Evaluation of the p-y method in the design of monopiles for offshore wind turbines

Monopile foundations, currently designed using the p-y method, are technically viable in supporting larger offshore wind turbines in waters to a depth of 30 m. The p-y method was developed to better understand the behavior of laterally loaded long slender piles required for the offshore oil and gas installations. The lateral load-deformation behavior of two monopiles, 5 and 7.5 m dia, installed in soft clays of varying undrained shear strength and stiffness, was studied. A combination of axial and lateral loads expected at an offshore wind farm location with a water depth of 30 m was used in the analysis. It was established that the Matlock (1970) p-y curves are too soft and under-estimate the ultimate soil reaction at all depths except at the monopile tip. At the pile tip, the base shear was not accounted for in the p-y curves, hence resulting in the over-estimation of the soil reaction. Consequently, the Matlock (1970) p-y formulation significantly underestimates the monopile ultimate lateral capacity. The use of the Matlock (1970) p-y method would result in over-conservative designs of monopiles for offshore wind turbines. This is an abstract of a paper presented at the Offshore Technology Conference (Houston, TX 5/6-9/2013).

The silent base flow and the sound sources in a laminar jet.

An algorithm to compute the silent base flow sources of sound in a jet is introduced. The algorithm is based on spatiotemporal filtering of the flow field and is applicable to multifrequency sources. It is applied to an axisymmetric laminar jet and the resulting sources are validated successfully. The sources are compared to those obtained from two classical acoustic analogies, based on quiescent and time-averaged base flows. The comparison demonstrates how the silent base flow sources shed light on the sound generation process. It is shown that the dominant source mechanism in the axisymmetric laminar jet is "shear-noise," which is a linear mechanism. The algorithm presented here could be applied to fully turbulent flows to understand the aerodynamic noise-generation mechanism.

Bayesian separation and recovery of convolutively mixed autoregressive sources

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.

Forcing of self-excited round jet diffusion flames

In this experimental and numerical study, two types of round jet are examined under acoustic forcing. The first is a non-reacting low density jet (density ratio 0.14). The second is a buoyant jet diffusion flame at a Reynolds number of 1100 (density ratio of unburnt fluids 0.5). Both jets have regions of strong absolute instability at their base and this causes them to exhibit strong self-excited bulging oscillations at welldefined natural frequencies. This study particularly focuses on the heat release of the jet diffusion flame, which oscillates at the same natural frequency as the bulging mode, due to the absolutely unstable shear layer just outside the flame. The jets are forced at several amplitudes around their natural frequencies. In the non-reacting jet, the frequency of the bulging oscillation locks into the forcing frequency relatively easily. In the jet diffusion flame, however, very large forcing amplitudes are required to make the heat release lock into the forcing frequency. Even at these high forcing amplitudes, the natural mode takes over again from the forced mode in the downstream region of the flow, where the perturbation is beginning to saturate non-linearly and where the heat release is high. This raises the possibility that, in a flame with large regions of absolute instability, the strong natural mode could saturate before the forced mode, weakening the coupling between heat release and incident pressure perturbations, hence weakening the feedback loop that causes combustion instability. © 2009 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Image-based localization and pose recovery using scale invariant features

In this paper, we propose a vision based mobile robot localization strategy. Local scale-invariant features are used as natural landmarks in unstructured and unmodified environment. The local characteristics of the features we use prove to be robust to occlusion and outliers. In addition, the invariance of the features to viewpoint change makes them suitable landmarks for mobile robot localization. Scale-invariant features detected in the first exploration are indexed into a location database. Indexing and voting allow efficient recognition of global localization. The localization result is verified by epipolar geometry between the representative view in database and the view to be localized, thus the probability of false localization will be decreased. The localization system can recover the pose of the camera mounted on the robot by essential matrix decomposition. Then the position of the robot can be computed easily. Both calibrated and un-calibrated cases are discussed and relative position estimation based on calibrated camera turns out to be the better choice. Experimental results show that our approach is effective and reliable in the case of illumination changes, similarity transformations and extraneous features. © 2004 IEEE.