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UNSTEADY AERODYNAMIC FORCE SENSING FROM MEASURED STRAIN

机译:测得的应变产生的非定常气动力

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摘要

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.
机译:在这项研究中,提出了一种简单的方法,该方法可以从模拟的实测应变数据计算出不稳定的空气动力。首先,使用两步法从非定常应变计算结构的挠度和斜率。使用自回归移动平均模型,在线参数估计器,低通滤波器和最小二乘曲线拟合方法以及关于时间的解析导数来计算结构的速度和加速度。最后,使用模态空气动力学影响系数矩阵,有理函数近似和时间行进算法来计算机翼上的空气动力学力。 1959年在NASA兰利研究中心(美国弗吉尼亚州汉普顿)建造和测试的悬臂矩形机翼用于验证这种简单方法。使用CFL3D计算流体动力学(CFD)代码和MSC / NASTRAN代码(美国加利福尼亚州纽波特比奇的MSC软件公司)计算不稳定的空气动力以及机翼的挠度,速度,加速度和应变,这些CFL3D-基于结果的假设为测量量。基于所测得的应变,可以使用所提出的方法来计算机翼挠度,速度,加速度和空气动力。将这些计算出的挠度,速度,加速度和不稳定的空气动力与基于CFL3D / NASTRAN的结果进行比较。通常,基于升速表面理论以亚音速计算的空气动力与使用带有欧拉方程的CFL3D代码生成的目标空气动力非常吻合。即使在-9.8dB的信噪比下获得不稳定的应变数据,也可以获得出色的气动弹性响应。每个传感器位置的偏转,速度和加速度与结构和空气动力学模型无关。因此,可将分布式应变数据与当前提出的方法一起用作分布式挠度,速度和加速度传感器。这项研究证明了通过使用分布式传感器技术和测得的应变数据来获得诱导的阻力和升力的可行性。因此,可以使用两个计算出的空气动力,即诱导的阻力和升力,来设计主动的诱导阻力控制系统,以提高飞机的燃油效率。结构有限元网格与CFD网格和质心之间的插值元素已成功地与非稳态气动弹性计算方案结合在一起。成功的方法最关键的技术是鲁棒的在线参数估计器,因为最小二乘曲线拟合方法在很大程度上取决于气动弹性系统的频率和阻尼系数。

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