|
| |
|
|
Specifications of the Ansys Fluent Solution Solver for low pressures in EREM
Šimík, Marcel ; Bílek, Michal (referee) ; Maxa, Jiří (advisor)
This thesis is focused on electron microscopy which issue is discussed at the beginning of work. The main attention is dedicated to the Environmental electron microscope, especially the differentially pumped chamber, which the thesis deals with. There is a production of an experimental chamber for analysis of shock waves on going therefore main goal of this thesis was to analyze the flow pattern in this chamber. Using the Ansys Fluent program, simulations of the characteristic flow that arises from the pumping of the vacuum chambers namely the ultrasonic flow at low pressures on which the most suitable turbulent module was applied as well as the degree of discretization was performed. The final analysis of this flow pattern is primarily focused on the localization of the shock wave which experimental evidence is to be lodged by shadow optical method as a part of the new concept of the chamber. The basis for the simulation of the chamber was taken over by Dr. Danilatos, with which the results were compared.
|
|
|
Uncertainty estimation of reservoir storage capacity in first stage of design preparation
Oulehla, Pavel ; Paseka, Stanislav (referee) ; Marton, Daniel (advisor)
The aim of the bachelor thesis is the estimation of reservoir storage capacity uncertainty. The input uncertainty is defined by the inaccuracy of the altitude geographic data. Using the appropriate altitude measuring and the estimated errors of the measurement, the change in the area – volumes curves is described as weel as its value of uncertainty. Afterwords the storage capacity loaded by batymetric curves uncertainty is calculated. Furthermore the uncertainty of the reservoir filling height has been quantified. For these kind of calculations the reservoir simulation model has been used, Monte Carlo method, to generate random values of the batygraphic curve has been used too. Expression of uncertainties when calculating the storage capacity can help to reduction risk of storage capacity failure, respectively reduction of water shortages during reservoirs operations during critical dry periods.
|
|
|
Optimization Methods for Compensation of Shooting Inaccuracy
Horníček, Jan ; Novotný, Jan (referee) ; Popela, Pavel (advisor)
In this work there is performed analysis of inaccuracy shooting and its optimum corrections especially for playing darts. At rst the model describing inaccurate shooting is made. Using this model we received prerequisites for numerical solving of our problem. Computing algorithm was made and than was proven that our problem can be solved with arbitrary precision by this algorithm. The algorithm was implemented in MATLAB and modied using functional Analysis to minimize computing time. Our problem was solved by this algorithm and in conclusion was made simple application for visualization of received data.
|
|
|
Using LabVIEW to determine measurement uncertainty
Hoferková, Kateřina ; Štohl, Radek (referee) ; Šedivá, Soňa (advisor)
This bachelor thesis is focused on problematics of determining the measurement uncertainty. In the theoretical part of the thesis there is a theory of the procedure of determining the uncertainty of the measurement. The practical part of the thesis is focused on the realization of the program created in LabVIEW 2017. The bachelor thesis is about a determining the measurement uncertainty according to GUM, the standard uncertainty of type A, the standard uncertainty of type B, the combined uncertainty and the expanded uncertainty. The thesis is focused on determining the measurement uncertainty of direct measurements, indirect measurements and Monte Carlo method. The enclosed LabVIEW program enables to insert the data to determine the measurement uncertainty. The program determines the measurement uncertainty according to GUM and Monte Carlo method. The results of a calculation can be optionally saved to a file for an archiving.
|
|
|
Using Artificial Neural Network Models to Assess Water Quality in Water Distribution Networks
Cuesta Cordoba, Gustavo Andres ; Tuhovčák, Ladislav (advisor)
A water distribution system (WDS) is based in a network of interconnected hydraulic components to transport the water directly to the customers. Water must be treated in a Water Treatment Plant (WTP) to provide safe drinking water to consumers, free from pathogenic and other undesirable organisms. The disinfection is an important aspect in achieving safe drinking water and preventing the spread of waterborne diseases. Chlorine is the most commonly used disinfectant in conventional water treatment processes because of its low cost, its capacity to deactivate bacteria, and because it ensures residual concentrations in WDS to prevent microbiological contamination. Chlorine residual concentration is affected by a phenomenon known as chlorine decay, which means that chlorine reacts with other components along the system and its concentration decrease. Chlorine is measured at the output of the WTP and also in several considered points within the WDS to control the water quality in the system. Simulation and modeling methods help to predict in an effective way the chlorine concentration in the WDS. The purpose of the thesis is to assess chlorine concentration in some strategic points within the WDS by using the historical measured data of some water quality parameters that influence chlorine decay. Recent investigations of the water quality have shown the need of the use of non-linear modeling for chlorine decay prediction. Chlorine decay in a pipeline is a complex phenomenon so it requires techniques that can provide reliable and efficient representation of the complexity of this behavior. Statistical models based on Artificial Neural Networks (ANN) have been found appropriated for the investigation and solution of problems related with non-linearity in the chlorine decay prediction offering advantages over more conventional modeling techniques. In this sense, this thesis uses a specific neural network application to solve the problem of forecasting the residual chlorine
|
|
|
Risk Analysis in Transport Infrastructure Projects
Hašek, Jiří ; Holá, Michaela (referee) ; Hromádka, Vít (advisor)
The subject of the master’s thesis is a risk analysis in transport infrastructure projects. In the theoretical part, I deal with public sector, life cycle of the project, evaluation of public projects, conception of risk, clasification of risk, risk analysis and valuation of the risk. In the practical section I process risk analysis of the project in transport infrastucture.
|
|
|
Reduced basis solver for stochastic Galerkin formulation of Darcy flow with uncertain material parameters
Béreš, Michal
In this contribution, we present a solution to the stochastic Galerkin (SG) matrix equations coming from the Darcy flow problem with uncertain material coefficients in the separable form. The SG system of equations is kept in the compressed tensor form and its solution is a very challenging task. Here, we present the reduced basis (RB) method as a solver which looks for a low-rank representation of the solution. The construction of the RB consists of iterative expanding of the basis using Monte Carlo sampling. We discuss the setting of the sampling procedure and an efficient solution of multiple similar systems emerging during the sampling procedure using deflation. We conclude with a demonstration of the use of SG solution for forward uncertainty quantification.
|
|
|
Generating random pattern-avoiding matrices
Kučera, Stanislav ; Jelínek, Vít (advisor) ; Šámal, Robert (referee)
Binary matrices not containing a smaller matrix as a submatrix have become an interesting topic recently. In my thesis, I introduce two new algorithms to test whether a big square binary matrix contains a smaller binary matrix together with a process using randomness, which approximates a uniformly random matrix not containing a given matrix. The reason to create such algorithms is to allow researchers test their conjectures on random matrices. Thus, my thesis also contains an effective cross- platform implementation of all mentioned algorithms. Powered by TCPDF (www.tcpdf.org)
|
|
|
Local polynomial regression
Cigán, Martin ; Bašta, Milan (advisor) ; Maciak, Matúš (referee)
This thesis examines local polynomial regression. Local polynomial regression is one of non-parametric approach of data fitting. This particular method is based on repetition of fitting data using weighted least squares estimate of the parameters of the polynomial model. The aim of this thesis is therefore revision of some properties of the weighted least squares estimate used in linear regression model and introduction of the non-robust method of local polynomial regression. Some statistical properties of the local polynomial regression estimate are derived. Conditional bias and conditional variance of the local polynomial regression estimate are then approximated using Monte Carlo method and compared with theoretical results. Powered by TCPDF (www.tcpdf.org)
|
guest ::
