Radiaalikompressorin spiraalivirtauksen numeerinen mallinnus

Diplomityössä mallinnetaan numeerisesti radiaalikompressorin spiraalin virtaus. Spiraalin tarkoituksena radiaalikompressorissa on kerätä tasaisesti virtaus diffuusorin kehältä. Spiraaliin on viime aikoina kiinnitetty enemmän huomiota, koska on havaittu, että kompressorin hyötysuhdetta voidaan parantaa spiraalia optimoimalla. Spiraalin toimintaa tarkastellaan kolmella eri massavirralla. Työn alussa käsitellään spiraalin toimintaperiaatteita. Numeerisena ratkaisijana käytetään Teknillisessä korkeakoulussa kehitettyä FIN-FLO -koodia. FINFLO -laskentaohjelmassa ratkaistaan Navier-Stokes yhtälöt kolmeulotteiselle laskenta-alueelle. Diskretointi perustuu kontrollitilavuus menetelmään. Työssä käsitellään laskentakoodin toimintaperiaatteitta. Turbulenssia mallinnetaan algebrallisella Baldwin-Lomaxin ja kahden yhtälön Chienin k-e turbulenssimalleilla. Laskentatuloksia verrataan Lappeenrannan teknillisessä korkeakoulussa tehtyihin mittauksiin kyseessä olevasta kompressorin spiraalista. Myös eri turbulenssimalleilla ja hilatasoilla saatuja tuloksia verrataan keskenään. Laskentatuloksien jälkikäsittelyä varten ohjelmoitiin neljä eri tietokoneohjelmaa. Laskennalla pyritään saamaan lisäselvyyttä virtauksen käyttäytymiseen spiraalissa ja erityisesti ns. kielen alueella. Myös kahden eri turbulenssimallin toimivuutta kompressorin numeerisessa mallinnuksessa tutkitaan.

Architectural characterization of a delta-front reservoir analogue combining ground penetrating radar and electrical resistivity tomography: Roda Sandstone (Lower Eocene, Graus-Tremp basin, Spain)

Three-dimensional reconstruction of reservoir analogues can be improved combining data from different geophysical methods. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) data are valuable tools, since they provide subsurface information from internal architecture and facies distribution of sedimentary rock bodies, enabling the upgrading of depositional models and heterogeneity reconstruction. The Lower Eocene Roda Sandstone is a well-known deltaic complex widely studied as a reservoir analogue that displays a series of sandstone wedges with a general NE to SW progradational trend. To provide a better understanding of internal heterogeneity of a 10m-thick progradational delta-front sandstone unit, 3D GPR data were acquired. In addition, common midpoints (CMP) to measure the sandstone subsoil velocity, test profiles with different frequency antennas (25, 50 and 100MHz) and topographic data for subsequent correction in the geophysical data were also obtained. Three ERT profiles were also acquired to further constrain GPR analysis. These geophysical results illustrate the geometry of reservoir analogue heterogeneities both depositional and diagenetic in nature, improving and complementing previous outcrop-derived data. GPR interpretation using radar stratigraphy principles and attributes analysis provided: 1)tridimensional geometry of major stratigraphic surfaces that define four units in the GPR Prism, 2) image the internal architecture of the units and their statistical study of azimuth and dips, useful for a quick determination of paleocurrent directions. These results were used to define the depositional architecture of the progradational sandbody that shows an arrangement in very-high-frequency sequences characterized by clockwise paleocurrent variations and decrease of the sedimentary flow, similar to those observed at a greater scale in the same system. This high-frequency sequential arrangement has been attributed to the autocyclic dynamics of a supply-dominated delta- front where fluvial and tidal currents are in competition. The resistivity models enhanced the viewing of reservoir quality associated with cement distribution caused by depositional and early diagenetic processes related to the development of transgressive and regressive systems tracts in igh-frequency sequences.

Flexible Multibody Simulation Approach in the Dynamic Analysis of Bone Strains Activity

The objective of this study is to show that bone strains due to dynamic mechanical loading during physical activity can be analysed using the flexible multibody simulation approach. Strains within the bone tissue play a major role in bone (re)modeling. Based on previous studies, it has been shown that dynamic loading seems to be more important for bone (re)modeling than static loading. The finite element method has been used previously to assess bone strains. However, the finite element method may be limited to static analysis of bone strains due to the expensive computation required for dynamic analysis, especially for a biomechanical system consisting of several bodies. Further, in vivo implementation of strain gauges on the surfaces of bone has been used previously in order to quantify the mechanical loading environment of the skeleton. However, in vivo strain measurement requires invasive methodology, which is challenging and limited to certain regions of superficial bones only, such as the anterior surface of the tibia. In this study, an alternative numerical approach to analyzing in vivo strains, based on the flexible multibody simulation approach, is proposed. In order to investigate the reliability of the proposed approach, three 3-dimensional musculoskeletal models where the right tibia is assumed to be flexible, are used as demonstration examples. The models are employed in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model is developed using the actual geometry of the subject’s tibia, which is obtained from 3 dimensional reconstruction of Magnetic Resonance Images. Inverse dynamics simulation based on motion capture data obtained from walking at a constant velocity is used to calculate the desired contraction trajectory for each muscle. In the forward dynamics simulation, a proportional derivative servo controller is used to calculate each muscle force required to reproduce the motion, based on the desired muscle contraction trajectory obtained from the inverse dynamics simulation. Experimental measurements are used to verify the models and check the accuracy of the models in replicating the realistic mechanical loading environment measured from the walking test. The predicted strain results by the models show consistency with literature-based in vivo strain measurements. In conclusion, the non-invasive flexible multibody simulation approach may be used as a surrogate for experimental bone strain measurement, and thus be of use in detailed strain estimation of bones in different applications. Consequently, the information obtained from the present approach might be useful in clinical applications, including optimizing implant design and devising exercises to prevent bone fragility, accelerate fracture healing and reduce osteoporotic bone loss.

Tangential migration of neuronal precursors of glutamatergic neurons in the adult mammalian brain.

In a classic model of mammalian brain formation, precursors of principal glutamatergic neurons migrate radially along radial glia fibers whereas GABAergic interneuron precursors migrate tangentially. These migration modes have significant implications for brain function. Here we used clonal lineage tracing of active radial glia-like neural stem cells in the adult mouse dentate gyrus and made the surprising discovery that proliferating neuronal precursors of glutamatergic granule neurons exhibit significant tangential migration along blood vessels, followed by limited radial migration. Genetic birthdating and morphological and molecular analyses pinpointed the neuroblast stage as the main developmental window when tangential migration occurs. We also developed a partial "whole-mount" dentate gyrus preparation and observed a dense plexus of capillaries, with which only neuroblasts, among the entire population of progenitors, are directly associated. Together, these results provide insight into neuronal migration in the adult mammalian nervous system.

Modeling the transport phenomena within arterial wall: porous media approach

The transport of macromolecules, such as low-density lipoprotein (LDL), and their accumulation in the layers of the arterial wall play a critical role in the creation and development of atherosclerosis. Atherosclerosis is a disease of large arteries e.g., the aorta, coronary, carotid, and other proximal arteries that involves a distinctive accumulation of LDL and other lipid-bearing materials in the arterial wall. Over time, plaque hardens and narrows the arteries. The flow of oxygen-rich blood to organs and other parts of the body is reduced. This can lead to serious problems, including heart attack, stroke, or even death. It has been proven that the accumulation of macromolecules in the arterial wall depends not only on the ease with which materials enter the wall, but also on the hindrance to the passage of materials out of the wall posed by underlying layers. Therefore, attention was drawn to the fact that the wall structure of large arteries is different than other vessels which are disease-resistant. Atherosclerosis tends to be localized in regions of curvature and branching in arteries where fluid shear stress (shear rate) and other fluid mechanical characteristics deviate from their normal spatial and temporal distribution patterns in straight vessels. On the other hand, the smooth muscle cells (SMCs) residing in the media layer of the arterial wall respond to mechanical stimuli, such as shear stress. Shear stress may affect SMC proliferation and migration from the media layer to intima. This occurs in atherosclerosis and intimal hyperplasia. The study of blood flow and other body fluids and of heat transport through the arterial wall is one of the advanced applications of porous media in recent years. The arterial wall may be modeled in both macroscopic (as a continuous porous medium) and microscopic scales (as a heterogeneous porous medium). In the present study, the governing equations of mass, heat and momentum transport have been solved for different species and interstitial fluid within the arterial wall by means of computational fluid dynamics (CFD). Simulation models are based on the finite element (FE) and finite volume (FV) methods. The wall structure has been modeled by assuming the wall layers as porous media with different properties. In order to study the heat transport through human tissues, the simulations have been carried out for a non-homogeneous model of porous media. The tissue is composed of blood vessels, cells, and an interstitium. The interstitium consists of interstitial fluid and extracellular fibers. Numerical simulations are performed in a two-dimensional (2D) model to realize the effect of the shape and configuration of the discrete phase on the convective and conductive features of heat transfer, e.g. the interstitium of biological tissues. On the other hand, the governing equations of momentum and mass transport have been solved in the heterogeneous porous media model of the media layer, which has a major role in the transport and accumulation of solutes across the arterial wall. The transport of Adenosine 5´-triphosphate (ATP) is simulated across the media layer as a benchmark to observe how SMCs affect on the species mass transport. In addition, the transport of interstitial fluid has been simulated while the deformation of the media layer (due to high blood pressure) and its constituents such as SMCs are also involved in the model. In this context, the effect of pressure variation on shear stress is investigated over SMCs induced by the interstitial flow both in 2D and three-dimensional (3D) geometries for the media layer. The influence of hypertension (high pressure) on the transport of lowdensity lipoprotein (LDL) through deformable arterial wall layers is also studied. This is due to the pressure-driven convective flow across the arterial wall. The intima and media layers are assumed as homogeneous porous media. The results of the present study reveal that ATP concentration over the surface of SMCs and within the bulk of the media layer is significantly dependent on the distribution of cells. Moreover, the shear stress magnitude and distribution over the SMC surface are affected by transmural pressure and the deformation of the media layer of the aorta wall. This work reflects the fact that the second or even subsequent layers of SMCs may bear shear stresses of the same order of magnitude as the first layer does if cells are arranged in an arbitrary manner. This study has brought new insights into the simulation of the arterial wall, as the previous simplifications have been ignored. The configurations of SMCs used here with elliptic cross sections of SMCs closely resemble the physiological conditions of cells. Moreover, the deformation of SMCs with high transmural pressure which follows the media layer compaction has been studied for the first time. On the other hand, results demonstrate that LDL concentration through the intima and media layers changes significantly as wall layers compress with transmural pressure. It was also noticed that the fraction of leaky junctions across the endothelial cells and the area fraction of fenestral pores over the internal elastic lamina affect the LDL distribution dramatically through the thoracic aorta wall. The simulation techniques introduced in this work can also trigger new ideas for simulating porous media involved in any biomedical, biomechanical, chemical, and environmental engineering applications.

Studies of Eu- and Yb-induced Reconstructions on the Si(100) Surface

This thesis presents experimental studies of rare earth (RE) metal induced structures on Si(100) surfaces. Two divalent RE metal adsorbates, Eu and Yb, are investigated on nominally flat Si(100) and on vicinal, stepped Si(100) substrates. Several experimental methods have been applied, including scanning tunneling microscopy/spectroscopy (STM/STS), low energy electron diffraction (LEED), synchrotron radiation photoelectron spectroscopy (SR-PES), Auger electron spectroscopy (AES), thermal desorption spectroscopy (TDS), and work function change measurements (Δφ). Two stages can be distinguished in the initial growth of the RE/Si interface: the formation of a two-dimensional (2D) adsorbed layer at submonolayer coverage and the growth of a three-dimensional (3D) silicide phase at higher coverage. The 2D phase is studied for both adsorbates in order to discover whether they produce common reconstructions or reconstructions common to the other RE metals. For studies of the 3D phase Yb is chosen due to its ability to crystallize in a hexagonal AlB2 type lattice, which is the structure of RE silicide nanowires, therefore allowing for the possibility of the growth of one-dimensional (1D) wires. It is found that despite their similar electronic configuration, Eu and Yb do not form similar 2D reconstructions on Si(100). Instead, a wealth of 2D structures is observed and atomic models are proposed for the 2×3-type reconstructions. In addition, adsorbate induced modifications on surface morphology and orientational symmetry are observed. The formation of the Yb silicide phase follows the Stranski-Krastanov growth mode. Nanowires with the hexagonal lattice are observed on the flat Si(100) substrate, and moreover, an unexpectedly large variety of growth directions are revealed. On the vicinal substrate the growth of the silicide phase as 3D islands and wires depends drastically on the growth conditions. The conditions under which wires with high aspect ratio and single orientation parallel to the step edges can be formed are demonstrated.

Families of periodic horseshoe orbits in the restricted three-body problem

We compute families of symmetric periodic horseshoe orbits in the restricted three-body problem. Both the planar and three-dimensional cases are considered and several families are found.We describe how these families are organized as well as the behavior along and among the families of parameters such as the Jacobi constant or the eccentricity. We also determine the stability properties of individual orbits along the families. Interestingly, we find stable horseshoe-shaped orbit up to the quite high inclination of 17◦

Point sampling with uniformly distributed lines

In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms

Design and analysis of a transversal-flux switched-reluctance-linear-machine pole-pair

The Switched Reluctance technology is probably best suited for industrial low-speed or zerospeed applications where the power can be small but the torque or the force in linear movement cases might be relatively high. Because of its simple structure the SR-motor is an interesting alternative for low power applications where pneumatic or hydraulic linear drives are to be avoided. This study analyses the basic parts of an LSR-motor which are the two mover poles and one stator pole and which form the “basic pole pair” in linear-movement transversal-flux switchedreluctance motors. The static properties of the basic pole pair are modelled and the basic design rules are derived. The models developed are validated with experiments. A one-sided one-polepair transversal-flux switched-reluctance-linear-motor prototype is demonstrated and its static properties are measured. The modelling of the static properties is performed with FEM-calculations. Two-dimensional models are accurate enough to model the static key features for the basic dimensioning of LSRmotors. Three-dimensional models must be used in order to get the most accurate calculation results of the static traction force production. The developed dimensioning and modelling methods, which could be systematically validated by laboratory measurements, are the most significant contributions of this thesis.

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.

Epälineaaristen regressiomenetelmien vertaaminen robottikäden otemallinnuksessa

Tässä työssä verrattiin monikerrosperseptronin, radiaalikantafunktioverkon, tukivektoriregression ja relevanssivektoriregression soveltuvuutta robottikäden otemallinnukseen. Menetelmille ohjelmoitiin koeympäristö Matlabiin, jossa mallit koestettiin kolmiulotteisella kappaledatalla. Koejärjestely sisälsi kaksi vaihetta. Kokeiden ensimmäisessä vaiheessa menetelmille haettiin sopivat parametrit ja toisessa vaiheessa menetelmät koestettiin. Kokeilla kerättiin dataa menetelmien keskinäiseen vertailuun. Vertailussa huomioitiin laskentanopeus, koulutusaika ja tarkkuus. Tukivektoriregressio löydettiin potentiaaliseksi vaihtoehdoksi mallintamiseen. Tukivektoriregression koetuloksia analysoitiin muita menetelmiä enemmän hyvien koetulosten takia.

Advances in modelling of mechatronic systems: the toolset FASIM_C++ for the simulation of vehicle dynamics

The increasing complexity of controller systems, applied in modern passenger cars, requires adequate simulation tools. The toolset FASIM_C++, described in the following, uses complex vehicle models in three-dimensional vehicle dynamics simulation. The structure of the implemented dynamic models and the generation of the equations of motion applying the method of kinematic differentials is explained briefly. After a short introduction in methods of event handling, several vehicle models and applications like controller development, roll-over simulation and real-time-simulation are explained. Finally some simulation results are presented.

Application of a non isotropic turbulence model to stable atmospheric flows and dispersion over 3D topography

A non isotropic turbulence model is extended and applied to three dimensional stably stratified flows and dispersion calculations. The model is derived from the algebraic stress model (including wall proximity effects), but it retains the simplicity of the "eddy viscosity" concept of first order models. The "modified k-epsilon" is implemented in a three dimensional numerical code. Once the flow is resolved, the predicted velocity and turbulence fields are interpolated into a second grid and used to solve the concentration equation. To evaluate the model, various steady state numerical solutions are compared with small scale dispersion experiments which were conducted at the wind tunnel of Mitsubishi Heavy Industries, in Japan. Stably stratified flows and plume dispersion over three distinct idealized complex topographies (flat and hilly terrain) are studied. Vertical profiles of velocity and pollutant concentration are shown and discussed. Also, comparisons are made against the results obtained with the standard k-epsilon model.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

A spheroid-based 3-D culture model for pancreatic cancer drug testing, using the acid phosphatase assay

Current therapy for pancreatic cancer is multimodal, involving surgery and chemotherapy. However, development of pancreatic cancer therapies requires a thorough evaluation of drug efficacy in vitro before animal testing and subsequent clinical trials. Compared to two-dimensional culture of cell monolayer, three-dimensional (3-D) models more closely mimic native tissues, since the tumor microenvironment established in 3-D models often plays a significant role in cancer progression and cellular responses to the drugs. Accumulating evidence has highlighted the benefits of 3-D in vitro models of various cancers. In the present study, we have developed a spheroid-based, 3-D culture of pancreatic cancer cell lines MIAPaCa-2 and PANC-1 for pancreatic drug testing, using the acid phosphatase assay. Drug efficacy testing showed that spheroids had much higher drug resistance than monolayers. This model, which is characteristically reproducible and easy and offers rapid handling, is the preferred choice for filling the gap between monolayer cell cultures and in vivo models in the process of drug development and testing for pancreatic cancer.