Violin string shape functions for finite element analysis of rotating Timoshenko beams

Violin strings are relatively short and stiff and are well modeled by Timoshenko beam theory. We use the static part of the homogeneous differential equation of violin strings to obtain new shape functions for the finite element analysis of rotating Timoshenko beams. For deriving the shape functions, the rotating beam is considered as a sequence of violin strings. The violin string shape functions depend on rotation speed and element position along the beam length and account for centrifugal stiffening effects as well as rotary inertia and shear deformation on dynamic characteristics of rotating Timoshenko beams. Numerical results show that the violin string basis functions perform much better than the conventional polynomials at high rotation speeds and are thus useful for turbo machine applications. (C) 2011 Elsevier B.V. All rights reserved.

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.

Optimization studies on limestone beneficiation

Limestone rejects from Bagalkot mines have been beneficiated by froth flotation with a view to reducing the magnesia content. In order to ascertain the effect of the main parameters such as sodium oleate concentration, sodium silicate concentration and pH on the MgO content, statistically designed experiments have been performed. The results indicate that under the optimum conditions arrived at limestone rejects could be beneficiated to produce a concentrate with magnesia. content meeting the specifications for cement manufacture.

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.

Classification of microwatersheds based on morphological characteristics

Three classification techniques, namely, K-means Cluster Analysis (KCA), Fuzzy Cluster Analysis (FCA), and Kohonen Neural Networks (KNN) were employed to group 25 microwatersheds of Kherthal watershed, Rajasthan into homogeneous groups for formulating the basis for suitable conservation and management practices. Ten parameters, mainly, morphological, namely, drainage density (D-d), bifurcation ratio (R-b), stream frequency (F-u), length of overland flow (L-o), form factor (R-f), shape factor (B-s), elongation ratio (R-e), circulatory ratio (R-c), compactness coefficient (C-c) and texture ratio (T) are used for the classification. Optimal number of groups is chosen, based on two cluster validation indices Davies-Bouldin and Dunn's. Comparative analysis of various clustering techniques revealed that 13 microwatersheds out of 25 are commonly suggested by KCA, FCA and KNN i.e., 52%; 17 microwatersheds out of 25 i.e., 68% are commonly suggested by KCA and FCA whereas these are 16 out of 25 in FCA and KNN (64%) and 15 out of 25 in KNN and CA (60%). It is observed from KNN sensitivity analysis that effect of various number of epochs (1000, 3000, 5000) and learning rates (0.01, 0.1-0.9) on total squared error values is significant even though no fixed trend is observed. Sensitivity analysis studies revealed that microwatershecls have occupied all the groups even though their number in each group is different in case of further increase in the number of groups from 5 to 6, 7 and 8. (C) 2010 International Association of Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.

The influence of temperature gradient and lowering speed on the melt-solid interface shape of GaxIn1-xSb alloy crystals grown by vertical Bridgman technique

Radially homogeneous bulk alloys of GaxIn1-xSb in the range 0.7 < x < 0.8, have been grown by vertical Bridgman technique. The factors affecting the interface shape during the growth were optimised to achieve zero convexity. From a series of experiments, a critical ratio of the temperature gradient (G) of the furnace at the melting point of the melt composition to the ampoule lowering speed (v) was deduced for attaining the planarity of the melt-solid interface. The studies carried out on directional solidification of Ga0.77In0.23Sb mixed crystals employing planar melt-solid interface exhibited superior quality than those with nonplanar interfaces. The solutions to certain problems encountered during the synthesis and growth of the compound were discussed. (C) 1999 Elsevier Science B.V. All rights reserved.

Application of an evolutionary fuzzy system for the estimation of workforce deployment and cross-training in an assembly environment

Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

Experimental study and optimization of Plasma Actuators for Flow control in subsonic regime

Experimental study and optimization of Plasma Ac- tuators for Flow control in subsonic regime PRADEEP MOISE, JOSEPH MATHEW, KARTIK VENKATRAMAN, JOY THOMAS, Indian Institute of Science, FLOW CONTROL TEAM | The induced jet produced by a dielectric barrier discharge (DBD) setup is capable of preventing °ow separation on airfoils at high angles of attack. The ef-fect of various parameters on the velocity of this induced jet was studied experimentally. The glow discharge was created at atmospheric con-ditions by using a high voltage RF power supply. Flow visualization,photographic studies of the plasma, and hot-wire measurements on the induced jet were performed. The parametric investigation of the charac- teristics of the plasma show that the width of the plasma in the uniform glow discharge regime was an indication of the velocity induced. It was observed that the spanwise and streamwise overlap of the two electrodes,dielectric thickness, voltage and frequency of the applied voltage are the major parameters that govern the velocity and the extent of plasma.e®ect of the optimized con¯guration on the performance characteristics of an airfoil was studied experimentally.

Control of transient thermal response during sequential open-die forging: A trajectory optimization approach

A trajectory optimization approach is applied to the design of a sequence of open-die forging operations in order to control the transient thermal response of a large titanium alloy billet. The amount of time tire billet is soaked in furnace prior to each successive forging operation is optimized to minimize the total process time while simultaneously satisfying constraints on the maximum and minimum values of the billet's temperature distribution to avoid microstructural defects during forging. The results indicate that a "differential" heating profile is the most effective at meeting these design goals.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

Fuzzy logic intelligent system for gas turbine module and system fault isolation

A fuzzy logic intelligent system is developed for gas-turbine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. These four measurements are also called the cockpit parameters and are typically found in almost all older and newer jet engines. The fuzzy logic system uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. It automates the reasoning process of an experienced powerplant engineer. Tests with simulated data show that the fuzzy system isolates faults with an accuracy of 89% with only the four cockpit measurements. However, if additional pressure and temperature probes between the compressors and before the burner, which are often found in newer jet engines, are considered, the fault isolation accuracy rises to as high as 98%. In addition, the additional sensors are useful in keeping the fault isolation system robust as quality of the measured data deteriorates.

Health monitoring,of a helicopter rotor in forward flight using fuzzy logic

A fuzzy logic system is developed for helicopter rotor system fault isolation. Inputs to the fuzzy logic system are measurement deviations of blade bending and torsion response and vibration from a "good" undamaged helicopter rotor. The rotor system measurements used are flap and lag bending tip deflections, elastic twist deflection at the tip, and three forces and three moments at the rotor hub. The fuzzy logic system uses rules developed from an aeroelastic model of the helicopter rotor with implanted faults to isolate the fault while accounting for uncertainty in the measurements. The faults modeled include moisture absorption, loss of trim mass, damaged lag damper, damaged pitch control system, misadjusted pitch link, and damaged flap. Tests with simulated data show that the fuzzy system isolates rotor system faults with an accuracy of about 90-100%. Furthermore, the fuzzy system is robust and gives excellent results, even when some measurements are not available. A rule-based expert system based on similar rules from the aeroelastic model performs much more poorly than the fuzzy system in the presence of high levels of uncertainty.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Optimization of off-oriented Ge substrates for MOVPE-grown GaAs solar cells

GaAs/Ge heterostructures having abrupt interfaces were grown on 2degrees, 6degrees, and 9degrees off-cut Ge substrates and investigated by cross-sectional high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy, photoluminescence spectroscopy and electrochemical capacitance voltage (ECV) profiler. The GaAs films were grown on off-oriented Ge substrates with growth temperature in the range of 600-700degreesC, growth rate of 3-12 mum/hr and a V/III ratio of 29-88. The lattice indexing of HRTEM exhibits an excellent lattice line matching between GaAs and Ge substrate. The PL spectra from GaAs layer on 6degrees off-cut Ge substrate shows the higher excitonic peak compared with 2degrees and 9degrees off-cut Ge substrates. In addition, the luminescence intensity from the GaAs solar cell grown on 6degrees off-cut is higher than on 9degrees off-cut Ge substrates and signifies the potential use of 6degrees off-cut Ge substrate in the GaAs solar cells industry. The ECV profiling shows an abrupt film/substrate interface as well as between various layers of the solar cell structures.

A fuzzy control for network overload alleviation

This paper presents a prototype of a fuzzy system for alleviation of network overloads in the day-to-day operation of power systems. The control used for overload alleviation is real power generation rescheduling. Generation Shift Sensitivity Factors (GSSF) are computed accurately, using a more realistic operational load flow model. Overloading of lines and sensitivity of controlling variables are translated into fuzzy set notations to formulate the relation between overloading of line and controlling ability of generation scheduling. A fuzzy rule based system is formed to select the controllers, their movement direction and step size. Overall sensitivity of line loading to each of the generation is also considered in selecting the controller. Results obtained for network overload alleviation of two modified Indian power networks of 24 bus and 82 bus with line outage contingencies are presented for illustration purposes.