Search Results (40)

Reliable multiscale models of thrombosis require platelet-scale fidelity at organ-scale cost, a gap that scientific machine learning has the potential to narrow. We trained a DeepONet surrogate on platelet dynamics generated with LAMMPS for platelets spanning ten elastic moduli and capillary numbers (0.07–0.77). The network takes as input the wall shear stress, bond stiffness, time, and initial particle coordinates and returns the full three-dimensional deformation of the membrane. Mean-squared-error minimization with Adam and adaptive learning-rate decay yields a median displacement error below 1%, a 90th percentile below 3%, and a worst case below 4% over the entire calibrated range while accelerating computation by four to five orders of magnitude. Leave-extremes-out retraining shows acceptable extrapolation: the held-out stiffest and most compliant platelets retain sub-3% median error and an 8% maximum. Error peaks coincide with transient membrane self-contact, suggesting improvements via graph neural trunks and physics-informed torque regularization. These results represent a first demonstration of how the surrogate has the potential for coupling with continuum CFD, enabling future platelet-resolved hemodynamic simulations in patient-specific geometries and opening new avenues for predictive thrombosis modeling. Full article

In the micro-EDM blind-hole machining of C_f-ZrB₂-SiC ceramics, defects such as bottom surface protrusion and machining fillets are often encountered. The implementation of an electrode-assisted oscillating device has proven effective in improving machining outcomes. To unravel the fundamental reasons behind the optimization enabled by this auxiliary oscillating device, this paper presents fluid simulation research, providing a quantitative comparison of the differences in machining gap flow field characteristics and debris motion behaviors under conditions with and without the assistance of the oscillating device. Firstly, this paper briefly describes the characteristics of C_f-ZrB₂-SiC discharge products and flow field deficiencies during conventional machining and introduces the working principle of electrode-assisted oscillation devices to establish the background and objectives of the simulation study. Subsequently, this research established simulation models for both conventional machining and oscillating machining based on actual processing conditions. CFD numerical simulations were conducted to compare flow field differences between conditions with and without auxiliary machining devices. The results demonstrate that, compared to conventional machining, electrode oscillation not only increases the maximum velocity of the working fluid by nearly 32% but also provides a larger debris accommodation space, effectively preventing secondary discharge. Regarding debris agglomeration, oscillating machining resolves the low-velocity zone issues present in conventional modes, increasing debris velocity from 0 mm/s to 7.5 mm/s and ensuring continuous debris motion. Furthermore, the DPM was used to analyze particle distribution and motion velocities, confirming that vortex effects form within the hole under oscillating conditions. These vortices effectively draw bottom debris outward, preventing local accumulation. Finally, from the perspective of debris distribution, the formation mechanisms of micro-hole morphology and the tool electrode wear patterns were explained. Full article

Steel is an important product in many engineering sectors; however, steelmaking remains one of the largest ${\mathrm{CO}}_2$ emitters. Therefore, new governmental policies drive the steelmaking industry toward a cleaner and more sustainable operation such as the gas-based direct reduction–electric arc furnace process. To become carbon neutral, utilizing more scrap is one of the feasible solutions to achieve this goal. Addressing knowledge gaps regarding scrap heterogeneity (size, shape, and composition) is essential to evaluate the effects of increased scrap ratios in basic oxygen furnace (BOF) operations. This review systematically examines heat and mass transfer correlations relevant to scrap melting in BOF steelmaking, with a focus on low Prandtl number fluids (thick thermal boundary layer) and dense particulate systems. Notably, a majority of these correlations are designed for fluids with high Prandtl numbers. Even for the ones tailored for low Prandtl, they lack the introduction of the porosity effect which alters the melting behavior in such high temperature systems. The review is divided into two parts. First, it surveys heat transfer correlations for single elements (rods, spheres, and prisms) under natural and forced convection, emphasizing their role in predicting melting rates and estimating maximum shell size. Second, it introduces three numerical modeling approaches, highlighting that the computational fluid dynamics–discrete element method (CFD–DEM) offers flexibility in modeling diverse scrap geometries and contact interactions while being computationally less demanding than particle-resolved direct numerical simulation (PR-DNS). Nevertheless, the review identifies a critical gap: no current CFD–DEM framework simultaneously captures shell formation (particle growth) and non-isotropic scrap melting (particle shrinkage), underscoring the need for improved multiphase models to enhance BOF operation. Full article

This study numerically investigates the suitability of biomass particles of varying diameters as alternative reducing agents in the blast furnace raceway zone, where harsh conditions can create internal gradients affecting conversion. An internally resolved 1D Lagrangian particle model, fully integrated into the open-source CFD toolbox OpenFOAM^®, is used to model temperature and species gradients within thermally thick particles. The particle model is coupled with the surrounding Eulerian phase and includes drying, pyrolysis, oxidation, and gasification submodels. Results show that only biomass particles smaller than 250 μm fully convert in the raceway, while larger particles carry unconverted material beyond, potentially reducing blast furnace efficiency. Full article

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Internal soil erosion caused by water infiltration around defective buried pipes poses a significant threat to the long-term stability of underground infrastructures such as pipelines and highway culverts. This study employs a coupled computational fluid dynamics–discrete element method (CFD–DEM) framework to simulate the detachment, transport, and redistribution of soil particles under varying infiltration pressures and pipe defect geometries. Using ANSYS Fluent (CFD) and Rocky (DEM), the simulation resolves both the fluid flow field and granular particle dynamics, capturing erosion cavity formation, void evolution, and soil particle transport in three dimensions. The results reveal that increased infiltration pressure and defect size in the buried pipe significantly accelerate the process of erosion and sinkhole formation, leading to potentially unstable subsurface conditions. Visualization of particle migration, sinkhole development, and soil velocity distributions provides insight into the mechanisms driving localized failure. The findings highlight the importance of considering fluid–particle interactions and defect characteristics in the design and maintenance of buried structures, offering a predictive basis for assessing erosion risk and infrastructure vulnerability. Full article

Traditional designs often ignore the effect of catalyst particle shape, which suffers from capturing detailed local flow hydrodynamics, mass transport and reaction behaviors, and further significantly affects reactor phenomena. This study aims to perform particle-resolved computational fluid dynamics (CFD) simulations to investigate the influence of operating conditions and various catalyst particle shapes on fixed-bed reactor performance. Three important industrial reaction systems, including methanol to dimethyl ether, CO₂ hydrogenation to methanol, and levulinic acid esterification, are discussed in fixed-bed reactors. The numerical results demonstrate that reactor performance varies from the important interactive contributions of hydrodynamics characteristics and reaction behaviors. Specifically, exothermic reactions such as methanol to dimethyl ether and CO₂ hydrogenation to methanol are characterized by a gradual increase in temperature along the reactor height, while endothermic reactions such as valeric acid esterification exhibit a gradual decrease in temperature along the reactor height. For the methanol to dimethyl ether system, the increase in operating temperature leads to a decrease in axial methanol concentration, as well as an improvement in axial dimethyl ether concentration. However, the change in methanol molar concentration has little influence on its conversion. Furthermore, reactor phenomena strongly vary from the different catalyst shapes. The numerical results demonstrate that the fixed bed with hollow cylinders facilitates a more uniform flow distribution, whereas the fixed bed with solid cylinders achieves higher conversion rates within a specific temperature range (483.15 K to 523.15 K). This research provides valuable insights for fixed-bed reactor optimized design, emphasizing the need for precise control over temperature, feed rate, and catalyst configuration to improve reactant conversion in industrial applications. Full article

This study achieves the particle-resolved modeling of biomass pyrolysis via a novel approach of integrating the Discrete Element Method (DEM) with a semi-detailed chemical kinetic mechanism. By coupling CFD-DEM with a 36-step reaction network, the multiscale interactions between particle-scale hydrodynamics and the formation kinetics of 19 tar components under varying temperatures (630–770 °C) are elucidated. Levoglucosan (44.79%) and methanol (18.64%) are identified as primary tar components. Combined with these, furfural (C₅H₄O₂, 7.22%), methanal (CH₂O, 6.75%), and glutaric acid (C₅H₈O₄, 4.20%) account for over 80% of all the tar components. The secondary decomposition pathways are successfully captured, and changes in the reaction rates, as seen in triglycerides (R23: 307.30% rate increase at 770 °C) and tannins (R24: 265.41% acceleration), are quantified. This work provides the ability to predict intermediate products, offering critical insights into reactor optimization. Full article

Simulative and experimental studies were carried out to address multi-dimensional particle fractionation of non-biological particles according to size, shape, and density inside a high-throughput DLD array. Density sensitive separation was achieved for melamine and polystyrene particles at a diameter of 5 µm at a Reynolds number (Re) of 82, corresponding to an overall flow rate of 11.3 mL/min. This process is very sensitive, as no fractionation occurred for Re = 85 (11.7 mL/min). For the first time, the fractionation of elliptical polystyrene particles (5 × 10 µm) at Re > 1 was investigated up to Re = 80 (11 mL/min). A separation of elliptical particles from spherical melamine particles (5 µm) was observed in single experiments at all investigated Reynolds numbers. However, the separation is not reliably repeatable due to partial clogging of ellipsoidal particles along the posts. In addition, higher concentrations of polydisperse silica suspensions were experimentally investigated by using polydisperse silica particles at concentrations up to 0.4% (m/V) up to Re = 80 (20 mL/min). The separation size generally decreased with increasing Reynolds number and increased with increasing concentration. Separation efficiency decreased with increasing concentration, independent of the Reynolds number. In order to investigate the material-dependent separation in a contactless dielectrophoresis system (cDEP), the resolved CFD-DEM software was extended to calculate dielectrophoretic forces on particles. With this, the second stage of a serial-combined DLD-DEP system was simulated, showing good separation at lower flow rates. For these systems, different fabrication methods to minimize the distance between the electrodes and the fluid as well as the requirement to withstand high-throughput applications, were investigated. Full article

The shape of particles is a critical determinant that significantly influences the accuracy of discrete element simulations. To reduce the discrepancies between the discrete element model of wheat seeds and the actual particle shapes, and to enhance the accuracy of Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) coupling simulations in gas–solid two-phase flow studies, We employed laser scanning and inverse modeling techniques to develop a three-dimensional (3D) reconstruction of the wheat seed. Subsequently, we employed Rocky DEM simulation software to develop a polyhedron model and an Angle of Repose (AOR) test model. The interval range of material parameters was determined through a series of physical experiments and subsequently employed to delineate the high and low levels of parameters for the simulation tests. The simulation parameters were calibrated using data from AOR simulation tests. The Plackett–Burman test, Steepest-Ascent test, and Box–Behnken test were conducted sequentially to determine the optimal parameter configuration. A test bench for wheat gas-assisted seeding was constructed, and a semi-resolved CFD-DEM coupling simulation model was developed to perform comparative analysis. The results demonstrated that the optimal parameters were as follows: the static friction coefficient of wheat seed was 0.15, the dynamic friction coefficient of wheat seed was 0.11694, and the dynamic friction coefficient between wheat seed and resin was 0.0797. In this scenario, the relative error of AOR was 2.3% and the maximum relative error of ejection velocity observed was 4.1%. The reliability of the polyhedron model and its calibration parameters was rigorously validated, thereby providing a robust reference for studies on gas–solid two-phase flows. Full article

Internal airflow dynamics play a crucial role in spray drying engineering by governing particle transport and, consequently, the quality of dried products. For this application, airflow dynamics represent short- and long-timescale behaviors across the main jet and recirculation regions and have been related, among other factors, to spray chamber design. This study examines the parametric effects of key geometrical design parameters on internal airflow dynamics using Design of Experiments (DOE) methodologies and 3D Computational Fluid Dynamics (CFD) simulations. The CFD model adopts a cost-efficient approach, including adaptive mesh refinement (AMR) methods, enabling running multiple simulation cases while retaining turbulence-resolving capabilities. The results provide quantitative parameter–response relationships, offering insights into the impact of chamber geometry on complex airflow behaviors. Among the parameters studied, the chamber aspect ratio strongly influences the strength of external recirculation flows. The inlet swirl primarily governs the stability of central and recirculating flows, while the conical–cylindrical section topology, in conjunction with the jet Reynolds number, affects flow impingement on walls, predominantly caused by the precession and reversal of the central jet. This methodology demonstrates significant potential for future studies on particle drying, equipment, process scale-up, and alternative chamber configurations in spray drying systems. Full article

Particle image velocimetry (PIV) measurements were performed inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions to investigate the near-endwall flow. Of particular research interest was the dominant periodic disturbance of the flow field by incoming wakes, which were generated by moving cylindrical bars at a frequency of 500 Hz. Two PIV setups were utilized to resolve both (1) a large blade-to-blade plane close to the endwall as well as midspan and (2) the wake effects in an axial flow field downstream of the blade passage. The measurements were performed using a phase-locked approach in order to align and compare the results with comprehensive CFD data that are also available for this test case. The experimental results not only support a better understanding and even a quantification of the wake-induced over/under-turning inside and downstream of the passage, they also enable the tracing of the ‘negative-jet-effect’, which is widely known in the CFD branch of the turbomachinery community but is seldom visualized in experiments. The results also reveal that the bar wake periodically widens the blade wake by up to 165%, while the secondary flow is less affected and exhibits a phase lag with respect to the 2D-flow effects. The results presented here are an essential basis for the subsequent investigation of the near-endwall blade suction surface effects using unsteady pressure-sensitive paint in the second part of this two-part publication. Full article

Measurements of ash deposition rates were made between the secondary superheater and reheater sections of a 450 MW cyclone-fired lignite boiler as the operational load varied from 33 to 100%. Significant reductions in deposition rates with a decrease in operational load were observed. To uncover the causative mechanisms behind these observations, operational data from the power plant were used to carry out computational fluid dynamic (CFD) simulations of the boiler. After ascertaining that the gas temperatures and velocities at various sections within the boiler were being represented adequately, decoupled simulations of the ash deposition process on the deposit probe were carried out using a finely resolved boundary layer mesh. Fly ash particle size distribution (PSD) and its concentration for the decoupled calculations were determined from stand-alone cyclone barrel simulations. The ash partitioning (mass %) between the fly ash and slag was found to be ~50:50, which was in line with previous field observations, and it did not vary significantly across different cyclone loads. The predicted PSD of the deposit ash was concentrated in the size range 10–30 microns, which was in agreement with cross-sectional images of the deposit obtained from the measurements. At lower loads, sharp variations in the deposition rates were predicted in the gas temperature range 950–1150 K. The particle kinetic energy—particle viscosity-based capture methodology utilized in this study in conjunction with appropriate ash compositions, ash viscosity models and gas temperature estimates can help estimate slagging propensities at different loads reasonably well in these systems. Full article

Particle settling is the process by which particulates move toward the bottom of a liquid, which can affect the sediment transport and energy balance of marine systems. However, the deficiency in understanding the resolved fluid–particle interactions with complex boundaries in the settling process awaits resolution. This study employs a hybrid approach that combines computational fluid dynamics (CFD) with the discrete element method (DEM) to fully simulate the free-settling behavior of polyhedral particles in water. The accuracy of the method is verified by comparing numerical results with experimental data of ellipsoidal particle settling. Two series of tests with horizontal and vertical particle release directions are established to investigate the effects of particle shape features, such as the aspect ratio (AR) and corner (C), on the particles’ mechanical behavior and hydrodynamic characteristics. The results demonstrate that particle shape exerts a substantial influence on fluid resistance, rotational motion, and fluid disturbance throughout the settling process. The maximum velocities in vertically released cases are roughly 1.2–1.3 times greater than those in horizontally released cases. The study highlights the potency of the resolved CFD-DEM method as a robust technique for comprehending fluid–particle phenomena within the marine geotechnical engineering, including sedimentation and erosion of seabed sediments. Full article

Deterministic lateral displacement (DLD) is a high-resolution passive microfluidic separation method for separating micron-scale particles according to their size. Optimizing these microsystems for larger throughputs and particle concentrations is of interest for industrial applications. This study evaluates the limitations of the functionality of the DLD separation principle under these specific conditions. For this reason, different particle volume fractions (up to 11%) and volumetric flow rates (corresponding to Reynolds numbers up to 50) were varied within the DLD microsystem and tested in different combinations. Resolved two-way coupled computational fluid dynamics/discrete element method (CFD-DEM) simulations including spherical particles were performed. The results show a general increase in the critical diameter with increasing volume fraction and decreasing separation efficiency. The largest tested Reynolds number (Re = 50) results in the highest separation efficiency, particularly at low volume fractions, and is only slightly less efficient than low Reynolds numbers as the volume fraction increases. The results indicate that by limiting the volume fraction to a maximum of 3.6%, the flow rate and the associated separation rate can be increased while maintaining a high separation efficiency. Full article