Energy harvesting from body motion using rotational micro-generation

Autonomous system applications are typically limited by the power supply operational lifetime when battery replacement is difficult or costly. A trade-off between battery size and battery life is usually calculated to determine the device capability and lifespan. As a result, energy harvesting research has gained importance as society searches for alternative energy sources for power generation. For instance, energy harvesting has been a proven alternative for powering solar-based calculators and self-winding wristwatches. Thus, the use of energy harvesting technology can make it possible to assist or replace batteries for portable, wearable, or surgically-implantable autonomous systems. Applications such as cardiac pacemakers or electrical stimulation applications can benefit from this approach since the number of surgeries for battery replacement can be reduced or eliminated. Research on energy scavenging from body motion has been investigated to evaluate the feasibility of powering wearable or implantable systems. Energy from walking has been previously extracted using generators placed on shoes, backpacks, and knee braces while producing power levels ranging from milliwatts to watts. The research presented in this paper examines the available power from walking and running at several body locations. The ankle, knee, hip, chest, wrist, elbow, upper arm, side of the head, and back of the head were the chosen target localizations. Joints were preferred since they experience the most drastic acceleration changes. For this, a motor-driven treadmill test was performed on 11 healthy individuals at several walking (1-4 mph) and running (2-5 mph) speeds. The treadmill test provided the acceleration magnitudes from the listed body locations. Power can be estimated from the treadmill evaluation since it is proportional to the acceleration and frequency of occurrence. Available power output from walking was determined to be greater than 1mW/cm³ for most body locations while being over 10mW/cm³ at the foot and ankle locations. Available power from running was found to be almost 10 times higher than that from walking. Most energy harvester topologies use linear generator approaches that are well suited to fixed-frequency vibrations with sub-millimeter amplitude oscillations. In contrast, body motion is characterized with a wide frequency spectrum and larger amplitudes. A generator prototype based on self-winding wristwatches is deemed to be appropriate for harvesting body motion since it is not limited to operate at fixed-frequencies or restricted displacements. Electromagnetic generation is typically favored because of its slightly higher power output per unit volume. Then, a nonharmonic oscillating rotational energy scavenger prototype is proposed to harness body motion. The electromagnetic generator follows the approach from small wind turbine designs that overcome the lack of a gearbox by using a larger number of coil and magnets arrangements. The device presented here is composed of a rotor with multiple-pole permanent magnets having an eccentric weight and a stator composed of stacked planar coils. The rotor oscillations induce a voltage on the planar coil due to the eccentric mass unbalance produced by body motion. A meso-scale prototype device was then built and evaluated for energy generation. The meso-scale casing and rotor were constructed on PMMA with the help of a CNC mill machine. Commercially available discrete magnets were encased in a 25mm rotor. Commercial copper-coated polyimide film was employed to manufacture the planar coils using MEMS fabrication processes. Jewel bearings were used to finalize the arrangement. The prototypes were also tested at the listed body locations. A meso-scale generator with a 2-layer coil was capable to extract up to 234 µW of power at the ankle while walking at 3mph with a 2cm³ prototype for a power density of 117 µW/cm³. This dissertation presents the analysis of available power from walking and running at different speeds and the development of an unobtrusive miniature energy harvesting generator for body motion. Power generation indicates the possibility of powering devices by extracting energy from body motion.

Development of a direct evaporation bismuth Hall thruster

Hall thrusters have been under active development around the world since the 1960’s. Thrusters using traditional propellants such as xenon have been flown on a variety of satellite orbit raising and maintenance missions with an excellent record. To expand the mission envelope, it is necessary to lower the specific impulse of the thrusters but xenon and krypton are poor performers at specific impulses below 1,200 seconds. To enhance low specific impulse performance, this dissertation examines the development of a Hall-effect thruster which uses bismuth as a propellant. Bismuth, the heaviest non-radioactive element, holds many advantages over noble gas propellants from an energetics as well as a practical economic standpoint. Low ionization energy, large electron-impact crosssection and high atomic mass make bismuth ideal for low-specific impulse applications. The primary disadvantage lies in the high temperatures which are required to generate the bismuth vapors. Previous efforts carried out in the Soviet Union relied upon the complete bismuth vaporization and gas phase delivery to the anode. While this proved successful, the power required to vaporize and maintain gas phase throughout the mass flow system quickly removed many of the efficiency gains expected from using bismuth. To solve these problems, a unique method of delivering liquid bismuth to the anode has been developed. Bismuth is contained within a hollow anode reservoir that is capped by a porous metallic disc. By utilizing the inherent waste heat generated in a Hall thruster, liquid bismuth is evaporated and the vapors pass through the porous disc into the discharge chamber. Due to the high temperatures and material compatibility requirements, the anode was fabricated out of pure molybdenum. The porous vaporizer was not available commercially so a method of creating a refractory porous plate with 40-50% open porosity was developed. Molybdenum also does not respond well to most forms of welding so a diffusion bonding process was also developed to join the molybdenum porous disc to the molybdenum anode. Operation of the direct evaporation bismuth Hall thruster revealed interesting phenomenon. By utilizing constant current mode on a discharge power supply, the discharge voltage settles out to a stable operating point which is a function of discharge current, anode face area and average pore size on the vaporizer. Oscillations with a 40 second period were also observed. Preliminary performance data suggests that the direct evaporation bismuth Hall thruster performs similar to xenon and krypton Hall thrusters. Plume interrogation with a Retarding Potential Analyzer confirmed that bismuth ions were being efficiently accelerated while Faraday probe data gave a view of the ion density in the exhausted plume.

Structural and surface property characterization of titanium dioxide nanotubes for orthopedic implants

This research focused on the to modification of the surface structure of titanium implants with nanostructured morphology of TiO2 nanotubes and studied the interaction of nanotubes with osteoblast cells to understand the parameters that affect the cell growth. The electrical, mechanical, and structural properties of TiO2 nanotubes were characterized to establish a better understanding on the properties of such nanoscale morphological structures. To achieve the objectives of this research work I transformed the titanium and its alloys, either in bulk sheet form, bulk machined form, or thin film deposited on another substrate into a surface of titania nanotubes using a low cost and environmentally friendly process. The process requires only a simple electrolyte, low cost electrode, and a DC power supply. With this simple approach of scalable nanofabrication, a typical result is nanotubes that are each approximately 100nm in diameter and have a wall thickness of about 20nm. By changing the fabrication parameters, independent nanotubes can be fabricated with open volume between them. Titanium in this form is termed onedimensional since electron transport is narrowly confined along the length of the nanotube. My Ph.D. accomplishments have successfully shown that osteoblast cells, the cells that are the precursors to bone, have a strong tendency to attach to the inside and outside of the titanium nanotubes onto which they are grown using their filopodia – cell’s foot used for locomotion – anchored to titanium nanotubes. In fact it was shown that the cell prefers to find many anchoring sites. These sites are critical for cell locomotion during the first several weeks of maturity and upon calcification as a strongly anchored bone cell. In addition I have shown that such a surface has a greater cell density than a smooth titanium surface. My work also developed a process that uses a focused and controllably rastered ion beam as a nano-scalpel to cut away sections of the osteoblast cells to probe the attachment beneath the main cell body. Ultimately the more rapid growth of osteoblasts, coupled with a stronger cell-surface interface, could provide cost reduction, shorter rehabilitation, and fewer follow-on surgeries due to implant loosening.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

WATER USE AND SYSTEM RELIABILITY UNDER DIESELGENERATOR AND SOLAR PHOTOVOLTAIC POWERED PUMPING SYSTEMS: A CASE STUDY OF SOLLA TOGO

Access to improved potable water sources is recognized as one of the key factors in improving health and alleviating global poverty. In recently years, substantial investments have been made internationally in potable water infrastructure projects, allowing 2.3 billion people to gain access to potable water from 1990-2012. One such project was planned and installed in Solla, Togo, a rural village in the northern part of the country, from 2010-2012. Ethnographic studies revealed that, while the community has access to potable water, an estimated 45% of the village’s 1500 residents still rely on unprotected sources for drinking and cooking. Additionally, inequality in system use based on income level was revealed, with the higher income groups accessing the system more regularly than lower income groups. Cost, as well as the availability of cheaper sources, was identified as the main deterrent from using the new water distribution system. A new water-pricing scheme is investigated here with the intention of making the system accessible to a greater percentage of the population. Since 2012, a village-level water committee has been responsible for operations and maintenance (O&M), fulfilling the community management model that is recommended by many development theorists in order to create sustainable projects. The water committee received post-construction support, mostly in the form of technical support during system breakdowns, from the Togolese Ministry of Water and Sanitation (MWSVH). While this support has been valuable in maintaining a functional water supply system in Solla, the water committee still has managerial challenges, particularly with billing and fee collection. As a result, the water committee has only received 2% - 25% of the fees owed at each private connection and public tap stand, making their finances vulnerable when future repairs and capital replacements are necessary. A new management structure is proposed by the MWSVH that will pay utilities workers a wage and will hire an accountant in order to improve the local management and increase revenue. This proposal is analyzed under the new water pricing schemes that are presented. Initially, the rural water supply system was powered by a diesel-generator, but in 2013, a solar photo-voltaic power supply was installed. The new system proved a fiscal improvement for the village water committee, since it drastically reduced their annual O&M costs. However, the new system pumps a smaller volume of water on a daily basis and did not meet the community’s water needs during the dry season of 2014. A hydraulic network model was developed to investigate the system’s reliability under diesel-generator (DGPS) and solar photovoltaic (PVPS) power supplies. Additionally, a new system layout is proposed for the PVPS that allows pumping directly into the distribution line, circumventing the high head associated with pumping solely to the storage tank. It was determined that this new layout would allow for a greater volume of water to be provided to the demand points over the course of a day, meeting a greater fraction of the demand than with the current layout.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.