Golden Ratio Phenomenon of Random Data Obeying von Karman Spectrum

von Karman originally deduced his spectrum of wind speed fluctuation based on the Stokes-Navier equation. Taking into account, the practical issues of measurement and/or computation errors, we suggest that the spectrum can be described from the point of view of the golden ratio. We call it the golden ratio phenomenon of the von Karman spectrum. To depict that phenomenon, we derive the von Karman spectrum based on fractional differential equations, which bridges the golden ratio to the von Karman spectrum and consequently provides a new outlook of random data following the von Karman spectrum in turbulence. In addition, we express the fractal dimension, which is a measure of local self-similarity, using the golden ratio, of random data governed by the von Karman spectrum.

In the field of random functions, more precisely, turbulence in fluid mechanics, a kind of power spectra density (PSD) function introduced by von Karman [31], known as the von Karman spectra (VKS), has been widely used in the diverse fields, ranging from turbulence to acoustic wave propagation in random media; see, for example, Goedecke et al. [32] and the references therein.Among the von Karman spectra, the spectrum (VKSW for short) expressed in (1) is particularly useful in the field of wind engineering for the modeling of wind speed fluctuation; see, for example, [33][34][35][36][37][38][39][40][41].That PSD is in the form where  is frequency (Hz),    is turbulence integral scale,  is mean speed,   is friction velocity (ms −1 ), and  V is friction velocity coefficient such that the variance of wind speed  2  =  V  2  .Note that (1) was conventionally deduced based on the Stokes-Navier equation ( [31], Bauer and Zeibig [42], Tropea [43], Monin and Yaglom [44], Xiushu [45]).It does not originally relate to the concept of either the golden ratio or fractal dimension.As a matter of fact, reports regarding turbulence's fractal dimension derived directly based on the Stokes-Navier equation are rarely seen as Gaoan stated in [46, page 55], letting alone the golden ratio.

Mathematical Problems in Engineering
This paper aims at contributing the following three results.First, we will propose a rigorous but concise derivation of (1).Then, we will generalize (1) such that the generalization may be described from the point of view of the golden ratio.Finally, we will explain the golden ratio phenomenon of the VKSW from the point of view of fractal dimension or local self-similarity.As a result, we achieve the goal of bridging the golden ratio to the VKSW as well as selfsimilarity of random data, establishing a new outlook of data following the VKSW.
The rest of the paper is organized as follows.The preliminaries are briefed in Section 2. The results are given in Section 3, which is followed by conclusions.

Preliminaries
2.1.Golden Ratio.One of the conventional ways to deduce the golden ratio  is to solve the difference equation that produces the Fibonacci sequences.The equation is given by (see, e.g., [1], Jamieson [46], Ranum [47], and Eggar [48]) Denote by   () the -transform of ().Then, doing the transform on both sides of (2) yields The above expression can be rewritten as The solutions to (4) are expressed by ( The golden ratio equals  1 ; that is, In addition,

Fractional Oscillators.
There are three types of fractional oscillators.The conventional type, see, for example, Achar et al. [49,50], is given by The second type was introduced by Lim and Muniandy [51].
It is in the form The third type introduced by Lim and Teo [52] is expressed by The symbol     is a fractional differential operator; see, for example, Eab and Lim [53,54], Lim et al. [55], Klafter et al. [56], Machado et al. [57], and Cattani [58].In what follows, we use (10) in the general sense.
We now consider the fractional differential equation with the coefficient  in the form where () is a white noise.Then, the solution to (11) is the fractional Ornstein-Uhlenbeck (OU) process [59], referring to Coffey et al. [60] for the meaning of OU process.

Results
Denote that  fOU () is the impulse response function of (11).Then, it is the solution to the following equation with zero initial conditions where () is the Dirac- function.Doing the Fourier transforms on both sides of the above equation yields where  fOU () is the Fourier transform of  fOU ().
Let   fOU () be the PSD of  fOU ().Then,   fOU () is given by Thus, we have the theorem below.
From Theorem 1, we obtain the following corollary.
Corollary 2 (modified VKSW).Let  vk () be the random function that is governed by the fractional differential equation given by Then, its solution in frequency domain is in the form The proof is straightforward and omitted consequently.
From Theorem 1 and Corollary 2, we immediately have the remark below.
Remark 3. The VKSW may be approximately expressed by the golden ratio.
As a matter of fact, Thus, ( 16) approximately equals (18).This may not be a simple approximation but substantially develops the implication of the VKSW from the point of view of the golden ratio.Note that there are errors in measuring real random data [61][62][63] and computation errors [64][65][66].Thus, from a view of practice, the power of the VKSW may not exactly be the value of 5/6 in most cases in engineering.Rather, it may be in the form where  is error.Thus, by using the golden ratio, ( 18) is quite reasonable to characterize random functions that obey the VKSW.
For the purpose of exhibiting the results in time domain, we denote by  and  −1 the operator of the Fourier transform and its inverse, respectively.Then, we get the theorem below. ) where where  ̸ = 1, 3, . ... Note that Then, denoting  vk () is the inverse Fourier transform of  vk (), one has The fractal dimension of a process can be determined by its autocorrelation function (ACF) for  → 0 [69].Thus,  vk (0) −  vk () ∼ || (−1)/2 for  → 0.
Therefore, with the probability one [69], the fractal dimension of the modified von Karman process based on the golden ratio is given by Approximately, it is expressed by Note that fractal dimension is a measure of local selfsimilarity, irregularity, or roughness [70].High value of fractal dimension of a sample path implies high irregularity of that path.Thus, (26) means that the modified von Karman process with the golden ratio has considerable local irregularity.
We would like to call out the work described above as the golden ratio phenomenon of the von Karman process.From the point of view of our work in data science or big data, this research may not be enough.The future work will investigate possible golden ratio phenomena in other topics of data such as those discussed in [71][72][73][74][75][76][77][78][79][80][81][82], exploring laws associating with the golden ratio in the universe.

Conclusions
We have given the derivation of the von Karman spectrum based on the fractional differential equation (10).The results suggest that the process obeying VKSW is in the class of fractional OU processes.Moreover, we have explained the reasons why the VKSW may be described from the point of view of the golden ratio.The fractal dimension of random data obeying the VKSW by using the golden ratio has also been discussed.

Theorem 4 .
The inverse Fourier transform of 1/[1+(2) 2 ] /2 is given by V () is the modified Bessel function of second kind or the MacDonald function and  is the time lag.