Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain

Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics.

Effects Of The Flash Welding Process On Mechanical And Microstructural Properties Of Structural Steel Joints Assessed Using Dest

ASTM A529 carbon¿manganese steel angle specimens were joined by flash butt welding and the effects of varying process parameter settings on the resulting welds were investigated. The weld metal and heat affected zones were examined and tested using tensile testing, ultrasonic scanning, Rockwell hardness testing, optical microscopy, and scanning electron microscopy with energy dispersive spectroscopy in order to quantify the effect of process variables on weld quality. Statistical analysis of experimental tensile and ultrasonic scanning data highlighted the sensitivity of weld strength and the presence of weld zone inclusions and interfacial defects to the process factors of upset current, flashing time duration, and upset dimension. Subsequent microstructural analysis revealed various phases within the weld and heat affected zone, including acicular ferrite, Widmanstätten or side-plate ferrite, and grain boundary ferrite. Inspection of the fracture surfaces of multiple tensile specimens, with scanning electron microscopy, displayed evidence of brittle cleavage fracture within the weld zone for certain factor combinations. Test results also indicated that hardness was increased in the weld zone for all specimens, which can be attributed to the extensive deformation of the upset operation. The significance of weld process factor levels on microstructure, fracture characteristics, and weld zone strength was analyzed. The relationships between significant flash welding process variables and weld quality metrics as applied to ASTM A529-Grade 50 steel angle were formalized in empirical process models.

Design and Preliminary Results of an Atmospheric-Pressure Model Gas Turbine Combustor Utilizing Varying CO2 Doping Concentration in CH4 to Emulate Biogas Combustion

Utilization of biogas can provide a source of renewable energy in both heat and power generation. Combustion of biogas in land-based gas turbines for power generation is a promising approach to reducing greenhouse gases and US dependence on foreign-source fossil fuels. Biogas is a byproduct from the decomposition of organic matter and consists primarily of CH4 and large amounts of CO2. The focus of this research was to design a combustion device and investigate the effects of increasing levels of CO2 addition to the combustion of pure CH4 with air. Using an atmospheric-pressure, swirl-stabilized dump combustor, emissions data and flame stability limitations were measured and analyzed. In particular, CO2, CO, and NOx emissions were the main focus of the combustion products. Additionally, the occurrence of lean blowout and combustion pressure oscillations, which impose significant limitations in operation ranges for actual gas turbines, was observed. Preliminary kinetic and equilibrium modeling was performed using Cantera and CEA for the CH4/CO2/Air combustion systems to analyze the effect of CO2 upon adiabatic flame temperature and emission levels. The numerical and experimental results show similar dependence of emissions on equivalence ratio, CO2 addition, inlet air temperature, and combustor residence time. (C) 2014 Elsevier Ltd. All rights reserved.

The Effect of Various Electrode Microstructure Parameters on the Effective Conductivity and Three-Phase Boundary Density of Infiltrated SOFC Electrodes

Solid oxide fuel cell (SOFC) technology has the potential to be a significant player in our future energy technology repertoire based on its ability to convert chemical energy into electrical energy. Infiltrated SOFCs, in particular, have demonstrated improved performance and at lower cost than traditional SOFCs. An infiltrated electrode comprises porous ceramic scaffolding (typically constructed from the oxygen ion conducting material) that is infiltrated with electron conducting and catalytic particles. Two important SOFC electrode properties are effective conductivity and three phase boundary density (TPB). Researchers study these electrode properties separately, and fail to recognize them as competing properties. This thesis aims to (1) develop a method to model the TPB density and use it to determine the effect of porosity, scaffolding particle size, and pore former size on TPB density as well as to (2) compare the effect of porosity, scaffolding particle size, and pore former size on TPB density and effective conductivity to determine a desired set of parameters for infiltrated SOFC electrode performance. A computational model was used to study the effect of microstructure parameters on the effective conductivity and TPB density of the infiltrated SOFC electrode. From this study, effective conductivity and TPB density are determined to be competing properties of SOFC electrodes. Increased porosity, scaffolding particle size, and pore former particle size increase the effective conductivity for a given infiltrate loading above percolation threshold. Increased scaffolding particle size and pore former size ratio, however, decreases the TPB density. The maximum TPB density is achievable between porosities of 45% and 60%. The effect of microstructure parameters are more prominent at low loading with scaffolding particle size being the most significant factor and pore former size ratio being the least significant factor.

High-resolution computer simulations of stacking of weak bases using a transient pH boundary in capillary electrophoresis. 1. Concept and impact of sample ionic strength

The dynamics of focusing weak bases using a transient pH boundary was examined via high-resolution computer simulation software. Emphasis was placed on the mechanism and impact that the presence of salt, namely, NaCl, has on the ability to focus weak bases. A series of weak bases with mobilities ranging from 5 x 10(-9) to 30 x 10(-9) m2/V x s and pKa values between 3.0 and 7.5 were examined using a combination of 65.6 mM formic acid, pH 2.85, for the separation electrolyte, and 65.6 mM formic acid, pH 8.60, for the sample matrix. Simulation data show that it is possible to focus weak bases with a pKa value similar to that of the separation electrolyte, but it is restricted to weak bases having an electrophoretic mobility of 20 x 10(-9) m2/V x s or quicker. This mobility range can be extended by the addition of NaCl, with 50 mM NaCl allowing stacking of weak bases down to a mobility of 15 x 10(-9) m2/V x s and 100 mM extending the range to 10 x 10(-9) m2/V x s. The addition of NaCl does not adversely influence focusing of more mobile bases, but does prolong the existence of the transient pH boundary. This allows analytes to migrate extensively through the capillary as a single focused band around the transient pH boundary until the boundary is dissipated. This reduces the length of capillary that is available for separation and, in extreme cases, causes multiple analytes to be detected as a single highly efficient peak.

Smooth Hazard Function Estimation for Interval Censored Data with Time Varying Covariates

In this paper we propose methods for smooth hazard estimation of a time variable where that variable is interval censored. These methods allow one to model the transformed hazard in terms of either smooth (smoothing splines) or linear functions of time and other relevant time varying predictor variables. We illustrate the use of this method on a dataset of hemophiliacs where the outcome, time to seroconversion for HIV, is interval censored and left-truncated.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.