Scaling of turbulent flame speed for expanding flames with Markstein diffusion considerations

In this paper we clarify the role of Markstein diffusivity, which is the product of the planar laminar flame speed and the Markstein length, on the turbulent flame speed and its scaling, based on experimental measurements on constant-pressure expanding turbulent flames. Turbulent flame propagation data are presented for premixed flames of mixtures of hydrogen, methane, ethylene, n-butane, and dimethyl ether with air, in near-isotropic turbulence in a dual-chamber, fan-stirred vessel. For each individual fuel-air mixture presented in this work and the recently published iso-octane data from Leeds, normalized turbulent flame speed data of individual fuel-air mixtures approximately follow a Re-T,f(0.5) scaling, for which the average radius is the length scale and thermal diffusivity is the transport property of the turbulence Reynolds number. At a given Re-T,Re-f, it is experimentally observed that the normalized turbulent flame speed decreases with increasing Markstein number, which could be explained by considering Markstein diffusivity as the leading dissipation mechanism for the large wave number flame surface fluctuations. Consequently, by replacing thermal diffusivity with the Markstein diffusivity in the turbulence Reynolds number definition above, it is found that normalized turbulent flame speeds could be scaled by Re-T,M(0.5) irrespective of the fuel, equivalence ratio, pressure, and turbulence intensity for positive Markstein number flames.

Evaluation of microwave assisted grafted sago starch as controlled release polymeric carrier

In the present investigation an attempt has been made to develop a new co-polymeric material for controlled release tablet formulations. The acrylamide grafting was successfully performed on the backbone of sago starch. The modified starch was tested for acute toxicity and drug-excipient compatibility study. The grafted material was used in making of controlled release tablets of lamivudine. The formulations were evaluated for physical characteristics such as hardness, friability, %drug content and weight variations. The in vitro release study showed that the optimized formulation exhibited highest correlation (R) value in case of Higuchi model and the release mechanism of the optimized formulation predominantly exhibited combination of diffusion and erosion process. There was a significant difference in the pharmacokinetic parameters (T-max, C-max, AUC, V-d, T-1/2 and MDT) of the optimized formulation as compared to the marketed conventional tablet Lamivir (R) was observed. The pharmacokinetics parameters were showed controlled pattern and better bioavailability. The optimized formulation exhibited good stability and release profile at the accelerated stability conditions. (c) 2013 Elsevier B.V. All rights reserved.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Polyvinylidene fluoride film based nasal sensor to monitor human respiration pattern: An initial clinical study

Design and development of a piezoelectric polyvinylidene fluoride (PVDF) thin film based nasal sensor to monitor human respiration pattern (RP) from each nostril simultaneously is presented in this paper. Thin film based PVDF nasal sensor is designed in a cantilever beam configuration. Two cantilevers are mounted on a spectacle frame in such a way that the air flow from each nostril impinges on this sensor causing bending of the cantilever beams. Voltage signal produced due to air flow induced dynamic piezoelectric effect produce a respective RP. A group of 23 healthy awake human subjects are studied. The RP in terms of respiratory rate (RR) and Respiratory air-flow changes/alterations obtained from the developed PVDF nasal sensor are compared with RP obtained from respiratory inductance plethysmograph (RIP) device. The mean RR of the developed nasal sensor (19.65 +/- A 4.1) and the RIP (19.57 +/- A 4.1) are found to be almost same (difference not significant, p > 0.05) with the correlation coefficient 0.96, p < 0.0001. It was observed that any change/alterations in the pattern of RIP is followed by same amount of change/alterations in the pattern of PVDF nasal sensor with k = 0.815 indicating strong agreement between the PVDF nasal sensor and RIP respiratory air-flow pattern. The developed sensor is simple in design, non-invasive, patient friendly and hence shows promising routine clinical usage. The preliminary result shows that this new method can have various applications in respiratory monitoring and diagnosis.

Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

Mechanistic Insights into a Non-Classical Diffusion Pathway for the Formation of Hollow Intermetallics: A Route to Multicomponent Hollow Structures

Hollow nanostructures are used for various applications including catalysis, sensing, and drug delivery. Methods based on the Kirkendall effect have been the most successful for obtaining hollow nanostructures of various multicomponent systems. The classical Kirkendall effect relies on the presence of a faster diffusing species in the core; the resultant imbalance in flux results in the formation of hollow structures. Here, an alternate non-Kirkendall mechanism that is operative for the formation of hollow single crystalline particles of intermetallic PtBi is demonstrated. The synthesis method involves sequential reduction of Pt and Bi salts in ethylene glycol under microwave irradiation. Detailed analysis of the reaction at various stages indicates that the formation of the intermetallic PtBi hollow nanoparticles occurs in steps. The mechanistic details are elucidated using control experiments. The use of microwave results in a very rapid synthesis of intermetallics PtBi that exhibits excellent electrocatalytic activity for formic acid oxidation reaction. The method presented can be extended to various multicomponent systems and is independent of the intrinsic diffusivities of the species involved.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

Growth of Phases and Diffusion of Components in the W-Pt System

Growth kinetics, phase boundary compositions, interdiffusion coefficients and the relative mobilities of the components are determined in the W-Pt system. The measured phase boundary compositions for the gamma phase are found to be different from the reported phase diagram. The interdiffusion coefficient and the activation energy decrease in the Pt(W) solid solution with increasing W content. An estimation of the parabolic growth constants and average interdiffusion coefficients in the gamma phase indicates that the diffusion process should be explained based on the estimation of diffusion parameters, which otherwise could lead to a wrong conclusion. The estimation of the relative mobilities of the components in the gamma phase indicates that Pt has a much higher diffusion rate than W. This is explained with the help of the crystal structure and the possible point defects present on different sublattices.

A Phase Transition for the Uniform Distribution in the Pattern Maximum Likelihood Problem

In this paper, we consider the setting of the pattern maximum likelihood (PML) problem studied by Orlitsky et al. We present a well-motivated heuristic algorithm for deciding the question of when the PML distribution of a given pattern is uniform. The algorithm is based on the concept of a ``uniform threshold''. This is a threshold at which the uniform distribution exhibits an interesting phase transition in the PML problem, going from being a local maximum to being a local minimum.

An enthalpy method for modeling eutectic solidification

This paper presents a new micro-scale model for solidification of eutectic alloys. The model is based on the enthalpy method and simulates the growth of adjacent alpha and beta phases from a melt of eutectic composition in a two-dimensional Eulerian framework. The evolution of the two phases is obtained from the solution of volume averaged energy and species transport equations which are formulated using the nodal enthalpy and concentration potential values. The three phases are tracked using the beta-phase fraction and the liquid fraction values in all the computational nodes. Solutal convection flow field in the domain is obtained from the solution of volume-averaged momentum and continuity equations. The governing equations are solved using a coupled explicit-implicit scheme. The model is qualitatively validated with Jackson-Hunt theory. Results show expected eutectic growth pattern and proper species transfer and diffusion field ahead of the interface. Capabilities of the model such as lamella width selection, division of lamella into thinner lamellae and the presence of solutal convection are successfully demonstrated. The present model can potentially be incorporated into the existing framework of enthalpy based micro-scale dendritic solidification models thus leading to an efficient generalized microstructure evolution model. (C) 2014 Elsevier Inc. All rights reserved.

Growth of hafnium and zirconium suicides by reactive diffusion

Diffusion controlled growth of the phases in Hf-Si and Zr-Si systems are studied by bulk diffusion couple technique. Only two phases grow in the interdiffusion zone, although several phases are present in both the systems. The location of the Kirkendall marker plane, detected based on the grain morphology, indicates that disilicides grow by the diffusion of Si. Diffusion of the metal species in these phases is negligible. This indicates that vacancies are present mainly on the Si sublattice. The activation energies for integrated diffusion coefficients in the HfSi2 and ZrSi2 are estimated as 394 +/- 37 and 346 +/- 34 kJ mol(-1), respectively. The same is calculated for the HfSi phase as 485 +/- 42 kJ mol(-1). The activation energies for Si tracer diffusion in the HfSi2 and ZrSi2 phases are estimated as 430 +/- 36 and 348 +/- 34 kJ mol(-1), respectively. (C) 2013 Elsevier B.V. All rights reserved.

Reactive diffusion in the Ti-Si system and the significance of the parabolic growth constant

Solid diffusion couple experiments are conducted to analyse the growth mechanism of the phases and the diffusion mechanism of the components in the Ti-Si system. The calculation of the parabolic growth constants and the integrated diffusion coefficients substantiates that the analysis is intrinsically prone to erroneous conclusions if it is based on just the parabolic growth constants determined for a multiphase interdiffusion zone. The location of the marker plane is detected based on the uniform grain morphology in the TiSi2 phase, which indicates that this phase grows mainly because of Si diffusion. The growth mechanism of the phases and morphological evolution in the interdiffusion zone are explained with the help of imaginary diffusion couples. The activation enthalpies for the integrated diffusion coefficient of TiSi2 and the Si tracer diffusion are calculated as 190 +/- 9 and 197 +/- 8 kJ/mol, respectively. The crystal structure, details on the nearest neighbours of the components, and their relative mobilities indicate that the vacancies are mainly present on the Si sublattice.

Growth of hafnium and zirconium suicides by reactive diffusion

Diffusion controlled growth of the phases in Hf-Si and Zr-Si systems are studied by bulk diffusion couple technique. Only two phases grow in the interdiffusion zone, although several phases are present in both the systems. The location of the Kirkendall marker plane, detected based on the grain morphology, indicates that disilicides grow by the diffusion of Si. Diffusion of the metal species in these phases is negligible. This indicates that vacancies are present mainly on the Si sublattice. The activation energies for integrated diffusion coefficients in the HfSi2 and ZrSi2 are estimated as 394 +/- 37 and 346 +/- 34 kJ mol(-1), respectively. The same is calculated for the HfSi phase as 485 +/- 42 kJ mol(-1). The activation energies for Si tracer diffusion in the HfSi2 and ZrSi2 phases are estimated as 430 +/- 36 and 348 +/- 34 kJ mol(-1), respectively. (C) 2013 Elsevier B.V. All rights reserved.