This report is the documentation of a master’s thesis which was conducted at Scania CV AB in Södertälje. In this study, the benefits, challenges and conditions of using parametric CAD-models for aiding CFD-simulations and performance-optimization in the product development within internal combustion engines have been assessed. The goal of the thesis included developing and proposing a methodology for design engineers at Scania which will aid them in creating parametric CAD-models which are robust, flexible, comprehensible and intelligent. The study also included assessing the benefits and pre-requisites of such methodology with both practical and theoretical approaches. The ultimate goal of this entire study was to create value for the organization by reducing lead-time in the design process while promoting the production of high quality products. A case-based approach was applied in the study in which modeling strategies resulting from practical investigations and analyzing existing methodologies were implemented on a CAD-model representing the gas-volume of a turbine volute. The chosen strategies were evaluated and subsequently documented as a part of the methodology or discarded depending on its support for the parameterization. The final methodology itself was evaluated based on the quality of the parameterized CAD-model, the time required to create the model and its compatibility to the present design process at Scania CV AB. Finally the methodology was discussed with respect to the different evaluations, and the defined research questions were discussed and answered. The results of the thesis revealed that if parametric CAD-models are made in a structured, standardized and conscious manner, they are able to be highly robust and flexible which gives the models the ability to assume a big set of different forms. The methodology is recommended to be tested in a pilot project and be implemented through internal courses at the company. It was concluded that a methodology which aids the design engineers in creating parametric CAD-models will be the key towards implementing parametric CAD-models in the company and also enabling the many benefits of parameterization, which includes reduced lead-time, enhanced component performance, increased knowledge about the component, and promotion of collaboration among engineers. It was also concluded that parametric models are best suited when the existing design freedom is big and when the time permits performance analyses via optimizations, while challenges include ensuring that the model is parameterized correctly with respect to the CFD-engineers’ wishes while taking into account the requirements from other disciplines. Therefore it is very important to establish a communication between the different engineers. Ultimately, when parametric models are established in the organization, they are recommended to be implemented eventually in both short-term and long-term projects within Scania for its beneficial properties.

The problem of constructing data-based, predictive, reduced models for the Kuramoto–Sivashinsky equation is considered, under circumstances where one has observation data only for a small subset of the dynamical variables. Accurate prediction is achieved by developing a discrete-time stochastic reduced system, based on a NARMAX (Nonlinear Autoregressive Moving Average with eXogenous input) representation. The practical issue, with the NARMAX representation as with any other, is to identify an efficient structure, i.e., one with a small number of terms and coefficients. This is accomplished here by estimating coefficients for an approximate inertial form. The broader significance of the results is discussed.

An evolutionary geometry parametrization is established to represent aerodynamic configurations. This geometry parametrization technique is constructed by integrating the classical B-spline formulation with the knot insertion algorithm. It is capable of inserting control points to a given parametrization without modifying its geometry. Taking advantage of this technique, a shape design problem can be solved as a sequence of optimizations from the basic parametrization to more refined parametrizations. Owing to the nature of the B-spline formulation, feasible parametrization refinements are not unique; guidelines based on sensitivity analysis and geometry constraints are developed to assist the automation of the proposed optimization sequence. Test cases involving airfoil optimization and induced drag minimization are solved adopting this method. Its effectiveness is demonstrated through comparisons with optimizations using uniform refined parametrizations.

An evolutionary geometry parametrization is established to represent aerodynamic configurations. This geometry parametrization technique is constructed by integrating the classical B-spline formulation with the knot insertion algorithm. It is capable of inserting control points to a given parametrization without modifying its geometry. Taking advantage of this technique, a shape design problem can be solved as a sequence of optimizations from the basic parametrization to more refined parametrizations. Owing to the nature of the B-spline formulation, feasible parametrization refinements are not unique; guidelines based on sensitivity analysis and geometry constraints are developed to assist the automation of the proposed optimization sequence. Test cases involving airfoil optimization and induced drag minimization are solved adopting this method. Its effectiveness is demonstrated through comparisons with optimizations using uniform refined parametrizations.

This work deals with the modelling of runoff processes in the experimental Bystřice river catchment in the Krušné Mountains. Rainfall-runoff model WaSiM (Topmodel version) was used for this purpose.Objective of this study was modelling snow accumulation and snowmelt in winter periods 2009/2010 and 2010/2011. Sensitivity analysis of TOPMODEL parameters was performed using Monte Carlo and GLUE methodology. Wasim was calibrated manually for 25 and 250 m grid scales and daily timestep. Results of simulations in both spatial scales different spatial scales differed significantly. Better performance of modelling in finer scale wasn't proved in validation of the model. Results of the simulations pointed out uncertainty in model calibration. Rasters of modeled snow water equivalent were also analyzed in selected days representing periods of snow accumulation and snowmelt. The goal was to examine the functioning of used snow model (combination of temperature index method and energy balance method) within the WaSiM frame. Finer scale raster proved to be practical for this purpose It was found that the spatial heterogeneity in the distribution of snow is determined by evapotranspiration and also by effect of radiation correction (in the case of rainfall).Influence of interception and vegetation effects on...

A radiação solar global (RG) é uma das variáveis meteorológicas mais importantes para a compreensão de processos biofísicos em ferramentas ao suporte de decisão na agricultura. Atualmente, ela pode ser medida por diferentes sensores de custo relativamente baixos e, de modo geral, apenas estações meteorológicas instaladas mais recentemente registram RG. Na falta de dados observados, torna-se necessário estimá-la através de modelos tão simples quanto possível e baseados em dados de entrada de fácil obtenção. O presente trabalho teve por objetivo analisar dois modelos (Bristow e Campbell (1984) (BC) e Hargreaves e Samani (1982) (H)) e otimizá-los estatisticamente, ajustando seus parâmetros, tomando como referência uma base de dados observados de 32 localidades pelo Instituto Nacional de Pesquisas Espaciais em todas as regiões brasileiras. O desempenho de cada modelo foi avaliado através do erro médio (EM), erro médio absoluto (EAM), coeficiente de determinação (R2), coeficiente de correlação (r), índice de concordância de Willmott (d) e raiz do erro médio quadrático (RMSE). Utilizando os parâmetros originais, o modelo H apresentou melhor desempenho, analisando RMSE, para todas as regiões brasileiras, com valores de 4.24 MJ.m-2d-1 para a região Norte, 4.55 MJ.m-2d-1 para a região Nordeste, 4.39 MJ.m-2d-1 para a região Centro Oeste, 4.61 MJ.m-2d-1 para a região Sul e 4.21 MJ.m-2d-1 para a região Sudeste. Após a otimização, o melhor desempenho foi dado pelo modelo BC, em todas as regiões do Brasil, com RMSE de 3.44 MJ.m-2d-1 para a Região Norte, 3.70 MJ.m-2d-1 para a região Nordeste, 3.62 MJ.m-2d-1 para a região Centro Oeste, 4.43 MJ.m-2d-1 para a região Sul e 3.50 MJ.m-2d-1 para a região Sudeste. Com a otimização dos parâmetros, encontraram-se valores médios para KT, utilizada pelo modelo de H: 0.152 °C-0,5 para a região Norte, 0.173 °C-0,5 para a região Nordeste, 0.145 °C-0,5 para a região Centro Oeste, 0.163 °C-0,5 para a região Sul e 0.152 °C-0,5 para a região Sudeste. Para os parâmetros adimensionais \"A\", \"B\" e \"C\" do modelo BC obteve-se para cada região, respectivamente, os seguintes valores: 0.619, 0.026 e 1.845 para a região Norte, 0.694, 0.074 e 1.489 para a região Nordeste, 0.635, 0.029 e 1.697 para a região Centro Oeste, 0.671, 0.044 e 1.580 para a região Sul e 0.702, 0.025 e 1.747 para a região Sudeste. / Global solar radiation (RG) is one of the most important weather variables for understanding the biophysical processes in agricultural support tools. Currently, it can be measured by different low cost sensors. In Brazil, weather stations just recently start to record RG values. In the absence of long term observed data, models for estimating RG are needed, and the objective of this study was to analyse two Bristow and Campbell (1984) (BC) and Hargreaves and Samani (1982) (H) models for different regions in Brazil against a reference database of 32 places collected the National Institute of Space Research (INPE) through the coefficient of determination (R2), correlation coefficient (r), Willmott concordance index (d), modelling efficiency (E), and root mean square error (RMSE). They were also statistically optimized based on an iterative approach. Using the original parameters, the H model presented the best performance for all Brazilian regions, with values with RMSE of 4.24 MJ.m-2d-1 for a North region, 4.55 MJ.m-2d-1 for the Northeast Region, 4.39 MJ.m-2d-1 for a Midwest region, 4.61 MJ.m-2d-1 for a South region and 4.21 MJ.m-2d-1 for a Southeast region. After the optimization process, the best performance was given by the BC model for all Brazilian regions, with RMSE of 3.44 MJ.m-2d-1 for a North Region, 3.70 MJ.m-2d-1 for a Northeast region, 3.62 MJ.m-2d-1 for a Midwest region, 4.43 MJ.m-2d-1 for a South region and 3.50 MJ.m-2d-1 for a Southeast region. After the parameter optimization, mean values for KT for H model were 0.152 °C-0.5 for the North region, 0.173°C-0.5 for the Northeast region, 0.145°C-0.5 for the Midwest region, 0.163 °C-0.5 for the South region and 0.152°C-0.5 for the Southeast region. For the BC´s dimensionless parameters \"A\", \"B\" and \"C\" it was found the following values, respectively: 0.619, 0.026 and 1.845 for the North region, 0.694, 0.074 and 1.489 for the Northeast region, 0.635, 0.029 and 1.697 for the Midwest region, 0.671, 0.044 and 1.580 for the South region, and 0.702, 0.025 and 1.747 for the Southeast region.

This thesis presents a new system that reconstructs the 3D representation of dental casts. To maintain the integrity of the 3D representation, a standard model is built to cover the blind spots that the camera cannot reach. The standard model is obtained by scanning a real human mouth model with a laser scanner. Then the model is simplified by an algorithm which is based on iterative contraction of vertex pairs. The simplified standard model uses a local parametrization method to obtain the curvature information. The system uses a digital camera and a square tube mirror in front of the camera to capture multi-view images. The mirror is made of stainless steel in order to avoid double reflections. The reflected areas of the image are considered as images taken by the virtual cameras. Only one camera calibration is needed since the virtual cameras have the same intrinsic parameters as the real camera. Depth is computed by a simple and accurate geometry based method once the corresponding points are identified. Correspondences are selected using a feature point based stereo matching process, including fast normalized cross-correlation and simulated annealing.

This thesis work presents a parametrized integration of the flight control system within RAPID by means of the automation in CATIA V5, using Knowledge Pattern. Nowadays aircraft’s design and development processes are not only time-consuming but also incur high economic cost. In addition, system integration is highly a multi-disciplinary design process which often involves a large number of different discipline teams working at the same time and space. The main objective of this thesis is to investigate how CAD (Computer Aided Design) software can be used in the early design stages to define the flight control system integration. The purpose of this work to improve the functionality of an in house produced aircraft conceptual design tool carried out at the Division of Fluid and Mechatronic Systems, Linköping University. The work consists of preliminary integration of the RAPID flight control system and the hydraulics associated to it. By defining several reusable templates, the automatic definition of a flight control system within the RAPID aircraft has been achieved. Moreover it is a parametrical model which allows the user to modify a high number of features as desired to enhance the design process. For this, a user interface in Microsoft Excel connected to CATIA has also been attained.

A radiação solar global (RG) é uma das variáveis meteorológicas mais importantes para a compreensão de processos biofísicos em ferramentas ao suporte de decisão na agricultura. Atualmente, ela pode ser medida por diferentes sensores de custo relativamente baixos e, de modo geral, apenas estações meteorológicas instaladas mais recentemente registram RG. Na falta de dados observados, torna-se necessário estimá-la através de modelos tão simples quanto possível e baseados em dados de entrada de fácil obtenção. O presente trabalho teve por objetivo analisar dois modelos (Bristow e Campbell (1984) (BC) e Hargreaves e Samani (1982) (H)) e otimizá-los estatisticamente, ajustando seus parâmetros, tomando como referência uma base de dados observados de 32 localidades pelo Instituto Nacional de Pesquisas Espaciais em todas as regiões brasileiras. O desempenho de cada modelo foi avaliado através do erro médio (EM), erro médio absoluto (EAM), coeficiente de determinação (R2), coeficiente de correlação (r), índice de concordância de Willmott (d) e raiz do erro médio quadrático (RMSE). Utilizando os parâmetros originais, o modelo H apresentou melhor desempenho, analisando RMSE, para todas as regiões brasileiras, com valores de 4.24 MJ.m-2d-1 para a região Norte, 4.55 MJ.m-2d-1 para a região Nordeste, 4.39 MJ.m-2d-1 para a região Centro Oeste, 4.61 MJ.m-2d-1 para a região Sul e 4.21 MJ.m-2d-1 para a região Sudeste. Após a otimização, o melhor desempenho foi dado pelo modelo BC, em todas as regiões do Brasil, com RMSE de 3.44 MJ.m-2d-1 para a Região Norte, 3.70 MJ.m-2d-1 para a região Nordeste, 3.62 MJ.m-2d-1 para a região Centro Oeste, 4.43 MJ.m-2d-1 para a região Sul e 3.50 MJ.m-2d-1 para a região Sudeste. Com a otimização dos parâmetros, encontraram-se valores médios para KT, utilizada pelo modelo de H: 0.152 °C-0,5 para a região Norte, 0.173 °C-0,5 para a região Nordeste, 0.145 °C-0,5 para a região Centro Oeste, 0.163 °C-0,5 para a região Sul e 0.152 °C-0,5 para a região Sudeste. Para os parâmetros adimensionais \"A\", \"B\" e \"C\" do modelo BC obteve-se para cada região, respectivamente, os seguintes valores: 0.619, 0.026 e 1.845 para a região Norte, 0.694, 0.074 e 1.489 para a região Nordeste, 0.635, 0.029 e 1.697 para a região Centro Oeste, 0.671, 0.044 e 1.580 para a região Sul e 0.702, 0.025 e 1.747 para a região Sudeste. / Global solar radiation (RG) is one of the most important weather variables for understanding the biophysical processes in agricultural support tools. Currently, it can be measured by different low cost sensors. In Brazil, weather stations just recently start to record RG values. In the absence of long term observed data, models for estimating RG are needed, and the objective of this study was to analyse two Bristow and Campbell (1984) (BC) and Hargreaves and Samani (1982) (H) models for different regions in Brazil against a reference database of 32 places collected the National Institute of Space Research (INPE) through the coefficient of determination (R2), correlation coefficient (r), Willmott concordance index (d), modelling efficiency (E), and root mean square error (RMSE). They were also statistically optimized based on an iterative approach. Using the original parameters, the H model presented the best performance for all Brazilian regions, with values with RMSE of 4.24 MJ.m-2d-1 for a North region, 4.55 MJ.m-2d-1 for the Northeast Region, 4.39 MJ.m-2d-1 for a Midwest region, 4.61 MJ.m-2d-1 for a South region and 4.21 MJ.m-2d-1 for a Southeast region. After the optimization process, the best performance was given by the BC model for all Brazilian regions, with RMSE of 3.44 MJ.m-2d-1 for a North Region, 3.70 MJ.m-2d-1 for a Northeast region, 3.62 MJ.m-2d-1 for a Midwest region, 4.43 MJ.m-2d-1 for a South region and 3.50 MJ.m-2d-1 for a Southeast region. After the parameter optimization, mean values for KT for H model were 0.152 °C-0.5 for the North region, 0.173°C-0.5 for the Northeast region, 0.145°C-0.5 for the Midwest region, 0.163 °C-0.5 for the South region and 0.152°C-0.5 for the Southeast region. For the BC´s dimensionless parameters \"A\", \"B\" and \"C\" it was found the following values, respectively: 0.619, 0.026 and 1.845 for the North region, 0.694, 0.074 and 1.489 for the Northeast region, 0.635, 0.029 and 1.697 for the Midwest region, 0.671, 0.044 and 1.580 for the South region, and 0.702, 0.025 and 1.747 for the Southeast region.

We investigate the mesh colors method for per-face parameterization for texture-mapping of geometry, implemented in the game engine Frostbite 3, for the purpose of evaluating the method compared to traditional texture-mapping in a real-time application. Traditional UV-mapping often causes discontinuities which commonly results in visible seams in the end results. If any change is done to the vertex positions or the topology a remapping of the UV-map has to be done. Mesh colors aims to avoid these problems by skipping the transformation to 2D space as in UV-mapping, and associating color samples directly with the geometry of a mesh. The implementation was done in Frostbite 3 in C++ and HLSL shader code, and rendered with the DirectX graphics API. The results show that mesh colors is a viable alternative in a real-time renderer. Though not as fast as regular UV-mapped textures due to lack of hardware accelerated filtering operations, mesh colors is a realistic alternative for special cases where regular texture-mapping would be cumbersome to work with or produce sub-par results. Possible areas of future research are efficient data structures suitable to handle data insertion dynamically, compression of mesh colors data, and mesh colors in the context of mesh LOD generation.