Matching Items (20)
Description
Current hybrid vehicle and/or Fuel Cell Vehicle (FCV) use both FC and an electric system. The sequence of the electric power train with the FC system is intended to achieve both better fuel economies than the conventional vehicles and higher performance. Current hybrids use regenerative braking technology, which converts the vehicles kinetic energy into electric energy instead of wasting it. A hybrid vehicle is much more fuel efficient than conventional Internal Combustion (IC) engine and has less environmental impact The new hybrid vehicle technology with it's advanced with configurations (i.e. Mechanical intricacy, advanced driving modes etc) inflict an intrusion with the existing Thermal Management System (TMS) of the conventional vehicles. This leaves for the opportunity for now thermal management issues which needed to be addressed. Till date, there has not been complete literature on thermal management issued of FC vehicles. The primary focus of this dissertation is on providing better cooling strategy for the advanced power trains. One of the cooling strategies discussed here is the thermo-electric modules.
The 3D Thermal modeling of the FC stack utilizes a Finite Differencing heat approach method augmented with empirical boundary conditions is employed to develop 3D thermal model for the integration of thermoelectric modules with Proton Exchange Membrane fuel cell stack. Hardware-in-Loop was designed under pre-defined drive cycle to obtain fuel cell performance parameters along with anode and cathode gas flow-rates and surface temperatures. The FC model, combined experimental and finite differencing nodal net work simulation modeling approach which implemented heat generation across the stack to depict the chemical composition process. The structural and temporal temperature contours obtained from this model are in compliance with the actual recordings obtained from the infrared detector and thermocouples. The Thermography detectors were set-up through dual band thermography to neutralize the emissivity and to give several dynamic ranges to achieve accurate temperature measurements. The thermocouples network was installed to provide a reference signal.
The model is harmonized with thermo-electric modules with a modeling strategy, which enables optimize better temporal profile across the stack. This study presents the improvement of a 3D thermal model for proton exchange membrane fuel cell stack along with the interfaced thermo-electric module. The model provided a virtual environment using a model-based design approach to assist the design engineers to manipulate the design correction earlier in the process and eliminate the need for costly and time consuming prototypes.
The 3D Thermal modeling of the FC stack utilizes a Finite Differencing heat approach method augmented with empirical boundary conditions is employed to develop 3D thermal model for the integration of thermoelectric modules with Proton Exchange Membrane fuel cell stack. Hardware-in-Loop was designed under pre-defined drive cycle to obtain fuel cell performance parameters along with anode and cathode gas flow-rates and surface temperatures. The FC model, combined experimental and finite differencing nodal net work simulation modeling approach which implemented heat generation across the stack to depict the chemical composition process. The structural and temporal temperature contours obtained from this model are in compliance with the actual recordings obtained from the infrared detector and thermocouples. The Thermography detectors were set-up through dual band thermography to neutralize the emissivity and to give several dynamic ranges to achieve accurate temperature measurements. The thermocouples network was installed to provide a reference signal.
The model is harmonized with thermo-electric modules with a modeling strategy, which enables optimize better temporal profile across the stack. This study presents the improvement of a 3D thermal model for proton exchange membrane fuel cell stack along with the interfaced thermo-electric module. The model provided a virtual environment using a model-based design approach to assist the design engineers to manipulate the design correction earlier in the process and eliminate the need for costly and time consuming prototypes.
ContributorsRamani, Dilip (Author) / Mayyas, Abdel Ra'Ouf (Thesis advisor) / Hsu, Keng (Committee member) / Madakannan, Arunachalanadar (Committee member) / Arizona State University (Publisher)
Created2014
Description
The demand for miniaturized components with feature sizes as small as tens of microns and tolerances as small as 0.1 microns is on the rise in the fields of aerospace, electronics, optics and biomedical engineering. Micromilling has proven to be a process capable of generating the required accuracy for these features and is an alternative to various non-mechanical micro-manufacturing processes which are limited in terms of cost and productivity, especially at the micro-meso scale. The micromilling process is on the surface, a miniaturized version of conventional milling, hence inheriting its benefits. However, the reduction in scale by a few magnitudes makes the process peculiar and unique; and the macro-scale theories have failed to successfully explain the micromilling process and its machining parameters. One such characteristic is the unpredictable nature of tool wear and breakage. There is a large cost benefit that can be realized by improving tool life. Workpiece rejection can also be reduced by successfully monitoring the condition of the tool to avoid issues. Many researchers have developed Tool Condition Monitoring and Tool Wear Modeling systems to address the issue of tool wear, and to obtain new knowledge. In this research, a tool wear modeling effort is undertaken with a new approach. A new tool wear signature is used for real-time data collection and modeling of tool wear. A theoretical correlation between the number of metal chips produced during machining and the condition of the tool is introduced. Experimentally, it is found that the number of chips produced drops with respect to the feedrate of the cutting process i.e. when the uncut chip thickness is below the theoretical minimum chip thickness.
ContributorsBajaj, Anuj Kishorkumar (Author) / SODEMANN, ANGELA A (Thesis advisor) / Bekki, Jeniffer (Committee member) / Hsu, Keng (Committee member) / Arizona State University (Publisher)
Created2015
Description
The concept of this thesis came up as a part of the efforts being devoted around the world to reduce energy consumption, CO2 emissions, global warming and ozone layer depletion. In the United States, HVAC units in residential buildings consumed about 350 billion kWh in 2017 [1],[2]. Although HVAC manufacturers are investing in new technologies and more efficient products to reduce energy consumption, there is still room for further improvement.
One way of reducing cooling and heating energy in residential buildings is by allowing the centralized HVAC unit to supply conditioned air to only occupied portions of the house by applying smart HVAC zoning. According to the United States Energy Information Administration [3], the percentage of houses equipped with centralized HVAC units is over 70%, which makes this thesis applicable to the majority of houses in the United States. This thesis proposes to implement HVAC zoning in a smart way to eliminate all human errors, such as leaving the AC unit on all day, which turns out to be causing a serious amount of energy to be wasted.
The total amount of energy that could be saved by implementing the concepts presented in this thesis in all single-family houses in the U.S. is estimated to be about 156 billion kWh annually. This amount of energy reduction is proportional to the electricity bills and the amount of dollars paid annually on energy that is technically being wasted.
One way of reducing cooling and heating energy in residential buildings is by allowing the centralized HVAC unit to supply conditioned air to only occupied portions of the house by applying smart HVAC zoning. According to the United States Energy Information Administration [3], the percentage of houses equipped with centralized HVAC units is over 70%, which makes this thesis applicable to the majority of houses in the United States. This thesis proposes to implement HVAC zoning in a smart way to eliminate all human errors, such as leaving the AC unit on all day, which turns out to be causing a serious amount of energy to be wasted.
The total amount of energy that could be saved by implementing the concepts presented in this thesis in all single-family houses in the U.S. is estimated to be about 156 billion kWh annually. This amount of energy reduction is proportional to the electricity bills and the amount of dollars paid annually on energy that is technically being wasted.
ContributorsFairag, Amr (Author) / Phelan, Patrick (Thesis advisor) / Bocanegra, Luis (Committee member) / Shuaib, Abdelrahman (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
Additive Manufacturing and 3D printing are becoming important technologies in the manufacturing sector. The benefits of this technology include complex part geometry, short lead-times, low waste, and simple user interface. However, the technology does not come without its drawbacks: mainly the removal of support structures from the component. Traditional techniques that involve sawing and cutting can be expensive and take a long time, increasing the overall price of 3D printed metal components. This paper discusses two approaches taken for dissolvable support structures in 3D printed stainless steel (17-4 PH). For the first time in powder bed fusion components, with the help of Christopher Lefky and Dr. Owen Hildreth, dissolvable support capabilities are achieved in metal prints. The first approach, direct dissolution, involves direct corrosion of the entire part, leading to support removal. This approach is not self-terminating, and leads to changes in final component geometry. The second approach involves a post-build sensitization step, which physically alters the microstructure and chemical stability of the first 100-200 microns of the metal. The component is then etched at an electric potential that will readily corrode this sensitized surface, but not the underlying base metal. An electrolytic solution of HNO3/KCl/HCl paired with an anodic bias was used for the direct dissolution approach, resulting in a loss of about 120 microns of material from the components surface. For the self-limiting approach, surface sensitization was achieve through a post build annealing step (800 C for 6 hours, air cooled) with exposure to a sodium hexacynoferrate slurry. When the slurry decomposes in the furnace, carbon atoms diffuse into the surface and precipitate a chromium-carbide, which reduces the chemical stability of the stainless steel. Etching is demonstrated in an anodic bias of HNO3/KCl. To determine proper etching potentials, open circuit potential and cyclic voltammetry experiments were run to create Potentiodynamic Polarization Curves. Further testing of the self-terminating approach was performed on a 316 stainless steel interlocking ring structure with a complex geometry. In this case, 32.5 hours of etching at anodic potentials replaced days of mechanical sawing and cutting.
ContributorsZucker, Brian Nicholas (Co-author) / Lefky, Christopher (Co-author) / Hildreth, Owen (Co-author, Thesis director) / Hsu, Keng (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The aerospace industry has been conducting research on the additive manufacturing (AM) process since the 1980's, but companies have recently just begun to apply AM in hopes that this new technology will meet or exceed the requirements met by previous manufacturing methods, as well as producing more cost effective, geometrically-complex products. This investigation evaluated the performance of 3D-printed aerospace test specimens made by Powder Bed Fusion Technologies, and compared them to forged specimens. A design of experiments varying build parameters was conducted in order to determine AM component porosity. Factors such as powder post-processing, directionality of the build, and fractology of the samples were evaluated through tensile strength testing and hardness testing of Inconel 718 wrought and EBM printed materials. Using electron microsopy, the responses to these factors were analyzed for stress fractures, grain boundaries, and other defects that occurred in the testing process. The comparison determined which metallurgical process provides the most effective material for aircraft usage.
ContributorsNez, Brittany Amber (Author) / Parsey, John (Thesis director) / Hsu, Keng (Committee member) / Godfrey, Donald (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Automobiles can advance greatly with the introduction of metal additive manufactured components. Additive tooling is slowly becoming additive manufacturing and someday the technology will be advanced enough that high volume can be supported. This research was conducted in order to show the advantages metal additive manufacturing has in the automobile industry. One large advantage to metal additive manufacturing is mass reduction. Components can be designed for production with different geometries than other manufacturing methods. The change in geometry can significantly reduce the product volume and therefore mass. Overall, mass reduction in the automotive industry is beneficial. Mass reduction can increase performance and fuel economy of the car. Once metal additive manufacturing becomes capable of higher production, metal additive manufacturing will play a major role in automobile manufacturing. Research was conducted to design and produce an optimized AC compressor bracket. The bracket was designed to the specifications of the OEM component, and the mass was reduced by more than half.
ContributorsSawyer, Brenton James (Author) / Hsu, Keng (Thesis director) / Parsey, John (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Determining the thermal conductivity of carbon gas diffusion layers used in hydrogen fuel cells is a very active topic of research. The primary driver behind this research is due to the need for development of proton exchange membrane fuels with longer usable life cycles before failure. As heat is a byproduct of the oxygen-hydrogen reaction an optimized pathway to remove the excess heat is needed to prevent thermal damage to the fuel cell as both mechanical and chemical degradation is accelerated under elevated temperatures. Commercial systems used for testing thermal conductivity are readily available, but are prohibitively expensive, ranging from just over $10,000 to $80,000 for high-end systems. As this cost can exclude some research labs from experimenting with thermal conductivity, a low cost alternative system is a desirable product. The development of a low cost system that maintained typical accuracy levels of commercials systems was carried out successfully at a significant cost reduction. The end product was capable of obtaining comparable accuracy to commercial systems at a cost reduction of more than 600% when compared to entry level commercial models. Combined with a system design that only required some basic fabrication equipment, this design will allow many research labs to expand their testing capabilities without straining departmental budgets. As expected with the development of low cost solutions, the reduction in cost came at the loss in other aspects of system performance, mainly run time. While the developed system requires a significate time investment to obtain useable results, the system can be improved by the used of RTDs in place of thermocouples or incorporation of an isothermal cold plate. These improvements would reduce the runtime to less than that of a standard work day while maintaining an approximate reduction in cost of 350%.
ContributorsSucher, Brent (Author) / Kannan, Arunachala (Thesis advisor) / Hsu, Keng (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2016
Description
This work aimed to characterize and optimize the variables that influence the Gas Diffusion Layer (GDL) preparation using design of experiment (DOE) approach. In the process of GDL preparation, the quantity of carbon support and Teflon were found to have significant influence on the Proton Exchange Membrane Fuel Cell (PEMFC). Characterization methods like surface roughness, wetting characteristics, microstructure surface morphology, pore size distribution, thermal conductivity of GDLs were examined using laser interferometer, Goniometer, SEM, porosimetry and thermal conductivity analyzer respectively. The GDLs were evaluated in single cell PEMFC under various operating conditions of temperature and relative humidity (RH) using air as oxidant. Electrodes were prepared with different PUREBLACK® and poly-tetrafluoroethylene (PTFE) content in the diffusion layer and maintaining catalytic layer with a Pt-loading (0.4 mg cm-2). In the study, a 73.16 wt.% level of PB and 34 wt.% level of PTFE was the optimal compositions for GDL at 70 °C for 70% RH under air atmosphere.
For most electrochemical processes the oxygen reduction is very vita reaction. Pt loading in the electrocatalyst contributes towards the total cost of electrochemical devices. Reducing the Pt loading in electrocatalysts with high efficiency is important for the development of fuel cell technologies. To this end, this thesis work reports the approach to lower down the Pt loading in electrocatalyst based on N-doped carbon nanotubes derived from Zeolitic Imidazolate Frameworks (ZIF-67) for oxygen reduction. This electrocatalyst perform with higher electrocatalytic activity and stability for oxygen reduction in fuel cell testing. The electrochemical properties are mainly due to the synergistic effect from N-doped carbon nanotubes derived from ZIF and Pt loading. The strategy with low Pt loading forecasts in emerging highly active and less expensive electrocatalysts in electrochemical energy devices.
This thesis focuses on: (i) methods to obtain greater power density by optimizing content of wet-proofing agent (PTFE) and fine-grained, hydrophobic, microporous layer (MPL); (ii) modeling full factorial analysis of PEMFC for evaluation with experimental results and predicting further improvements in performance; (iii) methods to obtain high levels of performance with low Pt loading electrodes based on N-doped carbon nanotubes derived from ZIF-67 and Pt.
For most electrochemical processes the oxygen reduction is very vita reaction. Pt loading in the electrocatalyst contributes towards the total cost of electrochemical devices. Reducing the Pt loading in electrocatalysts with high efficiency is important for the development of fuel cell technologies. To this end, this thesis work reports the approach to lower down the Pt loading in electrocatalyst based on N-doped carbon nanotubes derived from Zeolitic Imidazolate Frameworks (ZIF-67) for oxygen reduction. This electrocatalyst perform with higher electrocatalytic activity and stability for oxygen reduction in fuel cell testing. The electrochemical properties are mainly due to the synergistic effect from N-doped carbon nanotubes derived from ZIF and Pt loading. The strategy with low Pt loading forecasts in emerging highly active and less expensive electrocatalysts in electrochemical energy devices.
This thesis focuses on: (i) methods to obtain greater power density by optimizing content of wet-proofing agent (PTFE) and fine-grained, hydrophobic, microporous layer (MPL); (ii) modeling full factorial analysis of PEMFC for evaluation with experimental results and predicting further improvements in performance; (iii) methods to obtain high levels of performance with low Pt loading electrodes based on N-doped carbon nanotubes derived from ZIF-67 and Pt.
ContributorsKasat, Harshal Anil (Author) / Kannan, Arunachalana (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Arizona State University (Publisher)
Created2016
Description
Semiconductor manufacturing is one of the most complex manufacturing systems in today’s times. Since semiconductor industry is extremely consumer driven, market demands within this industry change rapidly. It is therefore very crucial for these industries to be able to predict cycle time very accurately in order to quote accurate delivery dates. Discrete Event Simulation (DES) models are often used to model these complex manufacturing systems in order to generate estimates of the cycle time distribution. However, building models and executing them consumes sufficient time and resources. The objective of this research is to determine the influence of input parameters on the cycle time distribution of a semiconductor or high volume electronics manufacturing system. This will help the decision makers to implement system changes to improve the predictability of their cycle time distribution without having to run simulation models. In order to understand how input parameters impact the cycle time, Design of Experiments (DOE) is performed. The response variables considered are the attributes of cycle time distribution which include the four moments and percentiles. The input to this DOE is the output from the simulation runs. Main effects, two-way and three-way interactions for these input variables are analyzed. The implications of these results to real world scenarios are explained which would help manufactures understand the effects of the interactions between the input factors on the estimates of cycle time distribution. The shape of the cycle time distributions is different for different types of systems. Also, DES requires substantial resources and time to run. In an effort to generalize the results obtained in semiconductor manufacturing analysis, a non- complex system is considered.
ContributorsSalvi, Tanushree Ashutosh (Author) / Bekki, Jennifer M (Thesis advisor) / Sodemann, Angela (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2017