If an Application Data Sheet (ADS) has been filed on the filing date of this application, it is incorporated by reference herein. Any applications claimed on the ADS for priority under 35 U.S.C. §§ 119, 120, 121, or 365(c), and any and all parent, grandparent, great-grandparent, etc. applications of such applications, are incorporated by reference, including any priority claims made in those applications and any material incorporated by reference, to the extent such subject matter is not inconsistent herewith.
The present application claims the benefit of the earliest available effective filing date(s) from the following listed application(s) (the “Priority Applications”), if any, listed below (e.g., claims earliest available priority dates for other than provisional patent applications or claims benefits under 35 U.S.C. § 119(e) for provisional patent applications, for any and all parent, grandparent, great-grandparent, etc. applications of the Priority Application(s)). In addition, the present application is related to the “Related Applications,” if any, listed below.
If the listings of applications provided above are inconsistent with the listings provided via an ADS, it is the intent of the Applicant to claim priority to each application that appears in the Priority Applications section of the ADS and to each application that appears in the Priority Applications section of this application.
All subject matter of the Priority Applications and the Related Applications and of any and all parent, grandparent, great-grandparent, etc. applications of the Priority Applications and the Related Applications, including any priority claims, is incorporated herein by reference to the extent such subject matter is not inconsistent herewith.
The claimed invention relates to drag reduction in a turbulent boundary layer of a fluid flow on a surface of an object and the power savings related to such drag reduction. Drag is a dissipative force created by fluid moving relative to an object. For example, a fluid moving through a pipe experiences a dissipative force that acts against the wall of the pipe. Similarly, a vehicle (e.g., a car, an airplane, a jet, a rocket, a boat, a ship, etc.) moving through air or water experiences a resistant force that acts against the movement of the vehicle. One component of this force is skin friction drag, which is created when fluid at the surface stops, slows down, or changes direction. This creates a turbulent boundary layer. A turbulent boundary layer of the fluid interacting with the surface of an object creates small-scale eddies close to the surface, which develop into large-scale eddies extending farther from the surface.
The systems and methods described herein are applicable to situations in which a fluid is moving relative to a stationary object, a fluid is moving relative to a moving object, and an object is moving relative to a fluid. For example, an airplane may be described as moving through stationary or quasi-stationary air, even though the air is likely flowing with various currents (e.g., updrafts, downdrafts, wind, etc.). For the sake of brevity and clarity, some examples are described herein in the context of an object moving through a fluid. However, the corollary situations in which the fluid is, alternatively or additionally, moving relative to the object are also implied.
The turbulent boundary layer impedes the motion of the object relative to the fluid around it. Throughout this disclosure, the turbulent boundary layer is characterized as including small-scale eddies and large-scale eddies. The turbulent boundary layer may include irregular fluid flows in the form of rotational vortices, irrotational vortices, currents, eddies, and other turbulent flows. Turbulent flows in the turbulent boundary layer can be generally characterized as exhibiting fluctuations in pressure and flow velocity.
For purposes of this disclosure, the term ‘small-scale eddy’ is used to describe near-wall turbulent flows with viscous length scales on the order of 100η or less and time scales on the order of 100η′ or less, as mathematically described in greater detail below. In contrast, the term ‘large-scale eddy’ is used herein to describe turbulent flows extending farther from the wall (and possibly not contacting the wall) that exist with time scales exceeding those of small-scale eddies. More specifically, a large-scale eddy is defined as having a time scale exceeding 300η′.
The ratio of inertial forces to viscous forces within a fluid moving relative to an object is referred to as the Reynolds number (Re), which is a dimensionless value. Throughout this disclosure, the term “fluid” is used to describe gasses, liquids, and combinations thereof. The Reynolds number increases as the size of the object and/or the speed of the object increases relative to the fluid. The Reynolds number also increases as the fluid kinematic viscosity decreases. Accordingly, the Reynolds number associated with the flow of a liquid through a pipe increases as the flow speed increases. At a given velocity for a fluid flow, the Reynolds number is higher for fluids with relatively low kinematic viscosity and lower for fluids with relatively high kinematic viscosity. The same principles apply to the motion of objects through air and other gasses (e.g., the motion of airplanes, vehicles, turbine blades, projectiles, rockets, missiles, and the like), as well as the motion of liquids relative to an object (e.g., a submarine moving through water or oil moving through a pipe).
As a flow over a surface becomes turbulent, a turbulent boundary layer is formed between the surface of the object and the flow far away from the surface (where the relative velocity of the fluid is at its free-stream value U∞). The large-scale eddies and the small-scale eddies in the flow contribute to the skin friction drag that slows the flow of the fluid and/or the movement of the object through the fluid. The local drag force acting on the surface (i.e., the “wall”) per unit area is the wall stress, τw. The wall stress has a time-average or mean value of
As previously described, the turbulent boundary layer includes turbulent flows of various sizes that can be classified as small-scale eddies or large-scale eddies. The smallest eddies have a characteristic length scale given by η=ν/uτ, where ν is the fluid kinematic viscosity and uτ is the friction velocity. This is often called the viscous length scale. The friction velocity, uτ, can be expressed as
where ρ is the fluid density. The smallest eddies have a characteristic time scale η′, which is defined as
Accordingly, the length scale, η, and the time scale, η′, of the smallest eddies can be characterized as:
The largest eddies in the turbulent boundary layer have a characteristic length scale, η0, equal to the boundary layer thickness, δ, and a characteristic time scale, η0′, equal to δ/U∞. In many common instances relating to practical applications of the presently described systems and methods, the friction velocity, uτ, is approximately 20-40 times smaller than the free-stream value, U∞.
In a turbulent boundary layer, the friction Reynolds number, Reτ, represents the ratio of the viscous length scale of the largest eddies to the viscous length scale of the smallest eddies, and is thus expressible as:
Accordingly, the range of scale between the large-scale eddies and the small-scale eddies in a turbulent boundary layer increases as the friction Reynolds number, Reτ, increases. By way of example, the friction Reynolds number, Reτ, associated with the flow of air over an airplane fuselage may be 100,000, while the friction Reynolds number, Reτ, associated with a fluid flowing through a large pipeline may exceed 1,000,000. As the friction Reynolds number, Reτ, increases, the relative contribution of the large-scale eddies to the production of turbulence, and therefore drag, increases.
Attempts to reduce skin friction drag have focused on mitigating or modifying small-scale eddies in flows with friction Reynolds numbers, Reτ, less than 1,000. Some of these approaches are described in the following publications, each of which is hereby incorporated by reference in its entirety to the extent allowed by law and assumed to be understood by one of skill in the art: Batchelor, An Introduction to Fluid Dynamics (Cambridge Mathematical Library), Cambridge University Press (2000), doi:10.1017/CBO9780511800955; Gatti et al., Reynolds-number dependence of turbulent skin friction drag reduction induced by spanwise forcing, Journal of Fluid Mechanics (2016), vol. 802, pp. 553-582; Corke et al., Active and Passive Turbulent Boundary layer Drag Reduction, AIAA Journal (October 2018), Vol. 56, No. 10, pp. 3835-3847; Kline et al., The structure of turbulent boundary layers, Journal of Fluid Mechanics (1967), Vol. 30, pp. 741-773; Mathis et al., Estimating wall-shear-stress fluctuations given an outer region input, Journal of Fluid Mechanics (2013), Vol. 715, pp. 163-180; Marusic et al., Predictive model for wall-bounded turbulent flow, Science (2010), Vol. 329(5988), pp. 193-196; Panton, Overview of the self-sustaining mechanisms of wall turbulence, Prog. Aerosp. Sci. (2001), Vol. 37, pp. 341-383; Smith et al., The characteristics of low-speed streaks in the near-wall region of a turbulent boundary layer, Journal of Fluid Mechanics (1983), Vol. 129, pp. 27-54; Smits et al., High Reynolds Number Wall Turbulence, Annu. Rev. Fluid Mech. (2011), Vol. 43, pp. 353-375; Alfredsson et al., Large-Eddy BreakUp Devices—a 40 Years Perspective from a Stockholm Horizon, Flow Turbulence Combust (2018), Vol. 100, pp. 877-888; Garcia-Mayoral et al., Drag reduction by riblets, Phil. Trans. R. Soc. A (2011), Vol. 369, pp. 1412-1427; Schoppa et al., A large-scale control strategy for drag reduction in turbulent boundary layers, Physics of Fluids (May 1998); Vol. 10(5), pp. 1049-51; and Gouder, Turbulent Friction Drag Reduction Using Electroactive Polymer Surfaces, Doctoral thesis, Imperial College, May 2011. Additional references relating to drag reduction include U.S. Pat. No. 8,074,938 titled “Active control of a body by altering surface drag,” by Hyde et al.; U.S. Pat. No. 8,074,939 titled “Active Control of Surface Drag,” by Hyde et al.; and U.S. Pat. No. 9,002,484 titled “System and method for deforming surfaces,” by Hyde et al., collectively referred to as “the Hyde Patents.”
Some of the disclosures identified above suggest drag reduction techniques in which components on a surface, or portions of the surface, are moved up and down at high frequency to disrupt small-scale eddies. The up and down movement described in these disclosures is not parallel or co-planar to the surface. Moreover, the disclosures identified above suggest approaches for reducing drag in fluid flows by modifying small-scale eddies in flows with friction Reynolds numbers, Reτ, less than 1,000. Many of the publications identified above assume that the high frequencies required for small-scale eddy actuation at friction Reynolds numbers, Reτ, greater than 1,500 are mechanically infeasible, cost-prohibitive, and/or result in a net power loss. The general consensus has been that drag reduction cannot be attained with a net power savings in fluid flows at friction Reynolds numbers, Reτ, greater than approximately 1,500. Additionally, the research has been focused primarily on actuating small-scale eddies, with some publications even predicting that almost no drag reduction can be attained by large-scale eddy actuation.
The focus on small-scale eddy actuation and the assumption that large-scale eddy actuation is not suitable for attaining drag reduction is likely due to the lack of simulations of fluid flows having high friction Reynolds numbers, Reτ; that is, friction Reynolds numbers, Reτ, exceeding 1,500. The computing power required to simulate fluid flows grows nonlinearly as the friction Reynolds number, Reτ, increases, and so most simulations have been practically limited to fluid flows with friction Reynolds numbers, Reτ, less than 1,000. The simulations at these relatively low friction Reynolds numbers, Reτ, lead to the prediction (shown to be incorrect by the inventors of the invention claimed herein) that large-scale eddy actuation is not an effective approach to reduce drag.
Accordingly, the existing literature teaches away from large-scale eddy actuation and does not provide any practical solutions (e.g., that provide a net power savings) for reducing drag in fluid flows that have friction Reynolds numbers, Reτ, greater than approximately 1,500. The existing literature does not suggest, and in some instances even teaches away from, large-scale eddy actuation via the injection of momentum parallel to the surface and transverse to the direction of the fluid flow.
As detailed above, existing publications predict that while drag reduction is possible, net power savings cannot be achieved using high-frequency actuation at friction Reynolds numbers, Reτ, exceeding 1,000. Furthermore, the spatial frequency and the temporal frequency of the momentum injection needed for increased or optimal drag reduction will increase as the friction Reynolds number, Reτ, increases. Therefore, at higher friction Reynolds numbers, Reτ, (e.g., above 1,500 and especially above 5,000 where many practical applications operate), it is impractical, difficult, or impossible with existing technologies to operate a momentum injection system at the high spatial and temporal frequencies necessary for direct modification of the small-scale eddies. Therefore, based on both theoretical and practical considerations, a different approach to transverse momentum injection is needed if net power savings is to be accomplished at commercial flow speeds and Reτ. The presently described systems and methods propose a new approach in which low-frequency transverse actuation is used to modify large-scale eddies to obtain net power savings.
The experiments described in U.S. Provisional Patent Application No. 63/155,408, titled “Turbulent Drag Reduction,” to which this application claims priority, demonstrate that efficient drag reduction (e.g., providing a net power savings) can be obtained in fluid flows that have high friction Reynolds numbers, Reτ, (e.g., greater than approximately 1,500). The experiments found that significant drag reduction was attainable in fluid flows with high friction Reynolds numbers through large-scale eddy actuation via the injection of momentum parallel to a surface and transverse to the flow of the fluid. This disclosure provides various systems and methods for controlling drag (e.g., reducing or increasing) in fluid flows that have friction Reynolds numbers, Reτ, exceeding 1,500 via large-scale eddy actuation.
The presently described systems and methods are applicable to a wide variety of fluids and surfaces that are in motion relative to one another. Examples of surfaces that may utilize the systems and methods described herein include, but are not limited to, fixed-wing aircrafts, rotary-wing aircrafts, rockets, missiles, projectiles, and the like. Additional examples include, but are again not limited to, various surfaces of a pipe, a pump, a fan, a turbine, a wind turbine, a mast, an airfoil, a hydrofoil, a sail, a boat rudder, a boat hull, a rocket nozzle, and a land vehicle.
The systems and method described herein may also be utilized to decrease or selectively increase friction within pipes or fluid vessels that operate to transport fluids, mix fluids, transfer heat from fluids, or manage chemical reactions of fluids. Examples of fluids for which in-plane, transverse momentum injection may decrease (or selectively increase) friction include, but are not limited to, air, water, gaseous mixtures, natural gas, various liquids, oil, and the like.
As described in greater detail below, a controller may control the actuation of any number of actuators, and multiple controllers and associated sets of actuators may operate in concert to achieve a target friction profile, friction reduction, or friction increase along one or more surfaces of an object that is in motion with respect to a fluid and/or a fluid that is in motion with respect to the object. Examples of suitable actuators that can be used to inject transverse momentum into the turbulent boundary layer in-plane with respect to the surface and at low frequencies to disrupt the large-scale eddies include, but are not limited to, piezoelectric actuators, electromagnetic actuators, electromechanical actuators, and dielectric-barrier discharge (DBD) devices.
For example, a controller may operate or actuate a plurality of actuators according to an actuation frequency, f, in Hz so that the period of the motion is given by T=1/f, and the angular frequency ω is defined as ω=2πf rad/s. In terms of the viscous time scale, η′, the period T can be expressed as a non-dimensional period, T+, (also referred to as a time-scale multiplier) defined as
For any given Reτ, η′ is constant. Recall, that small-scale eddies have time scales on the order of 100η′. Thus, when the controller is set to operate with a T+ in the order of 100, the actuation period (T) is similar to the timescale of (and therefore actuates) the small-scale eddies in the flow. Similarly, because large-scale eddies have time scales exceeding 300η′, when the controller is set to operate with a T+ of more than 300, the actuation period (T) is similar to the timescale of (and therefore actuates) the large-scale eddies in the flow.
The controller may identify the specific fluid flow characteristics of a turbulent boundary layer of the fluid. For example, the controller may be pre-programmed with specific data or use sensor data (e.g., in real-time) to measure characteristics of the fluid flow. Examples of fluid flow characteristics to be obtained from memory, a third-party server, or via sensor measurements include, but are not limited to, a mean or bulk velocity, U, a friction velocity, uτ, of the fluid, a kinematic viscosity, ν, of the fluid, and friction Reynolds numbers, Reτ, of the fluid.
The controller may calculate an actuation frequency, f, for transverse momentum injection along the surface (e.g., for in-plane momentum injection co-planar with the surface). The actuator frequency, f, may be selected to disrupt large-scale eddies in the turbulent boundary layer. Again, the terms “large-scale” and “small-scale” are used as descriptors to distinguish between two types of eddies in a turbulent boundary layer.
The controller may actuate the plurality of actuators on the surface of the object using the calculated or determined actuation frequency, f, to disrupt the large-scale eddies to selectively increase (or decrease) the drag of the fluid on the surface of the object. The actuation frequency, f, is selected based on the time scale multiplier, T+, that is at least 300, such that the low-frequency actuation disrupts large-scale eddies, as described herein. Alternatively, if the actuation frequency is known, the time scale multiplier, T+, is a function of the identified friction velocity squared, uτ2, divided by the product of (i) the calculated actuation frequency, f, and (ii) the identified kinematic viscosity, ν. Thus, the time scale multiplier, T+, is expressible as:
As an example, the controller may actuate the actuators on a time scale multiplier, T+, that is greater than 300 for fluid flows having friction Reynolds numbers, Reτ, greater than 1,500. According to various embodiments, the actuation frequency, f, is less than 20,000 Hz for friction Reynolds numbers, Reτ, greater than 1,500. In various embodiments, the systems and methods described herein may be utilized to create an adjustable friction surface. The adjustable friction surface may include one or more actuators (e.g., a plurality of actuators) positioned on a surface (e.g., extending slightly from the surface, co-planar with the surface, and/or recessed slightly beneath the surface). A controller may selectively increase or decrease the skin friction of a fluid flow by selectively actuating the actuators according to the principles described herein. Many existing computing devices and infrastructures may be used in combination with the presently described systems and methods. Some of the infrastructure that can be used with embodiments disclosed herein is already available, such as processors, microprocessors, microcontrollers, computer programming tools and techniques, digital storage media, and communication links. Many of the systems, subsystems, modules, components, and the like that are described herein may be implemented as hardware, firmware, and/or software. Various systems, subsystems, modules, and components are described in terms of the function(s) they perform because such a wide variety of possible implementations exist. For example, it is appreciated that many existing programming languages, hardware devices, frequency bands, circuits, software platforms, networking infrastructures, and/or data stores may be utilized alone or in combination to implement a specific function.
It is also appreciated that two or more of the systems, subsystems, components, modules, etc. that are described herein may be combined as a single system, subsystem, module, or component. Moreover, many of the systems, subsystems, components, and modules may be duplicated or further divided into discrete systems, subsystems, components, or modules to perform subtasks of those described herein. Any of the embodiments described herein may be combined with any combination of other embodiments described herein. Many of the embodiments of the systems and methods described herein that appear to be mutually exclusive may be used in combination as weighted functions of one another and/or in primary-backup configurations in which one embodiment is used primarily, and the other embodiment is available as a backup.
As used herein, a computing device, system, subsystem, module, or controller may include a processor, such as a microprocessor, a microcontroller, logic circuitry, or the like. A processor may include one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a programmable array logic (PAL) device, a programmable logic array (PLA), a programmable logic device (PLD), field-programmable gate array (FPGA), or another customizable and/or programmable device. The computing device or controller may also include a machine-readable storage device, such as non-volatile memory, static RAM, dynamic RAM, ROM, CD-ROM, disk, tape, magnetic, optical, flash memory, or another machine-readable storage medium. Various aspects of certain embodiments may be implemented using hardware, software, firmware, or a combination thereof.
The components of some of the disclosed embodiments are described and illustrated in the figures herein. Many portions thereof could be arranged and designed in a wide variety of different configurations. Furthermore, the features, structures, and operations associated with one embodiment may be applied to or combined with the features, structures, or operations described in conjunction with another embodiment. In many instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of this disclosure. The right to add any described embodiment or feature to any one of the figures and/or as a new figure is explicitly reserved.
The embodiments of the systems and methods provided within this disclosure are not intended to limit the scope of the disclosure but are merely representative of possible embodiments. In addition, the steps of a method do not necessarily need to be executed in any specific order, or even sequentially, nor do the steps need to be executed only once. As described above, descriptions and variations described in terms of transmitters are equally applicable to receivers, and vice versa.
The contribution of turbulence to the drag on the surface of the wall 175 is, at least in part, dependent upon mixing. For example, turbulent motions in the fluid 110 tend to homogenize flow properties such as momentum and heat, and thereby reduce bulk temperature and velocity gradients. This can be observed in turbulent boundary layers where the velocity gradients in the outer part of the boundary layer are small. However, the turbulent motions lead to very strong velocity gradients within a thin layer near the surface of the wall 175 since the velocity must obey a no-slip condition at the wall 175 (assuming the wall 175 is impermeable). Accordingly, a turbulent boundary layer of the fluid 110 proximate the wall 175 exhibits a higher skin friction drag than a laminar flow drag at the same free-stream velocity.
In terms of the turbulent velocity fluctuations, the wall-normal component, ν, is fundamental to the mixing process. A parcel of fluid 110 (e.g., a volume, a molecule, etc.) that moves from a lower location (e.g., location 130) on the mean velocity profile, ū(y), to a higher location (e.g., location 132) on the mean velocity profile, ū(y), has a positive fluctuation in velocity, ν, and a negative fluctuation in velocity, u, as compared to neighboring parcels of the fluid 110. In instances where the x-momentum of the parcel is conserved until it mixes upon arrival at the new location, the local value of the streamwise momentum is reduced.
Similarly, a parcel of the fluid 110 that moves from a higher location (e.g., location 130) on the mean velocity profile, ū(y), to a lower location (e.g., location 134) on the mean velocity profile, ū(y), has a negative fluctuation in velocity, ν, and a positive fluctuation in velocity, u, as compared to neighboring parcels of the fluid 110. Upon mixing, the parcel of the fluid 110 will increase the local value of the streamwise momentum. Wall-normal motions, therefore, tend to reduce velocity differences. Accordingly, momentum flux (i.e., when the kinematic Reynolds shear stress is equal to −
As provided by the Navier-Stokes equation, the total rate of change of momentum at any point near the wall 175 (approximately y/delta<0.15) in a zero-pressure gradient boundary layer that can be estimated by Equation 5 below:
∂(−
The total stress is expressed by the term in parentheses in Equation 5. By integration, we see that near the wall 175, the total stress is constant, and at the wall 175 where y=0 and ν=0, the total stress is equal to the wall shear stress, τω.
For approximately y/delta<0.15, the wall shear stress, can be estimated using Equation 6 below:
τω=(ν∂U/∂y)y=0=−
Accordingly, the total stress includes the turbulent part associated with −
The presently described systems and methods relate to transverse momentum injection that, as previously stated, is transverse or spanwise relative to the fluid flow direction and along the surface of the wall 175. While the surface of the wall 175 may be curved or otherwise non-planar, the transverse momentum injection is still described herein as being “co-planar” or “parallel” in the sense that the momentum is injected along the surface spanwise to the direction of the fluid flow.
W(x,t)=A sin(Kxx−ωt) Equation 7
In Equation 7, “W” is the transverse velocity, “A” is the transverse velocity magnitude, “Kx” is the wavenumber in the x-direction (inversely proportional to wavelength λ) and ω is the angular frequency. The non-dimensional time scale multiplier, T+, and the non-dimensional length scale, λ+, relate the physical variables, such as the wavelength, λ, and the angular frequency, ω, to the fluid properties. The fluid motion can be implemented in various ways, but the “A” and “ω” parameters are chosen based on the calculation of time scale multiplier using eta-prime (η′) and T+ values calculated using, for example, Equation 2 and Equation 4 above. In a similar way, the non-dimensional length scale, λ+, is defined as λ+=λ/η, which can also be used to choose a wavelength λ that affects the large-scale eddies. These non-dimensional scales thus facilitate comparisons of different flows and actuation mechanisms.
The systems and methods herein provide approaches to reduce the mixing action caused by large-scale eddies; that is, eddies that have characteristic time scales exceeding 300 η′. The systems, mechanical components, spacings, controllers, and functionality of the various components used to modify large-scale eddies are different from those used to impact small-scale eddies.
Existing approaches that utilize momentum injection have focused on direct modification of the small-scale eddies in fluid flows that have a relatively low friction Reynolds number, Reτ, (e.g., where Reτ is less than approximately 1,000). For fluid flows having relatively low friction Reynolds number, Reτ, the momentum is injected at very high spatial and temporal frequencies to directly affect the small-scale eddies. The injection of momentum at high spatial and temporal frequencies requires significant power to “pump” or otherwise move the fluid transversely and results in no net power savings and possibly even a net power loss. Additionally, the publications identified above suggest, and in some cases predict or model, that drag reduction decreases significantly when actuation is performed below an assumed optimum time scale multiplier, T+, of about 100.
The presently described systems and methods have been simulated and modeled via oscillatory surface actuation in a wind tunnel with friction Reynolds numbers, Reτ, between 6,000 and 13,000, as detailed in the provisional patent application(s) to which this application claims priority. The drag reduction accomplished via in-plane transverse momentum injection to disrupt large-scale eddies was measured directly via a large-scale drag balance (triangles) and indirectly via a hot-wire anemometer (circles). As illustrated, and contrary to earlier predictions, large-scale eddy actuation results in increased drag reduction as the friction Reynolds number, Reτ, increases.
In contrast, the graph 385 of W2 with respect to time, t, from t0 to tn illustrates the relatively slow motion of the surface actuators 360 based on a T+≥300. The relatively slow motion of the surface actuators based on a T+≥300 results in transverse momentum injection that affects the large-scale eddies in the turbulent boundary layer of the fluid flow 310 over the surface 320.
As is apparent via a comparison of
A transverse momentum injection system for low-frequency modification of large-scale eddies (e.g., those characterized as having time scales exceeding 300η′) may be incorporated into one or more surfaces of an aircraft (e.g., fuselage, wings, empennage, etc.), the blades or mast of a wind turbine, an airfoil, a hull of a ship, a control surface of a ship (e.g., a rudder), a ground-based vehicle (e.g., a train, a car, a truck, a bus, etc.), rockets, turbine blades, interior and exterior nacelle surfaces, exhaust cone surfaces, interior surfaces of heating and cooling system components (e.g., ductwork of HVAC systems), the interior of pipes and valves, and/or any of a wide variety of other surfaces that come into contact with any of a wide variety of fluids. Additional uses for transverse momentum injection systems configured to modify large-scale eddies in the turbulent boundary layer include fluid vessels for chemical reactions, fluid vessels for mixing, heat transfer fluid vessels, pipes, pumps, fans, turbine engines and fans, rocket nozzles, and the like.
While many of the embodiments and examples described herein relate specifically to reducing drag, the same principles and approaches can be operated in reverse to increase drag when warranted. As previously noted, in contrast to momentum injection approaches for affecting small-scale eddies, the systems and methods described herein implement transverse momentum injection along the surface (e.g., in-plane with respect to the surface or co-planar to the surface) at low actuation frequencies. For example, a transverse momentum injection system configured to modify and affect large-scale eddies may operate at a frequency between 10 Hertz and 10,000 Hertz.
According to various embodiments, a transverse momentum injection system includes a plurality of electronically controlled actuators on the surface of an object to modify large-scale eddies at time scale multipliers, T+, that are greater than 300 (i.e., T+>300) for fluid flows having any friction Reynolds number, Reτ. In some embodiments, a transverse momentum injection system to affect large-scale eddies via transverse momentum injection may operate at time scale multipliers, T+, that are greater than 300 in situations in which the friction Reynolds number, Reτ, exceeds 1,500.
In some embodiments, a transverse momentum injection system may be specifically configured to affect large-scale eddies in turbulent boundary layers where the streamwise length scale, L0+, defined as
is between 0.2 and 20. Specific embodiments of a transverse momentum injection system that are designed and adapted to affect large-scale eddies in turbulent boundary layers may be configured to operate with a streamwise actuation wavelength greater than 10 mm. In some embodiments, the transverse actuation velocity may be between 1% and 20% of free-stream velocity. In various embodiments, the transverse wavelength spacing between actuators in the transverse direction may be between δ/10 and δ/2.
Per
In each instance, actuation at a given Tosc+ affects a range of stresses. As the friction Reynolds number, Reτ, increases, proportionally more turbulence is present in higher T+ ranges. It follows that operating (i.e., actuating or oscillating) at a higher Tosc+ reduces large-scale eddy turbulence losses, which represent a larger portion of the total losses as the friction Reynolds number, Reτ, increases, and operation at higher Tosc+ also reduces some small-scale eddy losses. It is evident that operating at a specific actuation Tosc+ can affect a wide spectrum of wall stresses.
As illustrated, a controller 1060 can apply a voltage differential between the exposed electrodes 1040 and the covered electrodes 1020 to generate a region of plasma, resulting in the actuation force 1045 (ionic wind) that is transverse to the direction of the fluid flow 1010. According to various embodiments, the controller 1060 may operate to actuate the DBD actuators in the array of DBD actuators at low frequencies to affect large-scale eddies in the fluid flow 1010.
The system or controller may actuate, at 1130, a plurality of actuators on the surface of the object with the calculated actuation frequency, f, to disrupt the large-scale eddies to selectively increase or decrease the drag of the fluid on the surface of the object.
As illustrated, a fluid flow analysis module 1280 may determine the direction of fluid flow over a surface, the speed of the fluid relative to the surface, and/or specific characteristics of the fluid flow. For example, in complex examples, the fluid flow analysis module 1280 may determine specific characteristics of the flow and/or the turbulent boundary layer (e.g., components of the small-scale eddies and/or large-scale eddies). The computer-readable storage medium 1270 may further include an actuator control module 1282 to electronically control the frequency and amplitude of the actuations of sets or subsets of actuators on the surface. Additionally, a feedback control module 1284 may receive feedback from the fluid flow analysis module 1280 and modify the actuations via the actuator control module 1282 to improve drag reduction (or drag increase in some embodiments).
The actuators 1310 may be selectively controlled for transverse momentum injection into the large-scale eddies to reduce skin friction drag. In some instances (e.g., when braking), an electronic controller may selectively control the actuators 1310 for transverse momentum injection into the large-scale eddies to increase skin friction drag. The illustrated actuators 1310 represented by shaded rectangles are intended to convey an understanding of possible placement. However, the total number of actuators 1310, the relative sizes of the actuators 1310, the orientation(s) of the actuators 1310, the arrangements of the actuators 1310 (e.g., columns, rows, two-dimensional arrays, etc.), the types of actuators 1310, and/or other specific information may be different than illustrated. As such, the illustration is not intended to convey any information on the actual arrangement, size, orientation, relative quantity, or type of actuator 1310.
In some embodiments, a first subset of the actuators 1310 may be used for transverse momentum injection at low frequencies to affect large-scale eddies to reduce drag and a second subset of the actuators 1310 may be used for transverse momentum injection at high frequencies to affect small-scale eddies. For example, at relatively low velocities where the friction Reynolds number, Reτ, is less than a first threshold (e.g., 1,500 or 2,500, or 10,000) depending on the embodiment, a first subset of the actuators 1310 may be used for transverse momentum injection at high frequencies to directly modify small-scale eddies near the wall to reduce drag. As the velocity of the fluid relative to the object increases, the friction Reynolds number, Reτ, may increase beyond the first threshold value.
As the friction Reynolds number, Reτ, increases, the momentum and frequency required for continued drag reduction via direct modification of small-scale eddies via momentum injection increases beyond physical and/or financial practicality. For example, the extremely high frequencies and magnitudes of momentum required for effective transverse momentum injection in fluid flows with friction Reynolds numbers, Reτ, above the threshold value may not be physically attainable, may be cost-prohibitive, or may require energy inputs that exceed the energy savings attained by the reduced drag.
Accordingly, the system may identify that the friction Reynolds number, Reτ, has exceeded the threshold value (e.g., via a directly calculated friction Reynolds number, Reτ, or based on a relative speed of the object/surface and the fluid). As the friction Reynolds number, Reτ, passes the threshold value, the system may switch from high-frequency transverse momentum injection to directly affect the small-scale eddies to low-frequency transverse momentum injection to directly affect the large-scale eddies. In some embodiments, the system may utilize the same actuators for both low-frequency transverse momentum injection and high-frequency transverse momentum injection. In other embodiments, the operational frequency range of individual actuators may not be sufficient for both low-frequency transverse momentum injection and high-frequency transverse momentum injection. In such embodiments, the system may utilize a first set of actuators (e.g., mechanical actuators, piezoelectric actuators, actuators, wall-jets, etc.) for low-frequency transverse momentum injection and a second subset of the actuators (of the same type or a different type) for high-frequency transverse momentum injection.
In some embodiments, low-frequency actuators 1330 (or another low-frequency transverse momentum injection actuator) may be positioned on the high-speed blades 1335 of the wind turbine where the fluid flow is expected to have a relatively high friction Reynolds number, Reτ, (e.g., larger than 1,500, 2,500, 5,000, 10,000 or another threshold value). The low-frequency actuators 1330 may be electronically controlled to directly modify the large-scale eddies of a turbulent boundary layer to reduce drag (e.g., skin friction drag).
This disclosure has been made with reference to various exemplary embodiments, including the best mode. However, those skilled in the art will recognize that changes and modifications may be made to the exemplary embodiments without departing from the scope of the present disclosure. While the principles of this disclosure have been shown in various embodiments, many modifications of structure, arrangements, proportions, elements, materials, and components may be adapted for a specific environment and/or operating requirements without departing from the principles and scope of this disclosure. These and other changes or modifications are intended to be included within the scope of the present disclosure.
This disclosure is to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope thereof. Likewise, benefits, other advantages, and solutions to problems have been described above with regard to various embodiments. However, benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element. This disclosure includes and encompasses at least the following claims and all possible permutations thereof.
This application is a continuation of U.S. patent application Ser. No. 17/673,535 filed on Feb. 16, 2022, entitled “In-Plane Transverse Momentum Injection to Disrupt Large-Scale Eddies in a Turbulent Boundary Layer,” granting as U.S. Pat. No. 11,466,709 on Oct. 11, 2022, which claims benefit under 35 U.S.C. § 119 and priority to U.S. Provisional Patent Application No. 63/150,183 filed on Feb. 17, 2021, entitled “Drag Reduction Via Transverse Momentum Injection to Disrupt Large-Scale Eddies of a Turbulent Boundary Layer,” and U.S. Provisional Patent Application No. 63/155,408 filed on Mar. 2, 2021, entitled “Turbulent Drag Reduction,” each of which applications is hereby incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
1903823 | Lougheed | Apr 1933 | A |
2440198 | Green | Apr 1948 | A |
3289978 | Banaszak | Dec 1966 | A |
3578264 | Kuethe | May 1971 | A |
4102519 | Crosby | Jul 1978 | A |
4309901 | Rolinski | Jan 1982 | A |
4516747 | Lurz | May 1985 | A |
4526031 | Weisend | Jul 1985 | A |
4611492 | Koosmann | Sep 1986 | A |
4932612 | Blackwelder | Jun 1990 | A |
5037044 | Seyfang | Aug 1991 | A |
5106017 | Hicks | Apr 1992 | A |
5209438 | Wygnanski | May 1993 | A |
5359574 | Nadolink | Oct 1994 | A |
5365490 | Katz | Nov 1994 | A |
5369345 | Phan | Nov 1994 | A |
5374011 | Lazarus | Dec 1994 | A |
5445346 | Gilbert | Aug 1995 | A |
5531407 | Austin | Jul 1996 | A |
5540406 | Occhipinti | Jul 1996 | A |
5558156 | Tsutsui | Sep 1996 | A |
5558304 | Adams | Sep 1996 | A |
5573012 | McEwan | Nov 1996 | A |
5598990 | Farokhi | Feb 1997 | A |
5755408 | Schmidt | May 1998 | A |
5808210 | Herb | Sep 1998 | A |
5874671 | Lopez | Feb 1999 | A |
5942682 | Ghetzler | Aug 1999 | A |
5953773 | Asada | Sep 1999 | A |
5957413 | Glezer | Sep 1999 | A |
5961080 | Sinha | Oct 1999 | A |
5964433 | Nosenchuck | Oct 1999 | A |
5988522 | Glezer | Nov 1999 | A |
5988568 | Drews | Nov 1999 | A |
6016286 | Olivier | Jan 2000 | A |
6024119 | Kirschner | Feb 2000 | A |
6109565 | King, Sr. | Aug 2000 | A |
6123145 | Glezer | Sep 2000 | A |
6123296 | Mangalam | Sep 2000 | A |
6131853 | Bauer | Oct 2000 | A |
6215221 | Cabuz | Apr 2001 | B1 |
6332593 | Kamiadakis | Dec 2001 | B1 |
6443394 | Weisend, Jr. | Sep 2002 | B1 |
6484971 | Layukallo | Nov 2002 | B2 |
6644598 | Glezer | Nov 2003 | B2 |
6662647 | Schoess | Dec 2003 | B2 |
6795763 | Yao | Sep 2004 | B2 |
6821090 | Hassan | Nov 2004 | B1 |
6862502 | Peltz | Mar 2005 | B2 |
6871816 | Nugent | Mar 2005 | B2 |
6874748 | Hanagan | Apr 2005 | B2 |
6966231 | Sheplak | Nov 2005 | B2 |
6979050 | Browne | Dec 2005 | B2 |
7031871 | Severson | Apr 2006 | B2 |
7133785 | Larson | Nov 2006 | B2 |
7204731 | Gusler | Apr 2007 | B2 |
7251592 | Praisner | Jul 2007 | B1 |
7375911 | Li | May 2008 | B1 |
7380756 | Enloe et al. | Jun 2008 | B1 |
7434170 | Novak | Oct 2008 | B2 |
7537182 | Greenblatt | May 2009 | B2 |
7703839 | McKnight | Apr 2010 | B2 |
7854467 | McKnight | Dec 2010 | B2 |
7913928 | Tiliakos | Mar 2011 | B2 |
8006939 | McClure | Aug 2011 | B2 |
8074938 | Hyde et al. | Dec 2011 | B2 |
8074939 | Hyde et al. | Dec 2011 | B2 |
8091950 | Corke et al. | Jan 2012 | B2 |
8267355 | Patel et al. | Sep 2012 | B1 |
8286909 | Lee | Oct 2012 | B2 |
8308112 | Wood et al. | Nov 2012 | B2 |
8436509 | Branch | May 2013 | B1 |
8640995 | Corke et al. | Feb 2014 | B2 |
8783337 | Hyde | Jul 2014 | B2 |
8794574 | Lang | Aug 2014 | B2 |
8894019 | Alvi | Nov 2014 | B2 |
9002484 | Hyde et al. | Apr 2015 | B2 |
9410527 | Hsu | Aug 2016 | B2 |
9541106 | Patel et al. | Jan 2017 | B1 |
9834301 | Patel et al. | Dec 2017 | B1 |
9848485 | Corke et al. | Dec 2017 | B2 |
9883822 | Bhagavat | Feb 2018 | B2 |
9908616 | Horn | Mar 2018 | B1 |
10527074 | Corke et al. | Jan 2020 | B2 |
10543908 | Stefes | Jan 2020 | B2 |
11299260 | Wine | Apr 2022 | B2 |
11466709 | Smits | Oct 2022 | B2 |
20020079405 | Layukallo | Jun 2002 | A1 |
20020125376 | Kamiadakis | Sep 2002 | A1 |
20020131474 | Suga | Sep 2002 | A1 |
20040197519 | Elzey | Oct 2004 | A1 |
20040249257 | Tupin | Dec 2004 | A1 |
20050088057 | Kando | Apr 2005 | A1 |
20050121240 | Aase | Jun 2005 | A1 |
20050163963 | Munro | Jul 2005 | A1 |
20050241605 | Bedwell | Nov 2005 | A1 |
20060022092 | Miller | Feb 2006 | A1 |
20060040532 | Ozawa | Feb 2006 | A1 |
20060060722 | Choi | Mar 2006 | A1 |
20060236777 | Chambers | Oct 2006 | A1 |
20070113932 | Tiliakos | May 2007 | A1 |
20080128027 | Hyde | Jun 2008 | A1 |
20080128560 | Hyde | Jun 2008 | A1 |
20080128561 | Hyde | Jun 2008 | A1 |
20080193307 | Elata | Aug 2008 | A1 |
20080245520 | Hyde | Oct 2008 | A1 |
20090173837 | Silkey et al. | Jul 2009 | A1 |
20100123046 | Khozikov | May 2010 | A1 |
20100219296 | Shelman-Cohen | Sep 2010 | A1 |
20110224846 | Simon | Sep 2011 | A1 |
20110295102 | Lakkis | Dec 2011 | A1 |
20120193483 | Essenhigh | Aug 2012 | A1 |
20130009016 | Fox | Jan 2013 | A1 |
20150191244 | Rolston | Jul 2015 | A1 |
20150257653 | Hyde | Sep 2015 | A1 |
20160089052 | Cho | Mar 2016 | A1 |
20160174842 | Hyde | Jun 2016 | A1 |
20180298762 | Shelman-Cohen | Oct 2018 | A1 |
20190136881 | Amitay | May 2019 | A1 |
20200031456 | Wine | Jan 2020 | A1 |
20200148335 | Wine | May 2020 | A1 |
20200176664 | Wine | Jun 2020 | A1 |
20200191177 | Wine | Jun 2020 | A1 |
20200217337 | Loebig | Jul 2020 | A1 |
20210348628 | Holloway | Nov 2021 | A1 |
20220260098 | Smits | Aug 2022 | A1 |
Number | Date | Country |
---|---|---|
1481467 | Dec 2004 | EP |
2012139 | Jan 2009 | EP |
1053332 | Feb 1954 | FR |
2001076934 | Oct 2001 | WO |
2002103304 | Dec 2002 | WO |
2006040532 | Apr 2006 | WO |
2012054086 | Apr 2012 | WO |
2016179405 | Nov 2016 | WO |
2016189448 | Dec 2016 | WO |
2022177960 | Aug 2022 | WO |
Entry |
---|
U.S. Appl. No. 16/696,810, Non-Final Office Action dated Jun. 27, 2022, 11 pp. |
PCT International Patent Application No. PCT/US2019/063409, International Search Report and Written Opinion dated Feb. 21, 2020, 11 pp. |
Deep Science, LLC, International Patent Application PCT/US2022/016560, International Search Report and Written Opinion dated May 30, 2022, 10 pp. |
Mahfoze O et al., “Skin-friction drag reduction in a channel flow with streamwise-aligned plasma actuators,” Int'l J. of Heat and Fluid Flow, Butterworth Scientific LTD., Guildford, GB, vol. 66, Jun. 6, 2017, pp. 83-94. |
Alfredsson et al., Large-Eddy Breakup Devices—a 40 Years Perspective from a Stockholm Horizon, Flow Turbulence Combust (2018), vol. 100, pp. 877-888. |
Cattafesta et al., Actuators for Active Flow Control, Annu. Rev. Fluid Mech. 2001.43, pp. 247-272. |
Corke et al., Active and Passive Turbulent Boundary layer Drag Reduction, AIAA Journal (Oct. 2018), vol. 56, No. 10, pp. 3835-3847. |
Garcia-Mayoral et al., Drag rReduction by riblets, Phil. Trans. R. Soc. A (2011), vol. 369, pp. 1412-1427. |
Gatti et al., Reynolds-number dependence of turbulent skin-friction drag reduction induced by spanwise forcing, Journal of Fluid Mechanics (2016), vol. 802, pp. 553-582. |
Gouder, Turbulent Friction Drag Reduction Using Electroactive Polymer Surfaces, Doctoral thesis, Imperial College, May 2011. |
Kline et al., The structure of turbulent boundary layers, Journal of Fluid Mechanics (1967), vol. 30, pp. 741-773. |
Leschziner, Friction-Drag Reduction by Transverse Wall Motion—A Review, J. of Mechanics,DOI: 10.1017/mech.2020.31, 15 p. |
Marusic et al., Predictive model for wall-bounded turbulent flow, Science (2010), vol. 329(5988), pp. 193-196. |
Mathis et al., Estimating wall-shear-stress fluctuations given an outer region input, Journal of Fluid Mechanics (2013), vol. 715, pp. 163-180. |
Panton, Overview of the self-sustaining mechanisms of wall turbulence, Prog. Aerosp. Sci. (2001), vol. 37, pp. 341-383. |
Smith et al., The characteristics of low-speed streaks in the near-wall region of a turbulent boundary layer, Journal of Fluid Mechanics (1983), vol. 129, pp. 27-54. |
Smits et al., High Reynolds Number Wall Turbulence, Annu. Rev. Fluid Mech. (2011), vol. 43, pp. 353-375. |
Thomas et al., Turbulent drag reduction using pulsed-DC plasma actuation, J. of Physics D: Appl. Phys. 52 (2019) 434001, 13 p. |
Schoppa et al., A large-scale control strategy fordrag reduction in turbulent boundary layers, Physics of Fluids (May 1998); vol. 10(5), pp. 1049-1051. |
Smits, et al., U.S. Appl. No. 17/673,535, Notice of Allowance dated Jul. 26, 2022, 11 pp. |
U.S. Appl. No. 16/740,154, Non-Final Office Action dated May 6, 2022, 24 pp. |
U.S. Appl. No. 16/674,870, Non-Final Office Action dated May 26, 2022, 22 pp. |
International Patent Application PCT/US2019/059919, International Search Report dated Apr. 15, 2020, 17 pp. |
Gouder et al., “Turbulent Friction Drag Reduction Using electroactive Polymer & Electromagnetically-driven Surfaces”, Jan. 17, 2013, Experiments in Fluids, vol. 53, pp. 1-13. |
Ainajjar et al., “Receptivity of High-Speed Jets to Excitation Using an Array of Mems-based Mechanical Actuators”, ASME Fluids Engineering Division Summer Meeting, Jun. 22-26, 1997, pp. 1-6. |
Bird et al., “Compliant Kagome Lattice Structures for Generating in-plane Waveforms”, Jun. 1, 2018, vol. 141-142, pp. 86-101. |
Bird et al., “Experimental Control of Turbulent Boundary Layers with In-plane Travelling Waves”, May 14, 2018, Flow Turbulence Combust, vol. 100, pp. 1015-1035. |
Bird et al., “In-Plane Forcing of a Turbulent Boundary Layer, Through the Actuation of a Compliant Structure”, EDRFCM, Mar. 23-26, 2015, pp. 1-2. |
Braslow, “A History of Suction-Type Laminar-Flow Control with Emphasis on Flight Research”, Jan. 1, 1999, pp. 1-84. |
Bushnell, “Chapter VIII: Compliant Surfaces Introduction”, Viscous Flow Drag Reduction, Jan. 1, 1980, pp. 387-390. |
Chamorro et al., “Drag Reduction of Large Wind Turbine Blades through Riblets: Evaluation of Riblet Geometry and Application Strategies”, Feb. 2013, Renewable Energy, vol. 50, pp. 1095-1105. |
Examination Report issued on GB0911332.5 dated Mar. 31, 2011, 4 pages. |
Examination Report issued on GB0911333.3 dated Oct. 25, 2010, 2 pages. |
Gad-El-Hak and BUSHNELL, “Separation Control: Review”, Journal of Fluids Engineering, Mar. 1991, vol. 113, pp. 5-30. |
Gad-El-Hak, “Chapter 9: Drag Reduction Using Compliant Walls”, Flow Past Highly Compliant Boundaries and in Collapsible Tubes, Eds. Carpenter and Pedley, Mar. 26-31, 2001, pp. 191-229. |
Gatti and Quadrio et al., “Reynolds-number Dependence of Turbulent Skin-friction Drag Reduction Induced by Spanwise Forcing”, Sep. 10, 2016, J. Fluid Mech., vol. 802, pp. 553-582. |
Gatti, “Turbulent Drag Reduction at Moderate Reynolds Number via Spanwise Velocity Waves”, PAMM, Dec. 3, 2012, pp. 563-564. |
Grosjean et al., “Micro Balloon Actuators for Aerodynamic Control”, IEEE Proceedings MEMS 98, Jan. 25-28, 1998, pp. 1-6. |
Hong et al., “Turbulent Drag Reduction with Polymers in Rotating Disk Flow”, Jul. 13, 2015, Polymers, vol. 7, pp. 1279-1298. |
Huang et al., “MEMS Transducers for Aerodynamics-A Paradym Shift”, 38th Aerospace Sciences Meeting, Jan. 10-13, 2000, pp. 1-7. |
Hurst et al., “The Effect of Reynolds Number on Turbulent Drag Reduction by Streamwise Travelling Waves,” Nov. 25, 2014, J. Fluid Mech., vol. 759, pp. 28-55. |
Jones et al., “Modelling for Robust Feedback Control of Fluid Flows”, Feb. 2015, Journal of Fluid Mechanics, vol. 769, pp. 1-34. |
Jung et al., “Suppression of Turbulence in Wall-bounded flows by High-frequency Spanwise Oscillations”, Aug. 1992, Phys. Fluids A, vol. 4, No. 8, pp. 1605-1607. |
Kang and Choi, “Active Wall Motions for Skin-Friction Drag Reduction”, Dec. 2000, Physics of Fluids, vol. 12, No. 12, pp. 3301-3304. |
Karniadakis and Choi, “Mechanism on Transverse Motions in Turbulent Wall Flows”, Jan. 2003, Annu. Rev. Fluid Mech., vol. 35, pp. 45-62. |
Kasagi et al., “Toward Cost-Effective Control of Wall Turbulence of Skin Friction Drag Reduction”, Sep. 7-10, 2009, Advances in Turbulence XII, pp. 189-200. |
Laadhari et al., “Turbulence Reduction in a Boundary Layer by a Local Spanwise Oscillating Surface”, Oct. 1994, Physics of Fluids, vol. 6, pp. 3218-3220. |
Lee et al., “Control of Roll Moment by MEMS”, American Society of Mechanical Engineers, Dec. 1, 1996, pp. 797-803. |
Luhar et al., “A Framework for Studying the Effect of Compliant Surface on Wall Turbulence”, Apr. 10, 2015, J. Fluid Mech., vol. 768, pp. 415-441. |
Melton et al., “Active Flow Control via Discrete Sweeping and steady Jets on a Simple-Hinged Flap”, Aug. 2018, AIAA Journal, vol. 56, No. 8, pp. 2961-2973. |
Morrison, “MEMS Devices for Active Drag Reduction in Aerospace Applications”, Mar. 27, 2014, Electronic and Optical Materials, pp. 153-176. |
Naguib et al., “Arrays of MEMS-based Actuators for Control of Supersonic Jet Screech”, AIAA, Jun. 29, 1997-Jul. 2, 1997, pp. 1-9. |
Quadrio and Ricco, “The Laminar Generalized Stokes Layer and Turbulent Drag Reduction”, Jan. 25, 2011, J. Fluid. Mech., vol. 667, pp. 135-157. |
Quadrio et al., “Streamwise-traveling Waves of Spanwise Wall Velocity for Turbulent Drag Reduction”, May 25, 2009, vol. 627, pp. 161-178. |
Ricco, “Active and Passive Turbulent Drag Reduction” Workshop on Turbulent Skin Friction Drag Reduction, Imperial College London, Dec. 4-5, 2017, pp. 1-60. |
Sareen et al., “Drag Reduction Using Riblet Film Applied to Airfoils for Wind turbines”, 49th Aerospaces Sciences Meeting, Jan. 4-7, 2011, pp. 1-19. |
Schroder, “Drag Reduction via Transversal Wave Motions”, Institute of Aerodynamics, Jul. 2017, pp. 1-22. |
Shen, “Turbulent Flow over a Flexible Wall Undergoing a Streamwise Travelling Wave Motion”, Jun. 10, 2003, J. Fluid Mech., vol. 484, pp. 197-221. |
Symeonidis and Karniadakis, “Drag Reduction in Wall-Bound Turbulence Via a Transverse Travelling Wave”, J. Fluid Mech., vol. 457, pp. 1-34. |
Tamano, “Turbulent Drag Reduction due to Spanwise Traveling Waves with Wall Deformation”, Nov. 20, 2014, FOR 1779 Symposium, pp. 1-51. |
Tomiyama and Fukagata, “Direct Numerical Simulation of Drag Reduction in a Turbulent Channel Flow Using Spanwise Traveling Wave-like Wall Deformation”, Oct. 2013, Physics of Fluids, vol. 25, pp. 1-22. |
Tsao, “An Integrated MEMS System for Turbulent Boundary Layer Control”, Jul. 1997, IEEE Solid State Sensors and Actuators, pp. 1-4. |
Tsao, “Micromachined Magnetic Actuators for Active Fluid Control”, 1994 International Mechanical Engineering Congress and Exposition, Dec. 1, 1994, pp. 31-38. |
Van Buren and Amitay, “Piezoelectric Driven Oscillating Surface (PDOS)”, RPI, 2014, 6 pages. |
Viotti et al., “Streamwise Oscillation of Spanwise Velocity at the Wall of a Channel for Turbulent Drag Reduction”, Oct. 2009, Physics of Fluids, vol. 21 , pp. 1-9. |
Wang, “Flow over a Surface with Parallel Grooves”, May 2003, vol. 15, No. 5, pp. 1114-1121. |
Yang et al., “Micro Bellow Actuators”, IEEE International Solid State Sensors and Actuators Conference, Jun. 19, 1997, pp. 1-4. |
Zhao et al., “Turbulent Drag Reduction by Traveling Wave of Flexible Wall”, Mar. 31, 2004, Fluid Dynamics Research, vol. 34, pp. 175-198. |
Zhong et al., “Reduction of Pressure Losses in A Linear Cascade Using Herringbone Riblets”, School of Mechanical, Aerospace and civil Engineering, University of Manchester, Aug. 17, 2017, 16 pages. |
International Patent Application PCT/US2019/042832, International Search Report dated Nov. 4, 2019, 16 pp. |
Number | Date | Country | |
---|---|---|---|
20230044837 A1 | Feb 2023 | US |
Number | Date | Country | |
---|---|---|---|
63155408 | Mar 2021 | US | |
63150183 | Feb 2021 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 17673535 | Feb 2022 | US |
Child | 17938399 | US |