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<p>An explicit algebraic Reynolds stress model (EARSM) based ona pressure strain rate model including terms tensoriallynonlinear in the mean velocity gradients is developed in orderto improve predictions for .ows with strong curvature and/orrotation. This work has been carried out in the context of acollaborative international project on high-lift aerodynamics.For 2D mean .ows the nonlinear terms can easily be accountedfor in the model formulation. This is not the case for 3D mean.ows and approximations making the 2D and 3D mean .owformulations consistent are suggested. The proposed EARSM, theparent-EARSM and the corresponding di.erential Reynolds stressmodels (DRSM) are tested for spanwise rotating channel .ow andaxially rotating pipe .ow. The model predictions are comparedto experimental and DNS data. The nonlinear extensions areshown to have a signi.cant e.ect on the .ow predictions,somewhat less pronounced for the DRSM though. The turbulentdi.usion modelling in the EARSM computations is important forthe rotating pipe. It is shown that by using a Daly and Harlowdi.usion model, turbulence levels in good agreement withexperiments and DRSM can be achieved. However, by using asimpler e.ective eddy viscosity based di.usion model theturbulence kinetic energy levels are drastically overpredicted.Finally the proposed EARSM is tested on a standard high-liftcon.guration. The EARSM predictions are compared withexperiments and the predictions made by the standard K - ωtwo-equation model.</p><p><b>Descriptors:</b>Turbulence model, nonlinear modelling,streamline curvature, high-lift aerodynamics.</p>

An explicit algebraic Reynolds stress model (EARSM) based ona pressure strain rate model including terms tensoriallynonlinear in the mean velocity gradients is developed in orderto improve predictions for .ows with strong curvature and/orrotation. This work has been carried out in the context of acollaborative international project on high-lift aerodynamics.For 2D mean .ows the nonlinear terms can easily be accountedfor in the model formulation. This is not the case for 3D mean.ows and approximations making the 2D and 3D mean .owformulations consistent are suggested. The proposed EARSM, theparent-EARSM and the corresponding di.erential Reynolds stressmodels (DRSM) are tested for spanwise rotating channel .ow andaxially rotating pipe .ow. The model predictions are comparedto experimental and DNS data. The nonlinear extensions areshown to have a signi.cant e.ect on the .ow predictions,somewhat less pronounced for the DRSM though. The turbulentdi.usion modelling in the EARSM computations is important forthe rotating pipe. It is shown that by using a Daly and Harlowdi.usion model, turbulence levels in good agreement withexperiments and DRSM can be achieved. However, by using asimpler e.ective eddy viscosity based di.usion model theturbulence kinetic energy levels are drastically overpredicted.Finally the proposed EARSM is tested on a standard high-liftcon.guration. The EARSM predictions are compared withexperiments and the predictions made by the standard K - ωtwo-equation model. Descriptors:Turbulence model, nonlinear modelling,streamline curvature, high-lift aerodynamics.

The volatility of house prices can raise systemic risks in the housing market due to the vulnerability of the banking and mortgage sectors to such fluctuations. Moreover, the extreme increases in housing markets have been considered a key feature of the last economic crisis and the run-up to it. Such increases, however, came to a sudden halt immediately before the crisis or directly it began. Despite the recent growth of scholarly work on the role of house price behaviour in economic stability, fundamental questions have yet to be answered: for instance: (i) how far do the nonlinear models outperform the linear models? And how does such nonlinearity explain the asymmetry in the cycle; (ii) what are the main characteristics of house price cycles, and how do they differ over time; and (iii) what kind of policy intervention would stop a real estate boom? This thesis, made up of three empirical essays, aims to take a step forward in answering these questions. The first essay examines whether house prices in large metropolitan areas such as London, New York and Hong Kong follow linear or nonlinear models. The Smooth Transition Autoregressive model was used on a sample of monthly data over the period 1996:1 to 2015:12. The results indicate that linear models are unsuitable for modelling the housing market for the chosen cities. Moreover, strong evidence indicates that real estate prices are largely nonlinear and can well be modelled using a logistic smooth transition model (LSTAR). Estimation results also show different degrees of asymmetry. In particular, the speed of transition between the expansion and contraction of house prices is greater in London than it is in Hong Kong while the speed of transition between boom and bust in New York house prices is the slowest. Further, the forecast results suggest that the LSTAR outdoes the linear model in out-of-sample performance. The second essay investigates the main features of house price cycles in the same major metropolitan areas by providing a reasonable level of discrimination between the cyclical decomposition techniques available for capturing suitable measurements for house price cycles. Through a sample of large cities in several countries, it is shown that the model-based filter is suitable for capturing the main features of house price cycles and the results confirm that these cycles are centred at low frequency. Moreover, there is evidence of substantial variation in the duration and amplitude of these cycles both across cities and over time. The third essay provides evidence that real house prices are significantly affected by financial stability policies. Considering the Hong Kong experience, the results show strong evidence of duration dependences in both the upswing and downswing phases of the cycle. Moreover, the time taken to reach the turning point increases dramatically as the cycle proceeds. The findings also suggest that there is feedback between house price volatility and the policies that affect the housing market. Accordingly, house prices respond with more volatility to any change in the loan to value and lending policy indicators (ignoring the sign of this shock). Finally, the evidence of asymmetry suggests that unanticipated house price increases are more destabilising than unanticipated falls in house prices.

Esta tesis se dedica en un estudio de estabilidad no lineal de la morfodinàmica de la zona de rompientes de playas de arena. El modelo numérico MORFO55 resuelve las ecuaciones de aguas someras no lineales para la hidrodinámica y actualiza la topografía a partir del transporte de sedimento. En primer lugar, se aplica en el caso de playas complejas longitudinalmente no uniformes con objeto de probar sus distintas formulaciones. En secundo lugar, se usa para estudiar la generación de estructuras rítmicas en playas longitudinalmente uniformes. Entre estos patrones se distinguen las barras transversales y oblicuas, las barras crescenticas y los sistemas de barras/surcos (ridges/runnels). La hipótesis de que emergen a partir de inestabilidades internas del acoplamiento entre la topografía y la hidrodinámica se investiga. Los estudios previos de modelización numérica se limitaban a las etapas iniciales de la generación de las barras. En particular, mostraban que las barras transversales y oblicuas pueden formarse en playas planas mientras que las barras crecenticas aparecen en playas con barra. La formación de los sistemas de barras/surcos se explica con modelos conceptuales de la observación mediante satélite según los cuales emergerán a partir de la deformación de la barra intermareal. Esta tesis estudia el régimen no lineal de la evolución de todos estos sistemas. Particularmente se obtiene un estado 'nal de equilibrio. Los resultados generales coinciden cualitativamente con las barras observadas en la naturaleza. Se da una interpretación física de la formación, de la evolución y de la saturación del crecimiento de las barras. / This thesis performs a nonlinear stability study of the surf zone morphodynamics of sandy beaches. To this end the MORFO55 model based on a wave and depth averaged nonlinear shallow water equations solver with wave driver, sediment transport and bed updating is presented. It is first applied to complex longitudinally non-uniform beaches in order to test different model formulations. Second, it is applied to study the generation of surf zone rhythmic features on alongshore uniform beaches. Shore-attached transverse or oblique bars, crescentic bars and ridge and runnel systems are well known examples of such features. The hypothesis that they emerge by self organisation of the coupling between topography, waves and currents is here tested. In absence of shore-parallel bars, the initial formation of transverse and oblique bars had been shown by previous modelling studies of linear stability analysis but is now extended to the finite amplitude regime. In most of barred beaches, crescentic bars and ridge and runnel systems appear. Conceptual models based on field observations suggest that ridges and runnels could emerge by the deformation of the alongshore intertidal bar intercepted by crescentic bars. Up to now, only the formation of crescentic bars had numerically succeeded with linear and non linear models. This study shows that a dynamical equilibrium state of each of these rhythmic bar systems may be described with a numerical model. General results are in qualitative agreement with the bar systems observed in nature. A physical explanation for their formation, their evolution and the saturation of their growth is given.

Abstract The modern wireless communication techniques are aiming on increasing bandwidth and the number of carriers for higher data rate. This sets challenging linearity requirements for RF power amplifiers (PAs). Unfortunately, high linearity can only be obtained at the cost of efficiency. In order to improve the performance of the PA, in-depth understanding of nonlinear behaviour is mandatory. This calls for techniques that can give componentwise information of the causes of the distortion. The aim of this thesis is to develop a technique that can provide such information. This thesis proposes a detailed distortion analysis technique that is based on frequency domain fitting of polynomial models. Simulated large-signal spectra are used for fitting as these contain the necessary information about the large-signal bias point and amplitude range. Moreover, in the frequency domain the delays are easy to compensate, and detailed analysis to any fitted tone can be performed. The fitting procedure as such is simple but becomes difficult in multi-dimensional nonlinearities if the controlling voltages correlate strongly. In this thesis the solvability and reliability of the fitting procedure is increased by numerical operations, model-degree reduction and by using different excitations. A simplified Volterra method is used to calculate the distortion contributions by using the fitted model. The overall distortion is analysed by calculating the voltage response of the contributions of each nonlinearity to the terminal nodes of the device by the use of linear transfer functions of the circuit. The componentwise analysis is performed by phasor presentation enabling the cancelling mechanisms to be seen. The proposed technique is implemented on top of harmonic balance simulation in an APLAC circuit simulator in which extensive distortion simulations are performed. The technique relies on the existing device model and thus the fitted model can be only as accurate as the particular simulation model. However, two different RF PAs are analysed that show a good agreement between measurements and simulations. The proposed technique is verified with several test cases including amplitude dependent amplitude and phase distortion, intermodulation distortion sweet spots, bandwidth dependent memory effects and impedance optimization. The main finding of the detailed analysis is that the distortion is a result of several cancelling mechanisms. In general, cubic nonlinearity of transconductance is dominating the in-band distortion but is cancelled by the 2nd-degree nonlinearity that is mixed to the fundamental band from envelope and 2nd harmonic bands that is usually the main cause of memory effects.

Damage observed after previous earthquakes indicates that a large number of existing buildings are vulnerable to seismic hazard. This research intends to assess seismic vulnerability of regular and irregular shear wall buildings in Canada, having different heights and different levels of seismic design and detailing. As seismic hazard is a probabilistic event, a probabilistic methodology has been adopted to assess the seismic vulnerability of the shear wall buildings. The proposed research encompasses a comprehensive fragility analysis for seismic vulnerability of shear wall buildings in Canada. The first phase of the investigation involves shear wall buildings with different heights (hence different structural periods), designed based on the 2010 National Building Code of Canada. The second phase involves shear wall buildings designed prior to 1975, representing pre-modern seismic code era. The third phase involves the evaluation of pre-1975 shear wall buildings with irregularities. 3-Dimensional simulations of the buildings were constructed by defining nonlinear modelling for shear wall and frame elements. These models were subjected to dynamic time history analyses conducted using Perform 3D software. Two sets of twenty earthquake records, compatible with western and eastern Canadian seismicity, were selected for this purpose. Spectral acceleration and peak ground acceleration were chosen as seismic intensity parameters and the first storey drift was selected as the engineering demand parameter which was further refined for irregular cases. The earthquake records were scaled to capture the structural behaviour under different levels of seismic excitations known as Incremental Dynamic Analysis. The resulting IDA curves were used as the input for seismic fragility analysis. Fragility curves were derived as probabilistic tools to assess seismic vulnerability of the buildings. These curves depict probability of exceeding immediate occupancy, life safety and collapse prevention limit states under different levels of seismic intensity.

No description available.

<p>Mathematical models of classes of objects can significantly contribute to the analysis of digital images. A major problem in modelling is to establish suitable descriptions that cover not only a single object but also the variation that is usually present within a class of objects.</p><p>The objective of this thesis is to develop more general modelling strategies than commonly used today. In particular, the impact of the human factor in the model creation process should be minimised. It is presumed that the human ability of abstraction imposes undesired constraints on the description. In comparison, common approaches are discussed from the viewpoint of generality.</p><p>The technique considered introduces <i>appearance space </i>as a common framework to represent both shapes and images. In appearance space, an object is represented by a single point in a high-dimensional vector space. Accordingly, objects subject to variation appear as <i>nonlinear manifolds</i> in appearance space. These manifolds are often characterised by only a few intrinsic dimensions. A model of a class of objects is therefore considered equal to the mathematical description of this manifold.</p><p>The presence of nonlinearity motivates the use of artificial auto-associative neural networks in the modelling process. The network extracts nonlinear modes of variation from a number of training examples. The procedure is evaluated on both synthetic and natural data of shapes and images and shows promising results as a general approach to object modelling.</p>

Mathematical models of classes of objects can significantly contribute to the analysis of digital images. A major problem in modelling is to establish suitable descriptions that cover not only a single object but also the variation that is usually present within a class of objects. The objective of this thesis is to develop more general modelling strategies than commonly used today. In particular, the impact of the human factor in the model creation process should be minimised. It is presumed that the human ability of abstraction imposes undesired constraints on the description. In comparison, common approaches are discussed from the viewpoint of generality. The technique considered introduces appearance space as a common framework to represent both shapes and images. In appearance space, an object is represented by a single point in a high-dimensional vector space. Accordingly, objects subject to variation appear as nonlinear manifolds in appearance space. These manifolds are often characterised by only a few intrinsic dimensions. A model of a class of objects is therefore considered equal to the mathematical description of this manifold. The presence of nonlinearity motivates the use of artificial auto-associative neural networks in the modelling process. The network extracts nonlinear modes of variation from a number of training examples. The procedure is evaluated on both synthetic and natural data of shapes and images and shows promising results as a general approach to object modelling.