A dragonfly inspired flapping wing actuated by electro active polymers

An energy-based variational approach is used for structural dynamic modeling of the IPMC (Ionic Polymer Metal Composites) flapping wing. Dynamic characteristics of the wing are analyzed using numerical simulations. Starting with the initial design, critical parameters which have influence on the performance of the wing are identified through parametric studies. An optimization study is performed to obtain improved flapping actuation of the IPMC wing. It is shown that the optimization algorithm leads to a flapping wing with dimensions similar to the dragonfly Aeshna Multicolor wing. An unsteady aerodynamic model based on modified strip theory is used to obtain the aerodynamic forces. It is found that the IPMC wing generates sufficient lift to support its own weight and carry a small payload. It is therefore a potential candidate for flapping wing of micro air vehicles.

Retrieval of dust aerosols during night: improved assessment of long wave dust radiative forcing over Afro-Asian regions

Several investigators in the past have used the radiance depression (with respect to clear-sky infrared radiance), resulting from the presence of mineral dust aerosols in the atmosphere, as an index of dust aerosol load in the atmosphere during local noon. Here, we have used a modified approach to retrieve dust index during night since assessment of diurnal average infrared dust forcing essentially requires information on dust aerosols during night. For this purpose, we used infrared radiance (10.5-12.5 mu m), acquired from the METEOSAT-5 satellite (similar to 5 km resolution). We found that the `dust index' algorithm, valid for daytime, will no longer hold during the night because dust is then hotter than the theoretical dust-free reference. Hence we followed a `minimum reference' approach instead of a conventional `maximum reference' approach. A detailed analysis suggests that the maximum dust load occurs during the daytime. Over the desert regions of India and Africa, maximum change in dust load is as much as a factor of four between day and night and factor of two variations are commonly observed. By realizing the consequent impact on long wave dust forcing, sensitivity studies were carried out, which indicate that utilizing day time data for estimating the diurnally averaged long-wave dust radiative forcing results in significant errors (as much as 50 to 70%). Annually and regionally averaged long wave dust radiative forcing (which account for the diurnal variation of dust) at the top of the atmosphere over Afro-Asian region is 2.6 +/- 1.8 W m(-2), which is 30 to 50% lower than those reported earlier. Our studies indicate that neglecting diurnal variation of dust while assessing its radiative impact leads to an overestimation of dust radiative forcing, which in turn result in underestimation of the radiative impact of anthropogenic aerosols.

An algorithm to detect linearly separable clusters of binary patterns

The clusters of binary patterns can be considered as Boolean functions of the (binary) features. Such a relationship between the linearly separable (LS) Boolean functions and LS clusters of binary patterns is examined. An algorithm is presented to answer the questions of the type: “Is the cluster formed by the subsets of the (binary) data set having certain features AND/NOT having certain other features, LS from the remaining set?” The algorithm uses the sequences of Numbered Binary Form (NBF) notation and some elementary (NPN) transformations of the binary data.

Modified governing equations for gas-particle nozzle flows

A modified set of governing equations for gas-particle flows in nozzles is suggested to include the inertial forces acting on the particle phase. The problem of gas-particle flow through a nozzle is solved using a first order finite difference scheme. A suitable stability condition for the numerical scheme for gas-particle flows is defined. Results obtained from the present set of equations are compared with those of the previous set of equations. It is also found that present set of equations give results which are in good agreement with the experimental observation.

Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures

In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm. VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC). In the current work a modified version of VEABC algorithm for discrete variables has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria: failure mechanism based failure criteria, maximum stress failure criteria and the tsai-wu failure criteria. The optimization method is validated for a number of different loading configurations-uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Finally the performance is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA). The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations. (C) 2009 Elsevier B.V. All rights reserved.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Super-plasticized natural rubber latex modified concretes

Polymeric admixtures to concrete ingredients modify the properties of the processed concrete. Ductility is one such property modification. This investigation deals with the development of a method of incorporating natural rubber latex into concrete ingredients with only marginal effects on the compressive strength of base plain concrete. This retention of the strength has been effected by reducing the water/cement ratio with the aid of a superplasticizer. The quantity of natural rubber latex is expressed as the dry rubber content by percentage of volume of concrete. The compressive and tensile strengths, as well as post peak ductile behaviour have been the basis for comparison with those of unmodified concrete.

A parallel multistep predictor-corrector algorithm for solving ordinary differential equations

In this paper we give a generalized predictor-corrector algorithm for solving ordinary differential equations with specified initial values. The method uses multiple correction steps which can be carried out in parallel with a prediction step. The proposed method gives a larger stability interval compared to the existing parallel predictor-corrector methods. A method has been suggested to implement the algorithm in multiple processor systems with efficient utilization of all the processors.

An algorithm to find distant repeats in a pair of protein sequences

Distant repeats between a pair of protein sequences can be exploited to study the various aspects of proteins such as structure-function relationship, disorders due to protein malfunction, evolutionary analysis, etc. An in-depth analysis of the distant repeats would facilitate to establish a stable evolutionary relation of the repeats with respect to their three-dimensional structure. To this effect, an algorithm has been devised to identify the distant repeats in a pair of protein sequences by essentially using the scores of PAM (Percent Accepted Mutation) matrices. The proposed algorithm will be of much use to researchers involved in the comparative study of various organisms based on the amino-acid repeats in protein sequences. (C) 2010 Elsevier B.V. All rights reserved.

An efficient reduction algorithm for computation of interconnect delay variability for statistical timing analysis in clock tree planning

In this paper, we propose a novel and efficient algorithm for modelling sub-65 nm clock interconnect-networks in the presence of process variation. We develop a method for delay analysis of interconnects considering the impact of Gaussian metal process variations. The resistance and capacitance of a distributed RC line are expressed as correlated Gaussian random variables which are then used to compute the standard deviation of delay Probability Distribution Function (PDF) at all nodes in the interconnect network. Main objective is to find delay PDF at a cheaper cost. Convergence of this approach is in probability distribution but not in mean of delay. We validate our approach against SPICE based Monte Carlo simulations while the current method entails significantly lower computational cost.

A Computationally Efficient PWM Algorithm for Multilevel Inverters

Centred space vector PWM (CSVPWM) technique is popularly used for three level voltage source inverters. The reference voltage vector is synthesized by time-averaging of the three nearest voltage vectors produced by the inverter. Identifying the three voltage vectors, and calculation of the dwelling time for each vector are both computationally intensive. This paper analyses the process of PWM generation in CSVPWM. This analysis breaks up a three-level inverter into six different conceptual two level inverters in different regions of the fundamental cycle. Control of 3-level inverter is viewed as the control of the appropriate 2-level inverter. The analysis leads to a systematic simplification of the computations involved, finally resulting in a computationally efficient PWM algorithm. This algorithm exploits the equivalence between triangle comparison and space vector approaches to PWM generation. This algorithm does not involve any 3-phase/2-phase or 2-phase/3-phase transformation. This also does not involve any transformation from rectangular to polar coordinates, and vice versa. Further no evaluation of trigonometric functions is necessary. This algorithm also provides for the mitigation of DC neutral point unbalance, and is well suited to digital implementation. Simulation and experimental results are presented.

High-Temperature (1023 K to 1273 K 750 degrees C to 1000 degrees C]) Plastic Deformation Behavior of B-Modified Ti-6Al-4V Alloys: Temperature and Strain Rate Effects

A minor addition of B to the Ti-6Al-4V alloy, by similar to 0.1 wt pct, reduces its as-cast prior beta grain size by an order of magnitude, whereas higher B content leads to the presence of in situ formed TiB needles in significant amounts. An experimental investigation into the role played by these microstructural modifications on the high-temperature deformation behavior of Ti-6Al-4V-xB alloys, with x varying between 0 wt pct and 0.55 wt pct, was conducted. Uniaxial compression tests were performed in the temperature range of 1023 K to 1273 K (750 degrees C to 1000 degrees C) and in the strain rate range of 10(-3) to 10(+1) s(-1). True stress-true strain responses of all alloys exhibit flow softening at lower strain rates and oscillations at higher strain rates. The flow softening is aided by the occurrence of dynamic recrystallization through lath globularization in high temperature (1173 K to 1273 K 900 degrees C to 1000 degrees C]) and a lower strain rate (10(-2) to 10(-3) s(-1)) regime. The grain size refinement with the B addition to Ti64, despite being marked, had no significant effect on this. Oscillations in the flow curve at a higher strain rate (10(0) to 10(+1) s(-1)), however, are associated with microstructural instabilities such as bending of laths, breaking of lath boundaries, generation of cavities, and breakage of TiB needles. The presence of TiB needles affected the instability regime. Microstructural evidence suggests that the matrix cavitation is aided by the easy fracture of TiB needles.