Rural water system sustainability : a case study of community-managed water systems in Saramaka communities

Worldwide, rural populations are far less likely to have access to clean drinking water than are urban ones. In many developing countries, the current approach to rural water supply uses a model of demand-driven, community-managed water systems. In Suriname, South America rural populations have limited access to improved water supplies; community-managed water supply systems have been installed in several rural communities by nongovernmental organizations as part of the solution. To date, there has been no review of the performance of these water supply systems. This report presents the results of an investigation of three rural water supply systems constructed in Saramaka villages in the interior of Suriname. The investigation used a combination of qualitative and quantitative methods, coupled with ethnographic information, to construct a comprehensive overview of these water systems. This overview includes the water use of the communities, the current status of the water supply systems, histories and sustainability of the water supply projects, technical reviews, and community perceptions. From this overview, factors important to the sustainability of these water systems were identified. Community water supply systems are engineered solutions that operate through social cooperation. The results from this investigation show that technical adequacy is the first and most critical factor for long-term sustainability of a water system. It also shows that technical adequacy is dependent on the appropriateness of the engineering design for the social, cultural, and natural setting in which it takes place. The complex relationships between technical adequacy, community support, and the involvement of women play important roles in the success of water supply projects. Addressing these factors during the project process and taking advantage of alternative water resources may increase the supply of improved drinking water to rural communities.

Design of high fidelity building energy monitoring system

Building energy meter network, based on per-appliance monitoring system, willbe an important part of the Advanced Metering Infrastructure. Two key issues exist for designing such networks. One is the network structure to be used. The other is the implementation of the network structure on a large amount of small low power devices, and the maintenance of high quality communication when the devices have electric connection with high voltage AC line. The recent advancement of low-power wireless communication makes itself the right candidate for house and building energy network. Among all kinds of wireless solutions, the low speed but highly reliable 802.15.4 radio has been chosen in this design. While many network-layer solutions have been provided on top of 802.15.4, an IPv6 based method is used in this design. 6LOWPAN is the particular protocol which adapts IP on low power personal network radio. In order to extend the network into building area without, a specific network layer routing mechanism-RPL, is included in this design. The fundamental unit of the building energy monitoring system is a smart wall plug. It is consisted of an electricity energy meter, a RF communication module and a low power CPU. The real challenge for designing such a device is its network firmware. In this design, IPv6 is implemented through Contiki operation system. Customize hardware driver and meter application program have been developed on top of the Contiki OS. Some experiments have been done, in order to prove the network ability of this system.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

Orbits design for Leo space based solar power satellite system

Space Based Solar Power satellites use solar arrays to generate clean, green, and renewable electricity in space and transmit it to earth via microwave, radiowave or laser beams to corresponding receivers (ground stations). These traditionally are large structures orbiting around earth at the geo-synchronous altitude. This thesis introduces a new architecture for a Space Based Solar Power satellite constellation. The proposed concept reduces the high cost involved in the construction of the space satellite and in the multiple launches to the geo-synchronous altitude. The proposed concept is a constellation of Low Earth Orbit satellites that are smaller in size than the conventional system. For this application a Repeated Sun-Synchronous Track Circular Orbit is considered (RSSTO). In these orbits, the spacecraft re-visits the same locations on earth periodically every given desired number of days with the line of nodes of the spacecraft’s orbit fixed relative to the Sun. A wide range of solutions are studied, and, in this thesis, a two-orbit constellation design is chosen and simulated. The number of satellites is chosen based on the electric power demands in a given set of global cities. The orbits of the satellites are designed such that their ground tracks visit a maximum number of ground stations during the revisit period. In the simulation, the locations of the ground stations are chosen close to big cities, in USA and worldwide, so that the space power constellation beams down power directly to locations of high electric power demands. The j2 perturbations are included in the mathematical model used in orbit design. The Coverage time of each spacecraft over a ground site and the gap time between two consecutive spacecrafts visiting a ground site are simulated in order to evaluate the coverage continuity of the proposed solar power constellation. It has been observed from simulations that there always periods in which s spacecraft does not communicate with any ground station. For this reason, it is suggested that each satellite in the constellation be equipped with power storage components so that it can store power for later transmission. This thesis presents a method for designing the solar power constellation orbits such that the number of ground stations visited during the given revisit period is maximized. This leads to maximizing the power transmission to ground stations.

Life cycle assessment of biofuels produced by the new integrated hydropyrolysis-hydroconversion (IH2) process

Biofuels are alternative fuels that have the promise of reducing reliance on imported fossil fuels and decreasing emission of greenhouse gases from energy consumption. This thesis analyses the environmental impacts focusing on the greenhouse gas (GHG) emissions associated with the production and delivery of biofuel using the new Integrated Hydropyrolysis and Hydroconversion (IH2) process. The IH2 process is an innovative process for the conversion of woody biomass into hydrocarbon liquid transportation fuels in the range of gasoline and diesel. A cradle-to-grave life cycle assessment (LCA) was used to calculate the greenhouse gas emissions associated with diverse feedstocks production systems and delivery to the IH2 facility plus producing and using these new renewable liquid fuels. The biomass feedstocks analyzed include algae (microalgae), bagasse from a sugar cane-producing locations such as Brazil or extreme southern US, corn stover from Midwest US locations, and forest feedstocks from a northern Wisconsin location. The life cycle greenhouse gas (GHG) emissions savings of 58%–98% were calculated for IH2 gasoline and diesel production and combustion use in vehicles compared to fossil fuels. The range of savings is due to different biomass feedstocks and transportation modes and distances. Different scenarios were conducted to understand the uncertainties in certain input data to the LCA model, particularly in the feedstock production section, the IH2 biofuel production section, and transportation sections.

Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

Quantum dot / optical protein bio-nano hybrid system biosensing

The integration of novel nanomaterials with highly-functional biological molecules has advanced multiple fields including electronics, sensing, imaging, and energy harvesting. This work focuses on the creation of a new type of bio-nano hybrid substrate for military biosensing applications. Specifically it is shown that the nano-scale interactions of the optical protein bacteriorhodopsin and colloidal semiconductor quantum dots can be utilized as a generic sensing substrate. This work spans from the basic creation of the protein to its application in a novel biosensing system. The functionality of this sensor design originates from the unique interactions between the quantum dot and bacteriorhodopsin molecule when in nanoscale proximity. A direct energy transfer relationship has been established between coreshell quantum dots and the optical protein bacteriorhodopsin that substantially enhances the protein’s native photovoltaic capabilities. This energy transfer phenomena is largely distance dependent, in the sub-10nm realm, and is characterized experimentally at multiple separation distances. Experimental results on the energy transfer efficiency in this hybrid system correlate closely to theoretical predictions. Deposition of the hybrid system with nano-scale control has allowed for the utilization of this energy transfer phenomena as a modulation point for a functional biosensor prototype. This work reveals that quantum dots have the ability to activate the bacteriorhodopsin photocycle through both photonic and non-photonic energy transfer mechanisms. By altering the energy transferred to the bacteriorhodopsin molecule from the quantum dot, the electrical output of the protein can be modulated. A biosensing prototype was created in which the energy transfer relationship is altered upon target binding, demonstrating the applicability of a quantum dot/bacteriorhodopsin hybrid system for sensor applications. The electrical nature of this sensing substrate will allow for its efficient integration into a nanoelectronics array form, potentially leading to a small-low power sensing platform for remote toxin detection applications.

Cylinder wall waste heat recovery from liquid-cooled internal combustion engines utilizing thermoelectric generators

This report is a dissertation proposal that focuses on the energy balance within an internal combustion engine with a unique coolant-based waste heat recovery system. It has been predicted by the U.S. Energy Information Administration that the transportation sector in the United States will consume approximately 15 million barrels per day in liquid fuels by the year 2025. The proposed coolant-based waste heat recovery technique has the potential to reduce the yearly usage of those liquid fuels by nearly 50 million barrels by only recovering even a modest 1% of the wasted energy within the coolant system. The proposed waste heat recovery technique implements thermoelectric generators on the outside cylinder walls of an internal combustion engine. For this research, one outside cylinder wall of a twin cylinder 26 horsepower water-cooled gasoline engine will be implemented with a thermoelectric generator surrogate material. The vertical location of these TEG surrogates along the water jacket will be varied along with the TEG surrogate thermal conductivity. The aim of this proposed dissertation is to attain empirical evidence of the impact, including energy distribution and cylinder wall temperatures, of installing TEGs in the water jacket area. The results can be used for future research on larger engines and will also assist with proper TEG selection to maximize energy recovery efficiencies.

Non-invasive method to predict viscosity and size using total internal reflection fluorescence microscopy (TIRFM) system

This study develops an automated analysis tool by combining total internal reflection fluorescence microscopy (TIRFM), an evanescent wave microscopic imaging technique to capture time-sequential images and the corresponding image processing Matlab code to identify movements of single individual particles. The developed code will enable us to examine two dimensional hindered tangential Brownian motion of nanoparticles with a sub-pixel resolution (nanoscale). The measured mean square displacements of nanoparticles are compared with theoretical predictions to estimate particle diameters and fluid viscosity using a nonlinear regression technique. These estimated values will be confirmed by the diameters and viscosities given by manufacturers to validate this analysis tool. Nano-particles used in these experiments are yellow-green polystyrene fluorescent nanospheres (200 nm, 500 nm and 1000 nm in diameter (nominal); 505 nm excitation and 515 nm emission wavelengths). Solutions used in this experiment are de-ionized (DI) water, 10% d-glucose and 10% glycerol. Mean square displacements obtained near the surface shows significant deviation from theoretical predictions which are attributed to DLVO forces in the region but it conforms to theoretical predictions after ~125 nm onwards. The proposed automation analysis tool will be powerfully employed in the bio-application fields needed for examination of single protein (DNA and/or vesicle) tracking, drug delivery, and cyto-toxicity unlike the traditional measurement techniques that require fixing the cells. Furthermore, this tool can be also usefully applied for the microfluidic areas of non-invasive thermometry, particle tracking velocimetry (PTV), and non-invasive viscometry.

Stability analysis of a mono inverter dual sensorless motors system

When a single brush-less dc motor is fed by an inverter with a sensor-less algorithm embedded in the switching controller, the system exhibits a linear and stable output in terms of the speed and torque. However, with two motors modulated by the same inverter, the system is unstable and rendered useless for a steady application, unless provided with some resistive damping on the supply lines. The project discusses and analysis the stability of such a system through simulations and hardware demonstrations and also will discuss a method to derive the values of these damping.

Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study

The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.

Accelerometer based measurements of combustion in an automotive turbocharged diesel engine

The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations, develop alternative combustion strategies, and use of biofuels. In this dissertation, block mounted accelerometers were investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers were positioned in multiple placements and orientations on the engine, and engine testing was conducted under motored, single and pilot-main injection conditions. Engine tests were conducted at varying injection timings, engine loads, and engine speeds to observe the resulting time and frequency domain changes of the cylinder pressure and accelerometer signals. The frequency content of the cylinder pressure based signals and the accelerometer signals between 0.5 kHz and 6 kHz indicated a strong correlation with coherence values of nearly 1. The accelerometers were used to produce estimated combustion signals using the Frequency Response Functions (FRF) measured from the frequency domain characteristics of the cylinder pressure signals and the response of the accelerometers attached to the engine block. When compared to the actual combustion signals, the estimated combustion signals produced from the accelerometer response had Root Mean Square Errors (RMSE) between 7% and 25% of the actual signals peak value. Weighting the FRF’s from multiple test conditions along their frequency axis with the coherent output power reduced the median RMSE of the estimated combustion signals and the 95th percentile of RMSE produced from each test condition. The RMSE’s of the magnitude based combustion metrics including peak cylinder pressure, MPG, peak ROHR, and work estimated from the combustion signals produced by the accelerometer responses were between 15% and 50% of their actual value. The MPG measured from the estimated pressure gradient shared a direct relationship to the actual MPG. The location based combustion metrics such as the location of peak values and burn durations were capable of RMSE measurements as low as 0.9°. Overall, accelerometer based combustion sensing system was capable of detecting combustion and providing feedback regarding the in cylinder combustion process

Payone : incentive for epidemic protocol-based anonymity system

Anonymity systems maintain the anonymity of communicating nodes by camouflaging them, either with peer nodes generating dummy traffic or with peer nodes participating in the actual communication process. The probability of any adversary breaking down the anonymity of the communicating nodes is inversely proportional to the number of peer nodes participating in the network. Hence to maintain the anonymity of the communicating nodes, a large number of peer nodes are needed. Lack of peer availability weakens the anonymity of any large scale anonymity system. This work proposes PayOne, an incentive based scheme for promoting peer availability. PayOne aims to increase the peer availability by encouraging nodes to participate in the anonymity system by awarding them with incentives and thereby promoting the anonymity strength. Existing incentive schemes are designed for single path based approaches. There is no incentive scheme for multipath based or epidemic based anonymity systems. This work has been specifically designed for epidemic protocols and has been implemented over MuON, one of the latest entries to the area of multicasting based anonymity systems. MuON is a peer-to-peer based anonymity system which uses epidemic protocol for data dissemination. Existing incentive schemes involve paying every intermediate node that is involved in the communication between the initiator and the receiver. These schemes are not appropriate for epidemic based anonymity systems due to the incurred overhead. PayOne differs from the existing schemes because it involves paying a single intermediate node that participates in the network. The intermediate node can be any random node that participates in the communication and does not necessarily need to lie in the communication path between the initiator and the receiver. The light-weight characteristics of PayOne make it viable for large-scale epidemic based anonymity systems.

Wireless and passive pressure sensor system based on the magnetic higher-order harmonic field

The goal of this work is to develop a magnetic-based passive and wireless pressure sensor for use in biomedical applications. Structurally, the pressure sensor, referred to as the magneto-harmonic pressure sensor, is composed of two magnetic elements: a magnetically-soft material acts as a sensing element, and a magnetically hard material acts as a biasing element. Both elements are embedded within a rigid sensor body and sealed with an elastomer pressure membrane. Upon excitation of an externally applied AC magnetic field, the sensing element is capable of producing higher-order magnetic signature that is able to be remotely detected with an external receiving coil. When exposed to environment with changing ambient pressure, the elastomer pressure membrane of pressure sensor is deflected depending on the surrounding pressure. The deflection of elastomer membrane changes the separation distance between the sensing and biasing elements. As a result, the higher-order harmonic signal emitted by the magnetically-soft sensing element is shifted, allowing detection of pressure change by determining the extent of the harmonic shifting. The passive and wireless nature of the sensor is enabled with an external excitation and receiving system consisting of an excitation coil and a receiving coil. These unique characteristics made the sensor suitable to be used for continuous and long-term pressure monitoring, particularly useful for biomedical applications which often require frequent surveillance. In this work, abdominal aortic aneurysm is selected as the disease model for evaluation the performance of pressure sensor and system. Animal model, with subcutaneous sensor implantation in mice, was conducted to demonstrate the efficacy and feasibility of pressure sensor in biological environment.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.