Ionic polymers are a recently discovered class of active materials that exhibit bidirectional electromechanical coupling. They are `soft' transducers that perform best when the mechanical deformation involves bending of the transducer. Ionic polymers are low voltage actuators -- they only require inputs on the order of 1V and cannot tolerate voltages above approximately 10V. The mechanisms responsible for the electromechanical coupling are not yet fully understood, and reports of the capabilities and limitations of ionic polymer transducers vary widely. In addition, suitable engineering models have not been developed. This document presents a dynamic model for ionic polymer transducers that is based on a pair of symmetric, linearly coupled equations with frequency dependent coefficients. The model is presented in the form of an equivalent circuit, employing an ideal transformer with a frequency dependent turns ratio to represent the electromechanical coupling. The circuit elements have clear physical interpretations, and expressions relating them to transducer dimensions and material properties are derived herein. The material parameters required for the model: modulus, density, electrical properties, and electromechanical coupling term are determined experimentally. The model is then validated by comparing simulated and experimental responses, and the agreement is good. Further validation is presented in the form of extensive experiments that confirm the predicted changes in transducer performance as transducer dimensions are varied. In addition, reciprocity between mechanical and electrical domains is demonstrated. This reciprocity is predicted by the model, and is a direct result of the symmetry in the equations on which the model is based. The capabilities of ionic polymer sensors and actuators, when used in the cantilevered bender configuration, are discussed and compared to piezoceramic and piezo polymer cantilevered benders. The energy density of all three actuators are within an order of magnitude of one another, with peak values of approximately 10J/m^3 and 4mJ/kg for ionic polymer actuators actuated with a 1.2V signal. Ionic polymer sensors compare favorably to piezoelectric sensors. Their charge sensitivity is approximately 320E-6C/m for a 0.2 x 5 x 17mm cantilevered bender, two orders of magnitude greater than a piezo polymer sensor with identical dimensions. This work is concluded with a demonstration of feedback control of a device powered by ionic polymer actuators. An ionic polymer sensor was used to provide the displacement feedback signal. This experiment is the first demonstration of feedback control using an ionic polymer sensor. Compensator design was performed using the model developed in the first chapter of this document, and experiments confirmed that implementation of the control scheme improved, in a narrow frequency range, the system's ability to track sinusoidal inputs. / Ph. D.

archives@tulane.edu / 1 / Owen Richfield

The in-stream water quality model, QUAL2Kw, can provide guidance in watershed management decisions by linking changes in nutrient loads to responses in water quality. This model is particularly useful for determining wasteload allocations, aiding in total maximum daily load analyses, and developing numeric nutrient criteria. Unfortunately, states struggle to balance the data collection and modeling requirements to accomplish many of these water quality management tasks due to limited resources. This commonly results in routine data collection and monitoring efforts that do not satisfy the data requirements for modeling. To address this disconnect, this study presents a data collection and parameter calibration methodology suited to meet general QUAL2Kw modeling requirements. Then, with the goal of identifying a range of numeric nitrogen and phosphorus criteria, this general data collection and modeling strategy was applied to sites throughout Utah. To help automate and test scenarios targeted at tracking effects of loading and response combinations, a nutrient criteria tool was also developed to interface with these QUAL2Kw models. By implementing the tool on these models, input concentrations of ammonium (NH4+) ranging from 10 to 101 µg/L and inorganic phosphorus (PO4-) ranging from 1 to 14 µg/L were found to exceed thresholds of bottom algae, gross primary productivity, and ecosystem respiration. Conversely, NH4+ concentrations above 3,500 µg/L and PO4- above 490 µg/L exceeded dissolved oxygen thresholds of 5-6 mg/L in some applications. Some limitations of using mechanistic models in this manner were identified, including model capabilities (e.g., steady-state versus dynamic), inclusion of appropriate processes, uncertainty in calibrated parameters, and site-specific conditions. Although many problems will require more complex modeling efforts with significantly larger data collection efforts, this approach provides an initial framework that aids in the judicial use of resources to aid in watershed management decisions.

Autonomous mining machines can provide improvements in several desired aspects of the mining industry, ranging from improved safety and personnel expenses to machine utilization and fleets of machines working together. For these autonomous machines, control systems are essential. This thesis examines three different control strategies, PD, LQ, and PID, for a Boomer E drill rig from Epiroc. In order to develop control systems without spending valuable time on real world implementation and testing, simulations of control strategies are common. If a system is to be simulated, a model of the system is required which captures the dynamics of interest. The thesis examines different polynomial models for modeling of the dynamics of a SmartROC D65 drill rig from Epiroc.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20510号 / 情博第638号 / 新制||情||111(附属図書館) / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 石田 亨, 教授 多々納 裕一, 教授 鹿島 久嗣 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

No description available.

This thesis seeks to investigate the predictive capabilities of Advanced turbulence models in the wake region of a wall-mounted cube. Dynamic Hybrid RANS/LES (DHRL), Hybrid RANS/LES (HRL) models, Nonlinear Explicit Algebraic Reynolds Stress Model (NEARSM), One- and Two-equation models, and numerical flux schemes will be compared against Direct Numerical Simulation (DNS) results to determine which model, or combination of models, produce the closest replication. The simulations were ran in Loci-Chem using both built-in features and modular code additions. The simulation results show the Shear Stress Transport (SST) model ran with NEARSM and Optimized Gradient REconstruction (OGRE) scheme gives better results than all other RANS and HRL models investigated herein. This result is matched only by SST with DHRL and OGRE. The best results were achieved using SST with NEARSM, DHRL, and OGRE. Thus, the NEARSM model shows potential to improve simulation results compared to simpler linear eddy-viscosity models.

The main objective of this research was to create a two dimensional and three dimensional Environmental Fluid Dynamics Code (EFDC) model using Aberdeen Pool of the Tennessee-Tombigbee Waterway for the purpose of determining the differences in their ability to address sediment transport. These objectives were reached in the results with comparisons of water levels, sediment concentrations, shear stress, and bed change. The models produced very similar results for the majority of the sediment transport throughout both models with the overall trend being deposition except in the upper limits of the Tombigbee River. The main differences between the two models are produced from the 2D model being depth averaged and the 3D being able to transport sediment vertically. The results show the 2D model tends to erode less and deposit more whereas the 3D model tends to follow the same pattern except for less deposition with more erosion.

The Effective Continuum Micromechanics Analysis Code (EC-MAC) was developed for predicting effective properties of composites containing multiple distinct nanoheterogeneities (fibers, spheres, platelets, voids, etc.) each with an arbitrary number of coating layers based upon either the modified Mori-Tanaka method (MTM) and self consistent method (SCM). This code was used to investigate the effect of carbon nanofiber morphology (i.e., hollow versus solid cross-section), nanofiber waviness, and both nanofiber-resin interphase properties and dimensions on bulk nanocomposite elastic moduli. For a given nanofiber axial force-displacement relationship, the elastic modulus for hollow nanofibers can significantly exceed that for solid nanofibers resulting in notable differences in bulk nanocomposite properties. The development of a nanofiber-resin interphase had a notable effect on the bulk elastic moduli. Consistent with results from the literature, small degrees of nanofiber waviness resulted in a significant decrease in effective composite properties. Key aspects of nanofiber morphology were characterized using transmission electron microscopy (TEM) images for VGCNF/vinyl ester (VE) nanocomposites. Three-parameter Weibull probability density functions were generated to describe the statistical variation in nanofiber outer diameters, wall thicknesses, relative wall thicknesses, visible aspect ratios, and visible waviness ratios. Such information could be used to establish more realistic nanofiber moduli and strengths obtained from nanofiber tensile tests, as well as to develop physically motivated computational models for predicting nanocomposite behavior. This study represents one of the first attempts to characterize the distribution of VGCNF features in real thermoset nanocomposites. In addition, the influence of realistic nanoreinforcement geometries, distinct elastic properties, and orientations on the effective elastic moduli was addressed. The effect of multiple distinct heterogeneities, including voids, on the effective elastic moduli was investigated. For the composites containing randomly oriented wavy vapor grown carbon nanofibers (VGCNFs) and voids, the predicted moduli captured the essential character of the experimental data, where the volume fraction of voids was approximated as a nonlinear function of the volume fraction of reinforcements. This study should facilitate the development of multiscale materials design by providing insight into the relationships between nanomaterial morphology and properties across multiple spatial scales that lead to improved macroscale performance.

Lightweight structural components are important to the automotive and aerospace industries so that better fuel economy can be realized. Magnesium alloys in particular are being examined to fulfill this need due to their attractive stiffness- and strength-to-weight ratios when compared to other materials. However, when introducing a material into new roles, one needs to properly characterize its mechanical properties. Fatigue behavior is especially important considering aerospace and automotive component applications. Therefore, quantifying the structure-property relationships and accurately predicting the fatigue behavior for these materials are vital. This study has two purposes. The first is to quantify the structure-property relationships for the fatigue behavior in an AM30 magnesium alloy. The second is to use the microstructural-based MultiStage Fatigue (MSF) model in order to accurately predict the fatigue behavior of three magnesium alloys: AM30, Elektron 21, and AZ61. While some studies have previously quantified the MSF material constants for several magnesium alloys, detailed research into the fatigue regimes, notably the microstructurally small crack (MSC) region, is lacking. Hence, the contribution of this work is the first of its kind to experimentally quantify the fatigue crack incubation and MSC regimes that are used for the MultiStage Fatigue model. Using a multiaceted experimental approach, these regimes were explored with a replica method that used a dual-stage silicone based compound along with previously published in situ fatigue tests. These observations were used in calibrating the MultiStage Fatigue model.