Sliding mesh algorithm for CFD analysis of helicopter rotor–fuselage aerodynamics

The paper deals with a solution of radiation heat transfer problems in enclosures filled with nonparticipating medium using ray tracing on hierarchical ortho-Cartesian meshes. The idea behind the approach is that radiative heat transfer problems can be solved on much coarser grids than their counterparts from computational fluid dynamics (CFD). The resulting code is designed as an add-on to OpenFOAM, an open-source CFD program. Ortho-Cartesian mesh involving boundary elements is created based upon CFD mesh. Parametric non-uniform rational basis spline (NURBS) surfaces are used to define boundaries of the enclosure, allowing for dealing with domains of complex shapes. Algorithm for determining random, uniformly distributed locations of rays leaving NURBS surfaces is described. The paper presents results of test cases assuming gray diffusive walls. In the current version of the model the radiation is not absorbed within gases. However, the ultimate aim of the work is to upgrade the functionality of the model, to problems in absorbing, emitting and scattering medium projecting iteratively the results of radiative analysis on CFD mesh and CFD solution on radiative mesh.

Aerodynamic shape optimisation technology is presented, comprising an efficient variable fidelity shape parameterisation method, an efficient andhigh quality mesh deformation scheme, and a parallel optimisation algorithm. The objective of the research presented here is the comparison of truly three-dimensional optimisations of aircraft wings in both aerodynamic and aeroelastic environments. The novel shape parameterisation technique allows various fidelities of design parameters, ranging from detailed surface changes to novel truly three-dimensional planform adjustments. An efficient interpolation scheme, using radial basis functions, transfers domain element movements into direct deformations of the design surface and corresponding CFD mesh, thus allowing total independence from the grid generation package and type (structured or unstructured). Optimisation is independent from the CFD flow solver by obtaining sensitivity information for an advanced parallel gradient-based optimiser by finite-differences. This ‘wrap-around’ optimisation technique is applied to a modern large transport aircraft wing in the cruise flight condition for minimum drag with stringent constraints in lift, volume, and two root moments. The objective of all optimisations is aerodynamic, however the static aeroelastic deflection provided by an aeroelastic solver will give that particular optimisation increased accuracy and real world relevance. The result of a constrained inviscid aerodynamic optimisation is presented and has a significant reduction in drag when compared to the initial wing with no violation of any constraints. The shape parameterisation method demonstrates that only a low number of design variables are necessary to achieve innovative planform and surface geometries with dramatically improved performance. Computational fluid dynamics (CFD) methods are now commonplace in aerospace industries, and at the forefront of analysis capabilities, providing a fast and effective method of predicting a design’s aerodynamic performance. However, with ever increasing complexity of designs, engineers can often struggle to interpret the intricacies of the CFD results sufficiently to be able to manually alter the geometry to improve performance. Hence, there has been an increase in demand for intelligent and automatic shape optimisation schemes. This requires combining geometry control methods with numerical optimisation algorithms, to provide a mechanism to mathematically seek improved and optimum designs, using CFD as the analysis tool. Optimisation requires consideration of three issues, each of which have numerous solutions: shape parameterisation including CFD surface and volume mesh deformation, computation of design variable derivatives, and effective use of these derivatives to improve design. Geometry parameterisation is critical for effective shape optimisation. This is the method of representing the design surface, and defines the degrees of freedom in which the geometry can be altered and, ideally, this should be linked with an effective method of deforming the CFD surface and volume mesh in a corresponding fashion. Parameterising complex shapes is a problem that remains a serious obstacle to both manual and automatic CFD-based optimisation. A wide variety of shape control and morphing methods have been developed, but many do not allow sufficiently

The optimization of heat transfer between fluid and metal plays a crucial role in gas turbine design. An accurate prediction of temperature for each metal component can help to minimize the coolant flow requirement, with a direct reduction of the corresponding loss in the thermodynamic cycle. Traditionally, in industry fluid and solid simulations are conducted separately. The prediction of metal stresses and temperatures, generally based on finite element analysis, requires the definition of a thermal model whose reliability is largely dependent on the validity of the boundary conditions prescribed on the solid surface. These boundary conditions are obtained from empirical correlations expressing local conditions as a function of working parameters of the entire system, with validation being supplied by engine testing. However, recent studies have demonstrated the benefits of employing coupling techniques, whereby computational fluid dynamics (CFD) is used to predict the heat flux from the air to the metal, and this is coupled to the thermal analysis predicting metal temperatures. This paper describes an extension of this coupling process, accounting for the thermo-mechanical distortion of the metal through the engine cycle. Two distinct codes, a finite element analysis (FEA) solver for thermo-mechanical analysis and a finite volume solver for CFD, are iteratively coupled to produce temperatures and deformations of the solid part through an engine cycle. At each time step, the CFD mesh is automatically adapted to the FEA prediction of the metal position using efficient spring analogy methods, ensuring the continuity of the coupled process. As an example of this methodology, the cavity flow in a turbine stator well is investigated. In this test case, there is a strong link between the thermo-mechanical distortion, governing the labyrinth seal clearance, and the amount of flow through the stator well, which determines the resulting heat transfer in the stator well. This feedback loop can only be resolved by including the thermo-mechanical distortion within the coupling process.

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) offer significant advantages in operations requiring both vertical lift and efficient forward flight. However, VTOL aircraft design is challenge in terms of stability, control, and aerodynamic efficiency across flight regimes. Aerodynamic analysis is conducted to determine the variations of pressure distributions, lift and drag forces and center-of-pressure (CP) movement all of which are important towards design optimization and control modeling. This study focuses on aerodynamic analysis of a small VTOL fixed-wing UAV without using any additional actuators or complex tilting mechanisms. The designed UAV only uses the regular control surfaces such as Aileron, Rudder and Elevator of the fixed wing aircraft for maneuverability. Computational fluid dynamics (CFD) has become a essential tool in aerodynamic design and analysis. Studies of flyingwing VTOL UAVs revealed that CFD is effective in the prediction of stability and flow separation which is critical in transition controllability [1]. The structural and CFD studies were also coupled which showed that aeroelastic effects at high lift and inertia can be critical to performance and safety [2]. CFD has also been useful in wing and fuselage optimization to minimize drag and preserve lift as well as in the prediction of aerodynamic coefficients by use of turbulence models to provide reliable control inputs [3]. In addition to CFD, low-order methods like XFLR5 have been used to facilitate initial design through evaluation of centerof-gravity balance and optimization of wing geometry under structural constraints [4] [5]. On this basis, th present work implements CFD and XFLR5 to examine the aerodynamic forces, pressure field, and CP-CG interaction in a fixed-wing UAV-VTOL.

A summary of the computational aerodynamic performance tools and analyses for the development of the Surfing Aircraft Vortices for Energy (SAVE) formation flight concept is presented. Aerodynamic analysis is accomplished using several, multi-fidelity prediction methods, including a vortex lattice method (VLM) approach, a panel method to model body effects, and a high-fidelity hybrid computational fluid dynamics (CFD) method that couples a Reynolds Averaged Navier-Stokes (RANS) flow solver for the near-body simulation with a quasi-3D RANS approach for the evolution of wakes over long longitudinal distances. Computational analysis is used to develop a comprehensive aerodynamic database for flight simulation and control law design, to develop a drag benefit “map”, which is used to determine the optimum location of the trailing airplane relative to the leading airplane wake, and to compare with flight-derived performance data to validate the use of CFD for the SAVE program. Finally, an extension of the hybrid CFD method and initial results for a 3-airplane echelon formation to highlight the multiple wake interaction effects and complex flow physics is presented.

In axial turbine, the tip clearance flow occurring in rotor blade rows is responsible for about one-third of the aerodynamic losses in the blade row and in many cases is the limiting factor for the blade lifetime. The tip leakage vortex forms when the leaking fluid crosses the gap between the rotor blade tip and the casing from pressure to suction side and rolls up into a vortex on the blade suction side. The flow through the tip gap is both of high velocity and of high temperature, with the heat transfer to the blade from the hot fluid being very high in the blade tip area. In order to avoid blade tip burnout and a failure of the machine, blade tip cooling is commonly used. This paper presents the physical study and an improved design of a recessed blade tip for a highly loaded axial turbine rotor blade with application in high pressure axial turbines in aero engine or power generation. With use of three-dimensional computational fluid dynamics (CFD), the flow field near the tip of the blade for different shapes of the recess cavities is investigated. Through better understanding and control of cavity vortical structures, an improved design is presented and its differences from the generic flat tip blade are highlighted. It is observed that by an appropriate profiling of the recess shape, the total tip heat transfer Nusselt number was significantly reduced, being 15% lower than the flat tip and 7% lower than the base line recess shape. Experimental results also showed an overall improvement of 0.2% in the one-and-a-half-stage turbine total efficiency with the improved recess design compared to the flat tip case. The CFD analysis conducted on single rotor row configurations predicted a 0.38% total efficiency increase for the rotor equipped with the new recess design compared to the flat tip rotor.

The importance of using Agriculture unmanned helicopters (AUHs), especially for spraying pesticides and fertilizers on any terrain type to ensure crop yields, has been recently acknowledged. Apart from flying these helicopters at a super-low altitude and low speed, using an efficient and optimum rotor blade ensures a uniform and deep penetration of pesticide and fertilizers over a specified area. Accordingly, this work attempts to optimize the rotor blade of an AUH by using coupling statistics and several numerical techniques, including design of experiments, response surface method, and computational fluid dynamics. The experiments are designed using the central composite design method and by selecting the geometric variables that affect the aerodynamic performance of the rotor blade, including the root chord, tip chord, and angle of attack. The angle at the root and tip is optimized in order for the resulting twist to produce a uniform blade loading, achieve maximum lift, and minimize the required hover power. The required aerodynamic forces and limited availability of engine power are identified as constraints. The blade is optimized only when the helicopter is hovering at a persistent rotational speed, and the hover efficiency of the rotor blade with an optimal twist distribution is significantly higher than the baseline.

Progress and future prospects of CFD in aerospace—Wind tunnel and beyond

Tri-isotropic (TRISO) fuel particle coating is critical for the future use of nuclear energy produced byadvanced gas reactors (AGRs). The fuel kernels are coated using chemical vapor deposition in a spouted fluidized bed. The challenges encountered in operating TRISO fuel coaters are due to the fact that in modern AGRs, such as High Temperature Gas Reactors (HTGRs), the acceptable level of defective/failed coated particles is essentially zero. This specification requires processes that produce coated spherical particles with even coatings having extremely low defect fractions. Unfortunately, the scale-up and design of the current processes and coaters have been based on empirical approaches and are operated as black boxes. Hence, a voluminous amount of experimental development and trial and error work has been conducted. It has been clearly demonstrated that the quality of the coating applied to the fuel kernels is impacted by the hydrodynamics, solids flow field, and flow regime characteristics of the spouted bed coaters, which themselves are influenced by design parameters and operating variables. Further complicating the outlook for future fuel-coating technology and nuclear energy production is the fact that a variety of new concepts will involve fuel kernels of different sizes and with compositions of different densities. Therefore, without a fundamental understanding the underlying phenomena of the spouted bed TRISO coater, a significant amount of effort is required for production of each type of particle with a significant risk of not meeting the specifications. This difficulty will significantly and negatively impact the applications of AGRs for power generation and cause further challenges to them as an alternative source of commercial energy production. Accordingly, the proposed work seeks to overcome such hurdles and advance the scale-up, design, and performance of TRISO fuel particle spouted bed coaters. The overall objectives of the proposed work are to advance the fundamental understanding of the hydrodynamics by systematically investigating the effect of design and operating variables, to evaluate the reported dimensionless groups as scaling factors, and to establish a reliable scale-up methodology for the TRISO fuel particle spouted bed coaters based on hydrodynamic similarity via advanced measurement and computational techniques. An additional objective is to develop an on-line non-invasive measurement technique based on gamma ray densitometry (i.e. Nuclear Gauge Densitometry) that can be installed and used for coater process monitoring to ensure proper performance and operation and to facilitate the developed scale-up methodology. To achieve the objectives set for the project, the work will use optical probes and gamma ray computed tomography (CT) (for the measurements of solids/voidage holdup cross-sectional distribution and radial profiles along the bed height, spouted diameter, and fountain height) and radioactive particle tracking (RPT) (for the measurements of the 3D solids flow field, velocity, turbulent parameters, circulation time, solids lagrangian trajectories, and many other of spouted bed related hydrodynamic parameters). In addition, gas dynamic measurement techniques and pressure transducers will be utilized to complement the obtained information. The measurements obtained by these techniques will be used as benchmark data to evaluate and validate the computational fluid dynamic (CFD) models (two fluid model or discrete particle model) and their closures. The validated CFD models and closures will be used to facilitate the developed methodology for scale-up, design and hydrodynamic similarity. Successful execution of this work and the proposed tasks will advance the fundamental understanding of the coater flow field and quantify it for proper and safe design, scale-up, and performance. Such achievements will overcome the barriers to AGR applications and will help assure that the US maintains nuclear energy as a feasible option to meet the nation's needs for energy and environmental safety. In addition, the outcome of the proposed study will have a broader impact on other processes that utilize spouted beds, such as coal gasification, granulation, drying, catalytic reactions, etc.

Robust and efficient prediction of the collection efficiency in icing accretion simulation for 3D complex geometries using the Lagrangian approach I: an adaptive interpolation method based on the restricted radial basis functions

The Planar Inlet Design and Analysis Process (PINDAP) is a collection of software tools that allow the efficient aerodynamic design and analysis of planar (two -dimensional and axisymmetric) inlets. The aerodynamic analysis is performed using the Wind -US computational fluid dynamics (CFD) program. A major ele ment in PINDAP is a Fortran 90 code named PINDAP that can establish the parametric design of the inlet and efficiently model the geometry and generate the grid for CFD analysis with design changes to those parameters. The use of PINDAP is demonstrated for subsonic, supersonic, and hypersonic inlets.

Numerical simulation and modeling techniques are becoming the primary research tools for aerodynamic analysis and design. However, various uncertainties in physical modeling and numerical simulation seriously affect the credibility of Computational Fluid Dynamics (CFD) simulation results. Therefore, CFD models need to be adjusted and modified with consideration of uncertainties to improve the prediction accuracy and confidence level of CFD numerical simulations. This paper presents a parameter correction method of CFD for aerodynamic analysis by making full use of the advantages of the Approximate Bayesian Computation (ABC) technique in dealing with the analysis and inference of complex statistical models, in which the parameters of turbulence models for CFD are inferenced. The proposed parameter correction method is applied to the aerodynamic prediction of the NACA0012 airfoil. The results show the feasibility and effectiveness of the proposed approach in improving CFD prediction accuracy.

To expand the cruise speed of a compound helicopter, alleviating the compressibility effects on the advancing side with reduced rotor RPM is proved to be an effective design feature, which results in high advance ratio flight regime. To investigate the aerodynamic phenomena at high advance ratios and provide data for the validation of analytical tools, a series of wind tunnel tests were conducted progressively in the Glenn L. Martin Wind Tunnel with a 33.5-inch radius fourbladed articulated rotor. In a recent wind tunnel test, the rotor blades were instrumented with pressure sensors and strain gauges at 30% radius, and pressure data were acquired to calculate the sectional airloads by surface integration up to an advance ratio of 0.8. The experimental results of rotor performance, control angles, blade airloads, and structural loads were compared with the predictions of comprehensive analysis and computational fluid dynamics (CFD) analysis coupled with computational structural dynamics (CSD) structural model. The paper focuses on the data correlation between experimental pressure, airload, and structural load data and the CFD/CSD predicted results at various collective and shaft tilt angles. Overall, the data correlation was found satisfactory, and the study provided some insights into the aerodynamic mechanisms that affect the rotor airload and performance, in particular the mechanisms of backward shaft tilt, the effect of hub/shaft wake, and the formation of dynamic stall in the reverse flow region.

Rotor blades are essential for helicopter flight as they provide lift similar to an airplane’s wings, allowing the aircraft to take off, hover, and maneuver. However, they also generate aerodynamic drag, which can reduce maximum speed, stability, maneuverability, and fuel efficiency. The enhancement on the blade is usually done at the trailing edge area; however, this time it was done at the leading edge location. This study explored the use of passive flow control to enhance rotor blade performance by minimizing surface turbulence. Through Computational Fluid Dynamics (CFD) analysis, key parameters such as velocity and lift-to-drag ratios coefficient are examined at a Reynolds number (Re) of 3×10⁶. The research utilized the SST k-ω turbulence model and an unstructured mesh to simulate airflow around a NACA 0012 airfoil at a 15° angle of attack. Passive flow control was applied using slots of 5%, 10%, and 15% of the chord length, placed in turbulent flow regions and extending downstream. The findings indicate that positioning passive flow control further downstream increases the lift-to-drag ratio with 5% slot sizes delaying turbulence, improving velocity reattachment to the blade surface and improving the lift-to-drag ratio by approximately 77% compared with non slot blade. This highlights the effectiveness of passive flow control in improving the aerodynamic efficiency of rotor blades.