Comprehensive Computational Fluid Dynamics Research Articles

Study of Orifice Design on Oleo-Pneumatic Shock Absorber

Aircraft oil-strut shock absorbers rely on orifice designs to control fluid flow and optimize damping performance. However, the complex nature of cavitating flows poses significant challenges in predicting the influence of orifice geometry on energy dissipation and system reliability. This study presents a comprehensive computational fluid dynamics (CFD) analysis of the effects of circular, rectangular, semicircular, and cutback orifice profiles on the internal flow characteristics and damping behavior of oleo-pneumatic shock absorbers. High-fidelity simulations reveal that the rectangular orifice generates higher damping pressures and velocity magnitude than those generated by others designs, while the semicircular shape reduces cavitation inception and exhibits a more gradual pressure recovery. Furthermore, the study highlights the importance of considering both geometric and thermodynamic factors in the design and analysis of cavitating flow systems, as liquid properties and vapor pressure significantly impact bubble growth and collapse behavior. Increasing the orifice length had a negligible impact on damping but moderately raised orifice velocities. This research provides valuable insights for optimizing shock absorber performance across a range of operating conditions, ultimately enhancing vehicle safety and passenger comfort.

Enhancing energy efficiency for buildings in hot-desert climate: CFD investigation of Trombe walls using several thermal fins configuration

This study presents a comprehensive computational fluid dynamics (CFD) analysis of Trombe walls in laminar flow conditions, focusing on the impact of thermal fins. The investigation explores configurations with 3 and 5 fins, considering varying fin heights, numbers, and rotation angles. The Nusselt number, friction factor, heat transfer rate, and thermal efficiency are meticulously examined for Reynolds numbers ranging from 600 to 1600. Results reveal that for configurations with three fins, a rotation angle of 70° yields the highest thermal efficiency, showcasing a notable increase from 32.3 % to 44 % across all Reynolds numbers. In contrast, configurations with five fins exhibit enhanced thermal efficiency when fins are maintained horizontally (90°) at low Reynolds numbers but experience a decline as Reynolds numbers increase. Specifically, the thermal efficiency drops from 62.48 % to 55.5 % for Re = 1400 and from 64.7 % to 58 % for Re = 1600. The study concludes that Trombe walls with three fins should be designed with a 70° rotation angle, while those with five fins should feature horizontally oriented fins for optimal thermal performance. These findings offer valuable insights for the design and optimization of Trombe walls, providing guidance for achieving enhanced energy efficiency in passive heating systems.

Numerical modeling of fill-level and residence time in starve-fed single-screw extrusion: a dimensionality reduction study from a 3D CFD model to a 2D convection-diffusion model

This research delves into the numerical predictions of fill-level and residence time distribution (RTD) in starve-fed single-screw extrusion systems. Starve-feeding, predominantly used in ceramic extrusion, introduces challenges which this study seeks to address. Based on a physical industrial system, a comprehensive 3D computational fluid dynamics (CFD) model was developed using a porous media representation of the complex multi-hole plate die. Validations performed using real sensor data, accounting for partial wear on auger screw flights, show an ~11% discrepancy without accounting for screw wear and ~6% when considering it. A 2D convection-diffusion model was introduced as a dimensionality reduced order model (ROM) with the intention of bridging the gap between comprehensive CFD simulations and real-time applications. Central to this model’s prediction ability was both the velocity field transfer from the CFD model and calibration of the ROM diffusion coefficient such that a precise agreement of residence time distribution (RTD) curves could be obtained. Some discrepancies between the CFD and the ROM were observed, attributed to the loss of physical information of the system when transitioning from a higher fidelity CFD model to a semi-mechanistic ROM and the inherent complexities of the starved flow in the compression zone of the extruder. This research offers a comprehensive methodology and insights into reduced order modeling of starve-fed extrusion systems, presenting opportunities for real-time optimization and enhanced process understanding.

Numerical study of the influence of amplitudes on heat transfer in a tube bundle

The objective of this study is to investigate the impact of different surface roughness levels on a staggered arrangement of tubes in a cross-flow configuration, with water as the fluid being used. The focus lies in comparing the data obtained from the rough surface configuration with that of a smooth cylinder reference point. To assist this comparison, a comprehensive two-dimensional computational fluid dynamics (CFD) model is created, which accurately represents the distinctive characteristics of each surface shape. This study also included modifying the Remax within a range of 10 000–16 000 and analyzing the outcomes of using four different tube types, each with different supernatant thicknesses labeled as [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] accordingly. Surprisingly, the tube with a 0.4 wave surface had significantly higher average Nusselt numbers (Nu) compared to the other tubes, indicating superior performance. The ideal tube design was found based on three main metrics: The performance evaluation criterion (PEC), the global performance criterion (GPC) and the average Nu. The performance metrics encompassed the PEC, GPC and the Colburn factor [Formula: see text]. The average Nu of the wavy_0.4 tube was higher than that of the SM by 31.66–32.54%, higher than that of the wavy_0.2 tube by 19.76–20.74%, and higher than that of the wavy_0.1 tube by 9.38–16.58%. According to the statistics, a heat exchanger that cools and has a wave with an amplitude of 0 is the most efficient choice for offshore energy systems. The smooth bundle tube (SBT) demonstrated the most significant increase in GPC, with values of 9.3–12.7% and 20.3–28.3% higher than those of wavy tubes with amplitudes of 0.1 and 0.2, respectively. In addition, correlations for the Nu are given, with results verified using empirical data from Balabani et al.

Bottom-hole pressure inversion method for nature gas wells based on blowout combustion flame shape parameters

In response to the challenges associated with the difficulty of obtaining critical well control parameters, particularly bottom-hole pressure, during a well blowout fire, a comprehensive computational fluid dynamics (CFD) model for analyzing well blowout fires is developed based on fluid mechanics and combustion theory, considering factors such as gas composition, pressure, wellhead diameter, wind speed, and temperature, and is validated by published experiment date. Then, a CFD simulation database is constructed by conducting a sensitivity analysis of the flame height to investigate the correlations among flow field, operating conditions and flame parameters. Subsequently, an approach incorporates an AutoEncoder (AE) to reduce the dimensionality of the highly correlated raw data, and a Bayesian Optimization-based Radial Basis Function Network (BO-RBFN) to explore the inherent patterns within the established CFD dataset and then establishes a fuzzy relation between immeasurable wellhead flow velocity and well blowout fires operating parameters, achieving an accurate prediction of wellhead flow velocity. Furthermore, utilizing the wellhead gas velocity and the calculated wellhead pressure as the initial conditions, the bottom hole pressure during blowout fire is inversed based on wellbore temperature and pressure model. As a result of this study, a model integrating numerical model, databases, intelligent algorithms is developed for determining bottom-hole pressure in the presence of a blowout fire. And the proposed deep learning-based approach demonstrated exceptional accuracy in predicting wellhead gas flow velocity, with an average absolute difference of less than 2% between validation set and test set. In addition, as the ambient temperature, wellhead pressure, and wellhead diameter increase, the height of the blowout flame increases. In contrast, as the gas temperature and wind speed increase, the height of the blowout flame gradually decreases. Notably, only marginal changes in flame height resulted from alterations in gas composition. This study can quantitatively reveal the cause of well blowout and evaluate the severity of well blowout, and have practical significance in guiding the design and execution of subsequent rescue operations for uncontrolled blowouts fires.

Dynamic Modelling and Simulation of Industrial Plant Fire and Gas Detection Systems; Parametric Analysis of Nozzle Flow

Industrial plant safety is of paramount importance, and the effective operation of Fire and Gas Detection Systems (FGDS) plays a critical role in preventing and mitigating incidents. This study presents a comprehensive parametric computational fluid dynamics (CFD) analysis of nozzle flow, aimed at enhancing our understanding of the complex fluid dynamics within nozzle geometries. Nozzles find wide applications in industries ranging from aerospace propulsion systems to industrial processes. The analysis employs CFD simulations with varying geometric parameters, such as nozzle shape, throat diameter, and expansion ratio, to investigate their influence on flow characteristics, including velocity profiles, pressure distributions, and shock formations. The parametric study involves systematic variations of these geometric parameters, allowing for the identification of optimal configurations for specific applications. The results shed light on the intricate interplay between nozzle geometry and flow behavior, providing valuable insights for nozzle design and optimization.

Reduced chemical kinetics mechanism for modelling of n-Heptane/syngas combustion with NOx formation in a micro-pilot ignited dual fuel engine

A reduced chemical kinetics model was developed to simulate the combined combustion of n-Heptane with syngas, as well as the standalone syngas combustion and NOx formation in a pilot-ignited dual fuel engine. This simplified model comprises 75 different species and 276 reactions. Its accuracy was confirmed by comparing it with experimental data from existing literature and numerical results from established models. The comparison encompassed key factors such as ignition delay, the speed of combustion in a laminar flame, and the concentration profiles of NOx. The reduced model closely aligned with both experimental and simulated outcomes, particularly under conditions relevant to engine combustion.This reduced mechanism was then employed in a comprehensive computational fluid dynamics computations to predict syngas combustion in a dual-fuel engine that employs the injection of reduced amount of liquid n-Heptane fuel with subsequent micro-pilot ignition. The model accurately captured the necessary conditions for n-Heptane injection and the co-oxidation of syngas with n-Heptane. Moreover, it exhibited strong agreement with experimental measurements of the heat release rate (ROHR) and cylinder pressures. The study's results highlight that the reduced mechanism can precisely simulate combustion of syngas-based fuels in engine cylinder containing up to 57% hydrogen (H2) content. As a result, this simplified model is highly suitable for simulating engine conditions involving fuels derived from syngas.

Optimization of aerodynamic performance by applying the combination of lamellar and 3D wheel deflectors on the SUV model

In the developmental phase of an electric SUV model, optimizing the SUV model’s aerodynamic performance often involves the use of wheel deflectors to control airflow around the front wheels. While lamellar wheel deflectors are a common choice for reducing aerodynamic drag, the automotive industry is increasingly embracing 3D wheel deflectors to enhance drag reduction efforts. This study delves into the flow patterns surrounding the front wheels and the drag reduction mechanisms brought about by wheel deflectors. In this research, we harness the strengths of both lamellar and 3D wheel deflectors to introduce a more effective design approach. The conceived wheel deflectors aim to simultaneously decrease aerodynamic drag and lift, a dual-purpose strategy that extends the SUV’s range and optimizes its stability at high speeds. To validate these optimization effects, comprehensive Computational Fluid Dynamics (CFD) simulations and subsequent wind tunnel testing are conducted. The findings presented in this paper establish a crucial foundation for the design and optimization of wheel deflectors, contributing to advancements in the field.

Comparative computational fluid dynamics analysis of fast pyrolysis of agricultural feedstocks across different biomass categories

This article presents a comprehensive Computational Fluid Dynamics (CFD) assessment of fast pyrolysis of three different agricultural feedstocks representing three different categories: Red oak (hardwood), Switchgrass (herbaceous biomass), and Picea glauca (softwood). The study aimed to evaluate the performance of each feedstock based on particle density, temperature distribution, and volume fraction distribution. The comparison of the simulation results with experimental data showed an average error factor below 13%. The study discovered that Red oak had the highest bio-oil production yield, followed by Switchgrass, which had a yield 10% lower, and Picea glauca, which had the weakest performance having a yield 20% lower than Red oak. Interestingly, optimal operating conditions for the production of bio-oil across all three feedstocks comprised a temperature of 500 °C and particle size of approximately 400 μm. However, increasing the pyrolysis temperature resulted in an increase in gas yield, whereas increasing particle size led to a rise in char production yield. Furthermore, the findings suggest that herbaceous biomass tends to perform better in fast pyrolysis for bio-oil production compared to softwood. This is attributed to the higher hemicellulose content in herbaceous feedstock which has a significant impact on bio-oil yield compared to cellulose and lignin. Moreover, hardwood and herbaceous samples, which have similar levels of cellulose and hemicellulose, demonstrated superior performance compared to softwood, which has lower hemicellulose content. Nonetheless, herbaceous biomass had about 10% extractable content, which made it perform weaker than hardwood.

Investigating the Impact of Operating Conditions on Relief Pressure Valve Flow through CFD and Statistical Analysis

This paper presents a comprehensive computational fluid dynamics (CFD) analysis of air/water flow through a discharge valve, focusing on four different seat–valve distances and three adjustment nozzle positions. The study investigates the velocity distribution, pressure profiles, tangential stresses, and turbulent kinetic energy within the valve and analyzes its performance under various operating conditions. Notably, peak velocities of 3210 m/s were observed between the valve seat and valve, with significant variations for different nozzle positions. Extreme pressure values centered on the valve plate, reaching 4.3 MPa. Tangential stresses were highest on the chamfered plate surface and varied on the seat, turbulent kinetic energy (TKE) exhibited randomness. This study provides valuable information for enhancing the valve’s efficiency in a wide range of industrial applications.

Assessment of motor yacht hydrodynamic performance

This study presents a comprehensive Computational Fluid Dynamics (CFD) analysis of an 18-meter motor yacht featuring a trawler hull design with a swim platform. The investigation explores the hydrodynamic performance of the yacht across three distinct drafts and six varying speeds.

Power generation gas turbine performance enhancement in hot ambient temperature conditions through axial compressor design optimization

The output power and efficiency of gas turbines are profoundly influenced by ambient temperatures, with higher temperatures resulting in a notable decline in power output. This issue becomes particularly critical during periods of heightened power demand in hot climates. There are two common ways to solve this problem: incorporating auxiliary systems, such as inlet air cooling, or undertaking a comprehensive redesign of the gas turbine core engine. However, these methods sometimes are costly and unfeasible, particularly in regions characterized by arid conditions or constrained budgets for engine modifications. An alternative strategy has been developed to optimize axial compressor performance in order to improve gas turbine power in high-temperature environments, through an innovative approach. This approach centers on the concept of “re-staggering” the stator blades as a retrofit upgrade for existing gas turbines, enabling an increase in compressor inlet mass flow rate while maintaining peak efficiency at 45 °C. An in-house optimization tool was developed, incorporating a genetic algorithm and artificial neural network, to ascertain the optimal configuration of the re-stagger angles. This optimization process was initially coupled with a mean-line solver and subsequently refined using a through-flow model to enhance the preliminary design. The refined compressor design was then subjected to a comprehensive 3D Computational Fluid Dynamics analysis. Additionally, “end-bend” and “elliptical leading edge” techniques were employed to sustain compressor efficiency and ensure stability across various design and off-design operating conditions. Following a thorough structural analysis, the newly designed compressors were manufactured and tested at two distinct sites in Iran (Yazd and Bampur). The measured data demonstrated the commendable performance and stability of the redesigned compressors, aligning closely with numerical predictions. Notably, the results showcased a substantial increase in gas turbine power output ranging from 7.0% to 8.0% at hot ambient conditions, all while preserving efficiency and stability. Encouragingly, the upgraded compressor also exhibited superior performance even at lower temperatures, such as 15 °C. Consequently, this uprating concept presents a practical and cost-effective solution for power plant operators seeking a significant boost in power output, especially during hot weather conditions or in arid regions prone to drought.

Modeling and Simulation of a Multizone Circulating Reactor for Polyethylene Production with Internal Cooling.

Polyolefins play a role in industries and are typically manufactured using two types of reactors: high-pressure tubular reactors and fluidized bed reactors. An innovative technology called the Multizone Circulating reactor (MZCR) has emerged, which introduces an innovative approach with interconnected polymerization zones creating a continuous loop of polymer flow. This study focuses on modeling and simulating ethylene gas phase polymerization within the MZCR in the presence of internal cooling to gain insights into its behavior. To achieve this, a comprehensive computational fluid dynamics (CFD) simulation was developed. It considered momentum, material, and energy balance aspects. The model equations were solved using the finite difference method in COMSOL Multiphysics version 6.1. The investigation primarily focused on studying the impact of incorporating a cooler into the riser section on the temperature profile within the reactor and ethylene conversion. The presence of this cooler resulted in a reduction in temperature change along the riser from approximately 8.0 °C to 4.0 °C. Moreover, it led to an increase of 7%, in ethylene single-pass conversion.

Computational Fluid Dynamics Insights into Chemical Vapor Deposition of Homogeneous MoS2 Film with Solid Precursors

AbstractIn this work, a comprehensive computational fluid dynamics (CFD) investigation to develop an in‐depth understanding on the fluid flow to obtain a homogenous deposition of MoS2 thin film is reported. First, the effect of substrate orientations (0, 20, 45, 70, and 90°) was simulated using ANSYS Fluent. The horizontal substrate (0°) showed a non‐uniform surface deposition rate (SDR) with relative standard deviation (RSD) of 44.1 %. The non‐uniformity gradually reduces with the increase of substrate angles and reaches the lowest for 90° with RSD of 13.1 %. The transient state analysis showed that no growth occurred for the first 8 s, followed by an SDR overshoot and finally reached a steady state >200 s. Next, the effect of horizontal separation distance (d = 1 to 6 cm) between MoO3 and the substrate is investigated. It is find that the Mo/S ratio reduces with the increase of separation distance. For d between 5 and 6 cm, the Mo/S drops by >1000 times and causes the growth environment to switch from Mo to S‐rich. This work offers a fast and cost‐effective approach to understand the fluid flow and to obtain a homogeneous deposition of MoS2 and other 2D TMD thin films.

Exploring decentralized ammonia synthesis for hydrogen storage and transport: A comprehensive CFD investigation with experimental validation and parametric study

Hydrogen energy plays a vital role in the transition towards a carbon-neutral society but faces challenges in storage and transport, as well as in production due to fluctuations in renewable electricity generation. Ammonia (NH3), as a carbon-neutral hydrogen carrier, offers a promising solution to the energy storage and transport problem. To realize its potential and support the development of a hydrogen economy, exploring NH3 synthesis in a decentralized form that integrates with distributed hydrogen production systems is highly needed. In this study, a computational fluid dynamics (CFD) model for the Ruthenium (Ru) catalysts-based Haber–Bosch reactor is developed. First, a state-of-the-art kinetic model comprehensively describing the complex catalytic reaction is assessed for its sensitivity and applicability to temperature, pressure and conversion. Then, the kinetic model is integrated into the CFD model, and its accuracy is verified through comparison with experimental data obtained from different Ru-based catalysts and operation conditions. Detailed CFD results for a given case are presented, offering a visual understanding of thermal gradients and species distributions inside the reactor. Finally, a CFD-based parametric study is performed to reveal the impacts of key operation parameters and optimize the NH3 synthesis reactor. The results show that the NH3 production rate is predominantly influenced by temperature, with a two-fold difference observed for every 30 °C variation, while pressure primarily affects the equilibrium. Additionally, the affecting mechanism of space velocity is thoroughly discussed and the best value for efficient NH3 synthesis is found to be 180,000 h−1. In conclusion, the CFD model and simulation results provide valuable insights for the design and control of decentralized NH3 synthesis reactor and operation, contributing to the advancement of sustainable energy technologies.

Numerical Simulation and Computational Fluid Dynamics Analysis of Two-Dimensional Lid-Driven Cavity Flow Within the Weapon Bay of an Autonomous Fighter Drone

The efficient deployment of weapons in military operations is critical for mission success, and the flow of air within the weapon bay of an autonomous fighter drone plays a vital role in achieving this objective. In this paper, we present a comprehensive numerical simulation and computational fluid dynamics (CFD) analysis of the three-dimensional lid-driven cavity flow within the weapon bay of an autonomous fighter drone. To address this challenging problem, we employ CFD analysis and a multigrid approach to solve the Navier-Stokes equations for the aerodynamic problem. Our simulations include high Reynolds numbers of up to 10,000, which demonstrates the potential of CFD analysis in optimizing the design of autonomous fighter drones for military operations. We evaluate the effectiveness of the linked strongly implicit multigrid technique in estimating high-Re fine-mesh flow solutions using the vorticity-stream function formulation of the two-dimensional incompressible Navier-Stokes equations. The model issue is the driven flow in a square cavity, and we consider meshes up to 1024 x 1024 points and combinations with Reynolds numbers as high as 1000. To further improve the accuracy of our simulations, we employ one-dimensional grid clustering coordinate transformations instead of uniform mesh refinement, as the flow field exhibits one or more secondary vortices. Our findings demonstrate that CFD analysis can provide valuable insights into the complex flow dynamics within the weapon bay of autonomous fighter drones, which can lead to the optimization of their design for enhanced mission capabilities. Overall, our study highlights the significance of numerical simulations and CFD analysis in the design and optimization of autonomous fighter drones for military applications. Our results can serve as a basis for future research in the field of UAV aerodynamics and contribute to the development of more efficient and effective military operations.

Hydrodynamic behavior of liquid flow in a rotating packed bed

Rotating Packed Bed (RPB) technology has emerged as a promising technology for reducing carbon footprint of various petrochemical processes by leveraging the HiGee field-induced mass transfer enhancement and allow for better capture of greenhouse gases. Despite its potential, there are still significant challenges that hinder the effective utilization of RPB technology in process intensification. Specifically, the hydraulics of liquid and gas phases within RPB packings present a significant challenge. In this study, 2D – VOF approach is employed to study the behavior of liquid droplets impacting on single rotating wire and on a whole rotating wire mesh within a Rotating Packed Bed (RPB). A comprehensive computational fluid dynamics (CFD) model is developed to analyze the influence of rotating speed, liquid velocity, and droplet diameter on the dynamics of liquid droplets. The boundaries of splashing – no splashing and dripping – capture breakup modes were validated for a single rotating wire and identified for wire mesh in RPBs by constructing the corresponding regime maps. This is achieved thanks to a new data processing algorithm that applies the principle of neighborhood aggregation. The proposed data processing algorithm helps reconstruct the regime maps for the various breakup phenomena within RPBs. The results show that the splashing mechanism reproduces higher-velocity detached daughter droplets, while the momentum-induced dripping mechanism results in low velocity daughter droplets. The results also reveal that the deposited liquid film with the wires has a key role in enhancing the splashing phenomena in RPBs. The radial distribution of diameter and velocity of liquid droplets in RPB is also analyzed in light of the droplet impact dynamics. The increase in the average liquid velocity with radial direction was attributed to the increase of splashed drops, which led to a bigger number of high-velocity droplets. The conclusions of this study can be used to help improve the dynamics of the two-phase flow within RPBs through a better packing design and flow conditions.

Modeling of Oxidative Coupling of Methane for Manufacture of Olefins—Part I: CFD Simulations

This paper presents a comprehensive computational fluid dynamics (CFD) model for describing the oxidative coupling of methane (OCM) carried out in fixed-bed reactors for olefin production. Initially, a single pellet model was developed and implemented to describe the heat and mass transfer within the pellet and between the gaseous and solid phases. Subsequently, sensitivity analyses were performed to assess the impact of pellet arrangement and feed conditions on the heat and mass transfer rates, subsequently affecting concentration and temperature profiles. As indicated by the simulations, a high ethylene content could be obtained with the increase in the CH4/O2 ratio, aligning well with previous experimental studies. Furthermore, it was observed that pellet arrangement can significantly affect the reactor performance. Additionally, the behavior of temperature and concentration in the gaseous and solid phases can be very different, such that pseudo-homogeneous modeling approaches should not be assumed a priori. Finally, the simulated temperature differences between the gaseous and solid phases were very substantial and above 100 °C, indicating the occurrence of catalyst auto-ignition behavior.

Performance evaluation of a solar nano-photocatalytic reactor for wastewater treatment applications: Reaction kinetics, CFD, and scale-up perspectives

The solar-driven photocatalytic process, as a clean and efficient advanced oxidation process (AOP), is widely operated in wastewater treatment applications. In the present work, a solar nano photocatalytic reactor is designed, manufactured, and tested under different operating conditions. The irradiation-dependence reaction kinetics is studied in a batch operation process. A comprehensive computational fluid dynamics (CFD) model taking into account realistic solar flux distribution is developed and validated using experimental data. Finally, the reactor scaling-up analysis for higher treatment capacities is performed with the aim of the design of industrial-scale solar photocatalytic reactors. The research results indicate that when the initial dye concentration is increased from 5 to 175 mg/L, the period required to achieve 95% pollutant removal in 20 L solution and 10 mg/L photocatalyst concentration boosts up to 2.2 times. When the photocatalyst concentration in the solution is increased from 5 to 20 mg/L, the time required to achieve 95% total removal is reduced to 35.7%. For the photocatalyst concentration of 75 mg/L compared to 20 mg/L, the time required for 95% degradation increases up to 16.7%. To treat 90% of the total pollutant in a 50 mg/L dye solution with an initial volume of 5 m3 and using 20 mg/L photocatalyst concentration under 11 h operation with an average solar irradiation intensity of 750.46 W/m2, a solar reactor with a surface area of 50.45 m2 is required, while for 10 m3 wastewater sample and the same conditions and 95% pollutant removal, the collector area is obtained to be 121.36 m2. A horizontal solar reactor compared to its optimal tilt angle can reduce the treatment capacity up to 55%.

Numerical Simulation of Electric Arc Heating Process in the Refining Ladle

This article presents a comprehensive multiphase computational fluid dynamics model to simulate the arc heating process in the ladle. The results on temperature distribution, slag eye size, flow characteristics, and wall shear stress under three flow rate conditions are discussed. Validation of the results is carried out by comparing them with industrial measurements. The study highlights that when the flow rate increases by 100%, the temperature difference in the ladle decreases by 17.37%, while the slag eye‐opening and wall shear stress increase by 116.38% and 49.86%, respectively. The study emphasizes the details of model development and utilization of models to optimize the process.