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- All Subjects: engineering
- Genre: Doctoral Dissertation
- Creators: Liu, Yongming
- Member of: ASU Electronic Theses and Dissertations
Description
ABSTRACT Recent studies indicate that top-performing companies have higher-performing work environments than average companies. They receive higher scores for worker satisfaction with their overall physical work environment as well as higher effectiveness ratings for their workspaces (Gensler, 2008; Harter et al., 2003). While these studies indicate a relationship between effective office design and satisfaction they have not explored which specific space types may contribute to workers' overall satisfaction with their physical work environment. Therefore, the purpose of this study is to explore the relationship between workers' overall satisfaction with their physical work environments and their perception of the effectiveness of spaces designed for Conceptual Age work including learning, focusing, collaborating, and socializing tasks. This research is designed to identify which workspace types are related to workers' satisfaction with their overall work environment and which are perceived to be most and least effective. To accomplish this two primary and four secondary research questions were developed for this study. The first primary question considers overall workers' satisfaction with their overall physical work environments (offices, workstations, hallways, common areas, reception, waiting areas, etc.) related to the effective use of work mode workspaces (learning, focusing, collaborating, socializing). The second primary research question was developed to identify which of the four work mode space types had the greatest and least relationship to workers' satisfaction with the overall physical work environment. Secondary research questions were developed to address workers' perceptions of effectiveness of each space type. This research project used data from a previous study collected from 2007 to 2012. Responses were from all staff levels of US office-based office workers and resulted in a blind sample of approximately 48,000 respondents. The data for this study were developed from SPSS data reports that included descriptive data and Pearson correlations. Findings were developed from those statistics using coefficient of determination.
ContributorsHarmon-Vaughan, Elizabeth (Author) / Kroelinger, Michael D. (Thesis advisor) / Bernardi, Jose (Committee member) / Ozel, Filiz (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1, an introduction of this report is provided, in which a brief review is made about these three material systems. In Chapter 2, detailed discussion of the statistical morphological descriptors and a stochastic optimization approach for microstructure reconstruction is presented. In Chapter 3, the lattice particle method for micromechanical analysis of complex heterogeneous materials is introduced. In Chapter 4, a new class of hyperuniform heterogeneous material with superior mechanical properties is investigated. In Chapter 5, a bio-material system, i.e., cellularized collagen gel is modeled using correlation functions and stochastic reconstruction to study the collective dynamic behavior of the embed tumor cells. In chapter 6, LMPA soft robotic system is generated by generalizing the correlation functions and the rigidity tunability of this smart composite is discussed. In Chapter 7, a future work plan is presented.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Liu, Yongming (Committee member) / Wang, Qing Hua (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2018
Description
The 21st-century professional or knowledge worker spends much of the working day engaging others through electronic communication. The modes of communication available to knowledge workers have rapidly increased due to computerized technology advances: conference and video calls, instant messaging, e-mail, social media, podcasts, audio books, webinars, and much more. Professionals who think for a living express feelings of stress about their ability to respond and fear missing critical tasks or information as they attempt to wade through all the electronic communication that floods their inboxes. Although many electronic communication tools compete for the attention of the contemporary knowledge worker, most professionals use an electronic personal information management (PIM) system, more commonly known as an e-mail application and often the ubiquitous Microsoft Outlook program. The aim of this research was to provide knowledge workers with solutions to manage the influx of electronic communication that arrives daily by studying the workers in their working environment. This dissertation represents a quest to understand the current strategies knowledge workers use to manage their e-mail, and if modification of e-mail management strategies can have an impact on productivity and stress levels for these professionals. Today’s knowledge workers rarely work entirely alone, justifying the importance of also exploring methods to improve electronic communications within teams.
ContributorsCounts, Virginia (Author) / Parrish, Kristen (Thesis advisor) / Allenby, Braden (Thesis advisor) / Landis, Amy (Committee member) / Cooke, Nancy J. (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
Description
Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity resulted from the spatial discontinuity at the crack tip/front. The requirement of guiding criteria for various cracking behaviors, such as initiation, propagation, and branching, also poses some challenges. Comparing to the continuum based formulation, the discrete approaches, such as lattice spring method, discrete element method, and peridynamics, have certain advantages when modeling various fracture problems due to their intrinsic characteristics in modeling discontinuities.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
ContributorsChen, Hailong (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2015
Description
As the demand of sustainable construction materials increases, use of fibers and textiles as partial or full reinforcement in concrete members present a tremendous opportunity. Proper characterization techniques and design guides for hybrid materials are therefore needed. This dissertation presents a comprehensive study on serviceability-based design of strain softening and strain hardening materials. Multiple experimental procedures are developed to document the nature of single crack localization and multiple cracking mechanisms in various fiber and fabric reinforced cement-based composites. In addition, strain rate effects on the mechanical properties are examined using a high speed servo-hydraulic tension test equipment.
Significant hardening and degradation parameters such as stiffness, crack spacing, crack width, localized zone size are obtained from tensile tests using digital image correlation (DIC) technique. A tension stiffening model is used to simulate the tensile response that addresses the cracking and localization mechanisms. The model is also modified to simulate the sequential cracking in joint-free slabs on grade reinforced by steel fibers, where the lateral stiffness of slab and grade interface and stress-crack width response are the most important model parameters.
Parametric tensile and compressive material models are used to formulate generalized analytical solutions for flexural behaviors of hybrid reinforced concrete (HRC) that contains both rebars and fibers. Design recommendations on moment capacity, minimum reinforcement ratio etc. are obtained using analytical equations. The role of fiber in reducing the amount of conventional reinforcement is revealed. The approach is extended to T-sections and used to model Ultra High Performance Concrete (UHPC) beams and girders.
The analytical models are extended to structural members subjected to combined axial and bending actions. Analytical equations to address the P-M diagrams are derived. Closed-form equations that generate the interaction diagram of HRC section are presented which may be used in the design of multiple types of applications.
The theoretical models are verified by independent experimental results from literature. Reliability analysis using Monte Carlo simulation (MCS) is conducted for few design problems on ultimate state design. The proposed methodologies enable one to simulate the experiments to obtain material parameters and design structural members using generalized formulations.
Significant hardening and degradation parameters such as stiffness, crack spacing, crack width, localized zone size are obtained from tensile tests using digital image correlation (DIC) technique. A tension stiffening model is used to simulate the tensile response that addresses the cracking and localization mechanisms. The model is also modified to simulate the sequential cracking in joint-free slabs on grade reinforced by steel fibers, where the lateral stiffness of slab and grade interface and stress-crack width response are the most important model parameters.
Parametric tensile and compressive material models are used to formulate generalized analytical solutions for flexural behaviors of hybrid reinforced concrete (HRC) that contains both rebars and fibers. Design recommendations on moment capacity, minimum reinforcement ratio etc. are obtained using analytical equations. The role of fiber in reducing the amount of conventional reinforcement is revealed. The approach is extended to T-sections and used to model Ultra High Performance Concrete (UHPC) beams and girders.
The analytical models are extended to structural members subjected to combined axial and bending actions. Analytical equations to address the P-M diagrams are derived. Closed-form equations that generate the interaction diagram of HRC section are presented which may be used in the design of multiple types of applications.
The theoretical models are verified by independent experimental results from literature. Reliability analysis using Monte Carlo simulation (MCS) is conducted for few design problems on ultimate state design. The proposed methodologies enable one to simulate the experiments to obtain material parameters and design structural members using generalized formulations.
ContributorsYao, Yiming (Author) / Mobasher, Barzin (Thesis advisor) / Underwood, Benjamin (Committee member) / Neithalath, Narayanan (Committee member) / Rajan, Subramaniam D. (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2016
Description
The Very High Temperature Reactor (VHTR) is one of six conceptual designs proposed for Generation IV nuclear reactors. Alloy 617, a solid solution strengthened Ni-base superalloy, is currently the primary candidate material for the tubing of the Intermediate Heat Exchanger (IHX) in the VHTR design. Steady-state operation of the nuclear power plant at elevated temperatures leads to creep deformation, whereas loading transients including startup and shutdown generate fatigue. A detailed understanding of the creep-fatigue interaction in Alloy 617 is necessary before it can be considered as a material for nuclear construction in ASME Boiler and Pressure Vessel Code. Current design codes for components undergoing creep-fatigue interaction at elevated temperatures require creep-fatigue testing data covering the entire range from fatigue-dominant to creep-dominant loading. Classical strain-controlled tests, which produce stress relaxation during the hold period, show a saturation in cycle life with increasing hold periods due to the rapid stress-relaxation of Alloy 617 at high temperatures. Therefore, applying longer hold time in these tests cannot generate creep-dominated failure. In this study, uniaxial isothermal creep-fatigue tests with non-traditional loading waveforms were designed and performed at 850 and 950°C, with an objective of generating test data in the creep-dominant regime. The new loading waveforms are hybrid strain-controlled and force-controlled testing which avoid stress relaxation during the creep hold. The experimental data showed varying proportions of creep and fatigue damage, and provided evidence for the inadequacy of the widely-used time fraction rule for estimating creep damage under creep-fatigue conditions. Micro-scale damage features in failed test specimens, such as fatigue cracks and creep voids, were quantified using a Scanning Electron Microscope (SEM) to find a correlation between creep and fatigue damage. Quantitative statistical imaging analysis showed that the microstructural damage features (cracks and voids) are correlated with a new mechanical driving force parameter. The results from this image-based damage analysis were used to develop a phenomenological life-prediction methodology called the effective time fraction approach. Finally, the constitutive creep-fatigue response of the material at 950°C was modeled using a unified viscoplastic model coupled with a damage accumulation model. The simulation results were used to validate an energy-based constitutive life-prediction model, as a mechanistic model for potential component and structure level creep-fatigue analysis.
ContributorsTahir, Fraaz (Author) / Liu, Yongming (Thesis advisor) / Jiang, Hanqing (Committee member) / Rajagopalan, Jagannathan (Committee member) / Oswald, Jay (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2017
Description
Structural/system health monitoring (SHM) and prognostic health management (PHM) are vital techniques to ensure engineering system reliability and safety during the service. As multi-functionality and enhanced performance are in demand, modern engineering systems including aerospace, mechanical, and civil applications have become more complex. The constituent and architectural complexity, and multisource sensing sources in modern engineering systems may limit the monitoring capabilities of conventional approaches and require more advanced SHM/PHM techniques. Therefore, a hybrid methodology that incorporates information fusion, nondestructive evaluation (NDE), machine learning (ML), and statistical analysis is needed for more effective damage diagnosis/prognosis and system safety management.This dissertation presents an automated aviation health management technique to enable proactive safety management for both aircraft and national airspace system (NAS). A real-time, data-driven aircraft safety monitoring technique using ML models and statistical models is developed to enable an early-stage upset detection capability, which can improve pilot’s situational awareness and provide a sufficient safety margin. The detection accuracy and computational efficiency of the developed monitoring techniques is validated using commercial unlabeled flight data recorder (FDR) and reported accident FDR dataset. A stochastic post-upset prediction framework is developed using a high-fidelity flight dynamics model to predict the post-impacts in both aircraft and air traffic system. Stall upset scenarios that are most likely occurred during loss of control in-flight (LOC-I) operation are investigated, and stochastic flight envelopes and risk region are predicted to quantify their severities.
In addition, a robust, automatic damage diagnosis technique using ultrasonic Lamb waves and ML models is developed to effectively detect and classify fatigue damage modes in composite structures. The dispersion and propagation characteristics of the Lamb waves in a composite plate are investigated. A deep autoencoder-based diagnosis technique is proposed to detect fatigue damage using anomaly detection approach and automatically extract damage sensitive features from the waves. The patterns in the features are then further analyzed using outlier detection approach to classify the fatigue damage modes. The developed diagnosis technique is validated through an in-situ fatigue tests with periodic active sensing.
The developed techniques in this research are expected to be integrated with the existing safety strategies to enhance decision making process for improving engineering system safety without affecting the system’s functions.
ContributorsLee, Hyunseong (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Fard, Masoud Yekani (Committee member) / Tang, Pingbo (Committee member) / Campbell, Angela (Committee member) / Arizona State University (Publisher)
Created2021
Description
National Airspace Systems (NAS) are complex cyber-physical systems that require swift air traffic management (ATM) to ensure flight safety and efficiency. With the surging demand for air travel and the increasing intricacy of aviation systems, the need for advanced technologies to support air traffic management and air traffic control (ATC) service has become more crucial than ever. Data-driven models or artificial intelligence (AI) have been conceptually investigated by various parties and shown immense potential, especially when provided with a vast volume of real-world data. These data include traffic information, weather contours, operational reports, terrain information, flight procedures, and aviation regulations. Data-driven models learn from historical experiences and observations and provide expeditious recommendations and decision support for various operation tasks, directly contributing to the digital transformation in aviation. This dissertation reports several research studies covering different aspects of air traffic management and ATC service utilizing data-driven modeling, which are validated using real-world big data (flight tracks, flight events, convective weather, workload probes). These studies encompass a range of topics, including trajectory recommendations, weather studies, landing operations, and aviation human factors. Specifically, the topics explored are (i) trajectory recommendations under weather conditions, which examine the impact of convective weather on last on-file flight plans and provide calibrated trajectories based on convective weather; (ii) multi-aircraft trajectory predictions, which study the intention of multiple mid-air aircraft in the near-terminal airspace and provide trajectory predictions; (iii) flight scheduling operations, which involve probabilistic machine learning-enhanced optimization algorithms for robust and efficient aircraft landing sequencing; (iv) aviation human factors, which predict air traffic controller workload level from flight traffic data with conformalized graph neural network. The uncertainties associated with these studies are given special attention and addressed through Bayesian/probabilistic machine learning. Finally, discussions on high-level AI-enabled ATM research directions are provided, hoping to extend the proposed studies in the future. This dissertation demonstrates that data-driven modeling has great potential for aviation digital twins, revolutionizing the aviation decision-making process and enhancing the safety and efficiency of ATM. Moreover, these research directions are not merely add-ons to existing aviation practices but also contribute to the future of transportation, particularly in the development of autonomous systems.
ContributorsPang, Yutian (Author) / Liu, Yongming (Thesis advisor) / Yan, Hao (Committee member) / Zhuang, Houlong (Committee member) / Marvi, Hamid (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2023
Description
The design of energy absorbing structures is driven by application specific requirements like the amount of energy to be absorbed, maximum transmitted stress that is permissible, stroke length, and available enclosing space. Cellular structures like foams are commonly leveraged in nature for energy absorption and have also found use in engineering applications. With the possibility of manufacturing complex cellular shapes using additive manufacturing technologies, there is an opportunity to explore new topologies that improve energy absorption performance. This thesis aims to systematically understand the relationships between four key elements: (i) unit cell topology, (ii) material composition, (iii) relative density, and (iv) fields; and energy absorption behavior, and then leverage this understanding to develop, implement and validate a methodology to design the ideal cellular structure energy absorber. After a review of the literature in the domain of additively manufactured cellular materials for energy absorption, results from quasi-static compression of six cellular structures (hexagonal honeycomb, auxetic and Voronoi lattice, and diamond, Gyroid, and Schwarz-P) manufactured out of AlSi10Mg and Nylon-12. These cellular structures were compared to each other in the context of four design-relevant metrics to understand the influence of cell design on the deformation and failure behavior. Three new and revised metrics for energy absorption were proposed to enable more meaningful comparisons and subsequent design selection. Triply Periodic Minimal Surface (TPMS) structures were found to have the most promising overall performance and formed the basis for the numerical investigation of the effect of fields on the energy absorption performance of TPMS structures. A continuum shell-based methodology was developed to analyze the large deformation behavior of field-driven variable thickness TPMS structures and validated against experimental data. A range of analytical and stochastic fields were then evaluated that modified the TPMS structure, some of which were found to be effective in enhancing energy absorption behavior in the structures while retaining the same relative density. Combining findings from studies on the role of cell geometry, composition, relative density, and fields, this thesis concludes with the development of a design framework that can enable the formulation of cellular material energy absorbers with idealized behavior.
ContributorsShinde, Mandar (Author) / Bhate, Dhruv (Thesis advisor) / Peralta, Pedro (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023