Aerodynamic Analysis and Optimization of Gliding Locust Wing Using Nash Genetic Algorithm

In the development of bio-inspired Micro Air Vehicles (MAVs), flapping-wing configurations derived from natural fliers such as honeybees offer unique advantages in maneuverability and stability within complex environments. However, modeling the unsteady aerodynamic behavior of flapping wings is computationally intensive. In this study, a simplified quasi-steady approach is adopted by simulating the aerodynamics of a rigid, honeybee-inspired drone at multiple static orientations using a virtual inflow rotation technique. Computational Fluid Dynamics (CFD) simulations are performed at various effective angles of attack by altering the direction of the incoming flow while keeping the wing geometry fixed. Key vortex structures, including leading-edge and wingtip vortices, are analyzed to evaluate their role in lift and thrust generation. Aerodynamic forces (lift, drag, and thrust) are quantified across multiple static orientations to gain insights into aerodynamic performance. In parallel, a basic static structural analysis of the rigid wing is conducted using the aerodynamic pressure loads obtained from the CFD simulations. The structural response under representative aerodynamic loads is evaluated to assess stress distribution and potential wing deformation. This combined aerodynamic and structural analysis provides a comprehensive understanding of wing performance and structural integrity, offering valuable data for optimizing bio-mimetic MAV design.

While designing the power requirements of a ship, the most important factor to be considered is the ship resistance, or the sea drag forces acting on the ship. It is important to have an estimate of the ship resistance while designing the propulsion system since the power required to overcome the sea drag forces contribute to ‘losses’ in the propulsion system. There are three main methods to calculate ship resistance: Statistical methods like the Holtrop-Mennen (HM) method, numerical analysis or CFD (Computational Fluid Dynamics) simulations, and model testing, i.e. scaled model tests in towing tanks. At the start of the design stage, when only basic ship parameters are available, only statistical models like the HM method can be used. Numerical analysis/ CFD simulations and model tests can be performed only when the complete 3D design of the ship is completed. The present paper aims at predicting the calm water ship resistance using CFD simulations, using the Flow-3D software package. A case study of a roll-on/roll-off passenger (RoPax) ferry was investigated. Ship resistance was calculated at various ship speeds. Since the mesh affects the results in any CFD simulation, multiple meshes were used to check the mesh sensitivity. The results from the simulations were compared with the estimate from the HM method. The results from simulations agreed well with the HM method for low ship speeds. The difference in the results was considerably high compared to the HM method for higher ship speeds. The capability of Flow-3D to perform ship resistance analysis was demonstrated.

Purpose This study aims to validate the linear flow theory with computational fluid dynamics (CFD) simulations and to propose a novel shape for the airfoil that will improve supersonic aerodynamic performance compared to the National Advisory Committee for Aeronautics (NACA) 64a210 airfoil. Design/methodology/approach To design the new airfoil shape, this study uses a convex optimization approach to obtain a global optimal shape for an airfoil. First, modeling is conducted using linear flow theory, and then numerical verification is done by CFD simulations using ANSYS Fluent. The optimization process ensures that the new airfoil maintains the same cross-sectional area and thickness as the NACA 64a210 airfoil. This study found that an efficient way to obtain the ideal airfoil shape is by using linear flow theory, and the numerical simulations supported the assumptions inherent in the linear flow theory. Findings This study’s findings show notable improvements (from 4% to 200%) in the aerodynamic performance of the airfoil, especially in the supersonic range, which points to the suggested airfoil as a potential option for several fighter aircraft. Under various supersonic conditions, the optimized airfoil exhibits improved lift-over-drag ratios, leading to improved flight performance and lower fuel consumption. Research limitations/implications This study was conducted mainly for supersonic flow, whereas the subsonic flow is tested for a Mach number of 0.7. This study would be extended for both subsonic and supersonic flights. Practical implications Convex optimization and linear flow theory are combined in this work to create an airfoil that performs better in supersonic conditions than the NACA 64a210. By closely matching the CFD results, the linear flow theory's robustness is confirmed. This means that the initial design phase no longer requires extensive CFD simulations, and the linear flow theory can be used quickly and efficiently to obtain optimal airfoil shapes. Social implications The proposed airfoil can be used in different fighter aircraft to enhance performance and reduce fuel consumption. Thus, lower carbon emission is expected. Originality/value The unique aspect of this work is how convex optimization and linear flow theory were combined to create an airfoil that performs better in supersonic conditions than the NACA 64a210. Comprehensive CFD simulations were used for validation, highlighting the optimization approach's strength and usefulness in aerospace engineering.

Experimental Fluid Dynamics (EFD) and Computational Fluid Dynamics (CFD) have been instrumental in Fluid Mechanics to help solve scientific and engineering problems. This research attempts to use both techniques to perform a parametric study of turbulence flow around airfoil ClarkY-14 at various velocity and angle of attack (AoA). Clark Y-14 airfoil was designed in the 1920’s. It demonstrated good overall performance at low and moderate Reynolds numbers. With the progress in the aviation field, its performance was sub-optimal for newer aircraft designs. However, with the advent of RC airplanes and model aircrafts, there is a renewed interest in this airfoil. Various research projects have been conducted using this airfoil, but there hasn’t been a combined EFD and CFD study of the performance characteristics of the airfoil itself, which still finds real world applications today. One important aspect of this research included the investigation of the effects of a Force Measurement Device/Sensor, which is typically used in scaled/full-size wind tunnels to mount the test model as well as measure the forces/moments acting on it during the testing. The presence of such a device could affect the quality of the data obtained from the wind tunnel testing when compared to a real world application scenario where the aforementioned device may not be present. To the best of the author’s knowledge, no detailed study has been published on the effects of such devices. In this study, the results with and without the measuring device were generated by using CFD simulations. The results were then compared to see to what extent the inclusion of these devices will affect the results. The methodology used for this research was experimental as well as computational. In the present research, a commercially available CFD software STAR-CCM+ was employed to simulate the flows around airfoil Clark Y-14. The experimental data was obtained from wind tunnel tests using AEROLAB Educational Wind Tunnel (EWT) and compared with the simulation data from the CFD. The two data sets were in good agreement. Both experimental and simulation results were used to understand the effects of the measurement device/sensor used in the scaled wind tunnel on the lift and drag coefficients of the airfoil. Two separate CFD simulation setups were designed to model the presence and absence of the measurement device/sensor. These setups replicated the wind tunnel setup. The airfoil was tested and simulated at different speeds as well as different AoA. The comparative study gave a useful insight on the accuracy of the CFD simulations in relation to the actual testing. The analysis of results concluded that the force measurement device/sensor had insignificant effects on the accuracy and quality of data collected through wind tunnel testing.

Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.

Bench test and computational fluid dynamics (CFD ) simulation of the air pump loss on the 380 hydraulic retarder are completed in this paper . It turns out that the CFD simulation has nice reliability from the contrast of the air pump loss between the test and the simulation . And on this foundation , CFD simulation of two kinds of retarders with different turbulent structures is done . The contrast of the results of the simulation give the effects of different turbulent structures on cutting down the are pump loss .

This paper discusses the aerodynamics characteristics of Blended Wing Body — Baseline II E2, unmanned aerial vehicle aircraft. A computational method, Computational Fluid Dynamic (CFD) Star CCM+ software has been performed to obtain the aerodynamics characteristic of the BWB. The aerodynamic characteristics prediction of BWB-Baseline II E2 aircraft was obtained through CFD analysis using unstructured mesh and standard one — equation turbulence model, Spalart-Allmaras was selected in the investigations. Lift coefficient (CL), drag coefficient (CD) and moment coefficient (CM) were studied at flight condition of Mach 0.1 (∼34 m/s) at different angles of attack, α. The CFD results were compared with the experimental result. The results show the trend of lift curves are similar at the linear region (α = −10° to 7°) but at the higher angle of attack the trends become nonlinear. The drag coefficient for CFD simulations is greater than experimental result and there are differences in pitching moment curves between CFD simulation and experiment data which the experiment data shows a steep curve than simulation.

The chemical composition and properties of fuels used in compression-ignition engines can influence engine performance significantly. Consequently, the modeling of fuel chemistry within computational fluid dynamics (CFD) simulations of diesel and other compression ignition engines is important. Modern detailed chemical mechanisms may provide predictive modeling of fuel chemistry; however, they are generally far too computationally expensive for use in CFD. We present simulations of diesel engine combustion, focusing on the prediction of ignition, using the CONVERGE CFD software package. A CFD simulation framework with models for turbulence and spray breakup and atomization is presented with a reduced global reaction model to describe fuel oxidation and ignition. The global reaction model incorporates a single parameter, the derived cetane number (DCN), to describe fuel reactivity variability. CFD simulations are compared to experiments carried out in a single-cylinder diesel engine for compositionally diverse conventional and alternative diesel and jet fuels. Model-experiment comparisons show general agreement for ignition timing and the influence of fuel variability on ignition timing. In addition, the sensitivity of CFD predictions on the chemistry, turbulence, and spray models is illustrated.

Today, many wells in heterogeneous carbonate reservoirs throughout the Middle East and Caspian Sea area are being completed with long intervals and complex completion equipment, such as limited entry liners and inflow control devices (ICDs). Accurate modeling and understanding of fluid placement during a stimulation operation through such long complex completions can be quite challenging. In this paper, an integrated approach of modeling, experiments and computational fluid dynamics (CFD) simulations will be presented. A computational tool based on a transient one-dimensional (1D) approach has been developed in-house to model stimulation through such completions. In order to validate the 1D approach for reliable fluid displacement predictions, annulus fluid displacement experiments in perforated liners supported by CFD simulations have been conducted. The experimental setup consists of an outer Lucite pipe representing the well-bore geometry and an inner aluminum pipe with multiple perforations of variable diameter. The setup mimics the real field application in a 1:1 scale with respect to the pipe and perforation diameters while the test section is limited to 27 ft. The experimental procedure is as follows: fluid is pumped into the annulus through the perforations until the annulus is completely filled,the fluid tank is switched "on-the-fly" to the tank with the displacing fluid resulting in the displacement of the annulus fluid by the displacing fluid through the perforations. The experiments and the CFD simulations indicate that even with a single open perforation inside the 27-ft test section, the three-dimensional (3D) flow field around the perforation rapidly transitions to uniform annular flow within a few feet uniformly displacing the annulus fluid. The model also provides insight into various well injection processes in sandstone and carbonate formation, such as scale squeezes, solvent treatments, and HF acid treatments. Introduction The length of production and injection intervals in a single well continues to increase in order to contact more reservoir rock with a single wellbore penetration and improve project economics. Multiple, thick stacked reservoirs are accessed by vertical and deviated wells while thinner reservoirs are being exploited with longer and longer horizontal wells1–3. To keep up with drilling capability, completion technology has advanced considerably in the past few years. Horizontal wells are "compartmentalized" using mechanical and/or swellable packers. Within a given compartment, injection and production can be controlled by use of inflow control devices (ICDs), limited entry (LE) liners, and/or sliding sleeves. The liners also make it easier to enter the completion interval with logging tools, wire line, and coiled tubing. While various tools are available to evaluate long-term, steady-state production and injection into such wells, modeling of short-term, transient injection into such completions is very challenging due to the long lateral lengths, limited entry points from the liner to each compartment, and the presence of an open annulus with occasional packer isolations. This is especially important for long wells in carbonate formations as all wells require acid stimulation upon initial completion, and occasionally throughout the well life.

A normally-open thermally-actuated microvalve was designed (using microfabrication/soft-lithography techniques involving 3D Printed molds), assembled and tested. The motivation of the research work is to develop an array of microvalves for precise delivery of water to individual plants in a field (with the goal of developing smart irrigation systems for high value cash-crops in the agricultural sector). It is currently impossible to control application of irrigation-water at the level of a single plant. If such a capability were practically available on farms, the result would be a step change in precision agriculture, such that the output of every plant in a farm field could be optimized (i.e., food-water-energy nexus in sustainability applications). The aim of this study is to develop and test a microfluidic system (consisting of a microvalve array) that could be controlled, capillary by capillary, to deliver the needed amount of water to individual plants in a large field. Two types of test fluids were leveraged for thermo-hydraulic actuation of the microvalves developed in this study: (a) Design-I: using air, and (b) Design-II: using Phase Change Material (PCM). The PCM used in this study is PureTemp29. The proposed approach enabled a simple and cheap design for microvalves that can be manufactured easily and are robust to weather conditions (e.g., when exposed to the elements in orchards and open fields). Other advantages include: safe and reliable operation; low power consumption; can tolerate anomalous pressure loads/fluctuations; simple actuation; affords easy control schemes; is amenable for remote control; provides long-term reliability (life-cycle duration estimated to be 3∼5 years); can be mass produced and is low maintenance (possibly requiring no maintenance over the life time of operation). The microvalve consists of two layers: a flow layer and a control layer. The control layer is heated from below and contains a microfluidic chamber with a flexible polymeric thin-membrane (200 microns in thickness) on top. The device is microfabricated from Poly-Di-Methyl-Siloxane (PDMS) using soft lithography techniques (using a 3D Printed mold). The control chamber contains either air (thermo-pneumatic actuation) or PCM (thermo-hydraulic actuation involving repeated melting/freezing of PCM). The flow layer contains the flow channel (inlet and outlet ports, horizontal section and valve seat). The experimental results from testing the efficacy of the two types of micro-valves show a 60% reduction (for thermo-pneumatic actuation using air) and 40% reduction (for thermo-hydraulic actuation using PCM) in water flow rates for similar actuation conditions (i.e., heater temperature values). PCM design is expected to consume less power (lower OPEX) for long-term actuation but may have slower actuation speed and have higher manufacturing costs (CAPEX). Air actuation design is expected to consume more power (higher OPEX) for longer-term operation but may have faster actuation speeds and lower manufacturing costs (CAPEX). Computational Fluid Dynamics (CFD) simulations were performed to investigate the effect of flowing water (in the microfluidic channel) on the average absolute pressure and temperature of air in the actuation chamber. The CFD simulations were performed using a commercial tool (Ansys™ 2019R1®). The results from the CFD simulations are presented in this study.

To evaluate manoeuvring performance of merchant ships, the mathematical modeling group (MMG) or computational fluid dynamics (CFD) simulations are used. However, it is difficult to use the MMG to evaluate the manoeuvring performance of fishing vessels, thus research using CFD simulations is necessary. Also, since the course-changing and turning ability is crucial in fishing operations, a rudder design suitable for fishing vessels is necessary. This study designs a rudder using National Advisory Committee for Aeronautics (NACA) airfoil sections and evaluates its manoeuvring performance. A CFD model is used to evaluate the manoeuvring performance of the fishing vessel, and turning and zig-zag tests are conducted. The effectiveness of using CFD simulations based on Reynolds averaged Navier-Stokes equations to assess the manoeuvring performance of fishing vessels was validated. No significant difference was found in the manoeuvring performance for hull forms and rudder designs for course-changing ability. However, the original hull form showed superior turning performance. Among five rudders with varying aspect ratios and shapes, the rudder with 5.5% aspect ratio had the best turning performance. Regarding the rudder design for fishing vessels, NACA airfoil was employed, and a rudder aspect ratio of 5.5% based on the immersed hull side area is recommended.

Considerable improvements in the aerodynamic performance of a vertical axis wind turbine (VAWT) can be achieved by integrating computational fluid dynamics (CFD) simulation and wind tunnel investigation in their design improvement. With the growing demand for energy worldwide, conventional sources are becoming more scarce and expensive. Wind is among the most popular and fastest growing sources of alternative energy in the world. It is an inexhaustible, indigenous resource, pollution-free, and available almost any time of the day, especially in coastal regions. Industry experts predict that, with proper development, wind energy could provide 20% of the nation’s energy needs. Vertical axis wind turbines (VAWTs) may be as efficient and practical as, and simpler, and significantly cheaper to build and maintain than, horizontal axis wind turbines (HAWTs). They have other inherent advantages; for example, they always face the wind. VAWTs include both a drag-type configuration, such as the Savonius rotor, and a lift-type configuration, such as the Darrieus rotor. The Savonius wind turbine is the simplest. Its operation depends on the difference in drag force when the wind strikes either the convex or concave part of its semi-cylindrical blades. It is good at self-starting and works independently of wind direction. However, its efficiency is relatively lower than that of the lift-type VAWTs. Due to its simple design and low construction cost, Savonius rotors are primarily used for water pumping and to generate wind power on a small scale and its large starting torque makes it suitable for starting other types of wind turbines that have inferior starting characteristics. Recently, some generators with high torque at low rotational speed, suitable for small-scale wind turbines, have been developed, suggesting that Savonius rotors may yet be used to generate electric power. The main goal of this research work is to improve the aerodynamic performance of the three bladed vertical axis Savonius wind turbine. Based on this goal, the objective of this project is to study the performance characteristics of the Savonius wind turbine scale models both experimentally and numerically. The turbine scale models will have different designs with different overlap ratios (ratio of gap between two adjacent blades and the rotor diameter) and without overlap within three blades. The experimental measurements and testing will be conducted in front of a low speed subsonic wind tunnel at different Reynolds number and the computational fluid dynamic (CFD) flow simulation around those design models will be performed by commercial CFD software FLUENT and GAMBIT.

In response to a solicitation for Computational Fluid Dynamic (CFD) simulations of flow in a T-junction from the Nuclear Energy Agency of the Organization for Economic Co-operation and Development (OECD/NEA) [1], Structural Integrity (SI) Associates of San Jose, CA, USA has completed a simulation using the commercially available CFD code ANSYS-CFX. The simulation was carried out for geometry and flow conditions matching an experiment underway at Vattenfall Research and Development in Sweden where two streams of differing temperature mix in a T-junction. The benchmark was to be a blind test of CFD simulations. Experimental results were not released until after benchmark participants submitted the results of their simulation to the OECD/NEA. The CFD simulation done by SI was carried out on an all hexahedral mesh of 1,881,504 elements generated using the ANSYS Mechanical Finite Element program. The mesh was then transferred into the CFX program and, after applying proper boundary conditions, a time-dependent simulation was done using the Large Scale Eddy Simulation (LES) turbulence model [2] with Wall Adjusting Local Eddy Viscosity (WALE) sub-grid scale (SGS) turbulence model [2, 3]. Comparisons of the CFD results to the Vattenfall data show close correspondence for mean and root-mean-square (rms) turbulent temperature fluctuations.

CFD simulation and experimental validation of a GM type double inlet pulse tube refrigerator

Recently, image-based computational fluid dynamic (CFD) simulations have been proposed to investigate the local hemodynamics inside human cerebral aneurysms. It was suggested that the knowledge of the computed three-dimensional flow fields can be used to assist clinical risk assessment and treatment decision making. Therefore, it was desired to know the reliability of CFD for cerebral blood flow simulation, and be able to provide clinical feedback. However, the validations were not yet comprehensive as they lack either patient-specific boundary conditions (BCs) required for CFD simulations or quantitative comparison methods. In this study, based on a recently proposed in-vitro quantitative CFD evaluation approach via virtual angiography, the CFD evaluation was extended from phantom to patient studies. In contrast to previous work, patient-specific blood flow rates obtained by transcranial color coded Doppler ultrasound measurements were used to impose CFD BCs. Virtual angiograms (VAs) were constructed which resemble clinically acquired angiograms (AAs). Quantitative measures were defined to thoroughly evaluate the correspondence of the detailed flow features between the AAs and the VAs, and thus, the reliability of CFD simulations. The proposed simulation pipeline provided a comprehensive validation method of CFD simulation for reproducing cerebral blood flow, with a focus on the aneurysm region. Six patient cases were tested and close similarities were found in terms of spatial and temporal variations of contrast agent (CA) distribution between AAs and VAs. For patient #1 to #5, discrepancies of less than 11% were found for the relative root mean square errors in time intensity curve comparisons from characteristic vasculature positions. For patient #6, where the CA concentration curve at vessel inlet cannot be directly extracted from the AAs and given as a BC, deviations about 20% were found. As a conclusion, the reliability of the CFD simulations was well confirmed. Besides, it was shown that the accuracy of CFD simulations was closely related to the input BCs.