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Description
Utilizing the Arizona State University's Performance Based Studies Research Group, and their PIPS program, a roofing materials manufacturing company can evaluate performance of representatives, products and contractors. Service life of the systems can be tracked and customer satisfaction measured it provides an objective viable tool for the consumer to choose a quality product and contractor without the distractions of marketing, promises, or a salesman's hype. Facilities purchasing a new roof system, can benefit from the information gathered as a guide in making sound, value based decisions. Creating a historical, concise and accurate documentation of roofing systems is a benefit to all involved. The procurement process, installation and longevity of the roofing systems can be tracked and graded.
ContributorsGreenfeld, Larry (Author) / Kashiwagi, Dean T. (Thesis advisor) / Sullivan, Kenneth T. (Committee member) / Badger, William W. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Unfortunately, existing approaches to LCA are unreliable in the cases of emerging technologies, where data is unavailable and rapid technological advances outstrip environmental knowledge. Previous studies have demonstrated several shortcomings to existing practices, including the masking of environmental impacts, the difficulty of selecting appropriate weight sets for multi-stakeholder problems, and difficulties in exploration of variability and uncertainty. In particular, there is an acute need for decision-driven interpretation methods that can guide decision makers towards making balanced, environmentally sound decisions in instances of high uncertainty. We propose the first major methodological innovation in LCA since early establishment of LCA as the analytical perspective of choice in problems of environmental management. We propose to couple stochastic multi-criteria decision analytic tools with existing approaches to inventory building and characterization to create a robust approach to comparative technology assessment in the context of high uncertainty, rapid technological change, and evolving stakeholder values. Namely, this study introduces a novel method known as Stochastic Multi-attribute Analysis for Life Cycle Impact Assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces.
ContributorsPrado, Valentina (Author) / Seager, Thomas P (Thesis advisor) / Landis, Amy E. (Committee member) / Chester, Mikhail (Committee member) / White, Philip (Committee member) / Arizona State University (Publisher)
Created2013
Description
Dye sensitized solar cells (DSSCs) are currently being explored as a cheaper alternative to the more common silicon (Si) solar cell technology. In addition to the cost advantages, DSSCs show good performance in low light conditions and are not sensitive to varying angles of incident light like traditional Si cells. One of the major challenges facing DSSCs is loss of the liquid electrolyte, through evaporation or leakage, which lowers stability and leads to increased degradation. Current research with solid-state and quasi-solid DSSCs has shown success regarding a reduction of electrolyte loss, but at a cost of lower conversion efficiency output. The research work presented in this paper focuses on the effects of using nanoclay material as a gelator in the electrolyte of the DSSC. The data showed that the quasi-solid cells are more stable than their liquid electrolyte counterparts, and achieved equal or better I-V characteristics. The quasi-solid cells were fabricated with a gel electrolyte that was prepared by adding 7 wt% of Nanoclay, Nanomer® (1.31PS, montmorillonite clay surface modified with 15-35% octadecylamine and 0.5-5 wt% aminopropyltriethoxysilane, Aldrich) to the iodide/triiodide liquid electrolyte, (Iodolyte AN-50, Solaronix). Various gel concentrations were tested in order to find the optimal ratio of nanoclay to liquid. The gel electrolyte made with 7 wt% nanoclay was more viscous, but still thin enough to allow injection with a standard syringe. Batches of cells were fabricated with both liquid and gel electrolyte and were evaluated at STC conditions (25°C, 100 mW/cm2) over time. The gel cells achieved efficiencies as high as 9.18% compared to 9.65% achieved by the liquid cells. After 10 days, the liquid cell decreased to 1.75%, less than 20% of its maximum efficiency. By contrast, the gel cell's efficiency increased for two weeks, and did not decrease to 20% of maximum efficiency until 45 days. After several measurements, the liquid cells showed visible signs of leakage through the sealant, whereas the gel cells did not. This resistance to leakage likely contributed to the improved performance of the quasi-solid cells over time, and is a significant advantage over liquid electrolyte DSSCs.
ContributorsMain, Laura (Author) / Munukutla, Lakshmi (Thesis advisor) / Madakannan, Arunachalanadar (Committee member) / Polesky, Gerald (Committee member) / Arizona State University (Publisher)
Created2012
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Potential induced degradation (PID) due to high system voltages is one of the major degradation mechanisms in photovoltaic (PV) modules, adversely affecting their performance due to the combined effects of the following factors: system voltage, superstrate/glass surface conductivity, encapsulant conductivity, silicon nitride anti-reflection coating property and interface property (glass/encapsulant; encapsulant/cell; encapsulant/backsheet). Previous studies carried out at ASU's Photovoltaic Reliability Laboratory (ASU-PRL) showed that only negative voltage bias (positive grounded systems) adversely affects the performance of commonly available crystalline silicon modules. In previous studies, the surface conductivity of the glass surface was obtained using either conductive carbon layer extending from the glass surface to the frame or humidity inside an environmental chamber. This thesis investigates the influence of glass surface conductivity disruption on PV modules. In this study, conductive carbon was applied only on the module's glass surface without extending to the frame and the surface conductivity was disrupted (no carbon layer) at 2cm distance from the periphery of frame inner edges. This study was carried out under dry heat at two different temperatures (60 °C and 85 °C) and three different negative bias voltages (-300V, -400V, and -600V). To replicate closeness to the field conditions, half of the selected modules were pre-stressed under damp heat for 1000 hours (DH 1000) and the remaining half under 200 hours of thermal cycling (TC 200). When the surface continuity was disrupted by maintaining a 2 cm gap from the frame to the edge of the conductive layer, as demonstrated in this study, the degradation was found to be absent or negligibly small even after 35 hours of negative bias at elevated temperatures. This preliminary study appears to indicate that the modules could become immune to PID losses if the continuity of the glass surface conductivity is disrupted at the inside boundary of the frame. The surface conductivity of the glass, due to water layer formation in a humid condition, close to the frame could be disrupted just by applying a water repelling (hydrophobic) but high transmittance surface coating (such as Teflon) or modifying the frame/glass edges with water repellent properties.
ContributorsTatapudi, Sai Ravi Vasista (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
Description
With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic monitoring and management, etc. To better understand movement behaviors from the raw mobility data, this doctoral work provides analytic models for analyzing trajectory data. As a first contribution, a model is developed to detect changes in trajectories with time. If the taxis moving in a city are viewed as sensors that provide real time information of the traffic in the city, a change in these trajectories with time can reveal that the road network has changed. To detect changes, trajectories are modeled with a Hidden Markov Model (HMM). A modified training algorithm, for parameter estimation in HMM, called m-BaumWelch, is used to develop likelihood estimates under assumed changes and used to detect changes in trajectory data with time. Data from vehicles are used to test the method for change detection. Secondly, sequential pattern mining is used to develop a model to detect changes in frequent patterns occurring in trajectory data. The aim is to answer two questions: Are the frequent patterns still frequent in the new data? If they are frequent, has the time interval distribution in the pattern changed? Two different approaches are considered for change detection, frequency-based approach and distribution-based approach. The methods are illustrated with vehicle trajectory data. Finally, a model is developed for clustering and outlier detection in semantic trajectories. A challenge with clustering semantic trajectories is that both numeric and categorical attributes are present. Another problem to be addressed while clustering is that trajectories can be of different lengths and also have missing values. A tree-based ensemble is used to address these problems. The approach is extended to outlier detection in semantic trajectories.
ContributorsKondaveeti, Anirudh (Author) / Runger, George C. (Thesis advisor) / Mirchandani, Pitu (Committee member) / Pan, Rong (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
Description
III-Nitride nanostructures have been an active area of research recently due to their ability to tune their optoelectronic properties. Thus far work has been done on InGaN quantum dots, nanowires, nanopillars, amongst other structures, but this research reports the creation of a new type of InGaN nanostructure, nanorings. Hexagonal InGaN nanorings were formed using Metal Organic Chemical Vapor Deposition through droplet epitaxy. The nanorings were thoroughly analyzed using x-ray diffraction, photoluminescence, electron microscopy, electron diffraction, and atomic force microscopy. Nanorings with high indium incorporation were achieved with indium content up to 50% that was then controlled using the growth time, temperature, In/Ga ratio and III/N ratio. The analysis showed that the nanoring shape is able to incorporate more indium than other nanostructures, due to the relaxing mechanism involved in the formation of the nanoring. The ideal conditions were determined to be growth of 30 second droplets with a growth time of 1 minute 30 seconds at 770 C to achieve the most well developed rings with the highest indium concentration.
ContributorsZaidi, Zohair (Author) / Mahajan, Subhash (Thesis advisor) / O'Connell, Michael J (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Dealloying induced stress corrosion cracking is particularly relevant in energy conversion systems (both nuclear and fossil fuel) as many failures in alloys such as austenitic stainless steel and nickel-based systems result directly from dealloying. This study provides evidence of the role of unstable dynamic fracture processes in dealloying induced stress-corrosion cracking of face-centered cubic alloys. Corrosion of such alloys often results in the formation of a brittle nanoporous layer which we hypothesize serves to nucleate a crack that owing to dynamic effects penetrates into the un-dealloyed parent phase alloy. Thus, since there is essentially a purely mechanical component of cracking, stress corrosion crack propagation rates can be significantly larger than that predicted from electrochemical parameters. The main objective of this work is to examine and test this hypothesis under conditions relevant to stress corrosion cracking. Silver-gold alloys serve as a model system for this study since hydrogen effects can be neglected on a thermodynamic basis, which allows us to focus on a single cracking mechanism. In order to study various aspects of this problem, the dynamic fracture properties of monolithic nanoporous gold (NPG) were examined in air and under electrochemical conditions relevant to stress corrosion cracking. The detailed processes associated with the crack injection phenomenon were also examined by forming dealloyed nanoporous layers of prescribed properties on un-dealloyed parent phase structures and measuring crack penetration distances. Dynamic fracture in monolithic NPG and in crack injection experiments was examined using high-speed (106 frames s-1) digital photography. The tunable set of experimental parameters included the NPG length scale (20-40 nm), thickness of the dealloyed layer (10-3000 nm) and the electrochemical potential (0.5-1.5 V). The results of crack injection experiments were characterized using the dual-beam focused ion beam/scanning electron microscopy. Together these tools allow us to very accurately examine the detailed structure and composition of dealloyed grain boundaries and compare crack injection distances to the depth of dealloying. The results of this work should provide a basis for new mathematical modeling of dealloying induced stress corrosion cracking while providing a sound physical basis for the design of new alloys that may not be susceptible to this form of cracking. Additionally, the obtained results should be of broad interest to researchers interested in the fracture properties of nano-structured materials. The findings will open up new avenues of research apart from any implications the study may have for stress corrosion cracking.
ContributorsSun, Shaofeng (Author) / Sieradzki, Karl (Thesis advisor) / Jiang, Hanqing (Committee member) / Peralta, Pedro (Committee member) / Arizona State University (Publisher)
Created2012
Description
The focus of this document is the examination of a new robot simulator developed to aid students in learning robotics programming and provide the ability to test their programs in a simulated world. The simulator, accessed via a website, provides a simulated environment, programming interface, and the ability to control a simulated robot. The simulated environment consists of a user-customizable maze and a robot, which can be controlled manually, via Web service, or by utilizing the Web programming interface. The Web programming interface provides dropdown boxes from which the users may select various options to program their implementations. It is designed to aid new students in the learning of basic skills and thought processes used to program robots. Data was collected and analyzed to determine how effective this system is in helping students learn. This included how quickly students were able to program the algorithms assigned to them and how many lines of code were used to implement them. Students' performance was also monitored to determine how well they were able to use the program and if there were any significant problems. The students also completed surveys to communicate how well the website helped them learn and understand various concepts. The data collected shows that the website was a helpful learning tool for the students and that they were able to use the programming interface quickly and effectively.
ContributorsDrown, Garrett (Author) / Tsai, Wei-Tek (Thesis advisor) / Chen, Yinong (Thesis advisor) / Claveau, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation presents the Temporal Event Query Language (TEQL), a new language for querying event streams. Event Stream Processing enables online querying of streams of events to extract relevant data in a timely manner. TEQL enables querying of interval-based event streams using temporal database operators. Temporal databases and temporal query languages have been a subject of research for more than 30 years and are a natural fit for expressing queries that involve a temporal dimension. However, operators developed in this context cannot be directly applied to event streams. The research extends a preexisting relational framework for event stream processing to support temporal queries. The language features and formal semantic extensions to extend the relational framework are identified. The extended framework supports continuous, step-wise evaluation of temporal queries. The incremental evaluation of TEQL operators is formalized to avoid re-computation of previous results. The research includes the development of a prototype that supports the integrated event and temporal query processing framework, with support for incremental evaluation and materialization of intermediate results. TEQL enables reporting temporal data in the output, direct specification of conditions over timestamps, and specification of temporal relational operators. Through the integration of temporal database operators with event languages, a new class of temporal queries is made possible for querying event streams. New features include semantic aggregation, extraction of temporal patterns using set operators, and a more accurate specification of event co-occurrence.
ContributorsShiva, Foruhar Ali (Author) / Urban, Susan D (Thesis advisor) / Chen, Yi (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2012