Matching Items (190)
Description
Calcium hydroxide carbonation processes were studied to investigate the potential for abiotic soil improvement. Different mixtures of common soil constituents such as sand, clay, and granite were mixed with a calcium hydroxide slurry and carbonated at approximately 860 psi. While the carbonation was successful and calcite formation was strong on sample exteriors, a 4 mm passivating boundary layer effect was observed, impeding the carbonation process at the center. XRD analysis was used to characterize the extent of carbonation, indicating extremely poor carbonation and therefore CO2 penetration inside the visible boundary. The depth of the passivating layer was found to be independent of both time and choice of aggregate. Less than adequate strength was developed in carbonated trials due to formation of small, weakly-connected crystals, shown with SEM analysis. Additional research, especially in situ analysis with thermogravimetric analysis would be useful to determine the causation of poor carbonation performance. This technology has great potential to substitute for certain Portland cement applications if these issues can be addressed.
ContributorsHermens, Stephen Edward (Author) / Bearat, Hamdallah (Thesis director) / Dai, Lenore (Committee member) / Mobasher, Barzin (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor)
Created2015-05
Description
As green buildings become more popular, the challenge of structural engineer is to move beyond simply green to develop sustainable, and high-performing buildings that are more than just environmentally friendly. For decades, Portland cement-based products have been known as the most commonly used construction materials in the world, and as a result, cement production is a significant source of global carbon dioxide (CO2) emissions, and environmental impacts at all stages of the process. In recent years, the increasing cost of energy and resource supplies, and concerns related to greenhouse gas emissions and environmental impacts have ignited more interests in utilizing waste and by-product materials as the primary ingredient to replace ordinary Portland cement in concrete systems. The environmental benefits of cement replacement are enormous, including the diversion of non-recycled waste from landfills for useful applications, the reduction in non-renewable energy consumption for cement production, and the corresponding emission of greenhouse gases. In the vast available body of literature, concretes consisting activated fly ash or slag as the binder have been shown to have high compressive strengths, and resistance to fire and chemical attack. This research focuses to utilize fly ash, by-product of coal fired power plant along with different alkaline solutions to form a final product with comparable properties to or superior than those of ordinary Portland cement concrete. Fly ash mortars using different concentration of sodium hydroxide and waterglass were dry and moist cured at different temperatures prior subjecting to uniaxial compressive loading condition. Since moist curing continuously supplies water for the hydration process of activated fly ash mortars while preventing thermal shrinkage and cracking, the samples were more durable and demonstrated a noticeably higher compressive strength. The influence of the concentration of the activating agent (4, or 8 M sodium hydroxide solution), and activator-to-binder ratio of 0.40 on the compressive strengths of concretes containing Class F fly ash as the sole binder is analyzed. Furthermore, liquid sodium silicate (waterglass) with silica modulus of 1.0 and 2.0 along with activator-to-binder ratio of 0.04 and 0.07 was also studied to understand its performance in contributing to the strength development of the activated fly ash concrete. Statistical analysis of the compressive strength results show that the available alkali concentration has a larger influence on the compressive strengths of activated concretes made using fly ash than the influence of curing parameters (elevated temperatures, condition, and duration).
ContributorsBanh, Kingsten Chi (Author) / Neithalath, Narayanan (Thesis director) / Rajan, Subramaniam (Committee member) / Mobasher, Barzin (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
Peer-to-peer systems are known to be vulnerable to the Sybil attack. The lack of a central authority allows a malicious user to create many fake identities (called Sybil nodes) pretending to be independent honest nodes. The goal of the malicious user is to influence the system on his/her behalf. In order to detect the Sybil nodes and prevent the attack, a reputation system is used for the nodes, built through observing its interactions with its peers. The construction makes every node a part of a distributed authority that keeps records on the reputation and behavior of the nodes. Records of interactions between nodes are broadcast by the interacting nodes and honest reporting proves to be a Nash Equilibrium for correct (non-Sybil) nodes. In this research is argued that in realistic communication schedule scenarios, simple graph-theoretic queries such as the computation of Strongly Connected Components and Densest Subgraphs, help in exposing those nodes most likely to be Sybil, which are then proved to be Sybil or not through a direct test executed by some peers.
ContributorsCárdenas-Haro, José Antonio (Author) / Konjevod, Goran (Thesis advisor) / Richa, Andréa W. (Thesis advisor) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2010
Description
Concrete stands at the forefront of the construction industry as one of the most useful building materials. Economic and efficient improvements in concrete strengthening and manufacturing are widely sought to continuously improve the performance of the material. Fiber reinforcement is a significant technique in strengthening precast concrete, but manufacturing limitations are common which has led to reliance on steel reinforcement. Two-dimensional textile reinforcement has emerged as a strong and efficient alternative to both fiber and steel reinforced concrete with pultrusion manufacturing shown as one of the most effective methods of precasting concrete. The intention of this thesis project is to detail the components, functions, and outcomes shown in the development of an automated pultrusion system for manufacturing textile reinforced concrete (TRC). Using a preexisting, manual pultrusion system and current-day manufacturing techniques as a basis, the automated pultrusion system was designed as a series of five stations that centered on textile impregnation, system driving, and final pressing. The system was then constructed in the Arizona State University Structures Lab over the course of the spring and summer of 2015. After fabricating each station, a computer VI was coded in LabVIEW software to automatically drive the system. Upon completing construction of the system, plate and angled structural sections were then manufactured to verify the adequacy of the technique. Pultruded TRC plates were tested in tension and flexure while full-scale structural sections were tested in tension and compression. Ultimately, the automated pultrusion system was successful in establishing an efficient and consistent manufacturing process for continuous TRC sections.
ContributorsBauchmoyer, Jacob Macgregor (Author) / Mobasher, Barzin (Thesis director) / Neithalath, Narayanan (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / The Design School (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this model has focused on shape formation and other spatial configuration problems, including line formation, compression, and coating. In this work we study foundational computational tasks that exceed the capabilities of the individual constant memory particles described by the model. These tasks represent new ways to use these self-organizing systems, which, in conjunction with previous shape and configuration work, make the systems useful for a wider variety of tasks. We present an implementation of a counter using a line of particles, which makes it possible for the line of particles to count to and store values much larger than their individual capacities. We then present an algorithm that takes a matrix and a vector as input and then sets up and uses a rectangular block of particles to compute the matrix-vector multiplication. This setup also utilizes the counter implementation to store the resulting vector from the matrix-vector multiplication. Operations such as counting and matrix multiplication can leverage the distributed and dynamic nature of the self-organizing system to be more efficient and adaptable than on traditional linear computing hardware. Such computational tools also give the systems more power to make complex decisions when adapting to new situations or to analyze the data they collect, reducing reliance on a central controller for setup and output processing. Finally, we demonstrate an application of similar types of computations with self-organizing systems to image processing, with an implementation of an image edge detection algorithm.
ContributorsPorter, Alexandra Marie (Author) / Richa, Andrea (Thesis director) / Xue, Guoliang (Committee member) / School of Music (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Manufacture of building materials requires significant energy, and as demand for these materials continues to increase, the energy requirement will as well. Offsetting this energy use will require increased focus on sustainable building materials. Further, the energy used in building, particularly in heating and air conditioning, accounts for 40 percent of a buildings energy use. Increasing the efficiency of building materials will reduce energy usage over the life time of the building. Current methods for maintaining the interior environment can be highly inefficient depending on the building materials selected. Materials such as concrete have low thermal efficiency and have a low heat capacity meaning it provides little insulation. Use of phase change materials (PCM) provides the opportunity to increase environmental efficiency of buildings by using the inherent latent heat storage as well as the increased heat capacity. Incorporating PCM into concrete via lightweight aggregates (LWA) by direct addition is seen as a viable option for increasing the thermal storage capabilities of concrete, thereby increasing building energy efficiency. As PCM change phase from solid to liquid, heat is absorbed from the surroundings, decreasing the demand on the air conditioning systems on a hot day or vice versa on a cold day. Further these materials provide an additional insulating capacity above the value of plain concrete. When the temperature drops outside the PCM turns back into a solid and releases the energy stored from the day. PCM is a hydrophobic material and causes reductions in compressive strength when incorporated directly into concrete, as shown in previous studies. A proposed method for mitigating this detrimental effect, while still incorporating PCM into concrete is to encapsulate the PCM in aggregate. This technique would, in theory, allow for the use of phase change materials directly in concrete, increasing the thermal efficiency of buildings, while negating the negative effect on compressive strength of the material.
ContributorsSharma, Breeann (Author) / Neithalath, Narayanan (Thesis advisor) / Mobasher, Barzin (Committee member) / Rajan, Subramaniam D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation considers the question of how convenient access to copious networked observational data impacts our ability to learn causal knowledge. It investigates in what ways learning causality from such data is different from -- or the same as -- the traditional causal inference which often deals with small scale i.i.d. data collected from randomized controlled trials? For example, how can we exploit network information for a series of tasks in the area of learning causality? To answer this question, the dissertation is written toward developing a suite of novel causal learning algorithms that offer actionable insights for a series of causal inference tasks with networked observational data. The work aims to benefit real-world decision-making across a variety of highly influential applications. In the first part of this dissertation, it investigates the task of inferring individual-level causal effects from networked observational data. First, it presents a representation balancing-based framework for handling the influence of hidden confounders to achieve accurate estimates of causal effects. Second, it extends the framework with an adversarial learning approach to properly combine two types of existing heuristics: representation balancing and treatment prediction. The second part of the dissertation describes a framework for counterfactual evaluation of treatment assignment policies with networked observational data. A novel framework that captures patterns of hidden confounders is developed to provide more informative input for downstream counterfactual evaluation methods. The third part presents a framework for debiasing two-dimensional grid-based e-commerce search with observational search log data where there is an implicit network connecting neighboring products in a search result page. A novel inverse propensity scoring framework that models user behavior patterns for two-dimensional display in e-commerce websites is developed, which aims to optimize online performance of ranking algorithms with offline log data.
ContributorsGuo, Ruocheng (Author) / Liu, Huan (Thesis advisor) / Candan, K. Selcuk (Committee member) / Xue, Guoliang (Committee member) / Kiciman, Emre (Committee member) / Arizona State University (Publisher)
Created2021
Description本文对中国制药企业并购溢价影响因素进行了研究，提出了对制药企业并购非常重要的两个新的影响因素：可生产药品批文和在研新药批文。本文以2011年1月—2019年12月间我国制药行业上市公司并购事件为样本，对在研新药和可生产药品批文的价值从四个维度度量：是否有在研新药和可生产药品批文；在研新药数量及可生产药品批文数量；根据创新药和仿制药两个类别进行细分；标的企业所拥有的在研新药和可生产药品批文的市场价值。论文发现药品批文对企业并购溢价的影响不是很显著。进一步的，本文探究了药品批文对主并企业的对被并购公司的估值的影响。实证结果表明，我国制药企业在并购估值时确实会考虑到在研新药和可生产药品批文的价值。本文还发现对于可生产药品来说，相对创新药，被并购公司持有的仿制药批文影响更显著。而对于在研新药来说，主并企业更看重在研的创新药，在研仿制药对并购估值的影响不大。最后，本文选取了两个代表性案例进一步分析和探讨药品批文对企业并购的影响。
ContributorsYe, Tao (Author) / Shen, Wei (Thesis advisor) / Chang, Chun (Thesis advisor) / Jiang, Zhan (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Recent advances in cyber-physical systems, artificial intelligence, and cloud computing have driven the widespread deployment of Internet-of-Things (IoT) devices in smart homes. However, the spate of cyber attacks exploiting the vulnerabilities and weak security management of smart home IoT devices have highlighted the urgency and challenges of designing efficient mechanisms for detecting, analyzing, and mitigating security threats towards them. In this dissertation, I seek to address the security and privacy issues of smart home IoT devices from the perspectives of traffic measurement, pattern recognition, and security applications. I first propose an efficient multidimensional smart home network traffic measurement framework, which enables me to deeply understand the smart home IoT ecosystem and detect various vulnerabilities and flaws. I further design intelligent schemes to efficiently extract security-related IoT device event and user activity patterns from the encrypted smart home network traffic. Based on the knowledge of how smart home operates, different systems for securing smart home networks are proposed and implemented, including abnormal network traffic detection across multiple IoT networking protocol layers, smart home safety monitoring with extracted spatial information about IoT device events, and system-level IoT vulnerability analysis and network hardening.
ContributorsWan, Yinxin (Author) / Xue, Guoliang (Thesis advisor) / Xu, Kuai (Thesis advisor) / Yang, Yezhou (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2023
Description
The problem of monitoring complex networks for the detection of anomalous behavior is well known. Sensors are usually deployed for the purpose of monitoring these networks for anomalies and Sensor Placement Optimization (SPO) is the problem of determining where these sensors should be placed (deployed) in the network. Prior works have utilized the well known Set Cover formulation in order to determine the locations where sensors should be placed in the network, so that anomalies can be effectively detected. However, such works cannot be utilized to address the problem when the objective is to not only detect the presence of anomalies, but also to detect (distinguish) the source(s) of the detected anomalies, i.e., uniquely monitoring the network. In this dissertation, I attempt to fill in this gap by utilizing the mathematical concept of Identifying Codes and illustrating how it not only can overcome the aforementioned limitation, but also it, and its variants, can be utilized to monitor complex networks modeled from multiple domains. Over the course of this dissertation, I make key contributions which further enhance the efficacy and applicability of Identifying Codes as a monitoring strategy. First, I show how Identifying Codes are superior to not only the Set Cover formulation but also standard graph centrality metrics, for the purpose of uniquely monitoring complex networks. Second, I study novel problems such as the budget constrained Identifying Code, scalable Identifying Code, robust Identifying Code etc., and present algorithms and results for the respective problems. Third, I present useful Identifying Code results for restricted graph classes such as Unit Interval Bigraphs and Unit Disc Bigraphs. Finally, I show the universality of Identifying Codes by applying it to multiple domains.
ContributorsBasu, Kaustav (Author) / Sen, Arunabha (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2022