Discover better designs, faster.

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1 Discover better designs, faster. Design of next-generation rotorcraft systems Benefits: Reduced testing Lower development cost Faster-to-market rotorcrafts Fully optimized designs and safer vehicles Improved design cycle productivity Key Features: Overset Mesh/Virtual Blade Model FSI through Abaqus co-simulation or FE solver Multidisciplinary design exploration with HEEDS Fully 3D, single-platform icing/ice accretion solution Automated meshing and parametric CAD Fully coupled CHT analysis Drones and VTOL (Vertical Take-off and Landing) systems, unlike their fixed-wing counterparts, are extremely versatile in application and operate in highly complex, unsteady environments. The design of such systems has to account for and balance a multitude of physics fuselage/ rotor aerodynamics, aeroelastic and aerothermal effects, noise and vibration, icing, engine integration, fuselage-rotor aerodynamic interaction, transonic and compressibility effects and many more. Recent advances in automated mesh generation, the availability of high-fidelity and fully-coupled physics, and increased computational power are enabling factors for simulation-led, multidisciplinary design of next generation rotorcraft systems. With STAR-CCM+ software and HEEDS software, low and high-fidelity, multidisciplinary rotor simulations reduce risk and cost, improve designs faster and enhance operational safety. The Challenge Traditional rotorcraft design approaches based on empirical work, experience, wind tunnel and flight testing are expensive and time-consuming, taking several years to come up with a new design. The resulting designs have scope for improvement since the entire design space is not explored. Traditional computational methods use simplified, lower-fidelity models for each of these phenomena which is timeconsuming and not truly multidisciplinary. The design challenge lies in incorporating a high-fidelity, multidisciplinary, coupled numerical methodology that can account for the interacting effects of blade aerodynamics, flexibility, motion, icing, engine integration and structural analysis, while optimizing the design for the competing constraints. The Solution Simulation is the key to reducing expensive and prolonged testing, understanding the complex physics, finding the optimum designs and creating a better design, faster. Siemens PLM software s STAR-CCM+ offers unique capabilities that are wellvalidated for rotorcraft simulations, both at low and high fidelities of physics. With a single-integrated user interface, automated mesh generation, high fidelity and fully-coupled physics, high performance Figure 1: STAR-CCM+ simulation of rotor vortices (Left) Overset mesh on an Osprey (Right) Virtual blade model on a quadcopter

2 SIMCENTER computing and powerful postprocessing, STAR-CCM+ enables advanced simulations that fit into the design process, leading to a shorter design cycle and better component design. HEEDS MDO, the multidisciplinary design optimization software, along with Optimate+, the STAR-CCM+ addon optimization module leveraging the power of HEEDS, bring design and process optimization capability. Rotorcraft designers can now perform truly multidisciplinary simulation and optimization of their design and processes, bringing better rotorcraft designs to the market, faster. Key Applications the blade pitch and flap response needs to be accounted for. STAR-CCM+ offers the following motion modeling methods depending on the fidelity of physics needed: Overset/Sliding Interface: In order to capture high-fidelity physics, timeaccurate solutions employing overset mesh are used to accurately represent the motion of the rotor blades. In this method the rotor blades are explicitly meshed. The Overset Mesh implementation involves a background stationary grid surrounding the fuselage and airframe, while moving overset grids are created around the rotors. The overset grids undergo prescribed rotational blade motion accounting for the azimuthal as well as cyclic variation in blade pitch. An alternative way of incorporating blade motion modeling is through the use of the sliding interface option which makes use of the rigid body motion (RBM) along with the morphing mesh capability. The rotor mesh is rotated at a fixed rate per time step, while the blade rotations are superimposed by morphing the blade grid to account for cyclic variation in blade pitch. Virtual Blade Model (VBM): This model employs the blade element method (BEM), which is a time-averaged method that captures the effect of the rotor or propeller blades in the flow-field by AERODYNAMICS: The aerodynamic modeling challenges in rotorcraft design are many: Nonlinear, unsteady, three dimensional compressible flow, transonic flow near blade tips, rotor wake and asymmetric rotor loading. Additionally there are aerodynamic interaction effects between main rotor/tail rotor, main rotor/fuselage and interaction with other rotors in the vicinity. Prediction of vehicle performance in hover, forward, and maneuvering flight conditions are important for a rotorcraft designer. The highly flexible rotor blades make performance prediction an inherently aeroelastic problem. Noise reduction and enhanced performance prediction necessitates the use of advanced blade geometries and tip shapes. Additionally, hover performance of the vehicle also depends on in-ground-effect and outof-ground effects, for which appropriate physics needs to be considered. Wind tunnel tests are expensive and difficult for low speed interaction tests. STAR-CCM+ drastically reduces the number of wind tunnel tests and prototypes with interactional aerodynamic analysis of different designs and accurately resolves complex flow fields. Depending on the fidelity required, a full suite of turbulence models are available to accurately capture the flow field - Reynolds Averaged Navier Stokes (RANS), Unsteady Reynolds Averaged Navier Stokes (URANS) and Detached Eddy Simulation (DES). The γ-reθ transition model is available with these turbulence models to capture the flow transition from laminar to turbulent accurately. Key Technology 1: Motion Modeling For accurate aerodynamic performance prediction of rotors, the cyclic variation in Figure 2: (Top) Overset and sliding mesh on ROBIN body rotors; (Bottom) Rotor wake from STAR-CCM+

3 SIMCENTER explicitly introducing momentum sources inside the disk volume swept by the spinning rotor/propeller geometry. This is a cost-effective way where the blades are not explicitly modeled, removing the need for body fitted grids to model the rotor. The physical absence of the blade is substituted by blade twist, chord distribution while the aerodynamic behavior is modeled by including blade performance parameters in the form of lift and drag coefficients provided by the user. The BEM solver is implicitly coupled to the background flow-field and therefore provides an efficient way to capture time-averaged aerodynamic interaction effects with the surrounding environment. The method also includes a thrust/moment trimming algorithm which perturbs the blade pitch controls (collective and cyclic angles) in order to obtain the target thrust, pitching, and rolling moments. Moving Reference Frame (MRF): The low-fidelity MRF is a steady state approach which models a pure rotational motion by generating constant rotational grid fluxes in the governing equations rather than explicitly simulating the motion of the mesh. Applying a moving reference frame to a rotating region will generate constant rotational forces in the rotating domain to mimic rotating effects. STAR-CCM+ is well validated for handling the key aerodynamic challenges in rotorcraft simulations. Key validation data is presented below. Airframe Wake Interaction Validation Validation of interactional aerodynamics is conducted on the generic helicopter fuselage model (ROBIN body). Experimental data on the ROBIN body is available from Mineck1. The ROBIN model is a fuselage in forward flight at an airspeed of 27.2 m/s and rotor RPM of The helicopter is in forward flight at an advance ratio of and is operating at a thrust coefficient, CT of STAR-CCM+ is validated against test data by comparing the unsteady pressure readings along the fuselage, wake vortex propagation and trim controls estimation2. Rotation of the main rotor is modeled with overset mesh capability, and the individual rotors are meshed with their own overset meshes to model cyclic pitching motion. Final mesh count was 33 million cells. A time step corresponding to 1 azimuth per time step is used. Turbulence is resolved Figure 3: (Top Left) VBM disk on ROBIN body; (Top Right) Velocity profile at mid-plane around ROBIN body; (Bottom) Pressure coefficient comparison between experiment, overset mesh and VBM approach with the SST k-ω turbulence model. The averaged CT from STAR-CCM+ is and the solution is found to be periodic in 3 to 4 revolutions. Thus, STAR-CCM+ with overset mesh is validated for interactional aerodynamics. The computational time is around 2 days on 96 computational cores. The same case is then validated for VBM without the blades being explicitly modeled for both untrimmed and trimmed cases. The computed CT from untrimmed case is and for the trimmed case where the target thrust is matched. The computational time here was just 4 hours on 96 cores. A comparison of the timeaveraged modified pressure coefficient along the fuselage centerline from overset and VBM methods is compared with test data. Both methodologies show excellent agreement, with the VBM model reducing the computational time significantly at the expense of lower fidelity. The overset approach captures wake vortex structures and propagation while the VBM model produces fast results for averaged performance parameters suitable for parametric analysis. Hover Performance Prediction Validation For hover performance prediction, it is important to capture and maintain the vortical flow and wake in a time-accurate manner. Validation of STAR-CCM+ hover performance prediction on a S-76 rotor3 was conducted against test data and CFD predictions by a hybrid CFD-free wake modeling (GT-Hybrid) method for rotors in hover/forward flight. The validation work focused on capturing accurate trends in hover performance, tip vortex contraction rate, descent rate based on blade tip shape and Figure of Merit (ideal power/required power). The computational domain for the rotors extended to 6 radii above, radii below and 7 radii in the radial direction. Overset mesh is used for the rotor and for the individual blades with a total mesh count of approximately 15 million

4 SIMCENTER cells. Volumetric refinements are used to capture the vortex structures in the rotor vicinity. The solution is run for 16 to 20 revolutions with a time step equaling 1 azimuth. The near wake and the inner wake are well captured while the far field wake is smeared due to numerical diffusion from coarse grid. Discrete starting vortices appear over the first 10 to 12 revolutions. The performance parameters are compared with test data, GT-Hybrid data and other state-of-the-art wake-capturing methods from OVERFLOW and Helios software. STAR-CCM+ compares well with the test data and follows similar trends as the other approaches. The torque is slightly over-predicted at high-thrust settings. The solution is reached in 16 hours on 96 cores, showing efficient computational time and methodology for industrial use. Figure 4: (Left) Overset Mesh around S-76 rotor and blades; (Right) Rotor wake from STAR-CCM+ ENGINE INTEGRATION The performance, operability, and reliability demands placed on modern rotorcraft engines requires stringent management and control of the engine component operating temperatures. Temperature gradients are difficult and expensive to predict with testing. Engine integration often includes over 1,000 parts. Simulation can alleviate this difficulty by evaluating the thermal design of the engine and its integration with the fuselage. Numerical simulation of engine integration from a thermal perspective requires accurately capturing the engine in the cowling with the casing, bypass paths and all other engine details. STAR-CCM+, with its ability to capture and quickly mesh complex geometry, can cut down analysis time for engine integration from weeks and months to days. Key Technology 2: Complex Geometry Handling Accurate estimation of rotorcraft thermal performance starts with maintaining geometric fidelity. Complex geometry can either be created within STAR-CCM+ 3D-CAD modeler, imported in neutral, CAD or PLM formats or directly transferred to STAR-CCM+ from CAD software using CAD-Clients. An extensive set of surface preparation options can remove CAD errors. The Surface Wrapper feature automatically produces a water-tight, CFD-ready geometry without any defeaturing, providing high geometric fidelity. Automatic gap closure and contact prevention can reduce CAD-to-mesh time from months to days. Parametric CAD can Figure 5: Comparison of STAR-CCM+ Overset Mesh results on S-76 rotor with experiment and other codes be leveraged for quick design changes to achieve optimal thermal integration. Key Technology 3: Flexible, Automated Meshing Meshing for rotorcraft engine simulations requires accurate capture of the surface geometry and a fully conformal mesh between solid and fluid regions. The meshing in STAR-CCM+ is automated and parallel/concurrent, offering three choices for these simulations: polyhedral, tetrahedral and trimmed hexahedral meshing. The boundary layer flow is captured with automated prism layer meshing. Specialized meshers to capture intricate details include thin mesh, advancing layer mesh, extruder and generalized cylinder. Parts-based meshing provides full automation for design optimization studies and reduces turnaround time. Key Technology 4: Conjugate Heat Transfer (CHT) CHT analysis refers to the simultaneous heat transfer in both solid and fluid domains where conduction in the solid material and convection in the fluid are analyzed. The addition of radiation to this analysis offers a complete framework for accurate CHT analysis. STAR-CCM+ offers a robust and accurate CHT solution, including conduction, convection and radiation models. Automated, fully conformal polyhedral meshing provides optimal accuracy for thermal simulations with one-to-one connectivity at the solid-fluid

5 SIMCENTER Figure 6: Thermal contours from a CHT analysis on a rotorcraft engine Figure 7: Temperature profiles from engine integration analysis interface. For low-fidelity simulations, a non-conformal trimmed hexahedral mesh with mapped interface option reduces mesh preparation time. When in-plane conduction is important, the thin mesher and embedded thin mesher are available for meshing thin-walled bodies. ICING/ICE PROTECTION The cold environments in which rotorcrafts operate warrant a proper understanding of icing and protection against ice formation during design. Icing alters performance and reduces visibility and engines often stall and flame out due to extensive ice accretion on the turbine blades. Regulators require all rotorcraft to be certified to fly in icing conditions, including super cooled large droplet impingement and micro crystal impingement in engine. Designing and testing ice protection systems is a long, complicated and expensive process. With simulation, rotorcraft systems can be Figure 8: 3D glaze ice accretion from STAR-CCM+ on a swept wing with a GLC-305 airfoil section designed for various icing conditions and ice protection systems can be validated properly before testing prototypes. STAR-CCM+ is the only multidisciplinary CFD code that provides a single-integrated, fully 3D ice accretion and ice-protection simulation tool with a single license. The icing capability simulates collection efficiency, first ice location, ice shapes (accretion) and aerodynamic performance degradation due to ice accretion. First, STAR-CCM+ predicts the airflow, both internal (piccolo tubes, heating strips) and external, for complex geometries. Also calculated is the heat transfer distribution on the aircraft skin with CHT capability. 3D impingement information (collection efficiency) is obtained either via Lagrangian Multi-Phase (LMP) model, where individual supercooled water droplets are modeled, or via Dispersed Multi-Phase (DMP) model, a lightweight Eulerian model that uses a statistical distribution of particles of a given average size. Liquid film models then predict runback, freezing, evaporation and heat transfer effects of the ice accretion on the surface. Finally, a mesh morphing capability allows regeneration of the computational mesh for the estimated ice buildup (accretion) that is coupled with the airflow to accurately compute shapes and effects on aerodynamic performance FLUID-STRUCTURE INTERACTION (FSI) Rotorcraft designers focus is on the performance, operability and durability of the vehicle. The sizing of individual hub components depends on the peak loads and stresses developed on the rotor hub structure. Additionally, vibratory loads are also important from a fatigue standpoint. Rotor vibratory loads prediction is a challenging problem because of the inherent aeroelastic response of the blades.

6 SIMCENTER Figure 9: FSI simulation of HIRENASD wing from AIAA aeroelastic workshop; (Left) Displacement of wing; (Right) STAR-CCM+ comparison of displacement with experiment Accurate prediction of rotor loads requires accounting for the complex interaction of unsteady aerodynamics, inertial and elastic forces on the rotor blades. Thus, for a truly high-fidelity solution, the non-linear, unsteady aerodynamics must be coupled with the structural analysis to account for aeroelastic response. In addition, the process needs to be suitable for multidisciplinary design exploration to achieve the best compromise between the aerodynamic and structural components. STAR-CCM+ offers both tightly coupled and loosely coupled options for FSI with a deformable solid. Key Technology 5: Co-Simulation STAR-CCM+ offers a direct link to Abaqus finite element analysis (FEA) software through a co-simulation application programming interface (API) developed by SIMULIA. This delivers a fully-coupled, two-way, parallel, implicit/explicit, FSI capability for rotorcraft aeroelastic analysis. Import and export of beam motion and deformation data from comprehensive rotorcraft analysis tools such as RCAS, DYMORE and CAMRAD is also available. Key Technology 6: Computational Structural Mechanics (CSM) To answer the need for a single-integrated solution for CFD/CSD problems, STAR-CCM+ offers a fully integrated, implicit Finite Element (FE) solver. Rotorcraft engineers can couple fluid and structural analyses to tackle FSI design challenges from a singleintegrated user interface. The fluid and solid domains can be modeled in different reference frames, significantly improving convergence and stability, resulting from the elimination of large, non-linear displacement effects in the stiffness matrix which are expensive to compute. DESIGN SPACE EXPLORATION The ability to tackle the majority of design challenges from within a single environment in STAR-CCM+ has the capability to significantly reduce expensive testing, improve the design and reduce operational risk. A truly multidisciplinary design exploration (MDX) approach, offered by Siemens PLM software, is the final key to this design puzzle. STAR-CCM+ provides a complete MDX toolkit with advanced CAD-interface, process automation with JAVA and plug-ins, fully automated meshing, economic sensitivity analysis with adjoint solver and seamless design optimization with Optimate+. HEEDS MDO brings the power of MDX and process integration. In addition, our flexible power licensing schemes allow users to leverage their computational resources for a truly MDX approach. The Power-Session license, Power-On-Demand license and Power Tokens allow STAR-CCM+ to be distributed across an unlimited number of processors for a fixed cost, maximizing the return-on-investment and reducing simulation cost for design exploration and optimization. Key Technology 7: HEEDS MDO/ Optimate+ HEEDS MDO is a key differentiator in bringing the true power of MDX to rotorcraft design. HEEDS MDO utilizes the revolutionary SHERPA algorithm, adapting itself to the problem automatically, leading to improved design of a single rotorcraft component or analyzing complex multidisciplinary systems. With HEEDS MDO, users can now perform multidisciplinary, multi-objective parametric design optimization, automated design of experiments (DOE), sensitivity studies, and process integration/ automation and robustness/reliability assessments. When faster turnaround time is important, HEEDS PARALLEL allows simultaneous execution of design studies. With HEEDS, data flows automatically among CAD, CAE, in-house proprietary codes and cost models, eliminating tedious manual data transfer and costly errors. Optimate+ is a STAR-CCM+ add-on module that leverages HEEDS MDO to perform design exploration and optimization from within the STAR-CCM+ environment, leading to improved designs and productivity while reducing design cost. CONCLUSION The MDX approach to rotorcraft design, outlined here, offers a high-fidelity, fully coupled, design exploration and optimization approach that reduces physical testing, improves design, accounts for interactional effects and provides a streamlined design approach from within a single platform. REFERENCES 1) Steady and Periodic Pressure Measurements on a Generic Helicopter Fuselage Model in the Presence of a Rotor. Raymond E. Mineck, ) Kubrak, B., Snyder D., CFD Code Validation of Rotor/Fuselage Interaction Using the Commercial Software STAR-CCM Proceedings of the European Rotorcraft Forum ) Ritu M. Eshcol, Chong Zhou, Jeewoong Kim, and Lakshmi N. Sankar. «A Comparative Study of Two Hover Prediction Methodologies,» 54th AIAA Aerospace Sciences Meeting, AIAA SciTech, (AIAA ) 4) Robert Narducci, «Hover Performance Assessment of Several Tip Shapes using OVERFLOW,» 53rd AIAA Aerospace Sciences Meeting, AIAA SciTech, (AIAA ). Siemens PLM Software Americas Europe +44 (0) Asia-Pacific Siemens Product Lifecycle Management Software Inc. Siemens and the Siemens logo are registered trademarks of Siemens AG. Other logos, trademarks, registered trademarks or service marks belong to their respective holders A2 9/16 F