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Description
Natural rubber and rubber products can be produced from the guayule plant (Parthenium argentatum Gray), which is a low input perennial shrub native to Mexico and the American Southwest. Guayule rubber has the potential to replace Hevea (Hevea brasiliensis) rubber, the most common natural rubber, and synthetic rubber, which is

Natural rubber and rubber products can be produced from the guayule plant (Parthenium argentatum Gray), which is a low input perennial shrub native to Mexico and the American Southwest. Guayule rubber has the potential to replace Hevea (Hevea brasiliensis) rubber, the most common natural rubber, and synthetic rubber, which is derived from petroleum, in a wide variety of products, including automobile tires. Rubbers make up approximately 47% of the analyzed conventional passenger tire's weight, with 31% from synthetic rubber and 16% from natural Hevea rubber. Replacing the current rubber sources used for the tire industry with guayule rubber could help reduce dependency on imported rubber in addition to reducing greenhouse gas emissions. Moreover, residues from guayule rubber are being researched as a bioenergy feedstock to further improve the environmental footprint of guayule rubber products. This study used life cycle assessment (LCA), a useful tool to determine environmental impacts from a product or process, to quantify and compare environmental impacts of the raw material extraction, transportation and manufacturing of a conventional and a guayule rubber based passenger tire. The impact results of this comparative LCA identified the major environmental impacts and contributing process and informed how the impacts from the tire production can be reduced through utilization of natural rubber co-products as electricity off-sets and reducing guayule rubber's environmental impacts through agricultural and transportation modifications. Results showed that tire raw material extraction contributed the majority of impacts in all categories, where the production of guayule rubber for guayule tires, and the production of synthetic rubber for conventional tires, were the main contributors. Guayule rubber impacts occurred mainly from electricity consumption for agricultural irrigation, while synthetic rubber is a petroleum-based material resulting in high impacts. Transportation impacts had little significance compared to other stages in the life cycle, except for smog impacts, which occurred mainly from truck transport for guayule tires, and transoceanic transport for conventional tires. Tire manufacturing impacts occurred mainly from electricity use in the facilities and were reduced with the use of guayule rubber in guayule tires.
ContributorsRasutis, Daina (Author) / Landis, Amy E. (Thesis advisor) / Colvin, Howard (Committee member) / Seager, Thomas P. (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Research in design, emotion, and product experience has focused on establishing a connection between the aesthetic qualities of products and emotions. Studies in product expression have demonstrated relevant patterns between aesthetics and spatial reasoning. In design research, fully understanding latent qualities of consumers assists in developing an immersive product experience

Research in design, emotion, and product experience has focused on establishing a connection between the aesthetic qualities of products and emotions. Studies in product expression have demonstrated relevant patterns between aesthetics and spatial reasoning. In design research, fully understanding latent qualities of consumers assists in developing an immersive product experience which in turn can engender a lasting product relationship. This study evaluates how people interpret the emotionality of form in order to establish a veritable method for interpreting emotional variables in 3D objects.

This research assesses the emotional perception of aesthetic values in 2D and 3D teapots. A teapot image collection and taxonomy was constructed with 101 images of teapots across four centuries. Eighty-four participants completed a card sorting task of twenty randomly distributed teapot images (taken from the total 101 image collection) into Plutchik's eight emotion categories. Individual pieces of the teapots were coded according to the base, handle, lid, or spout that was presented in the image. The coded pieces from the card-sorting task were arranged per frequency in the overall set. Through the use of response data from the card sorting task, a network of the images was developed in Pathfinder. The content of these results were compared to images of models gathered during an interview with an interactive co-creation method referred to as Magnetic Modeling. Magnetic Modeling is a methodological tool that allowed participants to manipulate individualized pieces of 3D printed teapots into proposed emotional labels.

The findings of this research establish prototypical associations in aesthetic traits and teapot piece combinations for each emotion category. Participant responses were categorized into 4 personas representing the types of perceptual bias in the studies' participants. A discussion and comparison of the methods for academic and theoretical practice is provided.
ContributorsHorner, Candace (Author) / Takamura, John (Thesis advisor) / McDermott, Lauren (Committee member) / Branaghan, Russel; (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The main objective of this study is to investigate the behaviour and applications of strain hardening cement composites (SHCC). Application of SHCC for use in slabs of common configurations was studied and design procedures are prepared by employing yield line theory and integrating it with simplified tri-linear model developed in

The main objective of this study is to investigate the behaviour and applications of strain hardening cement composites (SHCC). Application of SHCC for use in slabs of common configurations was studied and design procedures are prepared by employing yield line theory and integrating it with simplified tri-linear model developed in Arizona State University by Dr. Barzin Mobasher and Dr. Chote Soranakom. Intrinsic material property of moment-curvature response for SHCC was used to derive the relationship between applied load and deflection in a two-step process involving the limit state analysis and kinematically admissible displacements. For application of SHCC in structures such as shear walls, tensile and shear properties are necessary for design. Lot of research has already been done to study the tensile properties and therefore shear property study was undertaken to prepare a design guide. Shear response of textile reinforced concrete was investigated based on picture frame shear test method. The effects of orientation, volume of cement paste per layer, planar cross-section and volume fraction of textiles were investigated. Pultrusion was used for the production of textile reinforced concrete. It is an automated set-up with low equipment cost which provides uniform production and smooth final surface of the TRC. A 3-D optical non-contacting deformation measurement technique of digital image correlation (DIC) was used to conduct the image analysis on the shear samples by means of tracking the displacement field through comparison between the reference image and deformed images. DIC successfully obtained full-field strain distribution, displacement and strain versus time responses, demonstrated the bonding mechanism from perspective of strain field, and gave a relation between shear angle and shear strain.
ContributorsAswani, Karan (Author) / Mobasher, Barzin (Thesis advisor) / Dharmarajan, Subramaniam (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Parkinson's disease is a neurodegenerative condition diagnosed on patients with

clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated

number of patients living with Parkinson's disease around the world is seven

to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor

signs of Parkinson's disease patients. It

Parkinson's disease is a neurodegenerative condition diagnosed on patients with

clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated

number of patients living with Parkinson's disease around the world is seven

to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor

signs of Parkinson's disease patients. It is an advanced surgical technique that is used

when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.

This work proposes a behavior recognition model for patients with Parkinson's

disease. In particular, an adaptive learning method is proposed to classify behavioral

tasks of Parkinson's disease patients using local field potential and electrocorticography

signals that are collected during DBS implantation surgeries. Unique patterns

exhibited between these signals in a matched feature space would lead to distinction

between motor and language behavioral tasks. Unique features are first extracted

from deep brain signals in the time-frequency space using the matching pursuit decomposition

algorithm. The Dirichlet process Gaussian mixture model uses the extracted

features to cluster the different behavioral signal patterns, without training or

any prior information. The performance of the method is then compared with other

machine learning methods and the advantages of each method is discussed under

different conditions.
ContributorsDutta, Arindam (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Holbert, Keith E. (Committee member) / Bliss, Daniel W. (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Research was conducted to observe the effect of Number of Transparent Covers and Refractive Index on performance of a domestic Solar Water heating system. The enhancement of efficiency for solar thermal system is an emerging challenge. The knowledge gained from this research will enable to optimize the number of transparent

Research was conducted to observe the effect of Number of Transparent Covers and Refractive Index on performance of a domestic Solar Water heating system. The enhancement of efficiency for solar thermal system is an emerging challenge. The knowledge gained from this research will enable to optimize the number of transparent covers and refractive index prior to develop a solar water heater with improved optical efficiency and thermal efficiency for the collector. Numerical simulation is conducted on the performance of the liquid flat plate collector for July 21st and October 21st from 8 am to 4 pm with different refractive index values 1.1, 1.4, 1.7 and different numbers of transparent covers (0-3). In order to accomplish the proposed method the formulation and solutions are executed using simple software MATLAB. The result demonstrates efficiency of flat plate collector increases with the increase of number of covers. The performance of collector decreases when refractive index is higher. The improved useful heat gain is obtained when number of cover used is 3 and refractive index is 1.1.
ContributorsSupriti, Shahina Parvin (Author) / Rogers, Bradley (Thesis advisor) / Madakannan, Arunachalanadar (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Qualifications based selection (QBS) of construction services uses a variety of criteria to evaluate proponents and select a contractor for the project. The criteria typically fall into three categories: past performance and technical capability, key personnel, and price, with price often being considered the most important factor in selection. Evaluation

Qualifications based selection (QBS) of construction services uses a variety of criteria to evaluate proponents and select a contractor for the project. The criteria typically fall into three categories: past performance and technical capability, key personnel, and price, with price often being considered the most important factor in selection. Evaluation and the merits of the key personnel category is not well described or discussed in research. Prior research has investigated the evaluation criteria elements and their ability to differentiate proponents. This case study uses QBS evaluation data from fifty-eight construction projects to show that use of a structured interview process provides the highest level of differentiation of qualifications of proponents, as compared to the proposed price and the technical proposal. The results of the analysis also indicate: 1) the key personnel element (the interview) is statistically more important than price,

2) Contractors who propose on projects using QBS should use their best people in proposal response, and 3) Contractors should educate/prepare their teams for interviews, people count.
ContributorsSawyer, Jeff T (Author) / Sullivan, Kennth S (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD)

In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD) employed to generate the packing ensembles will be discussed. A large number of 2D packing configurations of superdisks are subsequently analyzed, through which a relatively accurate theoretical scheme for packing-fraction prediction based on local particle contact configurations is proposed and validated via additional numerical simulations. Moreover, the studies on binary ellipsoid packing in 3D are briefly discussed and the effects of different geometrical parameters on the final packing fraction are analyzed.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Oswald, Jay (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Laminated composite materials are used in aerospace, civil and mechanical structural systems due to their superior material properties compared to the constituent materials as well as in comparison to traditional materials such as metals. Laminate structures are composed of multiple orthotropic material layers bonded together to form a single performing

Laminated composite materials are used in aerospace, civil and mechanical structural systems due to their superior material properties compared to the constituent materials as well as in comparison to traditional materials such as metals. Laminate structures are composed of multiple orthotropic material layers bonded together to form a single performing part. As such, the layup design of the material largely influences the structural performance. Optimization techniques such as the Genetic Algorithm (GA), Differential Evolution (DE), the Method of Feasible Directions (MFD), and others can be used to determine the optimal laminate composite material layup. In this thesis, sizing, shape and topology design optimization of laminated composites is carried out. Sizing optimization, such as the layer thickness, topology optimization, such as the layer orientation and material and the number of layers present, and shape optimization of the overall composite part contribute to the design optimization process of laminates. An optimization host program written in C++ has been developed to implement the optimization methodology of both population based and numerical gradient based methods. The performance of the composite structural system is evaluated through explicit finite element analysis of shell elements carried out using LS-DYNA. Results from numerical examples demonstrate that optimization design processes can significantly improve composite part performance through implementation of optimum material layup and part shape.
ContributorsMika, Krista (Author) / Rajan, Subramaniam D. (Thesis advisor) / Neithalath, Narayanan (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of

The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of the key applications of smart grid. Demand response today is envisioned as a method in which the price could be communicated to the consumers and they may shift their loads from high price periods to the low price periods. The development and deployment of the FREEDM system necessitates controls of energy and power at the point of end use.

In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.

The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
ContributorsMusani, Aatif (Author) / Heydt, Gerald (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs,

An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs, when compared with standard industrial resource sharing networks, prove to be of greater public advantage as they offer improved environmental and economic benefits, and higher operational efficiencies both upstream and downstream in their supply chain.

Although there have been many attempts to adapt EIP methodology to existing industrial sharing networks, most of them have failed for various factors: geographic restrictions by governmental organizations on use of technology, cost of technology, the inability of industries to effectively communicate their upstream and downstream resource usage, and to diminishing natural resources such as water, land and non-renewable energy (NRE) sources for energy production.

This paper presents a feasibility study conducted to evaluate the comparative environmental, economic, and geographic impacts arising from the use of renewable energy (RE) and NRE to power EIPs. Life Cycle Assessment (LCA) methodology, which is used in a variety of sectors to evaluate the environmental merits and demerits of different kinds of products and processes, was employed for comparison between these two energy production methods based on factors such as greenhouse gas emission, acidification potential, eutrophication potential, human toxicity potential, fresh water usage and land usage. To complement the environmental LCA analysis, levelized cost of electricity was used to evaluate the economic impact. This model was analyzed for two different geographic locations; United States and Europe, for 12 different energy production technologies.

The outcome of this study points out the environmental, economic and geographic superiority of one energy source over the other, including the total carbon dioxide equivalent emissions, which can then be related to the total number of carbon credits that can be earned or used to mitigate the overall carbon emission and move closer towards a net zero carbon footprint goal thus making the EIPs truly sustainable.
ContributorsGupta, Vaibhav (Author) / Calhoun, Ronald J (Thesis advisor) / Dooley, Kevin (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2014