Statistics of the received power for free space optical channels

Free space optical (FSO) communication links can experience extreme signal degradation due to atmospheric turbulence induced spatial and temporal irradiance fuctuations (scintillation) in the laser wavefront. In addition, turbulence can cause the laser beam centroid to wander resulting in power fading, and sometimes complete loss of the signal. Spreading of the laser beam and jitter are also artifacts of atmospheric turbulence. To accurately predict the signal fading that occurs in a laser communication system and to get a true picture of how this affects crucial performance parameters like bit error rate (BER) it is important to analyze the probability density function (PDF) of the integrated irradiance fuctuations at the receiver. In addition, it is desirable to find a theoretical distribution that accurately models these ?uctuations under all propagation conditions. The PDF of integrated irradiance fuctuations is calculated from numerical wave-optic simulations of a laser after propagating through atmospheric turbulence to investigate the evolution of the distribution as the aperture diameter is increased. The simulation data distribution is compared to theoretical gamma-gamma and lognormal PDF models under a variety of scintillation regimes from weak to very strong. Our results show that the gamma-gamma PDF provides a good fit to the simulated data distribution for all aperture sizes studied from weak through moderate scintillation. In strong scintillation, the gamma-gamma PDF is a better fit to the distribution for point-like apertures and the lognormal PDF is a better fit for apertures the size of the atmospheric spatial coherence radius ρ0 or larger. In addition, the PDF of received power from a Gaussian laser beam, which has been adaptively compensated at the transmitter before propagation to the receiver of a FSO link in the moderate scintillation regime is investigated. The complexity of the adaptive optics (AO) system is increased in order to investigate the changes in the distribution of the received power and how this affects the BER. For the 10 km link, due to the non-reciprocal nature of the propagation path the optimal beam to transmit is unknown. These results show that a low-order level of complexity in the AO provides a better estimate for the optimal beam to transmit than a higher order for non-reciprocal paths. For the 20 km link distance it was found that, although minimal, all AO complexity levels provided an equivalent improvement in BER and that no AO complexity provided the correction needed for the optimal beam to transmit. Finally, the temporal power spectral density of received power from a FSO communication link is investigated. Simulated and experimental results for the coherence time calculated from the temporal correlation function are presented. Results for both simulation and experimental data show that the coherence time increases as the receiving aperture diameter increases. For finite apertures the coherence time increases as the communication link distance is increased. We conjecture that this is due to the increasing speckle size within the pupil plane of the receiving aperture for an increasing link distance.

Microfluidic hydrogen generator : featuring passive on-demand gas generation and self-circulated reactant for integration with micro fuel cell

A microfluidic hydrogen generator is presented in this work. Its fabrication, characterization, and integration with a micro proton exchange membrane (PEM) fuel cell are described. Hydrogen gas is generated by the hydrolysis of aqueous ammonia borane. Gas generation, as well as the circulation of ammonia borane from a rechargeable fuel reservoir, is performed without any power consumption. To achieve this, directional growth and selective venting of hydrogen gas is maintained in the microchannels, which results in the circulation of fresh reactant from the fuel reservoir. In addition to this self-circulation mechanism, the hydrogen generator has been demonstrated to self-regulate gas generation to meet demands of a connected micro fuel cell. All of this is done without parasitic power consumption from the fuel cell. Results show its feasibility in applications of high-impedance systems. Lastly, recommendations for improvements and suggestions for future work are described

ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms.

Bayesian change-point analysis in linear regression model with scale mixtures of normal distributions

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.

THE USE OF LIFE-CYCLE ANALYSIS TO REDUCE THE ENVIRONMENTAL IMPACT OF MATERIALS IN MANUFACTURING

This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.