Single-degree-of-freedom Systems

As a simple example of a nonlinear system, the base excited Duffing oscillator

my¨+ c ˙y+ ky + εy³= −m¨b(t) (3.65) serves as a useful model for displaying the key features of the first kernel. In this case z = m ˙y and Ef^TM⁻¹f = m.

The first Wiener kernel is plotted in the time and frequency domains in Figure 3.1 for an oscillator with different values of the nonlinearity constant under white noise base excitation of spectrum S₀= 2πW/kg. The parameters used are m = 3kg, c = 0.4kg/s and k = 10N/m and it can clearly be seen that the initial jump of the time domain kernel is of magnitude m and the integral of Eq. (3.63) is 1.52, 1.49 and 1.52kg for ε = 0, 0.1 and 0.3N/m³respectively.

Additionally, as nonlinearity increases, the time domain first kernel decays more rapidly and the frequency domain kernel becomes lower and wider meaning that the kernel appears more damped with nonlinearity. This effect is due to the higher order kernels having greater influence at higher nonlinearity meaning more energy is distributed from the first kernel to the higher order ones thus increasing the energy loss, or damping, of the first kernel. The power dissipated can be calculated directly from the time domain results as 9.70, 9.23 and 9.60W and from Eq. (3.62) as P = 9.55, 9.36 and 9.55W for ε = 0, 0.1 and 0.3N/m³respectively showing that the simulations agree well with the theory and the white noise result of 9.42W from Eq. (3.61).

The base acceleration in the previous figure is white noise and so the result that the integral over the frequency domain first kernel must be constant has already been proven

-10 0 10 20 30 40 50

Fig. 3.1 a) Time and b) frequency domain first Wiener kernels under white noise when ε = 0 (blue), ε = 0.1 (red) and ε = 0.3N/m³(yellow).

from a combination of Wiener theory and [47]. Next, a non-white excitation with spectrum

S_{ξ ξ}(ω) =π S₀

is applied to three nonlinear oscillators: a monostable oscillator with k = 0, a bistable oscillator with k = −200 exhibiting inter-well dynamics and a bistable oscillator with k =

−300N/m largely vibrating in one potential well. The other parameters are m = 3kg, c = 0.4kg/s, ε = 300N/m³, ω₀= 16rad/s, ζ0= 0.3 and S₀= 0.3W/kg. Since the narrowband signal’s low spectrum at high frequencies amplifies errors in the first kernel, a very low level white noise has been applied in addition to the narrowband noise to provide a more significant spectrum at high frequencies. The effect of low or zero input spectrum at certain frequencies is discussed further in Section 3.6.

The time and real part of the frequency first kernels are displayed in Figure 3.2 where the addition of two potential wells is seen to strongly affect the kernels. The monostable case behaves with one strong resonance whereas the bistable cases contain two resonances, one at approximately the frequency of inter-well dynamics and one at approximately the frequency of single-well dynamics. In the case where the linear stiffness is more negative, a lower resonant peak is observed at the frequency of inter-well dynamics since the majority of motion is within one potential well. In the time domain, the responses are highly damped due to the strong nonlinearity and reflect the dominant frequencies present.

As before and expected by the theory, the initial jump of the time kernel is approximately of value m and the integral over the frequency kernel from Eq. (3.63) is 1.50, 1.43 and 1.52kg

0 0.5 1 1.5 2 2.5 3 3.5

Fig. 3.2 a) Time and b) frequency domain first extended Wiener kernels under narrowband noise when k = 0 (blue), k = −200 (red) and k = −300N/m (yellow).

for k = 0, k = −200 and k = −300N/m respectively. Additionally, the power dissipated can be calculated directly from the time domain results as 1.86, 2.33 and 3.25W and from Eq.

(3.62) as P = 1.85, 2.32 and 3.24W for k = 0, k = −200 and k = −300N/m respectively again showing that the simulations agree well with the theory.

An interesting feature of both Figures 3.1 and 3.2 is that the noisiness of the kernel in the frequency domain seems correlated to level of nonlinearity in the system. Whilst the noise decreases with a greater ensemble, this feature suggests that compared to the linear case where the response is consistent regardless of input magnitude, a nonlinear oscillator requires more information to build up a complete description and thus extended Wiener series of the response because the response varies with input level. Additionally, due to the cubic stiffness of the Duffing oscillator, the first kernel often contains a noisier region at approximately three times the resonance frequency.

For a nonlinear system, the kernels depend on both the magnitude and spectrum of the excitation. For example, taking the oscillator of Figure 3.1 with ε = 0.1N/m³, if the input magnitude was reduced, the output displacement would be smaller and therefore the stiffening nonlinearity would have less effect making the response lower frequency. Likewise, a large input excitation increases the response displacement, increasing the frequency and a similar plot to Figure 3.1 could be made.

It is also interesting to investigate the effect of different forms of input spectra although to provide a reasonable comparison the approximate magnitude of the input should be kept the same. Three input spectra; band-limited noise with a flat spectrum, low-pass noise of

0 5 10 15 ω

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Sξξ(ω)

Fig. 3.3 Base acceleration spectra for band-limited (blue), low-pass (red) and narrowband (yellow) noise all with the same mean square acceleration.

spectrum given by

S_{ξ ξ}(ω) = π S0

2

ω_c²

ω_c²+ ω² (3.67)

and narrowband noise of Eq. (3.66) each chosen to have the same mean square acceleration (and therefore integral over the spectrum) are applied to a nonlinear oscillator. The band limited noise is chosen to have a spectrum of magnitude 1.00W/kg at frequencies between 0 and 10 rad/s and zero spectrum elsewhere, the low pass noise has S₀= 1.30W/kg and ω_c= 5rad/s and the narrowband noise has S₀= 1.27W/kg, ω0= 5rad/s and ζ0= 0.5 and all three spectra are plotted in Figure 3.3.

The first kernel in the time and frequency domain is plotted in Figure 3.4 using m = 3kg, c= 0.2kg/s, k = 10N/m and ε = 0.3N/m³. Subtle differences are seen between the kernels from band-limited and low-pass noise, with the low-pass noise having marginally higher frequency and damping. The kernel from the narrowband noise is more different still, with greater damping and a higher resonant frequency suggesting it oscillates over a greater, and therefore stiffer, displacement range. The integral over the kernel remains within 4% of the expected value of 1.5kg with 1.52, 1.52 and 1.56kg from the band-limited, low-pass and narrowband noise respectively.

0 2 4 6 8 10 12 14 16

Fig. 3.4 a) Time and b) frequency domain first Wiener kernels under band-limited (blue), low-pass (red) and narrowband (yellow) noise.