Propagation of Fatigue Cracks under Shear Loading Modes II, III and II+III in the Near-Threshold Region

Práce je zaměřena na šíření únavových trhlin v módech II, III a II + III v prahové oblasti v kovových materiálech. Byly provedeny experimenty pro ARMCO železo, titan, nikl a austenitickou ocel na třech druzích vzorků pro zatěžování trhliny ve smykových módech. Byl použit zvláštní způsob vytváření iniciační trhliny, který eliminoval efekt zavírání trhliny na začátku smykového zatěžování. Ve všech zkoumaných materiálech byly efektivní prahové hodnoty v módu II přibližně 1,7 krát nižší než v módu III. Měřením úhlů lokálních odklonů a natočení lomových faset s použitím stereofotogrammetrie v SEM bylo usuzováno na tendenci trhliny k vyhýbání do lokálního módu I. Nejmenší úhly byly zjištěny u ARMCO železa pro trhliny v módech II i III, středně velké úhly u titanu a niklu a největší úhly (vyhnutí do čistého módu I) byly pozorovány u austenitické oceli. Tyto rozdíly lze vysvětlit různým počtem dostupných skluzových systémů v krystalových mřížkách daných materiálů. Poměry mezi naměřenými prahovými hodnotami v módu I, II a III byly srovnány s předpověďmi teoretických modelů. Byl navržen analytický vztah pro efektivní prahové hodnoty v módu II, který byl v dobré shodě s experimentálními výsledky. Pomocí efektivních prahových hodnot bylo vyčísleno kritérium pro vyhýbání do módu I, které vedlo ke kritickému úhlu odklonu 40° souvisejícímu s přechodem z lokálního smykového módu do otevíracího módu.The work is focused on fatigue crack propagation under modes II, III and II + III in the near-threshold region in metallic materials. Experiments were conducted for ARMCO iron, titanium, nickel and stainless steel on three types of specimens for shear-mode crack loading. A special technique of precrack generation was used which enabled a closure-free loading at the beginning of the shear-mode experiments. For all investigated materials the effective thresholds under the remote mode II loading were found to be about 1.7 times lower than those under the remote mode III. Tendency to local mode I branching was assessed by a measurement of local deflection and twist angles of fracture facets using stereophoto-grammetry in SEM. The lowest angles of both mode II and mode III cracks were identified for the ARMCO iron, the intermediate ones in titanium and nickel and the highest ones (pure mode I branches) were determined for the stainless steel. These differences can be explained by different numbers of available slip systems in crystal lattices of investigated materials. Ratios of measured effective thresholds in modes I, II and III were compared with results predicted by theoretical models. An analytical formula for effective mode-II thresholds was proposed and found in a good agreement with experimental results. The mode I branching criterion in terms of effective thresholds led to a critical deflection angle of 40° related to a transition from local shear to opening mode.

Credit-Scoring Methods (in English)

The paper reviews the best-developed and most frequently applied methods of credit scoring employed by commercial banks when evaluating loan applications. The authors concentrate on retail loans – applied research in this segment is limited, though there has been a sharp increase in the volume of loans to retail clients in recent years. Logit analysis is identified as the most frequent credit-scoring method used by banks. However, other nonparametric methods are widespread in terms of pattern recognition. The methods reviewed have potential for application in post-transition countries.banking sector, credit scoring, discrimination analysis, pattern recognition, retail loans

Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data

Credit to the private sector has risen rapidly in European emerging markets but its risk evaluation has been largely neglected. Using retail-loan banking data from the Czech Republic we construct two credit risk models based on logistic regression and Classification and Regression Trees. Both methods are comparably efficient and detect similar financial and socio-economic variables as the key determinants of default behavior. We also construct a model without the most important financial variable (amount of resources) that performs very well. This way we confirm significance of socio-demographic variables and link our results with specific issues characteristic to new EU members.credit scoring, discrimination analysis, banking sector, pattern recognition, retail loans, CART, European Union

Default Predictors and Credit Scoring Models for Retail Banking

This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using Classification and Regression Trees (CART, nonparametric). The models are compared in terms of efficiency and power to discriminate between low and high risk clients by employing data from a new European Union economy. We are able to detect the most important characteristics of default behavior: the amount of resources the client has, the level of education, marital status, the purpose of the loan, and the number of years the client has had an account with the bank. Both methods are robust: they found similar variables as determinants. We therefore show that parametric as well as non-parametric methods can produce successful models. We are able to obtain similar results even when excluding a key financial variable (amount of own resources). The policy conclusion is that socio-demographic variables are important in the process of granting credit and therefore such variables should not be excluded from credit scoring model specification.credit scoring, discrimination analysis, banking sector, pattern recognition, retail loans, CART, European Union

Comparing Guessing Games with homogeneous and heterogeneous players: Experimental results and a CH explanation

We investigate the decisions of individuals in simple and complex environments. We use a version of the Guessing Game (Beauty-contest Game) as a vehicle for our investigation, employing mathematically talented students. We find that our subjects think in complex environments more carefully before making decisions. We rationalize our findings using the Cognitive Hierarchy (CH) model proposed by Camerer, Ho, and Chong (2002). We relate our results to the emerging literature on the decision making of collective actors.Guessing Game

Modeling of Molecular Interactions Using Neural Networks

Síly působící mezi částicemi při interakcích lze popsat pomocí nadploch potenciálové energie. Cílem této práce je vyhodnotit, zda by použití správné neuronové sítě dokázalo reprezentovat tyto nadplochy s dostatečnou přesností. Pro ověření jsem používal dvou analytických modelů a to Lennard-Jonesova potenciálu a Morseho potenciálu. Nadplochy byly reprezentovány pomocí neuronových sítí s dopředným šířením signálu, které byly trénovány metodou zpětné propagace. V rámci této práce se podařilo vytvořit takové neuronové sítě, které dokáží predikovat nadplochu potenciálové energie z relativně malého souboru vstupních dat. Výsledné neuronové sítě jsou také schopny přibližné extrapolace potenciálových nadploch pro velké vzdálenosti mezi částicemi, mimo rozsah trénovacích dat. Výsledky získané v rámci této práce poslouží jako základ pro další výzkum, který se bude zabývat reprezentací větších systémů. Díky tomuto výzkumu bude možné efektivně reprezentovat nadplochy a predikovat hodnoty potenciálové energie i v oblastech, kde mají ab initio metody problémy s konvergencí nebo jsou příliš výpočetně náročné.The forces acting between the particles during their interactions can be described by potential energy surfaces. The aim of this work is to evaluate whether it is possible to represent these surfaces using neural networks with sufficient precision. For verification, I used two analytical models, namely Lennard-Jones potential and Morse potential. Surfaces were represented by feed-forward neural networks that were trained using back-propagation method. In this work, such neural networks have been created that can predict potential energy from a relatively small set of input data. The resulting neural networks are also able of an approximate extrapolation of potential surfaces in large distances between particles outside the range of training data. The results obtained in this thesis will serve as the basis for further research, which will deal with representations of larger systems. Thanks to this research, it will be possible to efficiently represent surfaces and predict potential energy values even in domains where ab initio methods have convergence problems or where their are computationally too demanding.460 - Katedra informatikyvýborn

Individual Professional Practice in the Company

Import 03/11/2016Táto práca popisuje priebeh individuálnej odbornej praxe absolvovanej v spoločnosti TELE DATA SYSTEM, spol. s.r.o.. Popisujem tu odborné zameranie firmy a ich produkty a práve na jednom z nich som pracoval počas celého trvania odbornej praxe. Jedná sa o SCADA software IDS HIGH-LEIT™. Ďalej opisujem technológie a nástroje, ktoré som používal pri práci. Zameriavam sa na konkrétne úlohy a projekty, ktoré som v rámci údržby a rozširovania softwaru IDS HIGH-LEIT™ vykonával. A v neposlednej rade uvádzam prínosy bakalárskej práce a využitie mojich riešení v softwari IDS HIGH-LEIT™.This thesis describe course of individual professional practice in the company TELE DATA SYSTEM, spol. s.r.o.. I describe specialism of this company and their products. I worked on one of company's products for the duration of professional practice. This product was the SCADA software IDS HIGH-LEIT™. It further describes technologies and tools, which I used at work. I focus on concrete tasks and project, which I done for the maintenance and extension of software IDS HIGH-LEIT™. Last but not least I submit benefits of professional practice and usage of my solutions in the software IDS HIGH-LEIT™.440 - Katedra telekomunikační technikyvýborn

Calibration of Interest Rate Models - Transition Market Case

A methodology to calibrate multifactor interest rate model for transition countries is proposed. The usual methodology of calibration with implied volatility cannot be used as there are no markets for regularly traded derivatives. The existence of such a markets is essential for this calibration. The paradigm used is the Brace-Gatarek- Musiela model of interest rates (Brace, Gatarek and Musiela (1997)), which models the evolution of LIBOR (London InterBank Offered Rate) market interest rates, together with the Orthogonal GARCH model proposed by Alexander (2002), and further generalized by van der Weide (2002). The estimated model is used for the analysis of interest rate markets with shorter-end maturities in the 4 Visegrad countries (Slovak Republic, Czech Republic, Poland and Hungary).Interest rate; Interest rate models, Calibration, Transition countries

Server-side navigation service benchmarking tool

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