Öljynjalostamon tyhjöyksikön esilämmitysuunin optimointi

Työn tarkoituksena oli vertailla kahta kaupallista prosessiuunisimulointiohjelmaa sekä selvittää onko toinen ohjelma soveltuva Neste Jacobs Oy:n käyttöön. Tavoitteena oli selvittää ohjelmien ominaisuuksien eroja ja rajoitteita sekä tuloksien yhdenmukaisuutta. Kirjallisuusosassa perehdyttiin prosessiuunien toimintaperiaatteisiin, yleisiin mitoitusperiaatteisiin ja säteilylämmönsiirron perusteisiin. Kirjallisuusosassa käsiteltiin myös prosessiuunien polttimien toimintaa ja NOx-päästöjä vähentäviä polttotekniikoita. Molemmilla laskentaohjelmilla laadittiin kuumaöljy- ja tyhjöuuni, joiden tuloksia vertailtiin tärkeimpien prosessiarvojen perusteella ja toisen ohjelman osalta myös laitevalmistajan ilmoittamiin arvoihin. Tällä ohjelmalla tutkittiin tyhjöuunin höyrynruiskutuksen ja koksaantumisen vaikutuksia prosessiin sekä säteilyosan leveyden muutoksen vaikutusta säteilylämmönsiirtoon. Ohjelmien ominaisuuksien keskeisimmät erot liittyivät kaksifaasivirtauksen laskentaan, prosessiaineen massavirran rajoituksiin, ilman esilämmittimen käyttöön ja laskentamallien paineen kontrollointiin. Tulokset erosivat savukaasun ja tuubien lämpötilojen ja painehäviön laskennassa. Tuloksien ja ominaisuuksien perusteella toisen ohjelman ei todettu olevan täysin soveltuva Neste Jacobs Oy:n käyttöön.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

On the q=1/2 non-extensive maximum entropy distribution

A detailed mathematical analysis on the q = 1/2 non-extensive maximum entropydistribution of Tsallis' is undertaken. The analysis is based upon the splitting of such adistribution into two orthogonal components. One of the components corresponds to theminimum norm solution of the problem posed by the fulfillment of the a priori conditionson the given expectation values. The remaining component takes care of the normalizationconstraint and is the projection of a constant onto the Null space of the "expectation-values-transformation"

A non-extensive maximum entropy based regulations method for bad conditioned inverse problems

A regularization method based on the non-extensive maximum entropy principle is devised. Special emphasis is given to the q=1/2 case. We show that, when the residual principle is considered as constraint, the q=1/2 generalized distribution of Tsallis yields a regularized solution for bad-conditioned problems. The so devised regularized distribution is endowed with a component which corresponds to the well known regularized solution of Tikhonov (1977).

Frames: a maximum entropy statistical estimate of the inverse problem

A maximum entropy statistical treatment of an inverse problem concerning frame theory is presented. The problem arises from the fact that a frame is an overcomplete set of vectors that defines a mapping with no unique inverse. Although any vector in the concomitant space can be expressed as a linear combination of frame elements, the coefficients of the expansion are not unique. Frame theory guarantees the existence of a set of coefficients which is “optimal” in a minimum norm sense. We show here that these coefficients are also “optimal” from a maximum entropy viewpoint.

Laser Cutting of Austenitic Stainless Steel with a High Quality Laser Beam

The thin disk and fiber lasers are new solid-state laser technologies that offer a combinationof high beam quality and a wavelength that is easily absorbed by metal surfacesand are expected to challenge the CO2 and Nd:YAG lasers in cutting of metals ofthick sections (thickness greater than 2mm). This thesis studied the potential of the disk and fiber lasers for cutting applications and the benefits of their better beam quality. The literature review covered the principles of the disk laser, high power fiber laser, CO2 laser and Nd:YAG laser as well as the principle of laser cutting. The cutting experiments were made with thedisk, fiber and CO2 lasers using nitrogen as an assist gas. The test material was austenitic stainless steel of sheet thickness 1.3mm, 2.3mm, 4.3mm and 6.2mm for the disk and fiber laser cutting experiments and sheet thickness of 1.3mm, 1.85mm, 4.4mm and 6.4mm for the CO2 laser cutting experiments. The experiments focused on the maximum cutting speeds with appropriate cut quality. Kerf width, cutedge perpendicularity and surface roughness were the cut characteristics used to analyze the cut quality. Attempts were made to draw conclusions on the influence of high beam quality on the cutting speed and cut quality. The cutting speeds were enormous for the disk and fiber laser cutting experiments with the 1.3mm and 2.3mm sheet thickness and the cut quality was good. The disk and fiber laser cutting speeds were lower at 4.3mm and 6.2mm sheet thickness but there was still a considerable percentage increase in cutting speeds compared to the CO2 laser cutting speeds at similar sheet thickness. However, the cut quality for 6.2mm thickness was not very good for the disk and fiber laser cutting experiments but could probably be improved by proper selection of cutting parameters.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

The maximum voltage drop in an on-chip power distribution network: analysis of square, triangular and hexagonal power pad arrangements

A mathematical model of the voltage drop which arises in on-chip power distribution networks is used to compare the maximum voltage drop in the case of different geometric arrangements of the pads supplying power to the chip. These include the square or Manhattan power pad arrangement, which currently predominates, as well as equilateral triangular and hexagonal arrangements. In agreement with the findings in the literature and with physical and SPICE models, the equilateral triangular power pad arrangement is found to minimize the maximum voltage drop. This headline finding is a consequence of relatively simple formulas for the voltage drop, with explicit error bounds, which are established using complex analysis techniques, and elliptic functions in particular.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.