4 resultados para Sums of squares

em QSpace: Queen's University - Canada


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Thermal and fatigue cracking are the two of the major pavement distress phenomena that contribute significantly towards increased premature pavement failures in Ontario. This in turn puts a massive burden on the provincial budgets as the government spends huge sums of money on the repair and rehabilitation of roads every year. Governments therefore need to rethink and re-evaluate their current measures in order to prevent it in future. The main objectives of this study include: the investigation of fatigue distress of 11 contract samples at 10oC, 15oC, 20oC and 25oC and the use of crack-tip-opening-displacement (CTOD) requirements at temperatures other than 15oC; investigation of thermal and fatigue distress of the comparative analysis of 8 Ministry of Transportation (MTO) recovered and straight asphalt samples through double-edge-notched-tension test (DENT) and extended bending beam rheometry (EBBR); chemical testing of all samples though X-ray Fluorescence (XRF) and Fourier transform infrared analysis (FTIR); Dynamic Shear Rheometer (DSR) higher and intermediate temperature grading; and the case study of a local Kingston road. Majority of 11 contract samples showed satisfactory performance at all temperatures except one sample. Study of CTOD at various temperatures found a strong correlation between the two variables. All recovered samples showed poor performance in terms of their ability to resist thermal and fatigue distress relative to their corresponding straight asphalt as evident in DENT test and EBBR results. XRF and FTIR testing of all samples showed the addition of waste engine oil (WEO) to be the root cause of pavement failures. DSR high temperature grading showed superior performance of recovered binders relative to straight asphalt. The local Kingston road showed extensive signs of damage due to thermal and fatigue distress as evident from DENT test, EBBR results and pictures taken in the field. In the light of these facts, the use of waste engine oil and recycled asphalt in pavements should be avoided as these have been shown to cause premature failure in pavements. The DENT test existing CTOD requirements should be implemented at other temperatures in order to prevent the occurrences of premature pavement failures in future.

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How do the magnetic fields of massive stars evolve over time? Are their gyrochronological ages consistent with ages inferred from evolutionary tracks? Why do most stars predicted to host Centrifugal Magnetospheres (CMs) display no H$\alpha$ emission? Does plasma escape from CMs via centrifugal breakout events, or by a steady-state leakage mechanism? This thesis investigates these questions via a population study with a sample of 51 magnetic early B-type stars. The longitudinal magnetic field \bz~was measured from Least Squares Deconvolution profiles extracted from high-resolution spectropolarimetric data. New rotational periods $P_{\rm rot}$ were determined for 15 stars from \bz, leaving only 3 stars for which $P_{\rm rot}$ is unknown. Projected rotational velocities \vsini~were measured from multiple spectral lines. Effective temperatures and surface gravities were measured via ionization balances and line profile fitting of H Balmer lines. Fundamental physical parameters, \bz, \vsini, and $P_{\rm rot}$ were then used to determine radii, masses, ages, dipole oblique rotator model, stellar wind, magnetospheric, and spindown parameters using a Monte Carlo approach that self-consistently calculates all parameters while accounting for all available constraints on stellar properties. Dipole magnetic field strengths $B_{\rm d}$ follow a log-normal distribution similar to that of Ap stars, and decline over time in a fashion consistent with the expected conservation of fossil magnetic flux. $P_{\rm rot}$ increases with fractional main sequence age, mass, and $B_{\rm d}$, as expected from magnetospheric braking. However, comparison of evolutionary track ages to maximum spindown ages $t_{\rm S,max}$ shows that initial rotation fractions may be far below critical for stars with $M_*>10 M_\odot$. Computing $t_{\rm S,max}$ with different mass-loss prescriptions indicates that the mass-loss rates of B-type stars are likely much lower than expected from extrapolation from O-type stars. Stars with H$\alpha$ in emission and absorption occupy distinct regions in the updated rotation-magnetic confinement diagram: H$\alpha$-bright stars are found to be younger, more rapidly rotating, and more strongly magnetized than the general population. Emission strength is sensitive both to the volume of the CM and to the mass-loss rate, favouring leakage over centrifugal breakout.

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Quantile regression (QR) was first introduced by Roger Koenker and Gilbert Bassett in 1978. It is robust to outliers which affect least squares estimator on a large scale in linear regression. Instead of modeling mean of the response, QR provides an alternative way to model the relationship between quantiles of the response and covariates. Therefore, QR can be widely used to solve problems in econometrics, environmental sciences and health sciences. Sample size is an important factor in the planning stage of experimental design and observational studies. In ordinary linear regression, sample size may be determined based on either precision analysis or power analysis with closed form formulas. There are also methods that calculate sample size based on precision analysis for QR like C.Jennen-Steinmetz and S.Wellek (2005). A method to estimate sample size for QR based on power analysis was proposed by Shao and Wang (2009). In this paper, a new method is proposed to calculate sample size based on power analysis under hypothesis test of covariate effects. Even though error distribution assumption is not necessary for QR analysis itself, researchers have to make assumptions of error distribution and covariate structure in the planning stage of a study to obtain a reasonable estimate of sample size. In this project, both parametric and nonparametric methods are provided to estimate error distribution. Since the method proposed can be implemented in R, user is able to choose either parametric distribution or nonparametric kernel density estimation for error distribution. User also needs to specify the covariate structure and effect size to carry out sample size and power calculation. The performance of the method proposed is further evaluated using numerical simulation. The results suggest that the sample sizes obtained from our method provide empirical powers that are closed to the nominal power level, for example, 80%.

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In geotechnical engineering, the stability of rock excavations and walls is estimated by using tools that include a map of the orientations of exposed rock faces. However, measuring these orientations by using conventional methods can be time consuming, sometimes dangerous, and is limited to regions of the exposed rock that are reachable by a human. This thesis introduces a 2D, simulated, quadcopter-based rock wall mapping algorithm for GPS denied environments such as underground mines or near high walls on surface. The proposed algorithm employs techniques from the field of robotics known as simultaneous localization and mapping (SLAM) and is a step towards 3D rock wall mapping. Not only are quadcopters agile, but they can hover. This is very useful for confined spaces such as underground or near rock walls. The quadcopter requires sensors to enable self localization and mapping in dark, confined and GPS denied environments. However, these sensors are limited by the quadcopter payload and power restrictions. Because of these restrictions, a light weight 2D laser scanner is proposed. As a first step towards a 3D mapping algorithm, this thesis proposes a simplified scenario in which a simulated 1D laser range finder and 2D IMU are mounted on a quadcopter that is moving on a plane. Because the 1D laser does not provide enough information to map the 2D world from a single measurement, many measurements are combined over the trajectory of the quadcopter. Least Squares Optimization (LSO) is used to optimize the estimated trajectory and rock face for all data collected over the length of a light. Simulation results show that the mapping algorithm developed is a good first step. It shows that by combining measurements over a trajectory, the scanned rock face can be estimated using a lower-dimensional range sensor. A swathing manoeuvre is introduced as a way to promote loop closures within a short time period, thus reducing accumulated error. Some suggestions on how to improve the algorithm are also provided.