Computational Fluid Dynamics Method Research Articles

Investigation of the aerodynamic performance of the dragonfly-inspired tandem wings considering the coupling between the stroke plane and phase difference

The dragonfly's tandem wings can make full use of the interference of various spatial vortices to obtain efficient flight capability. The complex coupling among multiple motion parameters will have an important influence on the interference between the forewing (FW) and hindwing (HW). In this paper, the aerodynamic performance of the dragonfly-inspired tandem wings is analyzed using the Computational Fluid Dynamics (CFD) method considering the coupling effect of the stroke plane and phase difference. The variation of the force coefficient, vortex structure and aerodynamic efficiency of the tandem wings in forward flight are analyzed, respectively. The results show that the stroke plane angle affects the distribution of the leading edge vortex (LEV) and trailing edge vortex (TEV), which primarily controls the trend of horizontal force variation. The phase difference of tandem wings will change the fluctuation of the horizontal force coefficient curve by affecting the meeting time of the forewing and hindwing. However, with the increase of stroke plane angle, the fluctuation of aerodynamic coefficient caused by phase difference will decrease. The propulsion efficiency(η) and power loading(PL) can be improved through increasing the stroke plane angle and selecting a reasonable phase difference. The conclusion can provide theoretical guidance for the design of the dragonfly-inspired tandem flapping wing aircraft (DTFWA) and the choice of motion parameters.

Physics-informed neural networks and higher-order high-resolution methods for resolving discontinuities and shocks: A comprehensive study

Addressing discontinuities in fluid flow problems is inherently difficult, especially when shocks arise due to the nonlinear nature of the flow. While handling discontinuities is a well-established practice in computational fluid dynamics (CFD), it remains a major challenge when applying physics-informed neural networks (PINNs). In this study, we compare the shock-resolving capabilities of traditional CFD methods with those of PINNs, highlighting the advantages of the latter. Our findings show that PINNs exhibit less dissipative behavior compared to conventional techniques. We evaluated the performance of both PINNs and traditional methods on linear and nonlinear test cases, demonstrating that PINNs offer superior shock-resolving properties. Notably, PINNs can accurately resolve inviscid shocks with just three grid points, whereas traditional methods require at least seven points. This suggests that PINNs are more effective at resolving shocks and discontinuities when using the same grid for both PINN and CFD simulations. However, it’s important to note that PINNs, in this context, are computationally more expensive than traditional methods on a given grid.

Numerical Simulation Study on the Stable Combustion of a 660 MW Supercritical Unit Boiler at Ultra-Low Load

To investigate the safe, stable, and economically viable operation of a boiler under ultra-low-load conditions during the deep peaking process of coal-fired units, a numerical simulation study was conducted on a 660 MW front- and rear-wall hedge cyclone burner boiler. The current research on low load conditions is limited to achieving stable combustion by adjusting the operating parameters, and few effective boiler operating parameter predictions are given for very low-load conditions, i.e., below 20%. Various burner operation modes under ultra-low load conditions were analyzed using computational fluid dynamics (CFDs) methods; this operation was successfully tested with six types of pulverized coal combustion in this paper, and fitting models for outlet flue gas temperature and NOx emissions were derived based on the combustion characteristics of different types of pulverized coal. The results indicate that under 20% ultra-low-load conditions, the use of lower burners leads to a uniform temperature distribution within the furnace, achieving a minimum NOx emission of 112 ppm and a flue gas temperature of 743 K. Coal type 3, with the highest carbon content and a calorific value of 22,440 kJ/kg, has the highest average section temperature of 1435.76 K. In contrast, coal type 1 has a higher nitrogen content, with a maximum cross-sectional average NOx concentration of 865.90 ppm and an exit NOx emission concentration of 800 ppm. The overall lower NOx emissions of coal type 3 are primarily attributed to its reduced nitrogen content and increased oxygen content, which enhance pulverized coal combustion and suppress NOx formation. The fitting models accurately capture the influence of pulverized coal composition on outlet flue gas temperature and NOx emissions. This control strategy can be extended to the stable combustion of many kinds of coal. For validation, the fitting error bar for the predicted outlet flue gas temperature based on the elemental composition of coal type 6 was 8.09%, whereas the fitting error bar for the outlet NOx emissions was only 1.45%.

Heat Transfer Analysis of Cooling Structure of Deuterium-Tritium Fusion Neutron Generator Target

A deuterium-tritium fusion neutron generator can produce high-intensity monoenergetic neutrons, which is important for the research and development of nuclear technology, and the neutron target is one of the crucial components of a neutron generator. For the neutron target, the most important technical index is the temperature of the target. Excessive temperature could impact the efficiency of nuclear reactions on the target surface and lead to target damage. Consequently, the thermal-hydraulic performance of the neutron target is significant for the performance of the neutron generator. In this paper, a curved channel with surface grooves was designed for the neutron target of a high-intensity neutron generator under design. The influence and mechanism of the curved angle and groove angle on the thermal-hydraulic performance of the minichannel were studied with the computational fluid dynamics method. The results indicated that a 45-deg curved channel with 135-deg surface grooves could enhance the turbulence within the minichannel, effectively improving the heat transfer performance of the neutron target with less pressure loss. Thus, the neutron target could withstand a higher-energy deuterium beam bombardment, increase neutron yield, and ease the pressure requirements on the cooling water pumps and sealing components.

Influence of a City Block on ES-CFD Coupled Analysis

Coupled analysis using the complementary methods of energy simulation (ES) and computational fluid dynamics (CFD) can improve the calculation accuracy of thermal environment simulations. However, existing studies on ES-CFD coupled analyses that consider the effects of solar radiation and surrounding conditions have been insufficient. In practice, net solar radiation fluctuates, owing to the influence of urban blocks, and the solar radiation incident on the interior determines the heating range of the interior, which results in fluctuations in the convective heat transfer coefficient. This study conducted an ES-CFD coupled analysis to examine differences in the convective heat transfer coefficients due to the different insolation conditions and the surroundings of target buildings. The risk of condensation was evaluated using the dew point temperature in the analysis model, and a neutral insulation performance was employed in the set cases with the presence or absence of urban streets as a variable. Buildings within urban city blocks were observed to have a lower dew point temperature and a higher risk of condensation, which is a reasonable assessment. The results of this study will contribute significantly to the development of comprehensive simulation technologies.

Numerical investigation of thermal-flow processes in the ejector-condenser for selected geometrical parameters

The paper presents the results of analysis of thermal-flow processes in the ejector-condenser for selected geometrical param-eters using CFD (Computational Fluid Dynamics) methods. The ejector-condenser is the water-driven, two-phase ejector responsible for creating a sub-pressure allowing exhaust gases (steam and CO2 mixture) to be entrained, condensing steam, and then increasing the pressure above the atmospheric conditions. The axisymmetric numerical model was developed to take into account multiphase, turbulent flow with steam condensation in the presence of inert gas. The influence of the selected geometrical parameters, such as the motive nozzle's and mixing chamber's diameters on the ejector performance was investi-gated. CFD analysis results are presented in the form of developed scalar distributions as well as pressure, temperature and steam mass flow changes along the flow path. Performances for different geometry modes were calculated and compared using parameters such as compression ratio, expansion ratio, mass entertainment ratio and condensation efficiency. The max-imum achieved compression ratio for the analyzed geometrical variants is 1.113 for the assumed mass entertainment ratio of 0.0295. The condensation efficiency varies in a range of 49.6%–91.4% depending on motive fluid inlet conditions and geom-etry mode.

A study on the thermal behavior of coal gangue mountains under airflow influence based on MD and CFD simulations

The long-term accumulation of coal gangue can lead to an increase in internal temperature. If the temperature becomes excessive, it can cause spontaneous combustion, posing serious environmental risks. The process is significantly influenced by external airflow. This study analyzes the thermodynamic properties and oxidation heat release rate of coal gangue samples through laboratory experiments. Subsequently, molecular dynamics (MD) simulations are used to investigate the mechanism of oxidation heat release during the heating process of coal gangue under varying oxygen supply conditions. Based on these findings, a coupled three-field model for the heating process of coal gangue mountains is developed. Using computational fluid dynamics (CFD) methods, transient simulations are conducted to analyze the internal thermal behavior of coal gangue mountains under the influence of external airflow, clarifying the risks of spontaneous combustion. The results indicate that after reaching T2 (295.16 °C), coal gangue enters an accelerated oxidation phase, with an increased heat release rate, heightening the risk of spontaneous combustion. The oxidation heat release rate of coal gangue accelerates with rising temperature and oxygen concentration, entering a rapid reaction phase after 300 °C, with a sharp increase in reaction rate. Compared to N2, coal gangue surfaces exhibit stronger adsorption of O2, and temperature changes affect N2 diffusion more sensitively (O2 diffusion coefficient increases by 0.312 Å2/ps, N2 diffusion coefficient increases by 0.334 Å2/ps). The isosteric heat of O2 adsorption in coal gangue decreases significantly with increasing adsorption amount, and higher temperatures hinder competitive adsorption of O2. The temperature in the deep and foot areas of the coal gangue mountains is lower, while the middle and upper areas near the slope surface exhibit higher temperatures, indicating a higher risk of spontaneous combustion in these regions. When environmental wind speed is too high or too low, both the internal temperature of the coal gangue mountains and the area of spontaneous combustion risk zones decrease. At a wind speed of 3 m/s, the spontaneous combustion risk zone reaches its maximum area of 73.47 m2, but when the wind speed increases to 7 m/s, the risk area decreases to 65.72 m2.

Numerical Study of Hydrogen-Rich Fuel Coherent Jet in Blast Furnace Tuyere

Injecting hydrogen-rich fuel into blast furnaces is an effective strategy to reduce carbon dioxide (CO2) emissions. The present study established a three-dimensional (3D) model based on a coherent jet of hydrogen-rich fuel. The combustion characteristics and the flow, heat, and mass transfer behaviors in the reaction region were simulated by the Computational Fluid Dynamics (CFD) method. The effects of fuel jet velocity on the distributions of gas velocity, temperature, and species in the reaction region were systematically analyzed. The results show that hydrogen-rich fuel burned around the main jet, generating a high-temperature, low-density flame. As flame length increased, the main jet experienced less decay. The outward expansion of the jet caused continuous diffusion of gas temperature and its components. As the fuel jet velocity increased, the temperature along the main jet centerline rose sharply, while the length of the high-concentration gas region extended. Doubling the jet velocity increased its centerline velocity by 11% and raised the average reaction region temperature by 4.12%. The obtained highlighted results are of paramount importance for optimizing hydrogen-rich smelting in blast furnaces.

Numerical analysis of the influence of cooling design on temperature uniformity in the large proton exchange membrane fuel cell stack

The temperature distribution has a significant influence on the performance and lifespan of proton exchange membrane fuel cell (PEMFC) stacks. However, analyzing the temperature distribution of large PEMFC stacks is challenging and has been rarely conducted. In this study, a simplified model of a large PEMFC stack is developed using computational fluid dynamics (CFD) methods, which includes 300 cells and 60 cooling plates. The influence of cooling parameters, including configurations, dimension and flow rate, is discussed. The study indicates that U-type stack exhibits better temperature uniformity than Z-type stack. Increasing the coolant flow rate can effectively reduce the stack temperature. The study proposes a modified cooling design, which effectively reduces the heat accumulation at the end of the stack. Lastly, a comparison between traditional serpentine channels and porous foam metal flow fields reveals that the porous foam metal flow field exhibits superior thermal management characteristics. The results can offer insights for thermal management of large-scale PEMFC stacks.

Development of a Novel Tailless X-Type Flapping-Wing Micro Air Vehicle with Independent Electric Drive

A novel tailless X-type flapping-wing micro air vehicle with two pairs of independent drive wings is designed and fabricated in this paper. Due to the complexity and unsteady of the flapping wing mechanism, the geometric and kinematic parameters of flapping wings significantly influence the aerodynamic characteristics of the bio-inspired flying robot. The wings of the vehicle are vector-controlled independently on both sides, enhancing the maneuverability and robustness of the system. Unique flight control strategy enables the aircraft to have multiple flight modes such as fast forward flight, sharp turn and hovering. The aerodynamics of the prototype is analyzed via the lattice Boltzmann method of computational fluid dynamics. The chordwise flexible deformation of the wing is implemented via designing a segmented rigid model. The clap-and-peel mechanism to improve the aerodynamic lift is revealed, and two air jets in one cycle are shown. Moreover, the dynamics experiment for the novel vehicle is implemented to investigate the kinematic parameters that affect the generation of thrust and maneuver moment via a 6-axis load cell. Optimized parameters of the flapping wing motion and structure are obtained to improve flight dynamics. Finally, the prototype realizes controllable take-off and flight from the ground.

Calibration of the Reynolds stress model for turbulent round free jets based on jet half-width

Reynolds stress model (RSM) turbulence models are expected to yield more accurate numerical results for flows with strong anisotropy, such as round free jets, because they directly solve Reynolds stresses rather than modeling them. However, when computational fluid dynamics (CFD) analyses were performed at moderate jet Reynolds numbers using the isotropization by production (IP) RSM model, it was observed that the calculated jet half-widths, decay constants, and spreading rates differed from experimental results due to uncertainties inherent in the turbulence model. In this study, the closure coefficients of the IP RSM turbulence model were calibrated using a variant of the Multi-Objective Genetic Algorithm based on jet half-width data obtained experimentally in the near-field region of the jet. With the use of appropriate discretization schemes and computational grids, the calibrated coefficient combination for the IP RSM turbulence model showed improved accuracy in modeling jet half-widths at Reynolds numbers of 10 000 and 20 000, reducing the errors of calculated decay constants and spreading rates approximately from 2% to 1% and from 16% to 5%, respectively. A detailed examination of the turbulence budget along the longitudinal axis in the self-similar region revealed that the new model coefficients enhanced the modeling of diffusion term but compromised the advection term. As a result of the altered advection term, increased error margins were observed in turbulence intensity (TI) and velocity distribution along the jet centerline, although dissipation along the axis was improved. Consequently, the modeling error in jet half-width calculations using the CFD method was decreased, enhancing the computational cost-effectiveness of the RSM turbulence model compared to more complex turbulence models.

Analysis and prediction of denitration performance of Mn1Co0.5Cr0.5Ox catalyst based on CFD and BP-GA method

Based on the experimental data of Mn1Co0.5Cr0.5Ox catalysts and the component transport model in Computational Fluid Dynamics (CFD), a kinetic model for the standard NH3-SCR (NH3 selective catalytic reduction) process was effectively established. The objective of the model development was to predict the denitrification reaction rate of the catalyst, which incorporates various factors such as the Arrhenius parameters (Pre-exponential factor and activation energy), inertial resistance, viscous resistance, and surface-to-volume ratio. To verify the practicability of the model, simulation results were compared with actual experimental data. The effects of NH3, NO, O2 concentrations, and gas hourly space velocity (GHSV) on NO conversion were simulated and analyzed. Subsequently, the NO conversion prediction model was trained and established using a combination of numerical simulation results, back-propagation neural network, and genetic algorithm (BP-GA). Furthermore, the significance of the impact that various factors had on the denitrification activity of the catalyst was determined.

3-D full-field reconstruction of chemically reacting flow towards high-dimension conditions through machine learning

Monitoring chemically reacting flow is crucial for optimizing and controlling the conversion processes in various chemical engineering scenarios. These processes are often influenced by multiple factors, creating a high-dimensional condition space that imposes intensive computational cost to computational fluid dynamics (CFD) methods. We present a machine learning (ML) framework to reconstruct the 3-D scalar field preserving the accuracy and resolution of CFD modeling. We demonstrate the framework’s effectiveness through a case study on biomass combustion in an industrial-scale grate furnace, which exemplifies the challenges of modeling chemically reacting flow in complex geometric domains influenced non-linearly by multiple parameters. The framework implements three core principles: (1) a Reactor-Structure-Resembled Network (RSRNet) reflecting the operational logics of the reactor, (2) an incremental learning strategy based on random Latin Hypercube Sampling, and (3) the incorporation of self-extracted high-level features from data as soft constraints in the loss function. Ground truth data were calculated through a CFD model, with all cases sampled from a 11-variable condition space. Using only 240 randomly sampled cases (around 1 % total cases in the discretized condition space), RSRNet precisely replicated 1-D and 2-D scalar distributions through incremental training. Further reconstruction of 3-D temperature field only used 40 3-D CFD cases, resulting in the training and testing errors decreased to 7.94 × 10-4 and 1.55 × 10-3, respectively, approaching the level of the 2-D reconstruction, with the average error in temperature field predictions not exceeding 50 K. The generalization ability was validated using a separate test dataset with continuously changing excess air ratio and capacity ratio in wide ranges, including some extreme values, and the model successfully captured complex phenomena under unseen conditions.

Novel passive flow control method using leading-edge prism-shaped cylinder: Performance enhancement of vertical-axis wind turbines

Due to periodic dynamic stall at low tip speed ratios (TSRs), vertical-axis wind turbines (VAWTs) experience notable performance challenges during rotation, which leads to fluctuations in torque and a decrease in energy capture. This research aims to boost the aerodynamic performance of Darrieus VAWTs by employing a leading-edge (LE) prism cylinder (PC) to enhance energy extraction. This novel small-scale device functions as a passive method for controlling flow separation, aiming to energize the boundary layer and adjust the pressure distribution on the blades. Its effectiveness depends on factors such as size, shape, and placement, necessitating careful optimization. A three-dimensional (3D) computational fluid dynamics (CFD) analysis, combined with Taguchi optimization and analysis of variance, is conducted to determine the optimal design parameters for the LE PC tool. This 3D CFD method captures the full complexity of flow dynamics, including vortex structures and wake behavior, leading to more accurate wind turbine performance predictions than two-dimensional (2D) CFD models. The results highlight the crucial role of PC size (Factor A), which contributes nearly 85% to the total contribution factor, while the angle of PC influence is minimal. The optimized rotor demonstrates a 36% increase in maximum average power coefficient (CP) compared to an uncontrolled rotor at TSR = 1.5. However, the effectiveness of this control method diminishes at higher TSRs because the blades encounter angles of attack below the critical stall angle throughout the rotation cycle, naturally preventing flow separation and making the flow separation control method unnecessary. The PC installed on the optimized blade delays flow separation to 55% of the blade chord length, compared to 40% for the base blade. Consequently, the rotor operates efficiently, ensuring consistent, and reliable power generation without flow separation issues.

Evaluation and optimization of interventional blood pump based on hydraulic performances and hemocompatibility performances

This study was designed to investigate the effects of hemodynamic environment and design factors on the hydraulic performance and hemocompatibility of interventional blood pumps using computational fluid dynamics methods combined with specialized mathematical models. These analyses assessed how different hemodynamic environments (such as support mode and artery size) and blood pump configurations (including entrance/exit blade angles, rotor diameter, blade number, and diffuser presence) affect hydraulic performance indicators (rotational speed, flow rate, pressure head, and efficiency) and hemocompatibility indicators (bleeding, hemolysis, and thrombosis). Our findings indicate that higher perfused flow rates necessitate greater rotational speeds, which, in turn, reduce both efficiency and hemocompatibility. As the artery size increases, the hydraulic performance of the pump improves but at the cost of worsening hemocompatibility. Among the design parameters, optimal configurations exist that balance both hydraulic performance and hemocompatibility. Notably, a configuration without a diffuser demonstrated better hydraulic performance and hemocompatibility compared to one with a diffuser. Further analysis revealed that flow losses primarily contribute to the degradation of hydraulic performance and deterioration of hemocompatibility. Shear stress was identified as the major cause of blood damage in interventional blood pumps, with residence time having a limited impact. This study comprehensively explored the effects of operating environment and design parameters on catheter pump performance using a multi-faceted blood damage model, providing insights into related complications from a biomechanical perspective. These findings offer valuable guidance for engineering design and clinical treatment.

Savonius wind turbine blade selection based on computational fluid dynamics

The Savonius vertical axis wind turbine is widely used because of its simple design and efficiency at low wind speeds. The next development is the mini multi-blade Savonius helical wind turbine. At this miniature size, the performance of a mini multi-blade helical Savonius turbine due to variations in the number of blades and its impact on the energy produced has not been investigated in depth. Therefore, adjustments to the size and number of blades need to be made to optimize the performance of this turbine. The research aims to obtain the performance of the Savonius type S wind turbine with 3 blades and 4 blades using the CFD (Computational Fluid Dynamics) method. The main dimensions of the simulation model are the shaft diameter of 0.008 m, the outer diameter of 0.24 m, the height of 0.4 m, and the number of blades 3 and 4. The inner diameter of the 3-blade turbine is 0.21 m while the inner diameter of the 4-blade turbine is also 0.21 m. Both turbine models are subjected to wind speeds of 4 m/s, 5 m/s, and 6 m/s. Based on the simulation results, a turbine with 4 blades has more optimal performance compared to the 3-blade type. At a wind speed of 6 m/s, the 4-blade Savonius helical turbine produces a rotation of 498,215 rpm and a maximum power of 6,129 watts. Meanwhile, the Savonius turbine with 3 blades at a wind speed of 6 m/s produces a rotation of 545,655 rpm and a maximum power of 4,390 watts. This difference in performance shows the importance of adjusting the number of blades in wind turbine design to achieve optimal efficiency. This research provides useful insights for the further development of mini helical Savonius wind turbines in various wind conditions

Study on oil film spreading characteristics on the jet lubricating tooth surface of aviation herringbone gear

Purpose During the oil lubrication process of aviation herringbone gears, lubricating oil is injected into and spreads around the tooth surface. Its spreading characteristics directly affect the lubrication state and transmission efficiency of gears. This study aims to investigate the effect of changing the injection parameters and gear operating conditions on the oil film deposition during injection lubrication. Design/methodology/approach The computational fluid dynamics method was used to establish the computational domain for the simulation and optimization using an orthogonal test. The oil film spreading and thickness of the tooth surface were calculated with the change in gear speed, fuel injection distance and fuel injection speed. Optimized oil injection lubrication parameters were obtained, and design ideas were provided for the oil injection lubrication analysis of aviation herringbone gears. Findings Under different operating conditions, such as varying the injection speed, gear rotational speed and injection distance, there were differences in the distribution of the lubricating oil film formed on the tooth surface. The thickness of the oil film decreases as the distance from the injection port increases. The thickness of the oil film deposition can be increased by increasing the injection velocity and reducing the gear rotation speed. The injection distance had a relatively small effect on the spreading thickness of the deposited oil film, affecting only the dynamic spreading process of oil film deposition. Furthermore, the simulation results are compared with the analytical calculation results, and finally the experimental verification is carried out. Originality/value Oil spray lubrication characteristics are important for achieving precise gear lubrication designs in the aerospace field. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0250/

Research on the Influence of Rectifying Orifice Plate on the Airflow Uniformity of Exhaust Hood

Designing and improving collection systems for dust and toxic pollutants is crucial for improving the safety and indoor air quality of laboratory buildings. Push–pull ventilation systems with uniformly distributed parallel airflow have been proven to be of great help in this task. Designing exhaust hoods with parallel airflow distribution can effectively enhance the airflow uniformity of push–pull ventilation systems, especially when combining it with the implementation of rectifying orifice plates on the exhaust hoods. Therefore, this study combines a computational fluid dynamics (CFD) method and experimental approach to analyze the influence of key factors that lead to improvements in the airflow uniformity through the use of rectifying orifice plates, namely the aperture and porosity, as well as the number of rectifying orifice plates on the airflow uniformity of exhaust hoods. The study shows the following: (1) The aperture of the rectifying orifice plate considerably affects the airflow uniformity of the exhaust hood. Specifically, near the exhaust hood outlet, the airflow uniformity is negatively correlated with the aperture; conversely, near the exhaust hood inlet, the airflow uniformity is positively correlated with the aperture. (2) A rectifying orifice plate with a porosity of 35.43% can effectively improve the airflow uniformity of the exhaust hood. (3) Exhaust hoods with a double-layer rectifying orifice plate structure can improve airflow uniformity by approximately 40% compared to those with a single-layer structure. The above research results can guide the optimization of exhaust hood design to improve airflow uniformity, thereby effectively enhancing the capture efficiency of the push–pull ventilation system for dust and toxic pollutants and providing a safer environment for experimenters in laboratory buildings.

Validated kinetic modelling of ladle furnace process for predicting inclusions in API steel grade

A kinetic model of ladle furnace (LF) process is developed in C++ format using the FactSage database and ChemApp subroutines. The model considers all the process parameters such as ferroalloy and slag dissolution, wire additions, electrical arcing, steel/slag reactions, reoxidation due to slag eye opening, heat exchange between metal/slag, and refractory dissolution. Further, a correlation for inclusion removal rate was developed as a function of argon flow rate, using discrete phase method (DPM) in Computational Fluid dynamics (CFD). Lollypop samples from steel bath and slag samples were collected from the plant for API steel grade for chemical analysis and inclusion characterisation. At LF_in, the inclusions found were mostly alumina spinel with very low amount of Mg (∼3%), followed by spinel at intermediate stage having ∼15 wt. % of Mg and after Ca treatment, inclusions transformed into CaS and Calcium Aluminate type of inclusions. Overall inclusion weight fraction varied from 136 ppm at LF_in to 93 ppm at LF_out. The model calculations were found to give very good prediction for steel and slag chemistry, and inclusion global composition as compared to the plant results. Predicted temperature was found with an accuracy of ± 5 oC, while the calculated inclusion weight fraction was having an accuracy of ±12 ppm.

Research and Analysis of the Small Disturbance Equation in Subsonic, Transonic, and Supersonic Regimes

This paper explores the application of the Small Disturbance Equation (SDE) across subsonic, transonic, and supersonic flow regimes. Derived from the Euler and Navier-Stokes equations, the SDE offers an efficient framework for analyzing aerodynamic behaviors, particularly through the utilization of discretization techniques and iterative solving methods executed in Python. The study assesses the accuracy and limitations of the SDE in detailing essential flow characteristics, revealing that while the equation performs effectively in subsonic and transonic flows, it encounters challenges in supersonic regimes. Nonlinear effects such as shock waves significantly hinder its performance at high speeds. Compared with conventional computational fluid dynamics (CFD) methods, the SDE stands out in scenarios where computational efficiency is paramount. However, its limitations in handling high-speed flows must be carefully considered, highlighting the need for further refinement in its application to supersonic dynamics. This analysis suggests that while the SDE is beneficial for certain aerodynamic studies, its scope and utility are constrained by the inherent complexities of high-speed fluid dynamics.