Search Results (776)

This study aims to use Computational Fluid Dynamics (CFD) analysis to improve inclusion removal efficiency in tundishes used in the steelmaking industry, with the broader goal of promoting more sustainable steel production and supporting circular economy objectives by producing cleaner steel. Inclusions are non-metallic particles, such as alumina, that enter the tundish with the molten steel and travel through it; if not removed, they can exit through the nozzles and adversely affect the mechanical properties of the final product and process yield. An existing tundish design is modified using three passive techniques, including adding a vertical dam, adding a horizontal baffle, and inclining the side walls, to assess their influence on fluid flow behavior and inclusion removal. Residence time distribution (RTD) analysis is employed to evaluate flow characteristics via key metrics such as dead zone and plug flow volume fractions, as well as plug-to-dead and plug-to-mixed flow ratios. In parallel, a discrete phase model (DPM) analysis is conducted to track inclusion trajectories for particles ranging from 5 to 80 μm. Results show that temperature gradients due to heat losses significantly influence flow patterns via buoyancy-driven circulation, changing RTD characteristics. Among the tested modifications, inclining the side walls proves most effective, achieving average inclusion removal improvements of 8% (Case B1) and 19% (Case B2), albeit with increased heat loss due to greater top surface exposure. Vertical dam and horizontal baffle, despite showing favorable RTD metrics, generally reduce the inclusion removal rate, highlighting a disconnect between RTD-based predictions and DPM-based outcomes. These findings demonstrate the limitations of relying solely on RTD metrics for evaluating tundish performance and suggest that DPM analysis is essential for a more accurate assessment of inclusion removal capability. Full article

Recently, considerable research has been conducted on wet shot peening (WSP), but a detailed investigation of this process is still lacking. For a systematic study, four three-dimensional models of WSP and shot peening (SP) were developed using the finite element method (FEM), based on the coupled Eulerian–Lagrangian (CEL) method. Micron-scaled water film is directly observed during WSP processing. Simulation results indicate that the water film has a significant impact on the dimple size and residual stress distribution. Compared with SP, WSP can produce (a) a dimple with a larger curvature radius, (b) greater compressive residual stress in the surface layer with a larger area, and (c) more uniformly distributed surface residual stress. This work reveals the mechanism underlying the changes mentioned above, which provides rationales for the promotional applications of WSP. Full article

Understanding the interaction between submerged water jets and cohesive deep-sea sediment is critical for optimizing deep-sea polymetallic nodule hydraulic mining techniques. This research investigated the distinct erosion behavior of cohesive sediments through laboratory experiments and numerical simulations. Cohesive deep-sea sediments were simulated using bentonite–kaolinite mixtures. A series of laboratory experiments, including vane shear tests and viscosity tests under varying moisture content, were conducted to assess the sediments’ mechanical properties. Experimental submerged water jet erosion tests provided basic data for validating the numerical simulations. A Eulerian multi-fluid (EMF) model was implemented to capture sediment–water jet interactions under varying operational parameters, including jet velocities and nozzle heights. The erosion process was found to comprise three distinct stages, including rapid erosion, steady erosion, and stabilization. Two distinct erosion mechanisms were identified, depending on the jet intensity, which affected the depth and shape of the erosion pits. Quantitative analysis revealed that erosion depth exhibits an approximately linear relationship with jet velocity and nozzle height, whereas the erosion diameter shows nonlinear characteristics. These findings enhance the fundamental understanding of cohesive sediment responses under hydraulic disturbances, providing crucial insights for the design and optimization of efficient deep-sea mining systems. Full article

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

Centrifugal irrigation pumps in Southern Xinjiang face severe performance degradation due to high fine-sediment loads in canal water. This study combines Eulerian multiphase simulations with experimental validation to investigate the coupled effects of sediment size (0.05~0.8 mm) and concentration (5~20%) on hydraulic performance. Numerical models incorporating Realizable k–ε turbulence closure and discrete phase tracking reveal two critical thresholds: (1) particle sizes ≥ 0.4 mm trigger a phase transition from localized disturbance to global flow disorder, expanding low-pressure zones by 37% at equivalent concentrations; (2) concentrations exceeding 13% accelerate nonlinear pressure decay through collective particle interactions. Velocity field analysis demonstrates size-dependent attenuation mechanisms: fine sediments (≤0.2 mm) cause gradual dissipation via micro-scale drag, while coarse sediments (≥0.6 mm) induce “cliff-like” velocity drops through inertial impact-blockade chains. Experimental wear tests confirm simulation accuracy in predicting erosion hotspots at impeller inlets/outlets. The identified synergistic thresholds provide critical guidelines for anti-wear design in sediment-laden irrigation systems. Full article

Remote photoplethysmography (rPPG) offers a promising solution for non-contact driver monitoring by detecting subtle blood flow-induced facial color changes from video. However, motion artifacts in dynamic driving environments remain key challenges. This study presents an rPPG framework that combines signal processing techniques before and after applying Eulerian Video Magnification (EVM) for pulse rate (PR) estimation in driving simulators. While not novel, the approach offers insights into the efficiency of the EVM method and its time complexity. We compare results of the proposed rPPG approach against reference Empatica E4 data and also compare it with existing achievements from the literature. Additionally, the possible bias of the Empatica E4 is further assessed using an independent dataset with both the Empatica E4 and the Faros 360 measurements. EVM slightly improves PR estimation, reducing the mean absolute error (MAE) from 6.48 bpm to 5.04 bpm (the lowest MAE (~2 bpm) was achieved under strict conditions) with an additional time required for EVM of about 20 s for 30 s sequence. Furthermore, statistically significant differences are identified between younger and older drivers in both reference and rPPG data. Our findings demonstrate the feasibility of using rPPG-based PR monitoring, encouraging further research in driving simulations. Full article

Predicting absolute values of hemolysis using the power law model to guide medical device design is hampered by uncertainties stemming from four sources of model inputs: incoming/upstream velocity profiles, blood viscosity models, power law hemolysis coefficients, and obtaining accurate stress exposure times. Amidst all these uncertainties, enabling rapid assessments and predictions of relative hemolysis would still be valuable for evaluating device design prototypes. Towards achieving this objective, hemolysis data from the Eulerian modeling framework was first generated from computational fluid dynamics simulations encompassing five blood viscosity models, four sets of hemolysis power law coefficients, fully developed as well as developing velocity flow conditions, and a wide range of shear stresses, strain rates, and stress exposure times. Corresponding hemolysis predictions were also made in a Lagrangian framework via numerical integration of shear stress and residence time spatial variations under the assumption of fully developed Newtonian fluid flow. Absolute hemolysis predictions (from both frameworks) were proportional to each other and independent of the blood viscosity model. Further, relative hemolysis trends were not dependent on the hemolysis power law coefficients. However, accuracy in wall shear stresses in developing flow conditions is necessary for accurate relative hemolysis assessments. Full article

A multiphase model of hydrothermal liquefaction (HTL) using the computational fluid dynamics coupling discrete element method (CFD-DEM) is used to simulate biocrude oil production from sludge flocs in a continuous stirred tank reactor (CSTR). Additionally, the influence of the agitator speed and the slurry flow rate on dynamic biocrude oil production is investigated through full transient CFD analysis in a scaled-up CSTR study. The kinetics of the HTL mechanism as a function of temperature, pressure, and residence time distribution were employed in the model through a user-defined function (UDF). The multiphysics simulation of the HTL process in a stirred tank reactor using the Lagrangian–Eulerian (LE) approach, along with a standard k-ε turbulence model, integrated HTL kinetics. The simulation accounts for particle–fluid interactions by coupling CFD-derived hydrodynamic fields with discrete particle motion, enabling prediction of individual particle trajectories based on drag, buoyancy, and interphase momentum exchange. The three-phase flow using a compressible non-ideal gas model and multiphase interaction as design requirements increased process efficiency in high-pressure and high-temperature model conditions. Full article

To investigate the internal flow characteristics of particles during hydraulic lifting in deep-sea mining risers, this study developed a three-dimensional curved riser multiphase flow model based on the Eulerian–Eulerian framework and the RNG k-ε turbulence model. The effects of particle distribution and pressure loss in the curved section, as well as the influence of curvature radius, were analyzed. Results indicate that particle distributions take concave circular or crescent-shaped patterns, becoming more uniform with larger curvature radii. Pressure on the extrados is consistently greater than on the intrados, with pressure loss increasing in the bend and peaking at the midpoint. A larger curvature radius leads to greater total pressure loss but lower frictional loss. Additionally, the bend experiences a restoring force toward the vertical position, which increases as the curvature radius decreases. Full article

Ensuring the safe landing of deep-sea mining vehicles (DSMVs) on soft seabed sediments is critical for the stability and operational reliability of subsea mineral extraction. However, deep-sea sediments, particularly in polymetallic nodule regions, are characterized by low shear strength, high compressibility, and rate-dependent behavior, posing significant challenges for full-scale experimental investigation and predictive modeling. To address these limitations, this study develops a high-fidelity finite element simulation framework based on the Coupled Eulerian–Lagrangian (CEL) method to model the landing and penetration process of full-scale DSMVs under various geotechnical conditions. To overcome the high computational cost of FEM simulations, a data-driven surrogate model using the random forest algorithm is constructed to predict the normalized penetration depth based on key soil and operational parameters. The proposed hybrid FEM–ML approach enables efficient multiparameter analysis and provides actionable insights into the complex soil–structure interactions involved in DSMV landings. This methodology offers a practical foundation for engineering design, safety assessment, and descent planning in deep-sea mining operations. Full article

This paper proposes a rotating test method to address the limitations of high costs and the inability to replicate high-speed multiphase environments in icing wind tunnels and artificial climate chambers. The method simulates high-speed multiphase in an enclosed space using relative motion and duct regulation at a lower cost. Using the FQJG2-30/16-400 type roof insulator, the Eulerian–Eulerian and CFD (computational fluid dynamics) method was employed to compare the proposed rotating method with traditional linear airflow tests in wind–sand erosion and high-speed icing experiments. Results show maximum differences of 3.23% in the collision rate and 4.34% in the icing mass, indicating good consistency. Validation experiments in an artificial climate chamber further confirmed the feasibility of the rotating test method, with icing mass differences within 5–8%. This study provides a cost-effective approach for high-speed testing in multiphase environments. Full article

In this study, the objective is to assess the impacts of NH₃ emissions from mink farming on human health and nature, which are sensitive to atmospheric nitrogen deposition. The impact-pathway approach is applied to follow the emissions from source to impact on human health in Europe (including Denmark) and from source to critical nitrogen load exceedances for NH₃-sensitive nature in Denmark. The Danish Eulerian Hemispheric Model (DEHM) is used for modelling the air pollution concentrations in Europe and nitrogen depositions on land and water surfaces in Denmark arising from NH₃ emissions from mink farming in Denmark. The Economic Valuation of Air (EVA) pollution model system is applied for deriving the health effects and corresponding socio-economic costs in Denmark and Europe arising from the emissions from mink farming. On a local scale in Denmark, the deposition resulting from the NH₃ emissions from mink farming is modelled using the results from the OML-DEP model at a high resolution to derive the critical nitrogen load exceedances for Danish nature areas sensitive to NH₃. From the analysis of the impacts through human exposure to the air pollutants PM_2.5, NO₂, and O₃, it is concluded that in total, ~60 premature deaths annually in Europe, including Denmark, can be attributed to the emissions of NH₃ to the atmosphere from the mink farming sector in Denmark. This corresponds to annual socio-economic costs on the order of EUR 142 million. From the analysis of critical load exceedances, it is concluded that an exceedance of the critical load of nitrogen deposition of ~14,600 hectares (ha) of NH₃-sensitive nature areas in Denmark can be attributed to NH₃ emissions from mink farming. The cost for restoring nature areas of this size, damaged by eutrophication from excess nitrogen deposition, is estimated to be ~EUR 110 million. In 2020, the mink sector in Denmark was shut down in connection with the COVID-19 pandemic. All mink were culled by order of the Danish Government, and now in 2025, the process of determining the level of financial compensation to the farmers is still ongoing. The socio-economic costs following the impacts on human health in Europe and nitrogen-sensitive nature in Denmark of NH₃ emissions from the now non-existing mink sector can therefore be viewed as socio-economic benefits. In this study, these benefits are compared with the expected level of compensation from the Danish Government to the mink farmers, and the conclusion is that the compensation to the mink farmers breaks even with the benefits from reduced NH₃ emissions over a timescale of ~20 years. Full article

This research paper addresses the problem of testing N × 1 random-access memories (RAMs) in which complex models of unlinked static neighborhood pattern-sensitive faults (NPSFs) are considered. Specifically, two well-known fault models are addressed: the classical NPSF model that includes only memory faults sensitized by transition write operations and an extended NPSF model that covers faults sensitized by transition write operations as well as faults sensitized by non-transition writes or read operations. For these NPSF models, near-optimal multirun march memory tests suitable for implementation in embedded self-test logic are proposed. Each of the two new memory tests completely covers the NPSF model considered. The assessment of optimality is based on the fact that for any group of cells corresponding to the NPSF model, the state graph is completely covered and each arc is traversed only once, which means that the graph is of the Eulerian type. However, we say that these memory tests are near-optimal and not optimal because some additional write operations are required for data background changes. A characteristic of a memory test algorithm where multiple data backgrounds are applied is that the test data is always correlated with the address of the accessed location. For easy implementation in embedded self-test logic, the proposed tests use 4 × 4 memory initialization patterns rather than the more difficult-to-implement 3 × 3 patterns, as is the case with other currently known near-optimal memory tests. Full article

To accommodate the extreme thermodynamic effects and erosion damage in throttling equipment for ultra-high-pressure natural gas wells (175 MPa), a coupled multiphase flow erosion numerical model for nozzles was established. This model incorporates a real gas compressibility factor correction and is based on the renormalized k-ε RNG (Renormalization Group k-epsilon model, a turbulence model that simulates the effects of vortices and rotation in the mean flow by modifying turbulent viscosity) turbulence model and the Discrete Phase Model (DPM, a multiphase flow model based on the Eulerian–Lagrangian framework). The study revealed that the nozzle flow characteristics follow an equal-percentage nonlinear regulation pattern. Choked flow occurs at the throttling orifice throat due to supersonic velocity (Ma ≈ 3.5), resulting in a mass flow rate governed solely by the upstream total pressure. The Joule–Thomson effect induces a drastic temperature drop of 273 K. The outlet temperature drops below the critical temperature for methane hydrate phase transition, thereby presenting a substantial risk of hydrate formation and ice blockage in the downstream outlet segment. Erosion analysis indicates that particles accumulate in the 180° backside region of the cage sleeve under the influence of secondary flow. At a 30% opening, micro-jet impact causes the maximum erosion rate to surge to 3.47 kg/(m²·s), while a minimum erosion rate is observed at a 50% opening. Across all opening levels, the maximum erosion rate consistently concentrates on the oblique section of the plunger front. Results demonstrate that removing the front chamfer of the plunger effectively improves the internal erosion profile. These findings provide a theoretical basis for the reliability design and risk prevention of surface equipment in deep ultra-high-pressure gas wells. Full article

This research explores supersonic cyclonic separation for natural gas liquefaction (LNG). A 3D computational model was developed using the Eulerian–Eulerian two-fluid framework to simulate spontaneous gas condensation. The model tracks droplet formation/growth mechanisms and employs Reynolds stress modeling (RSM) for turbulence, implemented in Fluent via user-defined functions (UDFs). Validated against experimental data, it accurately predicted condensation onset and shock wave behavior. A prototype separator designed for a natural gas peak-shaving station demonstrated lower temperatures than throttling valves but modest liquefaction efficiency (4.28% at 5 MPa inlet pressure). Two enhancement strategies were tested: (1) injecting submicron LNG condensation nuclei (radius < 1 × 10⁻⁹ m) significantly boosted liquefaction by reducing nucleation energy barriers and suppressing condensation shocks; (2) a multi-stage configuration increased total liquefaction by 156% versus single-stage operation. These findings highlight the technology’s potential for energy-efficient gas processing. Full article