## 1 Introduction
### New Research Scheme Proposal
With the concept of flow production control, two 3-D and one 2-D multiple-fan actively controlled wind tunnels were constructed at Miyazaki University. According to [PERSON] et al. [24], a 3-D multiple-fan actively controlled wind tunnel at Miyazaki University is an open-circuit wind tunnel with 99 fans, each with a diameter of 270 mm, arranged in a 9 \(\times\) 11 matrix. The test section is 15.5 m long, 2.6 m wide, and 1.8 m high, and the fans are driven by high-quality alternating current servo-motors through a computer, allowing them to be controlled at different frequencies of up to approximately 25 Hz. This enables fluctuating air flow in the test section, and, since the 99 fans can be programmed independently to deliver variable flows, phase shifts can be introduced among the fans, allowing transverse and vertical turbulence to be generated. Using the power spectrum modification method or time-lag modification method [25], highly accurate stationary ABL flow fields were simulated in multiple-fan wind tunnels, with turbulence parameter profiles and Re stress identical to the targets [25]. Furthermore, by repeated modification of both power spectrum and phase of the input data to the fans, [PERSON] et al. [24] achieved simulation of velocity histories with sharp velocity changes. The power spectrum modification method adopted by [PERSON]. [24,25] in simulating non-stationary velocity fields follows the procedures below:  
1. Transform the velocity history into voltage data proportionally, and input the data to the motors of the fans through AD converters. Because of the mechanical inertia of the rotating parts of the motor and because of the inertia of the air inside the tunnel, the velocity history generated cannot be the same as the voltage data history inputted to the motors;
2. Modify the input data of the fans and drive the fans with new input data. Mathematically, the velocity history can be expanded to be the sum of a series in the frequency domain by fast Fourier transform (FFT). If the power spectrum and phase of the generated velocity history agree with the target ones well at each frequency, the generated velocity history will be very similar to the target one, and high correlation will be achieved between them. Thus, modification of the input data includes the modifications of power spectrum and phase. The methods are expressed in Equations (1) and (2): \[S_{i}^{(k+1)}(f)=\frac{S_{t}(f)}{S_{m}^{(k)}(f)}\times S_{i}^{(k)}(f)\] (1) \[\phi_{i}^{(k+1)}(f)=\phi_{i}^{(k)}(f)+\left\{\phi_{t}(f)-\phi_{m}^{(k)}(f)\right\}\] (2) where \(f\) is the frequency, \(S_{m}^{(k)}(f)\), \(\phi_{m}^{(k)}(f)\) are the power spectrum and phase of the generated flow resulted from the input data with \(S_{i}^{(k)}(f)\) and \(\phi_{i}^{(k)}(f)\), and \(S_{i}(f)\) and \(\phi_{t}(f)\) are the target power spectrum and phase. By conducting inverse FFT with \(S_{i}^{(k+1)}(f)\) and \(\phi_{i}^{(k+1)}(f)\), new input data of the fans can be obtained;
3. Repeat the modification of the input data of the fans until satisfactory results are achieved. Modification of the input data should be repeated several times until satisfactory results can be achieved. Capabilities of CFD Technique and Multiple-Fan Actively Controlled Wind Tunnel Technique According to the Present Research  
On the Fluent 6.2.16 platform, we tried to reproduce the non-stationary flow field for Pengcheng cooling tower site based on a velocity sample measured on location [26] employing the simulation approach reported in ref. [23]. After the numerical simulation, it is found that the simulated velocity samples near the inlet are close to the input velocity time-history (the simulation target); however, when the simulated sample is extracted from a location far away from the inlet, it deviates from the simulation target in both frequency and time domains.