Optimization of ion energy spread in inductively coupled plasma source designed for focused ion beam applications

The ion energy distribution of inductively coupled plasma ion source for focused ion beam application is measured using a four grid retarding field energy analyzer. Without using any Faraday shield, ion energy spread is found to be 50 eV or more. Moreover, the ion energy distribution is found to have double peaks showing that the power coupling to the plasma is not purely inductive, but a strong parasitic capacitive coupling is also present. By optimizing the various source parameters and Faraday shield, ion energy distribution having a single peak, well separated from zero energy and with ion energy spread of 4 eV is achieved. A novel plasma chamber, with proper Faraday shield is designed to ignite the plasma at low RF powers which otherwise would require 300-400 W of RF power. Optimization of various parameters of the ion source to achieve ions with very low energy spread and the experimental results are presented in this article. (C) 2010 Elsevier Ltd. All rights reserved.

Characterization of unitary processes with independent and stationary increments

This is a continuation of the earlier work (Publ. Res. Inst. Math. Sci. 45 (2009) 745-785) to characterize unitary stationary independent increment Gaussian processes. The earlier assumption of uniform continuity is replaced by weak continuity and with technical assumptions on the domain of the generator, unitary equivalence of the process to the solution of an appropriate Hudson-Parthasarathy equation is proved.

Optimization of two-dimensional NMR by matched accumulation

It is well known that in the time-domain acquisition of NMR data, signal-to-noise (S/N) improves as the square root of the number of transients accumulated. However, the amplitude of the measured signal varies during the time of detection, having a functional form dependent on the coherence detected. Matching the time spent signal averaging to the expected amplitude of the signal observed should also improve the detected signal-to-noise. Following this reasoning, Barna et al. (J Magn. Reson.75, 384, 1987) demonstrated the utility of exponential sampling in one- and two-dimensional NMR, using maximum-entropy methods to analyze the data. It is proposed here that for two-dimensional experiments the exponential sampling be replaced by exponential averaging. The data thus collected can be analyzed by standard fast-Fourier-transform routines. We demonstrate the utility of exponential averaging in 2D NOESY spectra of the protein ubiquitin, in which an enhanced SIN is observed. It is also shown that the method acquires delayed double-quantum-filtered COSY without phase distortion.

Optimization of an ammonia reactor using regression analysis

This paper presents an optimization algorithm for an ammonia reactor based on a regression model relating the yield to several parameters, control inputs and disturbances. This model is derived from the data generated by hybrid simulation of the steady-state equations describing the reactor behaviour. The simplicity of the optimization program along with its ability to take into account constraints on flow variables make it best suited in supervisory control applications.

Nature inspired optimization techniques for the design optimization of laminated composite structures using failure criteria

The design optimization of laminated composites using naturally inspired optimization techniques such as vector evaluated particle swarm optimization (VEPSO) and genetic algorithms (GA) are used in this paper. The design optimization of minimum weight of the laminated composite is evaluated using different failure criteria. The failure criteria considered are maximum stress (MS), Tsai-Wu (TW) and failure mechanism based (FMB) failure criteria. Minimum weight of the laminates are obtained for different failure criteria using VEPSO and GA for different combinations of loading. From the study it is evident that VEPSO and GA predict almost the same minimum weight of the laminate for the given loading. Comparison of minimum weight of the laminates by different failure criteria differ for some loading combinations. The comparison shows that FMBFC provide better results for all combinations of loading. (C) 2010 Elsevier Ltd. All rights reserved.

Impact of physical processes on the chlorophyll distribution in the Bay of Bengal

Satellite-derived chlorophyll a concentration (chl a) maps show three regions with high chl a in the Bay of Bengal. First among these is close to the coast, particularly off river mouths, with high values coinciding with the season of peak discharge; second is in the southwestern bay during the northeast monsoon, which is forced by local Ekman pumping; and the third is to the east of Sri Lanka in response to the summer monsoon winds. Chlorophyll-rich water from the mouths of rivers flows either along the coast or in an offshore direction, up to several hundred kilometers, depending on the prevailing ocean current pattern. The Irrawady River plume flows toward offshore and then turns northwestward during October–December, but it flows along the coast into the Andaman Sea for the rest of the year. From the Ganga-Brahmaputra river mouth, chl a–rich water flows directly southward into the open bay during spring but along the Indian coast during summer and winter. Along the Indian coast, the flow of chl a–rich water is determined by the East India Coastal Current (EICC). Whenever the EICC meanders off the Indian coast, it leads to an offshore outbreak of chl a–rich water from the coastal region into open ocean. The EICC as well as open ocean circulation in the bay is made up of several eddies, and these eddies show relatively higher chl a. Eddies near the coast, however, can often have higher chl a because of advection from the coastal region rather than generation within the eddy itself. The bay experiences several cyclones in a year, most of them occurring during October–November. These cyclones cause a drop in the sea surface temperature, a dip in the sea level, and a local increase in chl a. The impact of a cyclone is weaker in the northern part of the bay because of stronger stratification compared to the southern parts.

Test Application Time Minimization for RAS using Basis Optimization of Column Decoder

Random Access Scan, which addresses individual flip-flops in a design using a memory array like row and column decoder architecture, has recently attracted widespread attention, due to its potential for lower test application time, test data volume and test power dissipation when compared to traditional Serial Scan. This is because typically only a very limited number of random ``care'' bits in a test response need be modified to create the next test vector. Unlike traditional scan, most flip-flops need not be updated. Test application efficiency can be further improved by organizing the access by word instead of by bit. In this paper we present a new decoder structure that takes advantage of basis vectors and linear algebra to further significantly optimize test application in RAS by performing the write operations on multiple bits consecutively. Simulations performed on benchmark circuits show an average of 2-3 times speed up in test write time compared to conventional RAS.

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.

Constrained optimization of heat exchangers

Optimizing a shell and tube heat exchanger for a given duty is an important and relatively difficult task. There is a need for a simple, general and reliable method for realizing this task. The authors present here one such method for optimizing single phase shell-and-tube heat exchangers with given geometric and thermohydraulic constraints. They discuss the problem in detail. Then they introduce a basic algorithm for optimizing the exchanger. This algorithm is based on data from an earlier study of a large collection of feasible designs generated for different process specifications. The algorithm ensures a near-optimal design satisfying the given heat duty and geometric constraints. The authors also provide several sub-algorithms to satisfy imposed velocity limitations. They illustrate how useful these sub-algorithms are with several examples where the exchanger weight is minimized.

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.

Optimization of hot workability of an Al-Mg-Si alloy using processing maps

The hot workability of an Al-Mg-Si alloy has been studied by conducting constant strain-rate compression tests. The temperature range and strain-rate regime selected for the present study were 300-550 degrees C and 0.001-1 s(-1), respectively. On the basis of true stress data, the strain-rate sensitivity values were calculated and used for establishing processing maps following the dynamic materials model. These maps delineate characteristic domains of different dissipative mechanisms. Two domains of dynamic recrystallization (DRX) have been identified which are associated with the peak efficiency of power dissipation (34%) and complete reconstitution of as-cast microstructure. As a result, optimum hot ductility is achieved in the DRX domains. The strain rates at which DRX domains occur are determined by the second-phase particles such as Mg2Si precipitates and intermetallic compounds. The alloy also exhibits microstructural instability in the form of localized plastic deformation in the temperature range 300-350 degrees C and at strain rate 1 s(-1).

Optimization of Lime Content for Fly Ash

Abundant quantities of fly ash have been produced by thermal power plants situated ail over the world. Many applications of fly ash depend upon its pozzolanic reactivity. This reactivity depends upon many factors, including lime content. Many fly ashes show marked improvement with the addition of lime. However, for every fly ash, there is an optimum lime content for its maximum reactivity. There is no well-established simple test to determine the optimum lime content. In this paper an attempt is made to use a simple physical and physico chemical test to determine the optimum lime content. The principle behind the use of a pH test, liquid limit test, and free swell index test to determine the optimum lime content has been explained. All the methods predict nearly the same optimum lime content and correlate well with that determined by the strength test.

Multiscale stochastic approximation for parametric optimization of hidden Markov models

A two-time scale stochastic approximation algorithm is proposed for simulation-based parametric optimization of hidden Markov models, as an alternative to the traditional approaches to ''infinitesimal perturbation analysis.'' Its convergence is analyzed, and a queueing example is presented.

Reverse flotation of silica from Kudremukh iron ore .2. Optimization of flotation process

An experimental programme based on statistical analysis was used for optimizing the reverse Rotation of silica from non-magnetic spiral preconcentrate of Kudremukh iron ore. Flotation of silica with amine and starch as the Rotation reagents was studied to estimate the optimum reagent levels at various mesh of grind. The experiments were first carried out using a two level three factor design. Analysis of the results showed that two parameters namely, the concentration level of the amine collector and the mesh of grind, were significant. Experiments based on an orthogonal design of the hexagonal type were then carried out to determine the effects of these two variables, on recovery and grade of the concentrate. Regression equations have been developed as models. Response contours have been plotted using the 'path of steepest ascent', maximum response has been optimized at 0.27 kg/ton of amine collector, 0.5 kg/ton of starch and mesh of grind of 48.7% passing 300 mesh to give a recovery of 83.43% of Fe in the concentrate containing 66.6% Fe and 2.17% SiO2.

Shape optimization of RC flexural members

A natural velocity field method for shape optimization of reinforced concrete (RC) flexural members has been demonstrated. The possibility of shape optimization by modifying the shape of an initially rectangular section, in addition to variation of breadth and depth along the length, has been explored. Necessary shape changes have been computed using the sequential quadratic programming (SQP) technique. Genetic algorithm (Goldberg and Samtani 1986) has been used to optimize the diameter and number of main reinforcement bars. A limit-state design approach has been adopted for the nonprismatic RC sections. Such relevant issues as formulation of optimization problem, finite-element modeling, and solution procedure have been described. Three design examples-a simply supported beam, a cantilever beam, and a two-span continuous beam, all under uniformly distributed loads-have been optimized. The results show a significant savings (40-56%) in material and cost and also result in aesthetically pleasing structures. This procedure will lead to considerable cost saving, particularly in cases of mass-produced precast members and a heavy cast-in-place member such as a bridge girder.