Adaptive optimization of continuous bioreactor using neural network model

An adaptive optimization algorithm using backpropogation neural network model for dynamic identification is developed. The algorithm is applied to maximize the cellular productivity of a continuous culture of baker's yeast. The robustness of the algorithm is demonstrated in determining and maintaining the optimal dilution rate of the continuous bioreactor in presence of disturbances in environmental conditions and microbial culture characteristics. The simulation results show that a significant reduction in time required to reach optimal operating levels can be achieved using neural network model compared with the traditional dynamic linear input-output model. The extension of the algorithm for multivariable adaptive optimization of continuous bioreactor is briefly discussed.

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.

Modeling Of Hydrolytic Polymerization In A Semibatch Nylon 6 Reactor

Hydrolytic polymerization of caprolactam to Nylon 6 in a semibatch reactor is carried out by heating a mixture of water and caprolactam. Evaporation of volatiles caused by heating results in a pressure build-up. After the pressure reaches a predetermined value, vapors are vented to keep the pressure constant for some time, and thereafter, to lower the pressure to a value slightly above atmospheric in a preprogrammed manner. The characteristics of the polymer are determined by the chemical reactions and the vaporization of water and caprolactam. The semibatch operation has been simulated and the predictions have been compared with industria data. The observed temperature and pressure histories were predicted with a fair degree of accuracy. It was found that the predictions of the degree of polymerization however are sensitive to the vapor-liquid equilibrium relations. A comparison with an earlier model, which neglected mass transfer resistance, indicates that simulation using the VLE data of Giori and Hayes and accounting for mass transfer resistance is more reliable.

Modes of binding of 2'-AMP to RNase T1. A computer modeling study

The modes of binding of adenosine 2'-monophosphate (2'-AMP) to the enzyme ribonuclease (RNase) T1 were determined by computer modelling studies. The phosphate moiety of 2'-AMP binds at the primary phosphate binding site. However, adenine can occupy two distinct sites--(1) The primary base binding site where the guanine of 2'-GMP binds and (2) The subsite close to the N1 subsite for the base on the 3'-side of guanine in a guanyl dinucleotide. The minimum energy conformers corresponding to the two modes of binding of 2'-AMP to RNase T1 were found to be of nearly the same energy implying that in solution 2'-AMP binds to the enzyme in both modes. The conformation of the inhibitor and the predicted hydrogen bonding scheme for the RNase T1-2'-AMP complex in the second binding mode (S) agrees well with the reported x-ray crystallographic study. The existence of the first mode of binding explains the experimental observations that RNase T1 catalyses the hydrolysis of phosphodiester bonds adjacent to adenosine at high enzyme concentrations. A comparison of the interactions of 2'-AMP and 2'-GMP with RNase T1 reveals that Glu58 and Asn98 at the phosphate binding site and Glu46 at the base binding site preferentially stabilise the enzyme-2'-GMP complex.

Image reconstruction from incomplete projections data: A multiresolution modeling approach

Computerized tomography is an imaging technique which produces cross sectional map of an object from its line integrals. Image reconstruction algorithms require collection of line integrals covering the whole measurement range. However, in many practical situations part of projection data is inaccurately measured or not measured at all. In such incomplete projection data situations, conventional image reconstruction algorithms like the convolution back projection algorithm (CBP) and the Fourier reconstruction algorithm, assuming the projection data to be complete, produce degraded images. In this paper, a multiresolution multiscale modeling using the wavelet transform coefficients of projections is proposed for projection completion. The missing coefficients are then predicted based on these models at each scale followed by inverse wavelet transform to obtain the estimated projection data.

DockYard-a repository to assist modeling of protein-protein docking

In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard (http://pallab.serc.iisc.ernet.in/dockYard), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with >= 90% or >= 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

Modeling of a reacting nanofilm on a composite substrate

This article provides a detailed computational analysis of the reaction of dense nanofilms and the heat transfer characteristics on a composite substrate. Although traditional energetic compounds based on organic materials have similar energy per unit weight, non-organic material in nanofilm configuration offers much higher energy density and higher flame speed. The reaction of a multilayer thin film of aluminum and copper oxide has been studied by varying the substrate material and thicknesses. The numerical analysis of the thermal transport of the reacting film deposited on the substrate combined a hybrid approach in which a traditional two-dimensional black box theory was used in conjunction with the sandwich model to estimate the appropriate heat flux on the substrate accounting for the heat loss to the surroundings. A procedure to estimate this heat flux using stoichiometric calculations is provided. This work highlights two important findings. One is that there is very little difference in the temperature profiles between a single substrate of silica and a composite substrate of silicon silica. Secondly, with increase in substrate thickness, the quenching effect is progressively diminished at a given speed. These findings show that the composite substrate is effective and that the average speed and quenching of flames depend on the thickness of the silica substrate, and can be controlled by a careful choice of the substrate configuration. (C) 2011 Elsevier Ltd. All rights reserved.

Optimization of Helicopter Rotor Using Polynomial and Neural Network Metamodels

This study aims to determine optimal locations of dual trailing-edge flaps and blade stiffness to achieve minimum hub vibration levels in a helicopter, with low penalty in terms of required trailing-edge flap control power. An aeroelastic analysis based on finite elements in space and time is used in conjunction with an optimal control algorithm to determine the flap time history for vibration minimization. Using the aeroelastic analysis, it is found that the objective functions are highly nonlinear and polynomial response surface approximations cannot describe the objectives adequately. A neural network is then used for approximating the objective functions for optimization. Pareto-optimal points minimizing both helicopter vibration and flap power ale obtained using the response surface and neural network metamodels. The two metamodels give useful improved designs resulting in about 27% reduction in hub vibration and about 45% reduction in flap power. However, the design obtained using response surface is less sensitive to small perturbations in the design variables.

The structures of bacteriorhodopsin with different retinal-Schiff base orientations--computer modeling and energy minimization studies

Bacteriorhodopsin has been the subject of intense study in order to understand its photochemical function. The recent atomic model proposed by Henderson and coworkers based on electron cryo-microscopic studies has helped in understanding many of the structural and functional aspects of bacteriorhodopsin. However, the accuracy of the positions of the side chains is not very high since the model is based on low-resolution data. In this study, we have minimized the energy of this structure of bacteriorhodopsin and analyzed various types of interactions such as - intrahelical and interhelical hydrogen bonds and retinal environment. In order to understand the photochemical action, it is necessary to obtain information on the structures adopted at the intermediate states. In this direction, we have generated some intermediate structures taking into account certain experimental data, by computer modeling studies. Various isomers of retinal with 13-cis and/or 15-cis conformations and all possible staggered orientations of Lys-216 side chain were generated. The resultant structures were examined for the distance between Lys-216-schiff base nitrogen and the carboxylate oxygen atoms of Asp-96 - a residue which is known to reprotonate the schiff base at later stages of photocycle. Some of the structures were selected on the basis of suitable retinal orientation and the stability of these structures were tested by energy minimization studies. Further, the minimized structures are analyzed for the hydrogen bond interactions and retinal environment and the results are compared with those of the minimized rest state structure. The importance of functional groups in stabilizing the structure of bacteriorhodopsin and in participating dynamically during the photocycle have been discussed.

Water Modeling Study Of The Jet Characteristics In A Continuous-Casting Mold

The jet characteristics and the fluid flow pattern in a continuous slab caster have been studied using a water model. The fluid jet is studied under free fall and submerged discharge conditions. In the latter case, the jet was followed by dye-injection technique and image analyser was used to find out the effect of nozzle parameters on jet-spread angle, jet-discharge angle and the volume entrainment by the jet. All free-fall jets with nozzle port angle zero and upward are found to be spinning. Some of the free-fall jets with downward nozzle-port angle are found to be spinning and rest are smooth. The spinning direction of the jets are found to change with time. The well depth, port diameter and the inner diameter of the nozzle have a clear effect on the free-fall jets with downward port angle. The jet-spread angle is found to be about 17-degrees for smooth jets. The spread angle for spinning jet increases as the nozzle-port angle is increased from downward 25 to upward 15-degrees. The jet-discharge angle is always downward even when the nozzle-discharge ports are angled upward. The extent of volume entrainment by the spinning jet is higher and it increases as the nozzle-port angle is increased from 25 downward to 15-degrees upward.

Mathematical modelling of neurons and neural networks

The basic concepts and techniques involved in the development and analysis of mathematical models for individual neurons and networks of neurons are reviewed. Some of the interesting results obtained from recent work in this field are described. The current status of research in this field in India is discussed

Vibration Signature Analysis Using Artificial Neural Networks

Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.

Modeling of angiogenin-3 '-NMP complex

Angiogenin belongs to the Ribonuclease superfamily and has a weak enzymatic activity that is crucial for its biological function of stimulating blood vessel growth. Structural studies on ligand bound Angiogenin will go a long way in understanding the mechanism of the protein as well as help in designing drugs against it. In this study we present the first available structure of nucleotide ligand bound Angiogenin obtained by computer modeling. The importance of this study in itself notwithstanding, is a precursor to modeling a full dinucleotide substrate onto Angiogenin. Bovine Angiogenin, the structure of which has been solved at a high resolution, was earlier subjected to Molecular Dynamics simulations for a nanosecond. The MD structures offer better starting points for docking as they offer lesser obstruction than the crystal structure to ligand binding. The MD structure with the least serious short contacts was modeled to obtain a steric free Angiogenin - 3' mononucleotide complex structure. The structures were energetically minimized and subjected to a brief spell of Molecular Dynamics. The results of the simulation show that all the li,ligand-Angiogenin interactions and hydrogen bonds are retained, redeeming the structure and docking procedure. Further, following ligand - protein interactions in the case of the ligands 3'-CMP and 3'-UMP we were able to speculate on how Angiogenin, a predominantly prymidine specific ribonuclease prefers Cytosine to Uracil in the first base position.

Modeling of precipitation in reverse micellar systems

A model of the precipitation process in reverse micelles has been developed to calculate the size of fine particles obtained therein. While the method shares several features of particle nucleation and growth common to precipitation in large systems, complexities arise in describing the processes of nucleation, due to the extremely small size of a micelle and of particle growth caused by fusion among the micelles. Occupancy of micelles by solubilized molecules is governed by Poisson statistics, implying most of them are empty and cannot nucleate of its own. The model therefore specifies the minimum number of solubilized molecules required to form a nucleus which is used to calculate the homogeneous nucleation rate. Simultaneously, interaction between micelles is assumed to occur by Brownian collision and instantaneous fusion. Analysis of time scales of various events shows growth of particles to be very fast compared to other phenomena occurring. This implies that nonempty micelles either are supersaturated or contain a single precipitated particle and allows application of deterministic population balance equations to describe the evolution of the system with time. The model successfully predicts the experimental measurements of Kandori ct al.(3) on the size of precipitated CaCO3 particles, obtained by carbonation of reverse micelles containing aqueous Ca(OH)(2) solution.

Modeling of the cooling process on the runout table of a hot strip mill - A parallel approach

This paper deals with the development of a new model for the cooling process on the runout table of hot strip mills, The suitability of different numerical methods for the solution of the proposed model equation from the point of view of accuracy and computation time are studied, Parallel solutions for the model equation are proposed.