Blast-induced vibrations from newly constructed tunnels may adversely affect adjacent existing tunnel structures. To ensure the safety of the existing tunnel, it is essential to investigate its dynamic response under blast disturbances. Based on an expansion project for a highway double-arch tunnel, this study employed the dynamic finite element program LS-DYNA to analyze the vibration velocity and effective stress in the tunnel lining subjected to blast vibrations. The distribution characteristics of vibration velocity and effective stress at different locations of tunnel lining were obtained. A relationship model between the peak particle velocity (PPV) and effective stress was established. According to the maximum tensile stress theory, a safety criterion based on vibration velocity was determined. To facilitate field monitoring, a correlation between the vibration velocity at the arch waist and foot was established, leading to a proposed safety threshold for the arch foot vibration velocity. Furthermore, a statistical relationship was developed between the charge weight per hole in the upper bench cut and the vibration velocity at the arch foot to guide blasting design. Using the arch foot vibration velocity as the safety standard, the maximum permissible charge weight to ensure the structural safety of the existing tunnel was recommended.

Subsequent particle impacts during cold spraying significantly influence the deformation and bonding characteristics of previously deposited particles. Due to the small particle size and extremely short deposition duration, experimental investigation of this phenomenon remains challenging. In contrast, numerical simulation offers a feasible approach to capturing minute material changes occurring over extremely brief time intervals. Molecular dynamics (MD) simulation can effectively reproduce the dynamic deformation behavior of materials at the atomic scale under extreme processing conditions and has become an essential tool for analyzing particle deformation and structural evolution during cold spraying. In this study, titanium (Ti) was selected as the spraying material, and an MD-based multiparticle impact model was developed to investigate the deformation and structural evolution of underlying particles subjected to sequential impingement. Furthermore, the synergistic effect of the particle velocity in enhancing this influence was systematically examined. The results demonstrate that under the impact of subsequent particles the bottommost particles undergo continuous deformation in the X, Y, and Z directions, inducing progressive deformation in the substrate. Concurrently, significant atomic intermixing is observed between the bottommost layer and the substrate as well as between the first- and second-layer particles. Stress evolution reveals that repeated impacts lead to continuous stress accumulation in the bottom region, with stress values exhibiting a sustained upward trend, which drives the internal crystal structure to transform into an amorphous phase, and higher particle velocities further accelerate amorphization. Furthermore, dislocations nucleate within high-stress regions and propagate inward progressively. Overall, these findings indicate that successive particle impacts enhance bottom-layer deformation through persistent stress transmission, promoting dislocation generation and structural amorphization, although this effect is gradually attenuated when the fourth layer is deposited. Despite inherent scale limitations in MD simulations compared to real conditions, the results provide valuable insights into the cold spray deposition mechanisms of difficult-to-deform metals.

Proximal Sound Printing (PSP) is a new class of additive manufacturing (AM) processes where on-demand polymerization occurs through ultrasound waves interacting with printing material right at the proximity of the acoustic aperture by inducing cavitation. Despite recent developments in sound-based AM techniques, inherent practical limitations still remain, such as low resolution and repeatability, as well as the inability to print multi-material structures. PSP overcomes these limitations, enhancing resolution tenfold, reducing printing power fourfold, and decreasing maximum acoustic streaming velocity 1600 times compared to common sound-based printing methods, enhancing repeatability and resolution. PSP offers greater versatility than existing methods in modulating feature size through printing aperture tuning. This capability is particularly valuable for fabricating microsystems, where high-resolution patterning and material integrity are essential. Furthermore, PSP enables the direct printing of heat-curing materials such as polydimethylsiloxane (PDMS), a widely used thermoset in microfluidics and soft lithography, without altering its native formulation. The PSP process is explored through sonochemiluminescence experiments and high-speed imaging and demonstrated by the successful printing of multi-material composite structures and functional microfluidic devices. Overall, PSP establishes a practical, high-resolution approach for sound-driven additive manufacturing.

Abstract The density and elastic properties of silicate melts are critical for understanding planetary differentiation and magma ocean dynamics. In this study, we measured the elastic properties of MgSiO3–FeAlO3 glasses with varying FeAlO3 contents (0–40 mol%), which we use as room-temperature analogs for planetary magma ocean melts, to elucidate the effects of Fe and Al on the melt elasticity, density, and viscosity. With increasing FeAlO3 content, glass density and elastic moduli increase, while acoustic velocities decrease. The lower molar volumes observed in Fe-rich glasses are consistent with enhanced elastic modulus and polymerization. We also found that normalized compressibility (∂V/∂P)S increases linearly with the non-bridging oxygen per tetrahedral cation (NBO/T) but decreases with FeAlO3 content. These results demonstrate that variations in glass composition, particularly FeAlO3 content, exert a strong control on physical properties and indicates that analogous compositional effects likely occur in silicate melts, with significant consequences for magma ocean crystallization dynamics.

Nowadays, the manipulation of water droplets has received growing interest in both academia and industry. In the current work, we aim to induce a quick sweep of deposited water droplets upon surfaces using impact nanoparticles. With the help of molecular dynamics (MD) simulations, we observe the dynamic evolution of targeted systems under different conditions. For a small value of particle's size, deposition, wrapped bounce, and separated bounce take place as a progressive increase in particle's velocity. The motion of a particle can be directly captured through obscuring water molecules. Moreover, the mechanisms underlying these different dynamic evolutions have been revealed through calculating kinetic energy, surface energy, and observing snapshots. In addition, we map two phase diagrams with respect to the dimensionless input kinetic energy (Ek, dim), the diameter of the nanoparticle to that of the water droplet (Δ), and the intrinsic wettability of the surface (θsur) to overall investigate these effects and observe all the possible outcomes. This work paves the way to understanding the progress of impingement of nanoparticles on deposited water droplets upon surfaces, which may be a good candidate for rapidly removing deposited water droplets and recovering the hydrophobicity of solid surfaces.

Abstract This study investigates a combined vertical array (CVA) comprising both vector hydrophones and pressure hydrophones, and proposes a CVA-based method for ultra-wideband constant-beamwidth beamforming. Based on the convex optimization strategy, the method is integrated with joint pressure and particle velocity processing to compute the optimized beamforming weight vectors for both the pressure and combined particle velocity channels of the CVA. Then, based on the beamforming weights of the combined particle velocity channel, the placement of vector hydrophones is optimized. Both simulation calculations and sea test processing results show that the CVA provides higher array gain than the pressure-sensor vertical array (PVA), while its beamforming performance closely approaches that of a full vector-sensor vertical array (VVA). Moreover, the CVA significantly reduces the number of array channels, data processing load, and system complexity compared to the VVA.

Understanding and controlling the motion of self-propelled particles in complex fluids is crucial for applications in targeted drug delivery, microfluidic transport, and the broader field of active matter. Here, we investigate the thermophoretic self-propulsion of partially gold-coated polystyrene Janus particles (Au-PS) in temperature-responsive linear poly(N-isopropyl acrylamide) (PNIPAM) solutions across various concentrations and temperatures. Particle velocities are examined at three representative temperatures: room temperature ((21 ± 0.2) °C), (28 ± 1) °C (just below the LCST), and (34 ± 1) °C (above the LCST). Viscosity values of the PNIPAM solutions were found to be close to those of pure water, with no significant shear thinning or other viscoelastic effects observed under relevant experimental conditions. In pure water, Au-PS Janus particles propel with the PS hemisphere leading, driven by their intrinsic thermophoretic response. At low polymer concentrations (0.05 wt%), experiments and theoretical calculations reveal a non-monotonic dependence of particle velocity on temperature, with a maximum near the LCST. In this regime, the positive Soret coefficient of PNIPAM causes the polymer to accumulate near the cooler PS hemisphere, generating a diffusiophoretic drift that can dominate the intrinsic thermophoretic motion and reverse the propulsion direction. Experimentally, the propulsion direction switches from PS-forward to Au-forward between 0.04 wt% and 0.05 wt%, and within the 0.05 wt% solution, a secondary reversal back to PS-forward is observed at higher temperatures, consistent with the weakening of the depletion-induced drift above the LCST. At higher concentrations (0.5 wt% and 1 wt%), the increased polymer content leads to stronger adsorption onto the entire particle surface, which suppresses propulsion by reducing local asymmetry. At 34 °C, thermophoretic propulsion stops, leaving only Brownian motion. Additionally, the diffusion coefficient increases due to temperature raise. These results highlight the potential of thermo-responsive polymers to control microswimmer dynamics, offering tunable transport properties for applications in active matter and targeted delivery systems.

We present a machine-augmented molecular dynamics (MAMD) framework in which particle velocities are updated using predictions from stacked long short-term memory networks trained on historical velocity and coordinate data. MAMD propagates coordinate trajectories in time without access to forces or energies during training or inference. Applied to isolated harmonic diatomics, MAMD conserves total energy, preserves molecular structure, and reproduces velocity autocorrelation functions. Small integration errors can accumulate over long trajectories, but we show that molecular dynamics stability can be recovered through periodic, but infrequent injections of velocity updates computed from Hamiltonian forces (frequency ≤0.01). We also find that the optimal history length for each diatom closely matches the first inflection point of its velocity autocorrelation function, suggesting a link between model architecture and statistical mechanics. These results establish MAMD as a proof-of-concept integration strategy for the isolated harmonic diatomic systems studied here, in which finite velocity memory supports short-horizon predictions and sparse Hamiltonian check-ins provide long-horizon stability. In particular, we show that force-free, velocity-based machine learning updates can be embedded directly into conventional molecular dynamics algorithms while retaining essential physical invariants, providing a physically interpretable basis for hybrid MD/ML integration. Systematic extensions to more complex systems and quantitative performance comparisons in regimes with expensive force evaluations (e.g., ab initio molecular dynamics) are left for future work.

Numerical simulation and remote measurement of temperature-dependent surface acoustic wave velocity by laser ultrasonics

A new method for simultaneous measurement of droplet or particle surface area and velocity

This paper presents the development of a validated numerical model of granular material flowability in a heat exchanger using the DEM modelling in STAR-CCM+ software. The model is developed based on an experiment. The simulation model is validated qualitatively and quantitatively from experimental data. The comparison between the experimental and simulated velocities, velocity profiles and mass flowrates demonstrate a high degree of similarity. For instance, the percentage difference of mass flowrate between the experiment and simulation data is 5.61% and the maximum percentage difference of the particle velocity is 9.53% which reflects a reasonable level of agreement.

Addressing environmental challenges in blasting: A dual-method data generation framework for peak particle velocity prediction

This paper presents an experimental investigation of granular material flowability in a heat exchanger. Spherical silicon particles are used as the granular materials in this study. The velocity profile created shows uneven particle velocity where particles towards the outlet flow faster with the velocity reaching 9.09 mm/s and the particles close to the wall flow slower with the velocity reaching 1.63 mm/s. Compared to the Carr classification of flowability proposed in the literature, the angle of repose obtained through the experiment, which is 15°, suggests that the particles are very free flowing. This is supported by the coefficient of rolling resistance which has been obtained as 0.001, suggesting that these particles have a lower rolling friction resistance, leading to a more efficient movement. Moreover, the mass flowrate implies that 140.85 grams of particles flow out per second. These findings suggest that particle size, outlet size, friction factors and the space between the heating elements and the walls affect the flowability of particles in the heat exchanger.

. Stone is one of the most widespread and important natural resources, which are actively used in various fields of activity. Energy costs for the working processes of machines for the production of building materials can be significant. In addition, constant costs for maintenance, spare parts and power also impose an additional financial burden on companies producing building materials. Considering these factors, the issue of optimizing and improving such machines is extremely important. Increasing their efficiency and reducing energy costs will significantly reduce the cost of manufacturing building materials, as well as reduce the environmental burden. A vertical shaft rotary crusher belongs to the class of centrifugal impact machines and works on the principle of material destruction by free impact in the field of action of centrifugal forces. In such crushers, several destruction mechanisms are implemented simultaneously. The interaction of these mechanisms ensures a very high crushing rate and obtaining a high-quality product. An important advantage of such crushers is that they work effectively at high rotor rotation speeds. The increase in the linear speed of the rotor flow enhances the impact effect, which makes it possible to destroy even very strong materials with relatively low energy consumption. At the same time, work on the principle of free impact ensures a uniform effect on each particle, which avoids excessive grinding and reduces the amount of dust fraction. The paper considers the critical velocity of a material particle when it leaves the rotor. The equation of particle motion is analyzed. The influence of the physical and mechanical properties of the material on the critical velocity of particle exit is studied. Dependencies for determining the productivity and power of a rotary crusher are considered.

The start-up of electrophoretic motion in a suspension of uniformly charged, porous, spherical particles within an arbitrary electrolyte solution under a suddenly applied electric field is investigated. The unsteady Stokes/Brinkman equations, modified to include the electric body force, are solved for the fluid velocity field using a unit cell model to account for the particle-particle interactions. An explicit expression for the transient electrophoretic velocity of a porous particle in a unit cell is derived in the Laplace transform domain as a function of the key governing parameters. The transient electrophoretic velocity, when normalized by its steady-state counterpart, increases monotonically with both elapsed time and the ratio of particle radius to Debye length, with other parameters held constant. It generally increases with the ratio of particle radius to permeation length and with porosity, while decreasing monotonically with an increase in the particle-to-fluid density ratio. Similar to its steady-state value, the transient electrophoretic mobility of the suspension is typically a decreasing function of the particle volume fraction. However, under conditions of small elapsed time and large density ratio, the transient mobility may exhibit an initial increase with particle volume fraction.

The present study presents long-term monitoring data on the dynamics of bedload transport processes in alpine gravel-bed river systems in Austria (Urslau, Strobler-Weißenbach) using radio frequency identification (RFID) technology. The detection of embedded RFID tracers was facilitated by the use of stationary antennas. This methodology enabled the acquisition of high-resolution data on particle transport velocities, transport distances, and sediment dynamics. Monitoring has been in operation permanently over a period of 8 years, including several intense flood events. In total, 1612 RFID-tagged stones were deployed, and the maximum measured particle velocity was 2.47 m s−1. The measurements at the Urslau stream revealed seasonal variability and long-term trends, while targeted short-term measurements at the Strobler-Weißenbach stream provided valuable insights into the dynamics of flood events. The results underscore the significance of environmental factors, including the grain size, river gradient, and hydraulic parameters, in the dynamics of bedload transport in alpine gravel bed streams. Furthermore, the efficiency of stationary antennas was optimised to ensure uninterrupted monitoring. This study underscores the importance of contemporary monitoring technologies in analysing river processes and addressing challenges, including those brought about by climate change.

Adiabatic propagation of spherical magneto hydrodynamic shock waves in an ideal gas has been carried out by the well-known CCW method under the impact of solid body rotation of medium. The effect of constant axial weak magnetic field of the phenomenon is estimated for the converging strong shock with constant angular velocity. Neglecting the flow behind the shock front the analytical expressions for shock velocity, shock strength, pressure and particle velocity just behind the shock front have been derived and discussed with the graphs and tables. The results accomplished here have been compared with dose for normal shock wave and earlier results

Increasing the service life of parts by forming protective and restorative coatings through cold spraying (CS) is a tough scientific and technical challenge. The object of the study is the process of accelerating powder particles in a supersonic rotating nozzle for CS. For CS, it is difficult, and sometimes even impossible, to form coatings on internal and hard-to-reach surfaces. In the practice of using the technology, this is considered one of the most problematic places, which limits the capabilities of the technology. This paper focused on improving the CS process by developing a new supersonic rotating nozzle for coating deposition on internal and hard-to-reach surfaces of parts, establishing the regularities of the trajectory of motion and acceleration of powder particles in it. During the study, classical methods of computational gas dynamics were used, including methods for investigating two-phase flows. Experimental verification of the modeling results was performed by the pneumatic method of determining the Mach number using a Pitot-Prandtl tube. Numerical modeling of CS processes was performed for two designed rotating nozzles – two-channel and three-channel. The values of the maximum velocity of aluminum powder particles with a diameter of 10 μm at an air stagnation pressure of 4.0 MPa and stagnation temperature of 550°C were obtained: 558 m/s for the two-channel nozzle, and 585 m/s for the three-channel one, which is sufficient for adhesion of particles to the substrate. A three-channel nozzle was chosen for manufacturing and experimental testing. The difference between the experimental and calculated values of the Mach number at the nozzle outlet did not exceed 10%. The presence of two additional nozzles, located in the main channel and directed at an angle to the main flow direction, ensures the rotation of the flow with particles from the initial direction at an angle of approximately 75 degrees, which satisfies the requirements for forming CS coatings.

This study examines the powder-gas flow dynamics in drug delivery through a nozzle integrated with a micro-shock tube-based needle-free device. The literature indicates that the pressure ratio (PR) influences particle velocity, which continues to increase even after exiting the nozzle causes momentum to the particles. As particle velocity increases post-nozzle exit, the stand-off distance emerges as a critical parameter. It minimizes the risk of device’s cross-contamination while ensuring optimal utilization of the PR to enhance particle velocity and promote penetration depth. The numerical investigation aimed to elucidate the influence of PR and stand-off distance on drug delivery. The current findings were validated by comparing numerical simulation results for nozzle exit pressure with experimental data from the literature, as discussed in the literature cited in this article. A parametric study was performed for PRs of 9, 15, 40, and 60. The selected PRs were based on data from the existing literature concerning powdered drug delivery devices. The influence of particle velocity by PR persists beyond the nozzle exit; therefore, the stand-off distance parameter ahead of the nozzle exit was included in this study. The maximum penetration depth of 75 µm at a PR of 60 was achieved for drug delivery within the epidermis region. It was observed that the optimal stand-off distance was determined to be 122 mm at PR = 60, resulting in a maximum penetration depth of 75.15 µm. The study revealed that the PR significantly influences particle velocity up to a specific stand-off distance along with penetration depth, even after the particles exit the nozzle region.

ABSTRACT Tool Condition monitoring is an important factor in manufacturing industries for improving the product quality, reducing the manufacturing losses It also helpful to optimize the labour cost as well as to increase the productivity. Several monitoring methods are used to monitor the tool condition either directly or indirectly. The study focuses the application of very near field acoustic emission technique used as an indirect measuring method for monitoring the tool condition. In the proposed system, sound particle velocity signal is captured and is used to monitor the tool condition. The machine learning models like K–nearestneighbors,decisiontree,randomforest,logisticregressionandgradientboostinglearning were used as decision making in tool condition monitoring system. Among the selected model, gradient boosting has an F1 score value of 1.0, indicates the chosen model performs better for the given data set with weighted average of 0.99. The Kappa score value of the gradient boosting algorithm is 0.98,indicates that there is a good agreement between the predicted versus actual. The AUC-ROC Score value 0.9991 indicates that the gradient boosting model is performed well for thegiven data set with different machine learning algorithms for varioustool state conditions.