A quasi-steady performance prediction model for dynamic characteristics of a volute pump

A performance prediction model generally applicable for volute-type centrifugal pumps has been extended to predict the dynamic characteristics of a pump during its normal starting and stopping periods. Experiments have been conducted on a volute pump with different valve openings to study the dynamic behaviour of the pump during normal start-up and stopping, when a small length of discharge pipeline is connected to the discharge flange of the pump. Such experiments have also been conducted when the test pump was part of a hydraulic system, an experimental rig, where it is pumping against three similar pumps, known as supply pumps, connected in series, with the supply pumps kept idle or running. Instantaneous rotational speed, flowrate, and delivery and suction pressures of the pump were recorded and it was observed in all the tested cases that the change of pump behaviour during the transient period was quasi-steady, which validates the quasi-steady approach presented in this paper. The nature of variation of parameters during the transients has been discussed. The model-predicted dynamic head-capacity curves agree well with the experimental data for almost all the tested cases.

Data compression by linear prediction for storage and transmission of EEG signals

The EEG time series has been subjected to various formalisms of analysis to extract meaningful information regarding the underlying neural events. In this paper the linear prediction (LP) method has been used for analysis and presentation of spectral array data for the better visualisation of background EEG activity. It has also been used for signal generation, efficient data storage and transmission of EEG. The LP method is compared with the standard Fourier method of compressed spectral array (CSA) of the multichannel EEG data. The autocorrelation autoregressive (AR) technique is used for obtaining the LP coefficients with a model order of 15. While the Fourier method reduces the data only by half, the LP method just requires the storage of signal variance and LP coefficients. The signal generated using white Gaussian noise as the input to the LP filter has a high correlation coefficient of 0.97 with that of original signal, thus making LP as a useful tool for storage and transmission of EEG. The biological significance of Fourier method and the LP method in respect to the microstructure of neuronal events in the generation of EEG is discussed.

Reaction of normal and pseudo 2-formylbenzenesulfonyl chlorides with amines:experimental and theoretical studies on the structure of 2-formyl benzenesulfonamides in solid, solution and gas phases

The reaction of 2-formylbenzenesulfonyl chloride 1 and its pseudo isomer 2 with primary amines give either the corresponding sulfonamido Schiff bases or the corresponding 2-formylbenzenesulfonamide depending on the concentration of the amine used. The derivatives exist as an equilibrium mixture of the corresponding sulfonamide and 2-alkyl-3-hydroxy(or 3-aminoalkyl)-benzisothiazole-1,1-dioxide. Spectroscopic studies suggest that 2-formylbenzenesulfonamides exist as benzisothiazole-1,1-dioxides in the solid state, as a mixture of 2-formylbenzenesulfonamide and the corresponding benzisothiazole-1,1-dioxide in solution and as 2-formyl-benzenesulfonamides in the gas phase.

Theoretical estimation of the effect of minor elements on the solubility of oxygen in silicon melt

The effect of fourteen minor elements (Al, As, B, Bi, C, Ga, Ge, In, N, P, Pb, S, Sb and Sn) on the solubility of oxygen in silicon melt has been estimated using a recently developed theoretical equation, with only fundamental physical parameters such as hard sphere diameter, atomic volume and molar heat of solution at infinite dilution as inputs. The results are expressed in the form of interaction parameters. Although only limited experimental data are available for comparison, the theoretical approach appears to predict the correct sign, but underestimates the magnitude of the interaction between oxygen and alloying elements. The present theoretical approach is useful in making qualitative predications on the effect of minor elements on the solubility of oxygen in silicon melt, when direct measurements are not available.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Pipelined ring algorithm for matrix multiplication on transputer networks: performance analysis and estimation

A parallel matrix multiplication algorithm is presented, and studies of its performance and estimation are discussed. The algorithm is implemented on a network of transputers connected in a ring topology. An efficient scheme for partitioning the input matrices is introduced which enables overlapping computation with communication. This makes the algorithm achieve near-ideal speed-up for reasonably large matrices. Analytical expressions for the execution time of the algorithm have been derived by analysing its computation and communication characteristics. These expressions are validated by comparing the theoretical results of the performance with the experimental values obtained on a four-transputer network for both square and irregular matrices. The analytical model is also used to estimate the performance of the algorithm for a varying number of transputers and varying problem sizes. Although the algorithm is implemented on transputers, the methodology and the partitioning scheme presented in this paper are quite general and can be implemented on other processors which have the capability of overlapping computation with communication. The equations for performance prediction can also be extended to other multiprocessor systems.

Quantum and non-Markovian effects in the electron transfer reaction dynamics in the Marcus inverted region

Electron transfer reactions in large molecules may often be coupled to both the polar solvent modes and the intramolecular vibrational modes of the molecule. This can give rise to a complex dynamics which may in some systems, like betaine, be controlled more by vibrational rather than by solvent effects. Additionally, a significant contribution from an ultrafast relaxation component in the solvation dynamics may enhance the complexity. To explain the wide range of behavior that has been observed experimentally, Barbara et al. recently proposed that a model of an electron transfer reaction should minimally consist of a low-frequency classical solvent mode (X), a low-frequency vibrational mode (Q), and a high-frequency quantum mode (q) (J. Phys. Chem. 1991, 96, 3728). In the present work, a theoretical study of this model is described. This study generalizes earlier work by including the biphasic solvent response and the dynamics of the low-frequency vibrational mode in the presence of a delocalized, extended reaction zone. A novel Green's function technique has been developed which allowed us to study the non-Markovian dynamics on a multidimensional surface. The contributions from the high-frequency vibrational mode and the ultrafast component in the non-Markovian solvent dynamics are found to be primarily responsible for the dramatic increase in charge transfer rate over the prediction of the classical theories that neglect both these factors. These, along with a large coupling between the reactant and the product states, may combine to render the electron transfer rate both very large and constant over a wide range of solvent relaxation rates. A study on the free energy gap dependence of the electron transfer rate reveals that the rates are sensitive to changes in the quantum frequency particularly when the free energy gap is very large.

Prediction of nonlocal scaling parameter for armchair and zigzag single-walled carbon nanotubes based on molecular structural mechanics, nonlocal elasticity and wave propagation

Atomic vibration in the Carbon Nanotubes (CNTs) gives rise to non-local interactions. In this paper, an expression for the non-local scaling parameter is derived as a function of the geometric and electronic properties of the rolled graphene sheet in single-walled CNTs. A self-consistent method is developed for the linearization of the problem of ultrasonic wave propagation in CNTs. We show that (i) the general three-dimensional elastic problem leads to a single non-local scaling parameter (e(0)), (ii) e(0) is almost constant irrespective of chirality of CNT in the case of longitudinal wave propagation, (iii) e(0) is a linear function of diameter of CNT for the case of torsional mode of wave propagation, (iv) e(0) in the case of coupled longitudinal-torsional modes of wave propagation, is a function which exponentially converges to that of axial mode at large diameters and to torsional mode at smaller diameters. These results are valid in the long-wavelength limit. (C) 2011 Elsevier Ltd. All rights reserved.

Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms. We use homology detection approaches against the protein-protein interaction databases. DIP and iPfam in order to predict interacting proteins in a host-pathogen pair. In the present work, we first applied this approach to the test cases involving the pairs phage T4 - Escherichia coli and phage lambda - E. coli and show that previously known interactions could be recognized using our approach. We further apply this approach to predict interactions between human and three pathogens E. coli, Salmonella enterica typhimurium and Yersinia pestis. We identified several novel interactions involving proteins of host or pathogen that could be thought of as highly relevant to the disease process. Serendipitously, many interactions involve hypothetical proteins of yet unknown function. Hypothetical proteins are predicted from computational analysis of genome sequences with no laboratory analysis on their functions yet available. The predicted interactions involving such proteins could provide hints to their functions. (C) 2011 Elsevier B.V. All rights reserved.

Theoretical studies of the spin states of macrocyclic aza-amido binuclear copper (II) complexes

The spin and charge excitation gaps and charge and spin density distributions have been studied in macrocyclic binuclear aza-amido copper (II) complexes employing a model Hamiltonian. The spin gaps depend on the σ-orbital occupancies, and for small gaps, the exchange integral between the σ orbitals of the bridging oxygen atoms, KOO, which is sensitive to geometry, determines the low-lying spin excitations. The singlet—singlet gaps also depend upon the σ-orbital occupancy but are weakly dependent upon KOO.

SCF and electron correlation studies on structure, force constants and vibrational spectra of borane monoammoniate complex

Effects of basis set and electron correlation on the equilibrium geometry, force constants and vibrational spectra of BH3NH3 have been studied. A series of basis sets ranging from double zeta to triple zeta including polarization and diffuse functions have been utilized. All the SCF based calculations overestimate the dative B-N bond distance and considerable improvement occurs when the treatment for electron correlation is introduced. Detailed vibrational analysis for BH3NH3 has been carried out. The mean absolute percentage deviation of the ab initio predicted vibration frequencies of (BH3NH3)-B-11 from the experiment is about 10% for the SCF based calculations and the MP2 method shows better agreement, the overall deviation being 5-6%. The ground state effective force constants of BH3NH3 were obtained using RECOVES procedure. The RECOVES sets of force constants are found to be highly satisfactory for the prediction of the vibrational frequencies of different isotopomers of BH3NH3. The mean absolute percentage deviation of the calculated frequencies of different isotopomers from the experiment is much less than 1%. The RECOVES-MP2/augDZP set of force constants was found to be the best set among the different sets for this molecule. Theoretical infrared intensities are in fair agreement with the observed spectral features.

Theoretical Analysis of the Electromotive Force of a Cell Incorporating a Composition Gradient Solid Electrolyte

New composition gradient solid electrolytes have been designed for application in high temperature solid-state galvanic sensors and in thermodynamic measurements. The functionally gradient electrolyte consists of a solid solution between two or more ionic conductors with a common ion and gradual variation in composition of the other ionic species. Unequal rates of migration of the ions, caused by the presence of the concentration gradient, may result in the development of space charge, manifesting as diffusion potential. Presented is a theoretical analysis of the EMF of cells incorporating gradient solid electrolytes. An analytical expression is derived for diffusion potential, using the thermodynamics of irreversible processes, for different types of concentration gradients and boundary conditions at the electrode/electrolyte interfaces. The diffusion potential of an isothermal cell incorporating these gradient electrolytes becomes negligible if there is only one mobile ion and the transport numbers of the relatively immobile polyionic species and electrons approach zero. The analysis of the EMF of a nonisothermal cell incorporating a composition gradient solid electrolyte indicates that the cell EMF can be expressed in terms of the thermodynamic parameters at the electrodes and the Seebeck coefficient of the gradient electrolyte under standard conditions when the transport number of one of the ions approaches unity.