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Building interoperation among separately developed software units requires checking their conceptual assumptions and constraints. However, eliciting such assumptions and constraints is time consuming and is a challenging task as it requires analyzing each of the interoperating software units. To address this issue we proposed a new conceptual interoperability analysis approach which aims at decreasing the analysis cost and the conceptual mismatches between the interoperating software units. In this report we present the design of a planned controlled experiment for evaluating the effectiveness, efficiency, and acceptance of our proposed conceptual interoperability analysis approach. The design includes the study objectives, research questions, statistical hypotheses, and experimental design. It also provides the materials that will be used in the execution phase of the planned experiment.
In 2006 Jeffrey Achter proved that the distribution of divisor class groups of degree 0 of function fields with a fixed genus and the distribution of eigenspaces in symplectic similitude groups are closely related to each other. Gunter Malle proposed that there should be a similar correspondence between the distribution of class groups of number fields and the distribution of eigenspaces in ceratin matrix groups. Motivated by these results and suggestions we study the distribution of eigenspaces corresponding to the eigenvalue one in some special subgroups of the general linear group over factor rings of rings of integers of number fields and derive some conjectural statements about the distribution of \(p\)-parts of class groups of number fields over a base field \(K_{0}\). Where our main interest lies in the case that \(K_{0}\) contains the \(p\)th roots of unity, because in this situation the \(p\)-parts of class groups seem to behave in an other way like predicted by the popular conjectures of Henri Cohen and Jacques Martinet. In 2010 based on computational data Malle has succeeded in formulating a conjecture in the spirit of Cohen and Martinet for this case. Here using our investigations about the distribution in matrixgroups we generalize the conjecture of Malle to a more abstract level and establish a theoretical backup for these statements.
This dissertation focuses on the evaluation of technical and environmental sustainability of water distribution systems based on scenario analysis. The decision support system is created to assist in the decision making-process and to visualize the results of the sustainability assessment for current and future populations and scenarios. First, a methodology is developed to assess the technical and environmental sustainability for the current and future water distribution system scenarios. Then, scenarios are produced to evaluate alternative solutions for the current water distribution system as well as future populations and water demand variations. Finally, a decision support system is proposed using a combination of several visualization approaches to increase the data readability and robustness for the sustainability evaluations of the water distribution system.
The technical sustainability of a water distribution system is measured using the sustainability index methodology which is based on the reliability, resiliency and vulnerability performance criteria. Hydraulic efficiency and water quality requirements are represented using the nodal pressure and water age parameters, respectively. The U.S. Environmental Protection Agency EPANET software is used to simulate hydraulic (i.e. nodal pressure) and water quality (i.e. water age) analysis in a case study. In addition, the environmental sustainability of a water network is evaluated using the “total fresh water use” and “total energy intensity” indicators. For each scenario, multi-criteria decision analysis is used to combine technical and environmental sustainability criteria for the study area.
The technical and environmental sustainability assessment methodology is first applied to the baseline scenario (i.e. the current water distribution system). Critical locations where hydraulic efficiency and water quality problems occur in the current system are identified. There are two major scenario options that are considered to increase the sustainability at these critical locations. These scenarios focus on creating alternative systems in order to test and verify the technical and environmental sustainability methodology rather than obtaining the best solution for the current and future water distribution systems. The first scenario is a traditional approach in order to increase the hydraulic efficiency and water quality. This scenario includes using additional network components such as booster pumps, valves etc. The second scenario is based on using reclaimed water supply to meet the non-potable water demand and fire flow. The fire flow simulation is specifically included in the sustainability assessment since regulations have significant impact on the urban water infrastructure design. Eliminating the fire flow need from potable water distribution systems would assist in saving fresh water resources as well as to reduce detention times.
The decision support system is created to visualize the results of each scenario and to effectively compare these results with each other. The EPANET software is a powerful tool used to conduct hydraulic and water quality analysis but for the decision support system purposes the visualization capabilities are limited. Therefore, in this dissertation, the hydraulic and water quality simulations are completed using EPANET software and the results for each scenario are visualized by combining several visualization techniques in order to provide a better data readability. The first technique introduced here is using small multiple maps instead of the animation technique to visualize the nodal pressure and water age parameters. This technique eliminates the change blindness and provides easy comparison of time steps. In addition, a procedure is proposed to aggregate the nodes along the edges in order to simplify the water network. A circle view technique is used to visualize two values of a single parameter (i.e. the nodal pressure or water age). The third approach is based on fitting the water network into a grid representation which assists in eliminating the irregular geographic distribution of the nodes and improves the visibility of each circle view. Finally, a prototype for an interactive decision support tool is proposed for the current population and water demand scenarios. Interactive tools enable analyzing of the aggregated nodes and provide information about the results of each of the current water distribution scenarios.
The recognition of day-to-day activities is still a very challenging and important research topic. During recent years, a lot of research has gone into designing and realizing smart environ- ments in different application areas such as health care, maintenance, sports or smart homes. As a result, a large amount of sensor modalities were developed, different types of activity and context recognition services were implemented and the resulting systems were benchmarked using state-of-the-art evaluation techniques. However, so far hardly any of these approaches have found their way into the market and consequently into the homes of real end-users on a large scale. The reason for this is, that almost all systems have one or more of the following characteristics in common: expensive high-end or prototype sensors are used which are not af- fordable or reliable enough for mainstream applications; many systems are deployed in highly instrumented environments or so-called "living labs", which are far from real-life scenarios and are often evaluated only in research labs; almost all systems are based on complex system con- figurations and/or extensive training data sets, which means that a large amount of data must be collected in order to install the system. Furthermore, many systems rely on a user and/or environment dependent training, which makes it even more difficult to install them on a large scale. Besides, a standardized integration procedure for the deployment of services in existing environments and smart homes has still not been defined. As a matter of fact, service providers use their own closed systems, which are not compatible with other systems, services or sensors. It is clear, that these points make it nearly impossible to deploy activity recognition systems in a real daily-life environment, to make them affordable for real users and to deploy them in hundreds or thousands of different homes.
This thesis works towards the solution of the above mentioned problems. Activity and context recognition systems designed for large-scale deployment and real-life scenarios are intro- duced. Systems are based on low-cost, reliable sensors and can be set up, configured and trained with little effort, even by technical laymen. It is because of these characteristics that we call our approach "minimally invasive". As a consequence, large amounts of training data, that are usu- ally required by many state-of-the-art approaches, are not necessary. Furthermore, all systems were integrated unobtrusively in real-world/similar to real-world environments and were evalu- ated under real-life, as well as similar to real-life conditions. The thesis addresses the following topics: First, a sub-room level indoor positioning system is introduced. The system is based on low-cost ceiling cameras and a simple computer vision tracking approach. The problem of user identification is solved by correlating modes of locomotion patterns derived from the trajectory of unidentified objects and on-body motion sensors. Afterwards, the issue of recognizing how and what mainstream household devices have been used for is considered. Based on a low-cost microphone, the water consumption of water-taps can be approximated by analyzing plumbing noise. Besides that, operating modes of mainstream electronic devices were recognized by using rule-based classifiers, electric current features and power measurement sensors. As a next step, the difficulty of spotting subtle, barely distinguishable hand activities and the resulting object interactions, within a data set containing a large amount of background data, is addressed. The problem is solved by introducing an on-body core system which is configured by simple, one-time physical measurements and minimal data collections. The lack of large training sets is compensated by fusing the system with activity and context recognition systems, that are able to reduce the search space observed. Amongst other systems, previously introduced approaches and ideas are revisited in this section. An in-depth evaluation shows the impact of each fusion procedure on the performance and run-time of the system. The approaches introduced are able to provide significantly better results than a state-of-the-art inertial system using large amounts of training data. The idea of using unobtrusive sensors has also been applied to the field of behavior analysis. Integrated smartphone sensors are used to detect behavioral changes of in- dividuals due to medium-term stress periods. Behavioral parameters related to location traces, social interactions and phone usage were analyzed to detect significant behavioral changes of individuals during stressless and stressful time periods. Finally, as a closing part of the the- sis, a standardization approach related to the integration of ambient intelligence systems (as introduced in this thesis) in real-life and large-scale scenarios is shown.
Test rig optimization
(2014)
Designing good test rigs for fatigue life tests is a common task in the auto-
motive industry. The problem to find an optimal test rig configuration and
actuator load signals can be formulated as a mathematical program. We in-
troduce a new optimization model that includes multi-criteria, discrete and
continuous aspects. At the same time we manage to avoid the necessity to
deal with the rainflow-counting (RFC) method. RFC is an algorithm, which
extracts load cycles from an irregular time signal. As a mathematical func-
tion it is non-convex and non-differentiable and, hence, makes optimization
of the test rig intractable.
The block structure of the load signals is assumed from the beginning.
It highly reduces complexity of the problem without decreasing the feasible
set. Also, we optimize with respect to the actuators’ positions, which makes
it possible to take torques into account and thus extend the feasible set. As
a result, the new model gives significantly better results, compared with the
other approaches in the test rig optimization.
Under certain conditions, the non-convex test rig problem is a union of
convex problems on cones. Numerical methods for optimization usually need
constraints and a starting point. We describe an algorithm that detects each
cone and its interior point in a polynomial time.
The test rig problem belongs to the class of bilevel programs. For every
instance of the state vector, the sum of functions has to be maximized. We
propose a new branch and bound technique that uses local maxima of every
summand.
Edgeworth expansions have been introduced as a generalization of the central limit theorem and allow to investigate the convergence properties of sums of i.i.d. random variables. We consider triangular arrays of lattice random vectors and obtain a valid Edgeworth expansion for this case. The presented results can be used, for example, to study the convergence behavior of lattice models.
In the theory of option pricing one is usually concerned with evaluating expectations under the risk-neutral measure in a continuous-time model.
However, very often these values cannot be calculated explicitly and numerical methods need to be applied to approximate the desired quantity. Monte Carlo simulations, numerical methods for PDEs and the lattice approach are the methods typically employed. In this thesis we consider the latter approach, with the main focus on binomial trees.
The binomial method is based on the concept of weak convergence. The discrete-time model is constructed so as to ensure convergence in distribution to the continuous process. This means that the expectations calculated in the binomial tree can be used as approximations of the option prices in the continuous model. The binomial method is easy to implement and can be adapted to options with different types of payout structures, including American options. This makes the approach very appealing. However, the problem is that in many cases, the convergence of the method is slow and highly irregular, and even a fine discretization does not guarantee accurate price approximations. Therefore, ways of improving the convergence properties are required.
We apply Edgeworth expansions to study the convergence behavior of the lattice approach. We propose a general framework, that allows to obtain asymptotic expansion for both multinomial and multidimensional trees. This information is then used to construct advanced models with superior convergence properties.
In binomial models we usually deal with triangular arrays of lattice random vectors. In this case the available results on Edgeworth expansions for lattices are not directly applicable. Therefore, we first present Edgeworth expansions, which are also valid for the binomial tree setting. We then apply these result to the one-dimensional and multidimensional Black-Scholes models. We obtain third order expansions
for general binomial and trinomial trees in the 1D setting, and construct advanced models for digital, vanilla and barrier options. Second order expansion are provided for the standard 2D binomial trees and advanced models are constructed for the two-asset digital and the two-asset correlation options. We also present advanced binomial models for a multidimensional setting.
In this paper we construct a numerical solver for the Saint Venant equations. Special attention
is given to the balancing of the source terms, including the bottom slope and variable cross-
sectional profiles. Therefore a special discretization of the pressure law is used, in order to
transfer analytical properties to the numerical method. Based on this approximation a well-
balanced solver is developed, assuring the C-property and depth positivity. The performance
of this method is studied in several test cases focusing on accurate capturing of steady states.
In this paper we propose a procedure to extend classical numerical schemes for
hyperbolic conservation laws to networks of hyperbolic conservation laws. At the
junctions of the network we solve the given coupling conditions and minimize the
contributions of the outgoing numerical waves. This flexible procedure allows
us to also use central schemes at the junctions. Several numerical examples are
considered to investigate the performance of this new approach compared to the
common Godunov solver and exact solutions.
The demand of sustainability is continuously increasing. Therefore, thermoplastic
composites became a focus of research due to their good weight to performance
ratio. Nevertheless, the limiting factor of their usage for some processes is the loss of
consolidation during re-melting (deconsolidation), which reduces the part quality.
Several studies dealing with deconsolidation are available. These studies investigate
a single material and process, which limit their usefulness in terms of general
interpretations as well as their comparability to other studies. There are two main
approaches. The first approach identifies the internal void pressure as the main
cause of deconsolidation and the second approach identifies the fiber reinforcement
network as the main cause. Due to of their controversial results and limited variety of
materials and processes, there is a big need of a more comprehensive investigation
on several materials and processes.
This study investigates the deconsolidation behavior of 17 different materials and
material configurations considering commodity, engineering, and performance
polymers as well as a carbon and two glass fiber fabrics. Based on the first law of
thermodynamics, a deconsolidation model is proposed and verified by experiments.
Universal applicable input parameters are proposed for the prediction of
deconsolidation to minimize the required input measurements. The study revealed
that the fiber reinforcement network is the main cause of deconsolidation, especially
for fiber volume fractions higher than 48 %. The internal void pressure can promote
deconsolidation, when the specimen was recently manufactured. In other cases the
internal void pressure as well as the surface tension prevents deconsolidation.
During deconsolidation the polymer is displaced by the volume increase of the void.
The polymer flow damps the progress of deconsolidation because of the internal
friction of the polymer. The crystallinity and the thermal expansion lead to a
reversible thickness increase during deconsolidation. Moisture can highly accelerate
deconsolidation and can increase the thickness by several times because of the
vaporization of water. The model is also capable to predict reconsolidation under the
defined boundary condition of pressure, time, and specimen size. For high pressure
matrix squeeze out occur, which falsifies the accuracy of the model.The proposed model was applied to thermoforming, induction welding, and
thermoplastic tape placement. It is demonstrated that the load rate during
thermoforming is the critical factor of achieving complete reconsolidation. The
required load rate can be determined by the model and is dependent on the cooling
rate, the forming length, the extent of deconsolidation, the processing temperature,
and the final pressure. During induction welding deconsolidation can tremendously
occur because of the left moisture in the polymer at the molten state. The moisture
cannot fully diffuse out of the specimen during the faster heating. Therefore,
additional pressure is needed for complete reconsolidation than it would be for a dry
specimen. Deconsolidation is an issue for thermoplastic tape placement, too. It limits
the placement velocity because of insufficient cooling after compaction. If the
specimen after compaction is locally in a molten state, it deconsolidates and causes
residual stresses in the bond line, which decreases the interlaminar shear strength. It
can be concluded that the study gains new knowledge and helps to optimize these
processes by means of the developed model without a high number of required
measurements.
Aufgrund seiner guten spezifischen Festigkeit und Steifigkeit ist der
endlosfaserverstärkte Thermoplast ein hervorragender Leichtbauwerkstoff. Allerdings
kann es während des Wiederaufschmelzens durch Dekonsolidierung zu einem
Verlust der guten mechanischen Eigenschaften kommen, daher ist Dekonsolidierung
unerwünscht. In vielen Studien wurde die Dekonsolidierung mit unterschiedlichen
Ergebnissen untersucht. Dabei wurde meist ein Material und ein Prozess betrachtet.
Eine allgemeine Interpretation und die Vergleichbarkeit unter den Studien sind
dadurch nur begrenzt möglich. Aus der Literatur sind zwei Ansätze bekannt. Dem
ersten Ansatz liegt der Druckunterschied zwischen Poreninnendruck und
Umgebungsdruck als Hauptursache der Dekonsolidierung zu Grunde. Beim zweiten
Ansatz wird die Faserverstärkung als Hauptursache identifiziert. Aufgrund der
kontroversen Ergebnisse und der begrenzten Anzahl der Materialien und
Verarbeitungsverfahren, besteht die Notwendigkeit einer umfassenden Untersuchung
über mehrere Materialien und Prozesse. Diese Studie umfasst drei Polymere
(Polypropylen, Polycarbonat und Polyphenylensulfid), drei Gewebe (Köper, Atlas und
Unidirektional) und zwei Prozesse (Autoklav und Heißpressen) bei verschiedenen
Faservolumengehalten.
Es wurde der Einfluss des Porengehaltes auf die interlaminare Scherfestigkeit
untersucht. Aus der Literatur ist bekannt, dass die interlaminare Scherfestigkeit mit
der Zunahme des Porengehaltes linear sinkt. Dies konnte für die Dekonsolidierung
bestätigt werden. Die Reduktion der interlaminaren Scherfestigkeit für
thermoplastische Matrizes ist kleiner als für duroplastische Matrizes und liegt im
Bereich zwischen 0,5 % bis 1,5 % pro Prozent Porengehalt. Außerdem ist die
Abnahme signifikant vom Matrixpolymer abhängig.
Im Falle der thermisch induzierten Dekonsolidierung nimmt der Porengehalt
proportional zu der Dicke der Probe zu und ist ein Maß für die Dekonsolidierung. Die
Pore expandiert aufgrund der thermischen Gasexpansion und kann durch äußere
Kräfte zur Expansion gezwungen werden, was zu einem Unterdruck in der Pore
führt. Die Faserverstärkung ist die Hauptursache der Dickenzunahme
beziehungsweise der Dekonsolidierung. Die gespeicherte Energie, aufgebaut während der Kompaktierung, wird während der Dekonsolidierung abgegeben. Der
Dekompaktierungsdruck reicht von 0,02 MPa bis 0,15 MPa für die untersuchten
Gewebe und Faservolumengehalte. Die Oberflächenspannung behindert die
Porenexpansion, weil die Oberfläche vergrößert werden muss, die zusätzliche
Energie benötigt. Beim Kontakt von benachbarten Poren verursacht die
Oberflächenspannung ein Verschmelzen der Poren. Durch das bessere Volumen-
Oberfläche-Verhältnis wird Energie abgebaut. Der Polymerfluss bremst die
Entwicklung der Dickenzunahme aufgrund der erforderlichen Energie (innere
Reibung) der viskosen Strömung. Je höher die Temperatur ist, desto niedriger ist die
Viskosität des Polymers, wodurch weniger Energie für ein weiteres Porenwachstum
benötigt wird. Durch den reversiblen Einfluss der Kristallinität und der
Wärmeausdehnung des Verbundes wird während der Erwärmung die Dicke erhöht
und während der Abkühlung wieder verringert. Feuchtigkeit kann einen enormen
Einfluss auf die Dekonsolidierung haben. Ist noch Feuchtigkeit über der
Schmelztemperatur im Verbund vorhanden, verdampft diese und kann die Dicke um
ein Vielfaches der ursprünglichen Dicke vergrößern.
Das Dekonsolidierungsmodell ist in der Lage die Rekonsolidierung vorherzusagen.
Allerdings muss der Rekonsolidierungsdruck unter einem Grenzwert liegen
(0,15 MPa für 50x50 mm² und 1,5 MPa für 500x500 mm² große Proben), da es sonst
bei der Probe zu einem Polymerfluss aus der Probe von mehr als 2 % kommt. Die
Rekonsolidierung ist eine inverse Dekonsolidierung und weist die gleichen
Mechanismen in der entgegengesetzten Richtung auf.
Das entwickelte Modell basiert auf dem ersten Hauptsatz der Thermodynamik und
kann die Dicke während der Dekonsolidierung und der Rekonsolidierung
vorhersagen. Dabei wurden eine homogene Porenverteilung und eine einheitliche,
kugelförmige Porengröße angenommen. Außerdem wurde die Massenerhaltung
angenommen. Um den Aufwand für die Bestimmung der Eingangsgrößen zu
reduzieren, wurden allgemein gültige Eingabeparameter bestimmt, die für eine
Vielzahl von Konfigurationen gelten. Das simulierte Materialverhalten mit den
allgemein gültigen Eingangsparametern erzielte unter den definierten
Einschränkungen eine gute Übereinstimmung mit dem tatsächlichen
Materialverhalten. Nur bei Konfigurationen mit einer Viskositätsdifferenz von mehr als 30 % zwischen der Schmelztemperatur und der Prozesstemperatur sind die
allgemein gültigen Eingangsparameter nicht anwendbar. Um die Relevanz für die
Industrie aufzuzeigen, wurden die Effekte der Dekonsolidierung für drei weitere
Verfahren simuliert. Es wurde gezeigt, dass die Kraftzunahmegeschwindigkeit
während des Thermoformens ein Schlüsselfaktor für eine vollständige
Rekonsolidierung ist. Wenn die Kraft zu langsam appliziert wird oder die finale Kraft
zu gering ist, ist die Probe bereits erstarrt, bevor eine vollständige Konsolidierung
erreicht werden kann. Auch beim Induktionsschweißen kann Dekonsolidierung
auftreten. Besonders die Feuchtigkeit kann zu einer starken Zunahme der
Dekonsolidierung führen, verursacht durch die sehr schnellen Heizraten von mehr als
100 K/min. Die Feuchtigkeit kann während der kurzen Aufheizphase nicht vollständig
aus dem Polymer ausdiffundieren, sodass die Feuchtigkeit beim Erreichen der
Schmelztemperatur in der Probe verdampft. Beim Tapelegen wird die
Ablegegeschwindigkeit durch die Dekonsolidierung begrenzt. Nach einer scheinbar
vollständigen Konsolidierung unter der Walze kann die Probe lokal dekonsolidieren,
wenn das Polymer unter der Oberfläche noch geschmolzen ist. Die daraus
resultierenden Poren reduzieren die interlaminare Scherfestigkeit drastisch um 5,8 %
pro Prozent Porengehalt für den untersuchten Fall. Ursache ist die Kristallisation in
der Verbindungszone. Dadurch werden Eigenspannungen erzeugt, die in der
gleichen Größenordnung wie die tatsächliche Scherfestigkeit sind.