Matching Items (79)
Description
Lonsdaleite, also called hexagonal diamond, has been widely used as a marker of asteroidal impacts. It is thought to play a central role during the graphite-to-diamond transformation, and calculations suggest that it possesses mechanical properties superior to diamond. However, despite extensive efforts, lonsdaleite has never been produced or described as a separate, pure material. Here we show that defects in cubic diamond provide an explanation for the characteristic d-spacings and reflections reported for lonsdaleite. Ultrahigh-resolution electron microscope images demonstrate that samples displaying features attributed to lonsdaleite consist of cubic diamond dominated by extensive {113} twins and {111} stacking faults. These defects give rise to nanometre-scale structural complexity. Our findings question the existence of lonsdaleite and point to the need for re-evaluating the interpretations of many lonsdaleite-related fundamental and applied studies.
ContributorsNemeth, Peter (Author) / Garvie, Laurence (Author) / Aoki, Toshihiro (Author) / Dubrovinskaia, Natalia (Author) / Dubrovinsky, Leonid (Author) / Buseck, Peter (Author) / Department of Chemistry and Biochemistry (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Earth and Space Exploration (Contributor) / Center for Meteorite Studies (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / LeRoy Eyring Center for Solid State Science (Contributor) / School of Molecular Sciences (Contributor)
Created2014-11-01
Description
Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to better understand craft labor productivity as an aspect of lean construction, an activity analysis was conducted at the Arizona State University Palo Verde Main engineering dormitory construction site in December of 2016. The objective of this analysis on craft labor productivity in construction projects was to gather data regarding the efficiency of craft labor workers, make conclusions about the effects of time of day and other site-specific factors on labor productivity, as well as suggest improvements to implement in the construction process. Analysis suggests that supporting tasks, such as traveling or materials handling, constitute the majority of craft labors' efforts on the job site with the highest percentages occurring at the beginning and end of the work day. Direct work and delays were approximately equal at about 20% each hour with the highest peak occurring at lunchtime between 10:00 am and 11:00 am. The top suggestion to improve construction productivity would be to perform an extensive site utilization analysis due to the confined nature of this job site. Despite the limitations of an activity analysis to provide a complete prospective of all the factors that can affect craft labor productivity as well as the small number of days of data acquisition, this analysis provides a basic overview of the productivity at the Palo Verde Main construction site. Through this research, construction managers can more effectively generate site plans and schedules to increase labor productivity.
ContributorsFord, Emily Lucile (Author) / Grau, David (Thesis director) / Chong, Oswald (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The overall energy consumption around the United States has not been reduced even with the advancement of technology over the past decades. Deficiencies exist between design and actual energy performances. Energy Infrastructure Systems (EIS) are impacted when the amount of energy production cannot be accurately and efficiently forecasted. Inaccurate engineering assumptions can result when there is a lack of understanding on how energy systems can operate in real-world applications. Energy systems are complex, which results in unknown system behaviors, due to an unknown structural system model. Currently, there exists a lack of data mining techniques in reverse engineering, which are needed to develop efficient structural system models. In this project, a new type of reverse engineering algorithm has been applied to a year's worth of energy data collected from an ASU research building called MacroTechnology Works, to identify the structural system model. Developing and understanding structural system models is the first step in creating accurate predictive analytics for energy production. The associative network of the building's data will be highlighted to accurately depict the structural model. This structural model will enhance energy infrastructure systems' energy efficiency, reduce energy waste, and narrow the gaps between energy infrastructure design, planning, operation and management (DPOM).
ContributorsCamarena, Raquel Jimenez (Author) / Chong, Oswald (Thesis director) / Ye, Nong (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Building construction, design and maintenance is a sector of engineering where improved efficiency will have immense impacts on resource consumption and environmental health. This research closely examines the Leadership in Environment and Energy Design (LEED) rating system and the International Green Construction Code (IgCC). The IgCC is a model code, written with the same structure as many building codes. It is a standard that can be enforced if a city's government decides to adopt it. When IgCC is enforced, the buildings either meet all of the requirements set forth in the document or it fails to meet the code standards. The LEED Rating System, on the other hand, is not a building code. LEED certified buildings are built according to the standards of their local jurisdiction and in addition to that, building owners can chose to pursue a LEED certification. This is a rating system that awards points based on the sustainable measures achieved by a building. A comparison of these green building systems highlights their accomplishments in terms of reduced electricity usage, usage of low-impact materials, indoor environmental quality and other innovative features. It was determined that in general IgCC is more holistic, stringent approach to green building. At the same time the LEED rating system a wider variety of green building options. In addition, building data from LEED certified buildings was complied and analyzed to understand important trends. Both of these methods are progressing towards low-impact, efficient infrastructure and a side-by-side comparison, as done in this research, shed light on the strengths and weaknesses of each method, allowing for future improvements.
ContributorsCampbell, Kaleigh Ruth (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Many researchers aspire to create robotics systems that assist humans in common office tasks, especially by taking over delivery and messaging tasks. For meaningful interactions to take place, a mobile robot must be able to identify the humans it interacts with and communicate successfully with them. It must also be able to successfully navigate the office environment. While mobile robots are well suited for navigating and interacting with elements inside a deterministic office environment, attempting to interact with human beings in an office environment remains a challenge due to the limits on the amount of cost-efficient compute power onboard the robot. In this work, I propose the use of remote cloud services to offload intensive interaction tasks. I detail the interactions required in an office environment and discuss the challenges faced when implementing a human-robot interaction platform in a stochastic office environment. I also experiment with cloud services for facial recognition, speech recognition, and environment navigation and discuss my results. As part of my thesis, I have implemented a human-robot interaction system utilizing cloud APIs into a mobile robot, enabling it to navigate the office environment, identify humans within the environment, and communicate with these humans.
ContributorsDSouza, Daniel Anand (Author) / Kambhampati, Subbarao (Thesis director) / Zhang, Yu (Committee member) / Computer Science and Engineering Program (Contributor) / School of Computing, Informatics, and Decision Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
This paper describes the research done to quantify the relationship between external air temperature and energy consumption and internal air temperature and energy consumption. The study was conducted on a LEED Gold certified building, College Avenue Commons, located on Arizona State University's Tempe campus. It includes information on the background of previous studies in the area, some that agree with the research hypotheses and some that take a different path. Real-time data was collected hourly for energy consumption and external air temperature. Intermittent internal air temperature was collected by undergraduate researcher, Charles Banke. Regression analysis was used to prove two research hypotheses. The authors found no correlation between external air temperature and energy consumption, nor did they find a relationship between internal air temperature and energy consumption. This paper also includes recommendations for future work to improve the study.
ContributorsBanke, Charles Michael (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The Chinese Construction Industry has grown to be one of the largest construction markets in the world within the last 10 years. The size of the Chinese Construction Industry is on par with many developed nations, despite it being a developing country. Despite its rapid growth, the productivity and profitability of the Chinese Construction Industry is low compared to similar sized construction industries (United States, United Kingdom, etc.). In addition to the low efficiency of the Chinese Construction Industry, there is minimal documentation available showing the performance of the Chinese Construction Industry (projects completed on time, on budget, and customer satisfaction ratings).
The purpose of this research is to investigate potential solutions that could address the poor efficiency and performance of the Chinese Construction Industry. This research is divided into three phases; first, a literature review to identify countries that have similar construction industries to the Chinese Construction Industry. The second phase is to compare the risks and identify solutions that are proposed to increase the performance of similar construction industries and the Chinese Construction Industry. The third phase is to create a survey from the literature-based information to validate the concepts with the Chinese Construction Industry professionals and stakeholders.
The purpose of this research is to investigate potential solutions that could address the poor efficiency and performance of the Chinese Construction Industry. This research is divided into three phases; first, a literature review to identify countries that have similar construction industries to the Chinese Construction Industry. The second phase is to compare the risks and identify solutions that are proposed to increase the performance of similar construction industries and the Chinese Construction Industry. The third phase is to create a survey from the literature-based information to validate the concepts with the Chinese Construction Industry professionals and stakeholders.
ContributorsChen, Yutian (Author) / Chong, Oswald (Thesis advisor) / Kashiwagi, Dean T. (Committee member) / Badger, Willliam (Committee member) / Arizona State University (Publisher)
Created2020
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
Retinotopic map, the map between visual inputs on the retina and neuronal activation in brain visual areas, is one of the central topics in visual neuroscience. For human observers, the map is typically obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Biological evidences show the retinotopic mapping is topology-preserving/topological (i.e. keep the neighboring relationship after human brain process) within each visual region.
Unfortunately, due to limited spatial resolution and the signal-noise ratio of fMRI, state of art retinotopic map is not topological.
The topic was to model the topology-preserving condition mathematically, fix non-topological retinotopic map with numerical methods, and improve the quality of retinotopic maps.
The impose of topological condition, benefits several applications.
With the topological retinotopic maps, one may have a better insight on human retinotopic maps, including better cortical magnification factor quantification, more precise description of retinotopic maps, and potentially better exam ways of in Ophthalmology clinic.
ContributorsTu, Yanshuai (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Crook, Sharon (Committee member) / Yang, Yezhou (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2022
Description
Multiple robotic arms collaboration is to control multiple robotic arms to collaborate with each other to work on the same task. During the collaboration, theagent is required to avoid all possible collisions between each part of the robotic arms.
Thus, incentivizing collaboration and preventing collisions are the two principles which
are followed by the agent during the training process. Nowadays, more and more
applications, both in industry and daily lives, require at least two arms, instead of
requiring only a single arm. A dual-arm robot satisfies much more needs of different
types of tasks, such as folding clothes at home, making a hamburger in a grill or
picking and placing a product in a warehouse.
The applications done in this paper are all about object pushing. This thesis
focuses on how to train the agent to learn pushing an object away as far as possible.
Reinforcement Learning (RL), which is a type of Machine Learning (ML), is then
utilized in this paper to train the agent to generate optimal actions. Deep Deterministic
Policy Gradient (DDPG) and Hindsight Experience Replay (HER) are the two RL
methods used in this thesis.
ContributorsLin, Steve (Author) / Ben Amor, Hani (Thesis advisor) / Redkar, Sangram (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2023