The context of this thesis is the numerical simulation of turbulent flows at moderate Reynolds numbers and the improvement of the capabilities of an in-house 3D unsteady and incompressible flow solver called SFELES to simulate such flows.<p>In addition to this abstract, this thesis includes five other chapters.<p><p>The second chapter of this thesis presents the numerical methods implemented in the two CFD solvers used as part of this work, namely SFELES and PHASTA.<p><p>The third chapter concentrates on the implementation of a new library called FlexMG. This library allows the use of various types of iterative solvers preconditioned by algebraic multigrid methods, which require much less memory to solve linear systems than a direct sparse LU solver available in SFELES. Multigrid is an iterative procedure that relies on a series of increasingly coarser approximations of the original 'fine' problem. The underlying concept is the following: low wavenumber errors on fine grids become high wavenumber errors on coarser levels, which can be effectively removed by applying fixed-point methods on coarser levels.<p>Two families of algebraic multigrid preconditioners have been implemented in FlexMG, namely smooth aggregation-type and non-nested finite element-type. Unlike pure gridless multigrid, both of these families use the information contained in the initial fine mesh. A hierarchy of coarse meshes is also needed for the non-nested finite element-type multigrid so that our approaches can be considered as hybrid. Our aggregation-type multigrid is smoothed with either a constant or a linear least square fitting function, whereas the non-nested finite element-type multigrid is already smooth by construction. All these multigrid preconditioners are tested as stand-alone solvers or coupled with a GMRES (Generalized Minimal RESidual) method. After analyzing the accuracy of the solutions obtained with our solvers on a typical test case in fluid mechanics (unsteady flow past a circular cylinder at low Reynolds number), their performance in terms of convergence rate, computational speed and memory consumption is compared with the performance of a direct sparse LU solver as a reference. Finally, the importance of using smooth interpolation operators is also underlined in this work.<p><p>The fourth chapter is devoted to the study of subgrid scale models for the large eddy simulation (LES) of turbulent flows.<p>It is well known that turbulence features a cascade process by which kinetic energy is transferred from the large turbulent scales to the smaller ones. Below a certain size, the smallest structures are dissipated into heat because of the effect of the viscous term in the Navier-Stokes equations.<p>In the classical formulation of LES models, all the resolved scales are used to model the contribution of the unresolved scales. However, most of the energy exchanges between scales are local, which means that the energy of the unresolved scales derives mainly from the energy of the small resolved scales.<p>In this fourth chapter, constant-coefficient-based Smagorinsky and WALE models are considered under different formulations. This includes a classical version of both the Smagorinsky and WALE models and several scale-separation formulations, where the resolved velocity field is filtered in order to separate the small turbulent scales from the large ones. From this separation of turbulent scales, the strain rate tensor and/or the eddy viscosity of the subgrid scale model is computed from the small resolved scales only. One important advantage of these scale-separation models is that the dissipation they introduce through their subgrid scale stress tensor is better controlled compared to their classical version, where all the scales are taken into account without any filtering. More precisely, the filtering operator (based on a top hat filter in this work) allows the decomposition u' = u - ubar, where u is the resolved velocity field (large and small resolved scales), ubar is the filtered velocity field (large resolved scales) and u' is the small resolved scales field. <p>At last, two variational multiscale (VMS) methods are also considered.<p>The philosophy of the variational multiscale methods differs significantly from the philosophy of the scale-separation models. Concretely, the discrete Navier-Stokes equations have to be projected into two disjoint spaces so that a set of equations characterizes the evolution of the large resolved scales of the flow, whereas another set governs the small resolved scales. <p>Once the Navier-Stokes equations have been projected into these two spaces associated with the large and small scales respectively, the variational multiscale method consists in adding an eddy viscosity model to the small scales equations only, leaving the large scales equations unchanged. This projection is obvious in the case of a full spectral discretization of the Navier-Stokes equations, where the evolution of the large and small scales is governed by the equations associated with the low and high wavenumber modes respectively. This projection is more complex to achieve in the context of a finite element discretization. <p>For that purpose, two variational multiscale concepts are examined in this work.<p>The first projector is based on the construction of aggregates, whereas the second projector relies on the implementation of hierarchical linear basis functions.<p>In order to gain some experience in the field of LES modeling, some of the above-mentioned models were implemented first in another code called PHASTA and presented along with SFELES in the second chapter.<p>Finally, the relevance of our models is assessed with the large eddy simulation of a fully developed turbulent channel flow at a low Reynolds number under statistical equilibrium. In addition to the analysis of the mean eddy viscosity computed for all our LES models, comparisons in terms of shear stress, root mean square velocity fluctuation and mean velocity are performed with a fully resolved direct numerical simulation as a reference.<p><p>The fifth chapter of the thesis focuses on the numerical simulation of the 3D turbulent flow over a re-entry Apollo-type capsule at low speed with SFELES. The Reynolds number based on the heat shield is set to Re=10^4 and the angle of attack is set to 180º, that is the heat shield facing the free stream. Only the final stage of the flight is considered in this work, before the splashdown or the landing, so that the incompressibility hypothesis in SFELES is still valid.<p>Two LES models are considered in this chapter, namely a classical and a scale-separation version of the WALE model. Although the capsule geometry is axisymmetric, the flow field in its wake is not and induces unsteady forces and moments acting on the capsule. The characterization of the phenomena occurring in the wake of the capsule and the determination of their main frequencies are essential to ensure the static and dynamic stability during the final stage of the flight. <p>Visualizations by means of 3D isosurfaces and 2D slices of the Q-criterion and the vorticity field confirm the presence of a large meandering recirculation zone characterized by a low Strouhal number, that is St≈0.15.<p>Due to the detachment of the flow at the shoulder of the capsule, a resulting annular shear layer appears. This shear layer is then affected by some Kelvin-Helmholtz instabilities and ends up rolling up, leading to the formation of vortex rings characterized by a high frequency. This vortex shedding depends on the Reynolds number so that a Strouhal number St≈3 is detected at Re=10^4.<p>Finally, the analysis of the force and moment coefficients reveals the existence of a lateral force perpendicular to the streamwise direction in the case of the scale-separation WALE model, which suggests that the wake of the capsule may have some <p>preferential orientations during the vortex shedding. In the case of the classical version of the WALE model, no lateral force has been observed so far so that the mean flow is thought to be still axisymmetric after 100 units of non-dimensional physical time.<p><p>Finally, the last chapter of this work recalls the main conclusions drawn from the previous chapters. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

<p>Gaussian Process Regression (GPR) is a widely used surrogate model in efficient global optimization (EGO) due to its capability to provide uncertainty estimates in the prediction. The cost of creating a GPR model for large data sets is high. On the other hand, neural network (NN) models scale better compared to GPR as the number of samples increase. Unfortunately, the uncertainty estimates for NN prediction are not readily available. In this work, a scalable algorithm is developed for EGO using NN-based prediction and uncertainty (EGONN). Initially, two different NNs are created using two different data sets. The first NN models the output based on the input values in the first data set while the second NN models the prediction error of the first NN using the second data set. The next infill point is added to the first data set based on criteria like expected improvement or prediction uncertainty. EGONN is demonstrated on the optimization of the Forrester function and a constrained Branin function and is compared with EGO. The convergence criteria is based on the maximum number of infill points in both cases. The algorithm is able to reach the optimum point within the given budget. The EGONN is extended to handle constraints explicitly and is utilized for aerodynamic shape optimization of the RAE 2822 airfoil in transonic viscous flow at a free-stream Mach number of 0.734 and a Reynolds number of 6.5 million. The results obtained from EGONN are compared with the results from gradient-based optimization (GBO) using adjoints. The optimum shape obtained from EGONN is comparable to the shape obtained from GBO and is able to eliminate the shock. The drag coefficient is reduced from 200 drag counts to 114 and is close to 110 drag counts obtained from GBO. The EGONN is also extended to handle uncertainty quantification (uqEGONN) using prediction uncertainty as an infill method. The convergence criteria is based on the relative change of summary statistics such as mean and standard deviation of an uncertain quantity. The uqEGONN is tested on Ishigami function with an initial sample size of 100 samples and the algorithm terminates after 70 infill points. The statistics obtained from uqEGONN (using only 170 function evaluations) are close to the values obtained from directly evaluating the function one million times. uqEGONN is demonstrated on to quantifying the uncertainty in the airfoil performance due to geometric variations. The algorithm terminates within 100 computational fluid dynamics (CFD) analyses and the statistics obtained from the algorithm are close to the one obtained from 1000 direct CFD based evaluations.</p>

Due to the increase of rotor size in horizontal axis wind turbine (HAWT) during the past 25 years in order to achieve higher power output, all wind turbine components and blades in particular, have to withstand higher structural loads. This upscalingproblem could be solved by applying technologies capable of reducing aerodynamic loads the rotor has to withstand, either with passive or active control solutions. These control devices and techniques can reduce the fatigue load upon the blades up to 40% and therefore less maintenance is needed, resulting in an important money savings for the wind farm manager. This project consists in a study of load control techniques for offshore wind turbines from an aerodynamic and aeroelastic point ofview, with the aim to assess a cost effective, robust and reliable solution which could operate maintenance free in quite hostile environments. The first part of this study involves 2D and 3D aerodynamic and aeroelastic simulations to validate the computational model with experimental data and to analyze the interaction between the fluid and the structure. The second part of this study is an assessment of the unsteady aerodynamic loads produced by a wind gust over the blades and to verify how a trailing edge flap would influence the aerodynamic control parameters for the selected wind turbine blade. / På grund av ökningen av rotorstorleken hos horisontella vindturbiner (HAWT) under de senaste 25 åren, en design som har uppstod för att uppnå högre effekt, måste alla vindkraftkomponenter och blad stå emot högre strukturella belastningar. Detta uppskalningsproblem kan lösas genom att använda metoder som kan minska aerodynamiska belastningar som rotorn måste tåla, antingen med passiva eller aktiva styrlösningar. Dessa kontrollanordningar och tekniker kan minska utmattningsbelastningen på bladen med upp till 40 % och därför behövs mindre underhåll, vilket resulterar i viktiga besparingar för vindkraftsägaren. Detta projekt består av en studie av lastkontrolltekniker för havsbaserade vindkraftverk ur en aerodynamisk och aeroelastisk synvinkel, i syfte att bedöma en kostnadseffektiv, robust och pålitlig lösning som kan fungera underhållsfri i tuffa miljöer. Den första delen av denna studie involverar 2D- och 3D-aerodynamiska och aeroelastiska simuleringar för att validera beräkningsmodellen med experimentella data och för att analysera interaktionen mellan fluiden och strukturen. Den andra delen av denna studie är en bedömning av de ojämna aerodynamiska belastningarna som produceras av ett vindkast över bladen och för att verifiera hur en bakkantklaff skulle påverka de aerodynamiska styrparametrarna för det valda vindturbinbladet.

Η σύγχρονη επιστήμη της εξωτερικής βλητικής έχει εξελιχθεί ως εξειδικευμένος κλάδος της δυναμικής των στερεών σωμάτων, που κινούνται υπό την επίδραση της βαρύτητας και των αεροδυναμικών δυνάμεων και ροπών. Στην παρούσα διατριβή μελετάται η προσομοίωση του δυναμικού μοντέλου ατμοσφαιρικής τροχιάς των 6 βαθμών ελευθερίας (6-DOF), εφαρμόζεται για ακριβή πρόβλεψη τροχιών από διάφορες γωνίες βολής σε μικρά και σε μεγάλα βεληνεκή και γίνεται σύγκριση με το γραμμικό μοντέλο τροχιάς, για περιστρεφόμενα ή μη περιστρεφόμενα βλήματα και σφαίρες λαμβάνοντας υπόψη τον αριθμό Mach και τις μεταβολές της συνολικής γωνίας εκτροπής σε σχέση με τους μεταβλητούς και σταθερούς αεροδυναμικούς συντελεστές. Επίσης, μελετώνται τα δύο είδη ευστάθειας του βλήματος: η στατική ή γυροσκοπική ευστάθεια που αφορά τη στατική θέση ισορροπίας του βλήματος και η δυναμική ευστάθεια που αφορά την κινητική του κατάσταση. Η λύση της διαφορικής εξίσωσης για ολοκληρωμένη ή απλοποιημένη κίνηση περιστρεφόμενων αξονοσυμμετρικών βλημάτων, μπορεί να μας περιγράψει την ακρογωνιαία φύση της επικυκλικής κίνησης των βλημάτων. Τέλος, αναπτύσσεται νέα σχέση υπολογισμού της επίδρασης του φαινόμενου της αεροδυναμικής αναπήδησης της ταχύτητας για περιστρεφόμενα βλήματα τα οποία πυροδοτούνται οριζόντια από μεταβλητές γωνίες, μέσα από ιπτάμενο όχημα (ελικόπτερο, πολεμικό αεροπλάνο). / On the battlefield, it is well known that the target effects using artillery systems diminish exponentially with the number of rounds fired at a particular target. To maximize target effects, rounds must be designed to hit a target with a minimum number of rounds that impact the target in rapid succession. The modern science of the exterior ballistics has evolved as a specialized branch of the dynamics of rigid bodies, moving under the influence of gravitational and aerodynamic forces and moments. The six degrees of freedom (6-DOF) simulation flight dynamics model is applied for the accurate prediction of short and long-range trajectories of high and low fin spin-stabilized projectiles and small bullets. Variable coefficients of aerodynamic forces, moments and Magnus effects are taken into account depending on Mach number and total angle of attack variations. The above analysis is compared to the modified linear modified simulation model for rapid trajectory predictions and high accuracy impact point computations for constant and variable aerodynamic coefficients is also applied for the accurate prediction of short and long range trajectories. The computational results of the proposed synthesized analysis give satisfactory agreement with other technical data and recognized exterior atmospheric projectile flight investigations. The variable modified atmospheric flight model can be further coupled to a suitable trajectory tracking control system for current and future control actions applied to projectiles for minimizing the estimated error to target impact area. Epicyclic motion and gyroscopic stability analysis are also examined for spinning and non-spinning projectiles. A new engineering correlation is proposed for the flat-fire disturbance due to aerodynamic jump performance firing at different angles which relative to the helicopter’s flight path motion. The computational results of the generalized aerodynamic jump formula are verified compared to McCoy’s recognized simulation modelling.

No description available.

<div> This thesis proposes an artificial neural network (NN) model to predict fuel consumption in heavy vehicles. The model uses predictors derived from vehicle speed, mass, and road grade. These variables are readily available from telematics devices that are becoming an integral part of connected vehicles. The model predictors are aggregated over a fixed distance traveled (i.e., window) instead of fixed time interval. It was found that 1km windows is most appropriate for the vocations studied in this thesis. Two vocations were studied, refuse and delivery trucks.</div><div><br></div><div> The proposed NN model was compared to two traditional models. The first is a parametric model similar to one found in the literature. The second is a linear regression model that uses the same features developed for the NN model.</div><div><br></div><div> The confidence level of the models using these three methods were calculated in order to evaluate the models variances. It was found that the NN models produce lower point-wise error. However, the stability of the models are not as high as regression models. In order to improve the variance of the NN models, an ensemble based on the average of 5-fold models was created. </div><div><br></div><div> Finally, the confidence level of each model is analyzed in order to understand how much error is expected from each model. The mean training error was used to correct the ensemble predictions for five K-Fold models. The ensemble K-fold model predictions are more reliable than the single NN and has lower confidence interval than both the parametric and regression models.</div>