utilization rate on an RTX 4090 GPU reaches 90%. We then conclude with a summary of the findings and remarks regarding future work. Full article

6G low-power and lossy network (6G LLN) is a kind of distributed network designed for IoT and edge computing scenarios of the sixth-generation mobile communication technology. Its routing technologies should fully consider characteristics of green and low carbon, constrained nodes, lossy links, etc. This paper proposes an improved routing protocol for low-power and lossy networks (I-RPL) to better suit the characteristics of 6G LLN and meet its application requirements. I-RPL has designed new context-aware routing metrics, which include the residual energy indicator, buffer utilization ratio, ETX, delay, and hop count to meet multi-dimensional network QoS requirements. The candidate parent and its preferred parent’s residual energy indicator and buffer utilization ratio are calculated recursively to reduce the effect of upstream parents. ETX and delay calculating methods are improved to ensure a better performance. Moreover, I-RPL has optimized the network construction process to improve energy and protocol efficiency. I-RPL has designed scientific multiple routing metrics evaluation theories (Lagrangian multiplier theories), proposed new rank computing and optimal route selecting mechanisms to simplify protocol, and optimized broadcast suppression and network reliability. Finally, theoretical analysis and experiment results show that the average end-to-end delay of I-RPL is 13% lower than that of RPL; the average alive node number increased 11% and so on. So, I-RPL can be applied well to the 6G LLN and is superior to RPL and its improvements. Full article

Accurate numerical simulations of soil-tire interactions are essential for optimizing agricultural machinery to minimize soil compaction and enhance crop yield. This study developed and compared two approaches for identifying and validating parameters of a LS-Dyna soil model. The laboratory-based approach derives parameters from triaxial, consolidation, and cone penetrometer tests (CPT), while the optimization-based method refines them using in-situ CPT data via LS-OPT to better capture field variability. Simulations employing Multi-Material Arbitrary Lagrangian–Eulerian (MM-ALE), Smoothed Particle Hydrodynamics (SPH), and Hybrid-SPH methods demonstrate that Hybrid-SPH achieves the optimal balance of accuracy (2% error post-optimization) and efficiency (14-h runtime vs. 22 h for SPH). Optimized parameters improve soil–tire interaction predictions, including net traction and tire sinkage across slip ratios from −10% to 30% (e.g., sinkage of 12.5 mm vs. 11.1 mm experimental at 30% slip, with overall mean-absolute percentage error (MAPE) reduced to 3.5% for sinkage and 4.2% for traction) and rut profiles, outperforming lab-derived values. This framework highlights the value of field-calibrated optimization for sustainable agriculture, offering a cost-effective alternative to field trials for designing low-compaction equipment and reducing yield losses from soil degradation. While sandy loam soil at 0.4% moisture content was used in this study, future extensions to different soil types with varied moisture are recommended. Full article

Flexible pipes have significant application potential in deep-sea mineral resource exploitation. As the innermost barrier of flexible pipes, the liner directly withstands abrasive wear from mineral particles. The extrusion quality of the liner is a decisive factor for the service life of the pipe and requires optimization of process parameters for improvement. However, the extrusion process of wear-resistant liners made of ultra-high molecular weight polyethylene (UHMWPE) involves complex thermo-mechanical coupling behavior, which creates major challenges in developing accurate numerical models that represent the entire process. To precisely simulate the extrusion process and guide process parameter optimization, this paper establishes a numerical simulation model for flexible pipe liner extrusion based on the Eulerian–Lagrangian coupling method. Simulations under various outlet temperature and screw speed conditions were carried out to reveal the evolution of mechanical behavior during extrusion and clarify the influence of key process parameters. The main conclusions can be summarized as follows. An increase in extrusion temperature reduces the maximum stress and promotes better molecular orientation and crystallinity in UHMWPE material, while the maximum heat flux remains essentially unchanged. An increase in screw speed has little effect on maximum material stress but leads to a significant increase in maximum heat flux. In addition, significant stress appears in the UHMWPE material at the extrusion die exit and is mainly concentrated in the unextruded material section. The numerical model effectively addresses the challenges of simulating material phase transition, large deformation and long-distance flow, which are difficult to capture with traditional methods. The findings offer a theoretical basis and technical guidance for optimizing extrusion process parameters and strengthening quality control in flexible pipe liner extrusion. Full article

As aviation operations extend into complex natural environments, dust particles present significant challenges to flight stability and safety, particularly in dust-prone regions like southern Xinjiang. This study employs high-fidelity computational fluid dynamics (CFD) simulations, combined with the SST turbulence model and the Lagrangian discrete phase model, to analyze the aerodynamic response of the NACA 0012 airfoil at varying wind speeds (5, 15, and 30 m/s) and angles of attack (3°, 8°, and 12°). The results indicate that, at low speeds and moderate to high angles of attack, dust particles reduce lift by over 70%, primarily due to boundary layer instability, weakened suction-side pressure, and premature flow separation. Higher wind speeds slightly delay flow separation, but cannot counteract the disturbances caused by the particles. At higher angles of attack, drag increases by more than 60%, driven by wake expansion, shear dissipation, and delayed pressure recovery. Pitching moment frequently reverses from negative to positive, reflecting a forward shift in the aerodynamic center and a loss of pitching stability. An increase in dust concentration amplifies these effects, leading to earlier moment reversal and more abrupt stall behavior. These findings underscore the urgent need to improve aircraft design, control, and safety strategies for operations in dusty environments. Full article

As the prevalence of respiratory diseases continues to rise, inhalation therapy has emerged as a crucial method for their treatment. The effective transmission of medications within the respiratory tract is vital to achieve therapeutic outcomes. Given that most inhaled particles carry electrostatic charges, understanding the electrostatic effect on particle behavior in bifurcated tubes is of significant importance. This work combined Large Eddy Simulation-Lagrangian particle tracking (LES-LPT) technology to simulate particle behavior with three particle sizes (10, 20, and 50 μm) from G2 to G3 (“G” stands for generation) in bifurcated tubes, either with or without electrostatics, under typical human physiological conditions (Re = 1036). The results indicate that the electrostatic force has a significant effect on particle behavior in bifurcated tubes, which increases with particle size. Within the bifurcated tubes, the electrostatic force enhances particle movement in alignment with the secondary flow as well as intensifies the interaction of particles with local turbulent vortices and promotes particle dispersion rather than agglomeration. On the other hand, the distribution of the electrostatic field is influenced by particle behavior. Higher particle concentration presents stronger electrostatic strength, which increases with particle size. Therefore, it can be concluded that the electrostatic interactions among particles can prevent particles from aggregating and enhance the efficiency of inhalation therapy. Full article