894 resultados para Model-Based Design


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The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

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The penetration of PKI technology in the market is moving slowly due to interoperability concerns. Main causes are not technical but political and social since there is no trust development model that appropriately deals with multidomain PKIs. We propose a new architecture that on one hand considers that trust is not an homogeneous property but tied to a particular relation, and on the other hand, trust management must be performed through specialized entities that can evaluate its risks and threads. The model is based on trust certificate lists that allows users to hold a personalized trust view without having to get involved in technical details. The model dynamically adapts tothe context changes thanks to a new certificate extension, we have called TrustProviderLink (TPL).

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BACKGROUND: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration. AIM: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function. METHODS: A highly accelerated compressed-sensing multi-slice cine sequence (CS-cineCMR) was combined with a non-model-based 3D reconstruction method to measure LA volumes with high temporal and spatial resolution during a single breath-hold. This approach was validated in LA phantoms of different shapes and applied in 3 patients. In addition, the influence of slice orientations on accuracy was evaluated in the LA phantoms for the new approach in comparison with a conventional model-based biplane area-length reconstruction. As a reference in patients, a self-navigated high-resolution whole-heart 3D dataset (3D-HR-CMR) was acquired during mid-diastole to yield accurate LA volumes. RESULTS: Phantom studies. LA volumes were accurately measured by CS-cineCMR with a mean difference of -4.73 ± 1.75 ml (-8.67 ± 3.54%, r2 = 0.94). For the new method the calculated volumes were not significantly different when different orientations of the CS-cineCMR slices were applied to cover the LA phantoms. Long-axis "aligned" vs "not aligned" with the phantom long-axis yielded similar differences vs the reference volume (-4.87 ± 1.73 ml vs. -4.45 ± 1.97 ml, p = 0.67) and short-axis "perpendicular" vs. "not-perpendicular" with the LA long-axis (-4.72 ± 1.66 ml vs. -4.75 ± 2.13 ml; p = 0.98). The conventional bi-plane area-length method was susceptible for slice orientations (p = 0.0085 for the interaction of "slice orientation" and "reconstruction technique", 2-way ANOVA for repeated measures). To use the 3D-HR-CMR as the reference for LA volumes in patients, it was validated in the LA phantoms (mean difference: -1.37 ± 1.35 ml, -2.38 ± 2.44%, r2 = 0.97). Patient study: The CS-cineCMR LA volumes of the mid-diastolic frame matched closely with the reference LA volume (measured by 3D-HR-CMR) with a difference of -2.66 ± 6.5 ml (3.0% underestimation; true LA volumes: 63 ml, 62 ml, and 395 ml). Finally, a high intra- and inter-observer agreement for maximal and minimal LA volume measurement is also shown. CONCLUSIONS: The proposed method combines a highly accelerated single-breathhold compressed-sensing multi-slice CMR technique with a non-model-based 3D reconstruction to accurately and reproducibly measure LA volumes and function.

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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

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This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

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Chemical-looping combustion (CLC) is a novel combustion technology with inherent separation of the greenhouse gas CO2. The technique typically employs a dual fluidized bed system where a metal oxide is used as a solid oxygen carrier that transfers the oxygen from combustion air to the fuel. The oxygen carrier is looping between the air reactor, where it is oxidized by the air, and the fuel reactor, where it is reduced by the fuel. Hence, air is not mixed with the fuel, and outgoing CO2 does not become diluted by the nitrogen, which gives a possibility to collect the CO2 from the flue gases after the water vapor is condensed. CLC is being proposed as a promising and energy efficient carbon capture technology, since it can achieve both an increase in power station efficiency simultaneously with low energy penalty from the carbon capture. The outcome of a comprehensive literature study concerning the current status of CLC development is presented in this thesis. Also, a steady state model of the CLC process, based on the conservation equations of mass and energy, was developed. The model was used to determine the process conditions and to calculate the reactor dimensions of a 100 MWth CLC system with bunsenite (NiO) as oxygen carrier and methane (CH4) as fuel. This study has been made in Oxygen Carriers and Their Industrial Applications research project (2008 – 2011), funded by the Tekes – Functional Material program. I would like to acknowledge Tekes and participating companies for funding and all project partners for good and comfortable cooperation.

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Calcium oxide looping is a carbon dioxide sequestration technique that utilizes the partially reversible reaction between limestone and carbon dioxide in two interconnected fluidised beds, carbonator and calciner. Flue gases from a combustor are fed into the carbonator where calcium oxide reacts with carbon dioxide within the gases at a temperature of 650 ºC. Calcium oxide is transformed into calcium carbonate which is circulated into the regenerative calciner, where calcium carbonate is returned into calcium oxide and a stream of pure carbon dioxide at a higher temperature of 950 ºC. Calcium oxide looping has proved to have a low impact on the overall process efficiency and would be easily retrofitted into existing power plants. This master’s thesis is done in participation to an EU funded project CaOling as a part of the Lappeenranta University of Technology deliverable, reactor modelling and scale-up tools. Thesis concentrates in creating the first model frame and finding the physically relevant phenomena governing the process.

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This thesis presents a set of methods and models for estimation of iron and slag flows in the blast furnace hearth and taphole. The main focus was put on predicting taphole flow patterns and estimating the effects of various taphole conditions on the drainage behavior of the blast furnace hearth. All models were based on a general understanding of the typical tap cycle of an industrial blast furnace. Some of the models were evaluated on short-term process data from the reference furnace. A computational fluid dynamics (CFD) model was built and applied to simulate the complicated hearth flows and thus to predict the regions of the hearth exerted to erosion under various operating conditions. Key boundary variables of the CFD model were provided by a simplified drainage model based on the first principles. By examining the evolutions of liquid outflow rates measured from the furnace studied, the drainage model was improved to include the effects of taphole diameter and length. The estimated slag delays showed good agreement with the observed ones. The liquid flows in the taphole were further studied using two different models and the results of both models indicated that it is more likely that separated flow of iron and slag occurs in the taphole when the liquid outflow rates are comparable during tapping. The drainage process was simulated with an integrated model based on an overall balance analysis: The high in-furnace overpressure can compensate for the resistances induced by the liquid flows in the hearth and through the taphole. Finally, a recently developed multiphase CFD model including interfacial forces between immiscible liquids was developed and both the actual iron-slag system and a water-oil system in laboratory scale were simulated. The model was demonstrated to be a useful tool for simulating hearth flows for gaining understanding of the complex phenomena in the drainage of the blast furnace.

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Tämä kandidaatintyö on kirjallisuustutkimus, joka selventää lukijalle mitä tarkoittaa käsite Model-Based Management (MBM). Työssä tarkastellaan keskeisiä suuntauksia, joihin MBM pohjautuu. Lisäksi tutkitaan miksi MBM on kehittynyt ja miten sitä voidaan hyödyntää yrityksissä. Nykyiset käytössä olevat johtamismallit ovat aikaansa jäljessä, eivätkä ne hyödynnä nykyteknologian luomia mahdollisuuksia. Teknologian kehityksen myötä tiedonsaanti on helpottunut ja monipuolistunut. Globalisaation seurauksena organisaatioiden toimintaympäristöt ovat monimutkaistuneet ja organisaatioiden rakenteet ovat muuttuneet. Tiedonsaannin helppous yhdistettynä yritysten monimutkaisiin rakenteisiin aiheuttaa ongelmia yrityksen johtamisen ja hallinnan kannalta. Johtajat eivät kykene ymmärtämään kokonaisuuksia, joiden kanssa he ovat tekemisissä. Kokonaisuuksien ymmärtämisessä hyödynnetään systeemiajattelua ja mallintamista. Malleja on käytetty yrityksissä jo pitkään johtamisen apuna. MBM pohjautuu siihen, että mallit ovat johtamisen lähtökohta. Mallit auttavat ymmärtämään kokonaisuuksia ja hahmottamaan eri tekijöiden yhteyksiä toisiinsa. MBM:n näkökulmasta organisaation rakenteiden mallintaminen on elintärkeää sen toimintakyvyn kannalta.