On the k(1)(-1) scaling in sink-flow turbulent boundary layers

Scaling of the streamwise velocity spectrum phi(11)(k(1)) in the so-called sink-flow turbulent boundary layer is investigated in this work. The present experiments show strong evidence for the k(1)(-1) scaling i.e. phi(11)(k(1)) = Lambda(1)U(tau)(2)k(1)(-1), where k(1)(-1) is the streamwise wavenumber and U-tau is the friction velocity. Interestingly, this k(1)(-1) scaling is observed much farther from the wall and at much lower flow Reynolds number (both differing by almost an order of magnitude) than what the expectations from experiments on a zero-pressure-gradient turbulent boundary layer flow would suggest. Furthermore, the coefficient A(1) in the present sink-flow data is seen to be non-universal, i.e. A(1) varies with height from the wall; the scaling exponent -1 remains universal. Logarithmic variation of the so-called longitudinal structure function, which is the physical-space counterpart of spectral k(1)(-1) scaling, is also seen to be non-universal, consistent with the non-universality of A(1). These observations are to be contrasted with the universal value of A(1) (along with the universal scaling exponent of 1) reported in the literature on zero-pressure-gradient turbulent boundary layers. Theoretical arguments based on dimensional analysis indicate that the presence of a streamwise pressure gradient in sink-flow turbulent boundary layers makes the coefficient A(1) non-universal while leaving the scaling exponent -1 unaffected. This effect of the pressure gradient on the streamwise spectra, as discussed in the present study (experiments as well as theory), is consistent with other recent studies in the literature that are focused on the structural aspects of turbulent boundary layer flows in pressure gradients (Harun etal., J. Flui(d) Mech., vol. 715, 2013, pp. 477-498); the present paper establishes the link between these two. The variability of A(1) accommodated in the present framework serves to clarify the ideas of universality of the k(1)(-1) scaling.

Effects of initial height on the steady-state persistence probability of linear growth models

The effects of the initial height on the temporal persistence probability of steady-state height fluctuations in up-down symmetric linear models of surface growth are investigated. We study the (1 + 1)-dimensional Family model and the (1 + 1)-and (2 + 1)-dimensional larger curvature (LC) model. Both the Family and LC models have up-down symmetry, so the positive and negative persistence probabilities in the steady state, averaged over all values of the initial height h(0), are equal to each other. However, these two probabilities are not equal if one considers a fixed nonzero value of h(0). Plots of the positive persistence probability for negative initial height versus time exhibit power-law behavior if the magnitude of the initial height is larger than the interface width at saturation. By symmetry, the negative persistence probability for positive initial height also exhibits the same behavior. The persistence exponent that describes this power-law decay decreases as the magnitude of the initial height is increased. The dependence of the persistence probability on the initial height, the system size, and the discrete sampling time is found to exhibit scaling behavior.

Electric field activated nonlinear anisotropic charge transport in doped polypyrrole

Electric field activated nonlinear transport is investigated in polypyrrole thin film in both in-plane and out-of-plane geometries down to 5 K and strong anisotropy is observed. A morphological model is suggested to explain the anisotropy through inter-chain and intra-chain transport. The deviation from the variable range hopping at low temperature is accounted by fluctuation assisted transport. From Zabrodaskii plots, it is found that electric field can tune the transport from insulating to metallic regime. Glazman-Matveev model is used to describe the nonlinear conduction. Field scaling analysis shows that conductance data at different temperature falls on to a single curve. Nonlinearity exponent, m(T) and characteristic length, L-E are estimated to characterize the transport in both the geometries. (C) 2013 AIP Publishing LLC.

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

Chemical vapor detection using nonlinear electrical properties of carbon nanotube bundles

We demonstrate the electrical transport behavior of carbon nanotubes (CNTs) upon exposure to organic analytes (namely ethanol, benzene, acetone and toluene). The resulting nonlinear current-voltage characteristics revealed a power law dependence of the differential conductivity on the applied bias voltage. Moreover, suppression of differential conductivity at zero bias is found to be dependent on different selective analytes. The power law exponent values have been monitored before, during and after exposure to the chemicals, which revealed a reversible change in the number of electron conducting channels. Therefore, the reduction in the number of conductive paths can be attributed to the interaction of the chemical analyte on the CNT surfaces, which causes a decrease in the differential conductivity of the CNT sample. These results demonstrate chemical selectivity of CNTs due to varying electronic interaction with different chemical analytes.

Trends in aerosol optical depth over Indian region: Potential causes and impact indicators

The first regional synthesis of long-term (back to similar to 25 years at some stations) primary data (from direct measurement) on aerosol optical depth from the ARFINET (network of aerosol observatories established under the Aerosol Radiative Forcing over India (ARFI) project of Indian Space Research Organization over Indian subcontinent) have revealed a statistically significant increasing trend with a significant seasonal variability. Examining the current values of turbidity coefficients with those reported similar to 50 years ago reveals the phenomenal nature of the increase in aerosol loading. Seasonally, the rate of increase is consistently high during the dry months (December to March) over the entire region whereas the trends are rather inconsistent and weak during the premonsoon (April to May) and summer monsoon period (June to September). The trends in the spectral variation of aerosol optical depth (AOD) reveal the significance of anthropogenic activities on the increasing trend in AOD. Examining these with climate variables such as seasonal and regional rainfall, it is seen that the dry season depicts a decreasing trend in the total number of rainy days over the Indian region. The insignificant trend in AOD observed over the Indo-Gangetic Plain, a regional hot spot of aerosols, during the premonsoon and summer monsoon season is mainly attributed to the competing effects of dust transport and wet removal of aerosols by the monsoon rain. Contributions of different aerosol chemical species to the total dust, simulated using Goddard Chemistry Aerosol Radiation and Transport model over the ARFINET stations, showed an increasing trend for all the anthropogenic components and a decreasing trend for dust, consistent with the inference deduced from trend in Angstrom exponent.

What mainly controls recession flows in river basins?

The ubiquity of the power law relationship between dQ/dt and Q for recession periods (-dQ/dt kQ(alpha); Q being discharge at the basin outlet at time t) clearly hints at the existence of a dominant recession flow process that is common to all real basins. It is commonly assumed that a basin, during recession events, functions as a single phreatic aquifer resting on a impermeable horizontal bed or the Dupuit-Boussinesq (DB) aquifer, and with time different aquifer geometric conditions arise that give different values of alpha and k. The recently proposed alternative model, geomorphological recession flow model, however, suggests that recession flows are controlled primarily by the dynamics of the active drainage network (ADN). In this study we use data for several basins and compare the above two contrasting recession flow models in order to understand which of the above two factors dominates during recession periods in steep basins. Particularly, we do the comparison by selecting three key recession flow properties: (1) power law exponent alpha, (2) dynamic dQ/dt-Q relationship (characterized by k) and (3) recession timescale (time period for which a recession event lasts). Our observations suggest that neither drainage from phreatic aquifers nor evapotranspiration significantly controls recession flows. Results show that the value of a and recession timescale are not modeled well by DB aquifer model. However, the above mentioned three recession curve properties can be captured satisfactorily by considering the dynamics of the ADN as described by geomorphological recession flow model, possibly indicating that the ADN represents not just phreatic aquifers but the organization of various sub-surface storage systems within the basin. (C) 2014 Elsevier Ltd. All rights reserved.

`Universal' recession curves and their geomorphological interpretation

The study of recession flows offers fundamental insights into basin hydrological processes and, in particular, into the collective behavior of the governing dominant subsurface flows and properties. We use here an existing geomorphological interpretation of recession dynamics, which links the exponent in the classic recession curve -dQ/dt - kQ(alpha) to the geometric properties of the time-varying drainage network to study the general properties of recession curves across a wide variety of river basins. In particular, we show how the parameter k depends on the initial soil moisture state of the basin and can be made to explicitly depend on an index discharge, representative of initial sub-subsurface storage. Through this framework we obtain a non-dimensional, event-independent, recession curve. We subsequently quantify the variability of k across different basins on the basis of their geometry, and, by rescaling, collapse curves from different events and basins to obtain a generalized, or `universal', recession curve. Finally, we analyze the resulting normalized recession curves and explain their universal characteristics, lending further support to the notion that the statistical properties of observed recession curves bear the signature of the geomorphological structure of the networks producing them. (C) 2014 Elsevier Ltd. All rights reserved.

Direct Characterizing of Densification Mechanisms during Spark Plasma Sintering

Spark plasma sintering (SPS) is a convenient and rapid means of producing dense ceramic compacts. However, the mechanisms responsible for rapid densification have not been identified satisfactorily, with different studies using an indirect approach yielding varied values for the densification parameters. This study involved SPS in high purity nanocrystalline alumina with temperatures ranging from 1173 to 1423K and stresses from 25 to 100MPa. A direct approach, with analyses at a constant density, revealed a stress exponent of similar to 1 and an inverse grain size dependence of similar to 3, consistent with Coble creep process. Whereas the direct approach gives a stress exponent of similar to 1, the indirect approach used previously gives stress exponents ranging from similar to 2.2 to 3.5 with the same data, thereby revealing potentially spurious values of the densification parameters from conventional indirect approaches to characterizing densification. The rapid densification during SPS is related to the finer grain sizes retained with the rapid heating rates and the imposed stress that enhances the driving force for densification.

Healing time for the growth of thin films on patterned substrates

The healing times for the growth of thin films on patterned substrates are studied using simulations of two discrete models of surface growth: the Family model and the Das Sarma-Tamborenea (DT) model. The healing time, defined as the time at which the characteristics of the growing interface are ``healed'' to those obtained in growth on a flat substrate, is determined via the study of the nearest-neighbor height difference correlation function. Two different initial patterns are considered in this work: a relatively smooth tent-shaped triangular substrate and an atomically rough substrate with singlesite pillars or grooves. We find that the healing time of the Family and DT models on aL x L triangular substrate is proportional to L-z, where z is the dynamical exponent of the models. For the Family model, we also analyze theoretically, using a continuum description based on the linear Edwards-Wilkinson equation, the time evolution of the nearest-neighbor height difference correlation function in this system. The correlation functions obtained from continuum theory and simulation are found to be consistent with each other for the relatively smooth triangular substrate. For substrates with periodic and random distributions of pillars or grooves of varying size, the healing time is found to increase linearly with the height (depth) of pillars (grooves). We show explicitly that the simulation data for the Family model grown on a substrate with pillars or grooves do not agree with results of a calculation based on the continuum Edwards-Wilkinson equation. This result implies that a continuum description does not work when the initial pattern is atomically rough. The observed dependence of the healing time on the substrate size and the initial height (depth) of pillars (grooves) can be understood from the details of the diffusion rule of the atomistic model. The healing time of both models for pillars is larger than that for grooves with depth equal to the height of the pillars. The calculated healing time for both Family and DT models is found to depend on how the pillars and grooves are distributed over the substrate. (C) 2014 Elsevier B.V. All rights reserved.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Dense shallow granular flows

Simplified equations are derived for a granular flow in the `dense' limit where the volume fraction is close to that for dynamical arrest, and the `shallow' limit where the stream-wise length for flow development (L) is large compared with the cross-stream height (h). The mass and diameter of the particles are set equal to 1 in the analysis without loss of generality. In the dense limit, the equations are simplified by taking advantage of the power-law divergence of the pair distribution function chi proportional to (phi(ad) - phi)(-alpha), and a faster divergence of the derivativ rho(d chi/d rho) similar to (d chi/d phi), where rho and phi are the density and volume fraction, and phi(ad) is the volume fraction for arrested dynamics. When the height h is much larger than the conduction length, the energy equation reduces to an algebraic balance between the rates of production and dissipation of energy, and the stress is proportional to the square of the strain rate (Bagnold law). In the shallow limit, the stress reduces to a simplified Bagnold stress, where all components of the stress are proportional to (partial derivative u(x)/partial derivative y)(2), which is the cross-stream (y) derivative of the stream-wise (x) velocity. In the simplified equations for dense shallow flows, the inertial terms are neglected in the y momentum equation in the shallow limit because the are O(h/L) smaller than the divergence of the stress. The resulting model contains two equations, a mass conservation equations which reduces to a solenoidal condition on the velocity in the incompressible limit, and a stream-wise momentum equation which contains just one parameter B which is a combination of the Bagnold coefficients and their derivatives with respect to volume fraction. The leading-order dense shallow flow equations, as well as the first correction due to density variations, are analysed for two representative flows. The first is the development from a plug flow to a fully developed Bagnold profile for the flow down an inclined plane. The analysis shows that the flow development length is ((rho) over barh(3)/B) , where (rho) over bar is the mean density, and this length is numerically estimated from previous simulation results. The second example is the development of the boundary layer at the base of the flow when a plug flow (with a slip condition at the base) encounters a rough base, in the limit where the momentum boundary layer thickness is small compared with the flow height. Analytical solutions can be found only when the stream-wise velocity far from the surface varies as x(F), where x is the stream-wise distance from the start of the rough base and F is an exponent. The boundary layer thickness increases as (l(2)x)(1/3) for all values of F, where the length scale l = root 2B/(rho) over bar. The analysis reveals important differences between granular flows and the flows of Newtonian fluids. The Reynolds number (ratio of inertial and viscous terms) turns out to depend only on the layer height and Bagnold coefficients, and is independent of the flow velocity, because both the inertial terms in the conservation equations and the divergence of the stress depend on the square of the velocity/velocity gradients. The compressibility number (ratio of the variation in volume fraction and mean volume fraction) is independent of the flow velocity and layer height, and depends only on the volume fraction and Bagnold coefficients.

Universal power law in crossover from integrability to quantum chaos

We study models of interacting fermions in one dimension to investigate the crossover from integrability to nonintegrability, i.e., quantum chaos, as a function of system size. Using exact diagonalization of finite-sized systems, we study this crossover by obtaining the energy level statistics and Drude weight associated with transport. Our results reinforce the idea that for system size L -> infinity nonintegrability sets in for an arbitrarily small integrability-breaking perturbation. The crossover value of the perturbation scales as a power law similar to L-eta when the integrable system is gapless. The exponent eta approximate to 3 appears to be robust to microscopic details and the precise form of the perturbation. We conjecture that the exponent in the power law is characteristic of the random matrix ensemble describing the nonintegrable system. For systems with a gap, the crossover scaling appears to be faster than a power law.

Sensitivity of meteorological input and soil properties in simulating aerosols (dust, PM10, and BC) using CHIMERE chemistry transport model

The objective of this study is to evaluate the ability of a European chemistry transport model, `CHIMERE' driven by the US meteorological model MM5, in simulating aerosol concentrations dust, PM10 and black carbon (BC)] over the Indian region. An evaluation of a meteorological event (dust storm); impact of change in soil-related parameters and meteorological input grid resolution on these aerosol concentrations has been performed. Dust storm simulation over Indo-Gangetic basin indicates ability of the model to capture dust storm events. Measured (AERONET data) and simulated parameters such as aerosol optical depth (AOD) and Angstrom exponent are used to evaluate the performance of the model to capture the dust storm event. A sensitivity study is performed to investigate the impact of change in soil characteristics (thickness of the soil layer in contact with air, volumetric water, and air content of the soil) and meteorological input grid resolution on the aerosol (dust, PM10, BC) distribution. Results show that soil parameters and meteorological input grid resolution have an important impact on spatial distribution of aerosol (dust, PM10, BC) concentrations.

Finite size scaling in crossover among different random matrix ensembles in microscopic lattice models

Using numerical diagonalization we study the crossover among different random matrix ensembles (Poissonian, Gaussian orthogonal ensemble (GOE), Gaussian unitary ensemble (GUE) and Gaussian symplectic ensemble (GSE)) realized in two different microscopic models. The specific diagnostic tool used to study the crossovers is the level spacing distribution. The first model is a one-dimensional lattice model of interacting hard-core bosons (or equivalently spin 1/2 objects) and the other a higher dimensional model of non-interacting particles with disorder and spin-orbit coupling. We find that the perturbation causing the crossover among the different ensembles scales to zero with system size as a power law with an exponent that depends on the ensembles between which the crossover takes place. This exponent is independent of microscopic details of the perturbation. We also find that the crossover from the Poissonian ensemble to the other three is dominated by the Poissonian to GOE crossover which introduces level repulsion while the crossover from GOE to GUE or GOE to GSE associated with symmetry breaking introduces a subdominant contribution. We also conjecture that the exponent is dependent on whether the system contains interactions among the elementary degrees of freedom or not and is independent of the dimensionality of the system.