Documents published in Scipedia

• Fluid-structure interaction tool for morphing blades

  G. Abate, J. Riemenschneider

  eccomas2022.

  
  

  Abstract

  The design of aeronautical components commonly involves two highly coupled disciplines: aerodynamics and structural mechanics. The interaction between them becomes even more relevant when morphing aeronautical structures are studied. Considering the importance of morphing technology for the future of the aerospace industry, several tools have already been developed to couple these two disciplines together, but all of them deal with pure twodimensional or three-dimensional aero-structural problems. In some circumstances, the study of aeronautical components requires to couple a 2D computational fluid-dynamics (CFD) analysis with a 3D finite element analysis (FEA). This usually happens in the preliminary design phase of aeronautical engine blades (i.e. compressor blades) where the aerodynamic study of the original 3D geometry is replaced by the analysis of a 2D blade cascade in order to reduce the overall computational cost. However, such an approach requires a specific method to couple the 2D CFD geometry/mesh with the 3D FEA geometry/mesh in order to transfer the aerodynamic loads from the CFD analysis to the structural one. As mentioned before, the existing fluid-structure interaction (FSI) tools cannot be implemented to solve a 2D-3D problem; therefore, a novel 2D3D aero-structure coupling approach needs to be developed. This paper describes step-by-step the 2D-3D aero-structure coupling strategy applied to the performance analysis of a morphing blade cascade with the goal of enhancing its aerodynamic performance. The results show a relevant decrease in the total pressure losses of the morphing cascade thanks to the adapting blade leading-edge. In order to highlight the reliability of the FSI framework, the developed approach is applied to four different blade configurations which differ in size and location of the two morphing devices.

  Abstract
  The design of aeronautical components commonly involves two highly coupled disciplines: aerodynamics and structural mechanics. The interaction between them becomes even more [...]

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• Unstructured high-order solutions of hovering rotors with and without ground effect

  P. A. S. F. Silva, P. Tsoutsanis, A. Antoniadis, K. Jenkins

  eccomas2022.

  
  

  Abstract

  This work describes the computational cost and accuracy of high-order numerical schemes on a simplified concept of multiple reference frame (MRF) technique using mixedelement unstructured grid framework widely tested for aerospace applications. The Reynolds averaged Navier-Stokes equations are approximated with up to fourth spatial order using Spalart Allmaras turbulence model on two types of reconstruction scheme: monotonic upwind scheme for conservation laws (MUSCL) and weighted non-oscillatory (WENO). The calculations were made for both out-of-ground-effect (OGE) and in-ground-effect (IGE) cases and compared with experimental data in terms of pressure distribution, tip-vortex trajectory, vorticity contours and integrated thrust and torque. The predictions were obtained for several ground distances. Our findings suggest that the resolution of the vortex path and wake breakdown were considerably improved with increased scheme order. It is noticeable how low-order scheme struggles to deal with the large amount of diffusion. This numerical nature contributes to the vortex system settle down and achieve this stable ring state structure as seen on a couple radii downstream the rotor. As the wake is transported downwards, it can be clearly seen the interaction primary and secondary structures, which stretch between the tip vortices making an S-shaped path also seen experimentally. The presence of the vortex-ring close to the rotor blade contributes to a larger induced flow and under predictions of thrust coefficient . As we increase the scheme-order, it becomes more evident how the helical system convects down and breakdown toroidal vortex into smaller scales.

  Abstract
  This work describes the computational cost and accuracy of high-order numerical schemes on a simplified concept of multiple reference frame (MRF) technique using mixedelement [...]

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• Large-eddy simulations of turbulent compressible supersonic jet flows using discontinuous Galerkin methods

  D. Abreu, C. Junqueira-Junior, E. Dauricio, J. Azevedo

  eccomas2022.

  
  

  Abstract

  In this work, a discontinuous Galerkin scheme is employed to perform large-eddy simulations of supersonic jet flows. A total of four simulations are performed with different meshes and order of accuracy to identify the resolution requirements to reproduce the physical characteristics from experiments. The number of degrees of freedom from the simulations varies from 50 × 106to 400 × 106. The results indicate that by increasing the resolution of simulation, in general, the results got closer to experimental data. The comparison of velocity distribution in the jet centerline and lipline from the simulation with 400 × 106with experimental shows that important characteristics of the flow are represented. The study investigated a procedure of using lower-order simulations to initialize high-order simulations to reduce the total computational cost of the calculation. This strategy is successful and allows the performance of high-order simulations with only 6% more computational effort than a second-order simulation with the same number of degrees of freedom.

  Abstract
  In this work, a discontinuous Galerkin scheme is employed to perform large-eddy simulations of supersonic jet flows. A total of four simulations are performed with different [...]

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• Accelerating the simulation of elastohydrodynamic lubrication in a line contact using a surrogate model

  N. Delaissé, P. Havaej, D. Fauconnier, J. Degroote

  eccomas2022.

  
  

  Abstract

  Elastohydrodynamically lubricated contacts are an example of a strongly coupled fluid-structure interaction problem. Typically, these problems are solved in a partitioned way and require multiple flow-structure iterations per time step to reach convergence. The manner in which these iterations are performed is determined by the coupling algorithm. In the previous decade, several algorithms have been proposed, most of which are based on a quasi-Newton principle. These methods use an approximate Jacobian, which is constructed during the calculation itself. However, in many cases, a simpler model is available, which provides an approximate solution and Jacobian, and is denoted as surrogate model. For the elastohydrodynamically lubricated contact, this model is the coupled Reynolds-Boussinesq approach, which evaluates significantly faster than the CFD-CSM simulation. The incorporation of a surrogate model in a quasi-Newton method is realized with the IQN-ILSM algorithm. This work is a first step towards employing this coupling method for the elastohydrodynamically lubricated contact and, in this way, combining the speed of the Reynolds-Boussinesq approach with the accuracy and versatility of the CFD-CSM modelling. In the current work, only the surrogate solution will be used as initial solution. The use of the surrogate Jacobian is future work.

  Abstract
  Elastohydrodynamically lubricated contacts are an example of a strongly coupled fluid-structure interaction problem. Typically, these problems are solved in a partitioned [...]

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• An extended discontinuous Galerkin method for high-order shock treatment

  J. Sebastian, F. Kummer

  eccomas2022.

  
  

  Abstract

  In this paper, we are going to present a high-order shock fitting approach based on a cut-cell method. We formulate a suitable Constraint Optimization Problem and develop an algorithm aiming to reconstruct the shock front represented by the zero iso-contour of a Level Set function.

  Abstract
  In this paper, we are going to present a high-order shock fitting approach based on a cut-cell method. We formulate a suitable Constraint Optimization Problem and develop [...]

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• Hybrid High-Order Finite Volume/Discontinuous Galerkin Methods for Turbulent Flows

  D. Yuan, P. Tsoutsanis, K. Jenkins

  eccomas2022.

  
  

  Abstract

  In this paper we develop a family of arbitrarily high-order non-oscillatory hybrid Finite Volume/Discontinuous Galerkin schemes for turbulent flows on mixed-element unstructured meshes. The schemes are inherently compact in the sense that the central stencils employed are as compact as possible, and that the directional stencils are reduced in size, simplifying their implementation. Their key ingredient is the switch between a DG method and a FV method based on the CWENOZ scheme when a troubled cell is detected. Therefore, in smooth regions of the computational domain, the high order of accuracy offered by DG is preserved, while in regions with sharp gradients, the robustness of FV is utilized. This paper also presents the time evolution of troubled cells in unsteady test cases and the use of extended bounds for troubled cell detection. We assess the performance of these schemes in terms of accuracy, robustness and computational cost through a series of stringent 2D and 3D test problems. The results obtained demonstrate the accuracy and robustness that the schemes offer and highlight areas of future improvements that are considered.

  Abstract
  In this paper we develop a family of arbitrarily high-order non-oscillatory hybrid Finite Volume/Discontinuous Galerkin schemes for turbulent flows on mixed-element unstructured [...]

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• Deep Neural Network-driven hp-adaptive Finite Element Method in three dimensions

  M. Paszynski, R. Grzeszczuk, W. Dzwinel, D. Pardo

  eccomas2022.

  
  

  Abstract

  Numerical solutions of Partial Differential Equations with Finite Element Method have multiple applications in science and engineering. Several challenging problems require special stabilization methods to deliver accurate results of the numerical simulations. The advection-dominated diffusion problem is an example of such problems. They are employed to model pollution propagation in the atmosphere. Unstable numerical methods generate unphysical oscillations, and they make no physical sense. Obtaining accurate and stable numerical simulations is difficult, and the method of stabilization depends on the parameters of the partial differential equations. They require a deep knowledge of an expert in the field of numerical analysis. We propose a method to construct and train an artificial expert in stabilizing numerical simulations based on partial differential equations. We create a neural network-driven artificial intelligence that makes decisions about the method of stabilizing computer simulations. It will automatically stabilize difficult numerical simulations in a linear computational cost by generating the optimal test functions. These test functions can be utilized for building an unconditionally stable system of linear equations. The optimal test functions proposed by artificial intelligence will not depend on the right-hand side, and thus they may be utilized in a large class of PDE-based simulations with different forcing and boundary conditions. We test our method on the model one-dimensional advection-dominated diffusion problem.

  Abstract
  Numerical solutions of Partial Differential Equations with Finite Element Method have multiple applications in science and engineering. Several challenging problems require [...]

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• A numerical set-up for the simulation of infection probability from SARS- CoV-2 in public transport vehicles

  E. Schillaci, J. Vera, N. Morozova, J. Rigola

  eccomas2022.

  
  

  Abstract

  In this work, a numerical framework aimed at simulating the transport of contaminants and infectious agents within a closed domain is presented. The method employs mature CFD algorithms to calculate air fields with reasonable computational costs. The main objective is to give fast response to stakeholders about air quality indicators in the design phase of HVAC systems. A discussion regarding the size and characteristics of different contaminants is proposed, highlighting the most appropriate methods and coefficients needed to simulate their transport. Next, the methodology employed to evaluate the risk of infection is presented. The numerical set-up, based on the buoyantBoussinesqPimpleFoam solver in OpenFOAM, was tuned by simulating the well-known case of the heated floor cavity, providing accurate results. Hence, the case study of a transport vehicle of generic shape is presented, in order to show possible results in terms of air-age distribution, PM2.5 distribution, and global infection risk matrix.

  Abstract
  In this work, a numerical framework aimed at simulating the transport of contaminants and infectious agents within a closed domain is presented. The method employs mature [...]

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• A CFD-based multi-fidelity surrogate model for prediction of flow parameters in a ventilated room

  N. Morozova, F. Trias, V. Vanovskiy, C. Oliet, E. Burnaev

  eccomas2022.

  
  

  Abstract

  In this work, we present a multi-fidelity machine learning surrogate model, which predicts comfort-related flow parameters in a ventilated room with a heated floor. The model uses coarseand fine-grid CFD data obtained using LES turbulence models. The dataset is created by changing the width aspect ratio of the rooms, inlet flow velocity, and temperature of the hot floor. The surrogate model takes the values of temperature and velocity magnitude at four different cavity locations as inputs. These probes are located such that they could be replaced by actual sensor readings in a practical case. The model's output is a set of comfort-related flow parameters. We test two multi-fidelity approaches based on Gaussian process regression (GPR), among them GPR with linear correction (LC GPR), and multi-fidelity GPR (MF GPR) or cokriging. The computational cost and accuracy of these approaches are compared with GPRs based on single-fidelity data. All of the tested multi-fidelity approaches successfully reduce the computational cost of dataset generation compared to high-fidelity GPR while maintaining the required level of accuracy. The co-kriging approach demonstrates the best trade-off between computational cost and accuracy.

  Abstract
  In this work, we present a multi-fidelity machine learning surrogate model, which predicts comfort-related flow parameters in a ventilated room with a heated floor. The model [...]

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• Refinement techniques for spline spaces with cloud-based geomiso TNL software

  P. Karakitsios, P. Kolios, A. Leontaris, G. Karaiskos

  eccomas2022.

  
  

  Abstract

  Geomiso TNL is a new both on-premises and cloud-based software, which delivers isogeometric analysis (IGA) and 3D design with splines. It combines IGA and cloud computing, one of the fastest growing fields in IT industry. The combination of cloud computing and advanced refinement techniques constitutes a real game changer in CAD/CAE fields. Cloud-based IGA represents the future of product engineering, soon to become an industry standard. Automatic mesh refinement has not been widely adopted in industry, because it requires access to the exact geometry. This hybrid program achieves seamless and automatic communication with CAD, thus mesh refinement utilizes the exact geometry, while cloud computing enables users to execute large-scale simulation experiments without the need for dedicated hardware. The recently developed cloud-based platform www.geomiso.cloud is introduced to help engineers and industries make effective use of inelastic static isogeometric analysis and design with advanced spline techniques. It is argued that Geomiso TNL is a new, more efficient, alternative to FEA software packages. This is the first time ever such a cloud-based program has been developed.

  Abstract
  Geomiso TNL is a new both on-premises and cloud-based software, which delivers isogeometric analysis (IGA) and 3D design with splines. It combines IGA and cloud computing, [...]

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