Variations in roughness predictions (flume experiments)

Data of flume experiments with bed forms are used to analyze and compare different roughness predictors. In this study, the hydraulic roughness consists of grain roughness and form roughness. We predict the grain roughness by means of the size of the sediment. The form roughness is predicted by three approaches: Van Rijn (1984), Vanoni & Hwang (1967) and Engelund (1966). The total roughness values (friction factors) are compared with the roughness values according to the DarcyWeisbach equation. Results show that the different methods predict different friction factors. In future research uncertainties in the hydraulic roughness will be taken into account to determine their influence on the computed water levels

Expert opinion: uncertainties in hydraulic roughness

Water level predictions in rivers are used for a variety of purposes in water management. For example, designing flood defence measures and evaluating natural rehabilitation in flood plains, cannot be done without water level predictions. However, these water level predictions are uncertain and a major part of this uncertainty is caused by the uncertainty in the roughness coefficient (Van der Klis, 2003; Van Vuren, 2005). Hydraulic roughness in rivers results from (among others): grain roughness, form roughness and vegetation roughness. The roughness coefficient is uncertain because different elements creating the hydraulic roughness are uncertain (e.g. grain size, dune height). To quantify the influence of the uncertain roughness coefficient on water level predictions, we first need a quantification of the uncertainty in the roughness coefficient

Ballistic thermal conductance limited by phonon roughness scattering: A comparison of power-law and Gaussian roughness

In this work, we have investigated the influence of power-law roughness on the ballistic thermal conductance KTH for a nanosized beam adiabatically connected between two heat reservoirs. The sideways wall beam roughness is assumed to be power-law type, which is described by the roughness amplitude w, the in-plane roughness correlation length ξ and the roughness exponent 0≤H≤1. Distinct differences occur in between power-law and Gaussian wall roughness. For power-law roughness with low roughness exponents H (<0.5), the influence of phonon scattering can be rather destructive leading to significant deviations from the universal conductance value for flat beam walls. On the other hand for large roughness exponents (H>0.5) the conductance drop is significantly smaller than that of Gaussian roughness assuming similar roughness ratios w/ξ.

Effect of wall roughness on liquid oscillations damping in rectangular tanks

Tests were conducted in two rectangular glass tanks using silicon carbide grit bonded to walls to determine effect of wall roughness for damping liquid oscillations. Tests included effects of roughness height, roughness location, roughness at various values, amplitude decay, Reynolds number, and boundary layer thickness

Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces

Rough surfaces are usually characterised by a single equivalent sand-grain roughness height scale that typically needs to be determined from laboratory experiments. Recently, this method has been complemented by a direct numerical simulation approach, whereby representative surfaces can be scanned and the roughness effects computed over a range of Reynolds number. This development raises the prospect over the coming years of having enough data for different types of rough surfaces to be able to relate surface characteristics to roughness effects, such as the roughness function that quantifies the downward displacement of the logarithmic law of the wall. In the present contribution, we use simulation data for 17 irregular surfaces at the same friction Reynolds number, for which they are in the transitionally rough regime. All surfaces are scaled to the same physical roughness height. Mean streamwise velocity profiles show a wide range of roughness function values, while the velocity defect profiles show a good collapse. Profile peaks of the turbulent kinetic energy also vary depending on the surface. We then consider which surface properties are important and how new properties can be incorporated into an empirical model, the accuracy of which can then be tested. Optimised models with several roughness parameters are systematically developed for the roughness function and profile peak turbulent kinetic energy. In determining the roughness function, besides the known parameters of solidity (or frontal area ratio) and skewness, it is shown that the streamwise correlation length and the root-mean-square roughness height are also significant. The peak turbulent kinetic energy is determined by the skewness and root-mean-square roughness height, along with the mean forward-facing surface angle and spanwise effective slope. The results suggest feasibility of relating rough-wall flow properties (throughout the range from hydrodynamically smooth to fully rough) to surface parameters

Surface roughness modeling of CBN hard steel turning

Study in the paper investigate the influence of the cutting conditions parameters on surface roughness parameters during turning of hard steel with cubic boron nitrite cutting tool insert. For the modeling of surface roughness parameters was used central compositional design of experiment and artificial neural network as well. The values of surface roughness parameters Average mean arithmetic surface roughness (Ra) and Maximal surface roughness (Rmax) were predicted by this two-modeling methodology and determined models were then compared. The results showed that the proposed systems can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments modeling technique and artificial neural network can be effectively used for the prediction of the surface roughness parameters of hard steel and determined significantly influential cutting conditions parameters

Tailoring the frictional properties of granular media

A method of modifying the roughness of soda-lime glass spheres is presented, with the purpose of tuning inter-particle friction. The effect of chemical etching on the surface topography and the bulk frictional properties of grains is systematically investigated. The surface roughness of the grains is measured using white light interferometry and characterised by the lateral and vertical roughness length scales. The underwater angle of repose is measured to characterise the bulk frictional behaviour. We observe that the co-efficient of friction depends on the vertical roughness length scale. We also demonstrate a bulk surface roughness measurement using a carbonated soft drink.Comment: 10 pages, 17 figures, submitted to Phys. Rev.

Anomalous roughening of wood fractured surfaces

Scaling properties of wood fractured surfaces are obtained from samples of three different sizes. Two different woods are studied: Norway spruce and Maritime pine. Fracture surfaces are shown to display an anomalous dynamic scaling of the crack roughness. This anomalous scaling behavior involves the existence of two different and independent roughness exponents. We determine the local roughness exponents ${\zeta}_{loc}$ to be 0.87 for spruce and 0.88 for pine. These results are consistent with the conjecture of a universal local roughness exponent. The global roughness exponent is different for both woods, $\zeta$ = 1.60 for spruce and $\zeta$ = 1.35 for pine. We argue that the global roughness exponent $\zeta$ is a good index for material characterization.Comment: 7 two columns pages plus 8 ps figures, uses psfig. To appear in Physical Review