Other affiliations: Mediterranea University of Reggio Calabria, Indian Institute of Science, Norwegian University of Science and Technology ...read more
Bio: Nilanjan Saha is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Offshore wind power & Wind speed. The author has an hindex of 11, co-authored 41 publications receiving 286 citations. Previous affiliations of Nilanjan Saha include Mediterranea University of Reggio Calabria & Indian Institute of Science.
Papers published on a yearly basis
TL;DR: In this paper, a wind turbine is mounted on a jacket structure at a water depth of 70m at a northern offshore site in the North Sea, and the turbine response is numerically obtained by using the aerodynamic software HAWC2 and the hydrodynamic software USFOS.
Abstract: Wind turbines must be designed in such a way that they can survive in extreme environmental conditions. Therefore, it is important to accurately estimate the extreme design loads. This paper deals with a recently proposed method for obtaining short-term extreme values for the dynamic responses of offshore fixed wind turbines. The 5 MW NREL wind turbine is mounted on a jacket structure (92 m high) at a water depth of 70 m at a northern offshore site in the North Sea. The hub height is 67 m above tower base or top of the jacket, i.e. 89 m above mean water level. The turbine response is numerically obtained by using the aerodynamic software HAWC2 and the hydrodynamic software USFOS. Two critical responses are discussed, the base shear force and the bending moment at the bottom of the jacket. The extreme structural responses are considered for wave-induced and wind-induced loads for a 100 year return-period harsh metocean condition with a 14.0 m significant wave height, a 16 s peak spectral period, a 50 m s − 1 (10 min average) wind speed (at the hub) and a turbulence intensity of 0.1 for a parked wind turbine. After performing the 10 min nonlinear dynamic simulations, a recently proposed extrapolation method is used for obtaining the extreme values of those responses over a period of 3 h. The sensitivity of the extremes to sample size is also studied. The extreme value statistics are estimated from the empirical mean upcrossing rates. This method together with other frequently used methods (i.e. the Weibull tail method and the global maxima method) is compared with the 3 h extreme values obtained directly from the time-domain simulations. Copyright © 2012 John Wiley & Sons, Ltd.
TL;DR: In this paper, the response of a jacket-supported offshore wind turbine (OWT) under wave loading, when (a) soil-structure interaction (SSI) is ignored and (b) SSI is considered, was compared by means of pushover analyses and irregular-wave dynamic analyses.
Abstract: This paper compares the response of a jacket-supported offshore wind turbine (OWT) under wave loading, when (a) soil–structure interaction (SSI) is ignored and (b) SSI is considered The jacket is placed in a water depth of 70 m and soil conditions off the west coast of India are used in the study The rotor of the OWT is considered to be parked, under a survival average wind speed of 50 m/s, significant waver height Hs=16 m and peak spectral period Tp=18 s The significance of includng SSI in OWT studies is investigated by means of pushover analyses and irregular-wave dynamic analyses Modal studies are performed to determine the variation in the free-vibration response of the two cases It is observed that ignoring SSI tends to over-estimate the ultimate strength characteristics of the OWT by 3–60% in various modes or increase the tower top displacement above serviceable limit For dynamics analysis, the wave elevation is generated using wave superposition method The JONSWAP wave spectrum is discretized using constant area method which introduces additional uncertainty The analysis shows that approximately 200 frequencies are necessary using constant area method to capture the tail region appropriately Also the statistical uncertainty in the generation of wave elevation for dynamic analyses is quantified by means of sample convergence studies The results show that approximately 20–40 samples are required in order to obtain reasonable statistics
TL;DR: In this paper, three variants of the extended Kalman filter (EKF) are proposed for parameter estimations in mechanical oscillators under Gaussian white noises, which are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDEs).
Abstract: We propose three variants of the extended Kalman filter (EKF) especially suited for parameter estimations in mechanical oscillators under Gaussian white noises. These filters are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDE-s). Besides a basic linearization of the non-linear drift functions via one-term replacements, linearizations using replacements through explicit Euler and Newmark expansions are also attempted in order to ensure higher closeness of true solutions with the linearized ones. Thus, unlike the conventional EKF, the proposed filters do not need computing derivatives (tangent matrices) at any stage. The measurements are synthetically generated by corrupting with noise the numerical solutions of the SDE-s through implicit versions of these linearizations. In order to demonstrate the effectiveness and accuracy of the proposed methods vis-a-vis the conventional EKF, numerical illustrations are provided for a few single degree-of-freedom (DOF) oscillators and a three-DOF shear frame with constant parameters.
TL;DR: In this paper, the effect of soil-structure interaction (SSI) on a jacket-offshore wind turbine (OWT) in a water depth of 70 m using JONSWAP spectrum was investigated.
Abstract: Wind turbines on jackets are being increasingly installed offshore. This paper attempts to investigate the effect of soil-structure interaction (SSI) on a jacket-offshore wind turbine (OWT) in a water depth of 70 m using JONSWAP spectrum. Stochastic responses of the OWT under varying soil profiles and met-ocean conditions are studied, by coupling the aerodynamic and hydrodynamic forces. From stochastic time domain response analyses, the SSI is observed to have significant influence in soft clay and layered soils at and above rated wind speeds whereas the dense sand have negligible influence.
TL;DR: In this paper, the authors deal with the dynamic analysis of the NREL 5MW OWT on a monopile foundation, in Indian waters, with an operational wind speed of 12 m/s and a sea state of 4 m significant wave height and 10 s spectral peak period.
Abstract: Offshore wind turbines (OWTs) offer an attractive, sustainable solution to the impending global energy crisis. A major challenge in fixed-bottom OWT design is accounting for soil-structure interaction (SSI) under the influence of random dynamic loading from wind, waves and currents. Usually, SSI is either ignored in OWT studies or is incorporated by means of simplified foundation concepts like the apparent fixity model. OWTs in shallow water depths (less than 30 m) are mostly supported on monopiles - large diameter steel pipe piles driven into the subsoil. Monopiles transfer the dynamic lateral loads into the soil by bending action. The present work deals with the dynamic analysis of the NREL 5MW OWT on a monopile foundation, in Indian waters. It involves parametric studies on various clayey soil profiles - soft, medium stiff and stiff clay. An operational wind speed of 12 m/s and a sea state of 4 m significant wave height and 10 s spectral peak period are considered. The OWT design should ensure that the natural frequency is away from the forcing frequencies of wind, wave and rotor. A water depth of 20 m is considered. Hub-height aerodynamic loads are obtained using the NREL-FAST code, which is based on the blade-element momentum (BEM) theory. The hydrodynamic time domain analyses are performed in the FEM based coupled hydrodynamic - geotechnical software, DNV-GL - USFOS. USFOS makes use of the JONSWAP spectrum to generate irregular waves. Soil is represented by means of p-y , Q-z and t-z curves. Results indicate the significance of including SSI in OWT studies. Variation in response due to change in pile penetration depth and pile diameter are also highlighted. Stiffness of clay is the design driver for OWTs.
TL;DR: This paper is devoted to the presentation of a new linear and nonlinear filter modeling based on a gravitational search algorithm (GSA) where unknown filter parameters are considered as a vector to be optimized.
Abstract: This paper is devoted to the presentation of a new linear and nonlinear filter modeling based on a gravitational search algorithm (GSA). To do this, unknown filter parameters are considered as a vector to be optimized. Examples of infinite impulse response (IIR) filter design, as well as rational nonlinear filter, are given. To verify the effectiveness of the proposed GSA based filter modeling, different sets of initial population with the presence of different measurable noises are given and tested in simulations. Genetic algorithm (GA) and particle swarm optimization (PSO) are also used to model the same examples and some simulation results are compared. Obtained results confirm the efficiency of the proposed method.
01 Jan 2011
TL;DR: In this paper, a study of rotor blade aerodynamic performances of wind turbine has been presented in which the aerodynamic effects changed by blade surface distribution as well as grid solution along the airfoil.
Abstract: The study of rotor blade aerodynamic performances of wind turbine has been presented in this thesis. This study was focused on aerodynamic effects changed by blade surface distribution as well as grid solution along the airfoil. The details of numerical calculation from Fluent were described to help predict accurate blade performance for comparison and discussion with available data. The direct surface curvature distribution blade design method for two-dimensional airfoil sections for wind turbine rotors have been discussed with the attentions to Euler equation, velocity diagram and the factors which affect wind turbine performance and applied to design a blade geometry close to an existing wind turbine blade, Eppler387, in order to argue that the blade surface drawn by direct surface curvature distribution blade design method contributes aerodynamic efficiency. The FLUENT calculation of NACA63-215V showed that the aerodynamic characteristics agreed well with the available experimental data at lower angles of attack although it was discontinuities in the surface curvature distributions between 0.7 and 0.8 in x/c. The discontinuities were so small that the blade performance could not be affected. The design of Eppler 387 blade performed to reduce drag force. The discontinuities of surface distribution matched the curve of the pressure coefficients. It was found in the curvature distribution that the leading edge pressure side had difficulties to connect to Bezier curve and also the trailing edge circle was never be tangent to the lines of trailing edge pressure and suction sides due to programming difficulties.
TL;DR: In this article, the present state of knowledge concerning geotechnical and structural issues affecting foundation types under consideration for the support structures of offshore wind turbines, and recommendations for future research and development are provided.
Abstract: Offshore wind is a source of clean, renewable energy of great potential value to the power industry in the context of a low carbon society. Rapid development of offshore wind energy depends on a good understanding of technical issues related to offshore wind turbines, which is spurring ongoing research and development programmes. Foundations of offshore wind turbines present one of the main challenges in offshore wind turbine design. This paper reviews the present state of knowledge concerning geotechnical and structural issues affecting foundation types under consideration for the support structures of offshore wind turbines, and provides recommendations for future research and development.
TL;DR: In this article, a nonlinear finite element (FE) model updating framework is proposed, in which advanced nonlinear structural FE modeling and analysis techniques are used jointly with the extended Kalman filter (EKF) to estimate time-invariant parameters associated to the nonlinear material constitutive models used in the structural system of interest.
Abstract: Summary This paper presents a novel nonlinear finite element (FE) model updating framework, in which advanced nonlinear structural FE modeling and analysis techniques are used jointly with the extended Kalman filter (EKF) to estimate time-invariant parameters associated to the nonlinear material constitutive models used in the FE model of the structural system of interest. The EKF as a parameter estimation tool requires the computation of structural FE response sensitivities (total partial derivatives) with respect to the material parameters to be estimated. Employing the direct differentiation method, which is a well-established procedure for FE response sensitivity analysis, facilitates the application of the EKF in the parameter estimation problem. To verify the proposed nonlinear FE model updating framework, two proof-of-concept examples are presented. For each example, the FE-simulated response of a realistic prototype structure to a set of earthquake ground motions of varying intensity is polluted with artificial measurement noise and used as structural response measurement to estimate the assumed unknown material parameters using the proposed nonlinear FE model updating framework. The first example consists of a cantilever steel bridge column with three unknown material parameters, while a three-story three-bay moment resisting steel frame with six unknown material parameters is used as second example. Both examples demonstrate the excellent performance of the proposed parameter estimation framework even in the presence of high measurement noise. Copyright © 2015 John Wiley & Sons, Ltd.
TL;DR: In this article, a framework for structural health monitoring (SHM) and damage identification of civil structures is presented, which integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of interest.
Abstract: This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer–Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.