Estimation of discharge and its distribution in compound channels简

Results of research into a compound channel having width ratio(?)in excess of 11 are presented in the form of boundary shear distributions across the compound cross section.New relationship is derived between the percentage of shear carried by the flood plains(%)fp S and the percentage of area occupied by the flood plains(%)fp A.The equation so derived is taken as the basis to develop a new methodology to predict the stage discharge relationship specifically for wide compound channels using Darcy’s friction factor(f)for the main channel and flood plain regions.The methodology also is used for compound channels with smaller width ratios by applying the appropriate relation for%fp S derived earlier by different researchers and seems to work well.Next,as a corollary to the methodology,separate formulae are proposed to estimate flow distribution in main channel and flood plain regions.The proposed method and its corollary are tested for their validity against well-published small-scale data series of previous researchers along with some large-scale data series from EPSRC-FCF(A-Series)compound channel experiments and very good agreement is observed between the measured values and predicted values for total flow as well as zonal distribution of flow.The methodology is also applied to some compound river section data published in literature and is found to serve well the purpose of predicting flow in real world application.This new method gives the least RMS value of error for discharge prediction compared with some other well-known methods used for estimating stage-discharge relation in compound channels by considering all data sets.     

Preference structure on alternatives and judges in a group decision problem—a fuzzy approach

In this paper a method is proposed for investigating the problem which deals with multi-judge, multi-criteria and multi-alternative decision problems. The objective of this paper basically consists of a procedure for giving a preference structure among the judges and ranking of alternatives with strength of preference by taking into account the opinion of all the judges according to their degree of efficiency. This paper also discusses some drawbacks of the application of majority rule for obtaining group consensus function.     

A new efficient optimal path planner for mobile robot based on Invasive Weed Optimization algorithm

Planning of the shortest/optimal route is essential for efficient operation of autonomous mobile robot or vehicle. In this paper Invasive Weed Optimization (IWO), a new meta-heuristic algorithm, has been implemented for solving the path planning problem of mobile robot in partially or totally unknown environments. This meta-heuristic optimization is based on the colonizing property of weeds. First we have framed an objective function that satisfied the conditions of obstacle avoidance and target seeking behavior of robot in partially or completely unknown environments. Depending upon the value of objective function of each weed in colony, the robot avoids obstacles and proceeds towards destination. The optimal trajectory is generated with this navigational algorithm when robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed algorithm has been demonstrated through series of simulation and experimental results. Finally, it has been found that the developed path planning algorithm can be effectively applied to any kinds of complex situation.     

The textural properties of soy paneer

Toned dairy milk and soy milk were mixed in different proportions and coagulated at various temperatures to produce paneer blends, and their textural properties were evaluated. As the soy milk proportion in the blend increased from 0% to 50%, hardness, cohesiveness and chewiness of the samples decreased initially, but further increase in the blend from 50% to 100% cause these values to increase slightly. The proportion of soymilk in the prepared paneer had a significant effect on hardness, cohesiveness, adhesiveness, chewiness and yield, whereas the coagulation temperature affected cohesiveness and yield. The process parameters did not show any effect on the springiness.     

COMPARISON OF A PAIR OF THREE PARAMETER EQUATIONS OF STATE

The lattice fluid (LF) equation of state derived by Sanchez and Lacombe from a lattice model is compared to the empirical Peng-Robinson (PR) equation for normal alkane fluids ranging from methane to heptadecane in molecular weight. With respect to vapor pressure predictions, the equations are both good. The LF equation is superior, especially for higher molecular weight fluids, to the Peng-Robinson equation in predicting saturated liquid densities. For carbon numbers less than 6, the PR equation predicts heats of vaporization more accurately, whereas for carbon numbers greater than 9 the LF equation is more accurate than the PR one for temperatures lower than about 95% of critical.     

Mechanical and morphological investigation of virgin polyethylene and silver nanoparticle-loaded nanocomposites film: comprehensive analysis of kinetic models for non-isothermal crystallization

This research was accomplished to examine the mechanical, morphological and crystallization kinetics study of polyethylene/silver nanoparticles (Ag-NPs) nanocomposite films. In this research, low-density polyethylene (LDPE) nanocomposite films were prepared containing Ag-NPs using maleic-anhydride-grafted low-density polyethylene (LDPE-g-MAH) as a compatibilizer by the melt mixing process. From mechanical property evaluation, it is revealed that the LDPE/LDPE-g-MAH/Ag-NPs nanocomposite films showed decreased tensile strength as compared with virgin LDPE matrix. Thermal characteristics of the prepared virgin LDPE and its nanocomposite films were studied by differential scanning calorimetry (DSC). Comprehensive analysis of different kinetic models such as the Avrami and Mo model on non-isothermal crystallization kinetics was performed in order to correlate the rate of crystallization and its various kinetic parameters. Further, the macrokinetic equation as proposed by Malkin has been applied to describe the kinetics of crystallization in the light of the Avrami equation. Concerning virgin LDPE and Ag-NP-reinforced LDPE, the former shows primary crystallization, whereas the later exhibits both primary and secondary crystallization with varying Avrami exponents. Kinetic parameters are recognized, and confirm the influence of Ag-NPs on crystallization kinetics. X-ray diffraction spectroscopy and transmission electron microscopic analysis of the nanocomposite films were conducted to verify the dispersion of inorganic filler particles in the resulting hybrids.     

Implementation of feedback-linearization-modelled induction motor drive through an adaptive simplified neuro-fuzzy approach

A simple modified version of neuro-fuzzy controller (NFC) method based on single-input, reduced membership function in conjunction with an intuitive flux–speed decoupled feedback linearization (FBL) approach of induction motor (IM) model is presented in this paper. The proposed NFC with FBL remarkably suppresses the torque and speed ripple and shows improved performance. Further, the modified NFC is tuned by genetic algorithm (GA) approach for optimal performance of FBL-based IM drive. Moreover, the GA searches the optimal parameters of the simplified NFC in order to ensure the global convergence of error. The proposed simplified NFC integrates the concept of fuzzy logic and neural network structure like a conventional NFC, but it has the advantages of simplicity and improved computational efficiency over the conventional NFC as the single input introduced here is an error (speed and torque) instead of two inputs, error and change in error, as in the conventional NFC. This structure makes the proposed NFC robust and simple as compared with conventional NFC and thus, can be easily applied to real-time industry application. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using FBL of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using the proposed simple NFC as compared to the conventional NFC; rather, it shows superior performance over PI-controller-based drive.     

Optimization of cryo-treated EDM variables using TOPSIS-based TLBO algorithm

In order to machine hard and high-strength-to-weight ratio materials, electrical discharge machining (EDM) process is extensively used in aerospace, automobile and other industrial applications. However, high erosion of tool and improper selection of machining variables have emerged as a major obstruction to achieve productivity in this direction. High erosion of tool not only enhances the cost of machining but also increases the machining time by causing interruption during machining. Therefore, proper selection of machining variables and tool material life are the two vital aspects for the tool engineers working in EDM. In view of this, the present work proposes an extensive experimental investigation and optimization of machining variables of cryogenically treated brass tool materials on machining competences of Inconel 718 workpiece. The study primarily highlights the outcome of cryogenically treated soaking duration of tools along with other important process variables, viz. discharge current, open-circuit voltage, pulse-on time, duty factor and flushing pressure, on the performance measures such as electrode wear ratio (EWR), surface roughness and radial over-cut. The study revealed that soaking duration in deep cryo-treatment of the electrode is a significant variable to achieve improved machining characteristics. The performance measures are converted into equivalent single performance measure by calculating the relative closeness coefficient by the techniques for order preferences by similarity to ideal solution (TOPSIS) approach. Finally, a novel teaching–learning-based optimization (TLBO) algorithm has been proposed to find the optimal level of machining variables for the performance measures. The optimal levels of cutting variables obtained through the algorithm are validated through confirmation test, predicting an error of 2.171 percentages between the computational and experimental results. The predicted result suggests that the proposed model can be used to select the ideal process states to achieve productivity for the cryo-treated EDM.     

A fuzzy approach to multi-objective routing problem with applications to process planning in manufacturing systems

In this paper a method is developed for the selection of an efficient path in a fuzzy multi-objective network. The application of the methodology developed is illustrated by a process plan selection problem in a manufacturing environment.     

Removal of phosphorus from aqueous solution using alumized red mud

Treated red mud, the solid residue from bauxite processing, was found to adsorb phosphorus from dilute aqueous solution effectively. Experiments were carried out in aqueous as well as buffer media to obtain the optimum conditions like contact time, pH, adsorbent dose, adsorbate concentration, temperature etc. The pH value of 4.5 was found to be optimum for maximum removal. The equilibrium was attained within 60 mins. Lower adsorbent dose and higher initial phosphorus concentration favoured higher loading capacity. The adsorption process followed Freundlich isotherm and Lagergren equations and they followed first order rate kinetics. The effect of different anions on phosphorus removal could be explained on the basis of the changing affinity of anions for the surface and their relative concentrations.