Today, we see a renewed interest in aircraft with multiple propellers. To support conceptual design of these vehicles, one of the major needs is a fast and accurate method for estimating wing aerodynamic characteristics in the presence of multiple propellers. For the method to be effective, it must be easy to use, have rapid turnaround time and should be able to capture major wing–propeller interaction effects with sufficient accuracy. This research is primarily motivated by the need to assess the effectiveness of computational fluid dynamics (CFD) for simulating aerodynamic characteristics of wings with multiple propellers. The scope of the present research is limited to investigating the interaction between a single tractor propeller and a wing. This research aims to compare computational results from a Reynolds-Averaged Navier-Stokes (RANS) method, StarCCM+, and a vortex lattice method (VLM), VSP Aero. Two configurations that are analysed are 1) WIPP Configuration (Workshop for Integrated Propeller Prediction) 2) APROPOS Configuration. For WIPP, computational results are compared with measured lift and drag data for several angles of attack and Mach numbers. StarCCM+ results of wake flow field are compared with WIPP's wake survey data. For APROPOS, computed data for lift-to-drag ratio of the wing are compared with test data for multiple vertical and spanwise locations of the propeller. The results of the simulations are used to assess the effectiveness of the two CFD methods used in this research. / Master of Science / Today, we see a renewed interest in aircraft with multiple propellers due to an increasing demand for vehicles which fly short distances at low altitudes, be it flying taxis, delivery drones or small passenger aircrafts. To support conceptual design of vehicles, one of the major needs is a fast and accurate method for estimating wing aerodynamic characteristics in the presence of multiple propellers. For the method to be effective, it must be easy to use, have rapid turnaround time and should be able to capture major wing–propeller inter- action effects with sufficient accuracy. This research is primarily motivated by the need to assess the effectiveness of computational fluid dynamics (CFD) for simulating aerodynamic characteristics of wings with multiple propellers. Then only can we can take full advantage of the capabilities of the CFD methods and support design of emerging propeller driven air vehicles with an appropriate level of confidence. This research aims to compare high level methods with increasingly complex geometries and realistic models of physics like Reynolds Averaged Navier Stokes (RANS) and low level methods that rely on simplified geometry and simplified physics models like Vortex Lattice Methods (VLM). We will analyse multiple configurations and validate them against experi- mental data and thus assessing the effectiveness of the CFD models. This research investigates two configurations, 1) WIPP configuration 2) APROPOS configuration, for which experimental data is available. The results of the simulations are used to assess the effectiveness of the two CFD methods used in this research.

An important aspect in the process of architectural design is the testing of solution alternatives in order to evaluate them on their appropriateness within the context of the design problem. Computational Fluid Dynamics (CFD) analysis is one of the approaches that have gained popularity in the testing of architectural design solutions especially for purposes of evaluating the performance of natural ventilation strategies in buildings. Natural ventilation strategies can reduce the energy consumption in buildings while ensuring the good health and wellbeing of the occupants. In order for natural ventilation strategies to perform as intended, a number of factors interact and these factors must be carefully analysed. CFD simulations provide an affordable platform for such analyses to be undertaken. Traditionally, these simulations have largely followed the direction of Best Practice Guidelines (BPGs) for quality control. These guidelines are built around certain simplifications due to the high computational cost of CFD modelling. However, while the computational cost has increasingly fallen and is predicted to continue to drop, the BPGs have largely remained without significant updates. The need to develop a CFD simulation framework that leverages the contemporary and anticipates the future computational cost and capacity can, therefore, not be overemphasised. When conducting CFD simulations during the process of architectural design, the variability of the wind flow field including the wind direction and its velocity constitute an important input parameter. Presently, however, in many simulations, the wind direction is largely used in a steady state manner. It is assumed that the direction of flow downwind of a meteorological station remains constant. This assumption may potentially compromise the integrity of CFD modelling as in reality, the wind flow field is bound to be dynamic from place to place. In order to improve the accuracy of the CFD simulations for architectural design, it is therefore necessary to adequately account for this variability. This study was a two-pronged investigation with the ultimate objective of improving the accuracy of the CFD simulations that are used in the architectural design process, particularly for the design and analysis of natural ventilation strategies. Firstly, a framework for integrated meso-scale and building scale CFD simulations was developed. Secondly, the newly developed framework was then implemented by deploying it to study the variability of the wind flow field between a reference meteorological station, the Virginia Tech Airport, and a selected localized building scale site on the Virginia Tech campus. The findings confirmed that the wind flow field varies from place to place and showed that the newly developed framework was able to capture this variation, ultimately, generating a wind flow field characterization representative of the conditions prevalent at the localized building site. This framework can be particularly useful when undertaking de-coupled CFD simulations to design and analyse natural ventilation strategies in the building design process. / Doctor of Philosophy / The use of natural ventilation strategies in building design has been identified as one viable pathway toward minimizing energy consumption in buildings. Natural ventilation can also reduce the prevalence of the Sick Building Syndrome (SBS) and enhance the productivity of building occupants. This research study sought to develop a framework that can improve the usage of Computational Fluid Dynamics (CFD) analyses in the architectural design process for purposes of enhancing the efficiency of natural ventilation strategies in buildings. CFD is a branch of computational physics that studies the behaviour of fluids as they move from one point to another. The usage of CFD analyses in architectural design requires the input of wind environment data such as direction and velocity. Presently, this data is obtained from a weather station and there is an assumption that this data remains the same even for a building site located at a considerable distance away from the weather station. This potentially compromises the accuracy of the CFD analyses as studies have shown that due to a number of factors such the urban built form, vegetation, terrain and others, the wind environment is bound to vary from one point to another. This study sought to develop a framework that quantifies this variation and provides a way for translating the wind data obtained from a weather station to data that more accurately characterizes a local building site. With this accurate site wind data, the CFD analyses can then provide more meaningful insights into the use of natural ventilation in the process of architectural design. This newly developed framework was deployed on a study site at Virginia Tech. The findings showed that the framework was able to demonstrate that the wind flow field varies from one place to another and it also provided a way to capture this variation, ultimately, generating a wind flow field characterization that was more representative of the local conditions.

Permeability is an important property of a porous medium and it controls the flow of fluid through the medium. Particle characteristics are known to affect the value of the permeability. However, experimental investigation of the effects of these particle characteristics on the value of permeability is time-consuming while analytical predictions have been reported to overestimate it leading to inefficient design. To overcome these challenges, there is the need for the development of new models that can predict permeability based on input variables and process conditions. In this research, data from experiments, Computational Fluid Dynamics (CFD) and literature were employed to develop new models using Multivariate Regression (MVR) and Artificial Neural Networks (ANNs). Experimental measurements of permeability were performed using high and low shear separation processes. Particles of talc, calcium carbonate and titanium dioxide (P25) were used in order to study porous media with different particle characteristics and feed concentrations. The effects of particle characteristics and initial stages of filtration as well as the reliability of filtration techniques (constant pressure filtration, CPF and constant rate filtration, CRF) were investigated. CFD simulations were also performed of porous media for different particle characteristics to generate additional data. The regression and ANN models also included permeability data taken from reliable literature sources. Particle cluster formation was only found in P25 leading to an increase of permeability especially in sedimentation. The constant rate filtration technique was found more suitable for permeability measurement than constant pressure. Analyses of data from the experiments, CFD and correlation showed that Sauter mean diameter (ranging from 0.2 to 168 μm), the fines ratio (x50/x10), particle shape (following Heywood s approach), and voidage of the porous medium (ranging from 98.5 to 37.2%) were the significant parameters for permeability prediction. Using these four parameters as inputs, performance of models based on linear and nonlinear MVR as well as ANN were investigated together with the existing analytical models (Kozeny-Carman, K-C and Happel-Brenner, H-B). The coefficient of correlation (R2), root mean square error (RMSE) and average absolute error (AAE) were used as performance criteria for the models. The K-C and H-B are two-variable models (Sauter mean diameter and voidage) and two variables ANN and MVR showed better predictive performance. Furthermore, four-variable (Sauter mean diameter, the x50/x10, particle shape, and voidage) models developed from the MVR and ANN exhibit excellent performance. The AAE was found with K-C and H-B models to be 35 and 40%, respectively while the results of using ANN2 model reduced the AAE to 14%. The ANN4 model further decreased the AAE to approximately 9% compared to the measured results. The main reason for this reduced error was the addition of a shape coefficient and particle spread (fine ratio) in the ANN4 model. These two parameters are absent in the analytical relations, such as K-C and H-B models. Furthermore, it was found that using the ANN4 (4-5-1) model led to increase in the R2 value from 0.90 to 0.99 and significant decrease in the RMSE value from 0.121 to 0.054. Finally, the investigations and findings of this work demonstrate that relationships between permeability and the particle characteristics of the porous medium are highly nonlinear and complex. The new models possess the capability to predict the permeability of porous media more accurately owing to the incorporation of additional particle characteristics that are missing in the existing models.

<p>This licentiate thesis describes development of modellingtools, experimental physical modelling and numerical modellingto simulate real combustion processes for advanced industrialutility boiler before and after retrofit.</p><p>The work presents extended study about formation,destruction and control of pollutants, especially NOx, whichoccur during combustion process.</p><p>The main aim of this work is to improve mixing process incombustion chamber. To do this, the optimization of placementand direction of additional air and fuel nozzles, the physicalmodelling technique is used. By using that method, it ispossible to obtain qualitative information about processes,which occur in the real boiler. The numerical simulationsverify the results from physical modelling, because duringmathematical modelling quantitative informations about flow andmixing patterns, temperature field, species concentration areobtained.</p><p>Two 3D cases, before and after retrofit, of pulverized fuelfired boiler at 125 MW output thermal power are simulated. Theunstructured mesh technique is also used to discretize theboiler. The number of grid was 427 656 before retrofit and 513362 after retrofit. The comparisons of results of numericalsimulation before and after retrofit are presented. The resultsfrom physical modelling and numerical simulation are alsoshown.</p><p>Results present that nozzles of additional air and fuel givea considerably better mixing process, uniform temperature fieldand CO2 mass fraction. The whole combustion chamber worksalmost as a "well stirred reactor", while upper part of boilerworks as a "plug flow reactor".</p><p>Differences between from measured of temperatures andpredicted temperatures are not too big, the maximum differenceis about 100 K. It seems, that calculated temperatures showgood agreement with measurement data.</p><p>The results illuminate the potential of physical andnumerical modelling methods as promising tools to deal with thecomplicated combustion processes, even for practicalapplication in the industry.</p><p><b>Keywords:</b>air staging, fuel staging, boiler, furnace,computational fluid dynamics, numerical simulation, pollutants,physical modeling, pulverized fuel combustion.</p>

In the process of engine design, it is important for the engine designer to predict the accurate component temperatures. Controlling the temperature of engine components requires a better understanding of the coolant behaviour in the coolant jacket of an engine which is critical to internal combustion engine design, The studies reported in the literature emphasize the influence of the cooling system on other engine operation such as exhaust emission, fuel consumption and engine wear. In this context, much work has been done with the purpose of improving the coolant jacket design and components of the cooling system to achieve higher performance. (Some of these studies) Previous researches have shown the possibility of achieving higher engine efficiency and performance with higher coolant temperature. This project aims at understanding the coolant flow behaviour in the coolant jackets of a diesel engine and investigating the possibility of running the engine at higher coolant temperatures by predicting the temperature distribution of the structure which is required for the assessment of the durability ofthe engine components. In this thesis, CFD (Computational Fluid Dynamics) and FE (Finite Element) techniques are used to study coolant flow in the coolant jackets and to predict the temperature distribution within the engine structure respectively. The objectives are to develop an FE model of the engine structure for thermal analyses and a CFD model of the fluid domain for the coolant flow CFD analyses. A number of case studies are carried out with the purpose of determining the most suitable technique for accurate temperature prediction. The methodology of manual coupling approach between CFD and FE analyses, which is more widely used in industry, and conjugate approach are demonstrated. Using these approaches, thermal analysis of the engine is conducted with the purpose of identifying the thermally critical locations throughout the engine. Furthermore, the influences of higher coolant temperature on these thermally critical regions of the engine are highlighted by carrying out four case studies with coolant inlet temperatures of 110°C, !ISOC, 117.5"C and !20°C. The temperature rise at the particular points around thermally critical regions is found to be in the range of 3-9 degrees at the higher coolant temperatures. This slight increase in temperature of critical locations may affect the durability of the structure. However, without carrying out the structural analyses it is not possible to comment on the durability of the engine structure. The effects of surface roughness and viscosity on heat transfer rate are also investigated and shown to be insignificant.

Multiphase flows are of great interest to a large variety of industries because flows of two or more immiscible liquids are encountered in a diverse range of processes and equipment. However, the advent of high viscosity oil requires more investigations to enhance good design of transportation system and forestall its inherent production difficulties. Experimental and numerical studies were conducted on water-sand, oil-water and oilwater- sand respectively in 1-in ID 5m long horizontal pipe. The densities of CYL680 and CYL1000 oils employed are 917 and 916.2kg/m3 while their viscosities are 1.830 and 3.149Pa.s @ 25oC respectively. The solid-phase concentration ranged from 2.15e-04 to 10%v/v with mean diameter of 150micron and material density of 2650kg/m3. Experimentally, the observed flow patterns are Water Assist Annular (WA-ANN), Dispersed Oil in Water (DOW/OF), Oil Plug in Water (OPW/OF) with oil film on the wall and Water Plug in Oil (WPO). These configurations were obtained through visualisation, trend and the probability density function (PDF) of pressure signals along with the statistical moments. Injection of water to assist high viscosity oil transport reduced the pressure gradient by an order of magnitude. No significant differences were found between the gradients of oil-water and oil-water-sand, however, increase in sand concentration led to increase in the pressure losses in oil-water-sand flow. Numerically, Water Assist Annular (WA-ANN), Dispersed Oil in Water (DOW/OF), Oil Plug in Water (OPW/OF) with oil film on the wall, and Water Plug in Oil (WPO) flow pattern were successfully obtained by imposing a concentric inlet condition at the inlet of the horizontal pipe coupled with a newly developed turbulent kinetic energy budget equation coded as user defined function which was hooked up to the turbulence models. These modifications aided satisfactory predictions.

This thesis is based on the PhD work of investigating the Friction Stir Welding process (FSW) with numerical and Artificial Neural Network (ANN) modelling methods. FSW was developed at TWI in 1991. As a relatively new technology it has great advantages in welding aluminium alloys which are difficult to weld with traditional welding processes. The aim of this thesis was the development of new modelling techniques to predict the thermal and deformation behaviour. To achieve this aim, a group of Gleeble experiments was conducted on 6082 and 7449 aluminium alloys, to investigate the material constitutive behaviour under high strainrate, near solidus conditions, which are similar to what the material experiences during the FSW process. By numerically processing the experimental data, new material constitutive constants were found for both alloys and used for the subsequent FSW modelling work. Importantly no significant softening was observed prior to the solidus temperature. One of the main problems with numerical modelling is determining the values of adjustable parameters in the model. Two common adjustable parameters are the heat input and the coefficients that describe the heat loss to the backing bar. To predict these coefficients more efficiently a hybrid model was created which involved linking a conventional numerical model to an ANN model. The ANN was trained using data from the numerical model. Then thermal profiles were abstracted (summarised) and used as inputs; and the adjustable parameters were used as outputs. The trained ANN could then use abstracted thermal profiles from welding experiments to predict the adjustable parameters in the model. The first stage involved developing a simplified FE thermal model which represents a typical welding process. It was used to find the coefficients that describe the heat loss to the backing bar, and the amount of power applied in the model. Five different thermal boundary conditions were studied, including both convective and ones that included the backing bar with a contact gap conductance. Three approaches for abstracting the thermal curves and using as inputs to the ANN were compared. In the study, the characteristics of the ANN model, such as the ANN topology and gradient descent method, were evaluated for each boundary condition for understanding of their influences to the prediction. The outcomes of the study showed that the hybrid model technique was able to determine the adjustable parameters in the model effectively, although the accuracy depended on several factors. One of the most significant effects was the complexity of the boundary condition. While a single factor boundary condition (e.g. constant convective heat loss) could be predicted easily, the boundary condition with two factors proved more difficult. The method for inputting the data into the ANN had a significant effect on the hybrid model performance. A small number of inputs could be used for the single factor boundary condition, while two factors boundary conditions needed more inputs. The influences from the characteristics of the ANN model were smaller, but again thermal model with simpler boundary condition required a less complex ANN model to achieve an accurate prediction, while models with more complex boundary conditions would need a more sophisticated ANN model. In the next chapter, the hybrid method was applied to a FSW process model developed for the Flexi-stir FSW machine. This machine has been used to analyse the complex phase changes that occur during FSW with synchrotron radiation. This unique machine had a complex backing bar system involving heat transfer from the aluminium alloy workpiece to the copper and steel backing bars. A temperature dependent contact gap conductance which also depends on the material interface type was used. During the investigation, the ANN model topologies (i.e. GFF and MFF) were studied to find the most effective one. Different abstracting methods for the thermal curves were also compared to explore which factors (e.g. the peak temperature in the curve, cooling slope of a curve) were more important to be used as an input. According to close matching between the simulation and experimental thermal profiles, the hybrid model can predict both the power and thermal boundary condition between the workpiece and backing bar. The hybrid model was applied to six different travel speeds, hence six sets of heat input and boundary condition factors were found. A universal set was calculated from the six outcomes and a link was discovered between the accuracy of the temperature predictions and the plunge depth for the welds. Finally a model with a slip contact condition between the tool and workpiece was used to investigate how the material flow behaviour was affected by the slip boundary condition. This work involved aluminium alloys 6082-T6 and 7449-T7, which have very different mechanical properties. The application of slip boundary condition was found to significantly reduce the strain-rate, compared to a stick condition. The slip condition was applied to the Flexi-stir FSW experiments, and the results indicated that a larger deformation region may form with the slip boundary condition. The thesis successfully demonstrates a new methodology for determining the adjustable parameters in a process model; improved understanding of the effect of slip boundary conditions on the flow behaviour during FSW and insight in to the behaviour of aluminium alloys at temperatures approaching the solidus and high strain-rates.

Together with the world economic growth is the increasing of energy generation demand. However, the upgrade of world power production capability could affect the environment negatively. Even the clean and renewable sources, such as hydroelectricity and wind powers have socio-economic and environmental disadvantages. For example, the required flooded area for a hydro power plant construction could devastate entire forests, and the installation of a wind farm power plant could affect migratory rotes of birds and generate high levels of noise. Hence, for the balancing of advantages and disadvantages of each power generation source, it is necessary to diversify, which requires investments in new power sources. In this context, the energy generation in the ocean is highlighted. The first point concerning the ocean energy is that there is no need of population removal from the installation area, such as the onshore based methods and the second point is that most of the population is concentrated in coastal areas. Therefore the production occurs near to the demand, decreasing the costs with energy distribution. The two main methodologies for harassing energy from oceans are based on gravity waves and in tides. And since the tidal cycles are governed mainly by the gravitational interaction between oceans, Moon and Sun, they are easily predictable, which increases the reliability of such systems. These works explores methodologies to analyse the power generation from a single axial tidal current turbine through a Steady State RANS methodology. Are discussed the effects of flow directionality, inlet velocity profile and turbulence levels and the results are compared with an experimental scheme. It is proposed an alternative methodology for free surface modelling in the CFD analysis. The usual methodology, VOF, it is based on a homogeneous, biphasic approach which requires an additional mesh refinement and is computationally expensive. This new methodology introduces an elastic wall approach in the free surface region in which the stiffness is calculated to provide the same restoring effect as gravity. In general, the results for open domain matched with the experimental results, validating the numerical model and the confined domain has shown a higher power and thrust coefficients if compared with the open domain, which is in accordance with the actuator disk theory approach. The elastic free surface presented convergence problems related to high Froude numbers and therefore to high deformations. However, a simulation with 10% of the original inlet velocity was performed, achieving reasonable results for both power and thrust coefficients evaluation. / O crescimento econômico mundial e o aumento na demanda pela geração de energia andam juntos. No entanto, uma maior capacidade de produção de energia poderia afetar negativamente o meio ambiente. Mesmo as fontes limpas e renováveis, como a hidrelétrica e a eólica acarretam em impactos socioeconômicos e ambientais. Por exemplo, a construção de uma usina hidrelétrica demanda uma imensa área alagada que pode devastar florestas inteiras e a instalação de uma usina eólica pode afetar a migração de certas espécies de pássaros e produzir altos níveis de barulho. Portanto, para equilibrar as vantagens e desvantagens devidas a cada meio de produção de energia, é necessária a diversificação, que demanda de investimentos em novas fontes. Neste contexto, a geração de energia nos oceanos é destacada. O primeiro ponto a respeito desta fonte é de que não há a necessidade de remoção da população na área de instalação, tal como os métodos de geração dentro do continente. O segundo principal ponto é a respeito da distribuição de energia. A maior parte da população mundial vive em regiões costeiras, diminuindo, portanto, a distância entre a produção e demanda, reduzindo assim, seus custos. As duas principais metodologias para se explorar a energia proveniente dos oceanos são: Energia de Ondas e Energia de Marés. E considerando que os ciclos de mare são governados principalmente pela interação gravitacional entre os oceanos, lua e sol, eles são facilmente previsíveis, o que aumenta a confiabilidade dos sistemas de geração de energia baseados em marés. Este trabalho explora as metodologias para analisar a geração de energia a partir de uma única turbina axial de corrente de maré através de uma metodologia baseada nas equações de Navier-Stokes com a média de Reynolds, analisadas em regime permanente. São discutidos efeitos da direção do escoamento, perfil de velocidades na entrada e nos níveis de turbulência. Os resultados são comparados com experimentos. É proposta uma metodologia alternativa para a modelagem da superfície livre com CFD uma vez que a metodologia atual é baseada em um escoamento bifásico que demanda de um refinamento adicional da malha e é computacionalmente caro. A nova metodologia usa uma parede elástica na região da superfície livre com a rigidez ajustada para se obter o mesmo efeito de restauração que a gravidade. De maneira geral, os resultados para o domínio aberto se aproximaram dos resultados experimentais, validando o modelo numérico e além disso, o modelo considerando confinamento da turbine mostrou maiores valores para os coeficientes de potência e empuxo, estando portanto, de acordo com a teoria do disco atuador. O modelo com a superfície livre elástica apresentou problemas de convergência, relacionados com números de Froude elevados, uma vez que isto se relaciona com maiores deformações na região da superfície livre. Uma simulação com 10% da velocidade original foi realizada, obtendo-se resultados coerentes para ambos coeficientes de potência e empuxo.

Tidal energy has the potential to make a valuable contribution to meeting future global energy demands. Converting the energy of tidal streams into useful electricity can be achieved with use of tidal-stream turbines, such as the Momentum-Reversal and Lift (MRL) device. This turbine utilises a blade motion where each blade rotates continuously through 180° about its own axis for every 360° of turbine rotation. The aim of the design is to harness both useful lift and drag forces when rotating at relatively slow speeds. However, no detailed analysis of the time-varying fluid dynamic behaviour of the turbine has been undertaken before this study. The primary aim of this study has been to further understanding of the performance characteristics of the MRL turbine design, focusing on a laboratory- scale device. The study has analysed both the time-averaged and time-varying torque and power output, and the associated fluid-dynamic structure of flow through the turbine. A secondary aim was to generate data that can be used by other researchers who focus on the wake generation of the MRL tidal turbine. This study has used OpenFOAM to develop a time-dependent RANS CFD model and investigate the performance of the MRL turbine. To allow validation of the CFD model, experiments were firstly undertaken in order to measure the cycle-mean torque and power output of the turbine when operating in a laboratory flume. Measurements of the flow velocity at a number of upstream and downstream locations were also taken, in order to allow comparison with the CFD simulation results, where appropriate. Also, in order to allow validation of the CFD approach against time-varying data, the motion of the turbine blades was analysed. This allowed suitable experimental test cases to be identified from the literature and CFD simulation results have been compared to these. A detailed sensitivity analysis of the MRL turbine CFD model was carried out, followed by two-dimensional simulations of the turbine involving a single-blade and three-blades. Three-dimensional simulations were also undertaken, with results compared to the gathered experimental results. Finally, the effect of varying turbine solidity was investigated with the CFD model. Overall it was found that the CFD simulations successfully reproduce the rotational speed at which maximum torque and power are developed. However, the three-dimensional simulations significantly over-predict the magnitude of results in comparison to the gathered experimental results. Regardless, the two- and three-dimensional simulations have allowed detailed analysis of the flow behaviour and structures that are responsible for the development of blade forces and turbine torque.

Turbinas eólicas usualmente são agrupadas em grandes parques, reduzindo o custo de instalação, transmissão da energia e manutenção periódica. A superposição das esteiras sobre turbinas adjacentes normalmente reduz consideravelmente a capacidade total, objeto de estudo de Micrositing. Porém, por vezes o “efeito Venturi” ocasionado pelas turbinas à montante induz maior velocidade às turbinas adjacentes aumentando o potencial eólico disponível nas linhas consecutivas. De forma inovadora empregar o Design Constructal de Bejan, o modelo do disco atuador genérico e a Dinâmica dos Fluidos Computacional (CFD) para obter a melhor disposição geométrica das turbinas em uma área plana e não rugosa, com foco à maior potência extraída por área de turbinas instaladas. Para tal, modelar e predizer o comportamento da esteira é fundamental, assim como conhecer os modelos de esteira e a aplicabilidade dos métodos empregados. O Design Constructal é a fonte dos parâmetros geométricos base das simulações: o espaçamento entre as turbinas e as razões de diâmetros. Após 64 simulações semi-iterativas e mais de 60 iterativas verifica-se que o maior ganho em potência disponível por área é de 7,37% para a configuração V = 7m/s, S = 3D, d/D = 0.5, L = 3D e 8,48% para a configuração V = 11m/s, S = 3D; d/D = 0.25 & 0.5, L= 0.75D, valor relativo à execução de somente um diâmetro de 100 metros. / Usually wind turbines are grouped in large parks, reducing the cost of installation, energy transmission and periodic maintenance. But the overlapping of the aerodynamical wakes on adjacent turbines reduces the total capacity, Micrositing study. However, the "Venturi effect" caused by the turbines upstream sometimes increases the speed to the adjacent turbines increasing the wind potential available in straight lines. Innovatively employing the Design Constructal Bejan, the model of the actuator disc and Computational Fluid Dynamics (CFD) to search the best geometrical layout of the turbines on a roughless and flat area, focus on higher power extracted by area. To do this, model and predict the wake of behavior is fundamental, as well as know the aerodynamical wakes models and the applicability of the methods employed. The Design Constructal is the source of the simulation’s parameters: spacing between the turbines and the diameter’s ratio. After concluded 64 semi-iterative and iterative simulations, and more than 60 verifies, the best gain in available power per area is 7.37% for the configuration V = 7 m/s; S = 3d; d/D = 0.5; L = 3D. And the gain of 8.48% for the configuration V = 11m/s, s = 3D; d/D = 0.25 & 0.50; L = 0.75D, comparing to the implementation of just 100 meters diameter.