The urgent need for a clean and sustainable power supply for wireless sensor nodes and low-power electronics in various monitoring systems and the Internet of Things has led to an explosion of research in substitute energy technologies. Traditional batteries are still the most widely used power source for these applications currently but have been blamed for chemical pollution, high maintenance cost, bulky volume, and limited energy capacity. Ambient energy in different forms such as vibration, movement, heat, wind, and waves otherwise wasted can be converted into usable electricity using proper transduction mechanisms to power sensors and low-power devices or charge rechargeable batteries. This dissertation focuses on the design, modeling, optimization, prototype, and testing of novel piezoelectric energy harvesters for extracting energy from human walking, bio-inspired bi-stable motion, and torsional vibration as an alternative power supply for wireless monitoring systems. To provide a sustainable power supply for health care monitoring systems, a piezoelectric footwear harvester is developed and embedded inside a shoe heel for scavenging energy from human walking. The harvester comprises of multiple 33-mode piezoelectric stacks within single-stage force amplification frames sandwiched between two heel-shaped aluminum plates taking and reallocating the dynamic force at the heel. The single-stage force amplification frame is designed and optimized to transmit, redirect, and amplify the heel-strike force to the inner piezoelectric stack. An analytical model is developed and validated to predict precisely the electromechanical coupling behavior of the harvester. A symmetric finite element model is established to facilitate the mesh of the transducer unit based on a material equivalent model that simplifies the multilayered piezoelectric stack into a bulk. The symmetric FE model is experimentally validated and used for parametric analysis of the single-stage force amplification frame for a large force amplification factor and power output. The results show that an average power output of 9.3 mW/shoe and a peak power output of 84.8 mW are experimentally achieved at the walking speed of 3.0 mph (4.8 km/h). To further improve the power output, a two-stage force amplification compliant mechanism is designed and incorporated into the footwear energy harvester, which could amplify the dynamic force at the heel twice before applied to the inner piezoelectric stacks. An average power of 34.3 mW and a peak power of 110.2 mW were obtained under the dynamic force with the amplitude of 500 N and frequency of 3 Hz. A comparison study demonstrated that the proposed two-stage piezoelectric harvester has a much larger power output than the state-of-the-art results in the literature. A novel bi-stable piezoelectric energy harvester inspired by the rapid shape transition of the Venus flytrap leaves is proposed, modeled and experimentally tested for the purpose of energy harvesting from broadband frequency vibrations. The harvester consists of a piezoelectric macro fiber composite (MFC) transducer, a tip mass, and two sub-beams with bending and twisting deformations created by in-plane pre-displacement constraints using rigid tip-mass blocks. Different from traditional ways to realize bi-stability using nonlinear magnetic forces or residual stress in laminate composites, the proposed bio-inspired bi-stable piezoelectric energy harvester takes advantage of the mutual self-constraint at the free ends of the two cantilever sub-beams with a pre-displacement. This mutual pre-displacement constraint bi-directionally curves the two sub-beams in two directions inducing higher mechanical potential energy. The nonlinear dynamics of the bio-inspired bi-stable piezoelectric energy harvester is investigated under sweeping frequency and harmonic excitations. The results show that the sub-beams of the harvester experience local vibrations, including broadband frequency components during the snap-through, which is desirable for large power output. An average power output of 0.193 mW for a load resistance of 8.2 kΩ is harvested at the excitation frequency of 10 Hz and amplitude of 4.0 g. Torsional vibration widely exists in mechanical engineering but has not yet been well exploited for energy harvesting to provide a sustainable power supply for structural health monitoring systems. A torsional vibration energy harvesting system comprised of a shaft and a shear mode piezoelectric transducer is developed in this dissertation to look into the feasibility of harvesting energy from oil drilling shaft for powering downhole sensors. A theoretical model of the torsional vibration piezoelectric energy harvester is derived and experimentally verified to be capable of characterizing the electromechanical coupling system and predicting the electrical responses. The position of the piezoelectric transducer on the surface of the shaft is parameterized by two variables that are optimized to maximize the power output. Approximate expressions of the voltage and power are derived by simplifying the theoretical model, which gives predictions in good agreement with analytical solutions. Based on the derived approximate expression, physical interpretations of the implicit relationship between the power output and the position parameters of the piezoelectric transducer are given. / Doctor of Philosophy / Wireless monitoring systems with embedded wireless sensor nodes have been widely applied in human health care, structural health monitoring, home security, environment assessment, and wild animal tracking. One distinctive advantage of wireless monitoring systems is to provide unremitting, wireless monitoring of interesting parameters, and data transmission for timely decision making. However, most of these systems are powered by traditional batteries with finite energy capacity, which need periodic replacement or recharge, resulting in high maintenance costs, interruption of service, and potential environmental pollution. On the other hand, abundant energy in different forms such as solar, wind, heat, and vibrations, diffusely exists in ambient environments surrounding wireless monitoring systems which would be otherwise wasted could be converted into usable electricity by proper energy transduction mechanisms. Energy harvesting, also referred to as energy scavenging and energy conversion, is a technology that uses different energy transduction mechanisms, including electromagnetic, photovoltaic, piezoelectric, electrostatic, triboelectric, and thermoelectric, to convert ambient energy into electricity. Compared with traditional batteries, energy harvesting could provide a continuous and sustainable power supply or directly recharge storage devices like batteries and capacitors without interrupting operation. Among these energy transduction mechanisms, piezoelectric materials have been extensively explored for small-size and low-power generation due to their merits of easy shaping, high energy density, flexible design, and low maintenance cost. Piezoelectric transducers convert mechanical energy induced by dynamic strain into electrical charges through the piezoelectric effect. This dissertation presents novel piezoelectric energy harvesters, including design, modeling, prototyping, and experimental tests for energy harvesting from human walking, broadband bi-stable nonlinear vibrations, and torsional vibrations for powering wireless monitoring systems. A piezoelectric footwear energy harvester is developed and embedded inside a shoe heel for scavenging energy from heel striking during human walking to provide a power supply for wearable sensors embedded in health monitoring systems. The footwear energy harvester consists of multiple piezoelectric stacks, force amplifiers, and two heel-shaped metal plates taking dynamic forces at the heel. The force amplifiers are designed and optimized to redirect and amplify the dynamic force transferred from the heel-shaped plates and then applied to the inner piezoelectric stacks for large power output. An analytical model and a finite model were developed to simulate the electromechanical responses of the harvester. The footwear harvester was tested on a treadmill under different walking speeds to validate the numerical models and evaluate the energy generation performance. An average power output of 9.3 mW/shoe and a peak power output of 84.8 mW are experimentally achieved at the walking speed of 3.0 mph (4.8 km/h). A two-stage force amplifier is designed later to improve the power output further. The dynamic force at the heel is amplified twice by the two-stage force amplifiers before applied to the piezoelectric stacks. An average power output of 34.3 mW and a peak power output of 110.2 mW were obtained from the harvester with the two-stage force amplifiers. A bio-inspired bi-stable piezoelectric energy harvester is designed, prototyped, and tested to harvest energy from broadband vibrations induced by animal motions and fluid flowing for the potential applications of self-powered fish telemetry tags and bird tags. The harvester consists of a piezoelectric macro fiber composite (MFC) transducer, a tip mass, and two sub-beams constrained at the free ends by in-plane pre-displacement, which bends and twists the two sub-beams and consequently creates curvatures in both length and width directions. The bi-direction curvature design makes the cantilever beam have two stable states and one unstable state, which is inspired by the Venus flytrap that could rapidly change its leaves from the open state to the close state to trap agile insects. This rapid shape transition of the Venus flytrap, similar to the vibration of the harvester from one stable state to the other, is accompanied by a large energy release that could be harvested. Detailed design steps and principles are introduced, and a prototype is fabricated to demonstrate and validate the concept. The energy harvesting performance of the harvester is evaluated at different excitation levels. Finally, a piezoelectric energy harvester is developed, analytically modeled, and validated for harvesting energy from the rotation of an oil drilling shaft to seek a continuous power supply for downhole sensors in oil drilling monitoring systems. The position of the piezoelectric transducer on the surface of the shaft is parameterized by two variables that are optimized to obtain the maximum power output. Approximate expressions of voltage and power of the torsional vibration piezoelectric energy harvester are derived from the theoretical model. The implicit relationship between the power output and the two position parameters of the transducer is revealed and physically interpreted based on the approximate power expression. Those findings offer a good reference for the practical design of the torsional vibration energy harvesting system.

Emerging technologies, including distributed energy resources (DERs), internet-of-things and advanced distribution management systems, are revolutionizing the power industry. They provide benefits like higher operation flexibility and lower bulk grid dependency, and are moving the modern power grid towards a decentralized, interconnected and intelligent direction. Consequently, the emphasis of the system operation management has been shifted from the supply-side to the demand-side. It calls for a reconsideration of the business model for future retail market operators. To address this need, this dissertation proposes an innovative retail market solution tailored to market environments penetrated with price-responsive DERs. The work is presented from aspects of theoretical study, test-bed platform development, and experimental analysis, within which two topics relevant to the retail market operation are investigated in depth. The first topic covers the modeling of key retail market participants. With regard to price-insensitive participants, fixed loads are treated as the representative. Deep learning-based day-ahead load forecasting models are developed in this study, utilizing both recurrent and convolutional neural networks, to predict the part of demands that keep fixed regardless of the market price. With regard to price-sensitive participants, battery storages are selected as the representative. An optimization-based battery arbitrage model is developed in this study to represent their price-responsive behaviors in response to a dynamic price. The second topic further investigates how the retail market model and pricing strategy should be designed to incentivize these market participants. Different from existing works, this study innovatively proposes a profit-neutral double-price-signal retail market model. Such a design differentiates elastic prosumers, who actively offer flexibilities to the system operation, from normal inelastic consumers/generators, based on their sensitivities to the market price. Two price signals, namely retail grid service price and retail energy price, are then introduced to separately quantify values of the flexibility, provided by elastic participants, and the electricity commodity, sold/bought to/from inelastic participants. Within the proposed retail market, a non-profit retail market operator (RMO) manages and settles the market through determining the price signals and supplementary subsidy to minimize the overall system cost. In response to the announced retail grid service price, elastic prosumers adjust their day-ahead operating schedules to maximize their payoffs. Given the interdependency between decisions made by the RMO and elastic participants, a retail pricing scheme, formulated based on a bi-level optimization framework, is proposed. Additional efforts are made on merging and linearizing the original non-convex bi-level problem into a single-level mixed-integer linear programming problem to ensure the computational efficiency of the retail pricing tool. Case studies are conducted on a modified IEEE 34-bus test-bed system, simulating both physical operations of the power grid and financial interactions inside the retail market. Experimental results demonstrate promising properties of the proposed retail market solution: First of all, it is able to provide cost-saving benefits to inelastic customers and create revenues for elastic customers at the same time, justifying the rationalities of these participants to join the market. Second of all, the addition of the grid service subsidy not only strengthens the profitability of the elastic customer, but also ensures that the benefit enjoyed per customer will not be compromised by the competition brought up by a growing number of participants. Furthermore, it is able to properly capture impacts from line losses and voltage constraints on the system efficiency and stability, so as to derive practical pricing solutions that respect the system operating rules. Last but not least, it encourages the technology improvement of elastic assets as elastic assets in better conditions are more profitable and could better save the electricity bills for inelastic customers. Above all, the superiority of the proposed retail market solution is proven. It can serve as a promising start for the retail electricity market reconstruction. / Doctor of Philosophy / The electricity market plays a critical role in ensuring the economic and secure operation of the power system. The progress made by distributed energy resources (DERs) has reshaped the modern power industry bringing a larger proportion of price-responsive behaviors to the demand-side. It challenges the traditional wholesale-only electricity market and calls for an addition of retail markets to better utilize distributed and elastic assets. Therefore, this dissertation targets at offering a reliable and computational affordable retail market solution to bridge this knowledge gap. Different from existing works, this study assumes that the retail market is managed by a profit-neutral retail market operator (RMO), who oversees and facilitates the system operation for maximizing the system efficiency rather than making profits. Market participants are categorized into two groups: inelastic participants and elastic participants, based on their sensitivity to the market price. The motivation behind this design is that instead of treating elastic participants as normal customers, it is more reasonable to treat them as grid service providers who offer operational flexibilities that benefit the system efficiency. Correspondingly, a double-signal pricing scheme is proposed, such that the flexibility, provided by elastic participants, and the electricity commodity, generated/consumed by inelastic participants, are separately valued by two distinct prices, namely retail grid service price and retail energy price. A grid service subsidy is also introduced in the pricing system to provide supplementary incentives to elastic customers. These two price signals in addition to the subsidy are determined by the RMO via solving a bi-level optimization problem given the interdependency between the prices and reaction of elastic participants. Experimental results indicate that the proposed retail market model and pricing scheme are beneficial for both types of market participants, practical for the network-constrained real-world implementation, and supportive for the technology improvement of elastic assets.

Traffic accidents are of concern for traffic safety; 1.25 million deaths are reported each year. Hence, it is crucial to have access to real-time data and rapidly detect or predict accidents. Predicting the occurrence of a highway car accident accurately any significant length of time into the future is not feasible since the vast majority of crashes occur due to unpredictable human negligence and/or error. However, rapid traffic incident detection could reduce incident-related congestion and secondary crashes, alleviate the waste of vehicles’ fuel and passengers’ time, and provide appropriate information for emergency response and field operation. While the focus of most previously proposed techniques is predicting the number of accidents in a certain region, the problem of predicting the accident occurrence or fast detection of the accident has been little studied. To address this gap, we propose a deep learning approach and build a deep neural network model based on long short term memory (LSTM). We apply it to forecast the expected speed values on freeways’ links and identify the anomalies as potential accident occurrences. Several detailed features such as weather, traffic speed, and traffic flow of upstream and downstream points are extracted from big datasets. We assess the proposed approach on a traffic dataset from Sacramento, California. The experimental results demonstrate the potential of the proposed approach in identifying the anomalies in speed value and matching them with accidents in the same area. We show that this approach can handle a high rate of rapid accident detection and be implemented in real-time travelers’ information or emergency management systems. / M.S. / Rapid traffic accident detection/prediction is essential for scaling down non-recurrent conges- tion caused by traffic accidents, avoiding secondary accidents, and accelerating emergency system responses. In this study, we propose a framework that uses large-scale historical traffic speed and traffic flow data along with the relevant weather information to obtain robust traffic patterns. The predicted traffic patterns can be coupled with the real traffic data to detect anomalous behavior that often results in traffic incidents in the roadways. Our framework consists of two major steps. First, we estimate the speed values of traffic at each point based on the historical speed and flow values of locations before and after each point on the roadway. Second, we compare the estimated values with the actual ones and introduce the ones that are significantly different as an anomaly. The anomaly points are the potential points and times that an accident occurs and causes a change in the normal behavior of the roadways. Our study shows the potential of the approach in detecting the accidents while exhibiting promising performance in detecting the accident occurrence at a time close to the actual time of occurrence.

Curved beams such as arches find ubiquitous applications in civil, mechanical and aerospace engineering, e.g., stiffened floors, fuselage, railway compartments, and wind turbine blades. The analysis of free vibrations of curved structures plays a critical role in their design to avoid transient loads with dominant frequencies close to their natural frequencies. One way to increase their areas of applications and possibly make them lighter without sacrificing strength is to make them of Functionally Graded Materials (FGMs) that are composites with continuously varying material properties in one or more directions. In this thesis, we study free vibrations of FGM circular beams by using a logarithmic shear deformation theory that incorporates through-the-thickness logarithmic variation of the circumferential displacement, and does not require a shear correction factor. The radial displacement of a point is assumed to depend only upon its angular position. Thus the beam theory can be regarded as a generalization of the Timoshenko beam theory. Equations governing transient deformations of the beam are derived by using Hamilton's principle. Assuming a time harmonic variation of the displacements, and by utilizing the generalized differential quadrature method (GDQM) the free vibration problem is reduced to solving an algebraic eigenvalue problem whose solution provides frequencies and the corresponding mode shapes. Results are presented for different spatial variations of the material properties, boundary conditions, and the aspect ratio. It is found that the radial and the circumferential gradation of material properties maintains their natural frequency within that of the homogeneous beam comprised of a constituent of the FGM beam. Furthermore, keeping every other variable fixed, the change in the beam opening angle results in very close frequencies of the first two modes of vibration, a phenomenon usually called mode transition. / Master of Science / Curved and straight beams of various cross-sections are one of the simplest and most fundamental structural elements that have been extensively studied because of their ubiquitous applications in civil, mechanical, biomedical and aerospace engineering. Many attempts have been made to enhance their material properties and designs for applications in harsh environments and reduce weight. One way of accomplishing this is to combine layerwise two or more distinct materials and take advantage of their directional properties. It results in a lightweight structure having overall specific strength superior to that of its constituents. Another possibility is to have volume fractions of two or more constituents gradually vary throughout the structure for enhancing its performance under anticipated applications. Functionally graded materials (FGMs) are a class of composites whose properties gradually vary along one or more space directions. In this thesis, we have numerically studied free vibrations of FGM circular beams to enhance their application domain and possibly use them for energy harvesting.

Asian, Black, Indigenous, Latine, and Pacific Islander students have increased their enrollment in private schools (2012–-2020) (NCES, 2021a) and have become the majority population in American public schools (NCES, 2021b), yet many educators are not adequately prepared to teach students from diverse backgrounds (Ladson-Billings, 2017; Paris & Alim, 2017). Within the field of choral music education, preservice choral educators are mostly prepared to teach Western European classical repertoire and bel canto vocal technique, both based on a Eurocentric paradigm (Good-Perkins, 2021b). This paradigm, however, is unlikely to be appropriate for students who are versed in diverse musical cultures (Carlow, 2006; Gustafson, 2008). The resulting cultural rift between students and choral educators can lead to student exclusion, cultural assimilation, and silencing (Bradley, 2015). Culturally sustaining pedagogy (CSP) is a theoretical construct focused on cultural and linguistic plurality in the classroom. CSP can address the potential cultural rift between educators using Eurocentric teaching paradigms and students’ unique cultures and ways of knowing music, sustaining students’ cultures and thereby preventing student silencing and assimilation (Good-Perkins, 2021b). Therefore, the purpose of this study was to discover the ways, if any, in which three high school choral educators—with multiple musical-cultural proficiencies—enacted culturally sustaining pedagogy in the choral classroom and student perceptions of their teaching. To address the purpose of this study, a multiple case study research method (Stake, 2013) was used. The themes that emerged upon completion of within case and cross-case data analysis included: musical-cultural alignment, importance of cultural dexterity, code-switching, and style shifting, interstitial space between styles, and developing connections. The implications of this research pertain to proposed changes in music teacher preparation and in-service music educator professional development. These changes could positively impact the skills and interests of the future pool of music education program applicants. The potential result of such changes at the K-12 and tertiary levels could be an increase in the diversity of music educators.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24897号 / 工博第5177号 / 新制||工||1988(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 五十嵐 晃, 教授 高橋 良和, 教授 後藤 浩之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Yes / Prior research ignores the specific role of acculturation attitudes in predicting acculturation behaviors and consumption choices across public and private life domains. The study uses self-administered questionnaires to collect data from 530 Turkish-Dutch respondents. The findings underscore the overall significance of investigating domain-specific (public vs. private) acculturation attitudes and subsequent acculturation behaviors. Enculturation (acculturation) behaviors function as a mediating variable in the relationship between acculturation attitudes and consumption of food and entertainment products from the heritage (host) culture. The study is one of the first to investigate the simultaneous effects of acculturation attitudes and acculturation behaviors on the choice to consumer foods and entertainment products from both heritage and host cultures. The article provides managerial implications and future research directions.

No / Since the beginning of time, energy has pervaded our earth. We rely on it to advance in any development. As the energy sources become scarcer, it is important to learn how to save and economize energy. A perfect energy should be cheap and efficient. Bi-Fuel system is such a concept, which combines the best of Diesel and Gas driven engines. Diesel driven engines though provide high power density but own the drawback of high cost and high on-site fuel storage. Gas driven engines provide low cost but own the drawback of low power density. A Bi-Fuel system is Compression ignited engine, which runs on the simultaneous combustion of Diesel and Natural gas. It works by introducing gas to the engine via various technologies and then electronically controlling flow dependent on output. This greatly extends the runtimes and limits the amount of diesel fuel that must be stored on site.

Digitaliseringstrenden har på senare tid medfört utmaningar för organisationer, genom ett allt större fokus på möjligheten att hantera komplexa data och information. Affärsverktyg såsom Business Intelligence (BI) erbjuder möjliga lösningar på dessa problem. Den här studien undersöker Business Intelligence, med fokus på kritiska framgångsfaktorer för BI, som fördelas till tre kategorier; organisatoriska, tekniska, och personalmässiga faktorer. Genom en kvalitativ studie undersöktes vilka faktorer som är allra viktigast för organisationer att ta i beaktning vid användning och förbättring av Business Intelligence. Resultatet indikerar att flera av de i litteraturen signifikanta framgångsfaktorer för BI-implementering även är kritiska för fortsatt integration inom organisationen. Däremot upptäcktes indikationer på att datakvalitet särskiljer sig som mest kritiska faktorn när det gäller BI-framgång, och att den faktorn ligger till grund för flera möjliga förbättringsfaktorer, samtidigt som det finns en rad grundförutsättningar som också måste uppfyllas.

Programmable matter is a material whose properties can be programmed to achieve particular shapes or mechanical properties upon command. This is an essential technique that could one day lead to morphing aircraft and ground vehicles. Metamaterials are the rationally designed artificial materials whose properties are not observed in nature. Their properties are typically controlled by geometry rather than chemical compositions. Combining metamaterials with a programmable function will create a new area in the intelligent material design. The objective of this study is to design and demonstrate a tunable metamaterial and to investigate its thermo-mechanical behavior. An integrated approach to the metamaterial design was used with analytical modeling, numerical simulation, and experimental demonstration. The dynamic thermo-mechanical analysis was used to measure base materials' modulus and thermal expansion coefficient as a function of temperature. CPS, the unit cell of the metamaterial, is composed of circular holes and slits. By decomposing kinematic rotation of the arm and elastic deformation of a bi-material hinge, thermo-mechanical constitutive models of CPS were developed and it was extended to 3D polyhedral structures for securing isotropic properties. Finite element based numerical simulations of CPS and polyhedral models were conducted for comparison with the analytical model. 3D printing of multi-materials was used for sample fabrication followed by tests with uniaxial compressive mechanical tests and thermal tests at 50℃. From the analytical model of the metamaterial, the contour plots were obtained for the effective properties – Poisson's ratio, the effective coefficient of thermal expansion of the metamaterial as a function of geometry and materials. A controllable range of temperature and strain was identified associated with maximized thermal expansion mismatch and contact on the slit surface of CPS, respectively. This work will pave the road toward the design of programmable metamaterials with both mechanically- and thermally- tunable capability and provide unique thermo-mechanical properties with a programmable function.