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- All Subjects: engineering
- Creators: Sugar, Thomas
- Creators: Neithalath, Narayanan
Description
The alkali activation of aluminosilicate materials as binder systems derived from industrial byproducts have been extensively studied due to the advantages they offer in terms enhanced material properties, while increasing sustainability by the reuse of industrial waste and byproducts and reducing the adverse impacts of OPC production. Fly ash and ground granulated blast furnace slag are commonly used for their content of soluble silica and aluminate species that can undergo dissolution, polymerization with the alkali, condensation on particle surfaces and solidification. The following topics are the focus of this thesis: (i) the use of microwave assisted thermal processing, in addition to heat-curing as a means of alkali activation and (ii) the relative effects of alkali cations (K or Na) in the activator (powder activators) on the mechanical properties and chemical structure of these systems. Unsuitable curing conditions instigate carbonation, which in turn lowers the pH of the system causing significant reductions in the rate of fly ash activation and mechanical strength development. This study explores the effects of sealing the samples during the curing process, which effectively traps the free water in the system, and allows for increased aluminosilicate activation. The use of microwave-curing in lieu of thermal-curing is also studied in order to reduce energy consumption and for its ability to provide fast volumetric heating. Potassium-based powder activators dry blended into the slag binder system is shown to be effective in obtaining very high compressive strengths under moist curing conditions (greater than 70 MPa), whereas sodium-based powder activation is much weaker (around 25 MPa). Compressive strength decreases when fly ash is introduced into the system. Isothermal calorimetry is used to evaluate the early hydration process, and to understand the reaction kinetics of the alkali powder activated systems. A qualitative evidence of the alkali-hydroxide concentration of the paste pore solution through the use of electrical conductivity measurements is also presented, with the results indicating the ion concentration of alkali is more prevalent in the pore solution of potassium-based systems. The use of advanced spectroscopic and thermal analysis techniques to distinguish the influence of studied parameters is also discussed.
ContributorsChowdhury, Ussala (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramanium D. (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2013
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 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
Description
For decades, microelectronics manufacturing has been concerned with failures related to electromigration phenomena in conductors experiencing high current densities. The influence of interconnect microstructure on device failures related to electromigration in BGA and flip chip solder interconnects has become a significant interest with reduced individual solder interconnect volumes. A survey indicates that x-ray computed micro-tomography (µXCT) is an emerging, novel means for characterizing the microstructures' role in governing electromigration failures. This work details the design and construction of a lab-scale µXCT system to characterize electromigration in the Sn-0.7Cu lead-free solder system by leveraging in situ imaging.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
ContributorsMertens, James Charles Edwin (Author) / Chawla, Nikhilesh (Thesis advisor) / Alford, Terry (Committee member) / Jiao, Yang (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2015
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 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
Description
The studies on aluminosilicate materials to replace traditional construction materials such as ordinary Portland cement(OPC) to reduce the effects caused has been an important research area for the past decades. Many properties like strength have already been studied and the primary focus is to learn about the reaction mechanism and the effect of the parameters on the formed products. The aim of this research was to explore the structural changes and reaction product analysis of geopolymers (Slag & Fly Ash) using Fourier transform infrared spectroscopy (FTIR) and deconvolution
techniques. Spectroscopic techniques give valuable information at a molecular level but not all methods are economic and simple. To understand the mechanisms of alkali activated aluminosilicate materials, attenuated total reflectance (ATR) FTIR has been used where the effect of the parameters on the reaction products have been analyzed. To analyze complex systems like geopolymers using FTIR, deconvolution techniques help to obtain the properties of a particular peak attributed to a certain molecular vibration.
Time and temperature dependent analysis were done on slag pastes to understand the polymerization of reactive silica in the system with time and temperature variance. For time dependent analysis slag has been activated with sodium and potassium silicates using two different `n'values and three different silica modulus [Ms- (SiO2 /M2O)] values. The temperature dependent analysis was done by curing the samples at 60C and 80C. Similarly fly ash has been studied by activating with alkali hydroxides and alkali silicates. Under the same curing conditions the fly ash samples were evaluated to analyze the effects of added silicates for alkali activation.
The peak shifts in the FTIR explains the changes in the structural nature of the matrix and can be identified using the deconvolution technique. A strong correlation is found between the concentrations of silicate monomer in the activating position of the main Si-O-T (where T is Al/Si) stretching band in the FTIR spectrum, which
gives an indication of the relative changes in the Si/Al ratio. Also, the effect of the cation and silicate concentration in the activating solution has been discussed using the Fourier self deconvolution technique.
techniques. Spectroscopic techniques give valuable information at a molecular level but not all methods are economic and simple. To understand the mechanisms of alkali activated aluminosilicate materials, attenuated total reflectance (ATR) FTIR has been used where the effect of the parameters on the reaction products have been analyzed. To analyze complex systems like geopolymers using FTIR, deconvolution techniques help to obtain the properties of a particular peak attributed to a certain molecular vibration.
Time and temperature dependent analysis were done on slag pastes to understand the polymerization of reactive silica in the system with time and temperature variance. For time dependent analysis slag has been activated with sodium and potassium silicates using two different `n'values and three different silica modulus [Ms- (SiO2 /M2O)] values. The temperature dependent analysis was done by curing the samples at 60C and 80C. Similarly fly ash has been studied by activating with alkali hydroxides and alkali silicates. Under the same curing conditions the fly ash samples were evaluated to analyze the effects of added silicates for alkali activation.
The peak shifts in the FTIR explains the changes in the structural nature of the matrix and can be identified using the deconvolution technique. A strong correlation is found between the concentrations of silicate monomer in the activating position of the main Si-O-T (where T is Al/Si) stretching band in the FTIR spectrum, which
gives an indication of the relative changes in the Si/Al ratio. Also, the effect of the cation and silicate concentration in the activating solution has been discussed using the Fourier self deconvolution technique.
ContributorsMadavarapu, Sateesh Babu (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Marzke, Robert (Committee member) / Arizona State University (Publisher)
Created2014
Description
Brain Computer Interfaces are becoming the next generation controllers not only in the medical devices for disabled individuals but also in the gaming and entertainment industries. In order to build an effective Brain Computer Interface, which accurately translates the user thoughts into machine commands, it is important to have robust and fail proof signal processing and machine learning modules which operate on the raw EEG signals and estimate the current thought of the user.
In this thesis, several techniques used to perform EEG signal pre-processing, feature extraction and signal classification have been discussed, implemented, validated and verified; efficient supervised machine learning models, for the EEG motor imagery signal classification are identified. To further improve the performance of system unsupervised feature learning techniques have been investigated by pre-training the Deep Learning models. Use of pre-training stacked autoencoders have been proposed to solve the problems caused by random initialization of weights in neural networks.
Motor Imagery (imaginary hand and leg movements) signals are acquire using the Emotiv EEG headset. Different kinds of features like mean signal, band powers, RMS of the signal have been extracted and supplied to the machine learning (ML) stage, wherein, several ML techniques like LDA, KNN, SVM, Logistic regression and Neural Networks are applied and validated. During the validation phase the performances of various techniques are compared and some important observations are reported. Further, deep Learning techniques like autoencoding have been used to perform unsupervised feature learning. The reliability of the features is analyzed by performing classification by using the ML techniques mentioned earlier. The performance of the neural networks has been further improved by pre-training the network in an unsupervised fashion using stacked autoencoders and supplying the stacked autoencoders’ network parameters as initial parameters to the neural network. All the findings in this research, during each phase (pre-processing, feature extraction, classification) are directly relevant and can be used by the BCI research community for building motor imagery based BCI applications.
Additionally, this thesis attempts to develop, test, and compare the performance of an alternative method for classifying human driving behavior. This thesis proposes the use of driver affective states to know the driving behavior. The purpose of this part of the thesis was to classify the EEG data collected from several subjects while driving simulated vehicle and compare the classification results with those obtained by classifying the driving behavior using vehicle parameters collected simultaneously from all the subjects. The objective here is to see if the drivers’ mental state is reflected in his driving behavior.
In this thesis, several techniques used to perform EEG signal pre-processing, feature extraction and signal classification have been discussed, implemented, validated and verified; efficient supervised machine learning models, for the EEG motor imagery signal classification are identified. To further improve the performance of system unsupervised feature learning techniques have been investigated by pre-training the Deep Learning models. Use of pre-training stacked autoencoders have been proposed to solve the problems caused by random initialization of weights in neural networks.
Motor Imagery (imaginary hand and leg movements) signals are acquire using the Emotiv EEG headset. Different kinds of features like mean signal, band powers, RMS of the signal have been extracted and supplied to the machine learning (ML) stage, wherein, several ML techniques like LDA, KNN, SVM, Logistic regression and Neural Networks are applied and validated. During the validation phase the performances of various techniques are compared and some important observations are reported. Further, deep Learning techniques like autoencoding have been used to perform unsupervised feature learning. The reliability of the features is analyzed by performing classification by using the ML techniques mentioned earlier. The performance of the neural networks has been further improved by pre-training the network in an unsupervised fashion using stacked autoencoders and supplying the stacked autoencoders’ network parameters as initial parameters to the neural network. All the findings in this research, during each phase (pre-processing, feature extraction, classification) are directly relevant and can be used by the BCI research community for building motor imagery based BCI applications.
Additionally, this thesis attempts to develop, test, and compare the performance of an alternative method for classifying human driving behavior. This thesis proposes the use of driver affective states to know the driving behavior. The purpose of this part of the thesis was to classify the EEG data collected from several subjects while driving simulated vehicle and compare the classification results with those obtained by classifying the driving behavior using vehicle parameters collected simultaneously from all the subjects. The objective here is to see if the drivers’ mental state is reflected in his driving behavior.
ContributorsManchala, Vamsi Krishna (Author) / Redkar, Sangram (Thesis advisor) / Rogers, Bradley (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2015
Description
The sensor industry is a growing industry that has been predicted by Allied Market Research to be a multi-billion industry by 2022. One of the many key drives behind this rapid growth in the sensor industry is the increase incorporation of sensors into portable electrical devices. The value for sensor technologies are increased when the sensors are developed into innovative measuring system for application uses in the Aerospace, Defense, and Healthcare industries. While sensors are not new, their increased performance, size reduction, and decrease in cost has opened the door for innovative sensor combination for portable devices that could be worn or easily moved around. With this opportunity for further development of sensor use through concept engineering development, three concept projects for possible innovative portable devices was undertaken in this research. One project was the development of a pulse oximeter devise with fingerprint recognition. The second project was prototyping a portable Bluetooth strain gage monitoring system. The third project involved sensors being incorporated onto flexible printed circuit board (PCB) for improved comfort of wearable devices. All these systems were successfully tested in lab.
ContributorsNichols, Kevin William (Author) / Redkar, Sangram (Thesis advisor) / Rogers, Brad (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2018
Description
Recent research and study have showed the potential of auto-parametric system in controlling stability and parametric resonance. In this project, two different designs for auto-parametrically excited mass-spring-damper systems were studied. The theoretical models were developed to describe the behavior of the systems, and simulation models were constructed to validate the analytical results. The error between simulation and theoretical results was within 2%. Both theoretical and simulation results showed that the implementation of auto-parametric system could help reduce or amplify the resonance significantly.
ContributorsLe, Thao (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Rogers, Brad (Committee member) / Arizona State University (Publisher)
Created2018
Description
Concrete is relatively brittle, and its tensile strength is typically only about one-tenth of its compressive strength. Regular concrete is therefore normally uses reinforcement steel bars to increase the tensile strength. It is becoming increasingly popular to use random distributed fibers as reinforcement and polymeric fibers is once such kind. In the case of polymeric fibers, due to hydrophobicity and lack of any chemical bond between the fiber and matrix, the weak interface zone limits the ability of the fibers to effectively carry the load that is on the matrix phase. Depending on the fiber’s surface asperity, shape, chemical nature, and mechanical bond characteristic of the load transfer between matrix and fiber can be altered so that the final composite can be improved. These modifications can be carried out by means of thermal treatment, mechanical surface modifications, or chemical changes The objective of this study is to measure and document the effect of gamma ray irradiation on the mechanical properties of macro polymeric fibers. The objective is to determine the mechanical properties of macro-synthetic fibers and develop guidelines for treatment and characterization that allow for potential positive changes due to exposure to irradiation. Fibers are exposed to various levels of ionizing radiation and the tensile, interface and performance in a mortar matrix are documented. Uniaxial tensile tests were performed on irradiated fibers to study fiber strength and failure pattern. SEM tests were carried out in order to study the surface characteristic and effect of different radiation dose on polymeric fiber. The interaction of the irradiated fiber with the cement composite was studied by a series of quasi-static pullout test for a specific embedded length. As a final task, flexural tests were carried out for different irradiated fibers to sum up the investigation. An average increase of 13% in the stiffness of the fiber was observed for 5 kGy of radiation. Flexural tests showed an average increase of 181% in the Req3 value and 102 % in the toughness of the sample was observed for 5 kGy of dose.
ContributorsTiwari, Sanchay Sushil (Author) / Mobasher, Barzin (Thesis advisor) / Neithalath, Narayanan (Thesis advisor) / Dharmarajan, Subramaniam (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Phase change materials (PCMs) are combined sensible-and-latent thermal energy storage materials that can be used to store and dissipate energy in the form of heat. PCMs incorporated into wall-element systems have been well-studied with respect to energy efficiency of building envelopes. New applications of PCMs in infrastructural concrete, e.g., for mitigating early-age cracking and freeze-and-thaw induced damage, have also been proposed. Hence, the focus of this dissertation is to develop a detailed understanding of the physic-chemical and thermo-mechanical characteristics of cementitious systems and novel coating systems for wall-elements containing PCM. The initial phase of this work assesses the influence of interface properties and inter-inclusion interactions between microencapsulated PCM, macroencapsulated PCM, and the cementitious matrix. The fact that these inclusions within the composites are by themselves heterogeneous, and contain multiple components necessitate careful application of models to predict the thermal properties. The next phase observes the influence of PCM inclusions on the fracture and fatigue behavior of PCM-cementitious composites. The compliant nature of the inclusion creates less variability in the fatigue life for these composites subjected to cyclic loading. The incorporation of small amounts of PCM is found to slightly improve the fracture properties compared to PCM free cementitious composites. Inelastic deformations at the crack-tip in the direction of crack opening are influenced by the microscale PCM inclusions. After initial laboratory characterization of the microstructure and evaluation of the thermo-mechanical performance of these systems, field scale applicability and performance were evaluated. Wireless temperature and strain sensors for smart monitoring were embedded within a conventional portland cement concrete pavement (PCCP) and a thermal control smart concrete pavement (TCSCP) containing PCM. The TCSCP exhibited enhanced thermal performance over multiple heating and cooling cycles. PCCP showed significant shrinkage behavior as a result of compressive strains in the reinforcement that were twice that of the TCSCP. For building applications, novel PCM-composites coatings were developed to improve and extend the thermal efficiency. These coatings demonstrated a delay in temperature by up to four hours and were found to be more cost-effective than traditional building insulating materials.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
ContributorsAguayo, Matthew Joseph (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Underwood, Benjamin (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2018