Computational Fluid Dynamics Optimization Research Articles

CFD design and optimization of a multi-probe device for temperature measurements in Waste-to-Energy plants

The temperature of exhaust gases is an essential parameter to monitor in Waste-to-Energy (WtE) plants, since it significantly affects energy efficiency, pollutant emissions and materials’ integrity. Current methods for monitoring gas temperature in such plants (i.e., thermocouples, infrared pyrometers, and aspirated thermocouples) exhibit shortcomings in both accuracy and reliability when used in environments where radiative heat exchange plays an important role. In previous research, by means of Computational Fluid Dynamics (CFD) simulations, the authors designed a new multi-probe device, with the aim of mitigating the issues associated with these commonly adopted techniques. The newly designed measuring device is herein further characterized by means of multi-region CFD simulations, to investigate any local thermal-fluid dynamics effects which may impair the measurement, due to the mutual influence of the ducts where the sensors are located. Results have shown that the mutual influence is not significant, confirming the validity of the designed shape.

Numerical simulation of optimizing the swing curve of a 3DOF biomimetic pectoral fin in drag mode

In response to the optimization problem of the motion law of the pectoral fins of biomimetic robotic fish, this paper uses computational fluid dynamics (CFD) methods to achieve the CFD optimization of two types of rigid biomimetic pectoral fins with three degrees of freedom (DOF): elliptical and 8-shaped swing curves. By analyzing the hydrodynamic characteristic curve of the pectoral fins, pressure distribution upstream and downstream of the fin surface, velocity vector of the surrounding flow field during pectoral fin swing, and three-dimensional vortex structure, it is found that when the pectoral fins are pushed forward in an elliptical swing curve, the resistance peak value decreases after two optimizations. However, at the same time, a certain amount of thrust is lost. When the pectoral fin advances in an 8-shaped swinging curve, after two optimizations, the pectoral fins resistance decreases while maintaining an enormous thrust, comprehensively improving the propulsive effect of the pectoral fin on the robotic fish. By substituting the optimized 8-shaped pattern into the robotic fish model, it is found that the flapping angle of 35° has better drag reduction performance, and the average swimming speed of the robotic fish is the fastest at this angle.

FEA and CFD analysis and optimization of tube in tube heat exchanger for various cases

This research describes the use of advanced simulation techniques to investigate use of different materials for a tube-in-tube heat exchanger. Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations are employed to simulate thermal aspects and optimize the heat exchanger design. The objective is to identify the best-Suitable material combination considering both design and thermal considerations. The findings of this research contribute to the development of more efficient heat exchanger designs.

Novel CFD and DMST Dual Method Parametric Study and Optimization of A Darrieus Vertical Axis Wind Turbine

The deteriorating effects of greenhouse gases resulting from the use of fossil fuels have led to increased public attention to renewable energy sources, with wind energy being a particularly favored option. This prompted the development of various wind turbine types' efficiency. This study intends to explore the influence of key design parameters consisting of the number of blades, blade chord length, helical angle, and J-shaped blade on the performance and self-starting ability of a Darrieus VAWT. Furthermore, implementing an efficient optimization model to obtain maximum power based on the numerical findings. To achieve this, two different numerical modeling approaches, namely Computational Fluid Dynamics (CFD) and Double Multi-Streamtube (DMST), have been applied. The results indicated that employing a higher blade number and chord length enhances the starting capability of the turbine. Moreover, increasing the helical angle to 60° reduces the generated torque fluctuations. Inspired by the design of the Savonius turbine, the implementation of a J-shaped airfoil boosted the Cp at low TSR. Finally, the Kriging optimization method has been employed to optimize the design parameters explored through CFD analysis. The outcomes showed that the optimum configuration of the examined Darrieus VAWT comprises a 3-bladed rotor with a blade chord length of 0.04 m and helical angle of 0° and a J-shaped blade length ratio of 0.68. This configuration yields an 10% increase in efficiency at the optimum TSR.

CFD analysis and optimization of thermal stratification in a Thermal Diode Tank (TDT)

Thermal stratification is a common and natural phenomenon in energy storage tanks. This paper presents a Computational Fluid Dynamics (CFD) analysis of thermal stratification within a novel cold energy storage, termed a Thermal Diode Tank (TDT). The TDT is a well-insulated water tank equipped with heat pipes for unidirectional heat transfer from water to the ambient air. When integrated into a Refrigeration and Air-conditioning (RAC) system, it provides cooling water to reduce the condensing temperature. The research problem revolves around the impact of thermal stratification on TDT performance and the identification of the optimal TDT structure when thermal stratification is present. Therefore, this study aims to employ CFD to simulate temperature profiles within a TDT, both with and without an obstacle. With validated models, parametric analysis has been conducted to determine the optimal TDT structure. Several design parameters have been investigated, including tank orientation, heat transfer capacity, the ratio of obstacle axial height to TDT height (ho/H), and the ratio of obstacle hole diameter to TDT diameter (do/D). Key findings reveal that a vertical tank orientation is more conducive to improving the TDT assisted RAC system performance than a horizontal one. Increasing the TDT's heat transfer capacity also positively contributes to the system performance. Parameters of an optimal TDT structure include a ho/H ratio of approximately 0.43 and a do/D ratio of 0.4. It is found that the do/D ratio should be at least 0.15 to obtain positive stratification. Furthermore, the presence of thermal stratification can increase the system's Coefficient of Performance (COP) by up to 10 %.

CFD simulation and optimization of an industrial cement gas–solid air classifier

An air classifier is one of the main and effective devices in cement industry. In this study, a three-dimensional, steady and two-phase (solid-gas) computational fluid dynamics (CFD) simulation was performed to optimize the performance of this device in the Kerman Momtazan cement plant, Iran. After the validation of CFD results, the air flow field and air path lines between fixed blades were checked carefully and the non-uniformity in velocity distribution and the formation of vortex flows between the blades close to particle inlets were observed. The study tried to improve the device efficiency by changing the method of entering particles into the device, resulting in a reduction in air classifier electrical energy consumption (from 41 to 35 (kW h)/t) and an increase in production rate (from 203 to 214 t/h). Additionally, the study investigated the effects of other modifiable operating conditions like rotary cage rotation speed, pressure difference, and inlet air temperature on the particle size distribution and classifier efficiency. The results showed that increasing the cage rotation speed decreased the product rate and the product particles mean diameter while increasing pressure difference or increasing temperature increased the product rate and the product particles mean diameter. It was concluded that these modifiable operating conditions can significantly affect the performance of the air classifier in the cement industry.

Superior performance of a membrane bioreactor through innovative in-situ aeration and structural optimization using computational fluid dynamics.

The optimization of membrane bioreactors (MBRs) involves a critical challenge in structural design for mitigation of membrane fouling. To address this issue, a three-dimensional computational fluid dynamics (CFD) model was utilized in this study to simulate the hydrodynamic characteristics of a flat sheet (FS) MBR. The optimization of the membrane module configuration and operating conditions was performed by investigating key parameters that altered the shear stress and liquid velocity. The mixed liquor suspended solids (MLSS) concentration was found to increase the shear stress, leading to a more uniform distribution of shear stress. By optimizing the appropriate bubble diameter to 5mm, the shear stress on the membrane surface was optimized with relatively uniform distribution. Additionally, extending the side baffle length dramatically improved the uniformity of the shear stress distribution on each membrane. A novel in-situ aeration method was also discovered to promote turbulent kinetic energy by 200 times compared with traditional aeration modes, leading to a more uniform bubble streamline. As a result, the novel in-situ aeration method demonstrated superior membrane antifouling potential in the MBR. This work provides a new approach for the structural design and optimization of MBRs. The innovative combination of the CFD model, optimization techniques, and novel in-situ aeration method has provided a substantial contribution to the advancement of membrane separation technology in wastewater treatment.

Approaches for Optimum Thermal Management of SOFC Cells: Fitting Operating Conditions & Smart Cell Design

The thrust of green hydrogen as energy vector for the consolidation of a net-zero emitting global energy system implies the necessity of a fast development of high performing and highly efficient fuel cells and electrolyzers. Among the commercial choices, solid oxide cells can be considered as a better performing alternative compared to commercial proton exchange membrane and alkaline technologies. The benefits of this kind of technology arise from their higher operating temperatures of around 700-900 ºC, which results in improved kinetics and favored thermodynamics, allowing to reach unrivaled conversion efficiencies and reduced electricity consumption. Furthermore, this allows operating the cell reversibly in both fuel cell (SOFC) and electrolysis (SOE) modes.However, cell overheating and non-uniform temperature distribution can lead to an acceleration of degradation processes and cell cracking and sintering, which challenges long-term cell stability. In this sense, modeling at cell level enables to optimize operating conditions, improve cell design and predict and minimize such phenomena. Simulations allow mimicking the response of the cells and stacks at diverse operating scenarios and accelerates the optimization process minimizing experimental efforts; saving materials, time, and economical resources. We model SOFC/SOE cell behavior by means of Computational Fluid Dynamics (CFD), solving the mass, species, momentum, energy and current conservation equations, as well as electrochemical reaction models.In this work, a detailed methodology to guide design of the thermal management of SOFC by means of CFD and numerical optimization tools is proposed. These approaches combine acting both on operating conditions and cell geometry. Initially, we study the influence of inlet gas flows and describe a procedure to optimize the flows while maximizing the energetic outcome. Afterwards, we describe how numerical methods can allow fitting feed gas temperatures to avoid overheating. Finally, we go a step further by optimizing cell interconnect plate geometries to minimize internal temperature gradients. All in all, we demonstrate how CFD studies can accelerate SOFC cell design in order to maximize performance and extend lifespan. Figure 1

CFD simulation and optimization of ventilation for the layout of community architecture inspired by fishbone form

The rise in urbanization has led to an increase in high-density communities. Our study drew inspiration from the fishbone structure and applied a bionic architectural layout to optimize the wind environment within the pedestrian areas of these communities. Additionally, our study delved into the intrinsic principles and simulation-based optimization methods for the wind environment in the pedestrian areas of the fishbone bionic architectural complex. Using Computational Fluid Dynamics (CFD) simulation technology, our study simulated the building models both before and after the community renovation. Furthermore, our study simulated nine architectural complex models proposed by our study, considering the architectural layout and facade height within the community. By verifying and comparing the simulation results, our study observed that the fishbone bionic architectural form significantly improved the wind environment within the community’s pedestrian areas. Regarding the facade height, our study discovered that taller architectural units should be positioned away from the prevailing wind direction to enhance the airflow within the architectural complex. This research carries substantial implications for the renovation and planning of residential communities, particularly in large urban settings with a substantial population.

Exploring synchronization and lift suppression in fluid flow around vibrating cylinder: a parallel CFD and global optimization investigation

In this study, we employ a parallel Computational Fluid Dynamics (CFD) code integrated with the VTDIRECT95 algorithm, a parallel deterministic global optimization method, to conduct global optimization for an oscillating circular cylinder. We conduct numerical simulations for the flow at a Reynolds number of 500 within the parameter range of 0.1≤Ax≤0.3 and 0.5fst≤fex≤2.5fst where Ax represents the inline oscillating amplitude, fex denotes the forcing oscillation frequency, and fst corresponds to the frequency of a stationary cylinder. To enhance computational efficiency, a combination of VTdirect and a CFD solver is utilized to efficiently identify the synchronization region, thereby reducing computational resources. The results reveal a significant reduction in the lift coefficient within the synchronized region compared to unsynchronized regimes. Furthermore, the study delves into the underlying flow physics behind synchronization and lift suppression. By synchronizing the shedding of vortices, their detrimental effects are nullified, resulting in a reduction in lift. Moreover, the research examines the influence of three-dimensional (3-D) flow by comparing 2-D and 3-D simulations at two different Reynolds numbers. It demonstrates that accounting for 3-D effects yields more accurate predictions of fluid behavior. Synchronization maps and root mean square (rms) lift coefficient plots illustrate the impact of Reynolds number and movement frequency on lift suppression. The findings indicate that achieving synchronization in 3-D flow necessitates stronger amplitudes and higher frequencies. At higher Reynolds numbers, the wake structures become unstable, leading to intricate vortical patterns. Consequently, the synchronization curve shifts towards higher amplitudes and frequencies in 3-D simulations. Understanding these phenomena is vital for reducing lift force in practical applications. This research significantly contributes to knowledge regarding synchronization and lift suppression in fluid flow around vibrating cylinders.

Design and optimisation of structural packings for rotating bed absorbers using computational fluid dynamics simulation

A method for pressure drop prediction using Computational fluid dynamics (CFD) was designed and validated experimentally with a set of baffle-based geometry types of Rotating Packed Bed’s packings. The methodology served as a foundation for a CFD optimisation tool of internal geometry based on minimal pressure drop. The baffles in the geometry were characterized by five parameters: bottom and top internal rounding, bottom and top external rounding, and baffle inclination angle. Based on the variables, 78 different geometry types were created and subjected to pressure drop optimisation with the CFD tool. The optimal geometry was manufactured, and the simulation results were verified experimentally. Up to 54% decrease in pressure drop was observed in comparison to the pre-optimisation packing. Mass transfer experiments were conducted with the use of CO2-NaOH absorption system, and results showed that the optimised packing, despite exhibiting less pressure drop, is capable of achieving up to 17% increase in effective mass transfer area.

CFD Simulation and Optimization of the Leaf Collecting Mechanism for the Riding-Type Tea Plucking Machine

In the process of tea plucking and leaf gathering, the structure optimization design of the leaf collecting mechanism is the key element responsible for collecting fresh leaves. The unreasonable design and manufacture of leaf collecting mechanisms will cause the smooth collection of fresh leaves, the quality of the collected fresh leaves will be damaged, and the commodity value will be reduced. In order to further study the structural characteristics of the leaf collecting mechanism, an air outlet model of the leaf collecting mechanism was established for the phenomena of internal vortex rotation and impact in the leaf collecting mechanism process. The internal flow field of the leaf collecting mechanism, the movement trajectory of fresh leaves, and the non-homogeneous flow are calculated using computational fluid dynamics (CFD). Based on Box-Behnken’s central combinatorial design theory, the velocity inlet and outlet air structure factors are taken as the influencing factors to carry out response surface test research. The effect of different parameters such as engine rotation, shape of the blowing cavity and air outlet parts, and velocity on the flow is determined. The optimal parameter combination is as follows: the height of the outlet end, the length of the inlet end, and the velocity inlet are 0.01 m, 0.03 m, and 25 m/s, respectively. Furthermore, it was found that when the number of plates increases from 1 to 4, the non-homogeneity decreases all the time, and the distribution of blowing air is improved without a sharp decrease in velocity. The average velocity outlet was larger than the velocity inlet, which meets the requirements of blade gathering. Considering comprehensively, the flow field simulation of the blade collecting mechanism with four baffles was consistent with the test results of the velocity outlet. The validation results showed that the model can successfully simulate the air flow inside the leaf-collecting mechanism, and the reasonable structure design was conducive to reducing the number of collisions between tea buds and improving the quality of tea buds. This research has certain theoretical and practical implications for the accurate plucking of high-quality tea.

Geometry optimization of a continuous millireactor via CFD and Bayesian optimization

Computational Fluid Dynamics (CFD) is a powerful tool which can help with the geometry optimization of continuous milli-scale reactors, which often are highly complex devices. Attempting to perform this optimization by manually modifying and testing geometry configurations can however be tedious and computationally inefficient. Addressing this problem, we present a framework in which the CFD software COMSOL Multiphysics is coupled with the multi-objective Bayesian Optimization algorithm TSEMO (Thompson sampling efficient multiobjective optimization), implemented in MATLAB. The mixing element geometry of a Miprowa Lab millireactor is parameterized, and the framework automatically executes CFD simulations to minimize areas of stagnating flow and maximize the mixing performance. The framework is able to find Pareto-optimal reactor variations, and can easily be adapted for other devices and objectives.

Characterization of Mixing by CFD Simulation and Optimization of Mixing Frequency to Break Scum and Enhance Methane Yield in Chinese Dome Digester

The Chinese dome digester (CDD) is a low-cost and the most popular anaerobic digester that is used for the treatment of organic waste such as food waste and cow dung. However, the main challenge of CDD is scum formation due to inadequate mixing intensity. This study explores computational fluid dynamics (CFD) to characterize mixing in CDD and the effects of mixing frequency (0, 4, 6, and 8 times per day) on the performance of semicontinuous anaerobic digestion to break scum and enhance methane yield. The flow field simulation on a lab-scale CDD by Ansys Fluent (v.19.2), a finite volume solver, estimated that 45% of CDD working volume was occupied by dead zones which could nurture scum. The simulation results elicited the optimization of mixing frequency. Four CDDs were operated to investigate the optimum mixing frequency. The average scum thickness for the non-mixed digester was 2 ± 0.1 cm compared to 0.2 ± 0.1, 0.8 ± 0.1, and 1.3 ± 0.2 cm for the mixed digesters (4, 6, and 8 times per day, respectively). The average methane yields for 0, 4, 6, and 8 times per day were 206 ± 191, 602 ± 87, 555 ± 59, and 492 ± 109 mL g-VS−1, respectively. Four times per day was the optimum mixing frequency and the energy required to break scum was 6.1 ± 0.3 Joules per mixing cycle. This study proves that by optimizing the mixing frequency in CDD, scum formation can be controlled without additional investment cost.

A hybrid of CFD and PSO optimization design method of the integrated slipper/swashplate structure in seawater hydraulic axial piston pump

An integrated slipper/swashplate structure is developed for seawater hydraulic axial piston pump. Considering the overturning moment of the integrated slipper, the transient hydrodynamic lubrication model of the integrated slipper is established, and the body-fitted grid and five-point finite difference method is employed to accurately solve the model. An optimization design method based on a hybrid of CFD (Computational Fluid Dynamics) and PSO (Particle Swarm Optimization) for the integrated slipper is proposed for the interface structure with the low leakage and power loss. The optimal sealing belt of the integrated slipper is obtained, and the leakage and power loss are reduced by 27.3% and 16.7% under the same gap size, respectively. The effects of working condition on the film-forming characteristics and power consumption characteristics of the lubricating film are analyzed based on the optimized integrated slipper. It is found that the leakage and total power loss increase significantly with the increasement of working pressure and shaft speed, and decrease with the increasement of temperature. The excellent lubrication characteristics and strong anti-overturning ability of the integrated slipper/swashplate structure can improve the performance of the seawater axial piston pump, and its optimization design method proposed in this study can provide a new reference for engineers.

Aerodynamic optimisation of civil aero-engine nacelles by dimensionality reduction and multi-fidelity techniques

PurposeAerodynamic shape optimisation is complex because of the high dimensionality of the problem, the associated non-linearity and its large computational cost. These three aspects have an impact on the overall time of the design process. To overcome these challenges, this paper aims to develop a method for transonic aerodynamic design with dimensionality reduction and multifidelity techniques.Design/methodology/approachThe developed methodology is used for the optimisation of an installed civil ultra-high bypass ratio aero-engine nacelle. As such, the effects of airframe-engine integration are considered during the optimisation routine. The active subspace method is applied to reduce the dimensionality of the problem from 32 to 2 design variables with a database compiled with Euler computational fluid dynamics (CFD) calculations. In the reduced dimensional space, a co-Kriging model is built to combine Euler lower-fidelity and Reynolds-averaged Navier stokes higher-fidelity CFD evaluations.FindingsRelative to a baseline aero-engine nacelle derived from an isolated optimisation process, the proposed method yielded a non-axisymmetric nacelle configuration with an increment in net vehicle force of 0.65% of the nominal standard net thrust.Originality/valueThis work investigates the viability of CFD optimisation through a combination of dimensionality reduction and multifidelity method and demonstrates that the developed methodology enables the optimisation of complex aerodynamic problems.

Computational Fluid Dynamics (CFD) modelling of the effect of distributor plate geometry in the bubbling fluidized bed reactor

Air distribution is the primary factor that influences the performance of fluidized beds. To understand the hydrodynamics and operation of a fluidized bed, an assessment of the airflow and its distribution is essential. The design and operation of the fluidized bed are complex therefore numerical models have been proposed to predict the behaviour of fluidized beds. Although fluidisation has been studied fundamentally, systematic investigation of air maldistribution due to fluidised bed reactor design and geometry has not been characterised. The effect of four distributor plates (Plate A, B, C and D with 8.67%, 6.12%,4,2% and 2.4% open area, respectively) and the two fluidised bed reactors (straight inlet and bend inlet reactors) on the fluidisation hydrodynamics have been investigated. OpenFOAM™ v1712 was used to develop a computational fluid dynamic (CFD11CFD- computational Fluid dynamics) model to predict the behaviour of a bubbling fluidised bed. The determination of these characteristics will allow for an improved CFD model and optimisation of an industrial fluidised bed granulator. The model was validated with experimental data. Plate pressure drops of 76 Pa,121 Pa,296 Pa and 886 Pa were achieved with plates A, B, C and D respectively. High bed pressure drops were observed for plate It was therefore concluded that the pitch and open area percentage of the distributor has an effect on both the plate and bed pressure drop. Particles with 1.3 mm diameter fluidised quicker with minimum fluidisation velocity range between 0.3 and 0.8 m/s. There was an agreement between the model and experiments for plate and bed pressure drop and bed expansion. Air maldistribution was observed for bend inlet reactor.

Towards Incompressible Laminar Flow Estimation Based on Interpolated Feature Generation and Deep Learning

For industrial design and the improvement of fluid flow simulations, computational fluid dynamics (CFD) solvers offer practical functions and conveniences. However, because iterative simulations demand lengthy computation times and a considerable amount of memory for sophisticated calculations, CFD solvers are not economically viable. Such limitations are overcome by CFD data-driven learning models based on neural networks, which lower the trade-off between accurate simulation performance and model complexity. Deep neural networks (DNNs) or convolutional neural networks (CNNs) are good illustrations of deep learning-based CFD models for fluid flow modeling. However, improving the accuracy of fluid flow reconstruction or estimation in these earlier methods is crucial. Based on interpolated feature data generation and a deep U-Net learning model, this work suggests a rapid laminar flow prediction model for inference of Naiver–Stokes solutions. The simulated dataset consists of 2D obstacles in various positions and orientations, including cylinders, triangles, rectangles, and pentagons. The accuracy of estimating velocities and pressure fields with minimal relative errors can be improved using this cutting-edge technique in training and testing procedures. Tasks involving CFD design and optimization should benefit from the experimental findings.

CFD Optimisation of the Longitudinal Volume Distribution of a Ship’s Hull by Constrained Transformation of the Sectional Area Curve

Abstract The paper presents a proposal for a formalised approach to hull shape optimisation with respect to total resistance, by fine-tuning longitudinal volume distribution. An algorithm for automated modification of the hull is presented, allowing for varying the sectional area distribution with a negligible influence on the resulting displacement. Computational fluid dynamics (CFD) solver STAR-CCM+ and computer computer-aided design (CAD) software NX were used to search the optimal volume distribution of selected parent shapes, with respect to total resistance. The bow part and the aft part were optimised separately. The resulting resistances of the selected optimal shapes were then verified by means of scale model tests, realised in the towing tank at the Maritime Advanced Research Centre (CTO) S.A. A noticeable gain in total resistance was achieved and confirmed by experimental tests. The proposed approach seems to be a promising method for relatively quick parametric optimisation of the designed hull shapes; it is also applicable for generic CFD optimisation studies.

Numerical study on the interaction of geometric parameters of a transcritical CO2 two-phase ejector using response surface methodology and genetic algorithm

In this study, the effect of the interaction of geometric parameters on the performance of the rectangular transcritical CO2 two-phase ejector was investigated, and a geometric optimization of the rectangular CO2 ejector was conducted using computational fluid dynamics (CFD) technique, response surface methodology (RSM) and genetic algorithm (GA). The significance of geometric factors on entrainment ratio was analyzed firstly using CFD simulation, and then a second-order regression model was successfully developed using the RSM. Furthermore, a GA was used to solve the response surface model to obtain the optimized geometric parameters. The reliability of GA optimization was verified with CFD simulation under different operating conditions. The analysis results indicated that the entrainment ratio was highly sensitive to the nozzle exit position (NXP), suction chamber angle and mixing chamber width. Besides, the strong interactions between the mixing chamber width and mixing chamber length, the mixing chamber width and NXP, the mixing chamber length and diffuser angle, the mixing chamber length and NXP as well as the suction chamber angle and NXP had significant influence on the entrainment ratio. The results of CFD and GA optimization demonstrated that the optimized ejector increased the velocity of secondary flow and broke the vortex in the ejector, and optimized ejector improved the ejector efficiency more than 41% on average for different primary flow operating conditions and ejector outlet pressure. Additionally, the results confirmed the combination of CFD, RSM and GA had a considerable reliability and an excellent performance to optimize the CO2 two-phase ejector.