Optimization of vibrating structures to reduce radiated noise

In this work, we propose an approach for reducing radiated noise from `light' fluid-loaded structures, such as, for example, vibrating structures in air. In this approach, we optimize the structure so as to minimize the dynamic compliance (defined as the input power) of the structure. We show that minimizing the dynamic compliance results in substantial reductions in the radiated sound power from the structure. The main advantage of this approach is that the redesign to minimize the dynamic compliance moves the natural frequencies of the structure away from the driving frequency thereby reducing the vibration levels of the structure, which in turn results in a reduction in the radiated sound power as an indirect benefit. Thus, the need for an acoustic and the associated sensitivity analysis is completely bypassed (although, in this work, we do carry out an acoustic analysis to demonstrate the reduction in sound power levels), making the strategy efficient compared to existing strategies in the literature which try to minimize some measure of noise directly. We show the effectiveness of the proposed approach by means of several examples involving both topology and stiffener optimization, for vibrating beam, plate and shell-type structures.

Modeling and optimization of a natural convection-based agricultural dryer

This study presents development of a computational fluid dynamic (CFD) model to predict unsteady, two-dimensional temperature, moisture and velocity distributions inside a novel, biomass-fired, natural convection-type agricultural dryer. Results show that in initial stages of drying, when material surface is wet and moisture is easily available, moisture removal rate from surface depends upon the condition of drying air. Subsequently, material surface becomes dry and moisture removal rate is driven by diffusion of moisture from inside to the material surface. An optimum 9-tray configuration is found to be more efficient than for the same mass of material and volume of dryer. A new configuration of dryer, mainly to explore its potential to increasing uniformity in drying across all trays, is also analyzed. This configuration involves diverting a portion of hot air before it enters over the first tray and is supplied directly at an intermediate location in the dryer. Uniformity in drying across trays has increased for the kind of material simulated.

Online Computation of Hysteresis Boundary for Constant Switching Frequency Current-Error Space-Vector-Based Hysteresis Controller for VSI-Fed IM Drives

This paper proposes a current-error space-vector-based hysteresis controller with online computation of boundary for two-level inverter-fed induction motor (IM) drives. The proposed hysteresis controller has got all advantages of conventional current-error space-vector-based hysteresis controllers like quick transient response, simplicity, adjacent voltage vector switching, etc. Major advantage of the proposed controller-based voltage-source-inverters-fed drive is that phase voltage frequency spectrum produced is exactly similar to that of a constant switching frequency space-vector pulsewidth modulated (SVPWM) inverter. In this proposed hysteresis controller, stator voltages along alpha- and beta-axes are estimated during zero and active voltage vector periods using current errors along alpha- and beta-axes and steady-state model of IM. Online computation of hysteresis boundary is carried out using estimated stator voltages in the proposed hysteresis controller. The proposed scheme is simple and capable of taking inverter upto six-step-mode operation, if demanded by drive system. The proposed hysteresis-controller-based inverter-fed drive scheme is experimentally verified. The steady state and transient performance of the proposed scheme is extensively tested. The experimental results are giving constant frequency spectrum for phase voltage similar to that of constant frequency SVPWM inverter-fed drive.

Damage-tolerant design optimization of laminated composite structures using dispersion of ply angles by genetic algorithm

This article aims to obtain damage-tolerant designs with minimum weight for a laminated composite structure using genetic algorithm. Damage tolerance due to impacts in a laminated composite structure is enhanced by dispersing the plies such that too many adjacent plies do not have the same angle. Weight of the structure is minimized and the Tsai-Wu failure criterion is considered for the safe design. Design variables considered are the number of plies and ply orientation. The influence of dispersed ply angles on the weight of the structure for a given loading conditions is studied by varying the angles in the range of 0 degrees-45 degrees, 0 degrees-60 degrees and 0 degrees-90 degrees at intervals of 5 degrees and by using specific ply angles tailored to loading conditions. A comparison study is carried out between the conventional stacking sequence and the stacking sequence with dispersed ply angles for damage-tolerant weight minimization and some useful designs are obtained. Unconventional stacking sequence is more damage tolerant than the conventional stacking sequence is demonstrated by performing a finite element analysis under both tensile as well as compressive loading conditions. Moreover, a new mathematical function called the dispersion function is proposed to measure the dispersion of ply angles in a laminate. The approach for dispersing ply angles to achieve damage tolerance is especially suited for composite material design space which has multiple local minima.

Electromechanical dynamics and optimization of pectoral fin-based ionic polymer-metal composite underwater propulsor

Ionic polymer-metal composites are soft artificial muscle-like bending actuators, which can work efficiently in wet environments such as water. Therefore, there is significant motivation for research on the development and design analysis of ionic polymer-metal composite based biomimetic underwater propulsion systems. Among aquatic animals, fishes are efficient swimmers with advantages such as high maneuverability, high cruising speed, noiseless propulsion, and efficient stabilization. Fish swimming mechanisms provide biomimetic inspiration for underwater propulsor design. Fish locomotion can be broadly classified into body and/or caudal fin propulsion and median and/or paired pectoral fin propulsion. In this article, the paired pectoral fin-based oscillatory propulsion using ionic polymer-metal composite for aquatic propulsor applications is studied. Beam theory and the concept of hydrodynamic function are used to describe the interaction between the beam and water. Furthermore, a quasi-steady blade element model that accounts for unsteady phenomena such as added mass effects, dynamic stall, and the cumulative Wagner effect is used to obtain hydrodynamic performance of the ionic polymer-metal composite propulsor. Dynamic characteristics of ionic polymer-metal composite fin are analyzed using numerical simulations. It is shown that the use of optimization methods can lead to significant improvement in performance of the ionic polymer-metal composite fin.

Robust solver based on modified particle swarm optimization for improved solution of diffusion transport through containment facilities

Accurate estimation of mass transport parameters is necessary for overall design and evaluation processes of the waste disposal facilities. The mass transport parameters, such as effective diffusion coefficient, retardation factor and diffusion accessible porosity, are estimated from observed diffusion data by inverse analysis. Recently, particle swarm optimization (PSO) algorithm has been used to develop inverse model for estimating these parameters that alleviated existing limitations in the inverse analysis. However, PSO solver yields different solutions in successive runs because of the stochastic nature of the algorithm and also because of the presence of multiple optimum solutions. Thus the estimated mean solution from independent runs is significantly different from the best solution. In this paper, two variants of the PSO algorithms are proposed to improve the performance of the inverse analysis. The proposed algorithms use perturbation equation for the gbest particle to gain information around gbest region on the search space and catfish particles in alternative iterations to improve exploration capabilities. Performance comparison of developed solvers on synthetic test data for two different diffusion problems reveals that one of the proposed solvers, CPPSO, significantly improves overall performance with improved best, worst and mean fitness values. The developed solver is further used to estimate transport parameters from 12 sets of experimentally observed diffusion data obtained from three diffusion problems and compared with published values from the literature. The proposed solver is quick, simple and robust on different diffusion problems. (C) 2012 Elsevier Ltd. All rights reserved.

Compiler-assisted energy optimization for clustered VLIW processors

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving the clock speed, reducing the energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires having high load capacitance which leads to delay in execution and significantly high energy consumption. Inter-cluster communication also introduces many short idle cycles, thereby significantly increasing the overall leakage energy consumption in the functional units. The trend towards miniaturization of devices (and associated reduction in threshold voltage) makes energy consumption in interconnects and functional units even worse, and limits the usability of clustered architectures in smaller technologies. However, technological advancements now permit the design of interconnects and functional units with varying performance and power modes. In this paper, we propose scheduling algorithms that aggregate the scheduling slack of instructions and communication slack of data values to exploit the low-power modes of functional units and interconnects. Finally, we present a synergistic combination of these algorithms that simultaneously saves energy in functional units and interconnects to improves the usability of clustered architectures by achieving better overall energy-performance trade-offs. Even with conservative estimates of the contribution of the functional units and interconnects to the overall processor energy consumption, the proposed combined scheme obtains on average 8% and 10% improvement in overall energy-delay product with 3.5% and 2% performance degradation for a 2-clustered and a 4-clustered machine, respectively. We present a detailed experimental evaluation of the proposed schemes. Our test bed uses the Trimaran compiler infrastructure. (C) 2012 Elsevier Inc. All rights reserved.

On maximum entropy and minimum KL-divergence optimization by Grobner basis methods

In this paper we study constrained maximum entropy and minimum divergence optimization problems, in the cases where integer valued sufficient statistics exists, using tools from computational commutative algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. We give an implicit description of maximum entropy models by embedding them in algebraic varieties for which we give a Grobner basis method to compute it. In the cases of minimum KL-divergence models we show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner basis method to embed minimum KL-divergence models in algebraic varieties. (C) 2012 Elsevier Inc. All rights reserved.

Causality analysis of groundwater dynamics based on a Vector Autoregressive model in the semi-arid basin of Gundal (South India)

Causal relationships existing between observed levels of groundwater in a semi-arid sub-basin of the Kabini River basin (Karnataka state, India) are investigated in this study. A Vector Auto Regressive model is used for this purpose. Its structure is built on an upstream/downstream interaction network based on observed hydro-physical properties. Exogenous climatic forcing is used as an input based on cumulated rainfall departure. Optimal models are obtained thanks to a trial approach and are used as a proxy of the dynamics to derive causal networks. It appears to be an interesting tool for analysing the causal relationships existing inside the basin. The causal network reveals 3 main regions: the Northeastern part of the Gundal basin is closely coupled to the outlet dynamics. The Northwestern part is mainly controlled by the climatic forcing and only marginally linked to the outlet dynamic. Finally, the upper part of the basin plays as a forcing rather than a coupling with the lower part of the basin allowing for a separate analysis of this local behaviour. The analysis also reveals differential time scales at work inside the basin when comparing upstream oriented with downstream oriented causalities. In the upper part of the basin, time delays are close to 2 months in the upward direction and lower than 1 month in the downward direction. These time scales are likely to be good indicators of the hydraulic response time of the basin which is a parameter usually difficult to estimate practically. This suggests that, at the sub-basin scale, intra-annual time scales would be more relevant scales for analysing or modelling tropical basin dynamics in hard rock (granitic and gneissic) aquifers ubiquitous in south India. (c) 2012 Elsevier B.V. All rights reserved.

Data-resolution based optimization of the data-collection strategy for near infrared diffuse optical tomography

Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]

Optimization of thermoacoustic primemover using response surface methodology

Thermoacoustic engines are energy conversion devices that convert thermal energy from a high-temperature heat source into useful work in the form of acoustic power while diverting waste heat into a cold sink; it can be used as a drive for cryocoolers and refrigerators. Though the devices are simple to fabricate, it is very challenging to design an optimized thermoacoustic primemover with better performance. The study presented here aims to optimize the thermoacoustic primemover using response surface methodology. The influence of stack position and its length, resonator length, plate thickness, and plate spacing on pressure amplitude and frequency in a thermoacoustic primemover is investigated in this study. For the desired frequency of 207 Hz, the optimized value of the above parameters suggested by the response surface methodology has been conducted experimentally, and simulations are also performed using DeltaEC. The experimental and simulation results showed similar output performance.

Supersymmetric Chern-Simons theories with vector matter

In this paper we discuss SU(N) Chern-Simons theories at level k with both fermionic and bosonic vector matter. In particular we present an exact calculation of the free energy of the N = 2 supersymmetric model (with one chiral field) for all values of the `t Hooft coupling in the large N limit. This is done by using a generalization of the standard Hubbard-Stratanovich method because the SUSY model contains higher order polynomial interactions.

Multilevel dodecagonal space-vector generation for induction motor drives by cascading three-level and two-level inverters

This study proposes an inverter circuit topology capable of generating multilevel dodecagonal (12-sided polygon) voltage space vectors by the cascaded connection of two-level and three-level inverters. By the proper selection of DC-link voltages and resultant switching states for the inverters, voltage space vectors whose tips lie on three concentric dodecagons, are obtained. A rectifier circuit for the inverter is also proposed, which significantly improves the power factor. The topology offers advantages such as the complete elimination of the fifth and seventh harmonics in phase voltages and an extension of the linear modulation range. In this study, a simple method for the calculation of pulse width modulation timing was presented along with extensive simulation and experimental results in order to validate the proposed concept.

Space-vector-based hybrid pulse width modulation technique to reduce line current distortion in induction motor drives

Pulse width modulation (PWM) techniques involving different switching sequences are used in space vector-based PWM generation for reducing line current ripple in induction motor drives. This study proposes a hybrid PWM technique employing five switching sequences. The proposed technique is a combination of continuous PWM, discontinuous PWM (DPWM) and advanced bus clamping PWM methods. Performance of the proposed PWM technique is evaluated and compared with those of the existing techniques on a constant volts per hertz induction motor drive. In terms of total harmonic distortion in the line current, the proposed method is shown to be superior to both conventional space vector PWM (CSVPWM) and DPWM over a fundamental frequency range of 32-50 Hz at a given average switching frequency. The reduction in harmonic distortion is about 42% over CSVPWM at the rated speed of the drive.

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.