Sidewall inclined slot in a rectangular waveguide: Theory and experiment

A novel analysis to compute the admittance characteristics of the slots cut in the narrow wall of a rectangular waveguide, which includes the corner diffraction effects and the finite waveguide wall thickness, is presented. A coupled magnetic field integral equation is formulated at the slot aperture which is solved by the Galerkin approach of the method of moments using entire domain sinusoidal basis functions. The externally scattered fields are computed using the finite difference method (FDM) coupled with the measured equation of invariance (MEI). The guide wall thickness forms a closed cavity and the fields inside it are evaluated using the standard FDM. The fields scattered inside the waveguide are formulated in the spectral domain for faster convergence compared to the traditional spatial domain expansions. The computed results have been compared with the experimental results and also with the measured data published in previous literature. Good agreement between the theoretical and experimental results is obtained to demonstrate the validity of the present analysis.

Mesh-free approximations via the error reproducing kernel method and applications to nonlinear systems developing shocks

Error estimates for the error reproducing kernel method (ERKM) are provided. The ERKM is a mesh-free functional approximation scheme [A. Shaw, D. Roy, A NURBS-based error reproducing kernel method with applications in solid mechanics, Computational Mechanics (2006), to appear (available online)], wherein a targeted function and its derivatives are first approximated via non-uniform rational B-splines (NURBS) basis function. Errors in the NURBS approximation are then reproduced via a family of non-NURBS basis functions, constructed using a polynomial reproduction condition, and added to the NURBS approximation of the function obtained in the first step. In addition to the derivation of error estimates, convergence studies are undertaken for a couple of test boundary value problems with known exact solutions. The ERKM is next applied to a one-dimensional Burgers equation where, time evolution leads to a breakdown of the continuous solution and the appearance of a shock. Many available mesh-free schemes appear to be unable to capture this shock without numerical instability. However, given that any desired order of continuity is achievable through NURBS approximations, the ERKM can even accurately approximate functions with discontinuous derivatives. Moreover, due to the variation diminishing property of NURBS, it has advantages in representing sharp changes in gradients. This paper is focused on demonstrating this ability of ERKM via some numerical examples. Comparisons of some of the results with those via the standard form of the reproducing kernel particle method (RKPM) demonstrate the relative numerical advantages and accuracy of the ERKM.

EXAFS studies of arsenic chalcogenide glasses

An EXAFS study at the AsK edge of the ternary glasses As2(S, Se)3 and As2(Se, Te)3 and the binary As2S3, As2Se3 and As2Te3 glasses has been carried out. Radial structure functions show that the environment of As in glasses of intermediate compositions is quite different from that in the binary glasses. In the As2(S, Se)3 system, this might arise from chemical disorder in the network while in the As2(Se, Te)3 system increased ionicity could be the cause of this behaviour. Glasses where the constituent atoms are of similar size seem to exhibit fewer peaks in the radial structure function.

An investigation of solid adamantane by a modified isothermal-isobaric ensemble Monte Carlo simulation

Isothermal-isobaric ensemble Monte Carlo simulation studies of adamantane have been carried out at different temperatures. Thermodynamic properties and radial distribution functions calculated by employing a simple potential model based on sitesite interactions show good agreement with experiment and suggest that the solid is orientationally disordered at high temperatures.

A new type of high-order elements based on the mesh-free interpolations

We propose a new type of high-order elements that incorporates the mesh-free Galerkin formulations into the framework of finite element method. Traditional polynomial interpolation is replaced by mesh-free interpolations in the present high-order elements, and the strain smoothing technique is used for integration of the governing equations based on smoothing cells. The properties of high-order elements, which are influenced by the basis function of mesh-free interpolations and boundary nodes, are discussed through numerical examples. It can be found that the basis function has significant influence on the computational accuracy and upper-lower bounds of energy norm, when the strain smoothing technique retains the softening phenomenon. This new type of high-order elements shows good performance when quadratic basis functions are used in the mesh-free interpolations and present elements prove advantageous in adaptive mesh and nodes refinement schemes. Furthermore, it shows less sensitive to the quality of element because it uses the mesh-free interpolations and obeys the Weakened Weak (W2) formulation as introduced in [3, 5].

Metamodeling approach to predict friction factor of alluvial channel

The flow resistance of an alluvial channel flow is not only affected by the Reynolds number and the roughness conditions but also the Froude number. Froude number is the most basic parameter in the case of the alluvial channel, thus effect of Froude number on resistance to flow should be considered in the formulation of the friction factor, which is not in the case of present available resistance equations. At present, no generally acceptable quantitative description of the effects of the Froude number on hydraulic resistance has been developed. Metamodeling technique, which is particularly useful in modeling a complex processes or where knowledge of the physics is limited, is presented as a tool complimentary to modeling friction factor in alluvial channels. Present work uses, a radial basis metamodel, which is a type of neural network modeling, to find the effect of Froude number on the flow resistance. Based on the experimental data taken from different sources, it has been found that the predicting capability of the present model is on acceptable level. Present work also tries in formulating an empirical equation for resistance in alluvial channel comprising all the three majorm, parameters, namely, roughness parameter, Froude number and Reynolds number. (C) 2009 Elsevier B.V. All rights reserved.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.

Orientational melting and reorientational motion in a cubane molecular crystal: A molecular simulation study

Detailed molecular simulations are carried out to investigate the effect of temperature on orientational order in cubane molecular crystal. We report a transition from an orientationally ordered to an orientationally disordered plastic crystalline phase in the temperature range 425-450 K. This is similar to the experimentally reported transition at 395 K. The nature of this transition is first order and is associated with a 4.8% increase in unit Cell volume that is comparable to the experimentally reported unit cell volume change of 5.4% (Phys. Rev. Lett. 1997, 78, 4938). An orientational order parameter, eta(T), has been defined in terms of average angle of libration of a molecular 3-fold axis and the orientational melting has been characterized by using eta(T). The orientational melting is associated with an anomaly in specific heat at constant pressure (C-p) and compressibility (kappa). The enthalpy of transition and entropy of transition associated with this orientational melting are 20.8 J mol(-1) and 0.046 J mol(-1) K-1, respectively. The structure of crystalline as well as plastic crystalline phases is characterized by using various radial distribution functions and orientational distribution functions. The coefficient of thermal expansion of the plastic crystalline phase is more than twice that of the crystalline phase.

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

Robust/optimal temperature profile control using neural networks

An approximate dynamic programming (ADP) based neurocontroller is developed for a heat transfer application. Heat transfer problem for a fin in a car's electronic module is modeled as a nonlinear distributed parameter (infinite-dimensional) system by taking into account heat loss and generation due to conduction, convection and radiation. A low-order, finite-dimensional lumped parameter model for this problem is obtained by using Galerkin projection and basis functions designed through the 'Proper Orthogonal Decomposition' technique (POD) and the 'snap-shot' solutions. A suboptimal neurocontroller is obtained with a single-network-adaptive-critic (SNAC). Further contribution of this paper is to develop an online robust controller to account for unmodeled dynamics and parametric uncertainties. A weight update rule is presented that guarantees boundedness of the weights and eliminates the need for persistence of excitation (PE) condition to be satisfied. Since, the ADP and neural network based controllers are of fairly general structure, they appear to have the potential to be controller synthesis tools for nonlinear distributed parameter systems especially where it is difficult to obtain an accurate model.

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Complexation of siRNA with Dendrimer: A Molecular Modeling Approach

This paper reports the structural behavior and thermodynamics of the complexation of siRNA with poly(amidoamine) (PAMAM) dendrimers of generation 3 (G3) and 4 (G4) through fully atomistic molecular dynamics (MD) simulations accompanied by free energy calculations and inherent structure determination. We have also done simulation with one siRNA and two dendrimers (2 x G3 or 2xG4) to get the microscopic picture of various binding modes. Our simulation results reveal the formation of stable siRNA-dendrimer complex over nanosecond time scale. With the increase in dendrimcr generation, the charge ratio increases and hence the binding energy between siRNA and dendrimer also increases in accordance with available experimental measurements. Calculated radial distribution functions of amines groups of various subgenerations in a given generation of dendrimer and phosphate in backbone of siRNA reveals that one dendrimer of generation 4 shows better binding with siRNA almost wrapping the dendrimer when compared to the binding with lower generation dendrimer like G3. In contrast, two dendrimers of generation 4 show binding without siRNA wrapping the den-rimer because of repulsion between two dendrimers. The counterion distribution around the complex and the water molecules in the hydration shell of siRNA give microscopic picture of the binding dynamics. We see a clear correlation between water. counterions motions and the complexation i.e. the water molecules and counterions which condensed around siRNA are moved away from the siRNA backbone when dendrimer start binding to the siRNA back hone. As siRNA wraps/bind to the dendrimer counterions originally condensed onto siRNA (Na-1) and dendrimer (Cl-) get released. We give a quantitative estimate of the entropy of counterions and show that there is gain in entropy due to counterions release during the complexation. Furthermore, the free energy of complexation of IG3 and IG4 at two different salt concentrations shows that increase in salt concentration leads to the weakening of the binding affinity of siRNA and dendrimer.

Temperature and concentration dependence of adsorption properties of methane in NaY: a molecular dynamics study

Molecular dynamics calculations on methane sorbed in NaY (Si/Al = 3.0) employing realistic methane-methane and methane-zeolite intermolecular potential functions at different temperatures (50, 150, 220, and 300 K) and concentrations (2, 4, 6, and 8 molecules/cage) are reported. The thermodynamic results are in agreement with the available experimental data. Guest-guest and guest-host radial distribution functions (rdfs), energy distribution functions, distribution of cage occupancy, center-of-cage-center-of-mass (coc-com) rdfs, velocity autocorrelation functions for com and angular motion and the Fourier transformed power spectra, and diffusion coefficients are presented as a function of temperature and concentration. At 50 K, methane is localized near the adsorption site. Site-site migration and essentially free rotational motion are observed at 150 K. Molecules preferentially occupy the region near the inner surface of the alpha-cage. The vibrational frequencies for the com of methane shift toward higher values with decreasing temperature and increasing adsorbate concentration. The observed frequencies for com motion are 36, 53, and 85 cm-1 and for rotational motion at 50 K, 95 and 150 cm-1 in agreement with neutron scattering data. The diffusion coefficients show a type I behavior as a function of loading in agreement with NMR measurements. Cage-to-cage diffusion is found to be always mediated by the surface.

Incipient motion design of sand bed channels affected by bed suction

Seepage through sand bed channels in a downward direction (suction) reduces the stability of particles and initiates the sand movement. Incipient motion of sand bed channel with seepage cannot be designed by using the conventional approach. Metamodeling techniques, which employ a non-linear pattern analysis between input and output parameters and solely based on the experimental observations, can be used to model such phenomena. Traditional approach to find non-dimensional parameters has not been used in the present work. Parameters, which can influence the incipient motion with seepage, have been identified and non-dimensionalized in the present work. Non-dimensional stream power concept has been used to describe the process. By using these non-dimensional parameters; present work describes a radial basis function (RBF) metamodel for prediction of incipient motion condition affected by seepage. The coefficient of determination, R-2 of the model is 0.99. Thus, it can be said that model predicts the phenomena very well. With the help of the metamodel, design curves have been presented for designing the sand bed channel when it is affected by seepage. (C) 2010 Elsevier B.V. All rights reserved.

A molecular dynamics study of a PbO.SiO2 glass and melt

The structures of a PbO.SiO2 glass and melt have been studied using molecular dynamics simulation employing Born-Mayer-Huggins pair potentials. Various pair distribution functions are presented and discussed. Pb-Pb correlations persist in the melt, in agreement with experimental observations. The calculated and experimental radial distribution functions are compared.