Zugl.: Kassel, Univ., Diss.

Traditional macroeconometric models of the Australian economy estimate the behaviour of wage and price inflation separately, thereby ignoring the possibility that there is a contemporaneous relationship between these two variables. This thesis follows a recent trend emerging in other small open economies, such as the UK and Norway, which is to estimate the behaviour of wage and price inflation in a simultaneous-equations model. In order to capture the behaviour of the major variables which drive wages and prices, a complete model is constructed which embeds these important transmission channels. The model is developed in three stages. First, underpinned by a theoretical framework of a unionized economy with imperfect competition, the core wage- price system is developed whereby consumer prices and average weekly earnings are jointly estimated in a simultaneous-equations framework. Particular atten- tion is given to estimating two identified cointegrating relationships for wages and prices. These equations are interpreted as the long-run targets of workers and firms respectively and are embedded in a parsimonious system of short-run dynamics which drive wages and prices towards their long-run levels. Second, llie behaviour of llie main feedback variables driving llie wage-price system is modelled, with particular attention given to the unemployment rate. While several of the most recent models of unemployment show that the aggregate unemployment rate in Australia does indeed behave differently during periods of low and high unemployment, none can explain what drives the unemployment rate to increase at such a rapid rate and what contributes to its much slower decrease. Another central issue of this thesis, therefore, is to propose a rationale for this as yet unexplained phenomenon. The remaining behavioural variables in the model, including aggregate labour productivity, domestic output and the real exchange rate, are all estimated in a single-equation framework. Third, these equations are then combined with a number of important identi- ties and an interest-rate reaction function to close the model. Then, the impacts of several simulated economic scenarios on Australia's economic landscape are considered. Special emphasis is given to analysing the impact of a large nomi- nal wage shock. The outcomes from these simulated scenarios are pertinent to understanding the inflation process and have important implications for a small open economy like Australia with an explicit inflation target. Overall, the major result to emerge from this thesis is that there is significant statistical support for the hypothesis that wage and price inflation in Australia are jointly determined. This phenomenon has not yet been fully exploited in current macroeconometric models of the Australian economy. The modelling exercise also reveals that the Australian unemployment rate is linear in demand and labour productivity shocks, with nonlinear behaviour caused by real wage rigidity and generous unemployment benefits. Importantly, this simple model is able to simulate the behaviour of the Australian economy extremely well. The outcome from the policy scenarios is clear: both demand-side and supply-side shocks have real and nominal effects on the economy in the short- to medium- run, ceteris paribus. Moreover, a large nominal wage shock to the economy, which results in a real wage rise, will have no sustained effect on the level of domestic activity in the economy, the inflation rate or the real exchange rate. Unemployment is, however, pushed slightly above equilibrium in the short- to medium-run due to a sustained higher real wage level.

Univ., Diss.--Karlsruhe, 2007.

Zugl.: Vallendar, WHU - Otto Beisheim School of Management, 2008.

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies.

This thesis presents Monza, a system for accelerating the simulation of modelsof physical systems described by ordinary differential equations, using a generalpurpose computer with a PCIe FPGA expansion card. The system allows bothautomatic generation of an FPGA implementation from a model described in theModelica programming language, and simulation of said system.Monza accomplishes this by using a customizable hardware architecture forthe FPGA, consisting of a variable number of simple processing elements. A cus-tom compiler, also developed in this thesis, tailors and programs the architectureto run a specific model of a physical system.Testing was done on two test models, a water tank system and a Weibel-lung,with up to several thousand state variables. The resulting system is several timesfaster for smaller models and somewhat slower for larger models compared to aCPU. The conclusion is that the developed hardware architecture and softwaretoolchain is a feasible way of accelerating model execution, but more work isneeded to ensure faster execution at all times.

A 0.24 degrees C jump of record warm global mean surface temperature (GMST) over the past three consecutive record-breaking years (2014-2016) was highly unusual and largely a consequence of an El Nino that released unusually large amounts of ocean heat from the subsurface layer of the northwestern tropical Pacific. This heat had built up since the 1990s mainly due to greenhouse-gas (GHG) forcing and possible remote oceanic effects. Model simulations and projections suggest that the fundamental cause, and robust predictor of large record-breaking events of GMST in the 21st century, is GHG forcing rather than internal climate variability alone. Such events will increase in frequency, magnitude, and duration, as well as impact, in the future unless GHG forcing is reduced.

One of the products produced by Motorpal a.s. is a camshaft. Recently, the company signed a contract with Bosch company to produce new types of camshaft. The analysis of the impact of the contract on the production was made by simulation. To perform the simulation it was necessary to map the whole process. The simulation of the current state was made in the first phase. The results shew many uneffectivnesses in the process and lack of capacity of some workplaces. Some changes in the process were suggested and tested with the aid of the simulation. The best results were achieved when the single-item flow was used. In the second phase the production of a new type of camshaft was added to the simulation. Analysis of these results was divided into two parts. The new production was analysed in the first part and it was discovered that the planned capacites are very deficient. The impact of the new production on the current one was analysed in the second part. It shew that this impact is negativ, especially on the duration of production.

The aim of this paper is to investigate using of hybrid turbulence models for strongly swirling flows. The work is focused on the possibility of applying a hybrid SBES model to simulate flow around a hydrofoil. The work further describes the creation of a mesh for the solved domain, the setting of boundary conditions and the setting of the solution for the software FLUENT. The simulation results are compared with experimentally measured values. The work also uses and evaluates data from PIV measurements. The knowledge that the paper brings as part of the results of a research project can be applied in the future in the design of blades of water turbines.

Diploma thesis is focused on hydraulic assessment of Lipůvka´s sewer system, done by dynamic rainfall-runoff simulation model. Because of this fact, chapter about mathematical models is included. Commonly used programs to this actions are listed as well. Next part of the thesis describes monitoring campaign, which was done in Lipůvka and results are used to calibrate the simulation model. Hydraulic assessment of sewer system by this calibrated model was done.