Advanced Computational Fluid Dynamics Research Articles

Numerical investigation of the reacting flows of three adjunct raceways in an industrial-scale blast furnace

The raceway dynamics in ironmaking blast furnaces (BFs) are critical to determining energy efficiency and greenhouse gas emissions, but a comprehensive assessment of the dynamics of adjunct raceways at the particle scale has not yet been undertaken. In this study, an advanced reactive Computational Fluid Dynamics – Discrete Element Method (rCFD-DEM) approach is employed to simulate three adjacent raceways inside an industrial-scale BF. The typical in-furnace phenomena of a middle raceway between two adjunct raceways are captured from a 3D perspective for the first time. The raceway depths predicted are nearly 1.23 m, which are remarkably greater than those predicted by recent simulations, but closer to the experimental measurements. Then, the effects of blast velocity and temperature on raceway dynamics and combustion are quantified. After that, the key parameters for accurately simulating and measuring raceways are discussed. The results indicate that the suitable threshold voidage to accurately capture the raceway cavity should be 0.55, and the treatment using two adjunct raceways is much better for a natural formation of the raceway. The raceway dynamics predicted under different particle size distributions are considerably different with the deviation up to over 300%. The study forwards the particle-scale modelling of raceway dynamics and combustion to a practical 3D perspective using multiple raceways and clarifies the key parameters for the accurate simulation of raceway dynamics in BFs.

Assessing the Feasibility of Gravitational Vortex Turbines for Sustainable Energy Production in Remote Hilly Areas of Bangladesh

This research paper presents a comprehensive study of the design, optimization, and performance analysis of a gravitational vortex water turbine for small-scale hydropower applications in the Chittagong Hill Tracts of Bangladesh. The urgent need for cleaner and more efficient energy sources to address global energy challenges drives the development of innovative renewable energy solutions. The proposed turbine harnesses the power of gravity-induced water flow to efficiently convert rotational energy from a water vortex into electrical energy. The research employs advanced computational fluid dynamics (CFD) analysis using ANSYS Fluent to investigate the intricate flow behavior and velocity distribution. Through CFD calculations, the study provides valuable insights into the turbine's performance, allowing for optimization of its design parameters. The influence of blade numbers on turbine efficiency contributes to a better understanding of the turbine's operational characteristics. The paper discusses the advantages of decentralized energy systems and emphasizes the potential of gravitational vortex turbines for small-scale hydropower projects. It highlights the importance of mathematical analysis and performance results, further supported by the CFD analysis, demonstrating the turbine's capabilities. The power outputs achieved by the turbine align with or surpass the potential power capacities of identified small hydro sites, reinforcing its viability as a clean and reliable energy solution. While the research findings showcase the turbine's potential, it emphasizes the need for further feasibility studies and site-specific assessments to ensure successful real-life implementation. The study underscores the significance of utilizing advanced computational techniques in developing efficient and environmentally friendly hydropower solutions. The findings offer lessons for researchers, engineers, and policymakers for cleaner and more sustainable energy sources.

Drug transport modeling in solid tumors: A computational exploration of spatial heterogeneity of biophysical properties

Inadequate uptake of therapeutic agents by tumor cells is still a major barrier in clinical cancer therapy. Mathematical modeling is a powerful tool to describe and investigate the transport phenomena involved. However, current models for interstitial flow and drug delivery in solid tumors have not yet embedded the existing heterogeneity of tumor biomechanical properties. The purpose of this study is to introduce a novel and more realistic methodology for computational models of solid tumor perfusion and drug delivery accounting for these regional heterogeneities as well as lymphatic drainage effects.Several tumor geometries were studied using an advanced computational fluid dynamics (CFD) modeling approach of intratumor interstitial fluid flow and drug transport. Hereby, the following novelties were implemented: (i) the heterogeneity of tumor-specific hydraulic conductivity and capillary permeability; (ii) the effect of lymphatic drainage on interstitial fluid flow and drug penetration.Tumor size and shape both have a crucial role on the interstitial fluid flow regime as well as drug transport illustrating a direct correlation with interstitial fluid pressure (IFP) and an inverse correlation with drug penetration, except for large tumors having a diameter larger than 50 mm. The results also suggest that the interstitial fluid flow and drug penetration in small tumors depend on tumor shape. A parameter study on the necrotic core size illustrated that the core effect (i.e. fluid flow and drug penetration alteration) was only profound in small tumors. Interestingly, the impact of a necrotic core on drug penetration differs depending on the tumor shape from having no effect in ideally spherical tumors to a clear effect in elliptical tumors with a necrotic core. A realistic presence of lymphatic vessels only slightly affected tumor perfusion, having no substantial effect on drug delivery.In conclusion, our findings illustrated that our novel parametric CFD modeling strategy in combination with accurate profiling of heterogeneous tumor biophysical properties can provide a powerful tool for better insights into tumor perfusion and drug transport, enabling effective therapy planning.

The UHURA project at a glance – motivation and objectives

The European H2020 project UHURA is focusing on the unsteady flow behaviour around high-lift systems and will first time deliver a deeper understanding of critical flow features at new types of high-lift devices of transport aircraft during their deployment and retraction together with a validated numerical procedure for its simulation. UHURA performed detailed experimental measurements in several wind tunnels to obtain a unique data set for validation purposes of Computational Fluid Dynamics (CFD) software, including detailed flow measurements by Particle Image Velocimetry (PIV) and other optical measurement technologies. Advanced CFD methods promising significant improvements in the design lead time are validated against this database to obtain efficient and reliable prediction methods for design.

Numerical simulation of unsteady generic Newtonian blood flow and heat transfer through discrepant shaped dilatable arterial stenosis

The contemporaneous research was conducted to evaluate the attribute of blood flow and degree of obstruction generated in the arteries pathway through different geometries. Flow of blood via the stenosed afflicted arteries is taken into account in this work. The viscous, unsteady, incompressible and laminar, blood plunge into the artery with a speed of 0.049 m s−1. Partial differential equations were demonstrated for the current problem. Time dependent direct solver was used to obtain the solution. Finite element discretization method (FDM) is used to obtain the solution. The research was accomplished by using advanced computational fluid dynamics (CFD) software. The blood flow behavior was investigated in order to determine velocity, pressure, and temperature changes caused by an arterial stenosis. It was discovered that the shape of the stenosis has a crucial impact on the velocity, total pressure reduction and temperature over the arterial constriction zone. Graphs are plotted to illustrate the solutions. Results shows that the trapezoidal and elliptical stenosis had the greatest pressure decrease, followed by the triangular stenosis. These findings will be extremely beneficial in the treatment of stenotic arteries.

On the Development of CFD Methodology for Free-Falling Varnish Stream Modeling to Support EV Motor Manufacturing

<div class="section abstract"><div class="htmlview paragraph">When manufacturing the stators in EV motors, stator wires are first coated with a layer of resin to provide primary insulation. After winding, impregnating varnish fills all voids within the windings and between the windings and lamination. In addition to electrically insulating the copper wires, another function of the varnish fill is to mechanically secure the copper wires from movement. The process is not complicated in terms of physics. In essence, the mechanics of the varnish flow is the balance of inertia force, viscous force, gravity and surface tension. However, understanding the fluid dynamics of the varnish flow is critical to predicting the quality of the varnish fill, which has a tremendous impact on motor performance. With the advancement of computational fluid dynamics (CFD), the industry can benefit greatly if the varnish trickling process can be tuned, without physical tryouts, to achieve optimal fill. The intent of this research is to develop the computational methodology to study the varnish flow, so that its flow pattern can be simulated and predicted in the varnish trickling process. Because varnish flow by nature is a two-phase flow, special attention is needed to treat the large density difference between air and varnish, as well as the surface tension acting on the phase boundary. Furthermore, the well-known Plateau-Rayleigh instability associated with free-falling streams poses great challenges to the numerical method. In this research, two distinctive computational methodologies, FVM (Finite Volume Method) and SPH (Smoothed-Particle Hydrodynamics), are utilized to model the varnish free-falling streams. The end results are compared with analytical solutions and experimental observations to verify their accuracy. Also included is the comparison of numerical artifacts introduced by the two CFD methods. Another valuable achievement is the utilization of experimental results to reduce the costly computation time for reaching steady-state solution.</div></div>

Numerical investigation of labyrinth-shaft spillway

In the present study, a new type of hybrid spillway termed labyrinth-shaft spillway was introduced to improve the discharge capacity and efficiency of the spillway. An advanced computational fluid dynamics (CFD) technique was used to analyze the performance of the labyrinth-shaft spillway. The hydraulic performance of the new model was investigated for different labyrinth geometries with a verified computational model. The analysis results demonstrated that the discharge capacity of the labyrinth-shaft spillway was better when compared to that of the conventional shaft spillways with the same weir heads. The discharge coefficient that reflects the efficiency of the labyrinth-shaft spillway was also much better when compared to the conventional spillway, while the opposite was observed with relatively small nappe heads. Similarly, the comparison with the findings of previous studies on labyrinth weirs in the literature demonstrated that labyrinth-shaft spillways performed better when compared to the conventional labyrinth weirs in-channel flow conditions, especially with high nappe heads. A new formula was also developed in the present study with regression analysis conducted on the collected data to calculate the discharge coefficients of the labyrinth-shaft spillway for H/P > 0.2.

Application of machine learning (ML) and genetic algorithm (GA) to optimize window wing wall design for natural ventilation

The recent global pandemic has shown the importance of natural ventilation not only in reducing energy consumption but also in reducing airborne contamination. Long-established studies have demonstrated the advantages of window wing walls – vertical projections attached to windows that create a pressure change near the openings - to increase indoor wind flow. However, these conventional strategies to improve natural ventilation rarely take into account site-specific conditions such as dynamic wind conditions throughout the year.This research aims to find a design configuration for window wing walls to improve air circulation through careful interventions for the whole year in classrooms with conventional one-sided openings. With data-driven design, natural ventilation can be maximized to reduce the risk of contamination by insufficient fresh air.The paper utilizes the Computational Fluid Dynamics (CFD) simulations and Artificial Neural Networks (ANN) to predict indoor air movement with less computational time and load. Coupled with Genetic Algorithm (GA), the paper develops an approach that would enable increased natural ventilation in rooms with one-sided windows. Resultsshow an increase in indoor wind speed in the optimized case compared to the baseline conditions. The main contribution of this study is to demonstrate the use of advanced CFD simulation to provide designers and users with a site-specific configuration for installing fixed wing walls that can maximize indoor wind flow from different wind directions over the whole year, not just for one wind direction.

Numerical study on the effect of airflow on powder mixing in a container blender

Powder mixing is critical in many industries. Despite the wide variety of available mixers, the container blender is favored in industries due to easy manufacturing and convenient operation. As fine powders are frequently encountered in practical mixing, the presence of air during mixing may significantly impact the process. However, a scientific understanding of air–particle interactions in powder mixing has not been established so far. From a physical view, the air drag force on particles might be significant when the gas velocity is high and the particles are fine. Therefore, this novel study numerically investigates the effects of particle size and air presence on powder mixing under typical conditions, such that the relationship between particle–fluid dynamics and mixing performance is clarified for the first time. In the calculation, our advanced computational fluid dynamics–discrete element method, namely, the flexible Eulerian–Lagrangian method with an implicit algorithm, is utilized. To examine the effect of particle size on powder mixing, the coarse-grained discrete element method is employed for fine particle systems. Through the advanced numerical framework, the effect of airflow on powder mixing can be discussed in depth. The numerical results show that airflow accelerates the mixing of fine particles under the investigated rotation speeds. Based on the calculation results of the particle kinetics and fluid velocity distribution, it is clarified that the accelerated mixing results from the fine particle movement under air entrainment. How the movement of fine particles is developed is also elucidated by the continuously circulating gas flow and fluid drag force. Thus, this study provides a new understanding of the effects of airflow on powder mixing, which has not been scientifically clarified in previous studies.

IRREGULAR WAVEMAKER (PISTON TYPE) IN A NUMERICAL AND PHYSICAL WAVE TANK

This paper describes the design and execution of a wavemaker system (piston type) in the Dokuz Eylül University Hydraulic Laboratory flume to perform hydraulic model tests using regular and irregular waves. In this study, we will focus on generating the irregular waves from the target JONSWAP spectrum using an adjusted random phase method; also, the control software of the wavemaker is described. An identical numerical channel wave to the physical flume was modeled to compare and observe the irregular wave profile using Flow 3D, one of the advanced computational fluid dynamics (CFD) software. The paddle movement was validated by comparing the experimental converted irregular wave surface elevations to the wave spectrum to the numerical models of several waves.

Computational aerodynamics of insect flight using volume penalization

The state-of-the-art of insect flight research using advanced computational fluid dynamics techniques on supercomputers is reviewed, focusing mostly on the work of the present authors. We present a brief historical overview, discuss numerical challenges and introduce the governing model equations. Two open source codes, one based on Fourier, the other based on wavelet representation, are succinctly presented and a mass-spring flexible wing model is described. Various illustrations of numerical simulations of flapping insects at low, intermediate and high Reynolds numbers are presented. The role of flexible wings, data-driven modeling and fluid–structure interaction issues are likewise discussed.

Thermal performance assessment of a retrofitted building using an integrated energy and computational fluid dynamics (IE - CFD) approach

The comfort of the occupant in the indoor thermal environment can be efficiently analysed using the principle of computational fluid dynamics (CFD) technique. This can be modelled as a difference of measure of a region equivalent to air circulation and diffusion in/out of the area. Other parameters influence the room operating condition and energy consumption by the building systems directly and indirectly over a period of time. This paper represents how to use comfort theory and CFD concepts to do a computational study of building comfort and improve the energy performance of the building during the summer and winter seasons in the subtropical climate. The occupants’ overall comfort evaluation results in the chosen building are recorded, taking into account the suitable climate-responsive heating, ventilation and air conditioning approach and envelope systems. The thermal CFD simulation model used in this study incorporates the most current turbulence simulation methodology appropriate for airflow modelling in buildings. The numerical comfort analysis methodology is used to analyse the indoor thermal condition, considering the Cooled Beam cooling system and BioPCM as an envelope solution for possible retrofitting. The simulation findings show that the uniform temperature distributions observed during working hours are adequate and demonstrate improved energy performance by the building systems. Moreover, the results suggest that the use of advanced computational fluid dynamics techniques is a valuable method for the analysis of human comfort in indoor spaces.

Shape design of channels and manifolds in a multichannel microreactor using thermal-fluid compartment models

In the design of microreactors, the shape as well as the size is an important design factor for achieving high performance. Recent advances in computational fluid dynamics (CFD) enable us to know flow and temperature distributions in microreactors of various shapes and sizes without conducting experiments. However, it is often important to develop a simpler model than CFD to further reduce the computational time required for reactor design with iterative performance evaluations. In this research, a thermal-fluid compartment model-based approach is proposed for basic design of a multichannel microreactor. The proposed approach consists of two parts, i.e., thermal design and fluid design. In the thermal design part, two types of thermal compartments, which are used to discretize a reaction channel surrounded by wall and describe the mass and heat balances over the channel, are developed to optimize the channel shape. In the fluid design part, three types of fluid compartments, which are used to discretize the reactor and describe the mass and pressure balances over the reactor, are introduced to optimize manifold shape. The proposed approach is applied to a design problem and the results show that microchannels and manifolds with varying width are effective in realizing the uniform temperature and flow distributions, respectively. In addition to the proposed design approach, a transfer function-based compartment model is developed to estimate the residence time distribution of fluid in a microreactor without running time-dependent CFD simulation.

Diesel Engine Cylinder Liner Distortion Analysis

Internal Combustion Engine is the heart of any automobile. Hence its performance directly affects the performance of automobile. To measure the performance of engine is an important aspect. When the engine is in working, due to high combustion gas pressure and temperature heat is generated inside the cylinder that heat is transferred to the cylinder wall, crank case oil and piston. In this report, the distortion of cylinder bore has been analyzed. As for the tri biological system, the ideal conditions for the function and durability, shape of liner should be circular as possible. The distortion of the cylinder liners of internal combustion engines has significant effect on engine operation .It can affect the oil consumption, the blow-by, the wear behavior and due to friction, fuel consumption. In order to achieve future requirements regarding exhaust emissions and fuel consumption the development of low distortion engine blocks will play significant role. The calculation of engine heat transfer is difficult, due to the periodic air and fuel flow and the complex geometry of the engine. We rely primarily on experimental results. With recent advances in computational fluid dynamics, computation of engine heat transfer is becoming more possible

Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders.

Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices (PI and RI), the interpretation of such metrics for disease assessment relies on ad hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer parameters, such as vascular resistance, compliance, and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with branching carotid artery and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

Review on validation techniques of blade element momentum method implemented in wind turbines

There are two broad kinds of energy sources: renewable and non-renewable. In the renewable energy sector, significant advancements have been made in wind energy, the world’s fastest-growing renewable energy production technology. Despite this rapid development, the wind industry must still strive to ensure that any device designed for commercial use is reliable and its performance satisfies its economic projections. The critical factor in achieving this target is rotor aerodynamics because the rotor is the part that mainly reacts with the wind. When designing a wind turbine, the assessment of the aerodynamic characteristics of the blades must be accurate. Errors may result in wrong estimates of the turbines’ performance and economic projections. If experimental measurements cannot determine these characteristics, a designer will use alternative methods. Several modeling methods have proven viable solutions for design and analysis purposes, like Blade Element Momentum (BEM) methods. BEM methods analyze the aerodynamic performance of wind turbines, but it requires validation to examine the accuracy of its results. This paper highlights and reviews BEM validation techniques implemented in wind turbine aerodynamics analyses. BEM is validated against experimental data and other advanced models, namely, higher-order vortex and CFD (Computational Fluid Dynamics) models. Nevertheless, the experimental data are essential in wind turbine studies for both understanding the aerodynamic mechanisms and validating all these models.

Numerical model of an ultrasonically induced cavitation reactor and application to heavy oil processing

This study describes a numerical approach to model ultrasonically induced cavitation (UIC) reactors. UIC forms vapour-filled cavities in a liquid medium due to an applied acoustic field and their eventual collapse. UIC reactors are characterized by the presence of a vibrating probe that generates pressure waves by high-frequency oscillations (>20 kHz), which control the formation, dynamics, and eventual collapse of the vapour cavities. Those vapour cavities eventually enhance mixing and favour the occurrence of gas-liquid reactions. The zones of high mixing and reactivity coincide with the presence of the bubble cloud, which depends on the shape of the vessel and sonotrode. The development of advanced computational fluid dynamics (CFD) models is crucial to optimizing UIC processes’ geometry and operation parameters. A new algorithm for modelling UIC has been implemented within the OpenFOAM framework in the present study. The volume-of-fluid (VoF) method employs a diffuse interface approach for the volume fraction transport equation. The bubble dynamics are solved with sub-grid models, and the coupling between the main flow field and the sub-grid scales is performed through source terms in the transport equations. The source terms are de-coupled from convective and diffusive components of the volume fraction equation. The history of the bubbles is considered to consist of nucleation, oscillations, and collapse. The oscillations are resolved via the Rayleigh–Plesset equation. The concluding part of the work demonstrates the application of the algorithm to simulate the operation of an UIC reactor, which was designed to desulfurize fuels using the oxidative (ODS) process.

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications.In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume.Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

Heat transfer and mixing enhancement by Poiseuille-Taylor-Couette flow between two rotating elliptically-deformed annular tubes

Multifunctional heat exchangers (HEX) are very important devices which are used in many industrial applications (aerospace, aeronautics, automobile, process and chemical engineering, etc). Improving their designs for an optimal overall performance is still a wide window for both research and development. In the present contribution, a new HEX design is proposed as two concentric elliptically-deformed tubes of complex geometry. Employing advanced computational fluid dynamics (CFD), we show how a combined Poiseuille-Taylor-Couette (PTC) analogous flow between two rotating concentric elliptically-deformed annular tubes, can efficiently enhance heat and mass transfer at low to medium Reynolds numbers (Re≤488). Furthermore, we illustrate how chaotic advection can be controlled by regulating the local flow inertia and rotational forces imposed by a combined flow between: i- Poiseuille flow, and ii- Taylor-Couette analogous flow that is generated by interchanging the clockwise/anticlockwise rotation of the inner and outer walls. Results are presented and discussed using Lagrangian tracking and Poincaré sections techniques that describe the different underlying physical phenomena of mixing and heat transfer.

3D Numerical Modeling and Quantification of Oblique Wave Forces on Coastal Bridge Superstructures

Simply supported bridges comprise the majority of bridge systems in coastal communities and are susceptible to severe damage from extreme waves induced by storms or tsunamis. However, the effects of oblique wave impacts have been less investigated due to the lack of appropriate numerical models. To address this issue, this study investigates the effects of wave incident angles on coastal bridge superstructures by developing an advanced computational fluid dynamics (CFD) model. Different wave scenarios, including wave height, relative clearance, incident angle, and wavelength are tested. It is found that the maximum wave forces in the horizontal and longitudinal directions could reach 1901 and 862 kN under extreme conditions, respectively, destroying bearing connections. Three surrogate models, i.e., the Gaussian Kriging surrogate model, the Artificial Neural Network (ANN), and the Polynomial Chaos Expansion (PCE), are established by correlating the wave parameters with the maximum wave forces. Through comparisons among the three surrogate models, it is found that the 3-order PCE model has better performance in predicting loads in vertical and horizontal directions, while the ANN model is more suitable for results in the longitudinal direction. This study contributes to the optimized design of coastal bridges and also offers an opportunity for future studies to investigate hazard damage-mitigation measures.