This is a study that is focused on developing an individual design methodology for a centrifugal impeller and generating a mixed flow impeller for a small turbojet engine by using this methodology. The structure of the methodology is based on the design, modeling and the optimization processes, which are operated sequentially. The design process consists of engine design and compressor design codes operated together with a commercial design code. Design of Experiment methods and an in-house Neural Network code is used for the modeling phase. The optimization is based on an in-house code which is generated based on multidirectional search algorithm. The optimization problem is constructed by using the inhouse parametric design codes of the engine and the compressor. The goal of the optimization problem is to reach an optimum design which gives the best possible combination of the thrust and the fuel consumption for a small turbojet engine. The final combination of the design parameters obtained from the optimization study are used in order to generate the final design with the commercial design code. On the last part of the thesis a comparison of the final design and a standard radial flow impeller is made in order to clarify the benefit of the study. The results have been showed that a mixed flow compressor design is superior to a standard radial flow compressor in a small turbojet application.

Neben der Sicherheit für Lebensmittel stehen auch immer mehr die Lebensmittelverpackungen im Fokus der Öffentlichkeit. Der Übergang von Stoffen aus der Verpackung in das Lebensmittel ist unerwünscht und gesetzlich reglementiert. Um den Verbraucherschutz zu gewährleisten, müssen Grenzwerte und gesetzliche Anforderungen eingehalten werden. Der Übergang von rechtlich geregelten und nicht geregelten Substanzen muss überprüft werden, was eine analytische Herausforderung darstellt. Die Untersuchung der migrierenden stickstoffhaltigen Substanzen aus Doseninnenbeschichtungen mittels eines Screenings aller migrierenden nicht-flüchtigen stickstoffhaltigen Substanzen mit einer molaren Masse kleiner 1000 Da wurde durchgeführt. Die Anwendbarkeit eines Stickstoff-selektiven Detektors für das Screening von Coating-Extrakten, welche stickstoffhaltige Verbindungen enthalten konnte gezeigt werden. Gegenstand der Untersuchung waren Vernetzersubstanzen, Flüssiglacke sowie Migrate der fertigen Beschichtung. Stickstoffhaltige potenziell migrierende Substanzen wurden zunächst in den Ausgangsmaterialien der Beschichtung identifiziert, um diese dann im Migrat der Beschichtung zu quantifizieren. Es sollte gezeigt werden, ob Substanzen, welche als Ausgangsstoffe im Lack eingesetzt werden, oder entstehende Reaktionsprodukte in ein Lebensmittelsimulanz migrieren. Um die Relevanz der migrierenden stickstoffhaltigen Verbindungen im Hinblick auf weitere nicht stickstoffhaltige migrierende Verbindungen zu zeigen, wurde das Gesamtmigrat der zur Verfügung stehenden Coatings bestimmt. Es zeigte sich, dass der Anteil von NCS an den insgesamt migrierenden Verbindungen zwischen 0,2 und 6,3 % liegt. Der Fokus des zweiten Teils der vorliegenden Arbeit liegt auf Lebensmittelverpackungen aus Kunststoff. Zunächst wurde eine HPLC-Methode mit Hilfe des Verdampfungslichtstreudetektors zur Bestimmung der Gesamtmigration mit dem Simulanz Sonnenblumenöl etabliert werden. Das Ziel dieser Untersuchungen ist, den Einfluss von Temperatur, Zeit und Schichtdicke auf das Migrationsverhalten von Siegelschichten für den Hochtemperaturbereich (> 70 °C) mit fetthaltigen Lebensmitteln mit Hilfe von statistischer Versuchsplanung vorherzusagen. Mit Hilfe einer statistischen Software konnte eine Regressionsgleichung zur Berechnung der Gesamtmigration auf der Grundlage eines Box-Behnken-Versuchsplans erstellt werden. Dabei hatte die Temperatur den größten Einfluss auf die Gesamtmigration. Die Einflüsse von Zeit und Schichtdicke waren im untersuchten Bereich des hier gezeigten Modells linear und stiegen mit Erhöhung der Temperatur. Weiterhin konnte je 10 °C Temperaturerhöhung eine Verdopplung des ermittelten Gesamtmigrationswertes beobachtet werden. Die Bestimmung der Additive aus den Ersatzsimulanzien 95 % Ethanol und Iso-Octan von Verpackungen sollte ebenfalls gezeigt werden. Ein Screening-Gradient zur Bestimmung von 25 Additiven in den Ersatzsimulanzien wurde etabliert. Die Identifizierung der migrierenden Additive erfolgte mittels der Detektoren UVD (DAD), FLD, ELSD und CLND. Mit Hilfe der verschiedenen Detektionsarten ist es möglich, die strukturelle Vielfalt der eingesetzten Additive abzudecken. Eine Absicherung der Ergebnisse konnte zudem über MS-Detektion erfolgen. Mit Hilfe der Untersuchungen wurden die gesamtmigrierenden Substanzen aus Verbundfolien zu 50 % (95 % Ethanol-Migrat) bzw. 10 % (Isooctan-Migrat) aufgeklärt. Die Konzentration der quantifizierten Additive zeigte im Verhältnis gesehen annähernd gleiche Werte. Der Unterschied in den ermittelten Gesamtmigraten (95 % Ethanol: 1,2 mg/dm2, Iso-Octan: 5,6 mg/dm2) konnte demnach nicht über die migrierenden Additive erklärt werden. Als weitere migrierende Substanzen wurden Ethylen-Oligomere identifiziert. Die Quantifizierung dieser erfolgte erstmals mit Hilfe der 1H-NMR-Spektroskopie. Die nahezu vollständige Aufklärung der Gesamtmigration einer Verbundfolie in den Ersatzsimulanzien konnte gezeigt werden. Die migrierenden Ethylen-Oligomere des Iso-Octan-Migrats wurden eingehender untersucht. Mit Hilfe von verschiedenen chromatographischen und spektroskopischen Methoden gelang eine Charakterisierung dieser im Migrat identifizierten Substanzen. / Besides the safety of food the focus on food packaging material increases in public. The migration of substances from the packaging into food is undesired and regulated by law. To ensure consumer protection legal limits and requirements have to be kept. The migration of regulated und not regulated substances has to be verified which means an analytical challenge. The determination of nitrogen containing substances (NCS) from food can coatings by screening of migrating, non-volatile substances with a molecular mass below 1000 Da from the coatings was carried out. The applicability of a nitrogen selective detector for the screening of coating extracts which contain nitrogen containing susbtances was shown. For the investigations crosslinking substances, liquid lacquers as well as migrates of the finished coatings have been available for determination. Nitrogen containing and potential migrating substances have been identified first in the raw marterial of the coating in order to quantify them in the migrates of the coating. It should be shown if substances from the raw materials or reaction products migrate into the food simulant. In order to show the relevance of the migrating nitrogen containing substances in respect to other non nitrogen containing compounds the overall migration of the available coatings was determined. It could be shown that the amount of NCS in the overall migrating substances was between 0.2 and 6.3 %. Focus of the second part of the work was on food packing made of plastic. First an HPLC-method with ELS detection for the determination of the overall migration in sunflower oil was developed. Purpose of this determination was to predict the influence of temperature, time and thickness of the layer on the migration behavior with fatty food of sealing layers in high temperature range (> 70 °C) by means of design of experiments. A statistical software computed a regression equation for the calculation the overall migration based on a Box-Behnken-Design. The highest influence could be shown for the temperature. The modell showed a duplication of the determined overall migration with 10 °C increase of temperature. The determination of plastic additives out of the 95 % ethanol and isooctane migrates of packaging material should also be conducted. An HPLC-screening method for the determination of 25 additives in the fat substitutes was established. The identification of the migrating additives was carried out with UV detection (DAD), FLD, ELSD and CLND. By means of the different detection systems it was possible to cover the structural diversity of the mainly used additives. To insure the results MS detection was used. By means of this investigations a clarification of the total migrating substances of a multilayer film was 50 % (95 % ethanol) and 10 % (isooctane), respectively. The concentration of the migrating substances on the scale of things is nearly identical. The difference in the overall migration (95 % ethanol: 1.2 mg/dm2, isooctane: 5.6 mg/dm2) can not be clarified by migration of additives. As other migrating substances ethylen oligomers can be identified. The quantification was carried out for the first time with 1H﷓NMR spectroscopy. An almost complete identification of migration substances of the overall migrate in food simulants can be shown. The migrating ethylen oligomers have been further investitgated. With the help of different chromatographic and spectroscopic methods a further characterisation of the migrating ethylen oligomers was successul.

The present project discusses the application of screening techniques in large-scale simulation models with the purpose of determining whether this kind of procedures could be a substitute for or a complement to simulation-based optimization for bottleneck identification and improvement. Based on sensitivity analysis, the screening techniques consist in finding the most important factors in simulation models where there are many factors, in which presumably only a few or some of these factors are important. The screening technique selected to be studied in this project is Sequential Bifurcation. This method consists in grouping the potentially important factors, dividing the groups continuously depending on the response generated from the model of the system under study. The results confirm that the application of the Sequential Bifurcation method can considerably reduce the simulation time because of the number of simulations needed, which decreased compared with the optimization study. Furthermore, by introducing two-factor interactions in the metamodel, the results are more accurate and may even be as accurate as the results from optimization. On the other hand, it has been found that the application of Sequential Bifurcation could become a problem in terms of accuracy when there are many storage buffers in the decision variables list. Due to all of these reasons, the screening techniques cannot be a complete alternative to simulation-based optimization. However, as shown in some initial results, the combination of these two methods could yield a promising roadmap for future research, which is highly recommended by the authors of this project.

This thesis presents a number of studies, where a multivariate approach was taken to construct models that predict wood species and thermo mechanical pulp brightness from roundwood of Norway spruce and Scots pine. The first and second studies produced multivariate prediction models for wood species from the bark of spruce and pine. These models can be used for wood species classification and would replace the manual log assessment that takes place today. Principal Component Analysis, PCA, and Partial least squares projections to Latent Structures, PLS, were used to predict the wood species from multivariate measurements recorded from the bark of spruce and pine. Two different kinds of measurements were employed, near-infrared spectroscopy and digital imaging. Both methods showed that it was possible to predict the wood species with a high accuracy. The third and fourth studies of the thesis are related to the wood storage of roundwood and the deterioration of wood that occurs during the storage. The third study used an experimental design with five storage factors that provided different conditions for the analysed wood. The experimental design made it possible to identify the factors and the interaction between factors, which were important for the ISO brightness of peroxide and dithionite bleached thermo mechanical pulp, TMP. The final study of the thesis used NIR spectroscopy for predicting the ISO brightness of bleached TMP. Spectra recorded from stored wood were used to construct PLS prediction models.

New techniques and approaches for organic synthesis, purification and biological testing are enabling pharmaceutical industries to produce and test increasing numbers of compounds every year. Surprisingly, this has not led to more new drugs reaching the market, prompting two questions – why is there not a better correlation between their efforts and output, and can it be improved? One possible way to make the drug discovery process more efficient is to ensure, at an early stage, that the tested compounds are diverse, representative and of high quality. In addition the biological evaluation systems have to be relevant and reliable. The diversity of the tested compounds could be ensured and the reliability of the biological assays improved by using Design Of Experiments (DOE) more frequently and effectively. However, DOE currently offers insufficient options for these purposes, so there is a need for new, tailor-made DOE strategies. The aim of the work underlying this thesis was to develop and evaluate DOE approaches for diverse compound selection and efficient assay optimisation. This resulted in the publication of two new DOE strategies; D-optimal Onion Design (DOOD) and Rectangular Experimental Designs for Multi-Unit Platforms (RED-MUP), both of which are extensions to established experimental designs. D-Optimal Onion Design (DOOD) is an extension to D-optimal design. The set of possible objects that could be selected is divided into layers and D-optimal selection is applied to each layer. DOOD enables model-based, but not model-dependent, selections in discrete spaces to be made, since the selections are not only based on the D-optimality criterion, but are also biased by the experimenter’s prior knowledge and specific needs. Hence, DOOD selections provide controlled diversity. Assay development and optimisation can be a major bottleneck restricting the progress of a project. Although DOE is a recognised tool for optimising experimental systems, there has been widespread unwillingness to use it for assay optimisation, mostly because of the difficulties involved in performing experiments according to designs in 96-, 384- and 1536- well formats. The RED-MUP framework combines classical experimental designs orthogonally onto rectangular experimental platforms, which facilitates the execution of DOE on these platforms and hence provides an efficient tool for assay optimisation. In combination, these two strategies can help uncovering the crossroads between biology and chemistry in drug discovery as well as lead to higher information content in the data received from biological evaluations, providing essential information for well-grounded decisions as to the future of the project. These two strategies can also help researchers identify the best routes to take at the crossroads linking biological and chemical elements of drug discovery programs.

Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as aircraft, power plants, etc., the prognostic activities have been limited to the component-level, primarily due to the complexity of large-scale engineering systems. However, the output of these prognostic algorithms can be practically useful for the system managers, operators, or maintenance personnel, only if it helps them in making decisions, which are based on system-level parameters. Therefore, there is an emerging need to build health assessment methodologies at the system-level. This research employs techniques from the field of design-of-experiments to build response surface metamodels at the system-level that are built on the foundations provided by component-level damage models.

This thesis illustrates parameter optimization of compressive strength, flexural strength and impact resistance of steel fiber reinforced high strength concrete (SFRHSC) by statistical design and analysis of experiments. Among several factors affecting the compressive strength, flexural strength and impact resistance of SFRHSC, five parameters that maximize all of the responses have been chosen as the most important ones as age of testing, binder type, binder amount, curing type and steel fiber volume fraction. Taguchi and regression analysis techniques have been used to evaluate L27(313) Taguchi&amp / #65533 / s orthogonal array and 3421 full factorial experimental design results. Signal to noise ratio transformation and ANOVA have been applied to the results of experiments in Taguchi analysis. Response surface methodology has been employed to optimize the best regression model selected for all the three responses. In this study Charpy Impact Test, which is a different kind of impact test, have been applied to SFRHSC for the first time. The mean of compressive strength, flexural strength and impact resistance have been observed as around 125 MPa, 14.5 MPa and 9.5 kgf.m respectively which are very close to the desired values. Moreover, this study is unique in the sense that the derived models enable the identification of underlying primary factors and their interactions that influence the modeled responses of steel fiber reinforced high strength concrete.

本論文針對防丟器的剖面進行追蹤分析。防丟器包含發射器及接收器，發射器會發射訊號，接收器會記錄RSSI (Receive Signal Strength Index)與發射點數，其中RSSI表示訊號的強度。在工程理論上，RSSI與距離具有函數關係；然而環境中的干擾及事件發生都會影響此函數關係，特別是事件發生會嚴重地改變此函數關係，因此論文主要目的在於區別事件是否發生。 　　所謂的剖面指的是變數之間的函數關係，而論文中的剖面追蹤是利用管制圖的概念，用管制圖來監控剖面的參數估計值。如果管制圖上的點子出界，則表示事件發生而導致失控。 　　本論文以腳踏車是否被偷為例，嘗試一些實驗後找出顯著影響的因子設計實驗，包含17種腳踏車未被偷之情境與18種腳踏車被偷情境；欲利用未被偷的實驗建立試驗管制圖，而以被偷之情境來追蹤，用以驗證管制圖之有效性。 　　論文中主要透過分析防丟器產生的RSSI與距離的剖面、距離與發射點數的剖面來探討事件是否發生。另外剖面追蹤其實是種事後追蹤的方法，為了能即時追蹤，本論文亦採用預測區間的方式，來追蹤事件是否發生。 　　本論文建議監控距離與發射點數的剖面，因該方法的表現最好，另外建議增加防丟器上能紀錄距離的功能，此方法會更加合適。 　　本論文提出的即時追蹤方式並沒有特別好，因此一個比較好的即時追蹤方法是未來值得研究的方向。 / The device of Babyfinder is designed to detect if an event occurs. The Babyfinder includes transceiver and receiver. The signal strength, Received Signal Strength Indicator (RSSI), generates once there are distances between transceiver and receiver. In wireless communication theory, the relationship between RSSI and distance should be expressed by the model that RSSI = a + b ln (distance) Nevertheless, some circumstance noises and user noises (or common causes), and/or events (special causes) may affect the variation of RSSI. Since the occurrence of events may change the functional relationship of RSSI and distance, to distinguish if the functional relationship is changed by the occurred events is the subject of this study. This study designs some events and noises experiments based on the real noise factors and special events. Two monitoring schemes are proposed to distinguish the occurred events and noise circumstance. One is the profile monitoring scheme, the other is the real time monitoring scheme. The two proposed approaches of profile monitoring scheme are considered to monitor the profile of RSSI and distance and that of distance and the number of transmitting points, respectively. The profile monitoring approach for distance and the number of transmitting points shows better performance. However, the profile monitoring is an after-event tracing approach. It cannot detect the occurred events in time. A better approach of real-time monitoring approach is worth to be proposed in the future study.

Human health is a complex and wide-ranging subject far beyond nutrition and physical exercise. Still, these factors have a huge impact on global health by their ability to prevent diseases and thus promote health. Thus, to identify health risks and benefits, it is necessary to reveal the underlying mechanisms of nutrition and exercise, which in many cases follows a complex chain of events. As a consequence, current health research is generating massive amounts of data from anthropometric parameters, genes, proteins, small molecules (metabolites) et cetera, with the intent to understand these mechanisms. For the study of health responses, especially related to physical exercise and nutrition, alterations in small molecules (metabolites) are in most cases immediate and located close to the phenotypic level and could therefore provide early signs of metabolic imbalances. Since there are roughly as many different responses to exercise and nutrients as there are humans, this quest is highly multifaceted and will benefit from an interpretation of treatment effects on a general as well as on an individual level. This thesis involves the application of chemometric methods to the study of global metabolic reactions, i.e. metabolomics, in a strategy coined predictive metabolomics. Via the application of predictive metabolomics an extensive hypothesis-free biological interpretation has been carried out of metabolite patterns in blood, acquired using gas chromatography-mass spectrometry (GC-MS), related to physical exercise, nutrition and diet, all in the context of human health. In addition, the chemometrics methodology have computational benefits concerning the extraction of relevant information from information-rich data as well as for interpreting general treatment effects and individual responses, as exemplified throughout this work. Health concerns all lifestages, thus this thesis presents a strategic framework in combination with comprehensive interpretations of metabolite patterns throughout life. This includes a broad range of human studies revealing metabolic patterns related to the impact of physical exercise, macronutrient modulation and different fitness status in young healthy males, short and long term dietary treatments in overweight post menopausal women as well as metabolic responses related to probiotics treatment and early development in infants. As a result, the studies included in the thesis have revealed metabolic patterns potentially indicative of an anti-catabolic response to macronutrients in the early recovery phase following exercise. Moreover, moderate differences in the metabolome associated with cardiorespiratory fitness level were detected, which could be linked to variation in the inflammatory and antioxidaive defense system. This work also highlighted mechanistic information that could be connected to dietary related weight loss in overweight and obese postmenopausal women in relation to short as well as long term dietary effects based on different macronutrient compositions. Finally, alterations were observed in metabolic profiles in relation to probiotics treatment in the second half of infancy, suggesting possible health benefits of probiotics supplementation at an early age. / Embargo until 2012-06-01

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Jogos educacionais constituem em uma importante ferramenta de ensino na área de Engenharia de Software, onde, muitas vezes, os alunos não passam por nenhum mecanismo de treinamento prático. Um jogo educacional de qualidade tem que ter objetivos educacionais bem definidos, motivar os alunos e efetivar a aprendizagem dos conteúdos. A aplicação de jogos no Ensino de Engenharia de Software deve ser realizada de forma sistemática e controlada com base em avaliação. A técnica Estatística de Experimentação permite a medição e a análise das variáveis envolvidas no processo de aplicação de jogos para que estes possam ser aplicados com qualidade. Para definir melhor os experimentos no uso de jogos para o ensino de Engenharia de Software, este trabalho propõe diretrizes para o planejamento de experimentos em jogos educacionais, de forma que permita verificar a influência e a significância da utilização desses jogos no ensino e aprendizado dos conceitos de Engenharia de Software. Um experimento com o SimulES-W foi realizado seguindo essas diretrizes, onde foi possível ser demonstrada sua aplicabilidade e simplicidade em sua definição. A experiência de uso do SimulES-W mostra que aprender com jogos de computador é divertido, interativo e que, apesar dos resultados obtidos não serem significativos estatisticamente, de certa forma contribui para o ensino da Engenharia de Software, não sendo necessariamente um conhecimento prévio do conteúdo. / Educational games constitute an important teaching tool in the area of Software Engineering, where, often, students do not pass through any mechanism for hands-on training. A quality educational game must have well-defined educational goals, motivate students and make effective learning of the content. The application of games in teaching Software engineering must be carried out in a systematic and controlled on the basis of evaluation. The statistical technique of experimentation allows the measurement and analysis of the variables involved in the process of applying for these games can be applied with quality. To further define the experiments in the use of games for teaching Software Engineering, this paper proposes guidelines for the design of experiments in educational games, in order to verify the influence and significance of the use of these games in the teaching and learning of the concepts of Software engineering. An experiment with SimulES-W was conducted following these guidelines, which may be demonstrated its applicability and simplicity in its definition. The experience of use of the SimulES-W shows that learning with computer games is fun, interactive and that, despite the results obtained are not statistically significant, somehow contributes to the teaching of Software Engineering, not necessarily a prior knowledge of the content.