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<p>Project Solaris is a student research project with the goal to build a solar powered Unmanned Aerial Vehicle. This study is one in a set of studies that make up the initial phase of project Solaris. The main objective of this report is to investigate earlier solar powered airplanes as well as evaluate (or explore) potential future niche markets where solar powered UAVs could excel.A presentation of earlier solar powered airplanes will give an overall understanding of how solar powered airplanes have evolved and also provide information about the goals and ambitions behind the projects.Potential applications such as power line inspection and algal bloom observation will be described and a list of specifications for each application will be presented.</p> / Solaris

Project Solaris is a student research project with the goal to build a solar powered Unmanned Aerial Vehicle. This study is one in a set of studies that make up the initial phase of project Solaris. The main objective of this report is to investigate earlier solar powered airplanes as well as evaluate (or explore) potential future niche markets where solar powered UAVs could excel.A presentation of earlier solar powered airplanes will give an overall understanding of how solar powered airplanes have evolved and also provide information about the goals and ambitions behind the projects.Potential applications such as power line inspection and algal bloom observation will be described and a list of specifications for each application will be presented. / Solaris

The Savannah River Site (SRS), a Department of Energy facility, generated non-hazardous petroleum and radiological co-contaminated soils that did not have a disposal pathway. The purpose of this project was to generate treatment data and test the hypothesis that an engineered biological process could safely and efficiently remove petroleum co-contamination from radiological contaminated soil. Demonstration of the treatment would allow the soils to be disposed as low-level radiological materials. Although radiation and radiological contamination may, depending on the type and level, impact microbial activity and growth, the impact of low levels of radiation were not expected to impact the biodegradation of petroleum contaminated soils. Important parameters identified for successful biological treatment included oxygen mass transfer, bioavailability, temperature, microbiological capabilities, nutrients, and moisture. System design was based on a bioventing approach to control the supply of oxygen (air) based on petroleum contamination levels and type of soil being treated. Before bioremediation began, a bioreactor system was permitted, designed, constructed, and tested. An operating permit was obtained from SCDHEC, as were approvals required by the SRS. The design was based on bioventing principles and used a modified prefabricated skid-pan, which was constructed by SRNL. System operation included formulating a test plan, developing and using system sampling and monitoring methods, loading the system, starting up operations, obtaining results, modifying operation, and final disposal of the soil after the bioremediation goal was achieved. The PRCS bioreactor operated for 22 months in various configurations treating the contaminated soil to a final TPH concentration of 45 mg/kg. During operation, degradation of over 20,000 mg/kg of waste was accounted for through monitoring of carbon dioxide levels in the effluent. System operation worked best when soil temperatures were above 15 ?nd the pumps were operated continuously. The low level radiological contaminated soil was disposed in an engineered trench at SRS that accepts this type of waste. The project demonstrated that co-contaminated soils could be treated biologically to remove petroleum contamination to levels below 100 mg/kg while protecting workers and the environment from radiological contamination.

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Emerging financial and environmental challenges associated with conventional power sources have increased global interest in consuming unpolluted, renewable energy sources for irrigation sector. Solar energy may be an attractive choice in this regard due to its strong influence on crop water use and related energy requirement. However, a comprehensive approach for a reliable and economically viable photovoltaic (PV) system design to produce energy from solar source is required to accurately explore its potential. This thesis describes the development and application of a reliability assessment model, identifies a suitable solar irrigation management scheme, and provides guidelines for evaluating economic viability of a solar-powered center pivot irrigation system. The reliability model, written in MATLAB, was developed based on the loss of power supply probability (LPSP) technique in which various sub-models for estimating energy production, energy requirement and energy storage were combined. The model was validated with actual data acquired from the study site located at Outlook, Saskatchewan, Canada and an excellent agreement was found. For example, normalized root mean square error (NRMSE) for the battery current was found to be 0.027. Irrigation management strategies (irrigation depth, frequency and timing) were investigated by comparing the PV system sizing requirement for a conventional (25-35 mm per application) and for a frequent light irrigation management strategy (5-8 mm per application). The results suggest that the PV sizing can be reduced significantly by adopting frequent light irrigations which utilize the power as it is produced during daylight hours, rather than relying on stored energy. The potential of a solar-powered center pivot irrigation system was revealed for three different crops (canola, soybean and table potato) at the site by conducting a detailed economic analysis for the designed PV system. High value crops with moderate water requirements such as table potatoes appeared to be the most feasible choice for the study site. However, the potential may greatly vary for different crops in altered locations due to management, agronomic, climate, social, and economic variations. It can be concluded that a holistic approach described here can be used as a tool for designing an appropriate PV powered center pivot irrigation system under variable operating and meteorological conditions. Furthermore, its potential can be accurately explored by conducting a detailed economic analysis for a given location, considering different available crop choices.

M.Ing. / Sustained or long endurance solar powered flight is defined as an aircraft capable of main- taining flight through multiple day-night flight cycles, using only solar power and rechargable energy stores. The project is focused on developing solar powered flight theory and real-world unmanned aerial vehicle implementations. The important aspects of system design are es- tablished and studied at a fundamental theoretical level. A preliminary design is conducted with endurance optimisation as the main aim. The optimisation process aims to establish a theoretical basis for sustained solar powered flight. The project is started with a feasibility and relevance study. A literature study was used to gather the required theoretical information. A novel theoretical preliminary design basis is conducted. The study is aimed at answering many questions in the field. The study is the first to show how previously varied aircraft from 3 m to 80 m are valid solutions to the long endurance flight requirement. The optimisation results correlates well with the current state-of-the-art. The theoretical models were then characterised through the development of two unmanned aerial vehicles. The development required a multidisciplinary integration of various fields. The development process was characterised and discussed. Flight automation was successfully integrated into the system. Multiple test flights were conducted. An interpretation of multi- faceted results are given. This project has contributed to international theory regarding solar powered and sustained endurance aircraft. Many specific contributions were made to the field. The project has achieved multiple unofficial records from the flight tests in the Southern Hemisphere and African continent.

Wireless sensor networks enable inexpensive distributed monitoring systems that are the backbone of smart cities. In this dissertation, we are interested in wireless sensor networks for traffic monitoring and an emergency flood detection to improve the safety of future cities. To achieve real-time traffic monitoring and emergency flood detection, the system has to be continually operational. Accordingly, an energy source is needed to ensure energy availability at all times. The sun provides for the most inexpensive source of energy, and therefore the energy is provided here by a solar panel working in conjunction with a rechargeable battery. Unlike batteries, solar energy fluctuates spatially and temporally due to the panel orientation, seasonal variation and node location, particularly in cities where buildings cast shadows. Especially, it becomes scarce whenever floods are likely to occur, as the weather tends to be cloudy at such times when the emergency detection system is most needed. These considerations lead to the need for the optimization of the energy of the sensor network, to maximize its sensing performance. In this dissertation, we address the challenges associated with long term outdoor deployments along with providing some solutions to overcome part of these challenges. We then introduce the energy optimization problem, as a distributed greedy approach. Motivated by the flood sensing application, our objective is to maximize the energy margin in the solar powered network at the onset of the high rain event, to maximize the network lifetime. The decentralized scheme will achieve this by optimizing the energy over a time horizon T, taking into account the available and predicted energy over the entire routing path. Having a good energy forecasting scheme can significantly enhance the energy optimization in WSN. Thus, this dissertation proposes a new energy forecasting scheme that is compatible with the platform’s capabilities. This proposed prediction scheme was tested on real data and compared with state-of-theart forecasting schemes on on-node WSN platforms. Finally, to establish the relevance of the aforementioned schemes beyond theoretical formulations and simulations, all proposed protocols and schemes are subjected to hardware implementation.

<p> Wireless mesh networks are now being used to deploy radio coverage in a large variety of outdoor applications. One of the major obstacles that these networks face is that of providing the nodes with electrical power and wired network connections. Solar powered mesh nodes are increasingly used to eliminate the need for these types of connections, making the nodes truly tether-less. In these types of networks however, the cost of the energy collection and storage components can be a significant fraction of the total node cost, which motivates a careful selection of these resources.</p> <p> This thesis focusses on key issues relating to the deployment and operation of solar powered wireless mesh networks. First, the problem of provisioning the mesh nodes with a suitable solar panel and battery configuration is considered. This is done by assuming a bandwidth usage profile and using historical solar insolation data for the desired deployment location. A resource provisioning algorithm is proposed based on the use of temporal shortest-path routing and taking into account the node energy-flow for the target deployment time period. A methodology is introduced which uses a genetic algorithm (GA) to incorporate energy-aware routing into the resource assignment procedure. Results show that the proposed resource provisioning algorithm can achieve large cost savings when compared to conventional provisioning methods.</p> <p> During post-deployment network operation, the actual bandwidth profile and solar insolation may be different than that for which the nodes were originally provisioned. To prevent node outage, the network must reduce its workload by flow controlling its input traffic. The problem of admitting network bandwidth flows in a fair manner is also studied. A bound is first formulated which achieves the best max/min fair flow control subject to eliminating node outage. The bound motivates a proposed causal flow control algorithm whose operation uses prediction based on access to on-line historical weather data. The results show that the proposed algorithm performs well when compared to the analytic bound that is derived for this problem.</p> <p> Finally, as user traffic evolves, the network resources need to be updated. This problem is considered using a minimum cost upgrade objective. A mixed integer linear programming (MILP) formulation is derived to obtain a lower bound on the network update cost. A genetic algorithm is used to determine practical cost-effective network resource upgrading. The results show that the proposed methodology can obtain significant cost savings.</p> / Thesis / Doctor of Philosophy (PhD)