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The Free Electron Laser (FEL) and Rail Gun are electric weapons which will require a significant amount of stored energy for operation. These types of weapons are ideal for use onboard an all-electric ship. An investigation is made of the effects these weapons will have on a proposed electrical system architecture using simulation modeling. Specifically, this thesis identifies possible design weaknesses and shows where further research and modeling is needed in order to ensure the proper integration of these electric weapons onboard an all-electric ship. The integration of these electric weapon systems with the power systems on electric ships will have an impact on naval operations. Several scenarios concerning specific naval missions are investigated using simulation software to understand the impact and limitations on the electric system using these new electric weapons.

The objective of this thesis was to investigate the suitability of some different Li4Ti5O12 materials as a negative electrode in hybrid supercapacitors. A hybrid supercapacitor is a combination of a battery and an electric double-layer capacitor that uses both a battery material and a capacitor material in the same device. The target for these combination devices is to bridge the performance gap between batteries and capacitors and enable both high energy and power density. To achieve this, materials with high capacity as well as high rate capability are needed. To improve the rate of the commonly slow battery materials nanosizing has been found to be an effective solution. This study shows that Li4Ti5O12 has a significantly higher experimental capacity than the most common capacitor material, activated carbon. The capacity remained high even at high discharge rates due to a successful nanostructuring that increased the accessibility of the material and shortened the diffusion distance for the ions, leading to a much improved power performance compared with the bulk material. The use of a nanostructured Li4Ti5O12 material in a hybrid device together with activated carbon was estimated to double the energy density compared to an electric double-layer capacitor and maintain the same good power performance. To further increase the energy density also improved materials for the positive electrode should be investigated.

Informationssystem är resultatet av samarbete människor emellan. System designas, realiseras, testas och implementeras i de verksamheter som de ska stödja. Samarbetekrävs under alla dessa steg. I utvecklingsarbetets inledning är det inte ovanligt att kraven på systemen formuleras genom projekt som organiseras genom olika typer avsamarbetsformer. I föreliggande avhandling lyfter vi pä locket på samarbetsinriktad modellering och studerar i detalj vad som sker när krav på system formuleras. Genom en gedigen forskningsdesign och ett rikt datamaterial följer vi två modelleringsteam när de facililerar verksamhetsrepresentanter i olika situationer under tre modelleringsprojekt. Avsikten är att utveckla kunskap om vad som utmärker facililering i dessa situationersamt studera vad som utmärker situationsanpassning när modellerarna underlättar och möjliggör arbetet. Genom videobaserad forskning har modelleringsarbetet dokumenterats och med hjälp av olika analysmetoder, såsom konversationsinriktad handlingsanalys och multigrundad teoriutveckling, tolkas episoder i materialet och en plattform för en praktisk teori om facililering utvecklas. Resultatet utgörs av en typologi över samarbetsinriktad modellering, åtgärder för att utföra facililering av arbetet, samt insikter om vad som utmärker situationsanpassning när facilitering utförs och olika omständigheter måste mötas. Synsättet som förespråkas är att tillämpande av struktur och utnyttjandet av frihet är förutsättningar då goda krav på informationssystem ska formuleras genom samarbete.

The main objective of my thesis is to develop a numerical model for small-scale thermal energy storage system and to see the effect of dispersing nano-particles and using fractal-like branching heat exchanger in phase change material for our proposed thermal energy storage system. The associated research problems investigated for phase change material (PCM) are the low thermal conductivity and low rate of heat transfer from heat transfer fluid to PCM in thermal energy storage system. In this study an intensive study is carried out to find the best material for thermal storage and later on as a high conductive nano-particle graphite is used to enhance the effective thermal conductivity of the mixed materials. As a thermal storage material molten solar Salt (60% NaNO3+40%KNO3) has been selected, after that detailed numerical modeling of the proposed design has been done using MATLAB algorithm and following the fixed grid enthalpy method. The model is based on the numerical computation of 1-D finite difference method using explicit scheme. The second part of the study is based on enhancing the heat transfer performance by introducing the concept of fractal network or branching heat exchanger. Results from the numerical computation have been utilized for the comparison between a conventional heating system (with a simple single tube as a heat exchanger) and a passive PCM thermal energy storage system with branching heat exchanger using NTU-effectiveness method and charging time calculation. The comparison results show a significant amount improvement using branching network and mixing nano-particle in terms of heat transfer (13.5% increase in effectiveness of branching level-02 heat exchangers from the conventional one ), thermal conductivity (increased 73.6% with 20% graphite nano-particle mix with solid PCM), charging time (57% decrease of charging time for the effect of both the dispersion of Graphite nano-particle and branching heat exchange) and pressure drop (36% decrease in level-02 branching). The results of this study prove that the proposed medium temperature TES system coupled with solar ORC can be the stepping-stone for energy efficient and sustainable future in small-scale/building level as the system proves to be better in terms of enhanced heat transfer, increased thermal conductivity and reduced pumping power and overall sustainability.

Much of the stochastic groundwater literature is devoted to the analysis of flow and transport in Gaussian or multi-Gaussian log hydraulic conductivity (or transmissivity) fields, Ydx_5ln Kdx_ (x being a position vector), characterized by one or (less frequently) a multiplicity of spatial correlation scales. Yet Y and many other variables and their (spatial or temporal) increments, DY, are known to be generally non-Gaussian. One common manifestation of non-Gaussianity is that whereas frequency distributions of Y often exhibit mild peaks and light tails, those of increments DY are generally symmetric with peaks that grow sharper, and tails that become heavier, as separation scale or lag between pairs of Y values decreases. A statistical model that captures these disparate, scale-dependent distributions of Y and DY in a unified and consistent manner has been recently proposed by us. This new `` generalized sub-Gaussian (GSG)'' model has the form Ydx_5Udx_Gdx_ where Gdx_ is (generally, but not necessarily) a multiscale Gaussian random field and Udx_ is a nonnegative subordinator independent of G. The purpose of this paper is to explore analytically, in an elementary manner, lead-order effects that non-Gaussian heterogeneity described by the GSG model have on the stochastic description of flow and transport. Recognizing that perturbation expansion of hydraulic conductivity K5eY diverges when Y is sub-Gaussian, we render the expansion convergent by truncating Y's domain of definition. We then demonstrate theoretically and illustrate by way of numerical examples that, as the domain of truncation expands, (a) the variance of truncated Y (denoted by Yt) approaches that of Y and (b) the pdf (and thereby moments) of Yt increments approach those of Y increments and, as a consequence, the variogram of Yt approaches that of Y. This in turn guarantees that perturbing Kt5eYt to second order in rYt (the standard deviation of Yt) yields results which approach those we obtain upon perturbing K5eY to second order in rY even as the corresponding series diverges. Our analysis is rendered mathematically tractable by considering mean-uniform steady state flow in an unbounded, twodimensional domain of mildly heterogeneous Y with a single-scale function G having an isotropic exponential covariance. Results consist of expressions for (a) lead-order autocovariance and cross-covariance functions of hydraulic head, velocity, and advective particle displacement and (b) analogues of preasymptotic as well as asymptotic Fickian dispersion coefficients. We compare these theoretically and graphically with corresponding expressions developed in the literature for Gaussian Y. We find the former to differ from the latter by a factor k5hU2 i= hUi 2 (h i denoting ensemble expectation) and the GSG covariance of longitudinal velocity to contain an additional nugget term depending on this same factor. In the limit as Y becomes Gaussian, k reduces to one and the nugget term drops out. Plain Language Summary Much of the stochastic groundwater literature is devoted to the analysis of flow and transport in Gaussian or multi- Gaussian log hydraulic conductivity fields, Y(x), (x being a position vector). Yet Y, as well as many other variables and their increments DY, are known to be generally non- Gaussian. One common manifestation of non- Gaussianity is that whereas frequency distributions of Y often exhibit mild peaks and light tails, those of increments are generally symmetric with peaks that grow sharper, and tails that become heavier, as separation scale or lag between pairs of Y values decreases. A statistical model that captures these disparate, scale- dependent distributions of Y and DY in a unified and consistent manner has been recently proposed by us. This new generalized sub- Gaussian (GSG) model has the form Y(x) 5U(x) G(x) where G(x) is (generally, but not necessarily) a multi- scale Gaussian random field and U(x) is a non- negative subordinator independent of G. The purpose of this paper is to explore analytically lead-order effects that non-Gaussian heterogeneity described by the GSG model have on the stochastic description of flow and transport. Our analysis is rendered mathematically tractable by considering mean uniform steady state flow in an unbounded, two-dimensional domain of mildly heterogeneous Y.

This thesis describes the background, investigation and construction of a system for storing data on the magnetic stripe of a standard three-inch plastic credit in: inch card. Investigation shows that the information storage limit within a 3.375 in by 0.11 in rectangle of the stripe is bounded to about 20 kBytes. Practical issues limit the data storage to around 300 Bytes with a low raw error rate: a four-fold density increase over the standard. Removal of the timing jitter (that is prob-' ably caused by the magnetic medium particle size) would increase the limit to 1500 Bytes with no other system changes. This is enough capacity for either a small digital passport photograph or a digitized signature: making it possible to remove printed versions from the surface of the card. To achieve even these modest gains has required the development of a new variable rate code that is more resilient to timing errors than other codes in its efficiency class. The tabulation of the effects of timing errors required the construction of a new code metric and self-recovering decoders. In addition, a new method of timing recovery, based on the signal 'snatches' has been invented to increase the rapidity with which a Bayesian decoder can track the changing velocity of a hand-swiped card. The timing recovery and Bayesian detector have been integrated into one computation (software) unit that is self-contained and can decode a general class of (d, k) constrained codes. Additionally, the unit has a signal truncation mechanism to alleviate some of the effects of non-linear distortion that are present when a magnetic card is read with a magneto-resistive magnetic sensor that has been driven beyond its bias magnetization. While the storage density is low and the total storage capacity is meagre in comparison with contemporary storage devices, the high density card may still have a niche role to play in society. Nevertheless, in the face of the Smart card its long term outlook is uncertain. However, several areas of coding and detection under short-duration extreme conditions have brought new decoding methods to light. The scope of these methods is not limited just to the credit card.

Call number: LD2668 .T4 1951 P79 / Master of Science

Silo bags are a recently-developed temporary grain storage system that is becoming more widely used in Western Canada without any scientific information about the effect of changing conditions over time on seed quality. The main goal of this study was to examine the conditions that would allow safe storage of canola in these bags in the Canadian Prairie provinces. Canola at three different moisture contents (m.c.) 8.9, 10.5 and 14.4% (wet basis), which represent dry, straight and damp classifications, were stored in silo bags for 40 weeks and seed germination, free fatty acid value (FAV), and moisture content of canola were analysed every 2 weeks along with carbon dioxide concentrations of intergranular air and temperature of canola. For dry grade canola, the germination was maintained above 90%, and FAV stayed within 1.5 times the initial value. However, the germination of damp canola dropped to below 80%, and FAV doubled its initial value within 8 weeks of storage. Another study was conducted for two storage years (2011-12 and 2013-14) to determine the changes in grain quality over time while storing 12% moisture content canola seeds in silo bags. The germination of canola seeds at most parts of the silo bags stayed above a safe level up to the end of the winter season. At the top layer of the silo bags, germination of canola seeds decreased to below 30% and FAV increased more than 2-fold of initial values during summer storage. A polynomial regression model was developed using field data to predict CO2 concentration inside a silo bag with canola. The coefficient of determination of this regression model was 0.76 and had a root mean square error (RMSE) value of 0.196. The standardized coefficients indicated that initial moisture content was 3.9 times more important than storage temperature for CO2 prediction. Permeability to CO2 and O2 of the silo bag material was determined using a specially designed testing unit and the permeability of silo bag material to CO2 was 21.61 ±1.50×10-6 m3 m d-1m-2atm-1, and for O2 was 1.95 ± 0.36×10-6, m3 m d-1m-2atm-1 at room temperature. / May 2016

Image/Video compression has great significance in the communication of motion pictures and still images. The need for compression has resulted in the development of various techniques including transform coding, vector quantization and neural networks. this thesis neural network based methods are investigated to achieve good compression ratios while maintaining the image quality. Parts of this investigation include motion detection, and weight retraining. An adaptive technique is employed to improve the video frame quality for a given compression ratio by frequently updating the weights obtained from training. More specifically, weight retraining is performed only when the error exceeds a given threshold value. Image quality is measured objectively, using the peak signal-to-noise ratio versus performance measure. Results show the improved performance of the proposed architecture compared to existing approaches. The proposed method is implemented in MATLAB and the results obtained such as compression ratio versus signalto- noise ratio are presented.