Matching Items (106)
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- All Subjects: Mechanical Engineering
- Creators: Jiang, Hanqing
- Creators: Rykaczewski, Konrad
- Member of: Theses and Dissertations
Description
In this research, a new cutting edge wear estimator for micro-endmilling is developed and the reliabillity of the estimator is evaluated. The main concept of this estimator is the minimum chip thickness effect. This estimator predicts the cutting edge radius by detecting the drop in the chip production rate as the cutting edge of a micro- endmill slips over the workpiece when the minimum chip thickness becomes larger than the uncut chip thickness, thus transitioning from the shearing to the ploughing dominant regime. The chip production rate is investigated through simulation and experiment. The simulation and the experiment show that the chip production rate decreases when the minimum chip thickness becomes larger than the uncut chip thickness. Also, the reliability of this estimator is evaluated. The probability of correct estimation of the cutting edge radius is more than 80%. This cutting edge wear estimator could be applied to an online tool wear estimation system. Then, a large number of cutting edge wear data could be obtained. From the data, a cutting edge wear model could be developed in terms of the machine control parameters so that the optimum control parameters could be applied to increase the tool life and the machining quality as well by minimizing the cutting edge wear rate.
In addition, in order to find the stable condition of the machining, the stabillity lobe of the system is created by measuring the dynamic parameters. This process is needed prior to the cutting edge wear estimation since the chatter would affect the cutting edge wear and the chip production rate. In this research, a new experimental set-up for measuring the dynamic parameters is developed by using a high speed camera with microscope lens and a loadcell. The loadcell is used to measure the stiffness of the tool-holder assembly of the machine and the high speed camera is used to measure the natural frequency and the damping ratio. From the measured data, a stability lobe is created. Even though this new method needs further research, it could be more cost-effective than the conventional methods in the future.
In addition, in order to find the stable condition of the machining, the stabillity lobe of the system is created by measuring the dynamic parameters. This process is needed prior to the cutting edge wear estimation since the chatter would affect the cutting edge wear and the chip production rate. In this research, a new experimental set-up for measuring the dynamic parameters is developed by using a high speed camera with microscope lens and a loadcell. The loadcell is used to measure the stiffness of the tool-holder assembly of the machine and the high speed camera is used to measure the natural frequency and the damping ratio. From the measured data, a stability lobe is created. Even though this new method needs further research, it could be more cost-effective than the conventional methods in the future.
ContributorsLee, Jue-Hyun (Author) / SODEMANN, ANGELA A (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Hsu, Keng (Committee member) / Artemiadis, Panagiotis (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2019
Description
Polymer fibers have broad applications in wearable electronics, bulletproof vests, batteries, fuel cells, filters, electrodes, conductive wires, and biomedical materials. Polymer fibers display light density and flexibility but are mostly weak and compliant. The ceramic, metallic, and carbon nanoparticles have been frequently included in polymers for fabricating continuous, durable, and functional composite fibers. Nanoparticles display large specific areas, low defect density and can transfer their superior properties to polymer matrices. The main focus of this thesis is to design, fabricate and characterize the polymer
anocarbon composite fibers with unique microstructures and improved mechanical/thermal performance. The dispersions and morphologies of graphene nanoplatelets (GNPs), the interactions with polyvinyl alcohol (PVA) molecules and their influences on fiber properties are studied. The fibers were fabricated using a dry-jet wet spinning method with engineered spinneret design. Three different structured fibers were fabricated, namely, one-phase polymer fiber (1-phase), two-phase core-shell composite fiber (2-phase), and three-phase co-axial composite fiber (3-phase). These polymer or composite fibers were processed at three stages with drawing temperatures of 100˚C, 150˚C, and 200˚C. Different techniques including the mechanical tester, wide-angle X-Ray diffraction (WAXD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC) have been used to characterize the fiber microstructures and properties.
anocarbon composite fibers with unique microstructures and improved mechanical/thermal performance. The dispersions and morphologies of graphene nanoplatelets (GNPs), the interactions with polyvinyl alcohol (PVA) molecules and their influences on fiber properties are studied. The fibers were fabricated using a dry-jet wet spinning method with engineered spinneret design. Three different structured fibers were fabricated, namely, one-phase polymer fiber (1-phase), two-phase core-shell composite fiber (2-phase), and three-phase co-axial composite fiber (3-phase). These polymer or composite fibers were processed at three stages with drawing temperatures of 100˚C, 150˚C, and 200˚C. Different techniques including the mechanical tester, wide-angle X-Ray diffraction (WAXD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC) have been used to characterize the fiber microstructures and properties.
ContributorsVerma, Rahul (Author) / Song, Kenan (Thesis advisor) / Jiang, Hanqing (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Soft polymer composites with improved thermal conductivity are needed for the thermal management of electronics. Interfacial thermal boundary resistance, however, prevents the efficient use of many high thermal conductivity fill materials. Magnetic alignment of ferrous fill material enforces percolation of the high thermal conductivity fill, thereby shifting the governing boundary resistance to the particle- particle interfaces and increasing the directional thermal conductivity of the polymer composite. Magnetic alignment maximizes the thermal conductivity while minimizing composite stiffening at a fill fraction of half the maximum packing factor. The directional thermal conductivity of the composite is improved by more than 2-fold. Particle-particle contact engineering is then introduced to decrease the particle- particle boundary resistance and further improve the thermal conductivity of the composite.
The interface between rigid fill particles is a point contact with very little interfacial area connecting them. Silver and gallium-based liquid metal (LM) coatings provide soft interfaces that, under pressure, increase the interfacial area between particles and decrease the particle-particle boundary resistance. These engineered contacts are investigated both in and out of the polymer matrix and with and without magnetic alignment of the fill. Magnetically aligned in the polymer matrix, 350nm- thick silver coatings on nickel particles produce a 1.8-fold increase in composite thermal conductivity over the aligned bare-nickel composites. The LM coatings provide similar enhancements, but require higher volumes of LM to do so. This is due to the rapid formation of gallium oxide, which introduces additional thermal boundaries and decreases the benefit of the LM coatings.
The oxide shell of LM droplets (LMDs) can be ruptured using pressure. The pressure needed to rupture LMDs matches closely to thin-walled pressure vessel theory. Furthermore, the addition of tungsten particles stabilizes the mixture for use at higher pressures. Finally, thiols and hydrochloric acid weaken the oxide shell and boost the thermal performance of the beds of LMDs by 50% at pressures much lower than 1 megapascal (MPa) to make them more suitable for use in TIMs.
The interface between rigid fill particles is a point contact with very little interfacial area connecting them. Silver and gallium-based liquid metal (LM) coatings provide soft interfaces that, under pressure, increase the interfacial area between particles and decrease the particle-particle boundary resistance. These engineered contacts are investigated both in and out of the polymer matrix and with and without magnetic alignment of the fill. Magnetically aligned in the polymer matrix, 350nm- thick silver coatings on nickel particles produce a 1.8-fold increase in composite thermal conductivity over the aligned bare-nickel composites. The LM coatings provide similar enhancements, but require higher volumes of LM to do so. This is due to the rapid formation of gallium oxide, which introduces additional thermal boundaries and decreases the benefit of the LM coatings.
The oxide shell of LM droplets (LMDs) can be ruptured using pressure. The pressure needed to rupture LMDs matches closely to thin-walled pressure vessel theory. Furthermore, the addition of tungsten particles stabilizes the mixture for use at higher pressures. Finally, thiols and hydrochloric acid weaken the oxide shell and boost the thermal performance of the beds of LMDs by 50% at pressures much lower than 1 megapascal (MPa) to make them more suitable for use in TIMs.
ContributorsRalphs, Matthew (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert Y (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Liping (Committee member) / Devasenathipathy, Shankar (Committee member) / Arizona State University (Publisher)
Created2019
Description
Toward the ambitious long-term goal of developing a robotic circus, this thesis addresses key steps toward the development of a ground robot that can catch a ball. Toward this end, we examine nonlinear quadratic drag trajectories for a tossed ball. Relevant least square error fits are provided. It is also shown how a Kalman filter and Extended Kalman filter can be used to generate estimates for the ball trajectory.
Several simple ball intercept policies are examined. This includes open loop and closed loop policies. It is also shown how a low-cost differential-drive research grade robot can be built, modeled and controlled. Directions for developing more complex xy planar intercept policies are also briefly discussed. In short, the thesis establishes a foundation for future work on developing a practical ball catching robot.
Several simple ball intercept policies are examined. This includes open loop and closed loop policies. It is also shown how a low-cost differential-drive research grade robot can be built, modeled and controlled. Directions for developing more complex xy planar intercept policies are also briefly discussed. In short, the thesis establishes a foundation for future work on developing a practical ball catching robot.
ContributorsDAS, NIRANGKUSH (Author) / Rodriguez, Armando A (Thesis advisor) / Berman, Spring M (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2018
Description
This investigation focuses on the development of uncertainty modeling methods applicable to both the structural and thermal models of heated structures as part of an effort to enable the design under uncertainty of hypersonic vehicles. The maximum entropy-based nonparametric stochastic modeling approach is used within the context of coupled structural-thermal Reduced Order Models (ROMs). Not only does this strategy allow for a computationally efficient generation of samples of the structural and thermal responses but the maximum entropy approach allows to introduce both aleatoric and some epistemic uncertainty into the system.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
ContributorsSong, Pengchao (Author) / Mignolet, Marc P (Thesis advisor) / Smarslok, Benjamin (Committee member) / Chattopadhyay, Aditi (Committee member) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
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
The advancements in additive manufacturing have made it possible to bring life to designs
that would otherwise exist only on paper. An excellent example of such designs
are the Triply Periodic Minimal Surface (TPMS) structures like Schwarz D, Schwarz
P, Gyroid, etc. These structures are self-sustaining, i.e. they require minimal supports
or no supports at all when 3D printed. These structures exist in stable form in
nature, like butterfly wings are made of Gyroids. Automotive and aerospace industry
have a growing demand for strong and light structures, which can be solved using
TPMS models. In this research we will try and understand some of the properties of
these Triply Periodic Minimal Surface (TPMS) structures and see how they perform
in comparison to the conventional models. The research was concentrated on the
mechanical, thermal and fluid flow properties of the Schwarz D, Gyroid and Spherical
Gyroid Triply Periodic Minimal Surface (TPMS) models in particular, other Triply
Periodic Minimal Surface (TPMS) models were not considered. A detailed finite
element analysis was performed on the mechanical and thermal properties using ANSYS
19.2 and the flow properties were analyzed using ANSYS Fluent under different
conditions.
that would otherwise exist only on paper. An excellent example of such designs
are the Triply Periodic Minimal Surface (TPMS) structures like Schwarz D, Schwarz
P, Gyroid, etc. These structures are self-sustaining, i.e. they require minimal supports
or no supports at all when 3D printed. These structures exist in stable form in
nature, like butterfly wings are made of Gyroids. Automotive and aerospace industry
have a growing demand for strong and light structures, which can be solved using
TPMS models. In this research we will try and understand some of the properties of
these Triply Periodic Minimal Surface (TPMS) structures and see how they perform
in comparison to the conventional models. The research was concentrated on the
mechanical, thermal and fluid flow properties of the Schwarz D, Gyroid and Spherical
Gyroid Triply Periodic Minimal Surface (TPMS) models in particular, other Triply
Periodic Minimal Surface (TPMS) models were not considered. A detailed finite
element analysis was performed on the mechanical and thermal properties using ANSYS
19.2 and the flow properties were analyzed using ANSYS Fluent under different
conditions.
ContributorsRaja, Faisal (Author) / Phelan, Patrick (Thesis advisor) / Bhate, Dhruv (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2019
Description
“Smart” materials are used for a broad range of application including electronics, bio-medical devices, and smart clothing. This work focuses on development of smart self-sealing and breathable protective gear for soldiers against Chemical Weapon Agents (CWA). Specifically, the response of chemo-mechanical swelling polymer modified meshes to contact with stimuli droplets was studied. Theoretical discussion of the mechanism of smart materials is followed by development and experimental analysis of different modified mesh designs. A multi-physics model is proposed based on experimental data and the prototype of the fabric is tested in aerosol impingement conditions to confirm the barrier formed by rapid-self-sealing feature of the design.
ContributorsUppal, Aastha (Author) / Rykaczewski, Konrad (Thesis advisor) / Hildreth, Owen (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2016
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