Enhancement of convective cooling using oscillating fins

Tailoring the local flow field around a fin can substantially enhance the forced convection heat transfer from a conventional heat sink. A fin is set into oscillation leading to rupture of the thermal boundary layer developed on either side of the fin. This enhancement in heat transfer is demonstrated through an increase in the time-averaged Nusselt Number (Nu) on the fin surfaces. Nu has been found to be strongly dependent on the flow Reynolds Number (Re), the frequency and amplitude of the fin oscillations. A threshold amplitude and frequency is identified beyond which Nu improvements are observed for fixed Re.     

Modeling of transient natural convection heat transfer in electric ovens

Prediction of transient natural convection heat transfer in vented enclosures has multiple applications such as understanding of cooking environment in ovens and heat sink performance in electronic packaging industry. The thermal field within an oven has significant impact on quality of cooked food and reliable predictions are important for robust design and performance evaluation of an oven. The CFD modeling of electric oven involves three-dimensional, unsteady, natural convective flow-thermal field coupled with radiative heat transfer. However, numerical solution of natural convection in enclosures with openings at top and bottom (ovens) can often lead to non-physical solutions such as reverse flow at the top vent, partly a function of initialization and sometimes dependent on boundary conditions. In this paper, development of a physics based robust CFD methodology is discussed. This model has been developed with rigorous experimental support and transient validation of this model with experiments show less than 3% discrepancy for a bake cycle. There is greater challenge in simulating a broil cycle, where the fluid inside the cavity is stably stratified and is also highlighted. A comparative analyses of bake and broil cycle thermal fields inside the oven are also presented.     

Optimisation of tensile membrane structures under uncertain wind loads using PCE and kriging based metamodels

Tensile membrane structures (TMS) are light-weight flexible structures that are designed to span long distances with structural efficiency. The stability of a TMS is jeopardised under heavy wind forces due to its inherent flexibility and inability to carry out-of-plane moment and shear. A stable TMS under uncertain wind loads (without any tearing failure) can only be achieved by a proper choice of the initial prestress. In this work, a double-loop reliability-based design optimisation (RBDO) of TMS under uncertain wind load is proposed. Using a sequential polynomial chaos expansion (PCE) and kriging based metamodel, this RBDO reduces the cost of inner-loop reliability analysis involving an intensive finite element solver. The proposed general approach is applied to the RBDO of two benchmark TMS and its computational efficiency is demonstrated through these case studies. The method developed here is suggested for RBDO of large and complex engineering systems requiring costly numerical solution.     

Invariants for homology classes with application to optimal search and planning problem in robotics

We consider planning problems on Euclidean spaces of the form ?, where $\widetilde{\mathcal{O}}$ is viewed as a collection of obstacles. Such spaces are of frequent occurrence as configuration spaces of robots, where $\widetilde{\mathcal{O}}$ represent either physical obstacles that the robots need to avoid (e.g., walls, other robots, etc.) or illegal states (e.g., all legs off-the-ground). As state-planning is translated to path-planning on a configuration space, we collate equivalent plannings via topologically-equivalent paths. This prompts finding or exploring the different homology classes in such environments and finding representative optimal trajectories in each such class. In this paper we start by considering the general problem of finding a complete set of easily computable homology class invariants for (N???1)-cycles in (?. We achieve this by finding explicit generators of the (N???1) ^st de Rham cohomology group of this punctured Euclidean space, and using their integrals to define cocycles. The action of those dual cocycles on (N???1)-cycles gives the desired complete set of invariants. We illustrate the computation through examples. We then show, for the case when N?=?2, due to the integral approach in our formulation, this complete set of invariants is well-suited for efficient search-based planning of optimal robot trajectories with topological constraints. In particular, we show how to construct an ‘augmented graph’, $\widehat{\mathcal{G}}$ , from an arbitrary graph $\mathcal{G}$ in the configuration space. A graph construction and search algorithm can hence be used to find optimal trajectories in different topological classes. Finally, we extend this approach to computation of invariants in spaces derived from (?by collapsing a subspace, thereby permitting application to a wider class of non-Euclidean ambient spaces.     

An adaptive differential evolution algorithm with novel mutation and crossover strategies for global numerical optimization

Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this paper, we propose a new mutation strategy, a fitness-induced parent selection scheme for the binomial crossover of DE, and a simple but effective scheme of adapting two of its most important control parameters with an objective of achieving improved performance. The new mutation operator, which we call DE/current-to-gr_best/1, is a variant of the classical DE/current-to-best/1 scheme. It uses the best of a group (whose size is q% of the population size) of randomly selected solutions from current generation to perturb the parent (target) vector, unlike DE/current-to-best/1 that always picks the best vector of the entire population to perturb the target vector. In our modified framework of recombination, a biased parent selection scheme has been incorporated by letting each mutant undergo the usual binomial crossover with one of the p top-ranked individuals from the current population and not with the target vector with the same index as used in all variants of DE. A DE variant obtained by integrating the proposed mutation, crossover, and parameter adaptation strategies with the classical DE framework (developed in 1995) is compared with two classical and four state-of-the-art adaptive DE variants over 25 standard numerical benchmarks taken from the IEEE Congress on Evolutionary Computation 2005 competition and special session on real parameter optimization. Our comparative study indicates that the proposed schemes improve the performance of DE by a large magnitude such that it becomes capable of enjoying statistical superiority over the state-of-the-art DE variants for a wide variety of test problems. Finally, we experimentally demonstrate that, if one or more of our proposed strategies are integrated with existing powerful DE variants such as jDE and JADE, their performances can also be enhanced.     

On the implementation of a copyright protection scheme using digital image watermarking

Multimedia Tools and Applications - In this paper, a spatial domain based digital image watermarking scheme has been developed to serve the purpose of copyright protection for digital images. This...     

Path homotopy invariants and their application to optimal trajectory planning

We consider the problem of optimal path planning in different homotopy classes in a given environment. Though important in robotics applications, path-planning with reasoning about homotopy classes of trajectories has typically focused on subsets of the Euclidean plane in the robotics literature. The problem of finding optimal trajectories in different homotopy classes in more general configuration spaces (or even characterizing the homotopy classes of such trajectories) can be difficult. In this paper we propose automated solutions to this problem in several general classes of configuration spaces by constructing presentations of fundamental groups and giving algorithms for solving the word problem in such groups. We present explicit results that apply to knot and link complements in 3-space, discuss how to extend to cylindrically-deleted coordination spaces of arbitrary dimension, and also present results in the coordination space of robots navigating on an Euclidean plane.     

On-the-fly model reduction for large-scale structural topology optimization using principal components analysis

Structural and Multidisciplinary Optimization - Despite a solid theoretical foundation and straightforward application to structural design problems, 3D topology optimization still suffers from a...     

A simulated weed colony system with subregional differential evolution for multimodal optimization

This article proposes a two-stage hybrid multimodal optimizer based on invasive weed optimization (IWO) and differential evolution (DE) algorithms for locating and preserving multiple optima of a real-parameter functional landscape in a single run. Both IWO and DE have been modified from their original forms to meet the demands of the multimodal problems used in this work. A p-best crossover operation is introduced in the subregional DEs to improve their exploitative behaviour. The performance of the proposed algorithm is compared with a number of state-of-the-art multimodal optimization algorithms over a benchmark suite comprising 21 basic multimodal problems and seven composite multimodal problems. Experimental results suggest that the proposed technique is able to provide better and more consistent performance over the existing well-known multimodal algorithms for the majority of test problems without incurring any serious computational burden.