917 resultados para Power Sensitivity Model


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As increasing efficiency of a wind turbine gearbox, more power can be transferred from rotor blades to generator and less power is used to cause wear and heating in the gearbox. By using a simulation model, behavior of the gearbox can be studied before creating expensive prototypes. The objective of the thesis is to model a wind turbine gearbox and its lubrication system to study power losses and heat transfer inside the gearbox and to study the simulation methods of the used software. Software used to create the simulation model is Siemens LMS Imagine.Lab AMESim, which can be used to create one-dimensional mechatronic system simulation models from different fields of engineering. When combining components from different libraries it is possible to create a simulation model, which includes mechanical, thermal and hydraulic models of the gearbox. Results for mechanical, thermal, and hydraulic simulations are presented in the thesis. Due to the large scale of the wind turbine gearbox and the amount of power transmitted, power loss calculations from AMESim software are inaccurate and power losses are modelled as constant efficiency for each gear mesh. Starting values for simulation in thermal and hydraulic simulations were chosen from test measurements and from empirical study as compact and complex design of gearbox prevents accurate test measurements. In further studies to increase the accuracy of the simulation model, components used for power loss calculations needs to be modified and values for unknown variables are needed to be solved through accurate test measurements.

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Gear rattle is a phenomenon that occurs when idling or lightly loaded gears collide due to engine’s torque fluctuations. This behaviour is related to vibration behaviour of the transmission system. Aim of this master’s thesis is to evaluate Adams and Adams/Machinery as a simulation tools for modelling the rattle e ect in a transmission system. A case study of tractor’s power take-o driveline, suspected to be prone to rattle, is performed in this work. Modelling methods used by Adams in this type of study are presented in the theory section while simulation model build with the software during this work is presented in the results. The Machinery toolbox is used to create gears and bearings while other model components are created with standard Adams tool set. Geometries and excitations are exported from other softwares. Results were obtained from multiple variations of a base model. These result sets and literature review suggest that Adams/Machinery may not be the most suitable tool for rattle analysis. While the system behaviour was partially captured, for accurate modelling user-written routines must be used which may be more easily performed with other tools. Further research about this topic is required.

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The application of VSC-HVDC technology throughout the world has turned out to be an efficient solution regarding a large share of wind power in different power systems. This technology enhances the overall reliability of the grid by utilization of the active and reactive power control schemes which allows to maintain frequency and voltage on busbars of the end-consumers at the required level stated by the network operator. This master’s thesis is focused on the existing and planned wind farms as well as electric power system of the Åland Islands. The goal is to analyze the wind conditions of the islands and appropriately predict a possible production of the existing and planned wind farms with a help of WAsP software program. Further, to investigate the influence of increased wind power it is necessary to develop a simulation model of the electric grid and VSC-HVDC system in PSCAD and examine grid response to different wind power production cases with respect to the grid code requirements and ensure the stability of the power system.

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This study is done to examine waste power plant’s optimal processing chain and it is important to consider from several points of view on why one option is better than the other. This is to insure that the right decision is made. Incineration of waste has devel-oped to be one decent option for waste disposal. There are several legislation matters and technical options to consider when starting up a waste power plant. From the tech-niques pretreatment, burner and flue gas cleaning are the biggest ones to consider. The treatment of incineration residues is important since it can be very harmful for the envi-ronment. The actual energy production from waste is not highly efficient and there are several harmful compounds emitted. Recycling of waste before incineration is not very typical and there are not many recycling options for materials that cannot be easily re-cycled to same product. Life cycle assessment is a good option for studying the envi-ronmental effect of the system. It has four phases that are part of the iterative study process. In this study the case environment is a waste power plant. The modeling of the plant is done with GaBi 6 software and the scope is from gate-to-grave. There are three different scenarios, from which the first and second are compared to each other to reach conclusions. Zero scenario is part of the study to demonstrate situation without the power plant. The power plant in this study is recycling some materials in scenario one and in scenario two even more materials and utilize the bottom ash more ways than one. The model has the substitutive processes for the materials when they are not recycled in the plant. The global warming potential results show that scenario one is the best option. The variable costs that have been considered tell the same result. The conclusion is that the waste power plant should not recycle more and utilize bottom ash in a number of ways. The area is not ready for that kind of utilization and production from recycled materials.

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A new approach to the determination of the thermal parameters of high-power batteries is introduced here. Application of local heat flux measurement with a gradient heat flux sensor (GHFS) allows determination of the cell thermal parameters in di_erent surface points of the cell. The suggested methodology is not cell destructive as it does not require deep discharge of the cell or application of any charge/discharge cycles during measurements of the thermal parameters of the cell. The complete procedure is demonstrated on a high-power Li-ion pouch cell, and it is verified on a sample with well-known thermal parameters. A comparison of the experimental results with conventional thermal characterization methods shows an acceptably low error. The dependence of the cell thermal parameters on state of charge (SoC) and measurement points on the surface was studied by the proposed measurement approach.

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In this work an agent based model (ABM) was proposed using the main idea from the Jabłonska-Capasso-Morale (JCM) model and maximized greediness concept. Using a multi-agents simulator, the power of the ABM was assessed by using the historical prices of silver metal dating from the 01.03.2000 to 01.03.2013. The model results, analysed in two different situations, with and without maximized greediness, have proven that the ABM is capable of explaining the silver price dynamics even in utmost events. The ABM without maximal greediness explained the prices with more irrationalities whereas the ABM with maximal greediness tracked the price movements with more rational decisions. In the comparison test, the model without maximal greediness stood as the best to capture the silver market dynamics. Therefore, the proposed ABM confirms the suggested reasons for financial crises or markets failure. It reveals that an economic or financial collapse may be stimulated by irrational and rational decisions, yet irrationalities may dominate the market.

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The purpose of this master’s thesis is to gain an understanding of passive safety systems’ role in modern nuclear reactors projects and to research the failure modes of passive decay heat removal safety systems which use phenomenon of natural circulation. Another purpose is to identify the main physical principles and phenomena which are used to establish passive safety tools in nuclear power plants. The work describes passive decay heat removal systems used in AES-2006 project and focuses on the behavior of SPOT PG system. The descriptions of the main large-scale research facilities of the passive safety systems of the AES-2006 power plant are also included. The work contains the calculations of the SPOT PG system, which was modeled with thermal-hydraulic system code TRACE. The dimensions of the calculation model are set according to the dimensions of the real SPOT PG system. In these calculations three parameters are investigated as a function of decay heat power: the pressure of the system, the natural circulation mass flow rate around the closed loop, and the level of liquid in the downcomer. The purpose of the calculations is to test the ability of the SPOT PG system to remove the decay heat from the primary side of the nuclear reactor in case of failure of one, two, or three loops out of four. The calculations show that three loops of the SPOT PG system have adequate capacity to provide the necessary level of safety. In conclusion, the work supports the view that passive systems could be widely spread in modern nuclear projects.

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Transmission system operators and distribution system operators are experiencing new challenges in terms of reliability, power quality, and cost efficiency. Although the potential of energy storages to face those challenges is recognized, the economic implications are still obscure, which introduce the risk into the business models. This thesis aims to investigate the technical and economic value indicators of lithium-ion battery energy storage systems (BESS) in grid-scale applications. In order to do that, a comprehensive performance lithium-ion BESS model with degradation effects estimation is developed. The model development process implies literature review on lifetime modelling, use, and modification of previous study progress, building the additional system parts and integrating it into a complete tool. The constructed model is capable of describing the dynamic behavior of the BESS voltage, state of charge, temperature and capacity loss. Five control strategies for BESS unit providing primary frequency regulation are implemented, in addition to the model. The questions related to BESS dimensioning and the end of life (EoL) criterion are addressed. Simulations are performed with one-month real frequency data acquired from Fingrid. The lifetime and cost-benefit analysis of the simulation results allow to compare and determine the preferable control strategy. Finally, the study performs the sensitivity analysis of economic profitability with variable size, EoL and system price. The research reports that BESS can be profitable in certain cases and presents the recommendations.

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Adults and children can discriminate various emotional expressions, although there is limited research on sensitivity to the differences between posed and genuine expressions. Adults have shown implicit sensitivity to the difference between posed and genuine happy smiles in that they evaluate T-shirts paired with genuine smiles more favorably than T-shirts paired with posed smiles or neutral expressions (Peace, Miles, & Johnston, 2006). Adults also have shown some explicit sensitivity to posed versus genuine expressions; they are more likely to say that a model i?,feeling happy if the expression is genuine than posed. Nonetheless they are duped by posed expressions about 50% of the time (Miles, & Johnston, in press). There has been no published study to date in which researchers report whether children's evaluation of items varies with expression and there is little research investigating children's sensitivity to the veracity of facial expressions. In the present study the same face stimuli were used as in two previous studies (Miles & Johnston, in press; Peace et al., 2006). The first question to be addressed was whether adults and 7-year-olds have a cognitive understanding of the differences between posed and genuine happiness {scenario task). They evaluated the feelings of children who expressed gratitude for a present that they did or did not want. Results indicated that all participants had a fundamental understanding of the difference between real and posed happiness. The second question involved adults' and children's implicit sensitivity to the veracity of posed and genuine smiles. Participants rated and ranked beach balls paired with faces showing posed smiles, genuine smiles, and neutral expressions. Adults ranked.but did not rate beach balls paired with genuine smiles more favorably than beach balls paired with posed smiles. Children did not demonstrate implicit sensitivity as their ratings and rankings of beach balls did not vary with expressions; they did not even rank beach balls paired with genuine expressions higher than beach balls paired with neutral expressions. In the explicit (show/feel) task, faces were presented without the beach balls and participants were first asked whether each face was showing happy and then whether each face wasfeeling happy. There were also two matching trials that presented two faces at once; participants had to indicate which person was actuallyfeeling happy. In the show condition both adults and 7-year-olds were very accurate on genuine and neutral expressions but made some errors on posed smiles. Adults were fooled about 50% of the time by posed smiles in thefeel condition (i.e., they were likely to say that a model posing happy was really feeling happy) and children were even less accurate, although they showed weak sensitivity to posed versus genuine expressions. Future research should test an older age group of children to determine when explicit sensitivity to posed versus genuine facial expressions becomes adult-like and modify the ranking task to explore the influence of facial expressions on object evaluations.

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Developmental coordination disorder (DCD) is a motor coordination disorder that is characterized by impairment of motor skills which leads to challenges with performing activities of daily living. Children with DCD have been shown to be less physically active and have increased body fatness. This is an important finding since a sedentary lifestyle and obesity are risk factors for cardiovascular disease. One indicator of cardiovascular health is baroreflex sensitivity (BRS), which is a measure of short term BP regulation that is accomplished through changes in HR. Diminished BRS is predictive of cardiovascular morbidity and mortality. The purpose of this study was to investigate BRS in 117 children aged 12 to 13 years with probable DCD (pOCO) and their matched controls with normal coordination. Following 15 minutes of supine rest, five minutes of continuous beat-by-beat blood pressure (Finapres) and RR interval were recorded (standard ECG). Spectral indices were computed using Fast Fourier Transform and transfer function analysis was used to compute BRS. High frequency and low frequency power spectral areas were set to 0.15-0.6 Hz and 0.04-0.15 Hz, respectively. BRS was compared between groups with an independent t-test and the difference was not significant. It is likely that a difference in BRS was not seen between groups since the difference in BMI between groups was small. As well, differences in BRS may not have manifested yet at this early age. However, the cardiovascular health of this population still deserves attention since differences in body composition and fitness were found between groups.

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The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

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O'Fallon and Butterfield (2005) in a review of the business ethics literature concluded that "ethical awareness" also called ethical sensitivity has received the least attention of the four steps in Rest's (1986) ethical decision making model. Available measures for ethical sensitivity are limited to specific contexts and suffer from several limitations. I extend the previous literature by creating a new measure for ethical sensitivity (AESS) that encompasses relevant dimensions for the accounting profession and is not specific to a particular setting. I also introduce a new individual differences variable to the accounting ethics literature. Specifically, I investigate the relationship between anti-intellectualism and ethical awareness. My findings support AESS as a measure of ethical sensitivity.

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Analysis of power in natural resources management is important as multiple stakeholders interact within complex, social-ecological systems. As a sub-set of these interactions, community climate change adaptation is increasingly using participatory processes to address issues of local concern. While some attention has been paid to power relations in this respect, e.g. evaluating international climate regimes or assessing vulnerability as part of integrated impact assessments, little attention has been paid to how a structured assessment of power could facilitate real adaptation and increase the potential for successful participatory processes. This paper surveys how the concept of power is currently being applied in natural resources management and links these ideas to agency and leadership for climate change adaptation. By exploring behavioural research on destructive leadership, a model is developed for informing participatory climate change adaptation. The working paper then concludes with a discussion of developing research questions in two specific areas - examining barriers to adaptation and mapping the evolution of specific participatory processes for climate change adaptation.

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The Feedback-Related Negativity (FRN) is thought to reflect the dopaminergic prediction error signal from the subcortical areas to the ACC (i.e., a bottom-up signal). Two studies were conducted in order to test a new model of FRN generation, which includes direct modulating influences of medial PFC (i.e., top-down signals) on the ACC at the time of the FRN. Study 1 examined the effects of one’s sense of control (top-down) and of informative cues (bottom-up) on the FRN measures. In Study 2, sense of control and instruction-based (top-down) and probability-based expectations (bottom-up) were manipulated to test the proposed model. The results suggest that any influences of medial PFC on the activity of the ACC that occur in the context of incentive tasks are not direct. The FRN was shown to be sensitive to salient stimulus characteristics. The results of this dissertation partially support the reinforcement learning theory, in that the FRN is a marker for prediction error signal from subcortical areas. However, the pattern of results outlined here suggests that prediction errors are based on salient stimulus characteristics and are not reward specific. A second goal of this dissertation was to examine whether ACC activity, measured through the FRN, is altered in individuals at-risk for problem-gambling behaviour (PG). Individuals in this group were more sensitive to the valence of the outcome in a gambling task compared to not at-risk individuals, suggesting that gambling contexts increase the sensitivity of the reward system to valence of the outcome in individuals at risk for PG. Furthermore, at-risk participants showed an increased sensitivity to reward characteristics and a decreased response to loss outcomes. This contrasts with those not at risk whose FRNs were sensitive to losses. As the results did not replicate previous research showing attenuated FRNs in pathological gamblers, it is likely that the size and time of the FRN does not change gradually with increasing risk of maladaptive behaviour. Instead, changes in ACC activity reflected by the FRN in general can be observed only after behaviour becomes clinically maladaptive or through comparison between different types of gain/loss outcomes.

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We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.