Validation Studies of Thermal-hydraulic Code for Safety Analysis of Nuclear Power Plants

This thesis gives an overview of the validation process for thermal hydraulic system codes and it presents in more detail the assessment and validation of the French code CATHARE for VVER calculations. Three assessment cases are presented: loop seal clearing, core reflooding and flow in a horizontal steam generator. The experience gained during these assessment and validation calculations has been used to analyze the behavior of the horizontal steam generator and the natural circulation in the geometry of the Loviisa nuclear power plant. The cases presented are not exhaustive, but they give a good overview of the work performed by the personnel of Lappeenranta University of Technology (LUT). Large part of the work has been performed in co-operation with the CATHARE-team in Grenoble, France. The design of a Russian type pressurized water reactor, VVER, differs from that of a Western-type PWR. Most of thermal-hydraulic system codes are validated only for the Western-type PWRs. Thus, the codes should be assessed and validated also for VVER design in order to establish any weaknesses in the models. This information is needed before codes can be used for the safety analysis. Theresults of the assessment and validation calculations presented here show that the CATHARE code can be used also for the thermal-hydraulic safety studies for VVER type plants. However, some areas have been indicated which need to be reassessed after further experimental data become available. These areas are mostly connected to the horizontal stem generators, like condensation and phase separation in primary side tubes. The work presented in this thesis covers a large numberof the phenomena included in the CSNI code validation matrices for small and intermediate leaks and for transients. Also some of the phenomena included in the matrix for large break LOCAs are covered. The matrices for code validation for VVER applications should be used when future experimental programs are planned for code validation.

Réhabilitation améliorée après chirurgie--L'ere de la prise en charge optimale du patient chirurgical [Enhanced Recovery After Surgery--optimal management of the surgical patient].

Enhanced Recovery After Surgery (ERAS) is a multimodal, standardized and evidence-based perioperative care pathway. With ERAS, postoperative complications are significantly lowered, and, as a secondary effect, length of hospital stay and health cost are reduced. The patient recovers better and faster allowing to reduce in addition the workload of healthcare providers. Despite the hospital discharge occurs sooner, there is no increased charge of the outpatient care. ERAS can be safely applied to any patient by a tailored approach. The general practitioner plays an essential role in ERAS by assuring the continuity of the information and the follow-up of the patient.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

Code Generator for Key Management Protocols - Design and Implementation

Key management has a fundamental role in secure communications. Designing and testing of key management protocols is tricky. These protocols must work flawlessly despite of any abuse. The main objective of this work was to design and implement a tool that helps to specify the protocol and makes it possible to test the protocol while it is still under development. This tool generates compile-ready java code from a key management protocol model. A modelling method for these protocols, which uses Unified Modeling Language (UML) was also developed. The protocol is modelled, exported as an XMI and read by the code generator tool. The code generator generates java code that is immediately executable with a test software after compilation.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Capital Controls with International Reserve Accumulation: Can this Be Optimal ?

Motivated by the Chinese experience, we analyze a semi-open economy where the central bank has access to international capital markets, but the private sector has not. This enables the central bank to choose an interest rate different from the international rate. We examine the optimal policy of the central bank by modelling it as a Ramsey planner who can choose the level of domestic public debt and of international reserves. The central bank can improve savings opportunities of credit-constrained consumers modelled as in Woodford (1990). We find that in a steady state it is optimal for the central bank to replicate the open economy, i.e., to issue debt financed by the accumulation of reserves so that the domestic interest rate equals the foreign rate. When the economy is in transition, however, a rapidly growing economy has a higher welfare without capital mobility and the optimal interest rate differs from the international rate. We argue that the domestic interest rate should be temporarily above the international rate. We also find that capital controls can still help reach the first best when the planner has more fiscal instruments.

Gene filtering with optimal threshold selection

Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.

Optimal Exchange Rate Policy in a Growing Semi-Open Economy

This paper considers an alternative perspective to China's exchange rate policy. It studies a semi-open economy where the private sector has no access to international capital markets but the central bank has full access. Moreover, it assumes limited financial development generating a large demand for saving instruments by the private sector. The paper analyzes the optimal exchange rate policy by modeling the central bank as a Ramsey planner. Its main result is that in a growth acceleration episode it is optimal to have an initial real depreciation of the currency combined with an accumulation of reserves, which is consistent with the Chinese experience. This depreciation is followed by an appreciation in the long run. The paper also shows that the optimal exchange rate path is close to the one that would result in an economy with full capital mobility and no central bank intervention.