1. Introduction
The growing concern over energy efficiency and environmental pollution is furthering the appeal of transport vehicles, particularly aircraft, that produce less aerodynamic drag. One of the most interesting passive drag reduction techniques is the use of riblets, i.e., streamwise-aligned micro-grooves that are known to reduce turbulent skin-friction drag (see, for example, the review paper [
1] and the many references therein), and are approaching usability in aeronautics.
Early studies, spurred by the oil crisis of the 1970s, were performed at NASA [
2], and important experiments were carried out in the Berlin oil tunnel by Bechert and coworkers [
3,
4]. They evidenced the crucial importance of the riblet shape, their size, and—most importantly—the sharpness of their tip; optimal configurations empirically determined at the time yield up to 6–8% and possibly higher reductions in skin friction for low-
flat plate-boundary layers studied in laboratory conditions. The theoretical understanding of the riblets working mechanism is due to Luchini [
5], who quantified the different resistance offered by a grooved wall to the parallel flow and the cross-flow. He also explained [
6] how skin-friction drag reduction is equivalent to an upward shift of the logarithmic portion of the turbulent velocity profile. This important argument, later taken up again by [
7], implies that it is incorrect to describe riblets performance simply as a percentage change of the skin-friction coefficient, as this simplistic figure depends on the Reynolds number of the flow. However, the value of the upward shift, once measured in viscous units, is Reynolds independent and should be used to characterize the ability of riblets (and other techniques) to reduce turbulent friction; in fact, recently this concept has been extended [
8] to other strategies of skin-friction reduction.
To capture, in a numerical simulation, the complex physics of the interaction between turbulence and a solid wall covered by riblets, and to properly measure friction reduction, direct numerical simulations (DNS) or wall-resolved large eddy simulations (LES) are required. Such computations are unfeasible for complex aeronautical configurations at high Reynolds numbers, where numerical simulations based on the Reynolds-Averaged Navier–Stokes equations (RANS) equipped with a turbulence model are the standard approach. Owing to their microscopic dimensions, however, riblets on an aircraft cannot be included directly in a RANS simulation. Even if they could, it is unclear to what extent a standard RANS model would be able to represent the physics of drag reduction.
Bridging the gap between drag reduction by riblets in turbulent flows and the need to incorporate it into RANS-type flow solvers has led to the development of computational models for riblets. Aupoix et al. [
9] modified the Spalart–Allmaras turbulence model to account for riblets by using smooth-wall geometry. Along similar lines, Mele et al. [
10] introduced a modified boundary condition for the
turbulence model, and Koepplin et al. [
11] extended the Aupoix model to describe riblets locally misaligned with the mean flow, and to account for mean pressure gradients.
How riblets affect a turbulent boundary layer with a non-zero pressure gradient is a debated subject [
12,
13,
14]. In 2018, Mele and Tognaccini [
15] developed a new model based on a slip-length concept, whose results provided an interesting view on the riblets drag reduction mechanism in presence of pressure gradients. In addition to friction reduction, they found that riblets alter the pressure distribution, and may provide additional pressure drag reduction. This indirect effect was also observed for other friction-reduction devices: Banchetti et al. [
16] used spanwise forcing to reduce turbulent friction on a wall with a bump, and found in their incompressible DNS study that a reduced friction drag is accompanied by a reduced pressure drag. Similarly, using DNS, Quadrio et al. [
17] studied the compressible flow over a wing, and observed how spanwise forcing affects the shock wave to yield large reduction of the total drag of the aircraft. The availability of a boundary condition to faithfully simulate in a RANS the presence of riblets on the surface of a solid body of complex shape is thus becoming extremely attractive.
The standard no-slip condition at a solid wall can be extended to a partial-slip one, which is useful to describe specific physical situations (e.g., flow over superhydrophobic surfaces). Riblets are amenable to such a description; their slip length is related to the protrusion height concept [
3,
4,
5]. In particular, Luchini in [
5] defined the longitudinal and transverse protrusion heights, which identify the virtual origin for the streamwise and spanwise velocity profiles, and realised that the only meaningful non-arbitrary quantity is their difference. Later, he also introduced [
18] a linearised boundary condition for generic roughness and the protrusion heights for various roughness types to be adopted in DNS. He also demonstrated that the difference
between the two riblets protrusion heights corresponds to the slip length
. Gomez de Segura et al. [
19] later discussed how the slip length
expressed in viscous units is equivalent to the upward displacement
of the mean velocity profile in the logarithmic region; here,
, where
is the kinematic viscosity,
is the friction velocity,
is the density, and
is the (local) shear stress.
The value of the slip length
depends upon the shape and size of the riblets cross-section. Bechert et al. [
4] found that the largest drag reduction for riblets of different shapes was obtained when
, the spanwise period of the riblets, is in the range 10–20. García-Mayoral and Jiménez [
1] tested alternative scalings to find whether drag reduction can be linked to a single geometric parameter that captures the importance of riblet spacing and their cross-sectional shape as well. Data for different riblets were found to best collapse when plotted against a dimensionless length scale
derived from the cross-sectional area
of the groove, and defined as
. For riblets of various geometries, the best performance was consistently found at
. For optimal triangular riblets,
corresponds to a unitary shift
, which coincides with the one reported in previous studies [
15,
20,
21]. Recently, Zhang et al. [
22] have been able to compute the slip length for other riblets shapes, i.e., with trapezoidal and blade cross-sections.
The goal of this paper is to present the implementation of a slip-length boundary condition for riblets, and to use it in a set of RANS simulations to assess the drag reduction capabilities of riblets when installed on a fixed-wing UAV, for which endurance is of capital importance. Indeed, over the years, riblets have been studied either at low speed over plane walls, or in transonic flow conditions for aeronautical applications, especially for medium- or long-range commercial passenger aircraft. Such studies, carried out both numerically [
10,
23] and experimentally [
24,
25,
26,
27,
28], provide interesting results for aircraft operating in a range of chord-based Reynolds numbers up to
. In contrast, the low-speed aircraft considered in the present work has a cruise speed of 22 m/s with
.
This paper describes the implementation into an incompressible CFD solver of a slip-length wall boundary condition, similar to that described in ref. [
21], to compute the drag reduction achievable with riblets of optimal dimensions. The computational model is validated against configurations of increasing complexity, and eventually applied to a realistic use case. We also consider selective deployment of riblets to different parts of the aircraft to show that drag reduction is not trivially proportional to the surface area covered by riblets. The structure of the work is as follows. After this introduction,
Section 2 describes our model and the computational setup;
Section 3 contains the results of preliminary simulations intended for validation; the actual results are described in
Section 4, and
Section 5 contains a concluding discussion.
2. Methods
2.1. Slip Length Boundary Condition
Both theory and experiments [
3,
4,
5] suggest that the physics involved in drag reduction by riblets acts through a local mechanism. Indeed, since riblets are small compared to the turbulent structures of the near-wall cycle, far enough from the wall, the turbulent flow perceives the presence of riblets only as a homogeneous effect: the upward shift
of the logarithmic portion of the mean velocity profile:
where
is the von Kármán constant, and
is the near wall intercept for smooth surfaces (these constants are set after [
29], but their numerical value does not affect the outcome of the study). The dimensionless vertical shift
equals the virtual shift in wall units of the non-slipping wall [
4], i.e., the slip length
. We exploit this shift to account for the presence of riblets via a slip boundary condition, which linearly relates the wall value of the longitudinal component of the velocity
(the subscript
w indicates quantities evaluated at the wall) to the wall shear rate
through the slip length
:
thus effectively recovering the no-slip condition when
. The discrete counterpart of Equation (
2), where the derivative is approximated with a finite difference, reads:
where
is the longitudinal velocity at the first inner mesh point, and
d is its distance from the wall. Hence, the velocity at the wall is:
In this work, we always set the shift of the mean velocity profile at
, which corresponds [
15,
20,
21] to the best-performing riblets with triangular cross-section. These riblets have a square root of the cross-sectional area of
, and provide a drag reduction of 7% when measured in the lab under controlled conditions and at low
. Using
implies setting
, whence the physical size of the riblets varies along the body with the friction velocity of the flow. In other words, riblets are assumed to be locally optimal everywhere, and the corresponding physical dimensions are computed as a result of the simulation.
It is worth noticing that the present boundary condition can be used to simulate, besides riblets, any other drag reduction method whose effect reduces to a shift in the mean velocity profile. To this purpose, only the slip-length value must be adjusted.
2.2. Computational Setup
The boundary condition described above has been implemented in OpenFOAM [
30], an open-source finite-volumes CFD library widely used in engineering and science, both in commercial and academic studies. Before considering the UAV, the boundary condition has been validated on flow cases of increasing complexity where at least partial information is available for comparison: a flat plate and a NACA 0012 airfoil.
The selected flow solver is SimpleFOAM, which uses the SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) algorithm to solve the incompressible steady RANS equations. The
SST turbulence model [
31] has been adopted in this work, where standard values for the coefficients and no transition model have been used. For all the simulations, we adopt a freestream ratio between eddy and laminar viscosity equal to 0.001, together with free-stream turbulence intensity of
, with the only exception of the flat plate case, for which
. The spatial discretization used for the divergence, gradient, and Laplacian operators is second-order accurate. All the results have been checked to be fully converged in integral quantities (drag and lift) and in the residuals, by ensuring that the
norm reduced to
times the initial value of the residual.
The study considers three geometries of increasing complexity. The first case is a two-dimensional flat plate boundary layer of length L = 2 m is considered, where . With air as working fluid, and a free-stream velocity of m/s, the computational domain is rectangular and extends for 2.3 m in length and 1 m in height. The flat plate sits along the lower boundary of the computational domain. The domain extends 0.3 m upstream of the flat plate, and a symmetry boundary condition is used to simulate a free stream approaching the plate in this region. A suitable volume mesh is designed with the BlockMesh utility available in OpenFoam, and checked to yield mesh-independent results with a mesh sensitivity study. The final mesh, which provides a local friction coefficient that does not vary with further refinements, consists of 125,000 hexahedral elements, with 250 cells in the wall-normal direction and 500 cells in the wall-parallel direction, of which 400 are distributed over the flat plate. Non-uniform grid spacing is adopted to obtain more resolution in the near-wall and in the leading-edge regions, to better capture the boundary-layer development. Transition is adequately described, and the distance of the first cell from the wall is always below unity when expressed in wall units, i.e., .
The second case is a two-dimensional NACA 0012 airfoil, at a chord-based Reynolds number of
. The airfoil chord
c is taken of unitary length at 1 m, and the far-field boundary is located approximately
away from the airfoil surface. A mesh sensitivity study is carried out on a number of C-type grids by observing changes in the drag coefficient after successive mesh refinements. The chosen grid consists of 450 hexahedral cells in the chord-normal and 725 in the chord-tangent directions, and provides a repeatable transition location. The mesh spacing near the airfoil is sufficient to ensure
over the airfoil surface. Stretching of the grid is used to improve resolution in the wake region. To further validate the mesh accuracy, the solution has also been checked as a function of the angle of attack
. Hence, a number of preliminary runs at various values of
have been performed, without riblets, by replicating the flow conditions used in [
32]. The outcome in terms of lift and drag coefficients is in very good agreement with the results reported by [
32], as well as with the experimental measurements described in [
33].
The final and most important case is the UAV. With a total length of 2.4 m and wing span of 3.6 m; its (simplified) geometry is described in some detail in
Section 2.3. Simulations are carried out first on the isolated UAV wing, to understand to what extent the indirect beneficial effects of riblets noticed for the NACA 0012 carry forward to three dimensions, and the complete UAV is then considered. In both cases, the computational domain is made by a hemisphere, with a radius of 50 m that surrounds the wing half-span and the UAV half-span mounted on the
plane, respectively. Symmetry is used to reduce computational cost. In this case, a commercial mesher is used to create unstructured meshes made by hexahedral and tetrahedral cells, with refinements boxes to capture the flow development near the body and in the wake. The grids possess 24 additional layers of hexahedral and tetrahedral elements aligned to the boundary surface, to guarantee that
, thus satisfying the requirements for an accurate computation inside the boundary layer within a low-
formulation that does not resort to wall functions or other models of the near-wall region. A suitable mesh density is determined by observing changes in the drag coefficient, and robustness in predicting transition. The final mesh is designed with 4 million elements for the wing and 9.6 million elements for the full UAV.
2.3. The UAV Model
The considered UAV belongs to the family of Mini and Light Tactical UAV, with a MTOW (maximum take-off weight) ranging from 25 to 50 kg. The UAVs of this class are designed to integrate multiple payloads with different capabilities, e.g., EO/IR sensors, multi/hyperspectral cameras, LiDAR, transmitters, and radars. Flexibility is ensured by the fuselage modularity and by the possibility of changing the onboard systems configuration to achieve an optimised aircraft balance.
In this work, we consider a simplified geometric model of the UAV, as plotted in
Figure 1, where small-scale geometric details and the propeller are omitted. The motivation is two-fold: such a simplified geometry, while remaining representative of the actual aircraft and retaining its essential qualitative features and dimensional characteristics, is free from intellectual property constraints; moreover, the lack of small-scale details allows some savings of computational effort. The simplified UAV is 2.4 m long and it has a span
m. It has a swept wing with a chord length of 0.3 m at the root with winglets at the tips of 0.22 m and dihedral angle of 21.5°. The considered reference surface area is
m
2. The UAV is characterised by a reverse V tail made by a symmetric four-digit NACA airfoil with a span of 1.05 m and a chord of 0.23 m. The tail is directly connected to the lower surface of the wing by two booms of 1.05 m with a circular cross-sectional area of radius 0.015 m. The fuselage is 1.41 m long and its cross-section originates from a rectangular shape, 0.29 m high and 0.23 m wide, with rounded edges. The drone cruise speed is 22 m/s, leading to a chord-based Reynolds number
. The UAV weight of 25 kg and the cruise speed of 22 m/s, together with the geometrical information mentioned above, imply a lift coefficient in cruise of
.
2.4. Dimensionless Force Coefficients
In this paper, the aerodynamic coefficients, i.e., the ratio of a force component and the reference quantity , are the lift coefficient and the total drag coefficient . The latter can be decomposed into friction and pressure drag coefficients; the former describes the resistance to the relative motion between the fluid and the solid boundary due to viscous effects, the latter quantifies the net drag force arising from pressure variation around the body. When a wing of finite span is considered, the drag coefficient can alternatively be decomposed into induced and profile drag coefficients. The former, defined as describes the additional drag due the three dimensional effects cause by the lift, and the latter, defined as describes the same quantity due to all the other types of drag except that which is lift induced. Profile drag can further be decomposed in friction drag and form drag . Lastly, the local skin-friction and pressure coefficients are defined as and (in the coefficient subscripts, capital letters indicate global quantities and small letters indicate local quantities).
Changes between clean and riblets configurations are computed as , where the subscript 0 refers to the clean configuration and x is the quantity of interest. The drag reduction rate, i.e., the change in drag normalised with the drag of the clean configuration is defined as .
5. Conclusions
The drag reduction potential of riblets deployed on a fixed-wing, low-speed Unmanned Air Vehicle (UAV) has been assessed with RANS simulations, with the aim of determining an optimal coverage policy. While riblets are fully characterised in low-speed flows over plane walls, and studies are available for aeronautical configurations in transonic flow (commercial mid- or long-range passenger aircraft), a low-speed aircraft such as the present one (for which the cruise speed is only 22 m/s) is considered here for the first time. Since the friction component of the aerodynamic drag of the UAV is modest, the effectiveness of riblets in this specific application needs to be assessed.
The RANS simulations, which employ a standard OpenFOAM setup, are unable to describe riblets directly. Thus, the presence of riblets is accounted for via a suitable slip condition enforced at the planar wall. The chosen amount of slip is constant in viscous units, and corresponds to riblets that locally possess optimal size in viscous wall units. The slip length model has been validated in the simple flows over a flat plate and around a subsonic airfoil, where results agree with available information.
Once applied to the UAV, the simulated riblets have brought out indirect and favourable effects, which go beyond the local reduction of friction drag, and also render the deployment of a friction-reduction device definitely interesting in such a low-speed application. Indeed, riblets significantly change the pressure distribution across the wing of the aircraft, which translates into an additional reduction of form drag, and in a lift increment as well. Although the latter obviously causes an increase in lift-induced drag, the requirement for the aircraft in cruise to fly at a given lift leads to a reduced angle of attack, and thus, to a further contribution to drag reduction. In the end, riblets provide up to 3% reduction of the total drag of the aircraft at cruise speed: a noticeable result, especially when the low-flight Reynolds number of the UAV is considered.
Once a cheap computational model is available to reliably compute the global effect of riblets on the aerodynamic drag, varying the riblets coverage policy becomes a computationally affordable task; relatively inexpensive simulations can help determine what drag benefit can be achieved with a given extent and location of the coverage of the aircraft surface. Thanks to the importance of secondary effects on pressure drag reduction induced by riblets, as a consequence of the significant pressure drag component, up to of total drag reduction is achieved by placing riblets on the upper surface of the wing only. In this configuration, the total drag reduction is almost of the maximum obtained with full coverage, but it is obtained with a coverage of less than of the total area. Since riblets costs (for application and maintenance) are directly linked to the amount of riblets-covered surface, the wing-only configuration offers a reduced cost–benefit ratio, and does not touch the UAV fuselage, where systems (sensors, cameras, and transmitters) are designed to be installed. Further analysis can determine the practicality of riblets removal from high-wear areas (e.g., the leading edge), which would further add to the practical appeal of riblets in this application. Such calculations are made possible by the simplicity of the slip-length model, whose validity goes beyond riblets, since it can be used to simulate a generic drag-reducing device which locally reduces the skin friction.