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Okinawa Institute of Science and Technology – Taylor–Couette (OIST-TC): a new experimental set-up to study turbulent Taylor–Couette flow

Published online by Cambridge University Press:  13 December 2024

Christian Butcher
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Julio M. Barros
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Yasuo Higashi
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Henry C.-H. Ng
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Tinihau Meuel
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Gustavo Gioia
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
Pinaki Chakraborty*
Affiliation:
Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan
*
*Corresponding author. E-mail: pinaki@oist.jp

Abstract

We present the Okinawa Institute of Science and Technology – Taylor–Couette set-up (OIST-TC), a new experimental set-up for investigating turbulent Taylor–Couette (TC) flow. The set-up has independently rotating inner and outer cylinders, and can achieve Reynolds numbers up to $10^6$. Noteworthy aspects of its design include innovative strategies for temperature control and vibration isolation. As part of its flow-measurement instrumentation, we have implemented the first ‘flying hot-wire’ configuration to measure the flow velocity whilst either or both cylinders are rotating. A significant challenge for obtaining reliable measurements from sensors within the inner cylinder is the data distortion resulting from electrical and electromagnetic interference along the signal pathway. Our solution involves internal digitization of sensor data, which provides notable robustness against noise sources. Additionally, we discuss our strategies for efficient operation, outlining custom automation tools that streamline both data processing and operational control. We hope this documentation of the salient features of OIST-TC is useful to researchers engaged in similar experimental studies that delve into the enchanting world of turbulent TC flow.

Information

Type
Case Study
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press
Figure 0

Figure 1. An annotated photograph of OIST-TC.

Figure 1

Figure 2. Cylinders. (a) A volumetric rendering of the inner and outer cylinders, shaft, and top and bottom flanges. (b) A photograph of the cylinders and their surroundings. (c) Examples of flow visualization at ${Re_i} = 5550$ (top) and ${Re_i} \approx 1.4 \times 10^5$ (bottom) (see figure S1 in SM for details). Consistent with previous studies (see, e.g. figure 5 in Lathrop, Fineberg & Swinney 1992b), Taylor vortices are clearly visible at ${Re_i} = 5550$ but are difficult to discern at ${Re_i} \approx 1.4 \times 10^5$.

Figure 2

Figure 3. Temperature control. (a) A volumetric rendering of the new design for the top flange's coolant feeding system. (b) Zoomed-in view of the contact between the graphite rings and ceramic plate. (c) Temperature time series from three temperature sensors at three axial locations (top, middle and bottom) in the middle section of the inner cylinder. The working fluid is water. The data correspond to ${Re_i} = 2.6 \times 10^5$ and ${Re_o} = 0$. Lines of different colours correspond to the three locations. The thin lines represent the data from the sensor, sampled every second. The thick lines represent the corresponding moving average over one minute. The slope of the linear trend line for each sensor is <0.01 $^\circ$C h$^{-1}$, signalling that the temperature is approximately constant in time. Also note that there is no discernible temperature difference between the three locations, signalling that the temperature is uniform in space.

Figure 3

Figure 4. A volumetric rendering of the CTA probe mounted on the inner cylinder in the flying hot-wire configuration. The probe causes minimal disturbance on the azimuthal flow as its blockage area is only $\approx$0.1 % of the cross-sectional flow area (in the axial–radial plane).

Figure 4

Figure 5. Sensors. (a) Locations of sensors for measuring torque and temperature. (b) A volumetric rendering of the torque sensor and its coupling flanges. Also depicted are the temperature and torque PCBs. All these items are located in the middle section of the inner cylinder.

Figure 5

Figure 6. Dimensionless mean-velocity profile across the radial gap. We show LDV data from OIST-TC (${Re_i} \approx 84\,000$, $\eta _r = 0.747$) and, for reference, particle image velocimetry (PIV) data from $\text {T}^3\text {C}$ (Huisman et al. 2013b) (${Re_i} \approx 100\,000$, $\eta _r = 0.716$). For both cases, ${Re_o} = 0$. We normalize $U_\theta (r)$ using $U_i \equiv U_{\theta }(r = R_i)=\varOmega _iR_i$. We normalize the gap as $\tilde {r}=(r-R_i)/(R_o-R_i)$. The spatial resolution of the LDV profile is $0.285$ mm and the PIV profile is $0.15$ mm. For ease of comparing the two profiles, we plot the data points undersampled at a resolution $\Delta \tilde {r} \approx 0.015$. The LDV profile starts at $\tilde {r} \approx 0.02$; reflections from the inner-cylinder wall make it difficult to measure the velocity at small $\tilde {r}$ (see, e.g. van Gils et al. 2012).

Figure 6

Figure 7. Energy spectra. (a) Dimensionless $E(k)$ from flying hot-wire (solid lines) and LDV (dot-dashed lines) at ${Re_i}\approx 32\,500$ and ${Re_o} = 0$. See table 1 for the experimental parameters. Inset: dimensionless dissipation spectrum, $k^2 E(k) \eta ^3/\nu ^2$ vs $k\eta$. Note that only the flying hot-wire data clearly resolve the peak of the dissipation spectrum. The dashed vertical lines mark the locations of $k_{max} \eta$ for the flying hot-wire and LDV spectra. (b) Local slope of the spectrum in panel (a). We compute the slope over a span of $\log _{10}(k d) = 0.3$. The error bars correspond to the $95$ % confidence interval of the linear fit of $\log _{10}(E(k))$ over the span. The slope $-5/3$, which corresponds to an energy cascade, is marked. Similar to the findings of Lewis & Swinney (1999), note the absence of an inertial range.

Figure 7

Table 1. Experimental parameters for the data plotted in figure 7. Here, $l$ is the length of the hot-wire, $f$ is the data-acquisition frequency, $k_{max}$ is the maximum resolved wavenumber of the energy spectrum, $\eta$ is the Kolmogorov length scale and $(a,b)$ are the lengths of the major and minor axes of the spheroidal LDV probe volume. We compute $\eta$ by using the approach discussed in Cerbus et al. (2020). We estimate $k_{max}$ from the inflection point of the dissipation spectrum, $k^2 E(k)$ (Cerbus et al. 2020). Note that the flying hot-wire spectrum extends deeper into the dissipative range ($k_{max} \eta \sim 0.5$) as compared with the LDV spectrum ($k_{max} \eta \sim 0.2$); see figure 7(a) (inset).

Figure 8

Figure 8. (a) Dimensionless torque, $G({Re_b},Ro^{-1})$, vs ${Re_b}$ for $10$ values of $Ro^{-1}$. We also plot error bars, which we compute using uncertainty propagation of the standard error of the mean corresponding to the $95$ % confidence interval. The black solid line represents the ${G_0}$ curve from the von Kármán-Prandtl theory: ${Re_b}/\sqrt {{G_0}} = N\log _{10}(\sqrt {{G_0}}) + M$, where $N$ and $M$ are empirical constants. (Fitting our data yields $N = 1.62$ and $M = -1.97$.) (b) Scaled $G$, $G/{G_0}$, vs $Ro^{-1}$ for the data shown in panel (a). Note the sharp peak at $Ro^{-1} \approx -0.25$. The black and green lines, showing linear dependence of $G/{G_0}$ with $Ro^{-1}$ on both sides of the peak, are added as a guide to the eye.

Supplementary material: File

Butcher et al. supplementary movie 1

Flow visualization at Rei = 5500
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Supplementary material: File

Butcher et al. supplementary movie 2

Flow visualization at Rei = 138,774
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Supplementary material: File

Butcher et al. supplementary material 3

Butcher et al. supplementary material
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