An EDC-based turbulent premixed combustion model

In the present study, a new turbulent premixed combustion model is proposed by integrating the Coherent Flame Model with the modified eddy dissipation concept, and relating the fine structure mass fraction to the flame surface density. First, experimental results of turbulent flame speed available from literature are compared with the predicted results at different turbulence intensities to validate the flame surface density model. It is observed that the model is able to predict the turbulent burning speeds accurately. Then, a comprehensive validation is carried out utilizing data on a turbulent lifted methane flame issuing into a vitiated co-flow. Detailed comparison of temperature and species concentrations between experiment and simulation is performed at different heights of the flame. Overall, the model is found to predict both the spatial variation and peak values of the scalars at various heights satisfactorily.

Ultrasonic Wave Dispersion Characteristics of Fluid-Filled Single-Walled Carbon Nanotubes Based on Nonclassical Shell Model

In this paper, ultrasonic wave propagation analysis in fluid filled single-walled carbon nanotube (SWCNT) is studied using nonlocal elasticity theory. The SWCNT is modeled using Flugge's shell theory, with the wall having axial, circumferential and radial degrees of freedom and also including small scale effects. The fluid inside the SWCNT is assumed as water. Nonlocal governing equations for this system are derived and wave propagation analysis is also carried out. The presence of fluid in SWCNT alters the ultrasonic wave dispersion behavior. The wavenumber and wave velocity are smaller in presence of fluid as compared to the empty SWCNT. The nonlocal elasticity calculation shows that the wavenumber tends to reach the continuum limit at certain frequencies and the corresponding wave velocity tends to zero at those frequencies indicating localization and stationary behavior. It has been shown that the circumferential. waves will propagate non-dispersively at higher frequencies in nonlocality. The magnitudes of wave velocities of circumferential waves are smaller in nonlocal elasticity as compared to local elasticity. We also show that the cut-off frequency depend on the nonlocal scaling parameter and also on the density of the fluid inside the SWCNT, and the axial wavenumber, as the fluid becomes denser the cut-off frequency decreases. The effect of axial wavenumber on the ultrasonic wave behavior in SWCNTS filled with water is also discussed.

Physics-Based Band Gap Model for Relaxed and Strained 100] Silicon Nanowires

In this paper, we propose a physics-based simplified analytical model of the energy band gap and electron effective mass in a relaxed and strained rectangular 100] silicon nanowires (SiNWs). Our proposed formulation is based on the effective mass approximation for the nondegenerate two-band model and 4 x 4 Luttinger Hamiltonian for energy dispersion relation of conduction band electrons and the valence band heavy and light holes, respectively. Using this, we demonstrate the effect of the uniaxial strain applied along 100]-direction and a biaxial strain, which is assumed to be decomposed from a hydrostatic deformation along 001] followed by a uniaxial one along the 100]-direction, respectively, on both the band gap and the transport and subband electron effective masses in SiNW. Our analytical model is in good agreement with the extracted data using the extended-Huckel-method-based numerical simulations over a wide range of device dimensions and applied strain.

Causality analysis of groundwater dynamics based on a Vector Autoregressive model in the semi-arid basin of Gundal (South India)

Causal relationships existing between observed levels of groundwater in a semi-arid sub-basin of the Kabini River basin (Karnataka state, India) are investigated in this study. A Vector Auto Regressive model is used for this purpose. Its structure is built on an upstream/downstream interaction network based on observed hydro-physical properties. Exogenous climatic forcing is used as an input based on cumulated rainfall departure. Optimal models are obtained thanks to a trial approach and are used as a proxy of the dynamics to derive causal networks. It appears to be an interesting tool for analysing the causal relationships existing inside the basin. The causal network reveals 3 main regions: the Northeastern part of the Gundal basin is closely coupled to the outlet dynamics. The Northwestern part is mainly controlled by the climatic forcing and only marginally linked to the outlet dynamic. Finally, the upper part of the basin plays as a forcing rather than a coupling with the lower part of the basin allowing for a separate analysis of this local behaviour. The analysis also reveals differential time scales at work inside the basin when comparing upstream oriented with downstream oriented causalities. In the upper part of the basin, time delays are close to 2 months in the upward direction and lower than 1 month in the downward direction. These time scales are likely to be good indicators of the hydraulic response time of the basin which is a parameter usually difficult to estimate practically. This suggests that, at the sub-basin scale, intra-annual time scales would be more relevant scales for analysing or modelling tropical basin dynamics in hard rock (granitic and gneissic) aquifers ubiquitous in south India. (c) 2012 Elsevier B.V. All rights reserved.

A physics-based flexural phonon-dependent thermal conductivity model for single layer graphene

In this paper, we address a physics-based closed-form analytical model of flexural phonon-dependent diffusive thermal conductivity (kappa) of suspended rectangular single layer graphene sheet. A quadratic dependence of the out-of-plane phonon frequency, generally called flexural phonons, on the phonon wave vector has been taken into account to analyze the behavior of kappa at lower temperatures. Such a dependence has further been used for the determination of second-order three-phonon Umklapp and isotopic scatterings. We find that these behaviors in our model are best explained through the upper limit of Debye cut-off frequency in the second-order three-phonon Umklapp scattering of the long phonon waves that actually remove the thermal conductivity singularity by contributing a constant scattering rate at low frequencies and note that the out-of-plane Gruneisen parameter for these modes need not be too high. Using this, we clearly demonstrate that. follows a T-1.5 and T-2 law at lower and higher temperatures in the absence of isotopes, respectively. However in their presence, the behavior of kappa sharply deviates from the T-2 law at higher temperatures. The present geometry-dependent model of kappa is found to possess an excellent match with various experimental data over a wide range of temperatures which can be put forward for efficient electro-thermal analyses of encased/supported graphene.

Improvement in Bone Properties by Using Risedronate Adsorbed Hydroxyapatite Novel Nanoparticle Based Formulation in a Rat Model of Osteoporosis

A superior drug formulation capable of achieving efficient osteogenesis is in imperative demand for the treatment of osteoporosis. In the present study we investigated the potential of using novel risedronate-hydroxyapatite (HA) nanoparticle based formulation in an animal model of established osteoporosis. Nanoparticles of HA loaded with risedronate (NHLR) of various sizes (80-130 nm) were generated for bone targeted drug delivery. Three months after ovariectomy, 36 ovariectomized (OVX) rats were divided into 6 equal groups and treated with various doses of NHLR (500,350 and 250 mu g/kg intravenous single dose) and sodium risedronate (500 mu g/kg, intravenous single dose). Untreated OVX and sham OVX served as controls. One month after drug administration, the left tibia and femur were tested for bone mechanical properties and histology, respectively. In the right femur, bone density was measured by method based on Archimedes principle and bone porosity analyses were performed using X-ray imaging. NHLR (250 mu g/kg) showed a significant increase in bone density and reduced bone porosity when compared with OVX control. Moreover, NHLR (250 mu g/kg) significantly increased bone mechanical properties and bone quality when compared with OVX control. The results strongly suggest that the NHLR, which is a novel nanoparticle based formulation, has a therapeutic advantage over risedronate sodium monotherapy for the treatment of osteoporosis in a rat model of postmenopausal osteoporosis.

A trust model for routing in MANETs: a cognitive agents based approach

Mobile ad hoc networks (MANETs) is one of the successful wireless network paradigms which offers unrestricted mobility without depending on any underlying infrastructure. MANETs have become an exciting and im- portant technology in recent years because of the rapid proliferation of variety of wireless devices, and increased use of ad hoc networks in various applications. Like any other networks, MANETs are also prone to variety of attacks majorly in routing side, most of the proposed secured routing solutions based on cryptography and authentication methods have greater overhead, which results in latency problems and resource crunch problems, especially in energy side. The successful working of these mechanisms also depends on secured key management involving a trusted third authority, which is generally difficult to implement in MANET environ-ment due to volatile topology. Designing a secured routing algorithm for MANETs which incorporates the notion of trust without maintaining any trusted third entity is an interesting research problem in recent years. This paper propose a new trust model based on cognitive reasoning,which associates the notion of trust with all the member nodes of MANETs using a novel Behaviors-Observations- Beliefs(BOB) model. These trust values are used for detec- tion and prevention of malicious and dishonest nodes while routing the data. The proposed trust model works with the DTM-DSR protocol, which involves computation of direct trust between any two nodes using cognitive knowledge. We have taken care of trust fading over time, rewards, and penalties while computing the trustworthiness of a node and also route. A simulator is developed for testing the proposed algorithm, the results of experiments shows incorporation of cognitive reasoning for computation of trust in routing effectively detects intrusions in MANET environment, and generates more reliable routes for secured routing of data.

k.p based closed form energy band gap and transport electron effective mass model for 100] and 110] relaxed and strained Silicon nanowire

In this paper, we address a physics based closed form model for the energy band gap (E-g) and the transport electron effective mass in relaxed and strained 100] and 110] oriented rectangular Silicon Nanowire (SiNW). Our proposed analytical model along 100] and 110] directions are based on the k.p formalism of the conduction band energy dispersion relation through an appropriate rotation of the Hamiltonian of the electrons in the bulk crystal along 001] direction followed by the inclusion of a 4 x 4 Luttinger Hamiltonian for the description of the valance band structure. Using this, we demonstrate the variation in Eg and the transport electron effective mass as function of the cross-sectional dimensions in a relaxed 100] and 110] oriented SiNW. The behaviour of these two parameters in 100] oriented SiNW has further been studied with the inclusion of a uniaxial strain along the transport direction and a biaxial strain, which is assumed to be decomposed from a hydrostatic deformation along 001] with the former one. In addition, the energy band gap and the effective mass of a strained 110] oriented SiNW has also been formulated. Using this, we compare our analytical model with that of the extracted data using the nearest neighbour empirical tight binding sp(3)d(5)s* method based simulations and has been found to agree well over a wide range of device dimensions and applied strain. (C) 2012 Elsevier Ltd. All rights reserved.

Time variant reliability model updating in instrumented dynamical systems based on Girsanov's transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

An enthalpy-based model of dendritic growth in a convecting binary alloy melt

Purpose-In the present work, a numerical method, based on the well established enthalpy technique, is developed to simulate the growth of binary alloy equiaxed dendrites in presence of melt convection. The paper aims to discuss these issues. Design/methodology/approach-The principle of volume-averaging is used to formulate the governing equations (mass, momentum, energy and species conservation) which are solved using a coupled explicit-implicit method. The velocity and pressure fields are obtained using a fully implicit finite volume approach whereas the energy and species conservation equations are solved explicitly to obtain the enthalpy and solute concentration fields. As a model problem, simulation of the growth of a single crystal in a two-dimensional cavity filled with an undercooled melt is performed. Findings-Comparison of the simulation results with available solutions obtained using level set method and the phase field method shows good agreement. The effects of melt flow on dendrite growth rate and solute distribution along the solid-liquid interface are studied. A faster growth rate of the upstream dendrite arm in case of binary alloys is observed, which can be attributed to the enhanced heat transfer due to convection as well as lower solute pile-up at the solid-liquid interface. Subsequently, the influence of thermal and solutal Peclet number and undercooling on the dendrite tip velocity is investigated. Originality/value-As the present enthalpy based microscopic solidification model with melt convection is based on a framework similar to popularly used enthalpy models at the macroscopic scale, it lays the foundation to develop effective multiscale solidification.

Model-checking bisimulation-based information flow properties for infinite state sstems

Bisimulation-based information flow properties were introduced by Focardi and Gorrieri [1] as a way of specifying security properties for transition system models. These properties were shown to be decidable for finite-state systems. In this paper, we study the problem of verifying these properties for some well-known classes of infinite state systems. We show that all the properties are undecidable for each of these classes of systems.

Time variant reliability model updating in instrumented dynamical systems based on Girsanov’s transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov’s transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

Biased PN based impact angle constrained guidance using a nonlinear engagement model

Impact angle constrained guidance laws are important in many applications such as guidance of torpedoes, anti-ballistic missiles and reentry vehicles. In this paper, we design a guidance law which is capable of achieving a wide range of impact angles. Biased proportional navigation guidance uses a bias term in addition to the basic PN command to satisfy additional constraints. Angle constrained BPNG (ACBPNG) uses small angle approximations to derive the bias term for impact angle requirement. We design a modified ACBPNG (MACBPNG) where the required bias term is derived in a closed form considering non-linear equations of motion. Simulations are carried out for a wide range of impact angle requirements. We also analyze capturability from different initial positions and also the launch angles possible at each initial position. The performance of the proposed law is compared with an existing law.

STUDENT'S-t MIXTURE MODEL BASED MULTI-INSTRUMENT RECOGNITION IN POLYPHONIC MUSIC

We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.