Mixed convection in non-Newtonian fluids along a horizontal plate in a porous medium

The problem of mixed convection from horizontal surfaces in a porous medium saturated with a power-law-type non-Newtonian fluid is investigated. The transformed conservation laws are solved numerically for the case of variable wall hear pur conditions. Results for the details of the velocity and temperature fields as well as the Nusselt number have been presented. The viscosity index ranged from 0.5-1.5.

Nonsimilar solutions for mixed convection in non-Newtonian fluids along horizontal surfaces in porous media

A nonsimilar boundary layer analysis is presented for the problem of mixed convection in power-law type non-Newtonian fluids along horizontal surfaces with variable heat flux distribution. The mixed convection regime is divided into two regions, namely, the forced convection dominated regime and the free convection dominated regime. The two solutions are matched. Numerical results are presented for the details of the velocity and temperature fields. A discussion is provided for the effect of viscosity index on the surface heat transfer rate.

Small-angle neutron scattering studies of different mixed micelles composed of dimeric and monomeric cationic surfactants

Measurements of small-angle neutron scattering (SANS) cross sections from different mixed micelles composed of CTAB and Br-, n-C16H33N+Me2-(CH2)(m)N+Me2-n-C16H33, Br- (16-m-16, 2Br(-), where m = 3, 5, and 10), in aqueous media (D2O) are reported. The data have been analyzed using the Hayter and Penfold model for macroion solution to compute the interparticle structure factor S(Q) taking into account the screened Coulomb interactions between the micelles. The aggregate composition matches with that predicted from an ideal mixing model. The SANS analysis further indicates that the extent of aggregate growth and the Variations of shapes of the mixed micelles could be modulated by the amount of dimeric surfactant present in these mixtures. With the spacer chain length m less than or equal to 4 in the dimeric surfactant, the propensity of micellar growth is particularly pronounced. The effect of the variation of the temperature for the mixed micellar system (23.1 mol % of 16-3-16, 2Br(-)) was also examined. The systemic microviscosities that the mixed micellar aggregates offer to a solubilized, extrinsic fluorescence probe, 1,6-diphenyl-1,3,5-hexatriene, were determined. The variation of the microviscosities of the mixed micelles as a function of percentages of the dimeric surfactants could be explained in terms of conformational variations and progressive looping of the spacer chain of dimeric surfactants in mixed micellar aggregates with increasing m values.

Muon-spin rotation spectra in the mixed phase of high-T-c superconductors: Thermal fluctuations and disorder effects

We study muon-spin rotation (mu SR) spectra in the mixed phase of highly anisotropic layered superconductors, specifically Bi2+xSr2-xCaCu2O8+delta (BSCCO), by modeling the fluid and solid phases of pancake Vortices using liquid-state and density functional methods. The role of thermal fluctuations in causing motional narrowing of mu SR line shapes is quantified in terms of a first-principles theory of the flux-lattice melting transition. The effects of random point pinning are investigated using a replica treatment of liquid-state correlations and a replicated density functional theory. Our results indicate that motional narrowing in the pure system, although substantial, cannot account for the remarkably small linewidths obtained experimentally at relatively high fields and low temperatures. We find that satisfactory agreement with the mu SR data for BSCCO in this regime can be obtained through the ansatz that this ''phase'' is characterized by frozen short-range positional correlations reflecting the structure of the liquid just above the melting transition. This proposal is consistent with recent suggestions of a ''pinned liquid'' or ''glassy'' state of pancake Vortices in the presence of pinning disorder. Our results for the high-temperature liquid phase indicate that measurable linewidths may be obtained in this phase as a consequence of density inhomogeneities induced by the pinning disorder. The results presented here comprise a unified, first-principles theoretical treatment of mu SR spectra in highly anisotropic layered superconductors in terms of a controlled set of approximations. [S0163-1829(99)08033-9].

The Wiener-Hopf solution of a class of mixed boundary value problems arising in surface water wave phenomena

Two mixed boundary value problems associated with two-dimensional Laplace equation, arising in the study of scattering of surface waves in deep water (or interface waves in two superposed fluids) in the linearised set up, by discontinuities in the surface (or interface) boundary conditions, are handled for solution by the aid of the Weiner-Hopf technique applied to a slightly more general differential equation to be solved under general boundary conditions and passing on to the limit in a manner so as to finally give rise to the solutions of the original problems. The first problem involves one discontinuity while the second problem involves two discontinuities. The reflection coefficient is obtained in closed form for the first problem and approximately for the second. The behaviour of the reflection coefficient for both the problems involving deep water against the incident wave number is depicted in a number of figures. It is observed that while the reflection coefficient for the first problem steadily increases with the wave number, that for the second problem exhibits oscillatory behaviour and vanishes at some discrete values of the wave number. Thus, there exist incident wave numbers for which total transmission takes place for the second problem. (C) 1999 Elsevier Science B.V. All rights reserved.

Evaluation of bearing capacity improvement using composite grids

Recently, composite reinforcements in which combinations of materials and material forms such as strips, grids, and strips and anchors, depending on requirements have proven to be effective in various ground improvement applications. Composite geogrids studied in this paper belong to the category of composite reinforcements and are useful for bearing capacity improvement. The paper presents evaluation of results of bearing capacity tests conducted oil a composite geogrid, made of composite reinforcement consisting of steel and cement mortar. The study shows that the behavior of composite reinforcements follows the general trends observed in the case of conventional geogrids, with reference to the depth of first layer below the footing, number of layers of reinforcement, and vertical spacing of the reinforcement. Results show that the performance is comparable to that of a conventional polymer geogrid.

Removal of As(V) by adsorption onto mixed rare earth oxides

Arsenic pollution of water is a major problem faced worldwide. Arsenic is a suspected carcinogen in human beings and is harmful to other living beings. In the present study, a novel adsorbent was used to remove arsenate [As(V)] from synthetic solutions. The adsorbent, which is a mixture of rare earth oxides, was found to adsorb As(V) rapidly and effectively. The effect of various parameters such as contact time, initial concentration, pH, and adsorbent dose on adsorption efficiency was investigated. More than 90% of the adsorption occurred within the first 10 min and the kinetic rate constant was found to be about 3.5 mg min(-1). Adsorption efficiency was found to be dependent on the initial As(V) concentration, and the adsorption behavior followed the Langmuir adsorption model. The optimum pH was found to be 6.5. The presence of other ions such as nitrate, phosphate, sulphate, and silicate decreased the adsorption of As(V) by about 20-30%. The adsorbed As(V) could be desorbed easily by washing the adsorbent with pH 12 solution. This study demonstrates the applicability of naturally occurring rare earth oxides as selective adsorbents for As(V) from solutions.

Unsteady mixed convection flow from a rotating vertical cone with a magnetic field

An analysis is developed to study the unsteady mixed convection flow over a vertical cone rotating in an ambient fluid with a time-dependent angular velocity in the presence of a magnetic field. The coupled nonlinear partial differential equations governing the flow have been solved numerically using an implicit finite-difference scheme. The local skin friction coefficients in the tangential and azimuthal directions and the local Nusselt number increase with the time when the angular velocity of the-cone increases, but the reverse trend is observed for decreasing angular velocity. However, these are not mirror reflection of each other. The magnetic field reduces the skin friction coefficient in the tangential direction and also the Nusselt number, but it increases the skin friction coefficient in the azimuthal direction. The skin friction coefficients and the Nusselt number increase with the buoyancy force.

Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids

As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

Executing Long-running Multi-component Applications on Batch Grids

Computational grids are increasingly being used for executing large multi-component scientific applications. The most widely reported advantages of application execution on grids are the performance benefits, in terms of speeds, problem sizes or quality of solutions, due to increased number of processors. We explore the possibility of improved performance on grids without increasing the application’s processor space. For this, we consider grids with multiple batch systems. We explore the challenges involved in and the advantages of executing long-running multi-component applications on multiple batch sites with a popular multi-component climate simulation application, CCSM, as the motivation.We have performed extensive simulation studies to estimate the single and multi-site execution rates of the applications for different system characteristics.Our experiments show that in many cases, multiple batch executions can have better execution rates than a single site execution.

A Multi-layer Perceptron based Non-linear Mixture Model to estimate class abundance from mixed pixels

Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.

Phylogenetic Predictions on Grids

A phylogenetic or evolutionary tree is constructed from a set of species or DNA sequences and depicts the relatedness between the sequences. Predictions of future sequences in a phylogenetic tree are important for a variety of applications including drug discovery, pharmaceutical research and disease control. In this work, we predict future DNA sequences in a phylogenetic tree using cellular automata. Cellular automata are used for modeling neighbor-dependent mutations from an ancestor to a progeny in a branch of the phylogenetic tree. Since the number of possible ways of transformations from an ancestor to a progeny is huge, we use computational grids and middleware techniques to explore the large number of cellular automata rules used for the mutations. We use the popular and recurring neighbor-based transitions or mutations to predict the progeny sequences in the phylogenetic tree. We performed predictions for three types of sequences, namely, triose phosphate isomerase, pyruvate kinase, and polyketide synthase sequences, by obtaining cellular automata rules on a grid consisting of 29 machines in 4 clusters located in 4 countries, and compared the predictions of the sequences using our method with predictions by random methods. We found that in all cases, our method gave about 40% better predictions than the random methods.

Middleware for Long-running Applications on Batch Grids. Student Research Symposium poster

Computational grids with multiple batch systems (batch grids) can be powerful infrastructures for executing long-running multicomponent parallel applications. In this paper, we have constructed a middleware framework for executing such long-running applications spanning multiple submissions to the queues on multiple batch systems. We have used our framework for execution of a foremost long-running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our framework coordinates the distribution, execution, migration and restart of the components of CCSM on the multiple queues where the component jobs of the different queues can have different queue waiting and startup times.