Hydration numbers of some metal acetates, monochloroacetates and trichloroacetates in solution from ultrasonic velocity and conpressibility measurements

Ultrasonic velocities in aqueous solutions of some metal acetates, monochloroacelates and trichloroacetates, and the respective acids have been measured at 1 MHz frequency using the pulse technique. The ultrsonic velocity, adiabatic compressibility and apperent molal compressibility were measured as a function of concentration. The apparent molal compressibility values at infinite dilution were calculated and used to determine the hydration numbers.

Mass transfer with surface reaction in arrays of cylinders at low reynolds and high peclet numbers

Creeping flow hydrodynamics combined with diffusion boundary layer equation are solved in conjunction with free-surface cell model to obtain a solution of the problem of convective transfer with surface reaction for flow parallel to an array of cylindrical pellets at high Peclet numbers and under fast and intermediate kinetics regimes. Expressions are derived for surface concentration, boundary layer thickness, mass flux and Sherwood number in terms of Damkoehler number, Peclet number and void fraction of the array. The theoretical results are evaluated numerically.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor

A health-monitoring and life-estimation strategy for composite rotor blades is developed in this work. The cross-sectional stiffness reduction obtained by physics-based models is expressed as a function of the life of the structure using a recent phenomenological damage model. This stiffness reduction is further used to study the behavior of measurable system parameters such as blade deflections, loads, and strains of a composite rotor blade in static analysis and forward flight. The simulated measurements are obtained using an aeroelastic analysis of the composite rotor blade based on the finite element in space and time with physics-based damage modes that are then linked to the life consumption of the blade. The model-based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems are developed for global online prediction of physical damage and life consumption using displacement- and force-based measurement deviations between damaged and undamaged conditions. Furthermore, local online prediction of physical damage and life consumption is done using strains measured along the blade length. It is observed that the life consumption in the matrix-cracking zone is about 12-15% and life consumption in debonding/delamination zone is about 45-55% of the total life of the blade. It is also observed that the success rate of the genetic fuzzy systems depends upon the number of measurements, type of measurements and training, and the testing noise level. The genetic fuzzy systems work quite well with noisy data and are recommended for online structural health monitoring of composite helicopter rotor blades.

Two-way converter logic for positive and negative binary numbers

This paper describes a hardware implementation of a two-way converter logic by which conversion between numbers from positive to negative binary representation is possible. Index terms: (i) Negative radix, (ii) Positive radix, (iii) Two-way conversion.

Fuzzy-expert approach for voltage-reactive power dispatch

The voltage stability control problem has become an important concern for utilities transmitting power over long distances. This paper presents an approach using fuzzy set theory for reactive power control with the purpose of improving the voltage stability of a power system. To minimize the voltage deviations from pre-desired values of all the load buses, using the sensitivities with respect to reactive power control variables form the basis of the proposed fuzzy logic control (FLC). Control variables considered are switchable VAR compensators, On Load Tap Changing (OLTC) transformers and generator excitations. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. The developed fuzzy system is tested on a few simulated practical Indian power systems and some IEEE standard test systems. The performance of the fuzzy system is compared with conventional optimization technique and results obtained are encouraging. Results obtained for a 24 - node equivalent EHV system of part of Indian southern grid and IEEE New England 39-bus system are presented for illustration purposes. The proposed Fuzzy-Expert technique is found suitable for on-line applications in energy control centre as the solution is obtained fast with significant speedups.

The Formation, Numbers And Radio Output Of Giant Radio Galaxies

The numbers and mean radio luminosities of giant radio galaxies (GRGs) have been calculated for redshifts up to z = 0.6, assuming a sensitivity limit of 1 Jy at 1 GHz for the observations. The estimates are obtained with a model for the beam propagation, first through the hot gaseaous halo around the parent galaxy, and thereafter, through the even hotter but less dense intergalactic medium. The model is able to accurately reproduce the observed numbers and mean radio luminosities of GRGs at redshifts of less than 0.1, and it predicts that a somewhat larger number of GRGs should be found at redshifts of greater than 0.1.

Transient Momentum and Enthalpy Transfer in Packed Beds at High Reynolds Numbers

An experimental study for transient temperature response and pressure drop in a randomly packed bed at high Reynolds numbers is presented.The packed bed is used as a compact heat exchanger along with a solid-propellant gas generator, to generate room-temperature gases for use in control actuation, air bottle pressurization, etc. Packed beds of lengths 200 and 300 mm were characterized for packing-sphere-based Reynolds numbers ranging from 0.8 x 10(4) to 8.5 x 10(4).The solid packing used in the bed consisted of phi 9.5 mm steel spheres. The bed-to-particle diameter ratio was with the average packed-bed porosity around 0.43. The inlet flow temperature was unsteady and a mesh of spheres was used at either end to eliminate flow entrance and exit effects. Gas temperature and pressure were measured at the entry, exit,and at three axial locations along centerline in the packed beds. The solid packing temperature was measured at three axial locations in the packed bed. A correlation based on the ratio of pressure drop and inlet-flow momentum (Euler number) exhibited an asymptotically decreasing trend with increasing Reynolds number. Axial conduction across the packed bed was found to he negligible in the investigated Reynolds number range. The enthalpy absorption rate to solid packing from hot gases is plotted as a function of a nondimensional time constant for different Reynolds numbers. A longer packed bed had high enthalpy absorption rate at Reynolds number similar to 10(4), which decreased at Reynolds number similar to 10(5). The enthalpy absorption plots can be used for estimating enthalpy drop across packed bed with different material, but for a geometrically similar packing.

Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation

The hazards associated with major accident hazard (MAN) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identification and quantification of these hazards related to chemical industries. Fault tree analysis (FTA) is an established technique in hazard identification. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. This paper outlines the estimation of the probability of release of chlorine from storage and filling facility of chlor-alkali industry using FTA. An attempt has also been made to arrive at the probability of chlorine release using expert elicitation and proven fuzzy logic technique for Indian conditions. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two-dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor involved in expert elicitation. (C) 2010 Elsevier B.V. All rights reserved.