Dissertationen zum Thema „Vícestupňové“

This master thesis summarizes the basic knowledge in the field of turbocharging of internal combustion piston engines. It also focuses on the analysis of some properties of multistage turbocharging, especially for diesel engines. Using analytical relationships, a model in the form of a web application has been created, which describes the cooperation of a turbocharger or turbochargers with an internal combustion engine. With the help of this model, some two-stage supercharging options for the selected engine have been then proposed.

The main objective of this thesis is to design blades for the axial pump with two counter-rotating rotors for design point. Then compare results with the standard concept with one runner and guide blades.

The ways of purifying waste water produced by human society are nowadays a great deal. With the increasing pressure on sustainable construction, technology using principles close to natural processes are at the forefront. Treatment wetlands have been in use for almost 30 years and thanks mainly to developments abroad, they prove they are a suitable option for smaller producers of pollution. When designing a treatment wetland for municipalities with a larger amount of inhabitants, it is necessary to modify the proposal in order to eliminate all types of pollution. This thesis therefore compares three sewage treatment plants with a multistage filtration system. Comparing the achieved parameters will be beneficial for defining the rules for optimal design of these types of wastewater treatment plant.

My Master's thesis deals with the problems of flow compression in network devices. Its outcome should alleviate memory consumption of the flows and simplify the processing of network traffic. As an introduction I provide a description of protocols serving for data storage and manipulation, followed by discussion about possibilities of compression methods that are employed nowadays. In the following part there is an in-depth analysis of source data that shows the structure and composition of the data and brings up useful observations, which are later used in the testing  of existing compression methods, as well as about their potential and utilization in flow compression. Later on, I venture into the field of lossy compression and basing on the test results a new approach is described, created by means of flow clustering and their subsequent lossy compression. The conclusion contains an evaluation of the possibilities of the method and the final summary of the thesis along with various suggestions for further development of the research.

This thesis is focused on experimental work in the domain of vacuum evaporation efficiency improvement. The first part introduces theory of liquids evaporation and its influencing factors, then multi-stage flash distillation technology. The next part of theory is an overview of other technologies used for desalination of sea water and introduction to the design of experiments. In the practical part are selected factors affecting efficiency of device and experiment plan is designed for them. When the experiment is done, optimal operating conditions of technology are designed on basis of analysis.

This dissertation thesis deals with the development of technology which could tackle two major issues related to biogas plants. These issues concern the insufficient use of waste heat from biogas combustion and its subsequent processing. It also concerns the use of the fermentation residues which are formed in large quantities and whose use is restricted by law. Based on a literary search of separation methods, a vacuum evaporator was selected as the most suitable technology. Its advantages include its simple construction, operational reliability and robustness, low costs of thickening medium pre-treatment, potential for a quick commercial application and, especially, the chance to use a low-potential waste heat. A primary purpose of this technological unit is the reduction in the volume of fermentation residues. Other benefits include the efficient use of waste heat from a biogas plant, which would otherwise be wasted. Evaporators with a low consumption of electrical energy (which is a main product of a biogas plant) seem to be the best option for applications in the biogas plants. Three of these technologies were subjected to a more thorough analysis, which included the development of computational models and their quantification for conditions in a sample biogas plant. A one-stage evaporator with a forced circulation (680 – 712 kWhth/m3, 25.9 – 30.5 kWhel/m3) was evaluated as the least suitable option in terms of energy demands. The energy intensity of a three-stage evaporator with a falling film (241 – 319 kWhth/m3, 12.0 – 23.6 kWhel/m3) and a nine-stage flash evaporator (236 – 268 kWhth/m3, 13.6 – 18.4 kWhel/m3) is significantly lower. A multi-stage flash evaporator (MSF) was then chosen for development and will form the central focus of this thesis. The reasons for the choice are as follows: the low requirements on the heat transfer surface, good operational experience in the field of desalination, its simple construction, modularity and evaporation outside the heat transfer surface. A thorough technical-economic evaluation was also performed on the integration of the evaporator into the biogas plant. The main part of the work included the experimental development of a MSF evaporator prototype. The main objective of this development was to achieve a stable flow rate of the thickening liquid digestate fraction and the continuous formation of the distillate. This was not an easy objective to achieve, especially due to the properties of the liquid digestate, which has a non-newtonian characteristic and increased density and viscosity compared to water. The tendency of the liquid digestate to form foam was also the subject of analysis. The development of the evaporator and first successful operational test are described in the thesis in detail. This required the use of an anti-foaming product. A fully-developed prototype of the MSF evaporator allowed us to achieve continuous operation with a distillate production, reaching from 5 to 10 kg/h at a liquid digestate flow rate of 0.4–0.5 m3/h. The main drawback of this technology is the pollution of the distillate with ammonia nitrogen, and it is for this reason that the basic procedures of its subsequent elimination was selected for further analysis.

This diploma thesis is mainly focused on the digestate thickening in a biogas plant. First, overview of the biogas technology in the Czech Republic is presented. Furthermore, problems with waste heat utilization and processing of fermentation residues (digestate) are described in more detail. Based on the research, multi-stage flash (MSF) evaporation was chosen as the technology for the digestate thickening. The main part deals with the integration of the chosen technology into a biogas plant process. The programming language Python was used to simplify the given task. In the preliminary stage, a complex mathematical model of a biogas plant was created, focusing particularly on the mass and energy balances. Subsequently, a computational model of the MSF evaporator was programmed. A procedure for the integration was suggested using the sensitivity analyses. Additionally, the model of a biogas plant was extended with the MSF evaporator. The key outcome of the thesis is a technical-economic analysis in which the impact of digestate transport price and electricity feed-in tariff on payback period is investigated. The results suggest profitability of MSF evaporator for biogas plants without subsidized feed-in tariff. Contrastingly, installation of MSF evaporator in older biogas plants with subsidized feed-in tariff can be economically viable only in cases of significantly longer transport distances.

Multistage stochastic optimization is used to solve many real-life problems where decisions are taken at multiple times, e.g., portfolio selection problems. Such problems need the definition of stochastic processes, which are usually approxim- ated by scenario trees. The choice of the size of the scenario trees is the result of a compromise between the best approximation and the possibilities of the com- puter technology. Therefore, once a master scenario tree has been generated, it can be needed to reduce its dimension in order to make the problem computation- ally tractable. In this thesis, we introduce several scenario reduction algorithms and we compare them numerically for different types of master trees. A simple portfolio selection problem is also solved within the study. The distance from the initial scenario tree, the computational time, and the distance between the optimal objective values and solutions are compared for all the scenario reduction algorithms. In particular, we adopt the nested distance to measure the distance between two scenario trees. 1

Multi-Stage Stochastic Programming with CVaR: Modeling, Algorithms and Robustness RNDr. Václav Kozmík Abstract: We formulate a multi-stage stochastic linear program with three different risk measures based on CVaR and discuss their properties, such as time consistency. The stochastic dual dynamic programming algorithm is described and its draw- backs in the risk-averse setting are demonstrated. We present a new approach to evaluating policies in multi-stage risk-averse programs, which aims to elimi- nate the biggest drawback - lack of a reasonable upper bound estimator. Our approach is based on an importance sampling scheme, which is thoroughly ana- lyzed. A general variance reduction scheme for mean-risk sampling with CVaR is provided. In order to evaluate robustness of the presented models we extend con- tamination technique to the case of large-scale programs, where a precise solution cannot be obtained. Our computational results are based on a simple multi-stage asset allocation model and confirm usefulness of the presented procedures, as well as give additional insights into the behavior of more complex models. Keywords: Multi-stage stochastic programming, stochastic dual dynamic programming, im- portance sampling, contamination, CVaR

THESIS ABSTRACT The topic of Multi-tiered dispute resolution methods (or "MDR") is one of growing importance for parties involved in international transactions. When applied it allows them to resolve their disputes "smoothly" with the possibility to avoid an open conflict scenario and reduce their transaction costs. This masters thesis aim is to describe the legal phenomenon mentioned above in seven chapters. The first three chapters deal with theoretical and historical background of the topic, followed by the description of a variety of possible dispute resolution methods in chapter IV. Chapter V. lists three model MDR clauses and describes the Med-arb method as a typical example of MDR. Chapters VI. and VII. are concerned with practical questions of relevant legal orders in the arbitration step of MDR and with the importance of recognition and enforcement of arbitral awards.

The thesis deals with a multistage stochastic model and its application to a number of practical problems. Special attention is devoted to the case where a random element follows an autoregressive sequence and the constraint sets correspond to the individual probability constraints. For this case conditions under which is the problem well-defined are specified. Further, the approximation of the problem and its convergence rate under the empirical estimate of the distribution function is analyzed. Finally, an example of the investment in financial instruments is solved, which is defined as a two-stage stochastic programming problem with the probability constraint and a random element following an autoregressive sequence. Powered by TCPDF (www.tcpdf.org)

This thesis deals with multi-stage stochastic programming in the context of random process representation. Basic structure for random process is a scenario tree. The thesis introduces general and stage-independent scenario tree and their properties. Scenario trees can be also combined with Markov chains which describe the state of the system and determine which scenario tree should be used. Another structure which enables reduce the complexity of the problem is a scenario lattice. Scenario generation is performed using moment method. Scenario trees are used for representation of random returns as the input to the investment problem.

This thesis deals with multi-stage stochastic programming in the context of random process representation. Basic structure for random process is a scenario tree. The thesis introduces general and stage-independent scenario tree and their properties. Scenario trees combined with Markov chains are also introduced. Markov chains states determine if there is a crisis period or not. Information about historical number of crises helps us to construct a scenario lattice. Scenario generation is performed using moment method. Scenario trees are used as an input to the investment problem.

The main objective of this thesis is to build a multi-stage stochastic pro- gram within an asset-liability management problem of a leasing company. At the beginning, the business model of such a company is introduced and the stochastic programming formulation is derived. Thereafter, three various risk constraints, namely the chance constraint, the Value-at-Risk constraint and the conditional Value-at-Risk constraint along with the second-order stochastic dominance constraint are applied to the model to control for riski- ness of the optimal strategy. Their properties and their effects on the optimal decisions are thoroughly investigated, while various risk limits are considered. In order to obtain solutions of the problems, random elements in the model formulation had to be approximated by scenarios. The Hull - White model calibrated by a newly proposed method based on maximum likelihood esti- mation has been used to generate scenarios of future interest rates. In the end, the performances of the optimal solutions of the problems for unconsid- ered and unfavourable crisis scenarios were inspected. The used methodology of such a stress test has not yet been implemented in stochastic programming problems within an asset-liability management. 1