The structure of turbulent boundary layers along mildly curved surfaces

This paper describes a detailed study of the structure of turbulence in boundary layers along mildly curved convex and concave surfaces. The surface curvature studied corresponds to δ/Rw = ± 0·01, δ being the boundary-layer thickness and Rw the radius of curvature of the wall, taken as positive for convex and negative for concave curvature. Measurements of turbulent energy balance, autocorrelations, auto- and cross-power spectra, amplitude probability distributions and conditional correlations are reported. It is observed that even mild curvature has very strong effects on the various aspects of the turbulent structure. For example, convex curvature suppresses the diffusion of turbulent energy away from the wall, reduces drastically the integral time scales and shifts the spectral distributions of turbulent energy and Reynolds shear stress towards high wavenumbers. Exactly opposite effects, though generally of a smaller magnitude, are produced by concave wall curvature. It is also found that curvature of either sign affects the v fluctuations more strongly than the u fluctuations and that curvature effects are more significant in the outer region of the boundary layer than in the region close to the wall. The data on the conditional correlations are used to study, in detail, the mechanism of turbulent transport in curved boundary layers. (Published Online April 12 2006)

Taxonomy of factors which influence heavy metal build-up on urban road surfaces

Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.

Build-up of toxic metals on the impervious surfaces of a commercial seaport

In the context of increasing threats to the sensitive marine ecosystem by toxic metals, this study investigated the metal build-up on impervious surfaces specific to commercial seaports. The knowledge generated in this study will contribute to managing toxic metal pollution of the marine ecosystem. The study found that inter-modal operations and main access roadway had the highest loads followed by container storage and vehicle marshalling sites, while the quay line and short term storage areas had the lowest. Additionally, it was found that Cr, Al, Pb, Cu and Zn were predominantly attached to solids, while significant amount of Cu, Pb and Zn were found as nutrient complexes. As such, treatment options based on solids retention can be effective for some metal species, while ineffective for other species. Furthermore, Cu and Zn are more likely to become bioavailable in seawater due to their strong association with nutrients. Mathematical models to replicate the metal build-up process were also developed using experimental design approach and partial least square regression. The models for Cr and Pb were found to be reliable, while those for Al, Zn and Cu were relatively less reliable, but could be employed for preliminary investigations.

Effect of creep deformations in mechanical systems under combined deterministic and random inputs

The effect of creep on the vibrations of a single degree of freedom system subjected to combined random and deterministic excitation has been studied in this paper. The deterministic part of the excitation is assumed to be a sinusoidal function while the random part of the excitation is considered as a narrow band process with a central frequency equal to the frequency of sinusoidal part of the excitation. Creep, an energy absorbing process, introduces an equivalent damping into the system. A measure of this damping and the statistical properties of the response of the mechanical system have been derived.

Mean Flow Measurements in Turbulent Boundary Layers along Mildly Curved Surfaces

An experimental investigation of the mean flow characteristics of two-dimensional turbulent boundary layers over surfaces of mild longitudinal curvature is reported. The study covered both convex and concave walls of \d/Rw I « 0.013 (d being the boundary-layer thickness and Rw being the wall radius). It was found that, whereas the region close to the wall was not affected significantly by wall curvature, the outer region was very sensitive to even mild wall curvature. A detailed study of the wake region using present and other available data suggests a systematic effect of b/Rw on the wake structure. The paper also discusses in detail the effect of mild wall curvature on the boundary-layer development with particular emphasis on the difference in behavior of the boundary layer at short and long distances from the leading edge of the curved wall, an aspect which has not received sufficient attention in previous experimental investigations. An attempt has been made to explain this behavior from a consideration of the structure of turbulence in boundary layers over curved surfaces taken into account.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

The non-linear response of a gyrostabilized platform: Effects of correction torque time delay and of random inputs

First, the non-linear response of a gyrostabilized platform to a small constant input torque is analyzed in respect to the effect of the time delay (inherent or deliberately introduced) in the correction torque supplied by the servomotor, which itself may be non-linear to a certain extent. The equation of motion of the platform system is a third order nonlinear non-homogeneous differential equation. An approximate analytical method of solution of this equation is utilized. The value of the delay at which the platform response becomes unstable has been calculated by using this approximate analytical method. The procedure is illustrated by means of a numerical example. Second, the non-linear response of the platform to a random input has been obtained. The effects of several types of non-linearity on reducing the level of the mean square response have been investigated, by applying the technique of equivalent linearization and solving the resulting integral equations by using laguerre or Gaussian integration techniques. The mean square responses to white noise and band limited white noise, for various values of the non-linear parameter and for different types of non-linearity function, have been obtained. For positive values of the non-linear parameter the levels of the non-linear mean square responses to both white noise and band-limited white noise are low as compared to the linear mean square response. For negative values of the non-linear parameter the level of the non-linear mean square response at first increases slowly with increasing values of the non-linear parameter and then suddenly jumps to a high level, at a certain value of the non-linearity parameter.

A Proof of Convergence of the B-RED and P-RED Algorithms for Random Early Detection

In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.

A parameter characterizing plowing nature of surfaces close to Gaussian

A non-dimensional parameter descriptive of the plowing nature of surfaces is proposed for the case of sliding between a soft and a relatively hard metallic pair. From a set of potential parameters which can be descriptive of the phenomenon, dimensionless groups are formulated and the influence of each one of them is analyzed. A non-dimensional parameter involving the root-mean square deviation (R-q) and the centroidal frequency (F-mean) deducted from the power-spectrum is found to have a high degree of correlation (as high as 0.93) with the coefficient of friction obtained in sliding experiments under lubricated condition.

Random network behaviour of protein structures

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure. At a coarse-grained level, we show that the network conforms remarkably well to realizations of random graphs and displays associated percolation behavior. Thus, within the rigid framework of the protein backbone that restricts the structure space, the side-chain interactions exhibit an element of randomness, which account for the functional flexibility and diversity shown by proteins. However, at a finer level, the network exhibits deviations from these random graphs which, as we demonstrate for a few specific examples, reflect the intrinsic uniqueness in the structure and stability, and perhaps specificity in the functioning of biological proteins.

Random security scheme selection for mobile transactions

Security in a mobile communication environment is always a matter for concern, even after deploying many security techniques at device, network, and application levels. The end-to-end security for mobile applications can be made robust by developing dynamic schemes at application level which makes use of the existing security techniques varying in terms of space, time, and attacks complexities. In this paper we present a security techniques selection scheme for mobile transactions, called the Transactions-Based Security Scheme (TBSS). The TBSS uses intelligence to study, and analyzes the security implications of transactions under execution based on certain criterion such as user behaviors, transaction sensitivity levels, and credibility factors computed over the previous transactions by the users, network vulnerability, and device characteristics. The TBSS identifies a suitable level of security techniques from the repository, which consists of symmetric, and asymmetric types of security algorithms arranged in three complexity levels, covering various encryption/decryption techniques, digital signature schemes, andhashing techniques. From this identified level, one of the techniques is deployed randomly. The results shows that, there is a considerable reduction in security cost compared to static schemes, which employ pre-fixed security techniques to secure the transactions data.

Domains in complex surfaces with non-compact automorphism groups

Let X be an arbitrary complex surface and D a domain in X that has a non-compact group of holomorphic automorphisms. A characterization of those domains D that admit a smooth, weakly pseudoconvex, finite type boundary orbit accumulation point is obtained.

Modelling of solute transport in a mild heterogeneous porous medium using stochastic finite element method: Effects of random source conditions

Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

Random existence of charge ordered stripes and its influence on the magnetotransport properties of La0.6Sr0.4MnO3 perovskite substituted with diamagnetic ions at Mn sublattice

Phase-singular solid solutions of La0.6Sr0.4Mn1-yMeyO3 (0 <= y <= 0.3) [Me=Li1+, Mg2+, Al3+, Ti4+, Nb5+, Mo6+ or W6+] [LSMey] perovskite of rhombohedral symmetry (space group: R (3) over barc) have been prepared wherein the valence of the diamagnetic substituent at Mn site ranged from 1 to 6. With increasing y-content in LSMey, the metal-insulator (TM-I) transition in resistivity-temperature rho(T) curves shifted to low temperatures. The magnetization studies M(H) as well as the M(T) indicated two groups for LSMey. (1) Group A with Me=Mg, Al, Ti, or Nb which are paramagnetic insulators (PIs) at room temperature with low values of M (< 0.5 mu(B)/Mn); the magnetic transition [ferromagnetic insulator (FMI)-PI] temperature (T-C) shifts to low temperatures and nearly coincides with that of TM-I and the maximum magnetoresistance (MR) of similar to 50% prevails near T-C (approximate to TM-I). (2) Group-B samples with Me=Li, Mo, or W which are FMIs with M-s=3.3-3.58 mu(B)/Mn and marginal reduction in T-C similar to 350 K as compared to the undoped LSMO (T-C similar to 378 K). The latter samples show large temperature differences Delta T=T-c-TM-I, reaching up to similar to 288 K. The maximum MR (similar to 60%) prevails at low temperatures corresponding to the M-I transition TM-I rather than around T-C. High resolution lattice images as well as microscopy analysis revealed the prevalence of inhomogeneous phase mixtures of randomly distributed charge ordered-insulating (COI) bistripes (similar to 3-5 nm width) within FMI charge-disordered regions, yet maintaining crystallographically single phase with no secondary precipitate formation. The averaged ionic radius < r(B)>, valency, or charge/radius ratio < CRR > cannot be correlated with that of large Delta T; hence cannot be used to parametrize the discrepancy between T-C and TM-I. The M-I transition is controlled by the charge conduction within the electronically heterogeneous mixtures (COI bistripes+FMI charge disordered); large MR at TM-I suggests that the spin-ordered FM-insulating regions assist the charge transport, whereas the T-C is associated with the bulk spin ordered regions corresponding to the FMI phase of higher volume fraction of which anchors the T-C to higher temperatures. The present analysis showed that the double-exchange model alone cannot account for the wide bifurcation of the magnetic and electric transitions, contributions from the charge as well as lattice degrees of freedom to be separated from spin/orbital ordering. The heterogeneous phase mixtures (COI+FMI) cannot be treated as of granular composite behavior. (c) 2008 American Institute of Physics.