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McNeill S.I.,Stress Engineering Services
Journal of Offshore Mechanics and Arctic Engineering | Year: 2012

Modal decomposition and reconstruction (MDR) of marine riser vortex induced vibration (VIV) is a technique where vibration is measured using accelerometers and/or angular rate sensors, the modal displacements are solved for and the stress and fatigue damage is reconstructed along the riser. Recent developments have greatly increased the accuracy and reliability of the method. However the computational burden is onerous due to stress time history reconstruction and rainflow cycle counting at every desired location along the riser. In addition, fully synchronous data are required to reconstruct the stress histories. Dirlik's method for obtaining rainflow damage for Gaussian random stress using only spectral information (four spectral automoments) has proven to be quite accurate with a significant reduction in computational effort. In this paper two spectral formulations of MDR are introduced. The first method is applicable when all the measured data are synchronous. In this method, spectral cross moments of the modal displacements are solved from the spectral cross moments of the measured data using basis vectors consisting of normal mode shapes. The spectral automoments of stress are obtained from the modal displacement cross moments and analytical stress mode shapes. Dirlik's method is then applied to obtain rainflow damage. The second method is a generalization of the first, where the measured data cross moments are only partially known. This method is applicable when measured data are partially synchronous or asynchronous. A numerical root-finding technique is employed to solve for the modal response cross moments. The method then proceeds in the same manner as the first. The spectral methods are applied to simulated VIV data of a full-scale deepwater riser and to Norwegian Deepwater Program (NDP) scale-model test data on a 38 m long slender riser. Comparisons of reconstructed fatigue damage versus simulated or measured damage indicate that the method is capable of estimating fatigue damage accurately for Gaussian VIV even when data are not fully synchronous. It is also shown that computational cost is greatly reduced. © 2012 American Society of Mechanical Engineers. Source


Acoustic emission testing (AET) is a powerful non-destructive testing technique that can be used to detect and locate several types of damage mechanisms. High-temperature hydrogen attack (HTHA) is a concern in the oil refining industry because many old vintage C-Mo and Cr-Mo steels remain in operation well past their design lives. There are several documents providing refinery owners and users with guidance on operating high-temperature reactors in hydrogen environments. Nelson curves (API 971) also help determine the likelihood of damage. For this inspection technique to succeed, HTHA damage must be stressed to levels beyond those normally seen during steady-state operating conditions. Thermal gradients during the unit's cool-down offer such an opportunity because they are produced by a relatively rapid temperature reduction that induces considerable thermal stresses. These can cause HTHA (micro-fissures) to propagate, and therefore be detectable by AET. This paper discusses applications of the AET technique and provides an example of this type of inspection. 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of ICM11 © 2011 Published by Elsevier Ltd. Source


McNeill S.I.,Stress Engineering Services
Journal of Sound and Vibration | Year: 2016

An algorithm for nonparametric decomposition of a signal into the sum of short-time narrow-banded modes (components) is introduced. Specifically, the signal data is augmented with its Hilbert transform to obtain the analytic signal. Then the set of constituent amplitude and frequency modulated (AM-FM) analytic sinusoids, each with slowly varying amplitude and frequency, is sought. The method for obtaining the short-time narrow-banded modes is derived by minimizing an objective function comprised of three criteria: smoothness of the instantaneous amplitude envelope, smoothness of the instantaneous frequency and complete reconstruction of the signal data. A minimum of the objective function is approached using a sequence of suboptimal updates of amplitude and phase. The updates are intuitive, efficient and simple to implement. For a given mode, the amplitude and phase are extracted from the band-pass filtered residual (signal after the other modes are removed), where the band-pass filter is applied about the previous modal instantaneous frequency estimate. The method is demonstrated by application to random output-only vibration data and order tracking data. It is demonstrated that vibration modal responses can be estimated from single channel data and order tracking can be performed without measured tachometer data. © 2016 Elsevier Ltd. Source


McNeill S.I.,Stress Engineering Services
JVC/Journal of Vibration and Control | Year: 2012

In this paper a complex-valued formulation of the modal superposition equation is provided and shown to be equivalent to the original, real-valued Blind Modal IDentification (BMID) problem. The complex-valued variant involves the analytic form of the physical and modal responses. The formulation is shown to be more concise and straightforward than the original. It is noted that complex-valued mode shapes can be obtained using a complex version of the two-step Joint Approximate Diagonalization (JAD) algorithm. Using this approach the modal response pairing step of the original BMID method is eliminated. Since the development of the original BMID method, several new, one-step JAD algorithms have been devised. Many of the algorithms can be extended to identify complex mixing matrices. A complex version of the one-step JAD method known as the Weighted Exhaustive Diagonalization with Gauss itErations algorithm is utilized to solve for the complex mode shapes and modal responses. By using this simplified formulation, the whitening step is eliminated, as well as the modal response pairing step, which is necessary in the original BMID algorithm.Performance of the new Complex BMID (CBMID) algorithm is evaluated by application to synthesized data from a three-degrees-of-freedom system with complex modes, application to measured laboratory data on a structural frame and application to measured output-only data from the Heritage Court Tower building. It is seen that the CBMID method results in essentially the same estimates of modal responses, complex mode shapes, natural frequencies and modal damping compared to results from BMID. Furthermore, it is shown that modal parameters from BMID and CBMID are very consistent with those obtained from state-of-the-art methods, such as the Eigensystem Realization Algorithm and the covariance-driven Stochastic Subspace Identification method. © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav. Source


Agarwal P.,Stress Engineering Services | Manuel L.,University of Texas at Austin
Applied Ocean Research | Year: 2011

Design of an offshore wind turbine requires estimation of loads on its rotor, tower and supporting structure. These loads are obtained by time-domain simulations of the coupled aero-servo-hydro-elastic model of the wind turbine. Accuracy of predicted loads depends on assumptions made in the simulation models employed, both for the turbine and for the input wind and wave conditions. Currently, waves are simulated using a linear irregular wave theory that is not appropriate for nonlinear waves, which are even more pronounced in shallow water depths where wind farms are typically sited. The present study investigates the use of irregular nonlinear (second-order) waves for estimating loads on the support structure (monopile) of an offshore wind turbine. We present the theory for the irregular nonlinear model and incorporate it in the commonly used wind turbine simulation software, FAST, which had been developed by National Renewable Energy Laboratory (NREL), but which had the modeling capability only for irregular linear waves. We use an efficient algorithm for computation of nonlinear wave elevation and kinematics, so that a large number of time-domain simulations, which are required for prediction of long-term loads using statistical extrapolation, can easily be performed. To illustrate the influence of the alternative wave models, we compute loads at the base of the monopile of the NREL 5MW baseline wind turbine model using linear and nonlinear irregular wave models. We show that for a given environmental condition (i.e., the mean wind speed and the significant wave height), extreme loads are larger when computed using the nonlinear wave model. We finally compute long-term loads, which are required for a design load case according to the International Electrotechnical Commission guidelines, using the inverse first-order reliability method. We discuss a convergence criteria that may be used to predict accurate 20-year loads and discuss wind versus wave dominance in the load prediction. We show that 20-year long-term loads can be significantly higher when the nonlinear wave model is used. © 2011 Elsevier Ltd. Source

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