A.H. van Zuijlen
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95 records found
1
Exhaust Dispersion on Naval Vessels
An LES Informed Evaluation of RANS Scalar Transport Closure Models to Improve Predictive Accuracy
tools for naval exhaust dispersion.
This research started with an evaluation of a fundamental study into a canonical wall mounted cube with an exhaust located in its wake as a simplified representation of ship superstructure flow. An Large Eddy Simulation (LES) was performed to resolve the dominant turbulent structures responsible for scalar mixing and was compared to experimental data. The resulting turbulence statistics were used to perform both a priori and a posteriori analyses of commonly used scalar transport closures, the Gradient Diffusion Hypothesis (GDH) and the Generalised Gradient Diffusion Hypothesis (GGDH). Finally the findings were applied in the context of a realistic geometry of a Commissioning Service Operating Vessel (CSOV).
The results show that LES predicts more realistic concentration distributions compared to the conventional RANS simulations, although both LES and RANS under predict the magnitude of the concentration compared to experimental observations. Deficiencies were found in the modelling of the turbulent scalar fluxes for both gradient based models. The inclusion of anisotropy through the Reynolds stress tensor in GGDH improves the alignment of the predicted scalar fluxes with the LES data and therefore also reduced the global prediction errors compared to the conventional isotropic GDH formulation. Constant model coefficients were determined from the mode of the LES inferred values of the coefficient. The improvement this made to the dispersion estimate was far greater than increasing the model complexity, the calibrated GDH model outperformed the uncalibrated GGDH simulation. Spatially varying model coefficients provided only limited additional benefit over optimised constant values, from a global prediction error perspective.
Applying the calibrated coefficients to a realistic ship geometry revealed that scalar concentration predictions exhibit strong sensitivity to local flow structures introduced by the different meshes investigated, even when global flow quantities such as aerodynamic force coefficients appear converged. The findings demonstrate that improving the reliability of practical exhaust dispersion simulations requires not only improved scalar closure models and coefficient selection, but also rigorous verification
of the underlying flow solution. ...
tools for naval exhaust dispersion.
This research started with an evaluation of a fundamental study into a canonical wall mounted cube with an exhaust located in its wake as a simplified representation of ship superstructure flow. An Large Eddy Simulation (LES) was performed to resolve the dominant turbulent structures responsible for scalar mixing and was compared to experimental data. The resulting turbulence statistics were used to perform both a priori and a posteriori analyses of commonly used scalar transport closures, the Gradient Diffusion Hypothesis (GDH) and the Generalised Gradient Diffusion Hypothesis (GGDH). Finally the findings were applied in the context of a realistic geometry of a Commissioning Service Operating Vessel (CSOV).
The results show that LES predicts more realistic concentration distributions compared to the conventional RANS simulations, although both LES and RANS under predict the magnitude of the concentration compared to experimental observations. Deficiencies were found in the modelling of the turbulent scalar fluxes for both gradient based models. The inclusion of anisotropy through the Reynolds stress tensor in GGDH improves the alignment of the predicted scalar fluxes with the LES data and therefore also reduced the global prediction errors compared to the conventional isotropic GDH formulation. Constant model coefficients were determined from the mode of the LES inferred values of the coefficient. The improvement this made to the dispersion estimate was far greater than increasing the model complexity, the calibrated GDH model outperformed the uncalibrated GGDH simulation. Spatially varying model coefficients provided only limited additional benefit over optimised constant values, from a global prediction error perspective.
Applying the calibrated coefficients to a realistic ship geometry revealed that scalar concentration predictions exhibit strong sensitivity to local flow structures introduced by the different meshes investigated, even when global flow quantities such as aerodynamic force coefficients appear converged. The findings demonstrate that improving the reliability of practical exhaust dispersion simulations requires not only improved scalar closure models and coefficient selection, but also rigorous verification
of the underlying flow solution.
Aerodynamic sensitivity of race cars
A case study of Le Mans Hypercars
This research further dissects the aerodynamic sensitivities of Le Mans Hypercars, and what the driving mechanisms are behind losses in specific conditions. Then, this research takes the step to develop designs that are able to turn the loss experienced during a lap into a gain. ...
This research further dissects the aerodynamic sensitivities of Le Mans Hypercars, and what the driving mechanisms are behind losses in specific conditions. Then, this research takes the step to develop designs that are able to turn the loss experienced during a lap into a gain.
For the rigid rotor, the coupled simulations converged stably across all flight conditions, and the predicted mean airloads and approximate blade-vortex interaction (BVI) locations compared reasonably well against HART-II experimental data, although the coarse CFD mesh limited the accuracy of the detailed sectional load fluctuations associated with BVI. In contrast, the flexible rotor simulations revealed a critical limitation: inconsistencies in the predicted aerodynamic pitching moment propagated into the elastic torsional response, producing an unstable aeroelastic feedback loop that caused chaotic blade flapping and feathering and, in several cases, prevented convergence of the trim solution.
These results indicate that the ENSOLV-FLIGHTLAB coupling is a verified and reliable framework for rigid rotor load prediction, but that its current implementation is not yet suitable for flexible aeroelastic rotor analysis. The dominant limitations are the coupling between the aerodynamic pitching moment and the structural torsional response, and insufficient resolution and preservation of the rotor wake. Recommendations to address these limitations are provided to guide future development of the framework. ...
For the rigid rotor, the coupled simulations converged stably across all flight conditions, and the predicted mean airloads and approximate blade-vortex interaction (BVI) locations compared reasonably well against HART-II experimental data, although the coarse CFD mesh limited the accuracy of the detailed sectional load fluctuations associated with BVI. In contrast, the flexible rotor simulations revealed a critical limitation: inconsistencies in the predicted aerodynamic pitching moment propagated into the elastic torsional response, producing an unstable aeroelastic feedback loop that caused chaotic blade flapping and feathering and, in several cases, prevented convergence of the trim solution.
These results indicate that the ENSOLV-FLIGHTLAB coupling is a verified and reliable framework for rigid rotor load prediction, but that its current implementation is not yet suitable for flexible aeroelastic rotor analysis. The dominant limitations are the coupling between the aerodynamic pitching moment and the structural torsional response, and insufficient resolution and preservation of the rotor wake. Recommendations to address these limitations are provided to guide future development of the framework.
This research addresses this physical modeling gap by developing and validating a high-fidelity partitioned static Fluid-Structure Interaction (FSI) framework. The proposed framework establishes a two-way coupling between Ansys Fluent and MSC Nastran, leveraging Computational Fluid Dynamics (CFD) to resolve complex aerodynamic phenomena and the Finite Element Method (FEM) for high-fidelity structural modeling. The framework is applied to the Onera M6 wing, serving as the primary validation case.
A parametric study involving multiple high-fidelity static FSI simulations across varied angles of attack and Mach numbers is then conducted. These results are contrasted against low-fidelity predictions, quantifying the significant errors introduced by neglecting non-linear flow characteristics. This comparison proves the high-fidelity framework's definitive capability to capture the complex physics required for accurate static aeroelastic modeling. ...
This research addresses this physical modeling gap by developing and validating a high-fidelity partitioned static Fluid-Structure Interaction (FSI) framework. The proposed framework establishes a two-way coupling between Ansys Fluent and MSC Nastran, leveraging Computational Fluid Dynamics (CFD) to resolve complex aerodynamic phenomena and the Finite Element Method (FEM) for high-fidelity structural modeling. The framework is applied to the Onera M6 wing, serving as the primary validation case.
A parametric study involving multiple high-fidelity static FSI simulations across varied angles of attack and Mach numbers is then conducted. These results are contrasted against low-fidelity predictions, quantifying the significant errors introduced by neglecting non-linear flow characteristics. This comparison proves the high-fidelity framework's definitive capability to capture the complex physics required for accurate static aeroelastic modeling.
This research project aimed to identify the main pressure drop drivers and develop an accurate, cost-effective numerical model for simulating arbitrary grille geometries. The impact of grille location and geometrical construction on radiator performance was analyzed to optimize cooling efficiency and aerodynamic performance. The investigation employed Computational Fluid Dynamics (CFD) RANS simulations using Ansys Fluent. Although multiple validation attempts were conducted using a radiator test bench, the experimental results showed unsatisfactory reproducibility and coherence.
The investigation identified the hexagonal mesh pattern with circular wire as the optimal grille configuration, delivering the lowest static pressure losses while maintaining equivalent debris protection. Pressure loss proved slightly more sensitive to wire thickness changes than to opening size variations. In both cases, the optimal configuration exists at the structural and functional limits: wire should be as thin as structurally viable, and openings as large as possible while maintaining protective capability.
Although pressure loss across the grille and radiator was independent of their separation distance, the radiator demonstrated increased aerodynamic efficiency when distance was minimized, making this the preferable setup. The research also explored using protective grilles to deflect and align airflow with the radiator inlet face. However, the complexity of achieving optimized grille design, combined with additional custom manufacturing costs, rendered this concept impractical.
Data from numerical tests on various grille configurations formed the foundation for developing a mathematical model capable of predicting pressure losses for arbitrary grilles at incoming flow speeds ranging from 6 to 22 m/s. This formulation was subsequently used to represent the grille as a porous medium. Numerical validation demonstrated that the modeled grille in series with a radiator exhibited total pressure loss only 0.5% higher than the geometrically modeled configuration, confirming the approach's robustness and accuracy.
This research advanced understanding of the aerodynamic impact of motorsport protective grilles, clarifying how key geometrical parameters and positioning relative to the radiator affect pressure losses. The developed grille modeling provides a robust and accurate method for simulating aerodynamic impact, enabling reduced safety margins in cooling system design. This work paves the way for further iterations and validation tests, ultimately supporting implementation in full-scale car simulations and contributing to more efficient thermal management solutions in high-performance motorsport applications.
...
This research project aimed to identify the main pressure drop drivers and develop an accurate, cost-effective numerical model for simulating arbitrary grille geometries. The impact of grille location and geometrical construction on radiator performance was analyzed to optimize cooling efficiency and aerodynamic performance. The investigation employed Computational Fluid Dynamics (CFD) RANS simulations using Ansys Fluent. Although multiple validation attempts were conducted using a radiator test bench, the experimental results showed unsatisfactory reproducibility and coherence.
The investigation identified the hexagonal mesh pattern with circular wire as the optimal grille configuration, delivering the lowest static pressure losses while maintaining equivalent debris protection. Pressure loss proved slightly more sensitive to wire thickness changes than to opening size variations. In both cases, the optimal configuration exists at the structural and functional limits: wire should be as thin as structurally viable, and openings as large as possible while maintaining protective capability.
Although pressure loss across the grille and radiator was independent of their separation distance, the radiator demonstrated increased aerodynamic efficiency when distance was minimized, making this the preferable setup. The research also explored using protective grilles to deflect and align airflow with the radiator inlet face. However, the complexity of achieving optimized grille design, combined with additional custom manufacturing costs, rendered this concept impractical.
Data from numerical tests on various grille configurations formed the foundation for developing a mathematical model capable of predicting pressure losses for arbitrary grilles at incoming flow speeds ranging from 6 to 22 m/s. This formulation was subsequently used to represent the grille as a porous medium. Numerical validation demonstrated that the modeled grille in series with a radiator exhibited total pressure loss only 0.5% higher than the geometrically modeled configuration, confirming the approach's robustness and accuracy.
This research advanced understanding of the aerodynamic impact of motorsport protective grilles, clarifying how key geometrical parameters and positioning relative to the radiator affect pressure losses. The developed grille modeling provides a robust and accurate method for simulating aerodynamic impact, enabling reduced safety margins in cooling system design. This work paves the way for further iterations and validation tests, ultimately supporting implementation in full-scale car simulations and contributing to more efficient thermal management solutions in high-performance motorsport applications.
Assessment of a GPU accelerated Cartesian Fast Multipole Method
Accuracy and performance analysis of Cartesian FMM applied on the vortex particle method
Inline with the increasing adoption of GPUs in performing scientific computations, the solver developed assigns computationally heavy tasks to parallelised execution on the CPU or GPU, using the taichi compiler. The accompanying introduction of reduced floating point accuracy introduces new considerations for the accuracy of the method when performed on the GPU. Error quantification is performed on a single timestep for a range of flow scenarios, with an emphasis on the effect of main FMM parameters on accuracy. Results indicate a positive impact of increasing the Taylor series truncation order on FMM accuracy, up to a plateau caused by the accumulation of rounding errors. The octree depth was found to have low impact on the accuracy. Validation of the solver is performed through underresolved direct numerical simulation (DNS) of Lamb-Oseen vortex, vortex ring, and colliding vortex ring test cases. The impact of FMM on particle velocities and positions throughout simulations is measured, and key flow diagnostics are provided, indicating minimal FMM impact on the physical validity of simulations.
More chaotic flows exhibited an unbounded nature of FMM error growth while low Reynolds number flows counteracted the FMM error. The performance of the main operations of the solver was profiled, highlighting trade-offs between speed and accuracy, and indicating areas for future performance improvements. ...
Inline with the increasing adoption of GPUs in performing scientific computations, the solver developed assigns computationally heavy tasks to parallelised execution on the CPU or GPU, using the taichi compiler. The accompanying introduction of reduced floating point accuracy introduces new considerations for the accuracy of the method when performed on the GPU. Error quantification is performed on a single timestep for a range of flow scenarios, with an emphasis on the effect of main FMM parameters on accuracy. Results indicate a positive impact of increasing the Taylor series truncation order on FMM accuracy, up to a plateau caused by the accumulation of rounding errors. The octree depth was found to have low impact on the accuracy. Validation of the solver is performed through underresolved direct numerical simulation (DNS) of Lamb-Oseen vortex, vortex ring, and colliding vortex ring test cases. The impact of FMM on particle velocities and positions throughout simulations is measured, and key flow diagnostics are provided, indicating minimal FMM impact on the physical validity of simulations.
More chaotic flows exhibited an unbounded nature of FMM error growth while low Reynolds number flows counteracted the FMM error. The performance of the main operations of the solver was profiled, highlighting trade-offs between speed and accuracy, and indicating areas for future performance improvements.
Stochastically excited structures in an infinite fluid domain
Numerical representation of the vibroacoustic behaviour of marine propellers under turbulent excitation
COMSOL Multiphysics is a software package used for verification. The complexity of the loads that can be used in COMSOL Multiphysics is limited and is not suitable for a turbulent flow load. Simple load cases were used as verification.
Various methods are employed to obtain a response power spectral density (PSD) identical to COMSOL Multiphysics. The KM-method matched the COMSOL response PSD well, while the A-matrix method faced challenges. The state-space reconstruction method showed some similarity while using a proportionally-damped response function, but did not fully match the COMSOL response PSD.
...
COMSOL Multiphysics is a software package used for verification. The complexity of the loads that can be used in COMSOL Multiphysics is limited and is not suitable for a turbulent flow load. Simple load cases were used as verification.
Various methods are employed to obtain a response power spectral density (PSD) identical to COMSOL Multiphysics. The KM-method matched the COMSOL response PSD well, while the A-matrix method faced challenges. The state-space reconstruction method showed some similarity while using a proportionally-damped response function, but did not fully match the COMSOL response PSD.
Modelling of Fluid-Structure Interaction of Tube Bundles Subjected to Cross-Flow
A Computational Study on Hybrid Turbulence Models for Flow-Induced Vibrations
Hybrid turbulence models, including Scale-Adaptive Simulation (SAS) and Delayed Detached
Eddy Simulation (DDES), were explored for their ability to balance computational efficiency with the accuracy required for FIV predictions. Simulations were conducted in ANSYS Fluent and STAR-CCM+ across various mesh configurations and flow conditions. The results indicate that DDES, particularly with fine polyhedral meshes and wall y+ < 1, provides improved predictions of flow-induced forces and vibrations. ANSYS Fluent exhibited greater robustness and reliability in this study, particularly for strongly coupled FSI problems in FIV simulations.
This research contributes to the ongoing efforts in refining FIV simulation methodologies by proposing a standardized workflow and offering insights into the applicability of hybrid turbulence modeling. The findings enhance the understanding of FIV phenomena and support the development of improved numerical approaches for the safer design of nuclear reactor components. ...
Hybrid turbulence models, including Scale-Adaptive Simulation (SAS) and Delayed Detached
Eddy Simulation (DDES), were explored for their ability to balance computational efficiency with the accuracy required for FIV predictions. Simulations were conducted in ANSYS Fluent and STAR-CCM+ across various mesh configurations and flow conditions. The results indicate that DDES, particularly with fine polyhedral meshes and wall y+ < 1, provides improved predictions of flow-induced forces and vibrations. ANSYS Fluent exhibited greater robustness and reliability in this study, particularly for strongly coupled FSI problems in FIV simulations.
This research contributes to the ongoing efforts in refining FIV simulation methodologies by proposing a standardized workflow and offering insights into the applicability of hybrid turbulence modeling. The findings enhance the understanding of FIV phenomena and support the development of improved numerical approaches for the safer design of nuclear reactor components.
Modeling Flow-Induced Vibrations in Tube Bundles: From Turbulence to Motion
A Comparative Study of Numerical Models and Solver Approaches
This work evaluates the accuracy and uncertainty of a Stochastic Noise Generation and Radiation (SNGR) pipeline that reconstructs time-resolved, divergence-free velocity fluctuation fields from RANS statistics to improve in FIV and aero-acoustic assessments. Therefore, helping to ensure nanometer-scale manufacturing precision. The MATLAB based implementation ingests CGNS/HDF5 solver output, assembles modal Fourier fields from a prescribed energy spectrum, enforces incompressibility, applies anisotropic tensor mapping to match Reynolds stresses, and offers both a time-marching (single time-loop) and an ensemble snapshot mode. Validation is performed against canonical
Direct Numerical Simulation (DNS) reference data for turbulent channel flow (Lee & Moser, up to Reτ ≈ 5200)
and a benchmark backward-facing step, and comparisons are made with RANS (StarCCM+) results. A modular MATLAB pipeline automates diagnostics and produces slice-wise statistics (RMSE, absolute/relative errors), spatial heatmaps, PSDs, and GIF visualizations. Results show that SNGR successfully reproduces spectral content and the
spatial distribution of turbulence, yielding instantaneous fields that correlate with RANS TKE maps. However, the analysis reveals that discrepancies - particularly concentrated in near-wall amplitudes, outer-layer overshoots and the smallest resolved scales - are primarily inherited from biases in the initial RANS model. The report quantifies how these RANS biases, domain and boundary conditions choices and numeric resolution propagate into SNGR
reconstructions, and it recommends practical diagnostics and sensitivity checks for the robust industrial application of the SNGR method. ...
This work evaluates the accuracy and uncertainty of a Stochastic Noise Generation and Radiation (SNGR) pipeline that reconstructs time-resolved, divergence-free velocity fluctuation fields from RANS statistics to improve in FIV and aero-acoustic assessments. Therefore, helping to ensure nanometer-scale manufacturing precision. The MATLAB based implementation ingests CGNS/HDF5 solver output, assembles modal Fourier fields from a prescribed energy spectrum, enforces incompressibility, applies anisotropic tensor mapping to match Reynolds stresses, and offers both a time-marching (single time-loop) and an ensemble snapshot mode. Validation is performed against canonical
Direct Numerical Simulation (DNS) reference data for turbulent channel flow (Lee & Moser, up to Reτ ≈ 5200)
and a benchmark backward-facing step, and comparisons are made with RANS (StarCCM+) results. A modular MATLAB pipeline automates diagnostics and produces slice-wise statistics (RMSE, absolute/relative errors), spatial heatmaps, PSDs, and GIF visualizations. Results show that SNGR successfully reproduces spectral content and the
spatial distribution of turbulence, yielding instantaneous fields that correlate with RANS TKE maps. However, the analysis reveals that discrepancies - particularly concentrated in near-wall amplitudes, outer-layer overshoots and the smallest resolved scales - are primarily inherited from biases in the initial RANS model. The report quantifies how these RANS biases, domain and boundary conditions choices and numeric resolution propagate into SNGR
reconstructions, and it recommends practical diagnostics and sensitivity checks for the robust industrial application of the SNGR method.
VPMFoam
A 2D Incompressible Hybrid Eulerian-Lagrangian Solver for External Aerodynamics
A common requirement across these diverse fields is the need for an in-depth understanding of aerodynamics. Accurate aerodynamic analysis is essential for enhancing design, efficiency, and effectiveness. However, the fast-paced nature of modern advancements limits reliance on experimental methods alone, as these can be time-consuming, costly, and impractical for all possible configurations. Consequently, combining experimental and computational studies becomes crucial.
This is where Computational Fluid Dynamics (CFD) comes into play. The development of efficient and accurate CFD tools has become essential in scientists' and engineers' hands to explore aerodynamics quickly and understand the physics of the flows. This fact has driven the present research. The primary goal of this dissertation is the development of a computational tool that is both accurate and efficient for exploring external aerodynamics simulations.
The main approaches in CFD today are the Eulerian and Lagrangian approaches, each comprising a family of methods. Eulerian methods, like the Finite Volume Method (FVM) and Finite Element Method (FEM), have been extensively used in exploring external aerodynamics, with their greatest advantage being accuracy in capturing the boundary layers. However, due to the diffusive nature of these methods, artificial diffusion is introduced into the flow, damping the vortex structures, which are crucial in many applications driven by strong body-vortex interactions. Moreover, the study of multibody objects often requires special treatments, especially for mesh generation, making the simulations extremely costly.
On the other hand, Lagrangian methods, like the Vortex Particle Method (VPM), are excellent for studying flows with a high presence of vortices, as they can preserve the vortex structures without damping them. Additionally, the particles participating in the flow are self-adaptive, satisfy the far-field boundary conditions automatically, and allow for easy implementation of multiple bodies into the simulation. However, resolving the boundary layer is very challenging and often very costly due to the inability to use anisotropic elements, making them less ideal for predicting aerodynamic forces.
Lagrangian solvers have become very popular in the last two to three decades, primarily due to the significant advancements in computer hardware, especially GPUs, which enable very fast calculations. This has encouraged engineers to explore ways to leverage this advantage in CFD, leading to the development of hybrid solvers that couple Eulerian and Lagrangian solvers. In this coupled approach, Eulerian solvers can be applied near the solid body to accurately and efficiently resolve the boundary layer region, while Lagrangian solvers preserve the vortex structures further from the body.
Building on this approach, this dissertation introduces a hybrid Eulerian-Lagrangian solver, named VPMFoam, developed to combine the strengths of both methods while minimizing their limitations. This is achieved by integrating OpenFOAM, a widely used open-source CFD software, with a Lagrangian VPM. The primary goal is to create an accurate tool focused on external aerodynamics that can efficiently handle cases with strong body-vortex interactions and multibody scenarios while maintaining a lower computational cost compared to pure Eulerian solvers. OpenFOAM was chosen primarily for its open-source flexibility and its extensive user base in academia and industry, offering broad access to this tool.
The solver's development focuses on a 2D version, with validation conducted through a step-by-step approach, starting with simple cases that exclude solid bodies. Once the successful coupling of the two solvers is verified, validation proceeds with cases involving solid bodies, such as flow around a cylinder. In these cases, the solver accurately predicts fluid flow and aerodynamic coefficients, showing strong agreement with established Eulerian solvers and effectively preserving the vorticity field in the wake. Further validations address dynamic mesh motions and multibody applications.
Following validation, the solver is applied to more realistic scenarios, including the static and dynamic stall of an airfoil and the simulation of hybrid Vertical Axis Wind Turbines using actuator models. A performance analysis of the code’s efficiency is also presented, highlighting the solver’s capability to conduct fast and accurate simulations.
By effectively combining the strengths of both Eulerian and Lagrangian approaches, VPMFoam addresses key challenges in aerodynamic analysis, particularly in cases with strong body-vortex interactions, and lays a strong foundation for further applications, including potential 3D extensions. This makes VPMFoam a valuable asset for applications requiring both high fidelity and computational efficiency. ...
A common requirement across these diverse fields is the need for an in-depth understanding of aerodynamics. Accurate aerodynamic analysis is essential for enhancing design, efficiency, and effectiveness. However, the fast-paced nature of modern advancements limits reliance on experimental methods alone, as these can be time-consuming, costly, and impractical for all possible configurations. Consequently, combining experimental and computational studies becomes crucial.
This is where Computational Fluid Dynamics (CFD) comes into play. The development of efficient and accurate CFD tools has become essential in scientists' and engineers' hands to explore aerodynamics quickly and understand the physics of the flows. This fact has driven the present research. The primary goal of this dissertation is the development of a computational tool that is both accurate and efficient for exploring external aerodynamics simulations.
The main approaches in CFD today are the Eulerian and Lagrangian approaches, each comprising a family of methods. Eulerian methods, like the Finite Volume Method (FVM) and Finite Element Method (FEM), have been extensively used in exploring external aerodynamics, with their greatest advantage being accuracy in capturing the boundary layers. However, due to the diffusive nature of these methods, artificial diffusion is introduced into the flow, damping the vortex structures, which are crucial in many applications driven by strong body-vortex interactions. Moreover, the study of multibody objects often requires special treatments, especially for mesh generation, making the simulations extremely costly.
On the other hand, Lagrangian methods, like the Vortex Particle Method (VPM), are excellent for studying flows with a high presence of vortices, as they can preserve the vortex structures without damping them. Additionally, the particles participating in the flow are self-adaptive, satisfy the far-field boundary conditions automatically, and allow for easy implementation of multiple bodies into the simulation. However, resolving the boundary layer is very challenging and often very costly due to the inability to use anisotropic elements, making them less ideal for predicting aerodynamic forces.
Lagrangian solvers have become very popular in the last two to three decades, primarily due to the significant advancements in computer hardware, especially GPUs, which enable very fast calculations. This has encouraged engineers to explore ways to leverage this advantage in CFD, leading to the development of hybrid solvers that couple Eulerian and Lagrangian solvers. In this coupled approach, Eulerian solvers can be applied near the solid body to accurately and efficiently resolve the boundary layer region, while Lagrangian solvers preserve the vortex structures further from the body.
Building on this approach, this dissertation introduces a hybrid Eulerian-Lagrangian solver, named VPMFoam, developed to combine the strengths of both methods while minimizing their limitations. This is achieved by integrating OpenFOAM, a widely used open-source CFD software, with a Lagrangian VPM. The primary goal is to create an accurate tool focused on external aerodynamics that can efficiently handle cases with strong body-vortex interactions and multibody scenarios while maintaining a lower computational cost compared to pure Eulerian solvers. OpenFOAM was chosen primarily for its open-source flexibility and its extensive user base in academia and industry, offering broad access to this tool.
The solver's development focuses on a 2D version, with validation conducted through a step-by-step approach, starting with simple cases that exclude solid bodies. Once the successful coupling of the two solvers is verified, validation proceeds with cases involving solid bodies, such as flow around a cylinder. In these cases, the solver accurately predicts fluid flow and aerodynamic coefficients, showing strong agreement with established Eulerian solvers and effectively preserving the vorticity field in the wake. Further validations address dynamic mesh motions and multibody applications.
Following validation, the solver is applied to more realistic scenarios, including the static and dynamic stall of an airfoil and the simulation of hybrid Vertical Axis Wind Turbines using actuator models. A performance analysis of the code’s efficiency is also presented, highlighting the solver’s capability to conduct fast and accurate simulations.
By effectively combining the strengths of both Eulerian and Lagrangian approaches, VPMFoam addresses key challenges in aerodynamic analysis, particularly in cases with strong body-vortex interactions, and lays a strong foundation for further applications, including potential 3D extensions. This makes VPMFoam a valuable asset for applications requiring both high fidelity and computational efficiency.
The research began with a detailed literature review, leading to the selection of four promising hybrid turbulence models: Improved Delayed Detached Eddy Simulation (IDDES), Scale Adaptive Simulation (SAS), Partially Averaged Navier–Stokes (PANS), and Struct Epsilon (SE). These models were implemented and tested through numerical case setups to validate their performance against established reference data for crossflow over a circular cylinder at a Reynolds number (Re) of 3900.
A comparative analysis was conducted to assess the performance of the selected models. Based on this analysis, two models were shortlisted for further testing. These models were subjected to additional validation on a rigid body motion case to ensure their reliability and accuracy in FSI applications.
In this validation, the models were used to simulate flow over an elastically mounted rigid cylinder in crossflow to evaluate the frequency and displacement of its oscillation. They were tested at different velocities to determine the amplitude and frequency response. The SE model was observed to be more robust and efficient than IDDES.
In conclusion, the research provides validation, selection and comparison of different hybrid turbulence models for FSI applications. Recommendations for future research are also provided to further refine these modeling approaches. ...
The research began with a detailed literature review, leading to the selection of four promising hybrid turbulence models: Improved Delayed Detached Eddy Simulation (IDDES), Scale Adaptive Simulation (SAS), Partially Averaged Navier–Stokes (PANS), and Struct Epsilon (SE). These models were implemented and tested through numerical case setups to validate their performance against established reference data for crossflow over a circular cylinder at a Reynolds number (Re) of 3900.
A comparative analysis was conducted to assess the performance of the selected models. Based on this analysis, two models were shortlisted for further testing. These models were subjected to additional validation on a rigid body motion case to ensure their reliability and accuracy in FSI applications.
In this validation, the models were used to simulate flow over an elastically mounted rigid cylinder in crossflow to evaluate the frequency and displacement of its oscillation. They were tested at different velocities to determine the amplitude and frequency response. The SE model was observed to be more robust and efficient than IDDES.
In conclusion, the research provides validation, selection and comparison of different hybrid turbulence models for FSI applications. Recommendations for future research are also provided to further refine these modeling approaches.
The work performed in this thesis focuses on realizing these aeropropulsive trade-offs by optimizing the engine and the BWB wing simultaneously using selectively non-axisymmetric engine design variables, including design variables for wing shape and engine placement. To achieve this objective, a free-form deformation (FFD) based parameterization scheme is developed for non-axisymmetric engine parameterization along with design variables for modifying wing shape and relative engine placement. ADflow CFD solver is used for the aerodynamic discipline, and the PyCycle thermodynamic cycle library is used for the propulsion discipline. Coupled aeropropulsive optimizations are performed by extending the MACH-Aero framework using coupled derivatives in an Individual Discipline Feasible (IDF) architecture for gradient-based optimization using the SNOPT optimization algorithm.
A set of studies are performed to establish the robustness and effectiveness of the proposed FFD-based parameterization for engine optimization in isolation. Later, the engine is mounted onto the BWB in an over-the-wing configuration, and the effect of non-axisymmetric engine design is explored in conjunction with engine placement and wing shape modifications. Optimizing the engine location with axisymmetric nacelle and wing shape design variables reduces the wing drag by 11.5% and engine fuel consumption by 2.3% compared to the baseline engine location. Using non-axisymmetric nacelle design variables further drops the fuel consumption by 1.1%. A comparison of this optimized engine-airframe design with an optimized engine in isolation shows that placing the engine in an over-the-wing configuration with the BWB reduces the thrust-specific fuel consumption by 4.4%. Non-axisymmetric nacelle design also improves the quality of engine inflow by eliminating local super velocities at the inlet lip. This study shows the benefits of an OWN configuration for the BWB and quantifies the performance gains from optimizing the engine location with non-axisymmetric nacelles. ...
The work performed in this thesis focuses on realizing these aeropropulsive trade-offs by optimizing the engine and the BWB wing simultaneously using selectively non-axisymmetric engine design variables, including design variables for wing shape and engine placement. To achieve this objective, a free-form deformation (FFD) based parameterization scheme is developed for non-axisymmetric engine parameterization along with design variables for modifying wing shape and relative engine placement. ADflow CFD solver is used for the aerodynamic discipline, and the PyCycle thermodynamic cycle library is used for the propulsion discipline. Coupled aeropropulsive optimizations are performed by extending the MACH-Aero framework using coupled derivatives in an Individual Discipline Feasible (IDF) architecture for gradient-based optimization using the SNOPT optimization algorithm.
A set of studies are performed to establish the robustness and effectiveness of the proposed FFD-based parameterization for engine optimization in isolation. Later, the engine is mounted onto the BWB in an over-the-wing configuration, and the effect of non-axisymmetric engine design is explored in conjunction with engine placement and wing shape modifications. Optimizing the engine location with axisymmetric nacelle and wing shape design variables reduces the wing drag by 11.5% and engine fuel consumption by 2.3% compared to the baseline engine location. Using non-axisymmetric nacelle design variables further drops the fuel consumption by 1.1%. A comparison of this optimized engine-airframe design with an optimized engine in isolation shows that placing the engine in an over-the-wing configuration with the BWB reduces the thrust-specific fuel consumption by 4.4%. Non-axisymmetric nacelle design also improves the quality of engine inflow by eliminating local super velocities at the inlet lip. This study shows the benefits of an OWN configuration for the BWB and quantifies the performance gains from optimizing the engine location with non-axisymmetric nacelles.
To quantify the effects of GTRF, before this thesis, a numerical FSI workflow called NRG-FSIFOAM was developed by Nuclear Research Group (NRG). The fluid modelling consisted of a synthetic turbulence model (AniPFM) developed in OpenFOAM. The structural solution was obtained using a 3D Finite Element Method (FEM) solver implemented in deal.II, while the mapping and coupling between the two solvers was handled by preCICE.
In this context, the objective of the thesis is to propose a simplified and cost-effective structural solver, without compromising the accuracy of the methodology. To this end, an eigenmode-based Reduced-Order Model (ROM) of a 1D beam-element FEM formulation is proposed. To further improve the computational costs, by taking into account the 1D FEM formulation of the structural solver, novel mapping routines between the fluid and the structural grid are also proposed. To ensure a strong coupling between the two domains, an Aitken subiteration algorithm is used. What’s more, to simplify the architecture of the methodology, the new features are directly implemented in OpenFOAM. Thus, the newly proposed workflow is fully contained within OpenFOAM, eliminating the need to additionally use deal.II and preCICE. This newly proposed FSI methodology is called NRG-beamFoam.
The thesis first deals with the individual verification of the structural solver, the mapping routines, and the Aitken subiteration scheme. Subsequently, all of the elements are combined within FSI simulations for the same benchmark case that was used for the validation of NRG-FSIFOAM. It is found that for simulations where an Unsteady Reynolds-Averaged Navier Stokes (URANS) fluid model is used, NRG-beamFoam reduces the computational cost per FSI subiteration by 48% compared to its NRG-FSIFOAM predecessor, while obtaining a 0.5% relative difference in the frequency and the damping ratio characterizing the structural dynamic response. What’s more, using the ROM, the instantaneous deformations of a single rod to turbulent excitation by axial water flow appear to be accurately computed using a total number of degrees of freedom that is reduced by a factor of approximately 103 compared to the FEM solver of NRG-FSIFOAM. Further research is recommended to improve the stability of NRG-beamFoam when coupled with the AniPFM for simulation times in the order of seconds. Furthermore, future studies ought to explore the causes for the small amplitude differences observed between the outputs of the ROM and the FEM solver for FSI simulations.
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To quantify the effects of GTRF, before this thesis, a numerical FSI workflow called NRG-FSIFOAM was developed by Nuclear Research Group (NRG). The fluid modelling consisted of a synthetic turbulence model (AniPFM) developed in OpenFOAM. The structural solution was obtained using a 3D Finite Element Method (FEM) solver implemented in deal.II, while the mapping and coupling between the two solvers was handled by preCICE.
In this context, the objective of the thesis is to propose a simplified and cost-effective structural solver, without compromising the accuracy of the methodology. To this end, an eigenmode-based Reduced-Order Model (ROM) of a 1D beam-element FEM formulation is proposed. To further improve the computational costs, by taking into account the 1D FEM formulation of the structural solver, novel mapping routines between the fluid and the structural grid are also proposed. To ensure a strong coupling between the two domains, an Aitken subiteration algorithm is used. What’s more, to simplify the architecture of the methodology, the new features are directly implemented in OpenFOAM. Thus, the newly proposed workflow is fully contained within OpenFOAM, eliminating the need to additionally use deal.II and preCICE. This newly proposed FSI methodology is called NRG-beamFoam.
The thesis first deals with the individual verification of the structural solver, the mapping routines, and the Aitken subiteration scheme. Subsequently, all of the elements are combined within FSI simulations for the same benchmark case that was used for the validation of NRG-FSIFOAM. It is found that for simulations where an Unsteady Reynolds-Averaged Navier Stokes (URANS) fluid model is used, NRG-beamFoam reduces the computational cost per FSI subiteration by 48% compared to its NRG-FSIFOAM predecessor, while obtaining a 0.5% relative difference in the frequency and the damping ratio characterizing the structural dynamic response. What’s more, using the ROM, the instantaneous deformations of a single rod to turbulent excitation by axial water flow appear to be accurately computed using a total number of degrees of freedom that is reduced by a factor of approximately 103 compared to the FEM solver of NRG-FSIFOAM. Further research is recommended to improve the stability of NRG-beamFoam when coupled with the AniPFM for simulation times in the order of seconds. Furthermore, future studies ought to explore the causes for the small amplitude differences observed between the outputs of the ROM and the FEM solver for FSI simulations.
The LS-DYNA CESE-Chemistry solver, employing an 8-step finite-rate reaction mechanism, was used to model the detonation blast wave. The structural response is coupled via Immersed Boundary Fluid-Structure Interaction (FSI). The detonation model was validated with literature results from a hydrogen-air detonation experiment, while the structural model was validated with blast-loaded circular plates, both showing good agreement.
Results show that the blast wave propagates in the tail cone with multiple reflections, producing 2–3 distinct pressure peaks. While the first pulse is the primary shock-loading in most locations, the second pulse is more significant at the bulkhead center, amplified by shock convergence effects.
The structural response occurs in four distinct phases: initial deformation, flexural wave propagation, secondary pulse loading, and snapback instability. Large deformations and high plasticity were observed at the bulkhead center and edge, identifying them as critical zones for damage. Parametric studies reveal that deflections increase with ignition distance and decrease with bulkhead thickness or radius. A linear relationship was found between a dimensionless impulse parameter and permanent deformations or plastic strains across varying bulkhead configurations.
The insights gained provide a foundation for designing safer hydrogen-powered aircraft and addressing regulatory gaps in explosion safety. Recommendations for future work include extending the model to 3D geometries, incorporating material failure models, and conducting tailored validation experiments.
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The LS-DYNA CESE-Chemistry solver, employing an 8-step finite-rate reaction mechanism, was used to model the detonation blast wave. The structural response is coupled via Immersed Boundary Fluid-Structure Interaction (FSI). The detonation model was validated with literature results from a hydrogen-air detonation experiment, while the structural model was validated with blast-loaded circular plates, both showing good agreement.
Results show that the blast wave propagates in the tail cone with multiple reflections, producing 2–3 distinct pressure peaks. While the first pulse is the primary shock-loading in most locations, the second pulse is more significant at the bulkhead center, amplified by shock convergence effects.
The structural response occurs in four distinct phases: initial deformation, flexural wave propagation, secondary pulse loading, and snapback instability. Large deformations and high plasticity were observed at the bulkhead center and edge, identifying them as critical zones for damage. Parametric studies reveal that deflections increase with ignition distance and decrease with bulkhead thickness or radius. A linear relationship was found between a dimensionless impulse parameter and permanent deformations or plastic strains across varying bulkhead configurations.
The insights gained provide a foundation for designing safer hydrogen-powered aircraft and addressing regulatory gaps in explosion safety. Recommendations for future work include extending the model to 3D geometries, incorporating material failure models, and conducting tailored validation experiments.
Generally, at ASML, experimental methods or numerical methods like Direct Numerical Simulation(DNS) or Large Eddy Simulation(LES) are used to compute turbulent fluctuations. However, these are time consuming, complex and computationally expensive. So, in this thesis a Reynolds Averaged Navier Stokes(RANS) based stochastic method has been developed from existing methods to generate turbulent velocity fluctuations for ASML applications. This method can account for multiple turbulence characteristics like spatial correlation, velocity-time correlation and anisotropy that are essential for computing FIV. In addition, a pressure Poisson equation solver has been developed to compute turbulent pressure fluctuations from velocity fluctuations. Further, the developed method has been validated for two academic test-cases, homogeneous isotropic turbulence(experiment) and turbulent channel flow(DNS). The method was found to generate turbulent fluctuations adhering to the energy spectrum imposed; the exponential time correlation applied and account for anisotropy based on the Reynolds Stress Tensor given as input. Finally, the method has been applied to a test-case, sharp-bend and compared against LES results. It was found that the method agrees well to the energy spectrum imposed, however it deviates from the LES energy spectrum. Nonetheless, the capability of turbulent fluctuation generation from RANS at lesser computational effort than LES/DNS has been demonstrated, even though there can be improvements made to the energy spectrum given as input to the developed method. ...
Generally, at ASML, experimental methods or numerical methods like Direct Numerical Simulation(DNS) or Large Eddy Simulation(LES) are used to compute turbulent fluctuations. However, these are time consuming, complex and computationally expensive. So, in this thesis a Reynolds Averaged Navier Stokes(RANS) based stochastic method has been developed from existing methods to generate turbulent velocity fluctuations for ASML applications. This method can account for multiple turbulence characteristics like spatial correlation, velocity-time correlation and anisotropy that are essential for computing FIV. In addition, a pressure Poisson equation solver has been developed to compute turbulent pressure fluctuations from velocity fluctuations. Further, the developed method has been validated for two academic test-cases, homogeneous isotropic turbulence(experiment) and turbulent channel flow(DNS). The method was found to generate turbulent fluctuations adhering to the energy spectrum imposed; the exponential time correlation applied and account for anisotropy based on the Reynolds Stress Tensor given as input. Finally, the method has been applied to a test-case, sharp-bend and compared against LES results. It was found that the method agrees well to the energy spectrum imposed, however it deviates from the LES energy spectrum. Nonetheless, the capability of turbulent fluctuation generation from RANS at lesser computational effort than LES/DNS has been demonstrated, even though there can be improvements made to the energy spectrum given as input to the developed method.