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- Creators: ASU Library. Music Library
ContributorsWard, Geoffrey Harris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-18
ContributorsWasbotten, Leia (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
ContributorsPonce, Angelita (Performer) / Rowland, Travis (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
Description
The friction condition is an important factor in controlling the compressing process in metalforming. The friction calibration maps (FCM) are widely used in estimating friction factors between the workpiece and die. However, in standard FEA, the friction condition is defined by friction coefficient factor (µ), while the FCM is used to a constant shear friction factors (m) to describe the friction condition. The purpose of this research is to find a method to convert the m factor to u factor, so that FEA can be used to simulate ring tests with µ. The research is carried out with FEA and Design of Experiment (DOE). FEA is used to simulate the ring compression test. A 2D quarter model is adopted as geometry model. A bilinear material model is used in nonlinear FEA. After the model is established, validation tests are conducted via the influence of Poisson's ratio on the ring compression test. It is shown that the established FEA model is valid especially if the Poisson's ratio is close to 0.5 in the setting of FEA. Material folding phenomena is present in this model, and µ factors are applied at all surfaces of the ring respectively. It is also found that the reduction ratio of the ring and the slopes of the FCM can be used to describe the deformation of the ring specimen. With the baseline FEA model, some formulas between the deformation parameters, material mechanical properties and µ factors are generated through the statistical analysis to the simulating results of the ring compression test. A method to substitute the m factor with µ factors for particular material by selecting and applying the µ factor in time sequence is found based on these formulas. By converting the m factor into µ factor, the cold forging can be simulated.
ContributorsKexiang (Author) / Shah, Jami (Thesis advisor) / Davidson, Joseph (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsZelenak, Kristen (Performer) / Detweiler, Samuel (Performer) / Rollefson, Justin (Performer) / Hong, Dylan (Performer) / Salazar, Nathan (Performer) / Feher, Patrick (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-31
ContributorsRyall, Blake (Performer) / Olarte, Aida (Performer) / Senseman, Stephen (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
Description
The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections.
ContributorsBaker, Noel C (Author) / Huang, Huei-Ping (Thesis advisor) / Trimble, Steve (Committee member) / Anderson, James (Committee member) / Clarke, Amanda (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsUhrenbacher, Tina (Performer) / Creviston, Hannah (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-31
ContributorsYi, Joyce (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-22
Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012