The behavior of structures is totally different when they are exposed to fluctuating loading rather than static one which is a well known phenomenon in engineering called fatigue. When the loading is not static but dynamic, the dynamics of the structure should be taken into account since there is a high possibility to excite the resonance frequencies of the structure especially if the loading frequency has a wide bandwidth. In these cases, the structure&rsquo / s response to the loading will not be linear. Therefore, in the analysis of such situations, frequency domain fatigue analysis techniques are used which take the dynamic properties of the structure into consideration. Vibration fatigue method is also fast, functional and easy to implement. In this thesis, vibration fatigue theory is examined. Throughout the research conducted for this study, the ultimate aim is to find solutions to problems arising from test application for the loadings with nonzero mean value bringing a new perspective to mean stress correction techniques. A new method is developed to generate a modified input loading history with a zero mean value which leads in fatigue damage approximately equivalent to damage induced by input loading with a nonzero mean value. A mathematical procedure is proposed to implement mean stress correction to the output stress power spectral density data and a modified input loading power spectral density data is obtained. Furthermore, this method is improved for multiaxial loading applications. A loading history power spectral density set with zero mean but modified alternating stress, which leads in fatigue damage approximately equivalent to the damage caused by the unprocessed loading set with nonzero mean, is extracted taking all stress components into account using full matrixes. The proposed techniques&rsquo / efficiency is discussed throughout several case studies and fatigue tests.

During the last decade, the transit method has evolved to one of the most promising techniques in the search for extrasolar planets and the quest to find other earth-like worlds. In theory, the transit method is straight forward being based on the detection of an apparent dimming of the host star’s light due to an orbiting planet traversing in front of the observer. However, in practice, the detection of such light curve dips and their confident ascription to a planetary transit is heavily burdened by the presence of different sources of noise, the most prominent of which is probably the so called intrinsic stellar variability. Filtering out potential transit signals from background noise requires a well adjusted high-pass filter. In order to optimize such a filter, i.e. to achieve best separation between signal and noise, one typically requires access to benchmark datasets that exhibit the same light curve with and without obstructing noise. Several methods for simulating stellar variability have been proposed for the construction of such benchmark datasets. However, while such methods have been widely used in testing transit method detection algorithms in the past, it is not very well known how such simulations compare to real recorded light curves - a fact that might be contributed to the lack of large databases of stellar light curves for comparisons at that time. With the increasing amount of light curve data now available due to missions such as Kepler, I have here undertaken such a comparison of synthetic and real light curves for one particular method that simulates stellar variability based on scaled power spectra of the Sun’s flux variations. Conducting the respective comparison also in terms of estimated power spectra of real and simulated light curves, I have revealed that the two datasets exhibit substantial differences in average power, with the synthetic power spectra having generally a lower power and also lacking certain distinct power peaks present in the real light curves. The results of this study suggest that scaled power spectra of solar variability alone might be insufficient for light curve simulations and that more work will be required to understand the origin and relevance of the observed power peaks in order to improve on such light curve models.

A potential characterization tool for printer quality is the power spectral density (PSD) analysis of flat-field printer outputs. This thesis explains the relationship between the PSD and characteristics of printer defects using examples of scanned printer outputs. In addition, a protocol is also presented for scanning flat fields and performing a PSD analysis. The protocol considers sampling and windowing issues to best focus on defects or quality issues of interest. The main objective of this work is to determine the interactive relationships of print defect patterns such as graininess, streaking, and banding under flat-field hardcopy outputs. The additive and multiplicative models are considered for describing the interaction between printer defects. Simulated print defect patterns and metrics base on the PSD are used to demonstrate the patterns generated by multiplicative and additive processes. These results are compared the PSD of actual flat-field prints from digital printers to draw conclusion concerning actual artifact interaction. For all defects examined the additive model is shown to be a good model of the interactions between printer defects.

A survey of the literature of grinding and surface texture shows the influence of dressing and wear on surfaces involved in the process and the advantages of stylus profilometry for data collection from both grinding wheels and ground surfaces. Statistical analysis is favoured for surface profile characterization and, of the various parameters used, power spectral density alone offers some prospect of effective comparison between these surfaces. Work on grinding with single crystals of natural corundum was eventually discontinued in favour of experiments with conventional bonded grinding wheels subjected to a dressing operation and some wear in grinding steel surfaces. Statistical parameters representing the surfaces are computed using data obtained from profilograms. Results in terms of power spectral density are presented showing progressive improvement following upon developments in apparatus and methods which facilitated the use of larger surface profile samples. Transfer functions are used to relate power spectra representing corresponding pairs of surfaces. The significance of power spectral density applied to surface profile characterization is discussed and, in this context, it is suggested that these should be described as variance spectra. Attention is drawn to certain disadvantages of variance spectra applied to grinding wheel and ground surface profiles. Methods designed to improve presentation of variance spectra lead to development of a proposed new and more suitable spectrum in which density of standard deviation of surface profile ordinates with respect to frequency is plotted against frequency. Transfer functions calculated from related pairs of these standard deviation spectra show a strong linear correlation with frequency and offer prospects of convenient comparison between the profiles of the various surfaces involved in grinding.

Transcranial direct current stimulation (TDCS) allows for the noninvasive modulation of cortical activity. In this study, the effects of cathodal and anodal TDCS treatment on baseline activity in the motor cortex of rats were investigated via translaminar electroencephalogram (EEG) recording and power spectral density analysis. Treatment with low intensity anodal TDCS for five minutes was found to increase delta and theta frequency cortical activity during and for up to five minutes following treatment. This study also assessed the interaction of TDCS with the phenomenon of cortical spreading depression (CoSD), which has been implicated in numerous disease states, including migraine and stroke. TDCS treatment was given concurrently with induction of CoSD via administration of potassium chloride to the surface of the dura. The presence of the spreading depression event, a characteristic low frequency wave observed to travel outwards from the point of CoSD induction and downwards through the cortex, was used as a proxy measure for the occurrence of CoSD. It was observed that animals treated with cathodal TDCS exhibited fewer spreading depression events relative to those treated with anodal TDCS or those receiving sham treatment. In this study, animals were segregated into groups that exhibited stimulus artifact during TDCS treatment and those that did not. Stimulus artifact was defined as a characteristic alpha and/or beta frequency activity spike lasting throughout and not longer than the period of stimulation. Those animals receiving TDCS without exhibiting stimulus artifact were considered for the purposes of this study to not have received proper TDCS treatment, and acted as a sham treatment group. Because salient differences emerged between the stimulus artifact positive and stimulus artifact negative groups, this study suggests that the presence of stimulus artifact could be used as a proxy measure for successful TDCS dosage.

abstract: Recent new experiments showed that wide-field imaging at millimeter scale is capable of recording hundreds of neurons in behaving mice brain. Monitoring hundreds of individual neurons at a high frame rate provides a promising tool for discovering spatiotemporal features of large neural networks. However, processing the massive data sets is impossible without automated procedures. Thus, this thesis aims at developing a new tool to automatically segment and track individual neuron cells. The new method used in this study employs two major ideas including feature extraction based on power spectral density of single neuron temporal activity and clustering tree to separate overlapping cells. To address issues associated with high-resolution imaging of a large recording area, focused areas and out-of-focus areas were analyzed separately. A static segmentation with a fixed PSD thresholding method is applied to within focus visual field. A dynamic segmentation by comparing maximum PSD with surrounding pixels is applied to out-of-focus area. Both approaches helped remove irrelevant pixels in the background. After detection of potential single cells, some of which appeared in groups due to overlapping cells in the image, a hierarchical clustering algorithm is applied to separate them. The hierarchical clustering uses correlation coefficient as a distance measurement to group similar pixels into single cells. As such, overlapping cells can be separated. We tested the entire algorithm using two real recordings with the respective truth carefully determined by manual inspections. The results show high accuracy on tested datasets while false positive error is controlled within an acceptable range. Furthermore, results indicate robustness of the algorithm when applied to different image sequences. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016

Made available in DSpace on 2014-10-09T12:41:26Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:03:23Z (GMT). No. of bitstreams: 0 / Dissertação (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

Obtemos a expressão da densidade espectral de uma impureza no modelo de Anderson assimétrico. No regime de Kondo de baixas energias o modelo de Anderson descreve sistemas quânticos com impurezas magnéticas em meios não magnéticos. Para energias características do orbital de impureza simples ou duplamente ocupado iguais a εf e 2εf+U, respectivamente, o modelo é chamado simétrico para 2εf + U = 0 e assimétrico quando 2εf + U ≠ 0. Para o caso simétrico existe uma expressão devido a Frota que descreve ressonância de Kondo na densidade espectral. Todavia, no caso assimétrico a expressão de Frota deixa de ser válida e é necessária uma nova abordagem. Nesta dissertação, a partir de dados numéricos obtidos pelo consagrado método do Grupo de Renormalização Numérico criado por Wilson em 1974 e de tópicos da física de muitos corpos estudamos a assimetria do modelo de Anderson no regime de Kondo e propomos uma expressão mais geral que a de Frota para a densidade espectral da impureza. / We propose an analytical expression for the impurity spectral density in the Kondo regime of the spin-degenerate asymmetric Anderson model. The Anderson model describes quantum systems of magnetic impurities in nonmagnetic metals. For characteristic energies of single and double impurity occupations εf and 2εf+U, respectively, the model is particlehole symmetric for 2εf + U = 0 and asymmetrical 2εf + U ≠ 0. In the symmetric case, there is an expression due to Frota that describes the Kondo resonance in the spectral density. However, in the asymmetric case Frota´s expression is not valid, and a new approach is necessary. In this work, starting with numerical data provided by the Numerical Renormalization Group method developed by Wilson in 1974, we study the asymmetric Anderson model in the Kondo regime and propose an expression for the impurity spectral density that is more general than Frota´s.

Made available in DSpace on 2014-10-09T12:41:26Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:03:23Z (GMT). No. of bitstreams: 0 / Este trabalho apresenta o estudo do efeito do refletor sobre o tempo de vida neutrônico do Reator IPEN/MB-01. O método empregado requer uma abordagem que leve em conta tanto o núcleo quanto o refletor, de modo que as equações de cinética pontual, as quais constituem a base teórica de todo desenvolvimento matemático, contemplem ambas as regiões do reator. A partir dessas equações, conhecidas como equações de cinética pontual do modelo duas regiões, são obtidas as expressões teóricas para as APSDs (Auto Power Spectral Densities), as quais são utilizadas para o ajuste por mínimos quadrados aos dados das APSDs experimentais obtidas em vários estados subcríticos. O tempo de geração de nêutrons prontos, o tempo de vida dos nêutrons no refletor e a fração desses nêutrons que retornam ao núcleo, são obtidos como parâmetros do ajuste. / Dissertação (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

A large-area electronics (LAE) strain sensor, termed soft elastomeric capacitor (SEC), has shown great promise in fatigue crack monitoring. The SEC is capable to monitor strain changes over a large structural surface and undergo large deformations under cracking. Previous tests verified that the SEC can detect and localize fatigue cracks under low-cycle fatigue loading. In this paper, we further investigate the SEC's capability for monitoring high-cycle fatigue cracks, which are commonly seen in steel bridges. The peak-to-peak amplitude (pk-pk amplitude) of the SEC measurement is proposed as an indicator of crack growth. This technique is is robust and insensitive to long-term capacitance drift. To overcome the difficulty of identifying the pk-pk amplitude in time series due to high signal-to-noise ratio, a signal processing method is established. This method converts the measured SEC capacitance and applied load to power spectral densities (PSD) in the frequency domain, such that the pk-pk amplitudes of the measurements can be accurately extracted. Finally, the performance of this method is validated using a fatigue test of a compact steel specimen equipped with a SEC. Results show that the crack growth under high-cycle fatigue loading can be successfully monitored using the proposed signal processing method.