Effect of wave frequency on the nonlinear interaction between Görtler vortices and three-dimensional Tollmien-Schlichting waves

The nonlinear interaction between Görtler vortices (GV) and three-dimensional Tollmien-Schlichting (TS) waves nonlinear interaction is studied with a spatial, nonparallel model based on the Parabolized Stability Equations (PSE). In this investigation the effect of TS wave frequency on the nonlinear interaction is studied. As verified in previous investigations using the same numerical model, the relative amplitudes and growth rates are the dominant parameters in GV/TS wave interaction. In this sense, the wave frequency influence is important in defining the streamwise distance traveled by the disturbances in the unstable region of the stability diagram and in defining the amplification rates that they go through.

Numerical study of Petrov-Galerkin formulations for the shallow water wave equations

The behavior of Petrov-Galerkin formulations for shallow water wave equations is evaluated numerically considering typical one-dimensional propagation problems. The formulations considered here use stabilizing operators to improve classical Galerkin approaches. Their advantages and disadvantages are pointed out according to the intrinsic time scale (free parameter) which has a particular importance in this kind of problem. The influence of the Courant number and the performance of the formulation in dealing with spurious oscillations are adressed.

Numerical study of wedge supported oblique shock wave-oblique detonation wave transitions

The results of a numerical study of premixed Hydrogen-air flows ignition by an oblique shock wave (OSW) stabilized by a wedge are presented, in situations when initial and boundary conditions are such that transition between the initial OSW and an oblique detonation wave (ODW) is observed. More precisely, the objectives of the paper are: (i) to identify the different possible structures of the transition region that exist between the initial OSW and the resulting ODW and (ii) to evidence the effect on the ODW of an abrupt decrease of the wedge angle in such a way that the final part of the wedge surface becomes parallel to the initial flow. For such a geometrical configuration and for the initial and boundary conditions considered, the overdriven detonation supported by the initial wedge angle is found to relax towards a Chapman-Jouguet detonation in the region where the wedge surface is parallel to the initial flow. Computations are performed using an adaptive, unstructured grid, finite volume computer code previously developed for the sake of the computations of high speed, compressible flows of reactive gas mixtures. Physico-chemical properties are functions of the local mixture composition, temperature and pressure, and they are computed using the CHEMKIN-II subroutines.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

Cardiovascular and respiratory changes during slow-wave sleep in rats are associated with electrocorticogram desynchronization

In awake rats a single recurrent larger tidal volume (deep breaths) occurs at regular intervals, followed by oscillations in arterial pressure and heart rate. In the present study we recorded the changes in blood pressure, heart rate and ventilation during the wakefulness-sleep cycle identified by electrocorticographic records in order to determine whether the deep breaths and cardiovascular oscillations were associated with changes in the electrocorticogram. During several episodes of slow-wave sleep (SWS) in 7 rats the deep breaths and oscillations in arterial pressure and heart rate were preceded by SWS desynchronization. The interval between deep breaths during SWS was 71 ± 4 s, the period between initial desynchronization and the generation of deep breaths was 3.98 ± 0.45 s and the duration of SWS desynchronization was 11 ± 0.65 s. Hypotension (-16 ± 1 mmHg) and tachycardia (+15 ± 5 bpm) were observed during deep breaths in the SWS state. These data indicate that the oscillations in arterial pressure and heart rate during SWS are associated with deep breaths, which in turn are preceded by desynchronization of the electrocorticogram in this state of sleep

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Radial frequency stimuli and sine-wave gratings seem to be processed by distinct contrast brain mechanisms

An assumption commonly made in the study of visual perception is that the lower the contrast threshold for a given stimulus, the more sensitive and selective will be the mechanism that processes it. On the basis of this consideration, we investigated contrast thresholds for two classes of stimuli: sine-wave gratings and radial frequency stimuli (i.e., j0 targets or stimuli modulated by spherical Bessel functions). Employing a suprathreshold summation method, we measured the selectivity of spatial and radial frequency filters using either sine-wave gratings or j0 target contrast profiles at either 1 or 4 cycles per degree of visual angle (cpd), as the test frequencies. Thus, in a forced-choice trial, observers chose between a background spatial (or radial) frequency alone and the given background stimulus plus the test frequency (1 or 4 cpd sine-wave grating or radial frequency). Contrary to our expectations, the results showed elevated thresholds (i.e., inhibition) for sine-wave gratings and decreased thresholds (i.e., summation) for radial frequencies when background and test frequencies were identical. This was true for both 1- and 4-cpd test frequencies. This finding suggests that sine-wave gratings and radial frequency stimuli are processed by different quasi-linear systems, one working at low luminance and contrast level (sine-wave gratings) and the other at high luminance and contrast levels (radial frequency stimuli). We think that this interpretation is consistent with distinct foveal only and foveal-parafoveal mechanisms involving striate and/or other higher visual areas (i.e., V2 and V4).

Development of project cash flow forecasting process

Process management refers to improving the key functions of a company. The main functions of the case company - project management, procurement, finance, and human resource - use their own separate systems. The case company is in the process of changing its software. Different functions will use the same system in the future. This software change causes changes in some of the company’s processes. Project cash flow forecasting process is one of the changing processes. Cash flow forecasting ensures the sufficiency of money and prepares for possible changes in the future. This will help to ensure the company’s viability. The purpose of the research is to describe a new project cash flow forecasting process. In addition, the aim is to analyze the impacts of the process change, with regard to the project control department’s workload and resources through the process measurement, and how the impacts take the department’s future operations into account. The research is based on process management. Processes, their descriptions, and the way the process management uses the information, are discussed in the theory part of this research. The theory part is based on literature and articles. Project cash flow and forecasting-related benefits are also discussed. After this, the project cash flow forecasting as-is and to-be processes are described by utilizing information, obtained from the theoretical part, as well as the know-how of the project control department’s personnel. Written descriptions and cross-functional flowcharts are used for descriptions. Process measurement is based on interviews with the personnel – mainly cost controllers and department managers. The process change and the integration of two processes will allow work time for other things, for example, analysis of costs. In addition to the quality of the cash flow information will improve compared to the as-is process. Analyzing the department’s other main processes, department’s roles, and their responsibilities should be checked and redesigned. This way, there will be an opportunity to achieve the best possible efficiency and cost savings.

Accuracy in book papers' sales forecasting

The main objective of this thesis was to study if the quantitative sales forecasting methods will enhance the accuracy of the sales forecast in comparison to qualitative sales forecasting method. A literature review in the field of forecasting was conducted, including general sales forecasting process, forecasting methods and techniques and forecasting accuracy measurement. In the empirical part of the study the accuracy of the forecasts provided by both qualitative and quantitative methods is being studied and compared in the case of short, medium and long term forecasts. The SAS® Forecast Server –tool was used in creating the quantitative forecasts.

Immediate effects of submaximal effort on pulse wave velocity in patients with Marfan syndrome

Marfan syndrome (MS) is a dominant autosomal disease caused by mutations in chromosome 15, the locus controlling fibrillin 1 synthesis, and may exhibit skeletal, ocular, cardiovascular, and other manifestations. Pulse wave velocity (PWV) is used to measure arterial elasticity and stiffness and is related to the elastic properties of the vascular wall. Since the practice of exercise is limited in MS patients, it was of interest to analyze the acute effect of submaximal exercise on aortic distensibility using PWV and other hemodynamic variables in patients with MS with either mild or no aortic dilatation. PWV and physiological variables were evaluated before and after submaximal exercise in 33 patients with MS and 18 controls. PWV was 8.51 ± 0.58 at rest and 9.10 ± 0.63 m/s at the end of exercise (P = 0.002) in the group with MS and 8.07 ± 0.35 and 8.98 ± 0.56 m/s in the control group, respectively (P = 0.004). Comparative group analysis regarding PWV at rest and at the end of exercise revealed no statistically significant differences. The same was true for the group that used β-blockers and the one that did not. The final heart rate was 10% higher in the control group than in the MS group (P = 0.01). Final systolic arterial pressure was higher in the control group (P = 0.02). PWV in MS patients with mild or no aortic dilatation did not differ from the control group after submaximal effort.

Reference value of brachial-ankle pulse wave velocity for the eastern Chinese population and potential influencing factors

The present study was conducted to obtain reference values for brachial-ankle pulse wave velocity (baPWV) and to evaluate influencing factors of baPWV according to gender. Using automatic devices, baPWV was measured simultaneously in 2095 subjects. A total of 647 healthy subjects, none of whom presented atherosclerotic risk factors, were analyzed in the present study. Two different statistical methods were used to obtain reference values for baPWV according to subject gender and age. The association between baPWV value and gender, as well as other features, were analyzed. For male subjects, multiple stepwise analysis showed that age, systolic blood pressure (SBP), heart rate (HR), and plasma levels of triglycerides (TG) were independent predictors of baPWV. For female subjects, age, SBP, HR, and plasma levels of uric acid (UA) were independent predictors of baPWV. In male subjects, the upper limits of baPWV values were 1497.43/1425.00, 1518.67/1513.25, 1715.97/1726.50, 1925.20/1971.90, and 2310.18/2115.00 cm/s, obtained using two different statistical methods for the age ranges of 30-39, 40-49, 50-59, 60-69, and 70 and older, respectively. For females, the upper limits of baPWV values were 1426.70/1411.13, 1559.15/1498.95, 1733.50/1739.00, 1958.63/1973.78, and 2720.80/2577.00 cm/s for the age ranges of 30-39, 40-49, 50-59, 60-69, and 70 and older, respectively. Aging is the most important influencing factor for baPWV value and its effect is more prominent in females. The reference values of baPWV according to age and gender may be useful for the clinical diagnosis and preventive therapy of cardiovascular diseases.