Fluid Dynamic Design Research Articles

Fluid-dynamic analysis and multi-objective design optimization of piezoelectric servo valves

This paper proposes an effective methodology for the fluid-dynamic design optimization of the main spool of a piezoelectric servo valve. The aim is to improve global performances of the piezoelectric servo valve by reducing the flow force acting on the main spool and the mass of the main spool. The main disturbance forces acting the main spool were analyzed. The steady-state flow force acting on the main spool was derived and the relationship between the flow force and the design parameters of the main spool was established. The design problem of the main spool was formulated mathematically as a multi-objective optimization problem. The minimum steady-state flow force and the minimum mass of main spool were considered as optimization objectives. The elitist non-dominated sorting genetic algorithm (NSGA-II) was applied and a set of Pareto-optimal solutions was calculated. The optimized results were analyzed and the final design parameters of the main spool were selected for the simulation analysis and experimental research. The computational fluid dynamics (CFD) simulation was employed to calculate the forces acting on the main spool. Simulation results show the flow force acting on the optimized main spool is significantly reduced. The unoptimized and optimized main spools were machined and experimental study was performed. Results show that the piezoelectric servo valve equipped with the optimized main spool has better response performance and dynamic bandwidth. The dynamic bandwidth is measured to 172 Hz under the amplitude attenuation of −3 dB. Compared with the piezoelectric servo valve with unoptimized main spool, the dynamic bandwidth of the piezoelectric servo valve with optimized main spool is increased by 26%.

Combination of computational fluid dynamics and design of experiments to optimize modules for direct contact membrane distillation

The design of membrane distillation modules is an important issue that must be addressed for it to be practically implemented. Herein, a combination of the design of experiments (DOE) and computational fluid dynamics (CFD) was developed to evaluate the interaction between variables of module geometry and how they affect the performance of a direct contact membrane distillation (DCMD) process. A three-dimensional CFD model was developed to calculate flux, the performance ratio (PR), and the permeate-to-feed ratio (ϕp) as functions of the height, length, and width of the channel in a plate-and-frame DCMD module. The CFD model was validated using experimental results in a laboratory DCMD system. Based on a DOE with a central composite design (CCD), CFD simulations were carried out, and response values were obtained for each combination. The results show that length is the most important factor affecting flux, and height is the most important factor affecting PR and ϕp. However, the effect of module width was not significant compared with that of the other variables. Based on the results, a set of regression models were developed to estimate flux, the PR, and ϕp, and these estimations match the CFD simulation results well. Using the derived models, the dimensions of the DCMD module were optimized to simultaneously increase water productivity and energy efficiency.

A Computational Fluid Dynamics-based Correlation to Predict Droplet Sauter Mean Diameter for Σ− Yliq Atomization Model in Pressure Swirl Atomizer

Liquid atomization is crucial to ensure efficient combustion as it is an inherent part of the injector system. The combustion of fuels relies on effective atomization to increase the surface area of the fuel and consequently achieve high rates of mixing and evaporation. Pressure swirl atomizers are inexpensive and reliable type of atomizer for fuel injection owing to its superior atomization characteristics and relatively simple geometry. The Sauter mean diameter (SMD) of atomizer contributes significantly to the combustion chamber performance. This paper presents a two-step strategy to predict droplet SMD for atomisation model in pressure swirl atomizer through the combination of experimentally validated Computation Fluid Dynamics (CFD) and Optimal Latin Hypercubes (OLHC) Design of Experiments (DoE) techniques. A three-dimensional Eulerian two-phase CFD model is developed to account for liquid and gas phases as a single continuum with high-density variation at large Reynolds and Weber numbers and validated against experimental measurements, before being employed to carry out a parametric study involving operating conditions and fluid properties of the pressure swirl atomizer. The atomizer is then represented in terms of four design variables, namely liquid viscosity, liquid velocity, surface tension and atomizer exit diameter. An 87-point OLHC DoE is constructed within the design variables space using a permutation genetic algorithm resulting in an accurate SMD prediction. Results show the newly developed SMD prediction is found to be superior compared with existing correlations and indicate significant improvement in the droplets SMD.

A Computational Fluid Dynamics-based Correlation to Predict Droplet Sauter Mean Diameter for ?? Yliq Atomization Model in Pressure Swirl Atomizer

Liquid atomization is crucial to ensure efficient combustion as it is an inherent part of the injector system. The combustion of fuels relies on effective atomization to increase the surface area of the fuel and consequently achieve high rates of mixing and evaporation. Pressure swirl atomizers are inexpensive and reliable type of atomizer for fuel injection owing to its superior atomization characteristics and relatively simple geometry. The Sauter mean diameter (SMD) of atomizer contributes significantly to the combustion chamber performance. This paper presents a two-step strategy to predict droplet SMD for atomisation model in pressure swirl atomizer through the combination of experimentally validated Computation Fluid Dynamics (CFD) and Optimal Latin Hypercubes (OLHC) Design of Experiments (DoE) techniques. A three-dimensional Eulerian two-phase CFD model is developed to account for liquid and gas phases as a single continuum with high-density variation at large Reynolds and Weber numbers and validated against experimental measurements, before being employed to carry out a parametric study involving operating conditions and fluid properties of the pressure swirl atomizer. The atomizer is then represented in terms of four design variables, namely liquid viscosity, liquid velocity, surface tension and atomizer exit diameter. An 87-point OLHC DoE is constructed within the design variables space using a permutation genetic algorithm resulting in an accurate SMD prediction. Results show the newly developed SMD prediction is found to be superior compared with existing correlations and indicate significant improvement in the droplets SMD.

Optimal Design of Computational Fluid Dynamics: Numerical Calculation and Simulation Analysis of Windage Power Losses in the Aviation

Based on the theory of computational fluid dynamics (CFD), with the help of the Fluent software and the powerful parallel computing capability of the super cloud computer, the single-phase flow transient simulation calculation of the windage power loss of the engagement spiral bevel gear pair (SBGP) was performed. The two-equation SST k-ω turbulence model based on the assumption of eddy viscosity was adopted, which was improved from the standard k-ε model combined with the Wilcox k-ω model. The SST k-ω turbulence model inherited the respective advantages of the Wilcox k-ω model in the near-wall region and the k-ε model in the free shear layer and could more accurately describe the resistance and separation effect of the gear tooth surface on the airflow. The simulation analyzed the airflow characteristics around SBGP and the mechanism of the windshield to reduce the windage loss of the gear. It also studied the influence of the windshield clearance and opening size on the windage power loss. Then the orthogonal experimental analysis method was adopted to perform numerical simulation analysis. The windage torque was studied under different clearance values between the windshield and the gear tooth surface, as well as the large end and the small end. The variance analysis was performed on the numerical simulation data. The results showed that when the windshield clearance value was 1 mm and the engagement opening was 30°, the windage torque was the smallest, and the effect of reducing the windage power loss was the best. According to the changes in the pressure, velocity, and turbulent kinetic energy cloud diagram of the flow field in the reducer during multi-group simulation tests, the local optimal windshield configuration was obtained, which provided a method for further research on the multi-objective optimization of the windshield and the windage loss of the gear pair under the oil–gas two-phase flow and also provided a reference for the practical engineering application of the windshield.

Performance assessment of solar PV and thermal-driven humidification dehumidification systems: A CFD modelling approach

Demand for clean water rises continuously with the increase in population. One of the promising techniques for sustainable water production is achieved through humidification and dehumidification (HDH) technique. The present study focuses on the fluid dynamic design processes and the system performance using solar energy as primary source in HDH process. Computational fluid dynamics (CFD) simulations are validated against the standard experimental results of solar photovoltaic panel (PVP) HDH system, published in the literature. The performance of the PVP HDH system is analyzed for improvement with the partitions and fin surfaces in the humidifier and dehumidifier chambers respectively. From this study, it is found that performance in yield of a basic PVP system increases by 16 % after the improvement in PVP system with partitions and fins in humidifier and dehumidifier respectively. For the efficient performance and cheaper production cost, the parabolic trough collector (PTC) HDH system is also investigated at horizontal and sloping conditions. Theoretical heat transfer calculations and experimental measurements from literature are included for the validation of PTC humidifier and dehumidifier investigations by CFD approach. Analytical calculations are performed in the combined PTC-solar still configuration also. The improved PTC system with slope shows 18 % higher yield as compared to the improved PVP system. GOR and SDWP are investigated between the PTC and PVP HDH systems and the cost analysis is included to find the payback time period in the basic and improved HDH systems.

Combining Analytical Models and Mesh Morphing Based Optimization Techniques for the Design of Flying Multihulls Appendages

Abstract The fluid dynamic design of hydrofoils involves most of the typical difficulties of aeronautical wings design with additional complexities related to the design of a device operating in a multiphase environment. For this reason, “high fidelity” analysis solvers should be, in general, adopted also in the preliminary design phase. In the case of modern fast foiling sailing yachts, the appendages accomplish both the task of lifting up the boat and to make possible upwind sailing by contributing balance to the sail side force and the heeling moment. Furthermore, their operative design conditions derive from the global equilibrium of forces and moments acting on the system which might vary in a very wide range of values. The result is a design problem defined by a large number of variables operating in a wide design space. In this scenario, the device performing in all conditions has to be identified as a trade-off among several conflicting requirements. One of the most efficient approaches to such a design challenge is to combine multi-objective optimization strategies with experienced aerodynamic design. This paper presents a numerical optimization procedure suitable for foiling multihulls. As a proof of concept, it reports, as an application, the foils design of an A-Class catamaran. The key point of the method is the combination of opportunely developed analytical models of the hull forces with high fidelity multiphase analyses in both upwind and downwind sailing conditions. The analytical formulations were tuned against a database of multiphase analyses of a reference demihull at several attitudes and displacements. An aspect that significantly contributes to both efficiency and robustness of the method is the approach adopted to the geometric parametrization of the foils which was implemented by a mesh morphing technique based on Radial Basis Functions.

Design Guidelines for Axial Turbines Operating With Non-Ideal Compressible Flows

Abstract The impact of non-ideal compressible flows on the fluid-dynamic design of axial turbine stages is examined. First, the classical similarity equation (CSE) is revised and extended to account for the effect of flow non-ideality. Then, the influence of the most relevant design parameters is investigated through the application of a dimensionless turbine stage model embedding a first-principles loss model. The results show that compressibility effects induced by the fluid molecular complexity and the stage volumetric flow ratio produce an offset in the efficiency trends and in the optimal stage layout. Furthermore, flow non-ideality can lead to either an increase or a decrease of stage efficiency up to 3–4% relative to turbines designed to operate in dilute gas state. This effect can be predicted at preliminary design phase through the evaluation of the isentropic pressure–volume exponent. Three-dimensional (3D) RANS simulations of selected test cases corroborate the trends predicted with the reduced-order turbine stage model. URANS computations provide equivalent trends, except for case study niMM1, featuring a non-monotonic variation of the generalized isentropic exponent. For such turbine stage, the efficiency is predicted to be higher than the one computed with any steady-state model based on the control volume approach.

Fluid Dynamics and Paper Airplane Design “Aerodynamics Explained by a World Record Paper Airplane Designer” with an Introduction to the Coandă Effect

<i>Fluid Dynamics and Paper Airplane Design “Aerodynamics Explained by a World Record Paper Airplane Designer” with an Introduction to the Coandă Effect</i>

Fully-turbulent adjoint method for the unsteady shape optimization of multi-row turbomachinery

The possibility of taking into account unsteady flow effects if performing turbomachinery shape optimization is attractive to accurately address inherently time dependent design problems. The harmonic balance method is an efficient solution for computational fluid dynamics problems of turbomachinery characterized by quasi-periodic flows. If applied in combination with adjoint methods, it enables the possibility to deal with unsteady fluid-dynamic design in a cost effective manner, opening the way towards multi-disciplinary applications. This paper presents the development of a novel fully-turbulent discrete adjoint based on the time domain harmonic balance method and its application to the constrained fluid dynamic optimization of an axial turbine stage. As opposed to previous works, the proposed method does not require any assumption on the turbulent eddy viscosity and on the set of input frequencies. The results show that the method provides accurate gradients, if compared with second order finite differences, and significant deviation with respect to the sensitivity computed with the constant eddy viscosity approximation. The application of the method to the fluid-dynamic shape optimization of the exemplary stage leads to improve the total-to-static efficiency of 0.8%. The efficiency increase is found to be higher than that obtained by means of a steady state optimization method.

Micro-Reactor System for Complete Oxidation of Volatile Organic Compounds

Based on previous Computational Fluid Dynamics (CFD) design results, an 11 channel microreactor of dimensions (0.5 mm × 0.5 mm × 100 mm) (width × depth × length) and optimal manifold geometry was fabricated, coated with a newly-developed Au/SBA-15 catalyst and then integrated in an experimental rig specifically built for this research. Propane (as model volatile organic compound) oxidation experiments were conducted at three different flow velocities, 12.5, 15.4 and 17.5 m/min, respectively, at six temperatures, 150, 200, 225, 250, 275, and 300 °C, respectively. The catalyst was prepared by one-pot sol-gel synthesis of SBA-15 with MPTMS (3-mercaptopropyl-trimethoxy-silane) before loading with HAuCl4 gold precursor and then characterized by SEM/EDX, TEM and wide angle XRD. A novel catalyst coating technique was developed, using airbrush (0.3 nozzle) to spray a catalyst slurry into the microchannels that produced a thin, firm and uniform layer of Au/SBA-15 catalyst coating inside the microreactor. The experimental measurements revealed that propane conversion increased as the flow feed rates decreased and increased with increasing temperatures in the reactor. For the built microreactor and for the flows and temperatures set, the combustion of propane was possible with measurable conversions and reasonable reactor stability, the performance of the catalyst appeared to be central to the satisfactory operation of the reactor.

Research on Solving Ionization Equation of High-Speed Aircraft Based on Euler Monte Carlo Method of Fluid Mechanics

Taking the aerodynamic calculation of high-speed aircraft as an example, this paper introduces the modelling and application of computational fluid dynamics in aircraft design. The application of computational fluid dynamics in the design of aircraft is accompanied by the development of computer technology and aerodynamics. From the earlier solution of the Euler equation and the NS equation from a macro perspective, to the solution of the NS equation with chemical reactions and ionization that considers the influence of real gases, and from the micro perspective, the Monte Carlo method is used to directly simulate and solve the gas molecule motion, that is, It represents the development of computational dynamics theory and is also the result of the development of computer technology today. This article discusses the application of computational fluid mechanics, including the selection of mathematical models, the selection of calculation methods, and its application to special problems in aircraft design.

Geometrical optimisation of Transpired Solar Collectors using design of experiments and computational fluid dynamics

Transpired Solar Collectors (TSCs) are simple low maintenance air heating systems which have been widely used for agricultural and industrial applications. In spite of their potential, these systems have not been yet widely employed in residential buildings as they are unable to generate high grade heat for moderate and low ventilation demands. Hence there is an opportunity for optimisation studies in order to enhance the thermal performance of these systems.Optimisation and parametric studies can be costly and time consuming if carried out by physical experiments. CFD models however offer a more flexible and less expensive tool to carry out such studies. This research has aimed to optimise the geometry of the solar absorber plate using a validated CFD model which accounts for a wide range of the key factors affecting TSC performance.A 2nd order polynomial predictive model was developed based on the CFD results with Root Mean Squared Error (RMSE) of 3.8%. The predictive model was used to identify an optimal geometry which delivers a Heat Exchange Effectiveness (HEE) of 0.739. The optimised geometry demonstrated 43% increase in HEE whilst using 28% less material compared to the baseline geometry under the same operating conditions. This geometry can be integrated with other performance enhancement techniques to further improve the thermal performance of TSCs.

Computational fluid dynamics analysis and design optimization of a porous annular powder‐liquid mixer

AbstractAn annular powder‐liquid mixer is a new type of jet pump used to mix powder. This mixer is mainly used to mix fracturing fluids in oil and natural gas exploitation processes. Free from powder pellets, the mixer has characteristics, such as high mixing efficiency and great suction. The structural parameters, such as hose diameter, exit section diameter, falloff angle, divergence angle, hose length‐diameter ratio, and annular nozzle diameter, may influence this new type of mixer. By using an orthogonal experiment to optimize the structure of an annular ring‐type powder mixer and performing a comparative analysis of the results of numerical simulations, this paper finally determines the mixer's structure. According to experiments, the mixer's negative suction can reach 0.09 MPa, there are no powder pellets during the mixing process, and the mixing effect is very good.

An evaluation of kinetic models for the simulation of Claus reaction furnaces in sulfur recovery units under different feed conditions

The modified Claus process is one of the major processes employed to convert hydrogen sulfide to elemental sulfur from acid gas. Kinetic models provide a better estimation of Claus reaction furnace effluents, however, kinetics of the coupled reactions are complex and depend upon the feed composition and conditions. Previous studies focused on fitting the kinetic parameters to better approximate the furnace effluents of the observed plants. In this work, a proposed kinetic model based on key global reactions is examined with different feed conditions and acid gas compositions without parameter fitting. Results of the proposed reduced model are compared with plant data, published data from lab-scale experiments, results of a detailed reaction mechanism and of a reduced kinetic model from the literature. Overall, a good agreement is found with each case for the prediction of the reaction furnace effluent temperature and compositions by the proposed model. The proposed model is computationally efficient for Computational Fluid Dynamics design, and optimization and control studies for Claus reaction furnaces.

Design and CFD Analysis of the Fluid Dynamic Sampling System of the "MicroMED" Optical Particle Counter.

MicroMED is an optical particle counter that will be part of the ExoMars 2020 mission. Its goal is to provide the first ever in situ measurements of both size distribution and concentration of airborne Martian dust. The instrument samples Martian air, and it is based on an optical system that illuminates the sucked fluid by means of a collimated laser beam and detects embedded dust particles through their scattered light. By analyzing the scattered light profile, it is possible to obtain information about the dust grain size and speed. To do that, MicroMED’s fluid dynamic design should allow dust grains to cross the laser-illuminated sensing volume. The instrument’s Elegant Breadboard was previously developed and tested, and Computational Fluid Dynamic (CFD) analysis enabled determining its criticalities. The present work describes how the design criticalities were solved by means of a CFD simulation campaign. At the same time, it was possible to experimentally validate the results of the analysis. The updated design was then implemented to MicroMED’s Flight Model.

Computational fluid dynamic design of spent coffee ground cabinet dryer using recycled heat from air compressor

This study designed a cabinet dryer assembled to an air compressor to utilize a free-of-charge waste heat for drying. Spent coffee ground (SCG), a residue from coffee brewing, was the tested material. Applying computational fluid dynamics (CFD), an appropriate cabinet dryer configuration could be achieved. As varying the hot air inlet/outlet position, the best drying characteristics providing uniform air flow occurred when hot air entered the chamber at the top and left the chamber at the bottom, opposite side to the inlet. A model dryer was then developed and used to validate the CFD prediction of dryer capacity which was dependent on the maximum numbers of mounted trays and the thickness of SCG layer. The computational prediction agreed well with the experimental results, showing that the dryer loading SCG at 3cm thickness performed best with two trays in the chamber. Adding another tray would result in an obstruction of the air flow, leaving more than 20% of the moisture content in the final product. Experimental determination of drying duration for drying SCG with varying thickness indicated that each centimeter of the increase in SCG bed thickness extended the drying duration by 3 fold. Particularly at the SCG layer thickness of 4cm, this fitted well with the simulation results at 97.2% accuracy. Mounted with 3 trays, each loaded 300g SCG (1cm bed thickness), the dryer could complete 6 cycles within regular operation hours of a coffee shop (12h) and thus accounted for 5400g of SCG as daily capacity of a dryer.

Computational Fluid Dynamic Design and Experimental Study of a Temperature Sensor Array Used in Climate Reference Station

Accurate air temperature measurements are demanded for climate change research. However, air temperature sensors installed in a screen or a radiation shield have traditionally resisted observation accuracy due to a number of factors, particularly solar radiation. Here we present a novel temperature sensor array to improve the air temperature observation accuracy. To obtain an optimum design of the sensor array, we perform a series of analyses of the sensor array with various structures based on a computational fluid dynamics (CFD) method. Then the CFD method is applied to obtain quantitative radiation errors of the optimum temperature sensor array. For further improving the measurement accuracy of the sensor array, an artificial neural network model is developed to learn the relationship between the radiation error and environment variables. To assess the extent to which the actual performance adheres to the theoretical CFD model and the neural network model, air temperature observation experiments are conducted. An aspirated temperature measurement platform with a forced airflow rate up to 20 m s−1 served as an air temperature reference. The average radiation errors of a temperature sensor equipped with a naturally ventilated radiation shield and a temperature sensor installed in a screen are 0.42° and 0.23°C, respectively. By contrast, the mean radiation error of the temperature sensor array is approximately 0.03°C. The mean absolute error (MAE) between the radiation errors provided by the experiments and the radiation errors given by the neural network model is 0.007°C, and the root-mean-square error (RMSE) is 0.009°C.

Design Method and Performance Prediction for Radial-Inflow Turbines of High-Temperature Mini-Organic Rankine Cycle Power Systems

The realization of commercial mini organic Rankine cycle (ORC) power systems (tens of kW of power output) is currently pursued by means of various research and development activities. The application driving most of the efforts is the waste heat recovery from long-haul truck engines. Obtaining an efficient mini radial inflow turbine, arguably the most suitable type of expander for this application, is particularly challenging, given the small mass flow rate, and the occurrence of nonideal compressible fluid dynamic effects in the stator. Available design methods are currently based on guidelines and loss models developed mainly for turbochargers. The preliminary geometry is subsequently adapted by means of computational fluid-dynamic calculations with codes that are not validated in case of nonideal compressible flows of organic fluids. An experimental 10 kW mini-ORC radial inflow turbine will be realized and tested in the Propulsion and Power Laboratory of the Delft University of Technology, with the aim of providing measurement datasets for the validation of computational fluid dynamics (CFD) tools and the calibration of empirical loss models. The fluid dynamic design and characterization of this machine is reported here. Notably, the turbine is designed using a meanline model in which fluid-dynamic losses are estimated using semi-empirical correlations for conventional radial turbines. The resulting impeller geometry is then optimized using steady-state three-dimensional computational fluid dynamic models and surrogate-based optimization. Finally, a loss breakdown is performed and the results are compared against those obtained by three-dimensional unsteady fluid-dynamic calculations. The outcomes of the study indicate that the optimal layout of mini-ORC turbines significantly differs from that of radial-inflow turbines (RIT) utilized in more traditional applications, confirming the need for experimental campaigns to support the conception of new design practices.

Application of the Design of Experiments and Computational Fluid Dynamics to Bow Design Improvement

Techniques of the design of experiments (DOE) and computational fluid dynamics (CFD) were applied for improving the bow shape of a tanker hull. Through this, a hull that could reduce the added resistance in waves was derived. The key design elements of the bow shape were selected as parameters for design optimization and added resistance in the short-wavelength region was interpreted through CFD considering the operational condition of the full scale ship. For design parameter changes, the number of analyses was minimized by applying DOE. The regression equation for calculating added resistance was derived using bow-shape design parameters by applying the response surface method and regression analysis to obtain the optimal hull with minimal added resistance was derived. The methodology was applied to an Aframax tanker hull form, and the derived added resistance regression equation and the added resistance value obtained through CFD analysis showed a difference of approximately 1%. The model test results of the improved hull form showed that the added resistance was reduced by 52% in comparison to that obtained for the original hull form.