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Revisiting the Lie-group symmetry method for turbulent channel flow with wall transpiration

The Lie-group-based symmetry analysis, as first proposed in Avsarkisov et al. (2014) and then later modified in Oberlack et al. (2015), to generate invariant solutions in order to predict the scaling behavior of a channel flow with uniform wall transpiration, is revisited. By focusing first on the results obtained in Avsarkisov et al. (2014), we failed to reproduce two key results: (i) For different transpiration rates at a constant Reynolds number, the mean velocity profiles (in deficit form) do not universally collapse onto a single curve as claimed. (ii) The universally proposed logarithmic scaling law in the center of the channel does not match the direct numerical simulation (DNS) data for the presented parameter values. In fact, no universal scaling behavior in the center of the channel can be detected from their DNS data, as it is misleadingly claimed in Avsarkisov et al. (2014). Moreover, we will demonstrate that the assumption of a Reynolds-number independent symmetry analysis is not justified for the flow conditions considered therein. Only when including also the viscous terms, an overall consistent symmetry analysis can be provided. This has been attempted in their subsequent study Oberlack et al. (2015). But, also the (viscous) Lie-group-based scaling theory proposed therein is inconsistent, apart from the additional fact that this study of Oberlack et al. (2015) is also technically flawed. The reason for this permanent inconsistency is that their symmetry analysis constantly involves several unphysical statistical symmetries that are incompatible to the underlying deterministic description of Navier-Stokes turbulence.


Motivation and objectives
The main purpose of this investigation is first to reveal in how far the work of Avsarkisov et al. (2014) can be reproduced. With focus on the results obtained from Lie-group analysis, we will re-examine all derivations and conclusions in Avsarkisov et al. (2014). One of the key results obtained therein was that of a new universal logarithmic scaling law in the center (core region) of a plane turbulent channel flow with uniform wall-normal transpiration. The derivation of this law, presented in Avsarkisov et al. (2014) as [Eq. (3.16)] where A 1 = kŪ 1 /k 1 , B 1 = k x 2 /(hk 1 ) are two group † and C 1 one arbitrary integration constant, is based on three independent scaling symmetries [Eqs. (3.2)-(3.4)] and two independent translation symmetries [Eqs. (3.5)-(3.6)] of the two-point correlation (TPC) equations [Eqs. (2.12)-(2.16)] for the purely inviscid case ν = 0. † The emergence of the particular scaling law (1.1) from these just mentioned symmetries is due to the externally set constant transpiration velocity v 0 , which acts as a symmetry breaking parameter in the scaling of the mean wall-normal velocityŪ 2 through the single constraint k 1 − k 2 + k s = 0 [Eq. (3.15)]. Central to the claim of Avsarkisov et al. (2014) is that when matching the new logarithmic law (1.1) to direct numerical simulation (DNS) data, then this law turns out to be a universal one when written in its deficit form (normalized to the mean friction velocity u τ as defined in [Eq. (2.1)] ‡ ) where all involved matching parameters γ, B 1 and C 1 are independent of the transpiration rate and Reynolds number. In particular, after a fit to the given data, the following universal values were proposed (Avsarkisov et al., 2014, Sec. 4, pp. 116-119): where γ is the new universal scaling coefficient to be distinguished from the usual von Kármán constant κ of the near-wall logarithmic scaling law, and where U B is the mean bulk velocity [Eq. (2.4)] which was kept universally constant in all performed simulation runs for different transpiration rates and Reynolds numbers (due to a fixed overall mass-flow rate employed in the used DNS code; for more details, see also Avsarkisov (2013)).
Our investigation on all these derived and proposed results involve three independent parts. After introducing the governing statistical equations and admitted Lie symmetries in Section 2 with the information only as given in Avsarkisov et al. (2014), we will demonstrate the following: (i) The DNS-data-matched value of A 1 in (1.1), namely A 1 = u τ /γ, is inconsistent to its theoretically derived value A 1 = kŪ 1 /k 1 composed of two group constants, which are, by construction, independent of the friction velocity u τ .
(ii) Fig. 9 (a) and (c) in Avsarkisov et al. (2014) cannot be reproduced when using the DNS data made available by the authors on their institutional website [fdy]. Neither does the data universally collapse onto a single curve for different blowing parameters in particular, nor does the logarithmic scaling law (1.2) with the proposed parameters (1.3) directly fit to this data.
(iii) For the inviscid (ν = 0) case, as particularly realized in Avsarkisov et al. (2014), as well as for the viscous (ν = 0) case, as subsequently modified in Oberlack et al. (2015), the Liegroup-based scaling theory shows in both cases a methodological inconsistency in that certain higher order velocity correlation functions cannot be matched anymore to the DNS data, despite involving all a priori known symmetries of the underlying statistical transport equations. The simple reason for this inconsistency is that several participating symmetries are unphysical in violating the classical principle of cause and effect. † Note that the large-Reynolds-number asymptotics in the cited reference Oberlack (2000) was performed differently than as claimed in the beginning of Sec. 3.1 on p. 109 in Avsarkisov et al. (2014). Not for |r| ≤ η, but rather, oppositely, only for |r| ≥ η it was shown that all viscous terms in the TPC equations vanish. For a corresponding English explanation of the "asymptotic analysis" performed in Oberlack (2000), see e.g. Oberlack (2002); Oberlack & Guenther (2003) or Khujadze & Oberlack (2004). Hence, oppositely as claimed, the symmetry analysis in Avsarkisov et al. (2014) was not performed on equations which have undergone a prior singular asymptotic analysis in the sense ν → 0, but instead, only on equations which just result from considering the purely inviscid (Euler) case ν = 0.
‡ In Appendix A we repeat the basic derivation of relation [Eq. (2.1)] in Avsarkisov et al. (2014) to acknowledge this result more carefully.

Governing statistical equations and admitted symmetries
Since the aim in Avsarkisov et al. (2014) is to investigate within the inviscid (ν = 0) TPC equations [Eqs. (2.12)-(2.15)] only large-scale quantities, such as the mean velocity or the Reynolds stresses, we will proceed accordingly by considering these TPC equations already in their onepoint limit (x (2) → x (1) = x, or in relative coordinates as r = x (2) − x (1) → 0): † ∂Ū k ∂x k = 0, (2.1) (2.4) are the Reynolds stresses and the third-order (one-point) velocity moments, respectively. Note that in this one-point limit all higher-order continuity constraints [Eqs.
Referring to the cited study Oberlack & Rosteck (2010) in Avsarkisov et al. (2014), it has been shown that that a simple and systematic structure for all symmetries is revealed if for the infinite hierarchy of multi-point correlation (MPC) equations the instantaneous (full) field approach is used (instead of the fluctuating, the so-called Reynolds-decomposed field approach as given above). In the one-point limit the corresponding full-field representation of the inviscid TPC equations reads: ∂U k ∂x k = 0, (2.5) which, of course, turns exactly into the system (2.1)-(2.3) when decomposing the full fields into their mean and fluctuating part, i.e., by performing a usual Reynolds field decomposition ‡ U i =Ū i + u i , P =P + p. (2.8) Although both representations (2.1)-(2.3) and (2.5)-(2.7) are equivalent, the latter one has the unreckoned advantage, according to Oberlack & Rosteck (2010), of being a linear system which makes the extraction of Lie symmetries considerably easier. For the specific flow considered in Avsarkisov et al. (2014), both systems (2.1)-(2.3) and (2.5)-(2.7) equivalently reduce further. Considered is a statistically stationary plane channel flow of width w = 2h with a mean constant wall-normal transpirationŪ 2 = v 0 . In the streamwise direction the flow is driven by constant mean pressure gradient, which we will denote as K, in particular ∂P /∂x 1 = −K, where K > 0 is some arbitrary but fixed positive value. Finally, due to spanwise homogeneity and a spanwise reflection symmetry in this flow, the mean spanwise velocity as well as all velocity moments involving an uneven number of spanwise velocity fields vanish. Hence, for the just-stated assumptions, the full-field system (2.5)-(2.7) reduces to: † ∂U 2 ∂x 2 = 0, (2.9) while its corresponding Reynolds decomposed system (2.1)-(2.3) equivalently reduces to: ∂Ū 2 ∂x 2 = 0, (2.12) (2.14) When considering the list of TPC symmetries [Eqs. (3.2)-(3.6)] as analyzed in Avsarkisov et al. (2014), then the reduced Reynolds-decomposed system (2.12)-(2.14) admits the symmetries ‡ T 1 : x * i = e k 1 x i ,Ū * i = e k 1Ū i ,P * = e 2k 1P , τ * ij = e 2k 1 τ ij , τ * ijk = e 3k 1 τ ijk , u i ∂p ∂x j * = e 2k 1 u i ∂p ∂x j , (2.15) i ,P * = e ksP , τ * ij = e ks τ ij + e ks − e 2ks Ū iŪj , τ * ijk = e ks τ ijk + e ks − e 2ks Ū i τ jk +Ū j τ ik +Ū k τ ij + e ks − 3e 2ks + 2e 3ks Ū iŪjŪk , u i ∂p ∂x j * = e ks u i ∂p ∂x j + e ks − e 2ks Ū i ∂P ∂x j , (2.17) † The two assumptions that the mean pressureP decays linearly in the streamwise direction and that the mean wall-normal velocityŪ2 is constant across the channel height will be applied at a later stage.
‡ Please note that since the system (2.9)-(2.11), or its equivalent Reynolds decomposed system (2.12)-(2.14), is unclosed even if the infinite hierarchy of equations is formally considered, all admitted invariant transformations can only be regarded in the weak sense as equivalence transformations, and not as true symmetry transformations in the strong sense. For more details, we refer to Frewer et al. (2014); Frewer (2015a,b) and the references therein. In the following, however, we will continue to call them imprecisely as "symmetries", like it was also done in Avsarkisov et al. (2014).
which directly follows from the set of TPC symmetries [Eqs. (3.2)-(3.6)] † in Avsarkisov et al. (2014) when performing the limit of zero spatial correlation r → 0 (one-point limit) and a subsequent prolongation to higher-order moments. By equivalently rewriting the moments into their full-field form, we obtain the corresponding symmetries admitted by the reduced full-field system (2.9)-(2.11): which again, when performing the Reynolds decomposition (2.8), turn back into the symmetries (2.15)-(2.19). In contrast to the translation symmetryTŪ 1 (2.24), the scaling symmetryT ′ s (2.22) gained a very simple form in the full-field representation. This so-called third scaling symmetrȳ T ′ s in the TPC equations was first derived and discussed in Khujadze & Oberlack (2004), and only later generalized in Oberlack & Rosteck (2010) for the infinite hierarchy of MPC equations.
As we will demonstrate in detail in Section 5, since our central aim is to coherently extend the invariance analysis in Avsarkisov et al. (2014) to higher-order moments in which the scaling law for the lowest-order moment (mean velocity field) is based on a translation symmetry, corre-sponding and independent translation symmetries are also needed for all higher-order moments in order to generate invariant functions with arbitrary offsets being flexible enough to match the DNS data. In other words, to be able to robustly match higher-order invariant functions to DNS data, higher-order translation symmetries are needed as they were first derived in Oberlack & Rosteck (2010).
In this regard it is worthwhile to note that the considered TPC translation symmetry [Eq.(3.6)] in Avsarkisov et al. (2014), does not correspond to the symmetry "discovered in the context of an infinite set of statistical symmetries in Oberlack & Rosteck (2010)" [p. 110], as misleadingly claimed in Avsarkisov et al. (2014). Instead, when adapted to the reduced one-point and full-field system (2.9)-(2.11), it is given by [Eq. (58)] in Oberlack & Rosteck (2010) (2.25) or, in its corresponding Reynolds decomposed form, as which does not reduce to (2.19), when specifying the group constants correspondingly to c 1 = kŪ 1 and c 2 = d = c ij = c ijk = 0, and which thus is the symmetry sought that independently translates all higher-order moments. In other words, the single translation symmetry (2.19) is not a "first principle" symmetry as misleadingly claimed in Avsarkisov et al. (2014), but was, in contrast to (2.26), rather introduced in an ad hoc manner just to serve the single purpose to generate a suitable logarithmic scaling law for the lowest-order moment (mean velocity field) without knowing at the same time whether this scaling is also consistent to all higher-order moments. ‡ Hence, next to the single translation symmetry (2.19), we will also apply the new "statistical translation symmetry" (2.26), first proposed in Oberlack & Rosteck (2010), in order to achieve a consistent prolongation to all higher-order moments within the symmetry analysis as particularly put forward and initialized in Avsarkisov et al. (2014) (see Section 5.1), and then as subsequently modified in Oberlack et al. (2015) (see Section 5.2).

On the inconsistency between the data-matched value and the theoretically predicted relation of A 1
As described in Sec. 4 in Avsarkisov et al. (2014), the best fit to all DNS data is obtained if the scaling coefficient in the theoretically derived law (1.1) is chosen as Since all simulation runs in Avsarkisov et al. (2014) were performed under the unusual constraint of a universally fixed mean bulk velocity U B = U * B for different transpiration rates v + 0 = v 0 /u τ † Due to the particular flow configuration considered, transformation (2.25) is only admitted as a symmetry by (2.9)-(2.11) if c13 = c23 = c333 = 0, and cij3 = 0, for all i = 3 and j = 3.
‡ Regarding the justification of the translation symmetry (2.19) given as [Eq.(3.6)] in Avsarkisov et al. (2014), it should be noted that also their statement "... that the first hint towards (3.6) has been given by Kraichnan (1965)" [p. 110], is incorrect and constitutes a misinterpretation of Kraichnan's idea to random Galilean invariance. This misconception has been recently revealed in Frewer et al. (2015). and Reynolds numbers Re τ = u τ h/ν, one inevitably obtains the following parametrical dependency relationship for the mean friction velocity †  Avsarkisov et al. (2014) and recalling the fact that due to the Navier-Stokes equations along with the supplemented boundary conditions, the mean streamwise velocity profile will in general be a function of all involved parameters of the considered flow (h: channel half-hight, K: constant mean streamwise pressure gradient, v 0 : constant mean wall-normal transpiration rate, ν: kinematic viscosity): where the last relation represents its non-dimensionalized single form (relative to u τ = |K|h) depending only on two dimensionless variables v , then two of the three parameters u τ , v + 0 and Re τ can be varied independently to satisfy this constraint. The third one is then predetermined by solving (3.3) for this parameter, e.g., if we choose u τ as the dependent one, we obtain in this particular normalization the relation which, of course, represents the unique dimensional reduction of its generalized expression (3.2).
In Table 1 we provide the set of data obtained in Avsarkisov et al. (2014) to illustrate the mode of action of relation (3.4) for different turbulent flow conditions. The corresponding laminar flow cases are given as a comparison, which, in contrast to the turbulent ones, can be determined analytically, where in particular the dimensionless function Π in (3.4) can be represented even in closed form (see (B.10) in Appendix B). To note is the non-intuitive result that if v + 0 stays fixed, u τ monotonically decreases as Re τ increases; a result obviously caused by the (universally fixed) constant mean bulk velocity U * B for these simulations. Hence, according to (3.4), the empirically matched scaling coefficient A 1 (3.1) shows the following dependency in that it can be equivalently written as .
(3.5) However, such a dependency is inconsistent to the theoretically derived result of A 1 in (1.1), which is given as where kŪ 1 and k 1 are two group parameters which both, due the particular symmetry analysis performed in Avsarkisov et al. (2014), are independent of the Reynolds number Re τ . The reason is that the performed symmetry analysis in Avsarkisov et al. (2014) was done under the constraint of zero viscosity (ν = 0), thus leading to a Lie-group-based derivation of A 1 (3.6), that, by construction, cannot depend on ν (or equivalently on Re τ ). † That an extra parametrical relation as (3.2) is necessary to follow and to understand the numerical simulation performed, has not been directly discussed in Avsarkisov et al. (2014). For all simulation runs, the value U * B was unconventionally chosen as U * B = 0.8987. Note that this information is not given in Avsarkisov et al. (2014); it can only be found on their institutional data repository [fdy].   Avsarkisov et al. (2014), while the values U * B and u τ for the turbulent flow case were taken from the corresponding DNS data base disclosed by the authors on their institutional website [fdy]. The values for the corresponding laminar friction velocities u L τ were calculated through the analytical formula (B.11) (for given U * B , Re τ and v + 0 ) to serve as a comparison to the DNS-determined mean friction velocities u τ in the turbulent case.
Although the friction velocity u τ (3.4) only shows a rather weak Re τ -dependence when compared to its dependence on the transpiration rate v + 0 , as can be seen in Table 1, this dependence, however, cannot be neglected: For example, for the fixed transpiration rate v + 0 = 0.05, we have a change of nearly 15% in u τ when increasing the Reynolds number from Re τ = 250 to 850. This change in u τ (3.4) is then directly reflected in A 1 according to its empirical relation (3.5) proposed in Avsarkisov et al. (2014). And this change will continue to grow when increasing the Reynolds number even further. But, as we can observe from the corresponding laminar values u L τ in Table 1, this growth is bounded, i.e., for Re τ → ∞ the values for u τ will converge to some certain finite value u ∞ τ , which is also expected to happen in the turbulent case since the flow is arranged under the same unusual condition of a universally fixed bulk velocity U * B : In contrast to the laminar case, where this value is analytically accessible and particularly given as u ∞ τ = U * B v + 0 , it is, of course, an unknown quantity for the turbulent case; yet still, it will take a different (most possibly lower) value than for any finite Reynolds number Re τ < ∞.
Although weak, the friction velocity u τ (3.4), and thus also the empirically matched logarithmic scaling coefficient A 1 (3.5), nevertheless shows a non-negligible Re τ -dependence for every initially fixed transpiration rate v + 0 , a dependence which, as we will demonstrate in Section 5.1, is critical when extending the symmetry analysis as put forward in Avsarkisov et al. (2014) to higher-order moments.
Hence, the central assumption in Avsarkisov et al. (2014) to predict the (non-normalized) mean velocity scaling behavior in the center of the channel by an invariant log-law resulting from a non-viscous (ν = 0) symmetry analysis, namely by (1.1) where A 1 and B 1 are independent on (-· -); dŪ + 1 /dx + 2 (· · · ); τ + − v + 0Ū + 1 (-), where τ + = −u 1 u 2 + + dŪ + 1 /dx + 2 is the total shear stress without transpiration as defined in [Eq. (2.11)] in Avsarkisov et al. (2014). The differences in this right plot to Fig. 3 (c) are of minor significance: (i) The small numerical error (misfeature) at the wall boundaries in the profile τ + − v + 0Ū + 1 (solid line) has not been displayed in Fig. 3 (c). Across the full channel height, a pure straight line with the same slope of measure one has been given instead, i.e., the true profile of this quantity has not been plotted in Avsarkisov et al. (2014). (ii) A careful comparison reveals a very small discrepancy in the vertical position of both the dashed-dotted and the solid line. This negligible difference may be explained by the circumstance that the data base on the author's website may refer to a different, most possibly to a newer simulation run with a better statistics than the one presented in Avsarkisov et al. (2014): The latter version was published in January 2014, while the released data base on their website was created a year later in February 2015. Nevertheless, both plots above show that Fig. 3 (a) and (c) in Avsarkisov et al. (2014) are reproducible, confirming thus that we are using the correct data set.
Re τ , is not justified. For that, a viscous (ν = 0) symmetry analysis has to be performed, but then, as we will consequently show in Section 5.2, no invariant mean velocity profile forŪ 1 can be constructed anymore, † due to the well-known (scaling) symmetry breaking mechanism of the viscous terms.

On the problems when trying to reproduce Figure 9
In this section we show the results of our effort to reproduce Figs. 9 (a) and (c) in Avsarkisov et al. (2014). The underlying simulation data were taken from the author's institutional website [fdy]. To verify and to ensure that we operate with the same data set as presented in Avsarkisov et al. (2014), we first have to check if we are able to repeat the construction of another figure. By choosing Figs. 3 (a) and (c) as representative test cases, our reproduced plots in Figure 1 undoubtedly show that we are indeed in hold of the correct simulation data to systematically investigate the reproducibility of all plots in Avsarkisov et al. (2014).
Hence, the result of Figure 1 allows us to make the conclusion that both Figs. 9 (a) and (c) in Avsarkisov et al. (2014) are not reproducible, when considering our reproduction in Figure 2 and Figure 3, respectively. † Except only for a linear profile (5.40) as derived in Section 5.2, but which, of course is not a reasonable turbulent scaling law. To note is that in Oberlack et al. (2015) the authors succeeded to derive both a logarithmic as well as an algebraic scaling law for the mean velocity field in the viscous case. But, as we will analytically prove in Section 5.2, both results are based on a methodological mistake. This is also expressed in the fact that as we repeat their inconsistent analysis, certain higher order moments cannot be matched to the DNS data.  Table 1 for the corresponding values). The solid line displays the new (theoretically predicted) logarithmic scaling law (1.2) for the parameters γ = 0.3, B 1 = 0 and C 1 = U B as proposed in Sec. 4 in Avsarkisov et al. (2014). Obviously, a comparison to Fig. 9 (a) readily reveals that this figure is not reproducible. It shows a strong discrepancy in two independent aspects with the effect that an overall opposite conclusion is obtained than as proposed in Avsarkisov et al. (2014). For more details, see the main text. Right plot: To have a qualitative comparison to the turbulent case, we plotted the corresponding laminar profiles for the same external parameters as were used in the figure on the left-hand side. From top to bottom (relative to the positive function values), the corresponding laminar profile structure is displayed for increasing transpiration rates v + 0 = 0.05, 0.1, 0.16, 0.26 at fixed Re τ = 480 and U B = U * B = 0.8987. The associated values for the laminar friction velocities u L τ can be taken from Table 1, which are based on the closed analytical expression for the laminar velocity profile U L 1 (B.11). See the main text for a comparative discussion between the turbulent case (left plot) and its corresponding laminar case (right plot).  Avsarkisov et al. (2014) with the data provided by the authors on their institutional website [fdy]. In the same way as in Figure 2, the mean velocity profile in deficit form is again displayed, but now at a constant transpiration rate v + 0 = 0.16 for different Reynolds numbers: Re τ = 250 (•); Re τ = 480 (•); Re τ = 850 ( ⊲). The solid line displays again the new (theoretically predicted) logarithmic scaling law (1.2) for the corresponding parameters γ = 0.3, B 1 = 0 and C 1 = U B , as proposed in Sec. 4 in Avsarkisov et al. (2014) also for this case. Right plot: For the same motivation as in Figure 2, the corresponding laminar deficit profiles are plotted. From left to right the Reynolds number increases Re τ = 250, 480, 850 at fixed transpiration rate v + 0 = 0.16 and bulk velocity U B = U * B = 0.8987. The laminar velocity profile U L 1 and its associated consistent friction velocity u L τ are given through the analytical expressions of (B.11); the explicit values of u L τ for the considered parameter combinations are given again in Table 1. For a comparative discussion between the turbulent case (left plot) and its corresponding laminar case (right plot), see again the main text. 4.1. The nonreproducibility of Figure 9 (a) Comparing our left plot in Figure 2 with the corresponding Fig. 9 (a) in Avsarkisov et al. (2014), readily reveals that this figure is not reproducible. It shows a strong discrepancy in two independent aspects with the effect that an overall opposite conclusion is obtained than as proposed in Avsarkisov et al. (2014): (i) The DNS data for the mean streamwise velocity at a fixed Reynolds number and varying transpiration rates, do not universally collapse onto one single curve when formulated in its deficit form. Instead we see a monotonous decay of the profile as the transpiration rate increases. (ii) The theoretically predicted scaling law (solid line) does not match the data, not even in a rough approximate sense. For that different matching parameters need to be formulated. If B 1 is continued to be chosen as zero, then both γ and C 1 need to be functions of v + 0 , where it should be noted that for higher transpiration rates the matching region shifts to the suction wall x 2 /h = 2.
The right plot in Figure 2 serves as a comparative reference to the left one. It allows to compare the differences and similarities between the laminar and the turbulent flow behavior. For the same external parameters as were used for the turbulent case, this plot shows the corresponding laminar profiles derived in analytically closed form in Appendix B, with the final result given in (B.11). Interesting to see is how the deficit profile at a constant finite Reynolds number decays for increasing transpiration rates until it globally goes to zero when reaching the . A similar behavior, although based on a more complex functional structure, is also to be expected for the turbulent case: † Indeed, in the left plot the onset of this global tendency in the DNS data can already be positively observed.

The nonreproducibility of Figure 9 (c)
Comparing now the left plot of Figure 3 with the corresponding Fig. 9 (c) in Avsarkisov et al. (2014), we see that although the DNS data in this case more or less universally collapses onto a single curve and also coincides with the representation and conclusion in Avsarkisov et al. (2014), the new logarithmic scaling law (1.2) (solid line), however, still does not match the data for the proposed parameters γ = 0.3, B 1 = 0 and C 1 = U B . For an unaltered γ, a vertical upward shift of at least 0.82 units is needed, i.e., in order to match the data, the integration constant C 1 needs to be modified from C 1 = U B at least to C 1 = U B + 0.82 · u τ , a result not obtained in Avsarkisov et al. (2014). Hence, we may correctly claim that also Fig. 9 (c) is not reproducible.
As in Figure 2, the corresponding laminar deficit profiles are presented and studied in the right plot of Figure 3. Interesting to see here is that by close inspection the deficit profiles at a constant transpiration rate do not really collapse onto a single curve, but rather, within the range 0 ≤ x 2 /h < 2, slowly converge to a particular linear profile in the limit of infinite Reynolds number Re τ → ∞. Note that this convergence takes place pointwise, i.e., the points close to the blowing wall (x 2 /h = 0) converge exponentially faster than those points close to the suction wall (x 2 /h = 2), due to the presence of a boundary layer at this side. In particular, the deficit profile converges to ( , equivalently as in the previous section for a fixed Reynolds number, the laminar velocity profile in this range converges again to U L 1 → U * B ·x 2 /h, since in this case for a fixed transpiration rate u L τ → U * B ·v + 0 ; see (B.11). A similar behavior, although based on a more complex functional structure, is also to be expected for the turbulent case: Indeed, by close inspection of the left plot of Figure 3, one can observe that everywhere throughout the channel, the DNS data does not universally lie on a single curve as claimed in Avsarkisov et al. (2014), but that in fact for increasing Reynolds number a (slow) pointwise convergence towards a particular profile takes place. † Note that global laminar flow properties are most probably also statistically featured by the corresponding turbulent flow condition and thus also to be expected in a qualitative sense. The opposite conclusion, however, is of course not true: A turbulent flow may statistically show additional features that are not existent in its associated laminar base flow.

On the inconsistency of the Lie-group-based scaling theory in turbulence
In this section we will reveal the fact that when coherently extending the Lie-group-based scaling theory as presented in Avsarkisov et al. (2014) for the newly proposed logarithmic law [Eq. (3.16)] to higher orders of the one-point velocity correlations, one unavoidably runs into a fundamental inconsistency in that one fails to match certain theoretically derived scaling laws to the given DNS data. We will investigate both the inviscid (Euler, ν = 0) case, as particularly realized in Avsarkisov et al. (2014), as well as the viscous (Navier-Stokes, ν = 0) case, as subsequently modified in Oberlack et al. (2015). To simplify formal expressions and calculations, we will derive all theoretical results in the full-field (instantaneous) representation. The corresponding Reynolds decomposed results (later needed to directly compare to the DNS data) are then obtained straightforwardly by just performing the decomposition (2.8). To demonstrate our point in this section, it is fully sufficient to only consider the turbulent transport equations up to second order, since they already involve (unclosed) third order moments for which the inconsistency to the DNS data is clearly pronounced.

The inviscid case (ν = 0)
The governing one-point equations for the flow considered in Avsarkisov et al. (2014) are given by the system (2.9)-(2.11), which, as discussed in Section 2, admits the continuous set of Lie-point symmetries (2.20)-(2.24) and (2.25), where the latter symmetry is needed to appropriately extend the construction of invariant solutions in Avsarkisov et al. (2014) to higher-order moments. Hence, when combining all symmetries and following the line of reasoning in Avsarkisov et al. (2014), we obtain the following invariant surface condition (5.1) which coherently extents their corresponding condition [Eq. (3.12)] up to third order including the pressure moments. The functional κ-extensions result from the single translation symmetrȳ TŪ 1 (2.19) when written in its equivalent full-field form (2.24), and are thus given as † Progressively, we will now determine all invariant functions from (5.1) and examine in how far they are compatible to the underlying equations (2.9)-(2.11). The first step in this procedure † Note that the quadratic term k 2 U 1 δ1iδ1j in the transformationTŪ 1 (2.24) for UiUj is not contributing in its local (infinitesimal) generator, since Lie-group symmetry theory is a linear theory where all information of the transformations is carried in the linear expansion terms of the group parameters.
is to ensure the invariance of any existing constraints. We recall the two constraints of a mean constant wall-normal velocity U 2 = v 0 , or, equivalently dU 2 = 0, and that of a mean constant streamwise pressure gradient ∂P /∂x 1 = −K, or, equivalently d(∂ 1 P ) = 0. Implementing the first constraint dU 2 = 0 into (5.1) will consequently result into the corresponding combined symmetry breaking constraint † k 1 − k 2 + k s = 0, and c 2 = 0, (5.3) as discussed and implemented in Avsarkisov et al. (2014). The second constraint d(∂ 1 P ) = 0, however, will result into an additional symmetry breaking constraint which was not discussed in Avsarkisov et al. (2014); an important result indeed, since, due to (5.3), it equivalently turns into the strong constraint Note that this result could have also been obtained when directly solving from condition (5.1) the invariant function for the pressure P as a function of x 1 and x 2 along with the first constraint of (5.3). Because, this result, when taking its gradient in the streamwise direction, if the integration function F 1 is a global constant equal to −K, and, if k 2 = 0. Collecting now all obtained symmetry breaking constraints and applying them to the originally formulated condition (5.1), will drastically restrict the possible structures for the considered invariant functions. For example, for the mean streamwise velocity profileŪ 1 only a logarithmic function of the form is possible, where C 1 is an arbitrary integration constant and A 1 = (kŪ 1 +c 1 )/k 1 , B 1 = k x 2 /(k 1 h) two independent parameters uniquely determined by internal group constants. But, not only the symmetry breaking constraints, also the underlying dynamical equations of the considered system restrict the functions (for ODEs) or the functional possibilities (for PDEs) even further, for example, when considering the full derivation of the invariant correlation U 1 U 2 : From the defining condition (5.1) with inserted constraints (5.8) it is initially given by where C 12 is again some arbitrary integration constant, and whereÃ 12 = −(kŪ , is a parameter that, apart from the external system parameter v 0 , comprises again internal group constants. ‡ However, the arbitrariness of C 12 is illusive, because the † Note that both constraints in (5.3) are necessary to avoid an overall zero surface condition (5.1). ‡ That the parameterÃ12 includes the external system parameter v0, is denoted by the "tilde" symbol. With the notation introduced in (5.12), this parameter can also be written asÃ12 = A12 + A0v0, where A12 = −c12/k1 and A0 = −kŪ 1 /k1 are then two parameters determined by internal group parameters only. This notation will also be used later in (5.15) when matching the invariant functions to DNS data, where the "tilde" symbol denotes essential fitting parameters collecting all constants, independent of their nature, into a single expression. underlying momentum equation (2.10) restricts it to (5.11) All remaining invariant functions can then be generically determined as where the C-parameters are arbitrary integration constants, while the A-parameters are determined through the group constants as and, finally, the modified δ-functions in (5.12) are defined as The arbitrary integration constants, however, are not fully independent but show certain fixed interrelations resulting from the underlying transport equations (2.9)-(2.11) that the invariant functions need to satisfy, e.g., C p = −C 22 /h, or 2C 122 /h + C p 12 + C p 21 = 0. When Reynolds decomposing all derived invariant results, we straightforwardly obtain † which then can be validated against the given DNS data. Note that we only listed those functions for which the statistical data has been made available from the DNS in Avsarkisov et al. (2014). For the scaling factor (5.11) we used the central definition u 2 τ = K · h (see [Eq. (2.1)]). When fitting the set of functions (5.15) to the data, special attention has to be paid to the invariant scaling laws for τ 11 , τ 12 and τ 112 , which all show a combination of an algebraic and a logarithmic scaling, an awkward property, which again only has its origin in the new statistical symmetries T ′ s (2.22) andT ′ c (2.25) first proposed in Oberlack & Rosteck (2010). † The four "tilde"-parameters are given as: Figure 4: Matching of the theoretically predicted scaling laws (5.15) to the DNS data for Re τ = 480 and v + 0 = 0.05. The DNS data is displayed by solid lines, the corresponding scaling laws by dashed lines. The associated parameters for this best fit in each case can be taken from Table 2, where the matching region was chosen in the range 0.50 ≤ x 2 /h ≤ 1.25. For more details and a discussion on the fitting results obtained, see the main text.
Figure 5: Matching of the theoretically predicted scaling laws (5.15) to the DNS data for the same Reynolds number Re τ = 480 as in the figure given above, but for a higher transpiration v + 0 = 0.16. The DNS data is again displayed by solid lines, the corresponding scaling laws by dashed lines. The associated best-fitted parameters can be taken again from Table 2, where the matching region was now set differently in the range 0.75 ≤ x 2 /h ≤ 1.70. For more details and a comparative discussion on the fitting results obtained between the lower (Figure 4) and the higher transpiration case ( Figure 5), see again the main text. Figure 4 & 5 show the matching of the analytically (from "first principles") derived scaling laws (5.15) to the DNS data at Re τ = 480 for the two different transpiration rates v + 0 = 0.05 and v + 0 = 0.16, respectively. The matching was performed in the u τ -normalization, i.e., for the normalized velocity correlations τ + ij = τ ij /u 2 τ and τ + ijk = τ ijk /u 3 τ , as well as for the normalized mean velocity field in its deficit form ( The particular values for u τ as well as for U B = U * B in each case can be taken from Table 1. The matching region in Figure 4 was chosen in the range 0.50 ≤ x 2 /h ≤ 1.25, based on the best fit regarding the central prediction in Avsarkisov et al. (2014), namely that of a new logarithmic scaling law (1.2) for the mean velocity field in the center of the channel  Table 2: Best-fitted parameters of the theoretically predicted scaling laws (5.15) to the DNS data as shown in Figure 4 & 5 for two different transpiration rates v + 0 = 0.05 and v + 0 = 0.16, respectively, at Re τ = 480. The parameter A + 0 was fitted for τ + 11 , and then applied in τ + 112 : It takes the value A + 0 = 13.82 for v + 0 = 0.05, and A + 0 = 6.971 for v + 0 = 0.16. The matching region for the lower rate v + 0 = 0.05 was chosen in the range 0.50 ≤ x 2 /h ≤ 1.25, while for the higher rate v + 0 = 0.16 it was determined to lie in the range 0.75 ≤ x 2 /h ≤ 1.70. For more details, see the main text.
with the fixed universal scaling coefficient γ = 0.3 referring to (1.3). Note that in Avsarkisov et al. (2014) no additional vertical shift λ was needed, but which, as we have demonstrated before, only leads to non-reproducible results (see Section 4, in particular the discussion on the nonreproducibility of Fig. 9 (c) in Avsarkisov et al. (2014)). Depending on the transpiration rate and the Reynolds number, a constant vertical upward shift λ > 0 is necessary to match the DNS data. Its presence, of course, re-defines the proposed integration constant in (1.3) as C 1 = U B + λ · u τ , turning thus C 1 into a non-universal constant, depending then on both the Reynolds number Re τ and the transpiration rate v + 0 , where the latter dependency is more pronounced than the former one. A result opposite to the one claimed in Avsarkisov et al. (2014), where C 1 was determined as a universal constant, with the particular value C 1 = U B (1.3) for a universally fixed bulk velocity U B = U * B as it is explicitly given in Table 1. Based on the matching region in Figure 4, the corresponding region for the higher transpiration rate in Figure 5 was determined to lie in the range 0.75 ≤ x 2 /h ≤ 1.70. This range was determined such that it has the same absolute residual range −0.015 ≤ y s − f m (x 2 /h) ≤ 0.015 as the one chosen for the lower transpiration rate in Figure 4 when fitting the central scaling law (5.16), where y s = (Ū 1 − U B )/u τ are the simulated (DNS) values and f m (x 2 /h) = ln(x 2 /h)/γ + λ the values from the considered model function. † Such a procedure is necessary if one is interested in how an initially chosen matching region changes when varying any external system parameters. When comparing the matching region 0.50 ≤ x 2 /h ≤ 1.25 for v + 0 = 0.05 in Figure 4, with the corresponding region 0.75 ≤ x 2 /h ≤ 1.70 for v + 0 = 0.16 in Figure 5, we clearly observe that as the transpiration rate moderately increases at constant Reynolds number (up to v + 0 ≤ 0.16), the matching region not only grows in extent, but that it also, at the same time, shifts to the right towards the suction wall (x 2 /h → 2). An important result which again has not been indicated in Avsarkisov et al. (2014). Instead, only the first property of a growing validity region is reported, which, however, cannot be true as a single statement for ever increasing transpiration rates: In fact, since for higher rates the validity region also shifts more and more to the fixed right-hand boundary at the suction wall, it eventually has to revert this growing trend at a certain transpiration rate high enough. For example, the rate v + 0 = 0.26 (at Re τ = 480) is already sufficient to demonstrate a non-increased validity region when compared to all lower rates at the same Reynolds number. Based on the same (residual) condition as for the considered lower rates, the matching region for v + 0 = 0.26 reduced to 1.35 ≤ x 2 /h ≤ 1.80, where at the same time a strong shift to the right (suction side) has occurred.
In the following (comparative) discussion on the quality of the fits for the velocity correlations τ + ij and τ + ijk in Figure 4 & 5, we will only focus on the systematic failure when fitting scaling laws which show a simultaneous combination of an algebraic and a logarithmic scaling. The fitted correlation functions in (5.15) can be separated into two classes: Those which show a strong (at least quadratic) dependency on the mean streamwise velocity fieldŪ 1 , as τ + 11 and τ + 112 , and those which only show a weak (at most linear) or no dependency at all on this field, as the remaining ones in this list: τ + 12 , τ + 33 and τ + 223 . While the latter correlations more or less satisfactorily match the DNS data (where the lower order correlations τ + 12 and τ + 33 show a better matching than the higher order one τ + 223 ), the fitting of the former correlations τ + 11 and τ + 112 fails to predict the tendency of the data.
Based on our previous studies Frewer et al. (2014Frewer et al. ( , 2015 supplemented by Frewer (2015c) and Frewer et al. (2016), several different mathematical proofs are given that explain this failure and discrepancy in the matching results. The origin simply lies in the fact that the general and explicitŪ i -dependency in the scaling laws (5.15) for the velocity correlations result from two "statistical symmetries"T ′ s (2.17) andT ′ c (2.26) that violate the classical principle of cause and effect. That is, theŪ 1 -as well as theŪ 2 -dependency in the velocity correlations τ + ij and τ + ijk are simply unphysical. The negative results appear more strongly, of course, in the correlations involving the unphysicalŪ 1 -dependence. † The unphysicalŪ 2 -dependence, however, is less critical for the particular flow case considered here, since it is only a global constant,Ū 2 = v 0 . Worthwhile to note here is that the mismatch of τ + 11 and τ + 112 in Figure 5 is less severe for a higher transpiration rate than in Figure 4 for a lower one. The reason is that the unphysical U 1 -dependence gets weaker for increasing transpiration rates, simply because the mean velocity fieldŪ + 1 itself is globally decaying for higher rates (see Figure 1). Moreover, the key assumption in Avsarkisov et al. (2014) that an inviscid (Re τ -independent) symmetry analysis is sufficient to capture the scaling behavior in the center of the channel, is not justified. Instead a strong sensitivity on Re τ in the scaling laws (5.15) is observed, which, in comparison to Figure 4, is shown in Figure 6. This figure was generated under the assumption of Avsarkisov et al. (2014) that the Reynolds-number-independent scaling of the (non-normalized) higher-order moments (5.15) is correct: All involved parameters, once matched for a certain fixed Reynolds number Re τ and transpiration rate v + 0 , should then stay invariant as Re τ changes. Of course, this assumed invariance should only hold for the non-normalized parameters as formulated in (5.15), and not for the u τ -normalized ones, simply because the friction velocity u τ itself changes when the Reynolds number Re τ varies. Although this dependence u τ ∼ u τ (Re τ ) is rather weak for a fixed transpiration rate v + 0 and bulk velocity U * B as can be seen in Table 1, † Note that we do not criticize the functional structure of the logarithmic scaling law ofŪ1 itself, which can be more or less robustly matched to the DNS data in the channel center. We rather criticize its invariant Liegroup based derivation yielding this function with the aid of unphysical symmetries, and its consequent unnatural appearance in all higher order velocity correlations having a streamwise component. This criticism is all the more significant and pertinent as in Avsarkisov et al. (2014) the misleading impression is conveyed that the new logarithmic scaling law [Eq. (4.3)] for the channel center is based on a derivation from first principles. Yet, in this regard, it also should be clear that we do not criticize the method of Lie-groups itself, being a very useful mathematical tool indeed, when only applied to the right problems. However, in Avsarkisov et al. (2014) the method of Lie symmetry groups has been misapplied. The reason for this mistake was, and still is, not to recognize that every methodology in science has its limits, in particular the fact that also the theory of Lie-groups cannot analytically circumvent the closure problem of turbulence, even if the infinite hierarchy of statistical equations is formally considered. Because, instead of true symmetry transformations only the weaker form of equivalence transformation can be generated for such (unclosed) systems, for which, in a strict mathematical sense, the construction of invariant solutions is misleading and sometimes even ill-defined if no further external information is provided: For example, as to close the system of equations through some modelling assumptions, or, as in the specific case of homogeneous isotropic turbulence, where one has exclusive access to additional nonlocal invariants such as the Birkhoff-Saffman or the Loitsyansky integral, to yield more valuable results from such equivalence scaling groups, in particular the explicit values for the decay rates. For more details, we again refer to Frewer et al. (2014);Frewer (2015a,b) and the references therein.
τ + 11 τ + 112 Figure 6: Sensitivity study on the Reynolds number Re τ at fixed transpiration rate v + 0 = 0.05. The solid lines display the DNS data for Re τ = 850; the dashed lines again the corresponding theoretically predicted (Re τ -independent) scaling laws (5.15) as proposed by Avsarkisov et al. (2014) when coherently prolonged to higher-order moments. This figure is to be compared with Figure 4, having the same transpiration rate v + 0 = 0.05 but at a lower Reynolds number Re τ = 480. Except for the mean velocity profile in deficit form, the strong sensitivity on Re τ for all higher-order moments hence proves our conclusion in Section 3: The central assumption made in Avsarkisov et al. (2014), namely that the scaling of a turbulent channel flow with uniform wall-normal transpiration can be predicted by considering an inviscid (ν = 0) symmetry analysis, i.e., by considering invariant solutions which, by construction, do not depend on Re τ , is not justified at all. Important to note here is that this strong sensitivity only lies in the matching parameters of the scaling laws (5.15), and not in the DNS data itself. For more details on how the above figure was generated and its connection to Figure 4, see the main text. this dependence, as was already discussed in Section 3, cannot be neglected, in particular not for any higher-order moments, where the relative change in the normalization factor u n τ for a moment of order n becomes more pronounced for increased order, as can be seen in Figure 6. The Reynolds number Re * τ refers to some fixed reference value, which, in the considered case for Re τ = 850 in Figure 6, is given by Re * τ = 480 (when compared to Figure 4). For example, for the given values u τ | Re * τ =480 ∼ 0.0551 and u τ | Reτ =850 ∼ 0.0501, taken from Table 1 at the fixed transpiration rate v + 0 = 0.05, the relative change in the normalization factor for the third order moment is already at ∆ % u 3 τ ∼ −25%; a change which definitely cannot be neglected anymore. Now, while the matching to the DNS data in Figure 4 was performed in the u τ -normalization for Re * τ = 480, and since for its comparison to a higher Reynolds number in Figure 6 a corresponding u τ -normalization for Re τ = 850 is needed, all "+"-parameters given in Table 2 have to be re-scaled by the ratio factor ϑ = u τ | Re * τ =480 /u τ | Reτ =850 ∼ 1.1011 in order to shift the (assumed invariant) non-normalized parameters as formulated in (5.15) from Re * τ = 480 to Re τ = 850. As mentioned before, although this factor ϑ is more or less close to one, it is not so anymore for the parametric values of any higher-order moments, where the change is significant. For example, for the normalized valueÃ + 12 of the second moment τ + 12 , fitted in Figure 4 and listed in Table 2, the relative change is already about 20%: It should be clear, that the scaling laws (5.15) in Figure 6 were not fitted to the DNS data, but the fact that they were obtained from the fitted results in Figure 4 by up-scaling the determined x 2 /h τ + 33 x 2 /h τ + 233 τ + 11 τ + 112 Figure 7: Matching of the theoretically predicted scaling laws (5.15) to the DNS data for Re τ = 850 and v + 0 = 0.05. The DNS data is displayed by solid lines, the corresponding scaling laws by dashed lines. The associated (non-normalized) parameters for this best fit in each case can be taken from Table 3, where the matching region was chosen in the same range 0.50 ≤ x 2 /h ≤ 1.25 as for Re τ = 480 in Figure 4. For more details and a discussion on the fitting results obtained, see the main text.
parameters of Table 2 from Re * τ = 480 to Re τ = 850 in using the procedure outlined in (5.18). Important to note here is that the up-scaling for the u τ -normalized mean velocity fieldŪ + 1 , to be needed in the higher-order moments τ + 11 , τ + 12 and τ + 112 , has been performed according to the (more or less correct) assumption of Avsarkisov et al. (2014) that the scaling law for the velocity fieldŪ 1 in its deficit form (5.16) stays invariant for different Reynolds numbers at a fixed transpiration rate:Ū which then can be solved to give the up-scaling relation forŪ + All these steps finally reveal the sensitivity of the invariant functions (5.15) on the Reynolds number Re τ , as can be explicitly seen in Figure 6. Another option to study this sensitivity, is to re-fit again the scaling laws (5.15) to the DNS data for Re τ = 850, and to see how far the bestfitted values are off from the ones listed in Table 2 relative to the reference Reynolds-number Re * τ = 480. As to be expected, the quality of the fit is similar to that of Figure 4, as can be seen in Figure 7, but it was achieved for different (non-normalized) parametric values which, as can be compared in Table 3, changed significantly, in particular the values for the two highest order moments τ + 112 and τ + 233 . Anyhow, except for the mean velocity in deficit form, all higher-order moments show a strong sensitivity on the Reynolds number at fixed transpiration rate, thus clearly invalidating the inviscid assumption in Avsarkisov et al. (2014). It should be clear that this strong sensitivity  Table 3: Best-fitted (non-normalized) parameters of the theoretically predicted scaling laws (5.15) to the DNS data as shown in Figure 4 & 7 for two different Reynolds numbers Re τ = 480 and Re τ = 850, respectively, at v + 0 = 0.05. In both cases, the parameter A + 0 was fitted for τ + 11 , and then applied in τ + 112 : It takes the (non-normalized) value A 0 = 0.761 for Re τ = 480, and A 0 = 0.723 for Re τ = 850. Also, in both cases, the overall matching region was chosen in the range 0.50 ≤ x 2 /h ≤ 1.25. Except for A 0 and the parameters of the velocity profile (γ and λ), a strong Reynolds number dependence is observed throughout all scaling law parameters. Although the inviscid (ν = 0) assumption in Avsarkisov et al. (2014) is more or less valid for the lowest order moment (the mean velocity), it is incorrect for all higherorder moments, in particular as the order of the moments increases, the Re τ -dependence becomes more and more pronounced, e.g., for the third order parameter A 233 we observe a relative change of nearly 30%. only lies in the matching parameters of the Lie-group generated scaling laws (5.15), and not in the DNS data itself. In other words, these scaling laws cannot be robustly matched to the DNS data when assuming independence in one of its external system parameters.
Returning to the inconsistent symmetry analysis performed in Avsarkisov et al. (2014), in particular to the application of the unphysical scaling symmetryT ′ s (2.22), the mathematical proof in Frewer et al. (2014), Appendix D, clearly shows that independent of the particular flow configuration, the Lie-group based turbulent scaling laws for all higher order velocity correlations as derived in (5.15) are not consistent to the scaling of the mean velocity field itself. In other words, the proof in Frewer et al. (2014) shows that for the lowest correlation order n = 1 (defined as the mean velocity field) no contradiction exists, only as from n = 2 onwards the contradiction starts, i.e., while the mean velocity field can be robustly matched to the DNS data, it consistently fails for all higher order correlation functions and gets more pronounced the higher the correlation order n is.
Hence, to justify their new scaling law [Eq. (4.3)] in Avsarkisov et al. (2014) by saying that it "was successfully validated with DNS data for moderate transpiration rates" [p. 119] is based on a fallacy. The problem is that this "validation" in Avsarkisov et al. (2014) was only performed for the lowest order moment, which, of course, can always be matched to the DNS data since there are enough free parameters available to be fitted. But, as soon as any higher order correlations functions get fitted, not enough free parameters are available anymore and the curve-fitting procedure consistently fails in Avsarkisov et al. (2014), as shown in Figure 4 & 5.
Therefore, no true validation of the Lie-group-based scaling theory has been performed in Avsarkisov et al. (2014). For that also the theoretically predicted pressure-velocity correlations need to be validated against the DNS data to check in how far the best-fitted parameters are consistent with the parametric relations resulting from the underlying statistical transport equations (2.9)-(2.11) including all correlations, velocity as well as pressure. In particular, as the study of Avsarkisov et al. (2014) is based on the findings of Oberlack & Rosteck (2010) which specifically considers the infinite (unclosed) system of all multi-point correlation equations and which thus is designed and laid-out to be a "first principle" scaling theory for all higher order correlations (including velocity and pressure), special attention has to be devoted to the prediction value of all those correlation functions which go beyond the lowest or next to the lowest order. And exactly this has been investigated by us in the present study, however, yet only for the velocity correlation functions up to third order, but which already gives a different picture than the "validation" procedure in Avsarkisov et al. (2014) is trying to suggest. The same issue we also face in their subsequent publication Oberlack et al. (2015), which we will discuss next.

The viscous case (ν = 0)
The viscous scaling theory to turbulent channel flow with constant wall-normal transpiration has not been studied in Avsarkisov et al. (2014). It only can be found in their subsequent publication Oberlack et al. (2015), where it is discussed in Sec. 6.2. For the same flow conditions as described in Section 2, the viscous transport equations corresponding to the inviscid ones (2.9)-(2.11) will have the extended form where the second order viscous terms can also be equivalently written within their full-field form as (5.24) Decomposing this system into mean and fluctuating fields according to (2.8), we obtain the corresponding viscous Reynolds transport equations where ε ij is the well-known dissipation tensor The set of symmetries admitted by (5.21)-(5.24) stays unchanged to the ones for the inviscid case used in the previous subsection, except for the two Euler scaling symmetriesT 1 (2.20) andT 2 (2.21) which both break due the appearance of the viscous terms. Nevertheless, they recombine to give the classical Navier-Stokes scaling symmetrȳ In Oberlack et al. (2015) another yet unmentioned symmetry is used which provokes to be analyzed in more detail. Due to the linearity of the MPC equations in their full-field representation, the governing system (5.21)-(5.24) admits the additional rather generic symmetrȳ where the functions F i , F ij , F ijk , G, G ij = G ji and L ij are any particular solutions of the governing system of equations (5.21)-(5.24), i.e., where these functions satisfy again the equations ∂F 2 ∂x 2 = 0, (5.31) This symmetry just reflects the superposition property which is featured by all (homogeneous) linear differential equations. However, this symmetry is of no value, because, as correctly already noted in Oberlack & Rosteck (2010), it "cannot directly be adopted for the practical derivation of group invariant solutions" [p. 463]. The simple reason it that the system of equations (5.31)-(5.33) is unclosed and no analytical solution is known yet which is consistent up to all higher orders in its infinite hierarchy, otherwise one would have found a solution to the still unsolved closure problem of turbulence. Any guessed solution, which only satisfies the system (5.31)-(5.33) up to a fixed order n = n 0 in its infinite hierarchy, is of no value if we cannot guarantee that (i) this solution is also consistent for all higher orders n > n 0 , and (ii) that it also represents a physical solution which is consistent to the DNS data; because, for such unclosed systems, infinitely many different and independent mathematical solutions can be generated which all in the end are not reflected in the DNS data (Frewer et al., 2014;Frewer, 2015a,b). Despite their concern in Oberlack & Rosteck (2010) that the superposition symmetry due to the closure problem cannot be exploited, it nevertheless was used in Oberlack et al. (2015) to generate invariant solutions. Therein the superposition symmetryT ′ + (5.30) shows its existence through the arbitrarily chosen symmetries Z zij in [Eq. (353)], where some of the functional translations in (5.30) were arbitrarily fixed as linear functions (in the one-point limit r → 0): The motivation to choose this particular set of (linear) functions (5.34) and not any other set of functions that may also solve the system (5.31)-(5.33), is not clear. However, if the motivation was such as to only gain a better matching of the invariant functions to the DNS data, then the procedure proposed in Oberlack et al. (2015) has nothing to do with a theoretical prediction or forecasting of turbulent scaling laws as claimed therein. Because, such an approach would then just be based on a trial and error procedure which incrementally improves the prediction of turbulent scaling only a posteriori, and not a priori, as required for a true theoretical and "first principle" ansatz. In other words, since we don't see in Oberlack et al. (2015) any clear motivation a priori for a linear solution ansatz of the functional translational symmetries Z zij [Eq. (353)], it seems that they were chosen a posteriori to only enhance the matching to the DNS data. But, as already said, such an approach is not in the sense of the inventor to forecast turbulent scaling laws from a "first principle" theory which is "fully algorithmic" and where "no intuition is needed" (Oberlack, 2001, p. 321). Hence, through the use of the superposition principleT ′ + (5.30) in an unclosed system (5.21)-(5.24), the Lie-group symmetry approach in Oberlack et al. (2015) degenerates down to a non-predictive incremental trial-and-error method.
But, as already discussed in the conclusion of the previous subsection, no matter how great the effort to incrementally improve the predictive ability of Lie-group generated invariant solutions for turbulent scaling, the methodological approach itself, as initially proposed in Oberlack & Rosteck (2010) and last applied in Oberlack et al. (2015), will always be inconsistent in that a comparison to DNS data will always fail when considering correlation orders higher than the well-matched threshold level of a lower correlation order. The simple reason is that the analysis is permanently set up by two unphysical "statistical symmetries"T ′ s (2.22) andT ′ c (2.25) that perpetually violate the classical principle of cause and effect. The only way thus to obtain an overall consistent symmetry analysis, is to discard all unphysical symmetries (Frewer et al., 2014(Frewer et al., , 2015Frewer, 2015c;Frewer et al., 2016).
(ii) The invariant (symmetry breaking) constraintŪ * 2 =Ū 2 of a constant wall-normal transpiration velocityŪ 2 = v 0 (denoted in Oberlack et al. (2015) as U T ) has already been directly implemented in both scaling symmetriesT ′ s (2.22) andT NS (5.29), namely by transferring these full-field symmetries back to their corresponding Reynolds-decomposed form under the separate conditions k s = 0 and k NS = 0. Such a procedure, however, is based on a fallacy, as we will show further below, because consistency reveals that k s and k NS each must be zero, i.e., when imposing the constraintŪ * 2 =Ū 2 , the symmetry breaking cannot be circumvented, no matter which modus operandi is applied.
(iii) The infinitesimal generator for R 12 in [Eq. (354)] in Oberlack et al. (2015) contains two misprints: The term "−k z,2 x 2 U T " has to be deleted, since a parameter such as k z,2 does not exist, neither in the considered symmetries nor in the derived invariant solutions [Eq. (357)] and [Eq. (363)]. Similar for the misprinted parameter "k sc,tr2 ", which should be replaced by k NS . Both misprints also appear in Rosteck (2014) [p. 228].
As also already outlined in the previous subsection, we recall again that before invariant solutions get determined from (5.35), we first have to ensure the invariance of two enclosed system constraints: That of a mean constant wall-normal velocity U 2 = v 0 , or, equivalently dU 2 = 0, and that of a mean constant streamwise pressure gradient ∂P /∂x 1 = −K, or, equivalently d(∂ 1 P ) = 0. Implementing these into (5.35) will then collectively result into the following symmetry breaking constraints Consequently, the only invariant structure that can be derived for the mean velocity profile U 1 from (5.35) is that of a linear function (5.40) which, of course, does not constitute a reasonable scaling law (where α = (kŪ 1 + c 1 )/k x 2 and β some arbitrary integration constant). Hence, in contrast to the inviscid symmetry analysis performed in the previous subsection which only fails at a higher-order moment, the current viscous analysis already fails at the lowest-order moment U 1 . The reason is that the viscous analysis misses out one scaling symmetry: Instead of three inviscid scaling symmetries,T 1 (2.20), T 2 (2.21) andT ′ s (2.22), we only face two possible scaling symmetries for the viscous case, namelȳ T NS (5.29) and againT ′ s (2.22), which turns out to be crucial when at least two independent symmetry breaking constraints are imposed, as can be seen in (5.38), or (5.39), where both scaling symmetries then get broken.
Although due to the symmetry breaking (5.39) no logarithmic or algebraic scaling for the mean velocity profile U 1 can be derived, the corresponding analysis carried out in Oberlack et al. (2015), however, nevertheless succeeded to do so. The mistake lies in the fallacy already pointed out in (ii) above. To comprehend the mistake that has been done in Oberlack et al. (2015), let us repeat their line of reasoning by first looking at the scaling symmetryT NS (5.29) in how the invariant (symmetry breaking) constraintŪ * 2 =Ū 2 of a constant wall-normal transpiration velocityŪ 2 = U T has been implemented under the condition of a non-zero group parameter k NS = 0 associated to that symmetry. The details can also be found in Rosteck (2014) [p. 229]. Although the same line of reasoning has also been used for the second scaling symmetryT ′ s (2.22), we will discuss it separately, due to being a special symmetry.
The starting point are the full-field statistical transport equations (5.21)-(5.24), where we explicitly insert the constraint of a constant wall-normal transpiration velocity U 2 (x 2 ) = U T : As a result, these equations do not dependent anymore on the mean wall-normal velocity U 2 , and this observation is true for all orders in the infinite hierarchy of equations. Hence, based on the scaling symmetryT NS (5.29) for the initial system (5.21)-(5.24), we now may consider a modified symmetryQ NS that already inherently respects the required invariant constraint U 2 * = U 2 = U T : Indeed, transformation (5.43) is admitted as a symmetry by the equations (5.41)-(5.42) as can be readily verified. However, important to note here is thatQ NS (5.43) is a different scaling symmetry than the initially consideredT NS (5.29), i.e., the latter symmetry cannot be reduced to the former one. WithQ NS (5.43) we obtained a symmetry that automatically obeys the invariant constraint U 2 * = U 2 = U T without breaking the group parameter q NS down to zero; a result impossible to achieve with the initial scaling symmetryT NS (5.29). Hence, when generating invariant solutions under the constraint U 2 * = U 2 = U T , the Navier-Stokes scaling symmetrȳ T NS (5.29) has to be replaced by its appropriate but non-linked modificationQ NS (5.43). In its equivalent Reynolds-decomposed form, the symmetryQ NS (5.43) reads (Rosteck, 2014;Oberlack et al., 2015): which indeed is a symmetry of the corresponding Reynolds-decomposed transport equations (5.25)-(5.28) forŪ 2 = U T : AlthoughQ NS (5.44) is mathematically correctly admitted as a symmetry transformation by the infinite and unclosed system of statistical equations (5.45)-(5.46), it nevertheless has to be checked whether this symmetry is also consistent with the underlying deterministic Navier-Stokes equations, in particular becauseQ NS (5.44) acts as a purely statistical symmetry which is not reflected in the original deterministic equations. Hence, it is necessary to check whether this symmetry violates the principle of cause and effect. As explained and discussed in Frewer et al. (2014Frewer et al. ( , 2015Frewer et al. ( , 2016, no violation of causality occurs if at least one (invertible) deterministic transformation Q NS of the Navier-Stokes equations can be found such that then the symmetrȳ Q NS (5.44) is induced on the statistical level, i.e., Q NS =Q NS , where · denotes any statistical averaging operator. Important to note here is that the deterministic cause Q NS itself need not to be symmetry in order to induce the statistical symmetryQ NS as an effect. The aim is to find at least one (invertible) deterministic transformation Q NS (which itself need not to be a symmetry) of the Navier-Stokes equations such that it induces the statistical symmetryQ NS (5.44), i.e., such that Q NS =Q NS . We will restrict the analysis only to point transformations, where the transformations for the fluctuations u * i and p * , as well as for the time t * , are unknown transformations that need to be determined. We start off with the symmetry transformation of τ * 33 , for which, according to (5.44), the transformed fluctuation u * 3 has to be the deterministic cause for the statistical symmetry-effect which can only be satisfied if u * 3 transforms as Then by considering the symmetry transformation of τ * 23 (5.44) Hence, for q NS = 0, the statistical symmetryQ NS (5.44) is violating the classical principle of cause and effect, since obviously no deterministic cause Q NS (5.47) can be found that statistically induces this symmetry-effectQ NS (5.44). The statistical symmetryQ NS (5.44) is thus inconsistent to its underlying deterministic theory, and can only be restored if q NS = 0, i.e. if the symmetry gets broken. The same line of reasoning also applies to the second scaling symmetryT ′ s (2.22). Based on this symmetry for the initial system (5.21)-(5.24), the analysis in Oberlack et al. (2015) considers again a modified symmetryQ s such that it already inherently respects again the required invariant constraint U 2 * = U 2 = U T : which indeed is a symmetry of the considered full-field system (5.41)-(5.42). In its equivalent Reynolds-decomposed form, this symmetry reads (Rosteck, 2014;Oberlack et al., 2015): which indeed is also a symmetry of the corresponding Reynolds-decomposed transport equations (5.45)-(5.46). However, as in the previous case forQ NS (5.44), although the second scaling trans-formationQ s (5.56) is also mathematically correctly admitted as a symmetry by its statistical equations, it nevertheless is inconsistent to its underlying deterministic description, too, since, also in this case, no deterministic cause can be found such that on its statistical level the symmetryQ s (5.56) can be observed, that is, such that Q s =Q s , where the deterministic cause Q s (5.57), of course, need not to be symmetry of the Navier-Stokes equations itself, in order to induce a symmetry as a statistical effect. Following the same procedure as outlined in (5.48)-(5.53) forQ NS (5.44), one again readily sees that the statistical scaling symmetryQ s (5.56) only can be made consistent to its underlying deterministic description if q s = 0. Hence, as in the full-field representation, where we obtained the symmetry-breaking result (5.39) k NS = 0, k s = 0, (5.58) for the two scaling symmetriesT NS (5.29) andT ′ s (2.22), we thus also obtain the equivalent result in the Reynolds-decomposed representation, namely that both correspondingly modified scaling symmetriesQ NS (5.44) andQ s (5.56) each must get broken q NS = 0, q s = 0, (5.59) when imposing the invariant constraintŪ * 2 =Ū 2 = U T in a consistent manner. Obviously, this constitutes a plausible result, because the full-field and the Reynolds-decomposed representation are ultimately equivalent to each other: Both must give the same mathematical and physical results with the same conclusions. Worthwhile to note in this regard is that, in contrast to the classical Navier-Stokes scaling symmetryT NS (5.29), which constitutes a consistent and welldefined symmetry, the new statistical scaling symmetryT ′ s (2.22), as first proposed in Khujadze & Oberlack (2004) and then later generalized in Oberlack & Rosteck (2010), is already inconsistent and thus unphysical by itself. For more details, we refer to Frewer et al. (2014Frewer et al. ( , 2015. For the sake of completeness, let us continue the inconsistent analysis as performed in Oberlack et al. (2015). This will lead us to another, independent mistake done therein. When rewriting the full-field invariant surface condition (5.35) into its Reynolds-decomposed form as proposed in Oberlack et al. (2015), namely by replacing the two full-field scaling symmetries T ′ s (2.22) andT NS (5.29) with their correspondingly modified Reynolds-decomposed scaling sym-metriesQ s (5.56) andQ NS (5.44), respectively, we obtain, for q s = 0 and q NS = 0, the following (inconsistent) invariant surface condition respecting the invariant constraintŪ * 2 =Ū 2 = U T : which is identical to result [Eq. (354)] † given in Oberlack et al. (2015), where the φ-terms result from the scaling symmetryQ NS (5.44) hierarchically given as (5.61) † Up to a non-essential linear combination in the translation symmetries and two misprints in the generator R12, as mentioned in the points (i) and (iii) in the beginning of this subsection (p. 24), respectively. Further note that the correspondence of the parameters used in (5.60)-(5.64) to the ones defined in Oberlack et al. (2015) is: kx 2 = kG,2, q NS = k NS , qs = ks, c1 = ktr,1, cij = kij , and kŪ 1 = kz1. the ψ-terms from the scaling symmetryQ s (5.56) the ω-terms from the linear superposition symmetryT ′ + (5.30) with the specification (5.34) and finally the ζ-terms resulting from the translation symmetryT ′ c (2.26) Note that (5.60) coherently extends the condition in Oberlack et al. (2015) up to third order in the velocity correlations, including the moments for pressure and dissipation. Anyhow, although the required constraint of a mean constant and invariant wall-normal ve-locityŪ * 2 =Ū 2 = U T has been (inconsistently) implemented into the invariant surface condition (5.60) without breaking a scaling symmetry, i.e. for q NS = 0 and q s = 0, this has not been done for the second required system constraint, namely that of a mean constant and invariant streamwise pressure gradient ∂P * /∂x * 1 = ∂P / ∂x 1 = −K. Because, when this constraint d(∂ 1P ) = 0 is applied to (5.60), it will unavoidably result into the two symmetry breaking constraints q NS φ p 1 + q s ψ p 1 = 0, and ω p 1 = 0, (5.65) which equivalently turn into the restrictions q s = 3q NS , and k z12 = 0, (5.66) an important result not obtained in Oberlack et al. (2015). The reason of why this result (5.66) was not obtained, is that in Oberlack et al. (2015) a second, independent mistake was made: Instead of correctly determining the invariant mean pressure gradient ∂ iP as a function of x 2 in the wall-normal and as a constant in the streamwise direction via its invariant surface condition (5.60), it was incorrectly determined as a functional residual of the two momentum equations (5.45), namely as where the parameters for the already determined invariant solutions of (5.60),Ū inv 1 , τ inv 12 and τ inv 22 , were then arranged such that ∂P /∂x 1 is a constant and ∂P /∂x 2 only a function of x 2 . The reason why the latter procedure is incorrect, is that it is decisively incomplete: The relations in (5.67) only give constraint conditions among the parameters of the invariant solutionsŪ inv 1 , τ inv 12 and τ inv 22 , under the assumption of a constant pressure gradient ∂P /∂x 1 = −K in the streamwise and a sole x 2 -dependence ∂P /∂x 2 = G(x 2 ) in the wall-normal direction. But, these relations do not warrant that the determined pressureP =P (x 1 , x 2 ) from (5.67), with gradient ∂ iP = −Kδ 1i + G(x 2 )δ 2i , constitutes an invariant function by itself, being compatible to the invariant pressure solutionP inv =P inv (x 1 , x 2 ) obtained from the invariant surface condition (5.60) with gradient ∂ iP inv = −Kδ 1i + G inv (x 2 )δ 2i . In other words, the pressure solution P obtained from (5.67) is in general not an invariant function under all symmetries considered, and thus in general not compatible to the invariant pressure solutionP inv obtained from (5.60). Generally speaking, the reason for this is that the residuals (5.67) do not constitute invariant relations, since the coordinates x 1 and x 2 themselves do not constitute invariant quantities. Hence, instead of the incomplete and thus in general incorrect relations (5.67) as considered in Oberlack et al. (2015), the following complete and correct relations have to be inquired which now not only give the correct and consistent constraint conditions among the parameters of all invariant solutions involved, but which will also give, in general, more constraint conditions than the (inconsistent) relations (5.67) may give, simply because the invariant-based system constraint for (5.68), ∂ iP inv = −Kδ 1i + G inv (x 2 )δ 2i , is in general more restrictive than the constraint ∂ iP = −Kδ 1i + G(x 2 )δ 2i for (5.67). For example, for the case presently studied, (5.67) will only give one non-zero-constraint, [Eq. (361)] or [Eq. (365)] † in Oberlack et al. (2015), while (5.68) will not only give more non-zero-constraints, but, additionally, also two pivotal constraints, namely exactly those two already obtained before in (5.66).
The methodological mistake done in Oberlack et al. (2015), namely to consider (5.67) and not (5.68), is critical to their conclusions: (i) Since the correct relation (5.68) will give the constraint q s = 3q NS (5.66), no logarithmic scaling law for the mean velocity profileŪ 1 can be derived as incorrectly claimed in Oberlack et al. (2015), because the ansatz q s = q NS would then only lead to q s = q NS = 0. Hence, only an algebraic invariant solution forŪ 1 can be generated. (ii) In their "algebraic solution" [Eq. (382)] for k s = 3k NS , the second constraint k z12 = 0 from (5.68) will give the analytical result D 12 = 0, being different to their DNS-matched value D 12 ∼ 1 [Table 10]. Hence, since D 12 represents the mean streamwise pressure gradient, the constraint k z12 = 0 thus can only go along with the constraint k s = 3k NS , in order to generate a non-zero streamwise pressure gradient.
In the following we repeat the (inconsistent) analysis of Oberlack et al. (2015), in generating several invariant solutions from (5.60) and matching them to the DNS data of Avsarkisov et al. (2014), however, only for the correctly posed constraints (5.66). For q NS = 0 and q s = 0, we yield from (5.60) with (5.66) only a quadratic power-law for the mean invariant velocity profile as where we use the parameter notation of Oberlack et al. (2015): The parameters A and B 1 are † To note is that the result for the invariant solutionR12 [Eq. (363)] in Oberlack et al. (2015) misses the summand UT kz1kG,2/(k NS (kG,2 + k NS x2)), but which apparently was absorbed into the term CI,12/(kG,2 + k NS x2) of the arbitrary integration constant CI,12, while the result for the invariant solutionR22 carries the wrong sign in the U 2 T -term.
given by [Eq. (379)], † as A = k x 2 /(h q NS ) and B 1 = −(kŪ 1 + c 1 )/(2q NS ), while C 1 is an arbitrary integration constant. Note the striking difference that for the presently considered viscous case (ν = 0), the consistent and correct scaling law for the mean velocity profile (5.69) carries one (matching) parameter less than the correspondingly derived (inconsistent) scaling law [Eq. (380)] in Oberlack et al. (2015). A consistent analysis shows that γ = 2, in clear contrast to the nonpositive and non-constantly matched values for γ in Oberlack et al. (2015) [ Table 10], where the algebraic scaling coefficient γ is declared to be a non-positive and dependent function on the transpiration rate and the Reynolds number: γ = γ(U + T , Re τ ) < 0. With the result (5.69), all remaining invariant solutions can be determined from (5.60) with (5.66) accordingly. For example, the invariant Reynolds stresses are given as where all β's are arbitrary integration constants, ‡ while the remaining parameters are determined through the group constants as An interesting measure to verify the predictability of the invariant functions from (5.60) is the dissipation, which is given as (5.72) where the µ's are again arbitrary integration constants. For the statistical DNS data available from Avsarkisov et al. (2014), we can only compare to the scalar dissipation defined as (5.73) which, since it was only calculated in the u τ -normalized form, has to be transformed accordingly Oberlack et al. (2015) contains two misprints: The parameter A is missing a factor 1/h to be dimensionally correct, and in C1 the non-constant k NS x ks/k NS −1 2 has to be replaced by k in [Eq. (380)], and as well as in [Eq. (384)], all field variables were misleadingly denoted in dimensionless "+"-units, although the functional expressions themselves are not normalized on uτ . Finally note that B1 in [Eq. (379)] differs by one translation group parameter to ours defined in (5.69). As already mentioned in point (i) in the beginning of this subsection (p. 24), the reason is that in Oberlack et al. (2015) a different but equivalent linear combination of the two independent translation symmetries is considered.
‡ Full arbitrariness in all parameters, however, is not given, since certain consistency relations have to be satisfied from the underlying statistical equations (5.45)-(5.46). For example, the parameter β12 is not arbitrary, but determined as β12 = u 2 τ + 2C1uτ /Reτ . Figure 8: Matching of the two theoretically predicted scaling laws for the (normalized) mean velocity field U + 1 (5.69) and the scalar dissipation ε + (5.74) to the DNS data of Avsarkisov et al. (2014) for Re τ = 480 and v + 0 = 0.10. The DNS data is displayed by solid lines, the corresponding scaling laws by dashed lines. The matching region 0.5 ≤ x 2 /h ≤ 1.6 has been taken over from the result determined in Oberlack et al. (2015) as listed in [ Table 9]. The resulting best-fitted parameters are given as: A = −2.035, B + 1 = 15.74, C + 1 = −1.643 and µ + = −0.114. While the fitting forŪ + 1 is more or less satisfactory, the fitting of ε + fails.
To note is that the above scaling law only has one free matching parameter µ + , since A and C + 1 are determined by the scaling law (5.69) of the normalized mean velocity fieldŪ + 1 . Hence, the scalar dissipation ε + will thus be the ultimate litmus test in how far the Lie-group-based scaling theory, as currently proposed in Oberlack et al. (2015), is able to consistently predict the scaling behavior of Navier-Stokes turbulence. As to be expected from the investigation done in this section, the proposed theory fails: As shown in Figure 8, the scaling law (5.74) for the scalar dissipation ε + fails to even roughly predict the tendency of the DNS data, although for the lowest order moment, the mean velocity fieldŪ + 1 , the scaling law (5.69) was matched more or less satisfactorily. † The reason for this failure is clear: The considered invariant surface condition (5.60), as proposed in Oberlack et al. (2015), involves two unphysical scaling symmetries, namelyQ NS (5.44) andQ s (5.56), which both are inconsistent to the underlying deterministic theory in violating the classical principle of cause and effect. As a consequence, the theoretically predicted scaling behavior of the lowest order momentŪ + 1 is incompatible to the scaling behavior of the higher-order moment ε + , as clearly seen in Figure 8, an incompatibility which also runs through all other higher-order moments.

Summary and conclusion
The main motivation of this investigation was to reveal in how far the study of Avsarkisov et al. (2014) is reproducible. With the data made available on their institutional website [fdy], we failed to reproduce Fig. 9 (a) & (c) in Avsarkisov et al. (2014). The critical conclusions made from these figures can not be confirmed from our analysis: Neither do the mean velocity profiles (in deficit form) universally collapse onto a single curve for different transpiration rates at a constant Reynolds number (Fig. 9 (a)), nor does the universally proposed logarithmic scaling law in the center of the channel match the DNS data for the presented parameter values (Fig. 9 (c)).
No universal scaling behavior in the center of the channel can be detected as claimed in Avsarkisov et al. (2014), not even when considering the case of a constant transpiration rate at different Reynolds numbers, which led to the incorrect assumption to only conduct a Reynoldsnumber independent symmetry analysis. Because, as we have demonstrated several times, such an assumption, of an inviscid (ν = 0) and thus Reynolds-number independent symmetry analysis, is not justified to consistently predict the scaling behavior of a channel flow with uniform wall-normal transpiration for the flow conditions considered. In particular, we revealed that the associated Re τ -independent scaling group parameter for the mean velocity field was inconsistently matched in Avsarkisov et al. (2014) to a Re τ -dependent quantity, being proportional to u τ , which, as clearly shown in Figure 6, or Table 3, inevitably leads to a strong Re τ -dependence in all invariant scaling laws when extending the scaling theory of Avsarkisov et al. (2014) coherently to higher orders beyond the mean velocity moment. Hence, a consistent symmetry analysis to all orders can only be achieved when also including the viscous terms. This has been attempted in their subsequent study Oberlack et al. (2015).
But, both the inviscid (ν = 0) as well as the viscous (ν = 0) symmetry analysis, performed in Avsarkisov et al. (2014) and Oberlack et al. (2015), respectively, is inconsistent per se. † As explained and discussed in the previous section, this inconsistency is due to that both their investigations involve several unphysical symmetries that are inconsistent with the underlying deterministic description of turbulence, in that they violate the classical principle of cause and effect: The former inviscid analysis in Avsarkisov et al. (2014) (when extended to higher-order moments) involves two unphysical symmetries, namelyT ′ s (2.17) andT ′ c (2.26), while the latter symmetry analysis in Oberlack et al. (2015) involves three unphysical symmetries,Q NS (5.44), ‡ Q s (5.56) and againT ′ c (2.26). The consequence: Any derived set of invariant solutions beyond the lowest-order moment cannot be consistently matched to the DNS data anymore, as clearly shown in Figure 4 & 8 for the inviscid and viscous symmetry analysis, respectively. In particular the matching of the scalar dissipation, being a critical indicator to judge the prediction quality of any theoretically proposed scaling laws, failed exceedingly. To gain the mathematical insight into the reason for this failure, we refer to our foregoing publications Frewer et al. (2014);Frewer (2015a,b); Frewer et al. (2015) and Frewer et al. (2016).

A. Friction velocity from both walls as a measure of the pressure gradient
In a canonical turbulent channel flow of height 2h without wall-normal transpiration, driven by a mean constant streamwise pressure gradient −∂P /∂x 1 = K > 0, between x 2 = 0 (lower plate) and x 2 = 2h (upper plate), the squared friction velocity (normalized on the density ρ) where τ = τ (x 2 ) being the total mean shear stress is simply determined by the pressure gradient and the half-width of the channel only (see. e.g. (Tennekes & Lumley, 1972)) due to the fact that at the center of the channel (x 2 = h) the total shear stress is zero, i.e., τ | x 2 =h = 0, for reasons of symmetry. In particular, this result (A.3) is obtained by integrating the mean streamwise momentum equation from the lower plate upwards 0 = (A.4) † Apart from the additional fact that the symmetry analysis in Oberlack et al. (2015) is also technically flawed, in that a wrong and not enough constraint relations from the statistical momentum equations are determined which incorrectly allow for a logarithmic as well as an algebraic invariant solution in the mean velocity field. Instead, a correct analysis reveals that only an algebraic invariant solution of quadratic type can be obtained. And when excluding even the unphysical symmetries, then only a featureless linear profile is obtained.
‡ Recall again that, although the artificially constructed and unphysical statistical symmetryQ NS (5.44) is motivated from the well-known single physical scaling symmetry of the Navier-Stokes equationsT NS (5.29), there is no connection between them.
which then reduces to (A.3) when evaluated at x 2 = h. However, when considering a turbulent channel flow with uniform wall-normal transpiration v 0 , the total shear stress (including the shear stress from the transpiration) is obviously not zero anymore at the center of the channel, i.e., T | x 2 =h = 0, but rather at some different, yet unknown height position x 2 = x * 2 somewhere inside the channel, i.e., T | x 2 =x * 2 = 0. Although not knowing this position 0 ≤ x * 2 ≤ 2h, one nevertheless can derive the same relation (A.3) in an averaged sense by considering the different shear stresses on both walls. Because, by first integrating the mean streamwise momentum equation once from the lower plate up to the unknown position and once from the unknown position up to the upper plate and then by adding both relations, we obtain the x * 2 -independent result which, according to the initial definition (A.1), finally turns into where we then have, according to (A.2), the wall shear stresses at the blowing (b) and the suction (s) wall, respectively, and thus overall coinciding with the result [Eq. (2.1)] given in Avsarkisov et al. (2014).

B. Laminar channel flow with uniform wall transpiration †
The governing equations are the incompressible Navier-Stokes equations which considerably reduces in dimension when considering a stationary laminar channel flow of width 2h driven by a constant streamwise pressure gradient K > 0. When additionally considering permeable walls in which a uniform wall-normal flow v 0 > 0 is injected at the lower † Alternative derivations for laminar solutions under these flow conditions can also be found, e.g., in Chang (2009) or in Avsarkisov (2013).
wall (the blowing side x 2 = 0) to be then also fully uniformly sucked out at the upper wall (the suction side x 2 = 2h), the overall flow conditions will read: for which the Navier-Stokes equations (B.1) will reduce to the single equation Two things should be pointed out: (i) If the dependent variable U 1 is not normalized, then equation (B.3) consists of three parameters which can be varied independently, the transpiration rate v 0 , the driving force K and the viscosity ν. This threefold independent variation turns out to be necessary when normalizing according to procedure outlined in Avsarkisov et al. (2014).
(ii) The DNS in Avsarkisov et al. (2014) was performed under the additional constraint of a constant mass flux. † This constraint was applied globally (universally) for all different initially chosen transpiration rates and Reynolds numbers. Now, since every DNS can also simulate laminar solutions as a special case, we will construct these in accord with the simulation performed in Avsarkisov et al. (2014), i.e., we will construct the set of all laminar solutions under the additional universal constraint of a constant mass flux Q = Q * , where Instead of Q we can also equivalently consider the bulk velocity U B (since the density ρ is treated here as constant which can be absorbed into Q, similar to the pressure P in (B.1) which is also normalized relative to ρ). Note that only the mass flux in the streamwise direction needs to be considered, since in the wall-normal direction the mass flux is already constant by construction. Hence, next to equation ( 3) needs to be solved such that the constraint is always universally satisfied for all different initially chosen parameters v 0 , K and ν. The particular value U * B can be chosen arbitrarily from the outset, but once chosen, it is universally fixed and cannot change anymore during solution construction.
Before we explicitly solve equation (B.3) under the constraint (B.5), it is advantageous to normalize the expressions appropriately. Two interrelated but different normalization choices exist: The first one is based on U * B along with h (for the independent spatial coordinate). The system (B.3) and (B.5) then turns into which, in terms of the dimensionless spatial coordinate x ′ 2 = x 2 /h, can be equivalently written as 1 (x ′ 2 ) dx ′2 , withÛ 1 (0) =Û 1 (2) = 0, (B.6) † To maintain during simulation a constant mass flux in each time step, the pressure gradient has to adapt accordingly. However, since we are only interested in the statistically stationary state, the pressure gradient will still average out to a constant in the streamwise direction, but in each case to different values for different transpiration rates and Reynolds numbers.
where v B 0 = v 0 /U * B , w B K = Kh/U * B and Re B = U * B h/ν are the (relative to the bulk velocity) normalized transpiration rate, the pressurized forcing rate and the bulk Reynolds number, respectively. Note that system (B.6) is yet not fully normalized, sinceÛ 1 (x ′ 2 ) still carries the dimension of velocity. Obviously, this quantity can be normalized by the remaining constant velocity scale w B K , but in this final step we have to bear in mind that the parameter w B K is explicitly needed to satisfy the constraint equation U B = U * B . Hence, only a partial normalization may be performed in which w B K is not completely absorbed by both equations. This will turn (B.6) into the equivalent system whereÛ w 1 =Û 1 /w B K is the normalized (dimensionless) velocity field relative to the velocity scale w B K ∼ K being a measure of the pressure gradient K. As already pointed out in the beginning of this section, three independent parameters need to be initialized in order to solve (B.7): v B 0 , Re B and U * B , representing ultimately the transpiration rate v 0 , the viscosity ν and indirectly, via U * B ∼ w B K , the pressure gradient K, respectively. Note that the fully normalized system (B.7) is uncoupled: The first equation givesÛ w 1 , which then immediately yields the consistent value for the unknown scale w B K by just evaluating the right-hand side of the second equation. The second normalization is based on u τ , as defined through [Eq. (2.1)] in Avsarkisov et al. (2014), and again along with h for the spatial coordinate. For this choice, system (B.3) and (B.5) turns into which then, again in terms of the dimensionless spatial coordinate x ′ 2 = x 2 /h, can be equivalently written as where u τ = √ Kh, v + 0 = v 0 /u τ and Re τ = u τ h/ν are the friction velocity (measured relative to the constant streamwise pressure gradient K > 0), the transpiration rate based on this scale u τ and friction Reynolds number, respectively. Note again that at this stage system (B.8) is yet not fully normalized, sinceÛ 1 (x ′ 2 ) still carries the dimension of velocity. Similarly as discussed before for the first normalization choice,Û 1 (x ′ 2 ) can be obviously normalized by the constant velocity scale u τ , but in this step we have to bear in mind again that the parameter u τ is explicitly needed to satisfy the constraint equation U B = U * B . Hence, again, only a partial normalization may be performed in which u τ may not be completely absorbed by both equations. This will turn (B.8) into the equivalent system   Avsarkisov et al. (2014), while the values for the corresponding laminar case were calculated according to the analytical relation (B.13), where we denoted the dimensionalized transpiration rate as v L 0 to distinguish it from the turbulent flow condition.
whereÛ + 1 =Û 1 /u τ is the normalized (dimensionless) velocity field relative to the velocity scale u τ ∼ √ K being again a measure of the pressure gradient K. As was also already discussed before, three independent parameters need to be given again in order to solve the (uncoupled) system (B.9): Two, namely v + 0 and Re τ , in the beginning to solve the first equation and then one, namely U * B , in the end to evaluate the second expression in order to obtain the consistent value for the unknown scale u τ .
The two different normalization choices just discussed above are, of course, interrelated. That is, system (B.7) can be bijectively mapped to system (B.9) and vive versa. The relations are: v B 0 /v + 0 = u τ /U * B and Re B /Re τ =Û w 1 /Û + 1 = U * B /u τ . Since the u τ -normalization is mainly used throughout this study, we will only show the explicit solution of system (B.9), which readŝ (B.10) or, in the non-normalized (dimensionalized) form, as: where we used the notation U 1 = U L 1 and u τ = u L τ from Section 3 & 4 to distinguish these quantities from the corresponding turbulent flow behavior. The initial (dimensionalized) system parameters v 0 , K and ν as given (B.3) are then related to the three independently chosen ones v + 0 , Re τ and U * B as follows: Hence, note that when initializing in the u τ -normalization the two independent system parameters v + 0 and Re τ , then the transpiration parameter normalized on the universal bulk velocity, i.e. v 0 /U * B , is determined as which converges to v +2 0 in the limit Re τ → ∞ at a fixed transpiration rate v + 0 . In other words, although the transpiration rate v + 0 inside the u τ -normalization can be chosen independently from Re τ , it is not so for the bulk-velocity-normalized transpiration rate v 0 /U * B , which is even bounded when the Reynolds number goes to infinity: lim Reτ →∞ v 0 /U * B = v +2 0 , a property also to be expected in the turbulent case, but where the value of course is unknown; see Table 4.