Sunetra Sarkar

Abstract: A nonlinear dynamic problem of stall induced flutter oscillation subject to physical uncertainties is analyzed using arbitrary polynomial chaos. A single-degree-of-freedom stall flutter model with torsional oscillation is considered subject to nonlinear aerodynamic loads in the dynamic stall regime and nonlinear structural stiffness. The analysis of the deterministic aeroelastic response demonstrated that the problem is sensitive to variations in structural natural frequency and structural nonlinearity. The effect of uncertainties in these parameters is studied. Arbitrary polynomial chaos is employed in which appropriate expansion polynomials are constructed based on the statistical moments of the uncertain input. The arbitrary polynomial chaos results are compared with Monte Carlo simulations.

Abstract: In this paper, nonlinear aeroelastic behavior of a two-dimensional symmetric rotor blade in the dynamic stall regime is investigated. Two different oscillation models have been considered here: pitching oscillation and flap–edgewise oscillation. Stall aeroelastic instability in such systems can potentially lead to structural damage. Hence it is an important design concern, especially for wind turbines and helicopter rotors, where such modes of oscillation are likely to take place. Most previous analyses of such dynamical systems are not exhaustive. System parameters like structural nonlinearity or initial conditions have not been studied which could play a significant role on the overall dynamics. In the present paper, a parametric study on the aeroelastic instability and the nonlinear dynamical behavior of the system has been performed. Emphasis is given on the effect of structural nonlinearity and initial conditions. The aerodynamic loads in the dynamic stall regime have been computed using the Onera model. The qualitative influence of the system parameters is different in the two systems studied. The effect of structural nonlinearity on the bifurcation pattern of the system response is significant in the case of pitching oscillation. The initial condition plays an important role on the aeroelastic stability as well as on the bifurcation pattern in both the systems. In the forced response study, interesting dynamical behavior, like period-3 response, has been observed in the pitching oscillation case. On the other hand, for the flap–edgewise oscillation case, super-harmonic and quasi-harmonic response have been found.

Abstract: In this paper probabilistic collocation for limit cycle oscillations (PCLCO) is proposed. Probabilistic collocation (PC) is a non-intrusive approach to compute the polynomial chaos description of uncertainty numerically. Polynomial chaos can require impractical high orders to approximate long-term time integration problems, due to the fast increase of required polynomial chaos order with time. PCLCO is a PC formulation for modeling the long-term stochastic behavior of dynamical systems exhibiting a periodic response, i.e. a limit cycle oscillation (LCO). In the PC method deterministic time series are computed at collocation points in probability space. In PCLCO, PC is applied to a time-independent parametrization of the periodic response of the deterministic solves instead of to the time-dependent functions themselves. Due to the time-independent parametrization the accuracy of PCLCO is independent of time. The approach is applied to period-1 oscillations with one main frequency subject to a random parameter. Numerical results are presented for the harmonic oscillator, a two-dof airfoil flutter model and the fluid-structure interaction of an elastically mounted cylinder.

Abstract: Earlier analytical and experimental studies predict that pitchingmotions at high frequency can generate thrust on the airfoil. Thepresent work is an effort towards a systematic understanding of theinfluence of various parameters on thrust generation from aharmonically pitching airfoil. Quantitative instantaneous forcecomputations have been discussed together with qualitative vortexpatterns using a 2-D discrete vortex simulation of incompressibleviscous flow. In general, thrust force increases with the oscillationfrequency. The trend is very similar to the inviscid theory prediction.Further, the thrust force is seen to decrease with the increase in meanangle of attack. However, in a clear deviation from inviscid theorytrends, pitching at high amplitudes about high mean angle of attack,only drag is observed for high values of reduced frequency considered.The effect of location of the pitching axis is also found to besignificant on the propulsive characteristics of the airfoil.

Abstract: Numerical simulations of a heaving airfoil undergoing non-sinusoidal motions in an incompressible viscous flow is presented In particular, asymmetric sinusoidal motions, constant heave rate oscillations, and sinusoidal motions with a quiescent gap, are considered The wake patterns, thrust force coefficients, and propulsive efficiency at various values of non-dimensional heave velocity are computed These have been compared with those of corresponding sinusoidal heaving motions of the airfoil It is shown that for a given non-dimensional heave velocity and reduced frequency of oscillation, asymmetric sinusoidal motions give better thrust and propulsive efficiencies in comparison to pure harmonic motion On the other hand, constant rate heave motion do not compare favourably with harmonic motion A train of sinusoidal pulses separated by a quiescent gap compares favourably with a pure sinusoidal motion, but with the notable exception that the quiescent gap induces a discontinuity that induces large impulses to the wake pattern

Abstract: Most numerical integration techniques consist of approximating the integrand by a polynomial in a region or regions and then integrating the polynomial exactly. Often a complicated integrand can be factored into a non-negative ''weight'' function and another function better approximated by a polynomial, thus $\int_{a}^{b} g(t)dt = \int_{a}^{b} \omega (t)f(t)dt \approx \sum_{i=1}^{N} w_i f(t_i)$. Hopefully, the quadrature rule ${\{w_j, t_j\}}_{j=1}^{N}$ corresponding to the weight function $\omega$(t) is available in tabulated form, but more likely it is not. We present here two algorithms for generating the Gaussian quadrature rule defined by the weight function when: a) the three term recurrence relation is known for the orthogonal polynomials generated by $\omega$(t), and b) the moments of the weight function are known or can be calculated.

Abstract: Polynomial chaos (PC) expansions are used in stochastic finite element analysis to represent the random model response by a set of coefficients in a suitable (so-called polynomial chaos) basis. The number of terms to be computed grows dramatically with the size of the input random vector, which makes the computational cost of classical solution schemes (may it be intrusive (i.e. of Galerkin type) or non intrusive) unaffordable when the deterministic finite element model is expensive to evaluate. To address such problems, the paper describes a non intrusive method that builds a sparse PC expansion. First, an original strategy for truncating the PC expansions, based on hyperbolic index sets, is proposed. Then an adaptive algorithm based on least angle regression (LAR) is devised for automatically detecting the significant coefficients of the PC expansion. Beside the sparsity of the basis, the experimental design used at each step of the algorithm is systematically complemented in order to avoid the overfitting phenomenon. The accuracy of the PC metamodel is checked using an estimate inspired by statistical learning theory, namely the corrected leave-one-out error. As a consequence, a rather small number of PC terms are eventually retained (sparse representation), which may be obtained at a reduced computational cost compared to the classical ''full'' PC approximation. The convergence of the algorithm is shown on an analytical function. Then the method is illustrated on three stochastic finite element problems. The first model features 10 input random variables, whereas the two others involve an input random field, which is discretized into 38 and 30-500 random variables, respectively.

Abstract: 流体力学杂志“Journal of Fluid Mechanics”由剑桥大学教授George Batchelor在1956年5月创办，在国际流体力学界享有很高的学术声望，被公认为是流体力学最著名的学术刊物之一，2005年的影响因子为2．061，雄居同类期刊之首．在它创刊50周年之际，2006年5月JFM出版了第554卷的纪念特刊，其中刊登了现任主编（美国西北大学S．H．Davis教授和英国剑桥大学T．J．Pedley教授）合写的述评：“Editorial：JFM at50”，以JFM为背景，从独特的视角对近50年来流体力学的发展进行了简明的回顾和展望，并归纳了一系列非常有启发性的有趣统计数字．2006年7月21日在剑桥大学应用数学和理论物理研究所（DAMTP）举行了创刊50周年的庆祝会．下午2点，JFM的新老编辑和来宾会聚一堂，Pedley教授致开幕词，其后是5个精彩的报告：The mysterious rattleback and its fluid counterpart（Keith Moffatt），Developments in shear instabilities（Patrick Huerre），Falling clouds（Elisabeth Guazzelli），Ecotectural fluid mechanics（Paul Linden），The success of JFM（Herbert Huppert），最后由Davis教授致闭幕词．

Abstract: Effects of large computational time steps on the computed turbulence were investigated using a fully implicit method. In turbulent channel flow computations the largest computational time step in wall units which led to accurate prediction of turbulence statistics was determined. Turbulence fluctuations could not be sustained if the computational time step was near or larger than the Kolmogorov time scale.

Abstract: Global sensitivity analysis aims at quantifying the relative importance of uncertain input variables onto the response of a mathematical model of a physical system. ANOVA-based indices such as the Sobol’ indices are well-known in this context. These indices are usually computed by direct Monte Carlo or quasi-Monte Carlo simulation, which may reveal hardly applicable for computationally demanding industrial models. In the present paper, sparse polynomial chaos (PC) expansions are introduced in order to compute sensitivity indices. An adaptive algorithm allows the analyst to build up a PC-based metamodel that only contains the significant terms whereas the PC coefficients are computed by least-square regression using a computer experimental design. The accuracy of the metamodel is assessed by leave-one-out cross validation. Due to the genuine orthogonality properties of the PC basis, ANOVA-based sensitivity indices are post-processed analytically. This paper also develops a bootstrap technique which eventually yields confidence intervals on the results. The approach is illustrated on various application examples up to 21 stochastic dimensions. Accurate results are obtained at a computational cost 2–3 orders of magnitude smaller than that associated with Monte Carlo simulation.