The flow under sluice gates is nowadays frequently still determined by empirical approaches, based on the Bernoulli equation and a specific discharge coefficient which depends on the geometry of the sluice gate. This discharge coefficient is determined from a selection of tables and charts, which are based on a variety of experimental series. In 2016 Malcherek developed a fundamentally new approach to describe hydraulic structures based on integral momentum balance instead of Bernoulli’s energy conservation principle. In this approach a flow is described as the result of the integral momentum balance including pressure forces on open boundaries as well as closed walls, momentum fluxes through open boundaries and gravitational and frictional forces. In this theoretical approach, the discharge under inclined sluice gates can be described as a result of the acting pressure forces and momentum fluxes. To apply the theory, the pressure integral at the sluicegate and under the sluice gate and also the momentum integral of the flow under the sluice gate have to be known. For the determination of these values, multiphase CFD simulations for different angles of inclination and waters levels upstream of the sluicegate were done by the authors in the paper “Theoretical and numerical analysis of the pressure distribution and discharge velocity in flows under inclined sluice gates” (AJKFLUIDS2019 5020). Using the values determined in this previous paper, parametrized model equations for the pressure and momentum integrals in dependency of the angle of inclination and upstream water levels were derived in this work. These polynomial approaches have been used to determine the three unknown physical quantities in the integral momentum balance: the pressure integral at the sluice gate, the pressure integral under the sluice gate and the momentum integral of the flow under the sluicegate. The polynomial approaches are shown in detail in this work.

The present paper presents some experimental and numerical modeling of the Newtonian and viscoelastic flows in bifurcated configurations of pipes, for stationary and non-permanent regimes. The main purpose of this study is to select an optimal design of the pipes ramifications, for minimizing the local pressure losses and to improve the efficiency of fluid transportation. The method is based on the transformation of the flow field obtained with particle image visualization technique, for different Reynolds numbers. Based on experimental results will be established optimum geometry of the ramifications. The results will be used as the boundary conditions for numerical modeling. The experimental measurements were performed into a closed circuit of pipes, with different diameters, consisting of a centrifugal pump supplied by a tank, sensors for estimating the pressure losses and devices for measuring the flow rate. It is detailed presented in a dedicated paragraph. The main pipe is connected to a transparent bifurcation with branches at different angles from the main pipe axis. The measurements illustrate that the flow has different aspects, depending on the bifurcation’s angle. The numerical simulations are performed with Fluent CFD based on the volume numerical method, to obtain the Navier-Stokes solutions for the Newtonian model in the laminar or turbulent flow conditions. A pre-processor has been used to create the geometry of the bifurcation and to generate the mesh. The 3D-flow domain contains 944390 volumes, tetrahedral hybrid. It was obtained the numerical solutions of the fluid flow in branching pipes for the Reynolds numbers from 1000 up to 40000. The governing equations were assumed from the k-ε model for turbulence flow, the equation of continuity, equation of fluid motion, and the transport equation. Finally, some conclusions and references are presented.

This paper demonstrates the application of artificial intelligence-driven turbomachinery design, its numerical performance predictions and their numerical validation. A common problem in the industrial application of turbomachinery is that readily available turbomachines are not necessarily matching the desired performance targets (performance characteristics) required for a specific application. Many machines operate under off-design conditions and hence are not operating at maximum efficiency. Traditional numerical analysis and response-driven optimization methods are ineffective and still too time-consuming and are particularly sensitive to changing performance targets. Most commercially available optimization algorithms are based on maximizing or minimizing a response function, for instance the standard error from a desired target performance characteristic of a turbomachine, by changing design variables. This work uses a newly developed artificial intelligence-based approach that is not dependent on the specific design target using the turbomachinery design software AxSTREAM from SoftInWay. Here a neural network was trained within a constraint design space by many samples of design variables and their respective numerical performance predictions. For the numerical verification of the designs the solver Simcenter STAR-CCM+ from Siemens was used. Subsequently the trained neural network was applied to generate a set of design parameters that satisfied the physically feasible desired target performance characteristics very fast. This trained neural network enabled an effective reversal of the traditional iterative design process where now the desired target performance characteristics became the input and the geometry became the output, turning it into a generative inverse design process. This method was applied to generate a centrifugal compressor design within a given geometrically and physically constraint design space. A specific desired target performance characteristic was chosen. The generated designs and results are presented in detail.

This is the first part of a two-part paper focusing on the flow instabilities of low-specific pump turbines. In this part, results of the CFD simulations and experiments of the research carried out on a low specific speed model pump-turbine at HSLU (Lucerne University of Applied Sciences) Switzerland are presented. The requirements of a stable and reliable pump-turbine operation under continuously expanding operating ranges, challenges the hydraulic design and requires new developments. Previous research at the HSLU [1] analyzed the instabilities of a medium specific speed (i.e. n q = 45) pump turbine. This paper presents the results of experimental (model pump-turbine at the test rig) and numerical (CFD) investigations of the pump-turbine instabilities of a low specific speed (n q = 25) pump-turbine in the turbine operating mode in the region of S-shaped characteristics (that is where the pump-turbine is synchronized and oscillations may occur during load rejection). The four-quadrant characteristics of a low specific speed model pump-turbine with two similar runners differentiating in the size (diameter) are measured. Testing of both runners with the same guide vane system provided information about the effects of the increased vaneless space (the distance between the guide vanes and runner) on the pump-turbine performance and stability both in turbine- and pump operating modes. A CFD methodology by using different numerical approaches and applying several turbulence models is developed in order to accurately predicting the characteristics of the reversible pump-turbines in the S-shaped region (speed no load conditions) as well as analyzing the flow features especially at off-design conditions. This CFD model is validated against the experimental data at 6° and 18° guide vane openings in turbine operating mode. With the measured data of the unsteady pressure measurements and detailed investigation of unstable ranges on the pump-turbine characteristics, flow instabilities in the low-specific speed model pump-turbine are analyzed. Relevant frequencies such as rotating stall, steady and unsteady vortex formations are determined. Based on the analysis of the experimental data and CFD results focusing especially on the flow features in the vaneless space and at the runner inlet, the onset and development of the flow instabilities are explored.

Fuel efficiency is very important when designing new vehicles. There is a continuous demand for lower fuel cost to customers. Many researchers have started to investigate the aerodynamics of tires. Since the experimental approaches are time consuming and costly, numerical methods have been developed to model the air flow around the tire. One of the challenges for modeling the tire is rotating boundary and contact patch. In the CFD model, both rotating and tire deformation have to be considered to get accurate predictions. However, most of the current methods neglect the tire deformation and contact patch. Therefore, in this study, three modeling approaches are compared for the modeling of tire rotation. They include rotating wall, multiple reference frame and sliding mesh. In CFD simulation, another challenge is mesh generation due to the sharp edge and large curvature around the contact patch. In order to generate mesh efficiently. A hybrid mesh which combines hex elements and polyhedral elements is used in this study. In addition, three different tire designs are investigated, including smooth tire, smooth tire with grooves and grooved tire with open rim. The results show that tire with open rim has the highest drag. Sliding mesh provides the most accurate predictions regarding of aerodynamic drag.

Vehicle evaporative emission is one of the most important sources of pollution from a gasoline-fueled vehicle. Since international regulations on Volatile Organic Compounds (VOC) emission are becoming increasingly stringent every year, the study of the VOC generation has become of fundamental importance. It is known that VOC generation is particularly high during the refueling phase: fresh fuel coming from the refueling nozzle impacts on the filling pipe wall and it is a source for sloshing in the fuel tank. Fuel vapor generated can be collected by a vapor recovery nozzle and stored in the gas station tank (Stage II vapor recovery system, European normative) or trapped by the vehicle carbon canister (On-board Refueling Vapor Recovery system, U.S. normative). In this activity, an automotive gasoline fuel tank for U.S. applications has been used for both experimental and numerical analyses, provided by FCA. Experiments were performed in FCA laboratories, in a sealed and thermal controlled environment (mini-SHED): vapor flow exiting the fuel tank during refueling has been measured, and fuel vapor mass has been evaluated by dynamically measuring the weight variation of a carbon canister filter connected to the fuel tank vent system. A CFD model was built based on CAD geometries provided by FCA, and numerical analysis of the refueling process has then been executed by using a commercial 3D CFD software. Results were then compared with experimental data. This activity is a part of a collaboration between University of Naples Federico II and FCA Italy about fuel vapor emissions control and prediction.

A two-fluid atomizer has been frequently used in a wide range of industries for various purposes such as painting, cleaning particles and snow making. In particular, the manufacturing of advance semiconductors using sensitive devices such as organic light emitting diodes (OLED) and dynamic random access memory (DRAM), require high performance nozzle. The droplets sprayed with a high relative gas velocity are widely used for cleaning particles. In this paper, two-fluid atomizer is numerically studied according to four variables to confirm the effect on the atomizer performance. The numerical results using the discrete phase model (DPM) with several break-up models are compared with the experimental data measured by the phase doppler particle analyzer (PDPA). Design of experiment (DOE) and genetic algorithm (GA) were used to obtain design points, and conduct sensitivity analysis, respectively. The results showed that the WAVE model has a good agreement compared to the other models, and the orifice diameter is a crucial factor for this model to determine the performance of Weber number and pressure.

Computational Fluid Dynamics (CFD) models have been regarded as inevitable tools in the design of various aerodynamics applications like formula 1 cars, wind turbines, airfoil design, and many others. Such models rely on applying advanced numerical methods to solve the set of Navier-Stokes equations and other auxiliary models to quantify the aerodynamics performance, such as lift and drag in airfoil applications. However, currently adopted advanced mathematical models that are used to predict airfoil performance, though are essential tools in the advancement of aviation industry, incur large computational costs. As a primary step, an approximate model of an airfoil is built for the sake of reducing computational cost while preserving accuracy. The approximate model is based on creating a simplified algebraic model which is suitable then to perform aerodynamic design optimization rather than solving the highly non-linear set of continuity and momentum equations. In this work, the non-intrusive polynomial chaos expansion (NIPC) technique is employed on a NACA-2412 airfoil. The main objective of this research is to investigate the performance of the NIPC model with different orders on solution accuracy. A methodology is designed by first developing a full CFD model of the NACA-2412 airfoil. An experimental setup of the airfoil was then prepared with the variations of lift and drag coefficients under different operative conditions were reported. The experimental data were used to validate the numerical results generated by the CFD simulations. The surrogate model was then constructed via the NIPC technique. The performance of the surrogate model was then benchmarked with CFD results under different flow and operating conditions. Analysis was also performed to investigate the effect of polynomial order on the solution accuracy. Results showed that for a given data set size, increasing the order of the polynomial would deteriorate the solution accuracy. At a certain order k, the analytical solution starts diverging especially for values of angle of attack close to −60 and 60°.

An optimized heat exchanger design is always a challenge to designers. This study presents a simplified simulation study on thermal-hydraulic of a small heat exchanger. Both the heat transfer coefficient and pressure drop are simulated for a nine tube shell and tube heat exchanger. A detailed mesh sensitivity analysis is performed to arrive at numerically converged solution. The results of the study are compared with Bell Delaware (BD) and Flow Stream (FS) analytical methods. Results obtained using all three methods show similar trends. Heat transfer coefficient determined using Bell Delaware method is found to be in good agreement with that of ANSYS CFX, whereas pressure drop calculated using Flow stream method is within small percentage difference with CFX results. Overall, the simulation results are verified by the results obtained using analytical methods.

Fluid flows in a microchannel with highly ordered laminar fashion. For this reason, two different fluid streams cannot mix easily, or it takes a very long time. The problem becomes intense for large molecules such as peptides, proteins, and nucleic acids during rapid mixing for biochemical applications in a microfluidic device. Many researchers tried to solve this problem by applying an electric potential. In this work, a numerical simulation was performed on a 2D micromixer. Four symmetric electrodes were placed on the wall of a straight microchannel of width 19 μm. The electroosmotic slip velocity boundary condition was used to create the turbulence on the laminar fluid stream. It was found that this model creates a well-mixed flow at the channel outlet. Then the input parameters were changed to compare the mixing performance in terms of concentration distribution at the channel outlet. Channel width, inter-electrodes gap, the magnitude of electric potential, frequency of the electric potential and asymmetricity of the electrodes were changed and results were compared. An experimental micromixer like the numerical model was fabricated by dc magnetron sputtering machine. Four gold electrodes (thickness, 120 nm) were sputtered on top of a silicon substrate. The value of the input parameters was chosen based on the results obtained from the numerical simulation. To test the mixing functionality of our device the movement of tracer particles was tracked down on the zone surrounded by four electrodes. The micro-PIV (Particulate Image Velocimetry) system was used to analyze the movement of the tracer particles and visualize the flow field in the mixing zone. The magnitude of the AC electric potential and frequency was changed to find out the optimum input parameters for the micromixer. These results could play an important role to design and improve a micromixer design using an AC electric field. A micromixer has many potential applications in biology (DNA analysis, enzyme Screening), chemistry (synthesis, polymerization) and detection (drug discovery, diagnosis).

Simulating convective heat transfer using traditional numerical methods requires explicit definition of thermal boundary conditions on all boundaries of the domain, which is almost impossible to fulfill in real applications. Here, we address this ill-posed problem using machine learning techniques by assuming that we have some extra measurements of the temperature at a few locations in the domain, not necessarily located on the boundaries with the unknown thermal boundary condition. In particular, we employ physics-informed neural networks (PINNs) to represent the velocity and temperature fields while simultaneously enforce the Navier-Stokes and energy equations at random points in the domain. In PINNs, all differential operators are computed using automatic differentiation, hence avoiding discretization in either space or time. The loss function is composed of multiple terms, including the mismatch in the velocity and temperature data, the boundary and initial conditions, as well as the residuals of the Navier-Stokes and energy equations. Here, we develop a data-driven strategy based on PINNs to infer the temperature field in the prototypical problem of convective heat transfer in flow past a cylinder. We assume that we have just a couple of temperature measurements on the cylinder surface and a couple more temperature measurements in the wake region, but the thermal boundary condition on the cylinder surface is totally unknown. Upon training the PINN, we can discover the unknown boundary condition while simultaneously infer the temperature field everywhere in the domain with less than 5% error in the Nusselt number prediction. In order to assess the performance of PINN, we carried out a high fidelity simulation of the same heat transfer problem (with known thermal boundary conditions) by using the high-order spectral/hp-element method (SEM), and quantitatively evaluated the accuracy of PINN’s prediction with respect to SEM. We also propose a method to adaptively select the location of sensors in order to minimize the number of required temperature measurements while increasing the accuracy of the inference in heat transfer.

The purpose of this study is to clarify the formation characteristics and production conditions of two-layer droplets using coaxial nozzle. In this study, we focus on Newtonian fluid only to pay attention to the fundamental formation characteristics of two-layer droplet. Also, the three liquids flowing in the apparatus were assumed to have the same viscosity and density. First, theoretical equations concerning the outer diameters of the single layer droplet and the two-layer droplet were obtained, and a conditional expression for detaching both nozzles simultaneously from the nozzle in dripping was obtained. These theoretical equations were verified using numerical analysis. By analyzing with various parameters changed, the following six formation modes could be confirmed. 2 interface both dripping, 2 interface both jetting, Outer interface is jetting and The inner interface is dripping, 2 interface comes into contact and the encapsulated liquid is discharged to the outside, Two or more droplets are formed in the interior, Liquid droplets containing liquid droplets and liquid droplets not containing liquid droplets are alternately formed. The validity of each theoretical expression and conditional expression was also be confirmed.

The flow under sluice gates is nowadays frequently still determined by empirical approaches, based on the Bernoulli equation and a specific discharge coefficient which depends on the geometry of the sluice gate. This discharge coefficient is determined either from potential theory approaches or from a variety of experimental series. Based on Malcherek’s new momentum balance theory approach, the flow under inclined sluice gates can be described now on a physical approach. While the pressure distribution of the vertical sluice gate, which was investigated by the authors in previous works, results in a horizontal acting force only, the pressure distribution of the inclined sluice gate brings an additional force component acting in the vertical direction. The magnitude and the sign of the force in the vertical direction depends on the sign and the value of the angle of inclination. With the commercial CFD solver Star-CCM+ from Siemens PLM, the flow under inclined sluice gates was investigated in detail, to be compared with Malcherek’s momentum balance theory. For this basic investigation, boundary layer effects and 3D effects were first neglected. For various angles of inclination and water levels the pressure distribution on the ground under the sluice gate and on the surface of the sluice gate itself, were evaluated and mathematical functions were introduced to describe the pressure distributions. These results were compared with the results from the vertical sluice gate. Also the discharge velocity and the volumetric flow rate were analyzed and compared with the Malcherek’s new momentum balance theory for inclined sluice gates.

In this paper an axial piston pump is studied using numerical and experimental approaches. The pump, manufactured by the company Continental Hydraulic Inc., has a maximum operating pressure limit of 280 bar and a displacement of 65.9 cm 3 /rev; it is a variable swashplate design with nine-piston, suitable for open circuit application, medium to high pressure. Two numerical approaches have been compared to simulate the pump units. First of all, an accurate 3D -CFD model has been built up putting emphasis on the description of the detailed features of the flow through the unit. Specific attention has been reserved to the flow losses due to cavitation. Then a fast-lumped parameter approach has been built up focusing the attention on the valve plate geometry. Using the proposed numerical approaches, it is possible to fully understand the unit operation with, obviously, different assumptions and level of result details. Numerical models have been validated with an experimental data performed by the pump manufactured on their test ring with high agreement. As results, the proposed analysis permit to gain a high level of understanding of the operation of the unit finding the critical aspects and giving important information to the designer in order to improve the pump performance. By the end a new valve plate has been designed to improve the pump volumetric efficiency and to reduce the flow ripples and the reverse flow.

Coronary artery disease (CAD) is among the foremost causes for human death worldwide. This study aims at investigating the performance of different boundary condition model types to characterize CAD functional significance. In addition, alternate models to estimate FFR using any different combination of boundary conditions at inlet and outlet were analyzed. In the first type of boundary condition, an outflow resistance model is used combined with a fixed pressure at inlet. In the second model of boundary conditions, constant pressure values are imposed at the domain inlet and outlet/s sections. In the third model, a zero diffusion flux is applied at outlet with a pre-specified flow rate at inlet. Numerical simulations performed on healthy and stenosed idealized and physiological arterial models revealed the superiority of the first type of boundary condition to directly capture the level of ischemia in diseased arteries. However, in this model, special numerical treatment at the outflow boundary is needed to dampen pseudo numerical reflections entering the computational domain. Alternative simple methods are developed to tackle the problem incurred in the second and third types of boundary condition types. The alternate models are effective for carrying extensive parametric studies with minimal computational effort. The new developed methods allow results generated via generic simulations under any specified boundary condition type to correctly estimate CAD functional significance. The obtained surrogate models account for the effects of the patient-specific physiologic parameters and can be easily incorporated without modifying existing CFD codes. Moreover, where it is unfeasible to experimentally incorporate the downstream effects of a given diseased arterial segment, an important aspect the alternative models provide is that they can be easily adopted by experimentalists through building in-vitro arterial models to assess the functional significance of the obstruction caused by the disease and its relation to any given patient specific physiologic parameter.

Supercritical octane flows that undergo thermal cracking in a heated circular tube were numerically investigated using our numerical methods based on the preconditioning method solving the compressible Navier–Stokes equations with the thermophyical properties from the Reference Fluid Thermodynamic and Transport Properties Database (REFPROP). The simple thermal-cracking model for octane was developed from the results calculated by KUCRS and Cantera software, assuming mild cracking condition and single-fluid flow. Supercritical octane flows were simulated under wall temperatures that would and would not encourage thermal cracking. Slight temperature differences affected the velocity distribution in the heated pipe because of the change in density. In low-wall-temperature conditions without thermal cracking, the simulated outlet temperatures were in good agreement with experimental results. Octane near the heated wall was decomposed by thermal cracking in the high wall temperature conditions. The wall temperature and the residual time affected the conversion rate of the thermal-cracking conversion rate. The present numerical methods underestimated the experimentally measured conversion rate, though the rough trends of the conversion rates were captured.

Turbulent flow in a homogeneous porous medium was investigated through the use of numerical methods by employing the Reynolds Averaged Navier-Stokes (RANS) modeling technique. The focus of our research was to study how microscopic vortices in porous media flow influence the heat transfer from the solid obstacles comprising the porous medium to the fluid. A Representative Elementary Volume (REV) with 4 × 4 cylindrical obstacles and periodic boundary conditions was used to represent the infinite porous medium structure. Our hypothesis is that the rate of heat transfer between the obstacle surface and the fluid ( q avg ) is strongly influenced by the size of the contact area between the vortices and the solid obstacles in the porous medium ( A vc ). This is because vortices are regions with low velocity that form an insulating layer on the surface of the obstacles. Factors such as the porosity (φ), Pore Scale Reynolds number ( Re p ), and obstacle shape of the porous medium were investigated. All three of these factors have different influences on the contact area A vc , and, by extension, the overall heat transfer rate q avg . Under the same Pore Scale Reynolds number ( Re p ), our results suggest that a higher overall heat transfer rate is exhibited for smaller contact areas between the vortices and the obstacle surface. Although the size of the contact area, A vc , is affected by Re p , the direct influence of Re p on the overall heat transfer rate q avg is much stronger, and exceeds the effect of A vc on q avg . The Pore Scale Reynolds number, Re p , and the mean Nusselt number, Nu m , have a seemingly logarithmic relationship.

A numerical analysis of an air-cooled proton exchange membrane fuel cell (PEMFC) has been conducted. The model utilizes the Eulerian multi-phase approach to predict the occurrence and transport of liquid water inside the cell. It is assumed that all the waste heat must be carried out of the fuel cell with the excess air which leads to a strong temperature increase of the air stream. The results suggest that the performance of these fuel cells is limited by membrane overheating which is ultimately caused by the limited heat transfer to the laminar air stream. A proposed remedy is the placement of a turbulence grid before such a fuel cell stack to enhance the heat transfer and increase the fuel cell performance.

A numerical study is conducted to investigate fluidic actuation with steady injection for active flow control and drag reduction in an Ahmed body. Numerical results are obtained for the unsteady three-dimensional Navier Stokes equations for both baseline as well as steady injection cases. This study examines the use of active flow control devices at the rear of the 25-deg Ahmed model to reduce drag by controlling an unsteady wake. The present work demonstrates that URANS model with grid refinement at critical locations can accurately describe the aerodynamics around the bluff body with computational time of several days compared to several weeks with traditional LES simulations. In order to modify the wake and reduce the pressure drag, active flow control technique using steady blowing was applied through a narrow slit along all rear edges of the model. The effect of inlet velocity for the baseline simulations was analyzed. Computed Results showed AFC achieves significant reduction in the drag coefficient (C d ) values over the baseline simulations.

A numerical analysis of a proton exchange membrane fuel cell (PEMFC) that contains a perforated metal plate at the cathode side has been conducted. The model utilizes the Eulerian multi-phase approach to predict the occurrence and transport of liquid water inside the cell. The PEMFC that was modelled contained micro-channels at both anode and cathode side. Results suggest that despite the fact that the inlet gases are fully saturated (RH = 100%), the holes in the metal sheet remain in the single phase, and the predicted maximum current densities are accordingly high. The high thermal conductivity of the metal sheets result in only a moderate temperature increase in the cell, and the fuel cell membrane is predicted to be hydrated under all conditions investigated. The fact that the cathode channel and the holes in the metal sheet remain dry is attributed to the high pressure drop inside the flow channel.