对低频域应用的实验伪等价确定性激发方法的扩展
Giulia Mazzeo1, Giuseppe Petrone2, Francesco Franco2
1Laboratoire de Tribologie et Dynamique des Systèmes, Ecole Centrale de Lyon Ecully 69130, France.
The Journal of the Acoustical Society of America
|December 1, 2023
概括
运输工程中的流动诱导振动可能是昂贵的测试. 实验性伪等效决定性激发方法 (X-PEDEM) 扩展到低频应用,为风洞测试提供了更有效的替代方案.
科学领域:
- 交通工程是交通工程.
- 结构动力学 结构动力学
- 空气动力学 在空气动力学.
背景情况:
- 流动诱导的振动会对系统运行和运输工程中的响应产生负面影响.
- 风洞测试对于评估结构设计和材料性能至关重要,但耗时且昂贵.
- 需要使用替代方法来加快测试并改进流边界层激发的不确定性分析.
研究的目的:
- 为低频域应用扩展实验性伪等价确定性激发方法 (X-PEDEM).
- 调查X-PEDEM在低频范围中的适用性和分析属性.
- 在各种数值条件下评估扩展X-PEDEM方法的可靠性.
主要方法:
- 扩展了实验性伪等效决定性激发方法 (X-PEDEM).
- 在低频域应用X-PEDEM.
- 使用不同的面板,边界条件和流速进行数值验证.
主要成果:
- 该研究调查了X-PEDEM在低频域中的适用性.
- 分析了扩展的X-PEDEM方法的特性.
- 数字测试证实了X-PEDEM在各种条件下的可靠性.
结论:
- 扩展的X-PEDEM方法显示了在低频域的适用性,用于模拟对流边界层激发的结构反应.
- 该方法为传统风洞测试提供了一个潜在的更高效和数据丰富的替代方案.
- 数字验证支持X-PEDEM在运输工程应用中的可靠性.
相关概念视频
Linear Approximation in Frequency Domain
92
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
92
Discrete-Time Fourier Series
277
The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
For a discrete-time periodic signal x[n]...
277
Frequency-Domain Interpretation of PD Control
112
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
The proportional control gain, combined with the...
112
Linear Approximation in Time Domain
83
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
83
Basic signals of Fourier Transform
504
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
504
Discrete Fourier Transform
295
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
295


