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- All Subjects: Mechanical Engineering
- Creators: Jiang, Hanqing
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Description
This dissertation presents the development of structural health monitoring and prognostic health management methodologies for complex structures and systems in the field of mechanical engineering. To overcome various challenges historically associated with complex structures and systems such as complicated sensing mechanisms, noisy information, and large-size datasets, a hybrid monitoring framework comprising of solid mechanics concepts and data mining technologies is developed. In such a framework, the solid mechanics simulations provide additional intuitions to data mining techniques reducing the dependence of accuracy on the training set, while the data mining approaches fuse and interpret information from the targeted system enabling the capability for real-time monitoring with efficient computation.
In the case of structural health monitoring, ultrasonic guided waves are utilized for damage identification and localization in complex composite structures. Signal processing and data mining techniques are integrated into the damage localization framework, and the converted wave modes, which are induced by the thickness variation due to the presence of delamination, are used as damage indicators. This framework has been validated through experiments and has shown sufficient accuracy in locating delamination in X-COR sandwich composites without the need of baseline information. Besides the localization of internal damage, the Gaussian process machine learning technique is integrated with finite element method as an online-offline prediction model to predict crack propagation with overloads under biaxial loading conditions; such a probabilistic prognosis model, with limited number of training examples, has shown increased accuracy over state-of-the-art techniques in predicting crack retardation behaviors induced by overloads. In the case of system level management, a monitoring framework built using a multivariate Gaussian model as basis is developed to evaluate the anomalous condition of commercial aircrafts. This method has been validated using commercial airline data and has shown high sensitivity to variations in aircraft dynamics and pilot operations. Moreover, this framework was also tested on simulated aircraft faults and its feasibility for real-time monitoring was demonstrated with sufficient computation efficiency.
This research is expected to serve as a practical addition to the existing literature while possessing the potential to be adopted in realistic engineering applications.
In the case of structural health monitoring, ultrasonic guided waves are utilized for damage identification and localization in complex composite structures. Signal processing and data mining techniques are integrated into the damage localization framework, and the converted wave modes, which are induced by the thickness variation due to the presence of delamination, are used as damage indicators. This framework has been validated through experiments and has shown sufficient accuracy in locating delamination in X-COR sandwich composites without the need of baseline information. Besides the localization of internal damage, the Gaussian process machine learning technique is integrated with finite element method as an online-offline prediction model to predict crack propagation with overloads under biaxial loading conditions; such a probabilistic prognosis model, with limited number of training examples, has shown increased accuracy over state-of-the-art techniques in predicting crack retardation behaviors induced by overloads. In the case of system level management, a monitoring framework built using a multivariate Gaussian model as basis is developed to evaluate the anomalous condition of commercial aircrafts. This method has been validated using commercial airline data and has shown high sensitivity to variations in aircraft dynamics and pilot operations. Moreover, this framework was also tested on simulated aircraft faults and its feasibility for real-time monitoring was demonstrated with sufficient computation efficiency.
This research is expected to serve as a practical addition to the existing literature while possessing the potential to be adopted in realistic engineering applications.
ContributorsLi, Guoyi (Ph.D.) (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Yekani Fard, Masoud (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2019
Description
Hydrogel polymers have been the subject of many studies, due to their fascinating ability to alternate between being hydrophilic and hydrophobic, upon the application of appropriate stimuli. In particular, thermo-responsive hydrogels such as N-Isopropylacrylamide (NIPAM), which possess a unique lower critical solution temperature (LCST) of 32°C, have been leveraged for membrane-based processes such as using NIPAM as a draw agent for forward osmosis (FO) desalination. The low LCST temperature of NIPAM ensures that fresh water can be recovered, at a modest energy cost as compared to other thermally based desalination processes which require water recovery at higher temperatures. This work studies by experimentation, key process parameters involved in desalination by FO using NIPAM and a copolymer of NIPAM and Sodium Acrylate (NIPAM-SA). It encompasses synthesis of the hydrogels, development of experiments to effectively characterize synthesized products, and the measuring of FO performance for the individual hydrogels. FO performance was measured using single layers of NIPAM and NIPAM-SA respectively. The values of permeation flux obtained were compared to relevant published literature and it was found to be within reasonable range. Furthermore, a conceptual design for future large-scale implementation of this technology is proposed. It is proposed that perhaps more effort should focus on physical processes that have the ability to increase the low permeation flux of hydrogel driven FO desalination systems, rather than development of novel classes of hydrogels
ContributorsAbdullahi, Adnan None (Author) / Phelan, Patrick (Thesis advisor) / Wang, Robert (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2019
Description
A new critical plane-energy model is proposed in this thesis for multiaxial fatigue life prediction of homogeneous and heterogeneous materials. Brief review of existing methods, especially on the critical plane-based and energy-based methods, are given first. Special focus is on one critical plane approach which has been shown to work for both brittle and ductile metals. The key idea is to automatically change the critical plane orientation with respect to different materials and stress states. One potential drawback of the developed model is that it needs an empirical calibration parameter for non-proportional multiaxial loadings since only the strain terms are used and the out-of-phase hardening cannot be considered. The energy-based model using the critical plane concept is proposed with help of the Mroz-Garud hardening rule to explicitly include the effect of non-proportional hardening under fatigue cyclic loadings. Thus, the empirical calibration for non-proportional loading is not needed since the out-of-phase hardening is naturally included in the stress calculation. The model predictions are compared with experimental data from open literature and it is shown the proposed model can work for both proportional and non-proportional loadings without the empirical calibration. Next, the model is extended for the fatigue analysis of heterogeneous materials integrating with finite element method. Fatigue crack initiation of representative volume of heterogeneous materials is analyzed using the developed critical plane-energy model and special focus is on the microstructure effect on the multiaxial fatigue life predictions. Several conclusions and future work is drawn based on the proposed study.
ContributorsWei, Haoyang (Author) / Liu, Yongming (Thesis advisor) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2016
Description
Origami and kirigami, the technique of generating three-dimensional (3D) structures from two-dimensional (2D) flat sheets, are now more and more involved in scientific and engineering fields. Therefore, the development of tools for their theoretical analysis becomes more and more important. Since much effort was paid on calculations based on pure mathematical consideration and only limited effort has been paid to include mechanical properties, the goal of my research is developing a method to analyze the mechanical behavior of origami and kirigami based structures. Mechanical characteristics, including nonlocal effect and fracture of the structures, as well as elasticity and plasticity of materials are studied. For calculation of relative simple structures and building of structures’ constitutive relations, analytical approaches were used. For more complex structures, finite element analysis (FEA), which is commonly applied as a numerical method for the analysis of solid structures, was utilized. The general study approach is not necessarily related to characteristic size of model. I believe the scale-independent method described here will pave a new way to understand the mechanical response of a variety of origami and kirigami based structures under given mechanical loading.
ContributorsLv, Cheng (Author) / Jiang, Hanqing (Thesis advisor) / Yu, Hongbin (Committee member) / Wang, Liping (Committee member) / Mignolet, Marc (Committee member) / Hildreth, Owen (Committee member) / Arizona State University (Publisher)
Created2016
Description
Human walking has been a highly studied topic in research communities because of its extreme importance to human functionality and mobility. A complex system of interconnected gait mechanisms in humans is responsible for generating robust and consistent walking motion over unpredictable ground and through challenging obstacles. One interesting aspect of human gait is the ability to adjust in order to accommodate varying surface grades. Typical approaches to investigating this gait function focus on incline and decline surface angles, but most experiments fail to address the effects of surface grades that cause ankle inversion and eversion. There have been several studies of ankle angle perturbation over wider ranges of grade orientations in static conditions; however, these studies do not account for effects during the gait cycle. Furthermore, contemporary studies on this topic neglect critical sources of unnatural stimulus in the design of investigative technology. It is hypothesized that the investigation of ankle angle perturbations in the frontal plane, particularly in the context of inter-leg coordination mechanisms, results in a more complete characterization of the effects of surface grade on human gait mechanisms. This greater understanding could potentially lead to significant applications in gait rehabilitation, especially for individuals who suffer from impairment as a result of stroke. A wearable pneumatic device was designed to impose inversion and eversion perturbations on the ankle through simulated surface grade changes. This prototype device was fabricated, characterized, and tested in order to assess its effectiveness. After testing and characterizing this device, it was used in a series of experiments on human subjects while data was gathered on muscular activation and gait kinematics. The results of the characterization show success in imposing inversion and eversion angle perturbations of approximately 9° with a response time of 0.5 s. Preliminary experiments focusing on inter-leg coordination with healthy human subjects show that one-sided inversion and eversion perturbations have virtually no effect on gait kinematics. However, changes in muscular activation from one-sided perturbations show statistical significance in key lower limb muscles. Thus, the prototype device demonstrates novelty in the context of human gait research for potential applications in rehabilitation.
ContributorsBarkan, Andrew (Author) / Artemiadis, Panagiotis (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2016
Description
Improved knowledge connecting the chemistry, structure, and properties of polymers is necessary to develop advanced materials in a materials-by-design approach. Molecular dynamics (MD) simulations can provide tremendous insight into how the fine details of chemistry, molecular architecture, and microstructure affect many physical properties; however, they face well-known restrictions in their applicable temporal and spatial scales. These limitations have motivated the development of computationally-efficient, coarse-grained methods to investigate how microstructural details affect thermophysical properties. In this dissertation, I summarize my research work in structure-based coarse-graining methods to establish the link between molecular-scale structure and macroscopic properties of two different polymers. Systematically coarse-grained models were developed to study the viscoelastic stress response of polyurea, a copolymer that segregates into rigid and viscous phases, at time scales characteristic of blast and impact loading. With the application of appropriate scaling parameters, the coarse-grained models can predict viscoelastic properties with a speed up of 5-6 orders of magnitude relative to the atomistic MD models. Coarse-grained models of polyethylene were also created to investigate the thermomechanical material response under shock loading. As structure-based coarse-grained methods are generally not transferable to states different from which they were calibrated at, their applicability for modeling non-equilibrium processes such as shock and impact is highly limited. To address this problem, a new model is developed that incorporates many-body interactions and is calibrated across a range of different thermodynamic states using a least square minimization scheme. The new model is validated by comparing shock Hugoniot properties with atomistic and experimental data for polyethylene. Lastly, a high fidelity coarse-grained model of polyethylene was constructed that reproduces the joint-probability distributions of structural variables such as the distributions of bond lengths and bond angles between sequential coarse-grained sites along polymer chains. This new model accurately represents the structure of both the amorphous and crystal phases of polyethylene and enabling investigation of how polymer processing such as cold-drawing and bulk crystallization affect material structure at significantly larger time and length scales than traditional molecular simulations.
ContributorsAgrawal, Vipin (Author) / Oswald, Jay (Thesis advisor) / Peralta, Pedro (Committee member) / Chamberlin, Ralph (Committee member) / Solanki, Kiran (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2016
Description
There is a concerted effort in developing robust systems health monitoring/management (SHM) technology as a means to reduce the life cycle costs, improve availability, extend life and minimize downtime of various platforms including aerospace and civil infrastructure. The implementation of a robust SHM system requires a collaborative effort in a variety of areas such as sensor development, damage detection and localization, physics based models, and prognosis models for residual useful life (RUL) estimation. Damage localization and prediction is further complicated by geometric, material, loading, and environmental variabilities. Therefore, it is essential to develop robust SHM methodologies by taking into account such uncertainties. In this research, damage localization and RUL estimation of two different physical systems are addressed: (i) fatigue crack propagation in metallic materials under complex multiaxial loading and (ii) temporal scour prediction near bridge piers. With little modifications, the methodologies developed can be applied to other systems.
Current practice in fatigue life prediction is based on either physics based modeling or data-driven methods, and is limited to predicting RUL for simple geometries under uniaxial loading conditions. In this research, crack initiation and propagation behavior under uniaxial and complex biaxial fatigue loading is addressed. The crack propagation behavior is studied by performing extensive material characterization and fatigue testing under in-plane biaxial loading, both in-phase and out-of-phase, with different biaxiality ratios. A hybrid prognosis model, which combines machine learning with physics based modeling, is developed to account for the uncertainties in crack propagation and fatigue life prediction due to variabilities in material microstructural characteristics, crack localization information and environmental changes. The methodology iteratively combines localization information with hybrid prognosis models using sequential Bayesian techniques. The results show significant improvements in the localization and prediction accuracy under varying temperature.
For civil infrastructure, especially bridges, pier scour is a major failure mechanism. Currently available techniques are developed from a design perspective and provide highly conservative scour estimates. In this research, a fully probabilistic scour prediction methodology is developed using machine learning to accurately predict scour in real-time under varying flow conditions.
Current practice in fatigue life prediction is based on either physics based modeling or data-driven methods, and is limited to predicting RUL for simple geometries under uniaxial loading conditions. In this research, crack initiation and propagation behavior under uniaxial and complex biaxial fatigue loading is addressed. The crack propagation behavior is studied by performing extensive material characterization and fatigue testing under in-plane biaxial loading, both in-phase and out-of-phase, with different biaxiality ratios. A hybrid prognosis model, which combines machine learning with physics based modeling, is developed to account for the uncertainties in crack propagation and fatigue life prediction due to variabilities in material microstructural characteristics, crack localization information and environmental changes. The methodology iteratively combines localization information with hybrid prognosis models using sequential Bayesian techniques. The results show significant improvements in the localization and prediction accuracy under varying temperature.
For civil infrastructure, especially bridges, pier scour is a major failure mechanism. Currently available techniques are developed from a design perspective and provide highly conservative scour estimates. In this research, a fully probabilistic scour prediction methodology is developed using machine learning to accurately predict scour in real-time under varying flow conditions.
ContributorsNeerukatti, Rajesh Kumar (Author) / Chattopadhyay, Aditi (Thesis advisor) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2016
Description
Hydrogen embrittlement (HE) is a phenomenon that affects both the physical and chemical properties of several intrinsically ductile metals. Consequently, understanding the mechanisms behind HE has been of particular interest in both experimental and modeling research. Discrepancies between experimental observations and modeling results have led to various proposals for HE mechanisms. Therefore, to gain insights into HE mechanisms in iron, this dissertation aims to investigate several key issues involving HE such as: a) the incipient crack tip events; b) the cohesive strength of grain boundaries (GBs); c) the dislocation-GB interactions and d) the dislocation mobility.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
ContributorsAdlakha, Ilaksh (Author) / Solanki, Kiran (Thesis advisor) / Mignolet, Marc (Committee member) / Chawla, Nikhilesh (Committee member) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this research work, the process optimization of silver iodide-silver meta phosphate ionic glass molding for solid state super ionic stamping was performed. Solid state super ionic stamping is a process of all solid ambient condition electrochemical nano patterning technique. In solid state super ionic stamping, anodic dissolution on a solid electrolyte –metal interface and subsequent charge-mass transport in the solid electrolyte is used for obtaining nanometer features on the metallic surface. The solid electrolyte referred to as the stamp is pre-patterned with features to be obtained on the metallic surface. This research developed the process for obtaining stamp with specific dimensions by making use of compression molding. The compression molding process was optimized by varying the five process parameters-temperature, pressure, holding time, pressing time and cooling time. The objective of the process optimization was to obtain best geometrical features for the stamp including flatness and surface roughness and by optimizing the compression molding process, stamp with minimum flatness and surface roughness was obtained. After the experimental optimization of the process was completed, statistical analysis was performed to understand the relative significance of the process parameters and the interaction of the process parameters on the flatness and surface roughness values of the molded stamp. Structural characterization was performed to obtain the variation of average domain size of ionic glass particles within the molded glass disk by varying the process parameters of holding time, pressing time and cooling time.
ContributorsPanikkar, Gautam (Author) / Hsu, Keng H (Thesis advisor) / Chan, Candace (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2015
Description
Uranium Dioxide (UO2) is a significant nuclear fission fuel, which is widely used
in nuclear reactors. Understanding the influence of microstructure on thermo-mechanical behavior of UO2 is extremely important to predict its performance. In particular, evaluating mechanical properties, such as elasticity, plasticity and creep at sub-grain length scales is key to developing this understanding as well as building multi-scale models of fuel behavior with predicting capabilities. In this work, modeling techniques were developed to study effects of microstructure on Young’s modulus, which was selected as a key representative property that affects overall mechanical behavior, using experimental data obtained from micro-cantilever bending testing as benchmarks. Beam theory was firstly introduced to calculate Young's modulus of UO2 from the experimental data and then three-dimensional finite element models of the micro-cantilever beams were constructed to simulate bending tests in UO2 at room temperature. The influence of the pore distribution was studied to explain the discrepancy between predicted values and experimental results. Results indicate that results of tests are significantly affected by porosity given that both pore size and spacing in the samples are of the order of the micro-beam dimensions. Microstructure reconstruction was conducted with images collected from three-dimensional serial sectioning using focused ion beam (FIB) and electron backscattering diffraction (EBSD) and pore clusters were placed at different locations along the length of the beam. Results indicate that the presence of pore clusters close to the substrate, i.e., the clamp of the micro-cantilever beam, has the strongest effect on load-deflection behavior, leading to a reduction of stiffness that is the largest for any location of the pore cluster. Furthermore, it was also found from both numerical and i
analytical models that pore clusters located towards the middle of the span and close to the end of the beam only have a very small effect on the load-deflection behavior, and it is concluded that better estimates of Young's modulus can be obtained from micro- cantilever experiments by using microstructurally explicit models that account for porosity in about one half of the beam length close to the clamp. This, in turn, provides an avenue to simplify micro-scale experiments and their analysis.
in nuclear reactors. Understanding the influence of microstructure on thermo-mechanical behavior of UO2 is extremely important to predict its performance. In particular, evaluating mechanical properties, such as elasticity, plasticity and creep at sub-grain length scales is key to developing this understanding as well as building multi-scale models of fuel behavior with predicting capabilities. In this work, modeling techniques were developed to study effects of microstructure on Young’s modulus, which was selected as a key representative property that affects overall mechanical behavior, using experimental data obtained from micro-cantilever bending testing as benchmarks. Beam theory was firstly introduced to calculate Young's modulus of UO2 from the experimental data and then three-dimensional finite element models of the micro-cantilever beams were constructed to simulate bending tests in UO2 at room temperature. The influence of the pore distribution was studied to explain the discrepancy between predicted values and experimental results. Results indicate that results of tests are significantly affected by porosity given that both pore size and spacing in the samples are of the order of the micro-beam dimensions. Microstructure reconstruction was conducted with images collected from three-dimensional serial sectioning using focused ion beam (FIB) and electron backscattering diffraction (EBSD) and pore clusters were placed at different locations along the length of the beam. Results indicate that the presence of pore clusters close to the substrate, i.e., the clamp of the micro-cantilever beam, has the strongest effect on load-deflection behavior, leading to a reduction of stiffness that is the largest for any location of the pore cluster. Furthermore, it was also found from both numerical and i
analytical models that pore clusters located towards the middle of the span and close to the end of the beam only have a very small effect on the load-deflection behavior, and it is concluded that better estimates of Young's modulus can be obtained from micro- cantilever experiments by using microstructurally explicit models that account for porosity in about one half of the beam length close to the clamp. This, in turn, provides an avenue to simplify micro-scale experiments and their analysis.
ContributorsGong, Bowen (Author) / Peralta, Pedro (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2015