Search Results (675)

Lava flows represent complex thermofluid phenomena in which surface cooling leads to the formation of a solidified surface layer. Understanding the influence of such a surface layer on fluid flow is an important issue in lava flow modeling. It also shares essential characteristics with a wide range of engineering problems involving surface solidification. However, the role of plastic surface skin in controlling flow deceleration and stopping behavior has not been sufficiently clarified in existing models. In this study, two-dimensional smoothed particle hydrodynamics (SPH) simulations were conducted to investigate the influence of surface skin formation on lava flow dynamics. The temperature dependence of viscosity was introduced to reproduce a plastic surface skin. The skin was represented as a low-temperature, high-viscosity region. Comparisons with simulations without surface skin formation demonstrated that the surface skin exhibits a suppressive effect on the flow. This behavior was consistent with qualitative observations of flowing lava. It was also found that this surface skin caused the successive deceleration characteristic in Bingham fluids. As a result, both the flow velocity and the flowing distance are affected. These results suggest that accurate lava flow simulations require models that incorporate both surface skin effects and non-Newtonian behavior. Full article

Post-grouting is an active reinforcement technique that can significantly enhance the bearing performance of bored piles. This study conducted field tests on three in situ test piles using tip grouting, side grouting, and combined tip-side grouting. Based on the analysis of static load test data, the improvement effects of different grouting methods on the vertical bearing behavior of the piles were quantified. In situ tests were then performed to elucidate the reinforcement mechanisms of various post-grouting techniques on the pile foundations. Based on the validated finite element model, the study explored the influence of key grouting parameters on the bearing performance of grouted piles. Analysis of the test data shows that all grouting methods improved the vertical bearing capacity of bored piles. The positive effect of tip grouting was more pronounced than that of side grouting. Furthermore, in the clay layer of the soft soil region, side grouting primarily manifested as splitting grouting, while tip grouting formed a hardened grout bulb at the pile tip through cementation and solidification, thereby significantly enhancing the mobilization of the pile tip bearing capacity. Finite element model analysis shows that, in terms of enhancing the bearing capacity of the pile, expanding the grout diffusion range is more effective than increasing the grout material strength. Full article

In this paper, an explainable decision-making and guidance integration method is developed based on dynamic Bayesian network and the optimized control method. The proposed method can be applied for the autonomous decision-making and guidance in the game of attacking and defending of unmanned combat aerial vehicles in close air combat. Firstly, the target maneuver recognition and target trajectory prediction are carried out according to the target information detected by the sensor. Then, a dynamic Bayesian network model for close combat decision is established by combining space occupancy situation and equipment performance information with target maneuver identification results. The decision model realizes the intelligent selection of the optimization index function of the maneuver. The optimal control constrained gradient method is adopted to realize the optimal calculation of the unmanned combat aerial vehicle occupancy guidance quantity by considering the constraint of unmanned combat aerial vehicle flight performance. The simulation results of several typical close air combat show that the proposed method can realize rationalized autonomous decision-making and space occupancy guidance of unmanned combat aerial vehicles, overcome the solidification of mobile action mode by traditional methods, and has better real-time performance and optimization performance. Full article

Shrinkage of injection-molded parts is a major challenge for dimensional accuracy, especially for semi-crystalline polymers where crystallization induces pronounced volume change and heat release during cooling. Because packing pressure is effective only before gate or local solidification, multi-stage packing is commonly used to regulate the overall shrinkage behavior. In practice, however, the solidification/transition temperature taken from standard material tests does not necessarily represent the actual in-cavity state behavior under specific cooling rate and pressure history, which compromises the consistency of P–V–T-based shrinkage prediction. In this study, a modified P–V–T-based framework (Tait equation) is developed for polypropylene (PP) by introducing a Thermal Enthalpy Transformation Method (TETM) to determine a process-relevant solidification time and crystallization-completion temperature (including the corresponding target specific volume) directly from in-cavity melt temperature monitoring using an infrared temperature sensor. The novelty TETM utilizes the crystallization-induced enthalpy release to identify the temperature–time plateau, from which one can identify the effective solidification point. Because the Tait equation adopts a two-domain formulation (molten and solidified states), accurate identification of the domain-switching temperature is critical for reliable shrinkage prediction in practical molding conditions. In the experiment execution, the optimum filling time was defined using the minimum pressure required for melt-filling. Four target specific volumes, three melt temperatures, and two mold temperatures were examined, and a two-stage packing strategy was implemented to achieve comparable shrinkage performance under different target specific volumes. A conventional benchmark based on the solidification temperature reported in the Moldex3D material database was used for comparison only. The results show that the target specific volume determined by the TETM exhibits a more consistent and near-linear relationship with the measured shrinkage rate, demonstrating that the TETM improves the robustness of solidification-time identification and the practical usability of P–V–T information for shrinkage control. Full article

Metal additive manufacturing (AM) generates complex microstructures through extreme thermal gradients and rapid solidification, critically influencing mechanical performance and industrial qualification. This review synthesizes recent advances in cellular automata (CA) and phase-field (PF) modeling to predict grain-scale microstructure evolution during AM. CA methods provide computational efficiency, enabling large-domain simulations and excelling in texture prediction and multi-layer builds. PF approaches deliver superior thermodynamic fidelity for interface dynamics, solute partitioning, and nonequilibrium rapid solidification through CALPHAD coupling. Hybrid CA–PF frameworks strategically balance efficiency and accuracy by allocating PF to solidification fronts and CA to bulk grain competition. Recent algorithmic innovations—discrete event-inspired CA, GPU acceleration, and machine learning—extend scalability while maintaining predictive capability. Validated applications across Ni-based superalloys, Ti-6Al-4V, tool steels, and Al alloys demonstrate robust process–microstructure–property predictions through EBSD and mechanical testing. Persistent challenges include computational scalability for full-scale components, standardized calibration protocols, limited in situ validation, and incomplete multi-physics coupling. Emerging solutions leverage physics-informed machine learning, digital twin architectures, and open-source platforms to enable predictive microstructure control for first-time-right manufacturing in aerospace, biomedical, and energy applications. Full article

The impact and solidification of multiple molten droplets on a cold substrate critically influence the quality and performance of thermally sprayed coatings. We present a Smoothed Particle Hydrodynamics (SPH) model that couples fluid-solid interaction, wetting, heat transfer and phase change to simulate multi-droplet impact and freezing. The model is validated against benchmark cases, including the Young–Laplace relation, wetting dynamics, single-droplet impact and the Stefan solidification problem, showing good agreement. Using the validated model, we investigate two droplets—either centrally or off-centrally—impacting on a cold surface. Simulations reveal two distinct solidification patterns: convex pattern (CVP), which results in a mountain-like splat morphology, and concave pattern (CCP), which leads to a valley-like shape. The criterion for the two patterns is explored with two dimensionless numbers, the Reynolds number $Re$ and the Stefan number $Ste$. When $Re\le 17.8$, droplets tend to solidify in CVP; at higher Reynolds numbers $Re\ge 18.8$, they tend to solidify in CCP. The transition between the two patterns is primarily governed by $Re$, with $Ste$ exerting a secondary influence. For example, when droplets have $Re=9.9$ and $Ste=5.9$, they tend to solidify in a convex pattern, whereas at $Re=19.8$ and $Ste=5.9$, they tend to solidify in a concave pattern. Also, the solidification state of the first droplet greatly influences the subsequent spreading and solidification of the second droplet. A parametric study on CCP cases with varying vertical and horizontal offsets shows that larger vertical offsets accelerate solidification and reduce the maximum spreading factor. For small vertical distances, the solidification time increases with horizontal offset by more than 29%; for large vertical distances the change is minor. These results clarify how droplet interactions govern coating morphology and thermal evolution during thermal spraying. Full article

The quantity, size, and distribution of non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel critically influence its service performance. Conventional detection methods often fail to adequately characterize extreme inclusion distributions in large-section components. This study developed an integrated full-process inclusion analysis system combining high-precision motion control, parallel optical imaging, and laser spectral analysis technologies to achieve rapid and automated identification and compositional analysis of inclusions in meter-scale samples. Through systematic investigation across the industrial process chain—from a dia. 740 mm consumable electrode to a dia. 810 mm electroslag remelting (ESR) ingot and finally to a dia. 400 mm forged billet—key process-specific insights were obtained. The results revealed the effective removal of Type D (globular oxides) inclusions during ESR, with their counts reducing from over 8000 in the electrode to approximately 4000–7000 in the ingot. Concurrently, the mechanism underlying the pronounced enrichment of Type C (silicates) in the ingot tail was elucidated, showing a nearly fourfold increase to 1767 compared to the ingot head, attributed to terminal solidification segregation and flotation dynamics. Subsequent forging further demonstrated exceptional refinement and dispersion of all inclusion types. The billet tail achieved exceptionally high purity, with counts of all inclusion types dropping to extremely low levels (e.g., Types A, B, and C were nearly eliminated), representing a reduction of approximately one order of magnitude. Based on these findings, enhanced process strategies were proposed, including shallow molten pool control, slag system optimization, and multi-dimensional quality monitoring. An intelligent analysis framework integrating a YOLOv11 detection model with spectral feedback was also established. This work provides crucial process knowledge and technological support for achieving the quality control objective of “known and controllable defects” in HSLA steel. Full article

Net-shaped casting processes in the automotive industry have proved to be difficult to simulate due to the complexities of the interactions amongst thermal, fluid, and solute transport regimes in the solidifying domain, along with the interface. The existing casting simulation software lacks the necessary real-time estimation of thermophysical properties (thermal diffusivity and thermal conductivity) and the interfacial heat-transfer coefficient (IHTC) to evaluate the thermal resistances in a casting process and solve the temperature in the solidifying domain. To address these shortcomings, an axial directional solidification experiment setup was developed to map the thermal data as the melt solidifies unidirectionally from the chill surface under unsteady-state conditions. A Dilute Eutectic Cast Aluminum (DECA) alloy, Al-5Zn-1Mg-1.2Fe-0.07Ti, Eutectic Cast Aluminum (ECA) alloys (A365 and A383), and pure Al (P0303) were used to demonstrate the validity of the experiments to evaluate the thermal diffusivity (α) of both the solid and liquid phases of the solidifying metal using an inverse heat-transfer analysis (IHTA). The thermal diffusivity varied from 0.2 to 1.9 cm²/s while the IHTC changed from 9500 to 200 W/m²K for different alloys in the solid and liquid phases. The heat flux was estimated from the chill side with transient temperature distributions estimated from IHTA for either side of the mold–metal interface as an input to compute the interfacial heat-transfer coefficient (IHTC). The results demonstrate the reliability of the axial solidification experiment apparatus in accurately providing input to the casting simulation software and aid in reproducing casting numerical simulation models efficiently. Full article

This study evaluated the properties of two commercial filaments intended for medical and sterile applications: PLACTIVE (Copper 3D, Santiago, Chile) and CPE ANTIBAC (Fiberlogy, Brzezie, Poland). The aim of the research was to compare the dimensional accuracy, repeatability of the fused deposition modeling (FDM) 3D printing process, and the antibacterial properties of the samples using standardized procedures. Four types of samples were manufactured: geometrically differentiated specimens for metrological measurements (S1); cylinders with a diameter of 15 mm and a height of 40 mm for assessing process repeatability (S2); rectangular specimens measuring 40 × 40 × 2 mm for surface topography analysis (S3); and rectangular samples measuring 20 × 20 × 2 mm for biocidal property evaluation (S4). The results demonstrated that PLACTIVE samples exhibited higher dimensional conformity with nominal values and lower variability of diameters than CPE ANTIBAC samples, which may be associated with greater process stability. For both materials, the PSm parameter was correlated with layer height only in the 90° printing orientation. Surface topography analysis showed that increasing the layer height from 0.08 mm to 0.20 mm led to a significant rise in Rsm, Ra, and Sa values, indicating deterioration in the reproduction of micro-irregularities and increased spatial differentiation of the surface. For PLACTIVE samples, a tendency toward more convex structures with positive Rsk values and moderate kurtosis (Rku) was observed, suggesting uniform plasticization and stable interlayer bonding, particularly at the 0° orientation. In contrast, CPE ANTIBAC samples (especially those printed at 90°) were characterized by higher Ra and Sa values and negative skewness (Rsk), indicating valley-dominated, sharper surface morphology resulting from different rheological behavior and faster solidification of the material. PLACTIVE samples did not exhibit antibacterial properties against Escherichia coli (E. coli), while for Staphylococcus aureus (S. aureus), the activity was independent of printing direction and layer height. The CPE ANTIBAC material showed antibacterial effects against both tested strains in approximately 50% of the samples. The findings provide insights into the relationships between material type, printing orientation, and process parameters in shaping the dimensional and biocidal properties of FDM filaments. Full article

The heat transfer behavior of flying molten droplets during gas atomization significantly impacts the performance of metal powders, and the cooling, deformation, breakup, and defect formation processes of these flying droplets are closely interrelated. In this study, a mathematical model was developed by combining the k-ε turbulence model, the VOF model, and the solidification/melting model to determine the cooling and solidification process of a flying molten droplet. The relationship between the atomization parameters and the cooling rate of the molten droplet, as well as the mechanisms of hollow powder formation, was investigated. The results indicate that an increase in the initial temperature of the molten droplet resulted in a delay in its initial solidification time, while its cooling rate remained essentially unchanged. The cooling rate of the molten droplet increased with the increase in the gas velocity but decreased with the increase in the droplet diameter and gas temperature. Among these factors, the droplet diameter had the greatest impact on the cooling rate. During the solidification process, when the droplet’s surface layer was fully solidified, the trapped gas failed to escape and eventually became encapsulated within the solidified particle, resulting in the formation of hollow powder. Full article

The low thermal conductivity of phase-change materials (PCMs) remains a key limitation in latent heat thermal energy storage systems, leading to slow melting and incomplete energy recovery. To address this challenge, this study explores extended Y-Fin geometries as a novel heat transfer enhancement strategy within a concentric-tube latent heat thermal energy storage configuration. Six fin designs, derived from a baseline Y-shaped structure, were numerically compared to assess their influence on the melting and solidification behavior of stearic acid. A two-dimensional transient enthalpy–porosity model was developed and rigorously verified through grid, temporal, and residual convergence analyses. The results indicate that fin geometry plays a critical role in enhancing heat transfer within the PCM domain. The extended Y-Fin configuration achieved the fastest melting time, 28% shorter than the baseline Y-Fin case, due to improved thermal penetration and bottom-region accessibility. Additionally, the thermal performance was evaluated using nano-enhanced PCMs (10% Al₂O₃ and CuO in stearic acid) and paraffin wax. The addition of Al₂O₃ nanoparticles significantly improved thermal conductivity, while paraffin wax exhibited the shortest melting duration due to its lower melting point and latent heat. This study introduces an innovative fin architecture combining extended conduction paths and improved convective reach for efficient latent heat storage systems. Full article

Ground settlement is readily induced by shield–tail gaps formed during tunneling, where soil loss must be compensated through backfill grouting. However, improper grouting control may trigger tunnel uplift, segment misalignment, and, after solidification, problems such as voids, cracking, and water ingress. Ensuring construction safety and long-term serviceability requires both reliable detection of grouting effectiveness and a mechanistic understanding of grout diffusion. This review systematically synthesizes sensing technologies, diffusion modeling, and intelligent data interpretation. It highlights their interdependence and identifies emerging trends toward multimodal joint inversion and real-time grouting control. Non-destructive testing techniques can be broadly categorized into geophysical approaches and sensor-based methods. For synchronous detection, vehicle-mounted GPR systems and IoT-based monitoring platforms have been explored, although studies remain sparse. Theoretically, grout diffusion has been investigated via numerical simulation and field measurement, including the spherical diffusion theory, columnar diffusion theory, and sleeve-pipe permeation grouting theory. These theories decompose the diffusion process of the slurry into independent movements. Nevertheless, oversimplified models and sparse monitoring data hinder the development of universally applicable frameworks capable of capturing diverse engineering conditions. Existing techniques are further constrained by limited imaging resolution, insufficient detection depth, and poor adaptability to complex strata. Looking ahead, future research should integrate complementary non-destructive methods with numerical simulation and intelligent data analytics to achieve accurate inversion and dynamic monitoring of the entire process, ranging from grout diffusion and consolidation to defect evolution. Such efforts are expected to advance both synchronous grouting detection theory and intelligent and digital-twin tunnel construction. Full article

In this research, we assess the feasibility of employing hybrid friction stir channeling (HFSC) to produce composite panels that combined an 8 mm thick AA6082-T6 aluminum alloy and 5 mm thick glass-fiber-reinforced Noryl GFN2. HFSC is an innovative solid-state technology that combines both friction stir joining and channeling characteristics, which enable the generation of integral internal channels while joining different components. A parametric study was outlined to explore the effects of the travel speed, probe length, and tool plunging on the resulting composite panels. The resulting composite panels were subsequently subjected to a comprehensive analysis encompassing exterior ceiling quality, internal channel, and joining interface morphology. Depending on the processing parameters, the geometry of the channels was found to be quasi-rectangular or quasi-trapezoidal, with significant variability on cross-sectional area, resulting in hydraulic diameters ranging from 1.2 to 2.9 mm. The joining interface was characterized by a concavity of aluminum that was extruded downwards into the polymeric molten pool, which was clinched after polymeric re-solidification. The experimental results prove the ability to join metals and polymers while creating an integral channel in a single process step using HFSC. Despite the positive effect of irregular shaped channels on heat exchange, the numerical models evidenced a detrimental effect of 14.3 and 16.3% on ultimate tensile and flexural loads, respectively. This way, this fabrication technology evidenced promising characteristics that are suitable for manufacturing thermal management systems such as conformal cooling for plastic injection molding or battery trays for EVs. Full article

This study investigates the effect of Interlayer Dwell Time (IDT) on the thermal behavior of the Wire-Laser Directed Energy Deposition (WLDED) process. A two-dimensional transient thermal model was developed in MATLAB, incorporating temperature-dependent material properties, a moving Gaussian heat source, and melting–solidification phase change to simulate sequential layer deposition. The model was calibrated for thin-walled geometries, numerically validated using ANSYS, and experimentally validated with literature data. Using the validated model, twenty-seven cases were simulated to examine the combined influence of IDT, part length, and layer thickness on melt-pool dimensions and layer-wise temperature distribution. The results show that increasing IDT reduces melt-pool depth and length by limiting heat accumulation, with the magnitude of this effect depending strongly on part length and layer thickness. Shorter parts and thicker layers exhibit the highest sensitivity to IDT variations. Additionally, the Thermal Stability Factor (TSF) is introduced, a dimensionless index that effectively identifies heat-accumulation phenomena and indicates thermal instabilities. Overall, the findings enhance the understanding of the impact of IDT in the thermal profile of WLDED and demonstrate that optimized IDT selection can stabilize melt-pool geometry and reduce thermal buildup, supporting future adaptive IDT strategies in wire-based metal additive manufacturing. Full article

Selective laser melting (SLM) is a 3D printing technology for precision manufacturing. Owing to its high forming accuracy, parts fabricated by SLM can often be used directly without secondary machining. Consequently, the stress field in the structure, especially local stress concentration in small regions, is of great importance. Building on our previous work, this study proposes an accurate and efficient thermo-mechanical analysis method that combines a computational fluid dynamics (CFD) model and a finite element method (FEM) model for stress prediction in micrometer-scale SLM. Compared with the conventional element birth–death method, the present model more faithfully reproduces the SLM process and the post-solidification morphology and stress distribution. Numerical simulation of a single-track TC4 scan shows that pronounced surface undulations and lack-of-fusion regions exhibit significant stress concentration: the local residual stress can reach approximately 900 MPa, whereas regions with relatively smooth surface geometry exhibit stresses of about 650 MPa. This indicates a clear positive correlation between surface quality and stress concentration. The results provide a new theoretical basis for understanding defect formation mechanisms, spatial stress distribution, and scan-path optimization in SLM components. Full article