Turbulence prediction device, turbulence prediction method, turbulence prediction program, turbulence control system, turbulence control method, and turbulence control program

Abstract

To provide a turbulence prediction device enabling general prediction of turbulence without the need for prior data.SOLUTION: A prediction device for turbulence generated in fluid flowing through a channel includes: a time-series data generation unit that creates time-series data of a physical quantity for evaluating the turbulence by direct numerical computation; and a prediction value calculation unit that calculates the predicted value of the physical quantity at a future prediction time continuous with the time-series data created by the time-series data generation unit, by using a nonlinear prediction method.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a turbulent flow prediction device, a turbulent flow prediction method, a turbulent flow prediction program, a turbulent flow control system, a turbulent flow control method, and a turbulent flow control program for turbulent flow occurring on the outer wall of an aircraft, the inner wall of a fluid transport pipe, etc.

Background Art

[0002] As a technique related to the control of turbulent flow occurring on a wall surface in contact with a fluid, such as the outer wall of an aircraft or the inner wall of a fluid transport pipe, there is a technique disclosed in Patent Document 1 below. In this Patent Document 1, "diagnosis of the state of the flow field is performed based on various flow quantities measured by fluid measurement means, the instability of the flow is predicted using information in a knowledge database related to fluid instability, and when it is determined that there is a precursor to the transition to turbulent flow or the separation of the flow, the most effective instability that can be obtained from the knowledge database related to fluid instability is extracted in order to generate a variation in the direction to cancel it" is described.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the technique described in Patent Document 1 above, in order to predict the instability of the flow, it is necessary to previously hold a knowledge database related to fluid instability. Therefore, it is impossible to predict and control turbulent flow for unstable flows without prior information, and it lacks versatility.

[0005] Therefore, an object of the present invention is to provide a turbulent flow prediction device, a turbulent flow prediction method, and a turbulent flow prediction program that can generally predict turbulent flow without requiring prior data, and to provide a turbulent flow control system, a turbulent flow control method, and a turbulent flow control program that can generally control turbulent flow.

Means for Solving the Problems

[0006] The present invention for achieving such an object is a turbulent flow prediction device for turbulent flow generated in a fluid flowing through a flow path, comprising: a time series data creation unit that creates time series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; and a predicted value calculation unit that calculates a predicted value of the physical quantity at a future prediction time consecutive to the time series data created by the time series data creation unit by a non-linear prediction method.

Effects of the Invention

[0007] According to the present invention, by creating time series data by direct numerical calculation at the time of executing prediction and using this for prediction and control of turbulent flow, it is possible to provide a turbulent flow prediction device, a turbulent flow prediction method, a turbulent flow prediction program, a turbulent flow control system, a turbulent flow control method, and a turbulent flow control program that can generally predict turbulent flow without requiring prior data related to the flow.

Brief Description of the Drawings

[0008]

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Mode for Carrying Out the Invention

[0009] Hereinafter, a turbulent flow prediction device, a turbulent flow prediction method, a turbulent flow prediction program, a turbulent flow control system, a turbulent flow control method, and a turbulent flow control program according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0010] ≪Turbulent Flow Control System≫ FIG. 1 is a schematic diagram showing the configuration of a turbulent flow control system 1 according to an embodiment. The turbulent flow control system 1 shown in FIG. 1 includes a measurement device 10, a turbulent flow prediction device 20, and a fluid supply device 30. Hereinafter, these elements constituting the turbulent flow control system 1 will be described.

[0011] <Measurement Device 10> The measurement device 10 is a measurement means for measuring a physical quantity that can be an index for evaluating turbulent flow, and acquires the physical quantity as time-series data. The physical quantity measured by the measurement device 10 is, for example, a flow velocity or a pressure. FIG. 2 is a diagram for schematically explaining a flow path 200a of a fluid 200 in an embodiment. As shown in FIG. 2, in the present embodiment, a flow path 200a in which the fluid 200 flows in one direction on a single wall surface 100 is assumed, and the flow direction X of the fluid 200 with respect to the wall surface 100, the height direction Y from the wall surface 100, and the width direction Z of the wall surface 100 perpendicular to the flow direction X will be described.

[0012] Referring to FIGS. 1 and 2, the measurement device 10 measures, for example, the flow velocity and pressure at a dimensionless predetermined height position [y + =[y1] from the wall surface 100 for each local portion of the wall surface 100 that the fluid 200 contacts, as physical quantities for evaluating turbulent flow. Here, as an example, the measurement device 10 measures the flow velocity and pressure at a dimensionless predetermined height position [y +The flow velocity in the height direction Y at [y1] is measured as the above physical quantity. Note that the flow velocity is not limited to one direction in the height direction Y and may be the flow velocities in three directions. Note that the measuring device 10 also constitutes a turbulent flow prediction device together with the turbulent flow prediction device 20 described below.

[0013] Here, the local area where the above physical quantity is measured is the size of the lattice in the direct numerical simulation (DNS) described later. This size, that is, the local range, is set based on the type of fluid and the flow path conditions. For example, assume a Reynolds number Reb = 5600 (friction Reynolds number Re_tau is about 180). When the working fluid is air (20 °C), the flow path half-width is 5 cm, and the average velocity is 8.4 m / s, the local range is preferably the flow direction X × width direction Z = 0.2 cm × 0.1 cm or less. Note that the flow path half-width of 5 cm is the value when assuming that the total width of the flow path is 10 cm and the fluid flows between infinitely wide parallel plates with a gap of 10 cm between the parallel plates.

[0014] <Turbulent flow prediction device 20> The turbulent flow prediction device 20 is a device for predicting the turbulent flow 201 generated in the fluid 200 flowing through the flow path 200a. The turbulent flow prediction device 20 is a so-called computer and includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and a network interface. The turbulent flow prediction device 20 predicts the turbulent flow by the CPU reading the turbulent flow prediction program from the ROM and expanding it into the RAM, and then the CPU executing the expanded program.

[0015] Such a turbulent flow prediction device 20 has each functional part of a time series data creation part 21 and a predicted value calculation part 22. The time series data creation part 21 creates time series data of physical quantities for evaluating the turbulent flow 201 by direct numerical calculation. Also, the predicted value calculation part 22 is for the future prediction time [T continuous with the time series data +The predicted value of the physical quantity in [] is calculated by a non-linear prediction method. Note that the future prediction time [T + is the future time after a predetermined time has elapsed from the final time of the time-series data created by the time-series data creation unit 21. The procedure for turbulent flow prediction performed by these time-series data creation unit 21 and predicted value calculation unit 22 will be described in the subsequent turbulent flow prediction method and turbulent flow control method.

[0016] <Fluid supply device 30> Based on the predicted value calculated by the predicted value calculation unit 22 of the turbulent flow prediction device 20, the fluid supply device 30 supplies, to the turbulent flow 201 in the flow path 200a, the fluid of the physical quantity that cancels out the predicted value at the time when the future prediction time [T + is reached. Such a fluid supply device 30 sucks the control fluid 200 from each local part of the wall surface 100 in contact with the fluid 200 at each suction speed and each suction amount, and also supplies the fluid 200 at each supply speed and each supply amount.

[0017] Such a fluid supply device 30 has a suction hole 30a and a supply hole 30b for the fluid 200 arranged on the wall surface 100. These suction holes 30a and supply holes 30b may be provided individually, or may be configured to use a common hole part as the suction hole 30a or the supply hole 30b by switching according to the situation. Further, the fluid supply device 30 has a drive control unit 31 for controlling the suction of the fluid from each suction hole 30a and the supply of the fluid from each supply hole 30b.

[0018] The suction holes 30a and the supply holes 30b are distributed in a mixed state over the entire area of the wall surface 100. The supply direction and suction direction of the fluid 200 from each suction hole 30a and each supply hole 30b are, for example, the height direction Y perpendicular to the wall surface 100.

[0019] The drive control unit 31 is also a computer similar to the turbulent flow prediction device 20. Based on the turbulent flow prediction by the turbulent flow prediction device 20, the CPU reads the turbulent flow control program from the ROM and expands it in the RAM, and then the CPU executes the expanded program. Thereby, the suction of the fluid from each suction hole 30a and the supply of the fluid from each supply hole 30b are controlled, and the turbulent flow 201 generated in the fluid 200 flowing through the flow path 200a is controlled. Such a drive control unit 31 may be incorporated in the turbulent flow prediction device 20. Note that the procedure for controlling the turbulent flow by the drive control unit 31 will be described in the subsequent turbulent flow control method.

[0020] ≪Turbulent Flow Control Method≫ Next, the turbulent flow control method according to the embodiment will be described. The turbulent flow control method described here includes the procedure for turbulent flow prediction implemented by the turbulent flow prediction program included in the turbulent flow prediction device 20 in the turbulent flow control system 1, and the procedure for turbulent flow control implemented by the fluid control program included in the drive control unit of the fluid supply device 30. FIG. 3 is a schematic diagram for explaining the procedure for predicting turbulent flow. Hereinafter, with reference to FIGS. 1 to 3, the turbulent flow control method including the turbulent flow prediction method will be described.

[0021] <Procedure for Predicting Turbulent Flow> [First Step] First, the time-series data creation unit 21 of the turbulent flow prediction device 20 creates time-series data 301 (see FIG. 3) of physical quantities for evaluating turbulent flow by direct numerical calculation (simulation) based on fluid dynamics. The time-series data creation unit 21 performs direct numerical calculation based on the physical quantities measured by the measuring device 10 and the physical property information about the wall surface 100, and creates the above-described time-series data of physical quantities. Here, as an example, for each local part of the wall surface 100, the flow velocity in the height direction Y at the dimensionless predetermined height position [y + =[y1] from the wall surface 100 is used as the physical quantity for evaluating turbulent flow. In this case, the physical quantity [x(t)] on the vertical axis in FIG. 3 is the flow velocity in the height direction Y.

[0022] [Second Step] Next, the prediction value calculation unit 22 of the turbulent flow prediction device 20 embeds the time series data 301 in the high-dimensional phase space 302 (see FIG. 3), and describes the time series data 301 as a group of deterministic orbits in the high-dimensional phase space 302.

[0023] Here, whether the time series data 301 can be described as a group of deterministic orbits in the high-dimensional phase space 302 depends on whether the turbulent flow 201 formed by the fluid 200 is deterministic chaos, that is, whether the time series data of the physical quantity (here, velocity) for evaluating the turbulent flow 201 exhibits deterministic chaos. Therefore, the inventor confirmed that the time series data of the physical quantity (here, velocity) for evaluating the turbulent flow 201 exhibits deterministic chaos as follows.

[0024] FIG. 4 is a diagram showing the time series data 301 of the physical quantity of the turbulent flow. As shown in FIG. 4, the inventor calculated the time series data 301 of the physical quantity for evaluating the turbulent flow by simulation based on direct numerical calculation in fluid dynamics. The turbulent flow in this case is channel turbulent flow between parallel plates, and is fully developed turbulent flow with a Reynolds number of Reb = 5600. The physical quantity is the flow velocity [μ + in the flow direction X of the fluid at the dimensionless predetermined height position [y + = [y1] from the wall surface 100.

[0025] The inventor encoded the time-series data 301 thus obtained using information theory based on symbolic dynamics, and calculated the information entropy [St] quantified as the amount of information. As a result, it was confirmed that the calculated information entropy [St] was 0.6 or more, and the time-series data 301 of the physical quantity for evaluating turbulent flow exhibited deterministic chaos. Thereby, it was confirmed that the time-series data 301 of the physical quantity regarding turbulent flow can be described as a group of deterministic orbits in the high-dimensional phase space 302. Note that it is as described in "Hiroya Mamori et al.", "Publication date: August 29, 2023", "Dynamic state of a low-Reynolds-number turbulent channel flow", "Physical Review E", "Volume 108", "Issue 2", "Page 025105" (https: / / journals.aps.org / pre / abstract / 10.1103 / PhysRevE.108.025105) that time-series data with an information entropy [St] of 0.6 or more exhibits deterministic chaos.

[0026] [Third step] Returning to FIGS. 1 to 3, the turbulent flow prediction device 20 calculates a predicted value 303 of a physical quantity (here, the flow velocity in the height direction Y) by a non-linear prediction method focusing on the orbits in the phase space 302. This predicted value 303 is data of the flow velocity at the future prediction time [T + , and is the flow velocity in the height direction Y at a dimensionless predetermined height position [y + =[y1] from the wall surface 100 for each local portion of the wall surface 100. Further, by performing the above processing at a predetermined sampling time interval [τ + , time-series data of predicted values (hereinafter referred to as time-series prediction data 304) can be obtained.

[0027] Note that in FIG. 4 above, the time-series prediction data 304 predicted by the non-linear prediction method is shown by a broken line. It was confirmed that this time-series prediction data 304 well reproduced the time-series data (solid line) 301 obtained by direct numerical calculation, indicating that accurate prediction was achieved.

[0028] <Turbulent flow control procedure> Subsequently, the drive control unit 31 of the fluid supply device 30, at the time when the future prediction time [T + is reached, based on the predicted value 303 calculated by the turbulent flow prediction device 20, sucks and supplies the fluid 200 from the suction holes 30a and supply holes 30b provided at each local part of the wall surface 100. At this time, the drive control unit 31 sucks the fluid 200 from each suction hole 30a and supplies the fluid 200 from each supply hole 30b at a speed that cancels out the flow velocity in the height direction Y indicated by the predicted value at the time when the future prediction time [T + is reached. Thereby, the turbulent flow 201 generated in the fluid 200 flowing on the wall surface 100 is controlled.

[0029] ≪Effects of the embodiment≫ According to the embodiment described above, time-series data of physical quantities for evaluating turbulent flow is directly created by numerical calculation, and based on this time-series data, the predicted value of the physical quantity is calculated by the turbulent flow non-linear prediction method. Therefore, it is possible to predict turbulent flow without requiring preliminary data about the fluid and the flow path.

[0030] Furthermore, when the future prediction time at which the physical quantity for evaluating turbulent flow becomes the predicted value is reached, by supplying the fluid of the physical quantity that cancels out the predicted value to the flow path to control the turbulent flow, control without time delay with respect to the predicted value of the physical quantity is possible. Thereby, it is possible to effectively suppress the generation of turbulent flow, and for example, it is possible to suppress the energy loss in an airplane, a fluid transport pipe, etc.

Example

[0031] FIG. 5 is a diagram showing an instantaneous turbulent flow field in the vicinity of the wall surface. FIG. 5(a) shows the turbulent flow field calculated by direct numerical calculation, and FIG. 5(b) shows the turbulent flow field calculated by the non-linear prediction method of the embodiment. The correlation value between the turbulent flow field in FIG. 5(a) and the turbulent flow field in FIG. 5(b) is 0.9, and it was confirmed that they match well. Thereby, it was confirmed that the turbulent flow prediction method of the present embodiment enables highly accurate turbulent flow prediction.

[0032] FIG. 6 is a distribution diagram of information entropy obtained from time-series data of physical quantities. FIG. 6(a) is a distribution diagram of information entropy obtained by direct numerical calculation, and FIG. 6(b) is a distribution diagram of information entropy calculated by the non-linear prediction method of the embodiment. The vertical axis represents the coordinate representing the distance from the wall surface by the wall index, and the horizontal axis represents the sampling time interval [τ + . When comparing the distribution diagram of FIG. 6(a) with the distribution diagram of FIG. 6(b), it was confirmed that the distribution diagram calculated by the non-linear prediction method of the embodiment in FIG. 6(b) well reproduced the distribution diagram based on the direct numerical calculation in FIG. 6(a).

[0033] Quantitatively, at a distance from the wall surface [y+]=4, the velocity at a time [T + =8.6 in the future in terms of the viscous scale could be predicted with a high correlation value (C = 0.9). Also, at a position far from the wall surface [y + =35, the correlation value (C = 0.9) was obtained at a future prediction time [T + =2.2, and the predictable time decreased. From this, it was confirmed that there is a difference in the predictable time depending on the measurement position of the physical quantity for evaluating turbulence. Therefore, it is important to set the measurement position of the physical quantity and the future prediction time [T + (sampling time interval [τ + ) in association.

[0034] FIG. 7 is a diagram showing the result of performing turbulence control by applying the embodiment. Here, for the turbulent flow in a parallel plate channel with a low Reynolds number, the turbulent flow of longitudinal vortices as shown in FIG. 1 was detected by a virtual sensor, and turbulence control was performed by supplying (suctioning) a fluid of a physical quantity that cancels out this turbulent flow from the wall surface. Also, this turbulence control was performed for each of the sampling time intervals [τ + =0.9, 1.8, 2.7. The horizontal axis in FIG. 7 is the elapsed time from the start of control, and the vertical axis is the reduction rate [RD] of the frictional resistance. The larger the reduction rate [RD], the more the frictional resistance of the turbulent flow decreases.

[0035] As shown in Fig. 7, it was confirmed that by controlling the turbulent flow to which this embodiment is applied, the reduction rate RD increases and the frictional resistance of the turbulent flow can be suppressed. Also, at the height from the wall surface where a sensor was virtually installed here, it was confirmed that the shorter the sampling time interval + , the higher the effect of suppressing the frictional resistance.

Explanation of Reference Numerals

[0036] 1... Turbulent flow control system 2... Turbulent flow prediction device 20... Turbulent flow prediction device 21... Time series data creation unit 22... Predicted value calculation unit 30... Fluid supply device 30a... Suction hole 30b... Supply hole 31... Drive control unit 100... Wall surface 200... Fluid 200a... Flow path 201... Turbulent flow 301, 301’... Time series data 302... Phase space 303... Predicted value 304... Time series prediction data

Claims

1. A turbulent flow prediction device for a fluid flowing through a flow path, comprising: a time series data creation unit that creates time series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; and a predicted value calculation unit that calculates a predicted value of the physical quantity at a future prediction time consecutive to the time series data created by the time series data creation unit by a non-linear prediction method. A turbulent flow prediction device.

2. The physical quantity is at least one of a flow velocity and a pressure measured at a predetermined height with respect to a wall surface constituting the flow path. The turbulent flow prediction device according to Claim 1.

3. The predicted value calculation unit describes the time series data as a group of orbits in a phase space, and calculates a predicted value of the physical quantity by a non-linear prediction method based on the group of orbits. The turbulent flow prediction device according to Claim 1.

4. A method for predicting turbulent flow in a fluid flowing through a flow path, comprising: a procedure for creating time series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; and a procedure for calculating a predicted value of the physical quantity at a future prediction time consecutive to the time series data created by the direct numerical calculation by a non-linear prediction method. A turbulent flow prediction method.

5. A turbulent flow prediction program for causing a computer to execute prediction of turbulent flow in a fluid flowing through a flow path, the program causing: a time series data creation unit to create time series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; and a predicted value calculation unit to calculate a predicted value of the physical quantity at a future prediction time consecutive to the time series data by a non-linear prediction method. A turbulent flow prediction program.

6. A turbulent flow control system for controlling turbulent flow in a fluid flowing through a flow path, comprising: the turbulent flow prediction device according to any one of Claims 1 to 3; and a fluid supply device that supplies, to the flow path, a fluid of a physical quantity that cancels out the predicted value calculated by the predicted value calculation unit in the turbulent flow prediction device at the time when the future prediction time is reached. A turbulent flow control system.

7. The fluid supply device includes: a supply hole that supplies the fluid from a wall surface constituting the flow path; a suction hole that sucks the fluid from the wall surface; and a drive control unit that controls supply of the fluid from the supply hole and suction of the fluid from the suction hole based on the predicted value calculated by the predicted value calculation unit. The turbulent flow control system according to Claim 6.

8. The physical quantity is the flow velocity in the height direction measured at a predetermined height with respect to the wall surface constituting the flow path. The drive control unit controls the supply velocity of the fluid from the supply hole and the suction velocity of the fluid from the suction hole based on the predicted value. The turbulent flow control system according to claim 7.

9. A turbulent flow control method for controlling turbulent flow generated in a fluid flowing through a flow path, comprising: a procedure for creating time-series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; a procedure for calculating a predicted value of the physical quantity at a future prediction time consecutive to the time-series data created by the direct numerical calculation by a non-linear prediction method; a procedure for supplying, to the flow path, a fluid having a physical quantity that cancels out the predicted value calculated by the non-linear prediction method at the time when the future prediction time is reached. Turbulent flow control method.

10. A turbulent flow control program for causing control of turbulent flow generated in a fluid flowing through a flow path, comprising: causing a time-series data creation unit to create time-series data of a physical quantity for evaluating the turbulent flow by direct numerical calculation; causing a predicted value calculation unit to calculate a predicted value of the physical quantity at a future prediction time consecutive to the time-series data by a non-linear prediction method; for causing a fluid supply device to supply, to the flow path, a fluid having a physical quantity that cancels out the predicted value calculated by the non-linear prediction method at the time when the future prediction time is reached. Turbulent flow control program.

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