Product lifecycles are complex heterogeneous systems. Applying control methods to lifecycles requires significant human capital. Additionally, measuring lifecycles relies primarily on domain expertise and estimates. Presented in this dissertation is a way to semantically represent a product lifecycle as a cyber-physical system for enabling the application of control methods to the lifecycle. Control requires a model and no models exist currently that integrate each phase of lifecycles. The contribution is an integration framework that brings all phases and systems of a lifecycle together. First presented is a conceptual framework and technology innovation. Next, linking product lifecycle data dynamical is described and then how that linked data could be certified and traced for trustworthiness. After that, discussion is focused how the trusted linked data could be combined with machine learning to drive applications throughout the product lifecycle. Last, a case study is provided that integrates the framework and technology. Integrating all of this would enable efficient and effective measurements of the lifecycle to support prognostic and diagnostic control of that lifecycle and related decisions. / Ph. D. / The manufacturing sector is on a precipice to disruptive change that will signifcantly alter the way industrial organizations think, communicate, and interact. Industry has been chasing the dream of integrating and linking data across the product lifecycle and enterprises for decades. However, inexpensive and easy to implement technologies to integrate the people, processes, and things across various enterprises are still not available to the entire value stream. Industry needs technologies that use cyber-physical infrastructures efectively and efciently to collect and analyze data and information across an enterprise instead of a single domain of expertise. Meeting key technical needs would save over $100 billion annually in emerging advanced manufacturing sectors in the US. By enabling a systems-thinking approach, signifcant economic opportunities can be achieved through an industrial shift from paper-based processes to a digitally enabled model-based enterprise via the digital thread. The novel contribution of this dissertation is a verifed and validated integration framework, using trusted linked-data, that brings all phases and systems of the product lifecycle together. A technology agnostic approach was pursued for dynamically generating links. A demonstration is presented as a reference implementation using currently available technology. Requirements, models, and policies were explored for enabling product-data trustworthiness. All methods were developed around open, consensus-based standards to increase the likelihood of scalability. The expected outcome of this work is efcient and efective measurements of the lifecycle to support data-driven methods, specifcally related to knowledge building, decision support, requirements management, and control of the entire product lifecycle.

DC nano-grid system shows promising prospect and enjoys some advantages over AC micro-grid system. It enables easier integration of multiple renewable energy sources with multiple loads. Photovoltaic (PV) is essentially a typical renewable source that serves as main power source in DC nano-grid system. Traditional PV system includes centralized PV system, string PV system and micro-converter PV system. More recently, smart converter PV system has been introduced and shown great improvement in aspects of power generation achieved by distributed Maximum Power Point Tracking (MPPT). It is also advantageous over micro-converter PV system due to lower cost and flexibility. Detailed case study demonstrates that power generation efficiency can be easily compromised because of mismatch between different panels in centralized and string PV systems. In smart converter PV system, this problem can be solved due to distributed MPPT for each individual panel. The smart converter system has a very wide voltage range within which all panels can generate maximum power. The location and the width of this range are subject to change under different mismatch conditions. A second stage converter is needed to locate the array MPPT range. However, there is instability problem when doing second stage MPPT with traditional methods. Modified methods based on conductance control and resistance control are analyzed and compared. Both methods can solve the MPPT instability problem. However, in terms of steady state performance, resistance control MPPT is more promising in terms of higher utilization ratio and faster tracking speed. It is because both methods are of inherited variable operating point step size with constant conductance or resistance perturbation step size. However, the operating point change decreases with resistance perturbation but increases with conductance perturbation otherwise. Therefore, resistance control MPPT is chosen as a good candidate. Both simulation and experimental results verifies the concept. / Master of Science

Ionic polymer membranes are commonly used in fuel cell power generation, water electrolysis and desalinization, chlorine generation, and other niche applications. Since the early 1990s ionic polymer membranes have also shown promise as distributed electromechanical actuators and sensors. The cost of these materials is very high because of the expensive noble metals that are used as the electrodes in these applications, however. Currently, high cost of these devices has prevented them from experiencing widespread use. The goal of the current research project is to study new methods of plating metal electrodes onto ionic polymer membranes in order to reduce the cost of these materials and open the door for potential industrial, aerospace, and biomedical applications. At this time ionic polymer actuators are only made using gold or platinum as the electrode in a lengthy and labor-intensive process. The current research focuses on using less costly metals and revising the metal deposition process. Several new methods allowing for faster deposition of metals onto ionic polymer membranes are developed and evaluated including sputter-coating, electroless plating, and impregnation/reduction. Using these methods, metal electrodes have been plated onto ionic polymer membranes in processes resulting in a purely surface deposition and in processes resulting in interpenetration of the metal into the polymer. This work shows that electromechanical coupling is present with all of these processes, although results indicate that interpenetration of the electrode is important for good adhesion of the metal and good performance of the transducers. Also studied were different metals; X-ray photoelectron spectroscopy (XPS) testing shows that the use of non-noble metals as the electrodes results in oxidation of the metal and corresponding loss of performance in the actuator. Noble metals are found to not experience the oxidation problem. Further work shows that non-noble metals can be effectively employed as electrodes if alloyed with noble metals by using a co-reduction technique. Also studied is the use of protective coatings of noble metal to stabilize the non-noble metal electrodes. Using these approaches, a new plating method is developed and the stability of the electrodes made using this method is studied. These results indicate that samples made using this new process may be actauted continuously for over 150,000 cycles with very little degredation in their performance. Using this new plating method, ionic polymer membrane transducers can be made in less than five hours. Characterization of these new devices shows that they have a mass energy density of 4-20 mJ/kg in the cantilevered mode. This compares well with a baseline material, which is found to have a mass energy density of 3-12 mJ/kg. Composition and morphology of the electrodes made using the new method are investigated using scanning electron microscopy (SEM) and the density and tensile modulus are measured. The density of the new material is found to be approximately 2100 kg/m^3 as compared to about 3200 kg/m^3 for the baseline material. Also, the tensile elastic modulus of the new material is about 55 MPa, or roughly one fourth of the tensile modulus of the baseline material (about 190 MPa). These results indicate that the new materials contain much less noble metal in the electrodes than the baseline material. The sensitivity of these devices has also been quantified and compared to the baseline. Results indicate that the new materials have a sensitivity on the order of 0.1-0.3 uA/mm/s whereas similarly sized samples of the baseline material typically have sensitivities on the order of 0.2-0.8 uA/mm/s. The most important conclusion of this work is that ionic polymer membrane transducers can be made using much less noble metal in the electrode than previously believed without sacrificing the performance of these devices. / Master of Science

Due to the ever increasing supply of new Internet of Things (IoT) devices being added onto a network, it is vital secure the devices from incoming cyber threats. The manufacturing process of creating and developing a new IoT device allows many new companies to come out with their own device. These devices also increase the network risk because many IoT devices are created without proper security implementation. Utilizing traffic patterns as a method of device type detection will allow behavior identification using only Internet Protocol (IP) header information. The network traffic captured from 20 IoT devices belonging to 4 distinct types (IP camera, on/off switch, motion sensor, and temperature sensor) are generalized and used to identify new devices previously unseen on the network. Our results indicate some categories have patterns that are easier to generalize, while other categories are harder but we are still able recognize some unique characteristics. We also are able to deploy this in a test production network and adapted previous methods to handle streaming traffic and an additional noise categorization capable of identify non-IoT devices. The performance of our model is varied between classes, signifying that much future work has to be done to increase the classification score and overall usefulness. / Master of Science / IoT (Internet of Things) devices are an exploding field, with many devices being created, manufactured, and utilized per year. With the rise of so many internet capable devices, there is a risk that the devices may have vulnerabilities and exploits able to allow unauthorized users to access. While a problem for a consumer network, this is an increased problem in an enterprise network, since much of the information on the network is sensitive and should be kept confidential and private. While a ban of IoT devices on a network is able to solve this problem, with the rise of machine learning able to characterize and recognize patterns, a smarter approach can be created to distinguish when and which types of IoT devices enter the network. Previous attempts to identify IoT devices used signature schemes specific to a single device, but this paper aims to generalize traffic behaviors and identifying a device category rather than a specific IoT device to ensure future new devices can also be recognized. With device category identification in place on an internet network, smarter approaches can be implemented to ensure the devices remain secure while still able to be used.

The rapid growth of the Internet of Things (IoT) has led to a situation where individual manufacturers develop their own communication protocols and frameworks that are often incompatible with other systems. Part of this is due to the use of incompatible communication hardware, and part is due to the entrenched proprietary systems. This has created a heterogeneous communication landscape, where it is difficult for devices to coordinate their efforts. To remedy this, a number of IoT Frameworks have been proposed to provide a common interface between IoT devices. There are many approaches to common frameworks, each with their strengths and weaknesses, but there is no clear winner among them. This thesis presents a virtual network testbed for implementing smart home IoT Frameworks. It consists of a simulated home network made up of multiple Virtual Machines (VM), simulated smart home devices and an implementation of the OpenHAB framework to integrate the devices. Simulated devices are designed to be network- accurate representations of actual devices, a LIFX smart lightbulb was developed and an existing Nest thermostat simulation was integrated. The demonstrated setup serves as a proof of concept for the idea of a home network testbed. Such a testbed could allow for the development of new IoT frameworks or the comparison of existing ones, and it could also serve as an education aid to illustrate how smart home IoT devices communicate with one another. / Master of Science / The rapid growth of the Internet of Things (IoT) has led to a situation where individual manufacturers develop their own systems for communicating with devices, which don’t work with other devices. A lot of this is due to devices using different technologies; for example, a Bluetooth device trying to talk to a Wi-Fi device. This has created a situation where it is difficult for different devices to communicate. To remedy this, a number of IoT Frameworks have been proposed to provide a common language between IoT devices. There are many approaches to common frameworks, each with their strengths and weaknesses, but there is no clear winner among them. This thesis presents a simulation environment for smart home IoT Frameworks. It consists of a simulated home network made up of multiple Virtual Machines (VM), simulated smart home devices and an implementation of the OpenHAB framework to integrate the devices. Simulated devices are designed to be accurate representations of actual devices, a LIFX smart lightbulb was developed and an existing Nest thermostat simulation was integrated. The demonstrated setup serves as a proof of concept for the idea of a home network testbed. Such a testbed could allow for the development of new IoT frameworks or the comparison of existing ones, and it could also serve as an education aid to illustrate how smart home IoT devices communicate with one another.

Yes / Smart cities can help in achieving UN SDG. This research carries out a comprehensive analysis of the role of smart cities on creating sustainable cities and communities, which is one of 17 UN sustainable goals. Current research focuses on number of aspect of sustainable environment such as renewable and green energy, energy efficiency, environmental monitoring, air quality, and water quality. This study provides a valuable synthesis of the relevant literature on smart cities by analysing and discussing the key findings from existing research on issues of smart cities in creating sustainable cities and communities. The findings of this study can provide an informative framework for research on smart cities for academics and practitioners.

A computational model is presented which predicts the force, stroke, and energy needed to overcome aerodynamic loads encountered by morphing wings during aircraft maneuvers. This low-cost model generates wing section shapes needed to follow a desired flight path, computes the resulting aerodynamic forces using a unique combination of conformal mapping and the vortex panel method, computes the longitudinal motion of the simulated aircraft, and closes the loop with a zero-error control law. The aerodynamic force prediction method has been verified against two more expensive codes. This overall model will be used to predict the performance of morphing wings and the requirements for the active material actuators in the wings. / Master of Science

Yes / Engineered Cementitious Composites (ECC) is a material which possesses advanced self-healing properties. Although the self-healing performance of ECC has been revealed in numerous studies, only small-scale, laboratory-size specimens have been used to assess it under fixed laboratory conditions and curing techniques. In order to evaluate the effect of intrinsic self-healing ability of ECC on the properties of structural-size, large-scale reinforced-beam members, specimens with four different shear span to effective depth (a/d) ratios, ranging from 1 to 4, were prepared to evaluate the effects of shear and flexural deformation. To ensure a realistic assessment, beams were cured using wet burlap, similar to on-site curing. Each beam was tested for mechanical properties including load-carrying capacity, deflection capacity, ductility ratio, yield stiffness, energy absorption capacity, and the influence of self-healing, by comparing types of failure and cracking. Self-healed test beams showed higher strength, energy absorption capacity and ductility ratio than damaged test beams. In test beams with an a/d ratio of 4 in which flexural behavior was prominent, self-healing application was highly successful; the strength, energy absorption capacity and ductility ratios of these beams achieved the level of undamaged beams. In addition, flexural cracks healed better, helping recover the properties of beams with predominantly flexural cracks rather than shear cracks. / The authors gratefully acknowledge the financial assistance of the Scientific and Technical Research Council (TUBITAK) of Turkey provided under Project: MAG-112M876 and the Turkish Academy of Sciences, Young Scientist Award program. The second author would also like to acknowledge the financial support of TÜBITAK for the 2219 Scholarship.

published_or_final_version / Business Administration / Master / Master of Business Administration

Examensarbetet Binary surfaces - ljusemitterande textiler för inredningssammanhang är ett undersökande arbete om hur fiberoptik kan användas i vävda strukturer. I arbetet har de parametrar som påverkar mötet mellan fiberoptik och väv, samt de möjligheter de tillsammans skapar utforskats. Resultatet är två exempel på tyger vävda med fiberoptik i kombination med mer traditionella textila material. Exemplen är framtagna för inredningssammanhang och visas som en rumsavdelare och som yttertyg på sittmöbler. / The thesis Binary surfaces - light-emitting textiles for an interior design context is an investigative work on how optical fibres can be used in woven structures. The work explores the different parameters that affect the interaction between optical fibres and weaving, and the possibilities they create together. The result is two examples of fabrics woven with optical fibres in combination with more traditional textile materials. The examples are designed for an interior context and are shown as a room divider and as outer fabric on seating furnishing.