Matching Items (109)
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- All Subjects: Mechanical Engineering
- Creators: Liu, Yongming
- Creators: Rykaczewski, Konrad
Description
Thermodynamic development and balance of plant study is completed for a 30 MW solar thermochemical water splitting process that generates hydrogen gas and electric power. The generalized thermodynamic model includes 23 components and 45 states. Quasi-steady state simulations are completed for design point system sizing, annual performance analysis and sensitivity analysis. Detailed consideration is given to water splitting reaction kinetics with governing equations generalized for use with any redox-active metal oxide material. Specific results for Ceria illustrate particle reduction in two solar receivers for target oxygen partial pressure of 10 Pa and particle temperature of 1773 K at a design point DNI of 900 W/m2. Sizes of the recuperator, steam generator and hydrogen separator are calculated at the design point DNI to achieve 100,000 kg of hydrogen production per day from the plant. The total system efficiency of 39.52% is comprised of 50.7% hydrogen fraction and 19.62% electrical fraction. Total plant capital costs and operating costs are estimated to equate a hydrogen production cost of $4.40 per kg for a 25-year plant life. Sensitivity analysis explores the effect of environmental parameters and design parameters on system performance and cost. Improving recuperator effectiveness from 0.7 to 0.8 is a high-value design modification resulting in a 12.1% decrease in hydrogen cost for a modest 2.0% increase in plant $2.85M. At the same time, system efficiency is relatively inelastic to recuperator effectiveness because 81% of excess heat is recovered from the system for electricity production 39 MWh/day and revenue is $0.04 per kWh. Increasing water inlet pressure up to 20 bar reduces the size and cost of super heaters but further pressure rises increasing pump at a rate that outweighs super heater cost savings.
ContributorsBudama, Vishnu Kumar (Author) / Johnson, Nathan (Thesis advisor) / Stechel, Ellen (Committee member) / Rykaczewski, Konrad (Committee member) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2018
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
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
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (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
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
It is well known that the geckos can cling to almost any surface using highly dense micro
ano fibrils found on the feet that rely on Van Der Waals forces to adhere. A few experimental and theoretical approaches have been taken to understand the adhesion mechanism of gecko feet. This work explains the building procedure of custom experimental setup to test the adhesion force over a temperature range and extends its application in space environment, potentially unsafe working condition.
This study demonstrates that these adhesive capable of switching adhesive properties not only at room environment but also over a temperature range of -160 degC to 120 degC in vacuum conditions. These conditions are similar to the condition experienced by a satellite in a space orbiting around the earth. Also, this study demonstrated various detachment and specimen patch preparation methods. The custom-made experimental setup for adhesion test can measure adhesion force in temperature and pressure controlled environment over specimen size of 1 sq. inch. A cryogenic cooling system with liquid nitrogen is used to achieve -160 degC and an electric resistive heating system are used to achieve 120 degC in controlled volume. Thermal electrodes, infrared thermopile detectors are used to record temperature at sample and pressure indicator to record vacuum condition in controlled volume. Reversibility of the switching behaviour of the specimen in controlled environment confirms its application in space and very high or very low-temperature conditions.
The experimental setup was developed using SolidWorks as a design tool, Ansys as simulation tool and the data acquisition utilizes LabVIEW available in the market today.
ano fibrils found on the feet that rely on Van Der Waals forces to adhere. A few experimental and theoretical approaches have been taken to understand the adhesion mechanism of gecko feet. This work explains the building procedure of custom experimental setup to test the adhesion force over a temperature range and extends its application in space environment, potentially unsafe working condition.
This study demonstrates that these adhesive capable of switching adhesive properties not only at room environment but also over a temperature range of -160 degC to 120 degC in vacuum conditions. These conditions are similar to the condition experienced by a satellite in a space orbiting around the earth. Also, this study demonstrated various detachment and specimen patch preparation methods. The custom-made experimental setup for adhesion test can measure adhesion force in temperature and pressure controlled environment over specimen size of 1 sq. inch. A cryogenic cooling system with liquid nitrogen is used to achieve -160 degC and an electric resistive heating system are used to achieve 120 degC in controlled volume. Thermal electrodes, infrared thermopile detectors are used to record temperature at sample and pressure indicator to record vacuum condition in controlled volume. Reversibility of the switching behaviour of the specimen in controlled environment confirms its application in space and very high or very low-temperature conditions.
The experimental setup was developed using SolidWorks as a design tool, Ansys as simulation tool and the data acquisition utilizes LabVIEW available in the market today.
ContributorsMate, Sunil (Author) / Marvi, Hamidreza (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2016
Description
This paper details ink chemistries and processes to fabricate passive microfluidic devices using drop-on-demand printing of tetraethyl-orthosilicate (TEOS) inks. Parameters space investigation of the relationship between printed morphology and ink chemistries and printing parameters was conducted to demonstrate that morphology can be controlled by adjusting solvents selection, TEOS concentration, substrate temperature, and hydrolysis time. Optical microscope and scanning electron microscope images were gathered to observe printed morphology and optical videos were taken to quantify the impact of morphology on fluid flow rates. The microscopy images show that by controlling the hydrolysis time of TEOS, dilution solvents and the printing temperature, dense or fracture structure can be obtained. Fracture structures are used as passive fluidic device due to strong capillary action in cracks. At last, flow rate of passive fluidic devices with different thickness printed at different temperatures are measured and compared. The result shows the flow rate increases with the increase of device width and thickness. By controlling the morphology and dimensions of printed structure, passive microfluidic devices with designed flow rate and low fluorescence background are able to be printed.
ContributorsHuang, Yiwen (Author) / Hildreth, Owen (Thesis advisor) / Wang, Robert (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2016