Computational Fluid Dynamics Predictions Research Articles

Experimental Characterization of a Bladeless Air Compressor

Abstract The Tesla compressor is an innovative technology that offers a unique approach to fluid compression. Unlike traditional compressors that use rotating blades, bladeless compressors utilize closely spaced disks to create compression. The purpose of this article is to design a prototype Tesla air compressor with optimal design parameters and investigate the performance and loss characteristics based on numerical analysis and experimental demonstration. The prototype model has been numerically investigated at different rotational speeds, and the results have been compared with those obtained in experiments. Computational fluid dynamics (CFD) simulations indicate that the rotor-only efficiency is greater than 90% at very low mass flowrates, while the coupling of the rotor and volute leads to a total-to-static efficiency of approximately 58% (without losses) at 14 g/s. At a nominal mass flow of 4 g/s, the highest total-to-static pressure ratio would be around 1.27. Experimental results indicate leakage losses greatly reduce net mass flow, while pressure ratio values are in good agreement with CFD predictions. During this experiment, a maximum isentropic efficiency of 32.4% is measured. Indeed, the prototype included ventilation and leakage losses, which were not modeled in the CFD analysis. It is remarkable that the compressor does not show any unstable behavior down to zero mass flow (closed valve test), where the CFD and the experiment show consistent pressure ratios. An estimation of the losses from end-wall friction and leakage flow is carried out using numerical simulations at different exit radial clearances. Increasing radial clearance results in an increase in leakage and end-wall power loss, the latter being driven mainly by the axial clearance with the casing, which remained unchanged. To minimize leakage, a Teflon ring has been used as a first measure. Numerical calculations have indicated that the leakage rate is approximately 6 g/s at design speed. A brush seal-type solution can improve the sealing system to reduce leakage.

Practical computational fluid dynamic predictions of a cyclist in a time trial position

On a flat road, at race speeds, aerodynamic drag is the main resistive force a cyclist must overcome. Computational fluid dynamics (CFD) can be a useful tool to predict and understand the complex flow and, therefore, drive developments to reduce drag. However, cycling aerodynamics is complex. The effects of Reynolds number, surface roughness, boundary layer transition, flow separation, and turbulent wakes are challenging to accurately predict. High fidelity time-resolved computations, such as Large eddy simulations (LES), require high-performance computing and lengthy simulation times. This paper examines whether lower fidelity CFD, such as Reynolds averaged approaches, can predict the drag of a cyclist with sufficient accuracy and within practical timescales on a desktop PC. Wind tunnel tests of a rider model (without bicycle) were conducted at Reynolds numbers equivalent to speeds of ~ 20–70 km/h. Measured drag showed a notable Reynolds number dependency with the drag coefficient reducing almost linearly by ~ 20% from 0.88 to 0.71. The computational accurately replicated this relationship but only when employing a boundary layer transition model. The steady computations underpredicted the magnitude of the measured drag coefficient by ~ 3% but the unsteady computations were within ~ 2%. Examination of the predicted flow field revealed variations in boundary layer transition, separation, and wake formation from each body part which combine in a complex wake system. Overall, the data confirm validity and suitable accuracy of the CFD, and therefore this provides a practical time and cost-effective tool for further examination of drag reduction within cycling.

A Comparative Study on the Prediction of Hydrogen, Nitrogen, and Water Vapor of Regenerative Hydrogen Pump With Different Turbulence Models

Abstract The flow in a regenerative hydrogen pump used in a proton exchange membrane (PEM) fuel cell system is complex, including velocity mixing, streamline distortion, swirling flow, corner flow, and possible boundary separation. Experimental measurement and computational fluid dynamics (CFD) prediction are the main methods used to evaluate such performance. In this work, regenerative hydrogen designed for fuel cell electric vehicles with an impeller diameter of 91 mm and a shaft speed of 22,000 rpm is tested with a mixture of nitrogen, hydrogen, and water vapor. During the test, the flowrate and shaft speed ranges are 151–881 L/min and 8000–22,000 rpm, respectively. The inlet pressure and temperature are 171 kPa and 66 °C, respectively. Then, the flow is predicted by the k − ε model, the renormalization group (RNG) k − ε model, the explicit algebraic Reynolds stress models (EARSM) and the shear-stress transport (SST) detached eddy simulation (DES) model. The differences between the tested and predicted performances are compared. With these results, the velocity distribution in the side channel, the radial force of the impeller and casting, and the changes in the downstream pressure and velocity are analyzed in consideration of the ability of the turbulence models to simulate each characteristic flow. On this basis, the differences and abilities of the turbulence models for predicting the flow in regenerative hydrogen pumps are summarized.

AN AERODYNAMIC INVESTIGATION OF A HIGH-PRESSURE TURBINE USING ROTOR CASING STATIC PRESSURE MEASUREMENTS AT ENGINE REPRESENTATIVE CONDITIONS WITH DIFFERENT TIP DESIGNS, TIP GAPS AND INLET TEMPERATURE PROFILES

Abstract A rotating High-Pressure (HP) turbine, in modern aircraft engines, is subjected to high cyclic thermal and mechanical loads. Shroudless turbines experience high heat loads on the rotor tip and casing, which makes them one of the life-limiting components for an engine. If the rotor tip starts to erode, then the tip clearance increases which increases the over-tip leakage flow, resulting in reduced stage efficiency and ultimately, the engine lifetime. The Oxford Turbine Research Facility (OTRF) is a high- speed rotating transient test facility that allows unsteady aerodynamics and heat transfer measurements, at engine representative conditions. This paper presents an experimental investigation, of the HP turbine rotor casing aerodynamics, performed in the OTRF. Steady and unsteady casing static pressure measurements were acquired, using pneumatic lines and high-frequency response (∼ 100 kHz) Kulite pressure transducers respectively. The single-stage HP turbine consisted of cooled vanes (featuring film and trailing edge slot cooling), and uncooled rotor blades. Three different tip designs (two squealers and one flat) were tested, at two tip gaps, and with two inlet temperature profiles that included a spatially uniform total temperature profile and an engine representative HP turbine inlet total temperature profile. In parallel, a numerical investigation of the experimental test cases is presented using unsteady Computational Fluid Dynamics (CFD) predictions. The experimental results from this study provide a unique dataset to validate numerical models.

Blast wave ingress into a room through an opening – Review of past research and US DoD UFC 3-340-02

Blast wave ingress into a room through a facade opening results in complex pressure-time loadings on interior surfaces due to shock diffraction and interior reflections. The U.S. DoD UFC 3-340-02 Structures to Resist the Effects of Accidental Explosions includes a method to predict internal loading for such cases. Parameters such as the opening size, room dimensions and the external pressure wave characteristics influence the interior loading. Recent work suggests that the UFC methodology might overpredict the interior loading by some 600%. Such conservatism can result in over-engineered or prohibitively expensive protective solutions. In this paper we critically review the methodology of the UFC, that of Kaplan’s preceding work (on which the UFC relies), and the experimental data that informed both these works. Through a series of 45 case-studies we compare the UFC and Kaplan’s predictions with those of a computational fluid dynamics (CFD) model. The UFC consistently overpredicts the CFD area-averaged peak pressure of the back wall by up to 290% and the side-wall by up to 425%. Similarly, the UFC overpredicted the CFD side wall positive phase impulse by up to 565%. By contrast, the UFC predicted back wall positive phase impulse was similar to the CFD results. As our CFD results for side and back walls are area averaged, and not solely for the wall centre-point, as in other recent work, our paper gives support for the use of CFD prediction over the UFC for cost-effective design of structures to resist blast ingress.

Computational fluid dynamics investigation of pesticide spraying by agricultural drones

Precise control over pesticide spraying by agricultural drones requires fundamental research of multiphase flow, heat and mass transfer of liquid droplets in downwash flow. In this study, water was used as a carrier agent in pesticide formulations, in which the liquid droplets exhibit a Newtonian fluid behavior. A general computational fluid dynamics (CFD) model that characterizes propeller motion coupled with droplet evaporation and deposition was developed. The downwash flow generated by the propeller rotation was simulated using a multiple reference frame method along with the SST-k-ω turbulence model. Spraying of liquid droplets was simulated using a discrete phase model. The flow model validation was conducted by comparing the simulated velocities with experimental data, and the spray model validation was completed by a comparison of droplet depositions from CFD predictions and experiments. The results indicated that the droplet deposition fluctuates with an increase of propeller speed, and that both temperature and relative humidity affect the droplet deposition. In addition, the relation between the number of particles and the impact velocity was identified quantitatively, impact velocity with respect to particle diameter was predicted, and the effects of surface inclination, surface roughness, and crosswind speed on droplet deposition were analyzed. Moreover, an in-depth discussion about the intrinsic relation between downwash flow and droplet spraying was conducted.

Deforming Patient-Specific Models of Vascular Anatomies to Represent Stent Implantation via Extended Position Based Dynamics.

Angioplasty with stent placement is a widely used treatment strategy for patients with stenotic blood vessels. However, it is often challenging to predict the outcomes of this procedure for individual patients. Image-based computational fluid dynamics (CFD) is a powerful technique for making these predictions. To perform CFD analysis of a stented vessel, a virtual model of the vessel must first be created. This model is typically made by manipulating two-dimensional contours of the vessel in its pre-stent state to reflect its post-stent shape. However, improper contour-editing can cause invalid geometric artifacts in the resulting mesh that then distort the subsequent CFD predictions. To address this limitation, we have developed a novel shape-editing method that deforms surface meshes of stenosed vessels to create stented models. Our method uses physics-based simulations via Extended Position Based Dynamics to guide these deformations. We embed an inflating stent inside a vessel and apply collision-generated forces to deform the vessel and expand its cross-section. We demonstrate that this technique is feasible and applicable for a wide range of vascular anatomies, while yielding clinically compatible results. We also illustrate the ability to parametrically vary the stented shape and create models allowing CFD analyses. Our stenting method will help clinicians predict the hemodynamic results of stenting interventions and adapt treatments to achieve target outcomes for patients. It will also enable generation of synthetic data for data-intensive applications, such as machine learning, to support cardiovascular research endeavors.

A comprehensive study of recent studies on the efficiency of axial flow turbines with an investigation on blade profile modifications in stator and rotor assemblies

Axial flow turbines are crucial in energy production and propulsion across diverse applications. As global energy needs rise, optimizing turbine efficiency is paramount. This review delves into the aerodynamic design of turbine blades, specifically examining blade profile modifications in both stator and rotor assemblies of state-of-the-art models proposed in the studies from 2019 to 2024. The focus is on mitigating performance discrepancies between idealized simulations and real-world applications, which present significant challenges such as inconsistencies in computational fluid dynamics (CFD) predictions and manufacturing constraints. Key findings from this review highlight a potential efficiency gain of 1%–3% through optimal blade designs that reduce incidence losses, secondary flows, and tip vortex formation. Advanced modeling techniques, including high-fidelity, multi-objective optimization with machine learning, are evolving to better predict and enhance turbine performance. However, gaps remain in system-level integration and the limited experimental data restricts comprehensive validation of these new designs. The insights from this review will aid the research community by identifying critical areas for future investigation, such as integrating blade aerodynamics with heat transfer and structural mechanics. Further, it emphasizes the need for exploring combinations of passive and active flow control strategies to fully harness the benefits of blade profile enhancements. These efforts are crucial for achieving substantial improvements in turbine efficiency, which are essential for meeting the growing demands for sustainable and efficient energy production.

Effectiveness of Three Turbulence Modeling Approaches in a Crosswind–Sedan–Dune Computational Fluid Dynamics Framework

The aerodynamic loads of a sedan experience significant fluctuations when passing by a sand dune at the roadside under crosswinds, which can easily cause yawing and overturning. Computational fluid dynamics (CFD) methods, based on different turbulence modeling approaches, yield different aerodynamic results for sedans. This study aims to investigate the effects of three prevailing turbulence modeling approaches (renormalization group (RNG) k-ε, large eddy simulation (LES), and improved delayed detached eddy simulation (IDDES)) on the aerodynamic characteristics of a sedan passing by a sand dune under crosswinds. The CFD dynamic mesh models are constructed using the “mosaic” mesh technique to account for the dune–air–sedan interaction. The reliability of the CFD prediction method is verified by comparing it with field test results. The predictive capabilities of the three turbulence modeling approaches are compared in terms of aerodynamic loads and flow field characteristics. The simulation of sand particle movement is conducted through the discrete phase model, aiming to assess the impact of wind–sand flow on the aerodynamic properties of sedans. Corresponding results show that the aerodynamic loads predicted by the LES model closely match (within 4.4–7.5%) the corresponding data obtained from field tests. While the IDDES and LES models demonstrate similar abilities in characterizing the wind field details, and their results exhibit maximum differences of 8.3–15.7%. Meanwhile, the maximum difference between the results obtained by the RNG k-ε and LES models ranges from 14.8% to 18.4%, attributed to its inability to capture subtle changes in the vortex structure within the flow field. This work will provide a numerical modeling reference for studies on the wind–sand flow and the aerodynamic characteristics of sedans running through the desert, and it has implications for the safe driving of sedans under extreme conditions.

Numerical modeling and experimental validation of fluid flow in micro- and meso-fluidic siphons

Siphons have been used for thousands of years to transfer fluids without the use of pumps or power and are present in our daily lives. Paradoxically, it is only in recent decades that the operation of siphons has been fully clarified, which is now understood to be exclusively linked to gravity and molecular cohesion. Siphons are uniquely able to offer automatic, intermittent flow, yet present the main drawback of requiring a source of energy to induce initial flow. Our research team has recently disclosed a microfluidic siphon able to self-prime and deliver a sequence of bioanalytical reagents, previously demonstrated for high-performance, multi-reagents diagnostic testing. Here we show for the first time 2D and 3D computational fluid dynamics (CFD) modeling and the experimental characterization of fluid flow in a range of miniaturized hydrophilic siphons of varying hydraulic liquid height-to-length ratios, ΔH/LT = 0–0.9, using fluids of varying viscosities. CFD simulations using velocity- and pressure-driven inlet boundary conditions were generally in good agreement with experimental fluid flow rates and pressure-balance predictions for plastic ∼0.2 mm and glass ∼0.6 mm internal diameter microfluidic siphons. CFD predictions of fluid flow in “meso-scale” siphons with 1 and 2 mm internal diameters also fully matched normalized experimental data, suggesting that miniaturized siphons are scalable. Their discharge rate and pressure drop are readily predicted and fine-tunable through the physical properties of the fluid and some design parameters of the siphon. The wide range of experimental and numerical parameters studied here provide an important framework for the design and application of gravity-driven micro- and meso-fluidic siphons in many applications, including but not limited to life sciences, clinical diagnostics, and process intensification.

Predicting the Adhesive Layer Thickness in Hybrid Joints Involving Pre-Tensioned Bolts.

While most academic studies focus on the properties of cured joints, this research addresses the manufacturing process of hybrid joints in their uncured state. Hybrid joints that combine adhesive bonding with pre-tensioned bolts exhibit superior mechanical performance compared to exclusively bonded or bolted joints. However, the adhesive flow during manufacturing in hybrid joints often results in a nonuniform adhesive thickness, where obtaining an exact thickness is crucial for accurate load capacity predictions. This paper presents experiments involving three different adhesives, providing precise measurements of the adhesive layer thickness distribution, which served as a reference when evaluating and validating the subsequent numerical predictions. The numerical predictions were performed using computational fluid dynamics (CFD) to model the flow behavior of the adhesives during the bonding process and their interactions with the metal substrates. The CFD predictions of the adhesive layer thickness showed good agreement with the experimental data, with the relative differences between the average experimental and numerical thickness values ranging from 4.07% to 27.1%. The results were most accurate for the adhesive with sand particles, whose particles remained intact, ensuring that the adhesive's rheology remained unchanged. The results highlight the importance of the rheological behavior of the adhesive in the final distribution of the adhesive layer thickness, thereby expanding the understanding of these joints.

Back to Bernoulli: a simple formula for trans-stenotic pressure gradients and retrospective estimation of flow rates in cerebral venous disease

BackgroundVenous sinus stenosis can be associated with cerebrovascular disorders. Understanding the role of blood flow disturbances in these disorders is often hampered by the lack of patient-specific flow rates. Our...

Aerodynamic and aeroacoustic design of electric ducted fans

This paper describes the aerodynamic and aeroacoustic design of an electric ducted fan (EDF). A prototype EDF was designed and built with three different rotor-stator sets to operate at design flow coefficients ϕd=[0.60,0.75,0.90]. Computational Fluid Dynamics (CFD) simulations show that changing the design flow coefficient changes the proportions of endwall and blade profile loss, with the ϕd=0.75 design providing the optimum balance. CFD predictions of aerodynamic performance are compared with experimental measurements and show good agreement. Data collected from full annulus Unsteady Reynolds-Averaged Navier Stokes (URANS) CFD simulations is used to predict tonal noise radiation using a numerical solution to Farassat's Formulation 1A, and compare favourably to acoustic measurements in an anechoic chamber. All three EDF iterations show similar levels of broadband noise radiation, although tonal noise radiation decreases with increasing design flow coefficient and results in more favourable Sound Quality Metrics performance. Design flow coefficient is shown to have a first-order impact on both the aerodynamic and aeroacoustic behaviour of the EDF, and it is proposed that an optimal design, encompassing both aerodynamic performance and reduced acoustic impact, can be achieved at design flow coefficients between ϕd=0.75 and ϕd=0.90.

A Computational Analysis of Turbocharger Compressor Flow Field with a Focus on Impeller Stall

Understanding the flow instabilities encountered by the turbocharger compressor is an important step toward improving its overall design for performance and efficiency. While an experimental study using Particle Image Velocimetry was previously conducted to examine the flow field at the inlet of the turbocharger compressor, the present work complements that effort by analyzing the flow structures leading to stall instability within the same impeller. Experimentally validated three-dimensional computational fluid dynamics predictions are carried out at three discrete mass flow rates, including 77 g/s (stable, maximum flow condition), 57 g/s (near peak efficiency), and 30 g/s (with strong reverse flow from the impeller) at a fixed rotational speed of 80,000 rpm. Large stationary stall cells were observed deep within the impeller at 30 g/s, occupying a significant portion of the blade passage near the shroud between the suction surface of the main blades and the pressure surface of the splitter blades. These stall cells are mainly created when a substantial portion of the inlet core flow is unable to follow the impeller’s axial to radial bend against the adverse pressure gradient and becomes entrained by the reverse flow and the tip leakage flow, giving rise to a region of low-momentum fluid in its wake. This phenomenon was observed to a lesser extent at 57 g/s and was completely absent at 77 g/s. On the other hand, the inducer rotating stall was found to be most dominant at 57 g/s. The entrainment of the tip leakage flow by the core flow moving into the impeller, leading to the generation of an unstable, wavy shear layer at the inducer plane, was instrumental in the generation of rotating stall. The present analyses provide a detailed characterization of both stationary and rotating stall cells and demonstrate the physics behind their formation, as well as their effect on compressor efficiency. The study also characterizes the entropy generation within the impeller under different operating conditions. While at 77 g/s, the entropy generation is mostly concentrated near the shroud of the impeller with the core flow being almost isentropic, at 30 g/s, there is a significant increase in the area within the blade passage that shows elevated entropy production. The tip leakage flow, its interaction with the blades and the core forward flow, and the reverse flow within the impeller are found to be the major sources of irreversibilities.

On the determination of the standing oblique detonation wave in an engine combustor using laser absorption spectroscopy of hydroxyl radical

Freejet experiments were conducted in the hypersonic flight-duplicated shock tunnel (JF-12) to understand the detonation combustion mode in the combustor of a standing oblique detonation ramjet (Sodramjet) engine prototype. Besides the traditional schlieren imaging to capture the oblique shock positions in the combustor, we implemented laser absorption spectroscopy of hydroxyl (OH) radical with three laser beams around the shock front. The Sodramjet engine combustor provides an ideal condition to measure OH because its molar fraction within the detonation front is estimated to exceed 0.03, which is much higher than other combustors. However, the harsh environment of freejet shock tunnel test poses a great challenge to the reliability of measurement systems. In this work, near-infrared tunable laser diode sensors centered at 1528 nm were chosen to measure the line-of-sight average of OH partial pressure. Continuous absorption measurements were conducted near the shock front, indicating a thin OH region after shock compression that could only be achieved by detonation combustion. The time-varied OH partial pressure was well predicted by the computational fluid dynamics (CFD) prediction. Our measurement results verified the detonation combustion of Sodramjet engine prototype and showed that in situ, real-time detonation diagnostics based on laser absorption spectroscopy is possible in freejet experiments of shock tunnel.

Assessment of CFD Predictions Using Experiments from a Heated Gas-Cooled Pebble Bed Facility

This paper presents computational fluid dynamics (CFD) simulations of the coolant gas flow in a pebble bed reactor core to assess the suitability of CFD models to accurately predict the temperature distribution and possible occurrence of local hot spots that may affect pebble integrity. This study assessed CFD predictions against temperature distribution measurements from the SANA test facility at the Research Center Jülich in Germany. A realistic pebble bed structure of randomly packed 1584 pebbles was produced using the discrete element method to model the pebble packing in detail. A total of 96 experimental temperature pebble points were used for the assessments, covering a broad range of heating powers (10 kW ≤ Poperation ≤ 35 kW). A good agreement between the CFD predictions and the SANA measurements was obtained for two coolants, nitrogen and helium, along the height of the pebble bed. It is anticipated that a better understanding of the suitability of the existing CFD models gained through this study will aid in the identification of gaps and areas of improvement for CFD to support the design and safety evaluations for pebble bed small modular reactors.

Impact of semi-empirical methods implemented in heat, air, and moisture (HAM) models on predicted wind-driven rain (WDR) loads and hygrothermal responses

The amount, duration, and intensity of wind-driven rain (WDR) are instrumental to the durability and sustainability of building components. Semi-empirical methods implemented in heat, air, and moisture (HAM) models have proved to be a practical and efficient approach to quantify WDR exposure of building components and to examine WDR's influence on hygrothermal responses of building envelopes. However, specific assumptions and simplifications in the implementations can cause discrepancies in WDR calculations and hygrothermal responses. While measured datasets or computational fluid dynamics (CFD) predictions are employed to validate WDR calculations in previous studies, few address the further influence on hygrothermal responses, particularly confronted with full-scale experimental datasets. This paper starts with a general formulation of semi-empirical methods for WDR calculation and elaborates the ASHRAE and ISO standards implemented in two representative HAM models, WUFI and DELPHIN. In the first phase of simulations, two full-scale experimental datasets at Leuven (Belgium) and Eindhoven (the Netherlands) are reproduced by the two models to compare predicted WDR loads. In the second phase, the predicted and measured WDR loads are imposed as boundary conditions of different scenarios of one benchmark case to further analyze the influence on the hygrothermal responses. The results indicate that both models roughly reproduce the semi-empirical methods. Because of disparity in algorithms and implementations and differences in weather and building conditions, the simulated WDR loads show similar trends with deviations to the measured datasets. The predicted hygrothermal responses show deviations to different extents, presumably due to disparity in WDR load predictions during certain periods.

Computational fluid dynamics analysis of scaled Thermo-Compressor Performance in Multi-effect Distillation plants with Thermal Vapor Compression

This paper investigates scaled Thermo-Compressors for Multi-Effect Distillation with Thermal Vapor Compression (MED-TVC) desalination plants using Computational Fluid Dynamics (CFD). Initial validation compared CFD predictions with a real MED-TVC plant. Scaled-down Thermo-Compressors exhibited constant entrainment and pressure ratios, validating design scalability. The study expanded to test with compressed air as a practical substitute for steam under identical conditions. Results showed minimal deviation in entrainment and pressure ratios, affirming the feasibility of air testing. To account for temperature differences, a correction factor was introduced for accurate prediction when testing with air. Crucially, we explored substituting high-temperature steam with compressed air for testing. Lowering the air temperature allowed a reduced pressure of 13.12 bar while maintaining equivalent performance ratios compared to steam at 16 bar and 474.7 K. These findings are pivotal for developing small-scale Thermo-Compressor prototypes, facilitating testing with steam or air, and reducing risks and costs associated with full-scale fabrication. The study contributes practical insights for optimizing Thermo-Compressor designs in MED-TVC desalination, presenting compressed air as a viable alternative for efficient and cost-effective testing.

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).

Optimization of Savonius rotor blade performance using Taguchi method: Experimental and 3D-CFD approach

The Savonius hydrokinetic turbine (HKT) is both cost-effective and reliable, providing clean energy with minimum environmental impact. The efficiency of the Savonius rotor can be improved by modifying the blade profile to increase the effective torque. However, past research works reported that modifying the blade profile is quite challenging due to small Cp improvement and design constraint. Therefore, the present study proposes a newly developed blade profile blueprint, akin to parameterizable designs such as the modified Bach and Benesh profiles but offering more shape versatility. This new blueprint is optimized with a systematic design of experiment (DOE) using a 3D computational fluid dynamics (CFD) simulation to maximize the Cp. The best design is determined statistically using the Taguchi method and analysis of variance (ANOVA). The optimized rotor profile enhances Cp by approximately 10.9 % compared to the conventional Savonius rotor at the optimal TSR (best Cp = 0.159) and 16.7 % improvement at a higher TSR value of 0.9 (Cp = 0.158). Moreover, the optimized rotor outperforms the Fibonacci rotor (Fibonacci blade profile) by 27 % in terms of efficiency. A thorough CFD analysis suggests that the optimized blade profile has a greater lift generated at the convex side of the advancing blade due to its streamlined shape, which delays the flow separation further up to the root of the blade. The confirmation test (experiment) is also performed to verify the Cp improvement of the optimized rotor, and the results herein concluded that the present CFD prediction is accurate and consistent with the experimental values.