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The existing approach in aircraft wing design optimizes the structure for strength and buckling design criteria followed by a flutter stability check, which leads to design that may not be optimal. This study proposes the flutter stability as an integral of weight optimization by a two-step procedure. Step 1 comprises series of flutter and static analyses of finite element (FE) models with different weapon configurations and aerodynamic loads, which give limiting values of wing tip deflection and wing twist as flutter constraints. Step 2 focuses on weight optimization of the laminate for strength and stiffness design parameters along with the flutter constraints. The algorithm minimizes structural weight by ply drop, which is based on evaluation of the fitness value of laminates generated by a stochastic operator. The ply drop design algorithm is applied to optimize the FE model of a fourth-generation fighter aircraft wing box with three representative aerodynamic loads and three weapon configurations. The application evolved optimal laminate with seamless and symmetric plies, which has 35% lesser weight compared with the initial model having quasi-isotropic laminates for given strength and flutter stability design requirement. The application of genetic algorithm (GA) to get an initial laminate instead of quasi-isotropic laminates further improved the design by 2.5% weight reduction.

The objective of VRNPR is to extract vehicle license plate information from number plate of vehicles. As the traffic control and vehicle proprietor recognizable proof is a significant issue in every country, it is important to develop such a device that automatically detects those vehicle owners who violates traffic rules and drives fast [1]. There are many VRNPR systems are present but there is challenging factor like accuracy of extraction, speed of vehicles, lightening condition, quality of images [2]. In this paper, different methods of VRNPR and emerging technologies are used to get accurate result. The important work is the detection and recognition of the number plate which is accomplished by the Convolution Neural Network (CNN). Reason to choose CNN is the high accuracy of around 90% even with relatively small training size [4]. We categorize many VRNPR techniques as per their features they used in each stage and compare them in terms of their advantages and disadvantages, accuracy and processing speed.

The ply-drop (PD) is termination of specific plies at rib-axis for getting tapered laminates. The present optimization study aims to achieve minimum weight tapered wing panels laminates by PD followed by ply-migrations (PM). The PM are required for ply-continuity (blending) and achieving smooth external aerodynamic surface . A genetic-algorithm mutation operator and fitness based search algorithm is developed in the present study for the optimization. The laminate weight minimization has been achieved as goal of multi-objective optimization (MOO), by utilizing excess design margins of Tsai-Wu first ply failure-index (FI) and wing tip lateral deflection . The finite-element (FE) model of laminate is a set of discrete laminates (chromosomes) between ribs with continuity by virtue of ply-orientations . To select best fit laminate, ply orientations were randomly selected and perturbed for thickness during optimization. The fitness function for evaluating chromosomes is a composite function of multi-objective design requirements and design constraints. The algorithm submits orientation/thickness combinations to ABAQUS/CAE by python-script for function evaluation. The application of algorithm over an initially assumed quasi-isotropic laminate of uniform thickness showed 57% weight reduction for a fighter aircraft’s wing panel. The optimization process is automated making PD practically viable in the design process itself.

The present study aims to minimize the weight of multi-laminate aerospace structures by a classical Genetic Algorithm (GA) interfaced with a CAE solver. The structural weight minimization is a multi-objective optimization problem subjected to fulfilling of strength and stiffness design requirements as well. The desired fitness function connects the multi-objective design requirements to form a single-objective function by using carefully chosen scaling factors and a weight vector to get a near optimal solution. The scaling factors normalize and the weight vector prioritizes the objective functions. The weight vector selection was based on a posteriori articulation, after obtaining a series of Pareto fronts by 3D hull plot of strength, stiffness and assembly weight data points. During the optimization, the algorithm does an intelligent laminate selection based on static strength and alters the ply orientations and thickness of laminae for faster convergence. The study further brings out the influence of mutation percentage on convergence. The optimization procedure on a transport aircraft wing torsion box has showed 29% weight reduction compared to an initial quasi-isotropic laminated structure and 54% with respect to the metallic structure.

For the past six years, we have been benefiting from the discovery by Tsai and Melo (2014) that the trace of the plane stress stiffness matrix ( tr ( Q ) ) of an orthotropic composite is a fundamental and powerful scaling property of laminated composite materials. Algebraically, tr ( Q ) turns out to be a measure of the summation of the moduli of the material. It is, therefore, a material property. Additionally, since tr ( Q ) is an invariant of the stiffness tensor Q , independently of the coordinate system, the number of layers, layup sequence and loading condition (in-plane or flexural) in a laminate, if the material system remains the same, tr ( Q ) = tr ( A ∗ ) = tr ( D ∗ ) is still the same. Therefore, tr ( Q ) is the total stiffness that one can work with making it one of the most powerful and fundamental concepts discovered in the theory of composites recently. By reducing the number of variables, this concept shall simplify the design, analysis and optimization of composite laminates, thus enabling lighter, stronger and better parts. The reduced number of variables shall result in reducing the number and type of tests required for characterization of composite laminates, thus reducing bureaucratic certification burden. These effects shall enable a new era in the progress of composites in the future. For the above-mentioned reasons, it is proposed here to call this fundamental property, tr ( Q ) , as Tsai’s Modulus.

The aerospace industry is on a perpetual drive to optimize structures with developments in modeling and analysis capabilities. The traditionally used laminates with 0 ° , 90 ° , ± 45 ° orientations are called Legacy QUAD Laminates (LQL). The recent discovery of Trace of an orthotropic stress tensor A allows reduction of design variables by the replacement of LQL with equivalent stiffness DD 1 (double-double) laminate having self-repeating orientations in a set of ± ϕ / ± ψ . The optimized LQL structures are with mid-plane symmetry, excessive ply-migrations, and variability in ply-orientations, which make the manufacturing process cumbersome. On the other hand, DD-laminates are simplified, thinner and free from mid-plane symmetry, thus enable ten-fold reduction in production resources. The present study, an artificial intelligent (AI) genetic-algorithm based stochastic optimizer replaces LQL with DD-laminates, which follows DD-drop design for mass optimization. The optimization algorithm works with unit-circle failure, buckling mode, and wing-tip deflection design criteria and derives optimal-wing with lowest mass, well suited for design requirements in multiple design load-case. The application of algorithm shows 68–70% mass reduction to an initial full-length ply wing-box model of LQL. The minimization of ply-migrations by D/DD-drop optimization yields structures with better resistance for delamination and well suited for automated production.

This work proposes an Hilbert Huang transform based protection technique for DSTATCOM compensated three phase transmission line. The proposed technique employs three steps. The first step makes the inequity between faults and healthy conditions. The second step identifies the fault section. If a fault is detected in its section then the third stage is triggered which classifies the faulty phase. Hilbert Huang transform has been used to capture the fault information contained in the three phase fault current signals. The three phase current signals recorded at only one end of the line are given to Hilbert Huang transform, which aspires at fault detection, fault section identification and faulty phase classification. The simulation results demonstrate that all types of faults, its section and faulty phase can be perfectly identified. The proposed technique is adaptive to the variation of fault type, fault inception time, fault location, fault resistance, ground resistance and voltage source parameters.

A redesign of canard control-surface of an advanced all-metallic fighter aircraft was carried out by using carbon fibre composite (CFC) for ribs and panels. In this study ply-orientations of CFC structure are optimized using a Genetic-Algorithm (GA) with an objective function to have minimum failure index (FI) according to Tsai-Wu failure criterion. The redesigned CFC structure was sufficiently strong to withstand aerodynamic loads from stress and deflection points of view. Now, in the present work CFC canard structure has been studied for its buckling strength in comparison to existing metallic design. In this study, the existing metallic design was found to be weak in buckling. Upon a detailed investigation, it was revealed that there are reported failures in the vicinity of zones where initial buckling modes are excited as predicted by the finite element based buckling analysis. In view of buckling failures, the redesigned CFC structure is sufficiently reinforced with stringers at specific locations. After providing reinforcements against buckling, the twist and the camber variations of the airfoil are checked and compared with existing structure data. Finally, the modal analysis has been carried out to compare the variation in excitation frequency due to material change. The CFC structure thus redesigned is safe from buckling and aerodynamic aspects as well.

The minimization of weight and maximization of payload is an ever challenging design procedure for air vehicles. The present study has been carried out with an objective to redesign control surface of an advanced all-metallic fighter aircraft. In this study, the structure made up of high strength aluminum, titanium and ferrous alloys has been attempted to replace by carbon fiber composite (CFC) skin, ribs and stiffeners. This study presents an approach towards development of a methodology for optimization of first-ply failure index (FI) in unidirectional fibrous laminates using Genetic-Algorithms (GA) under quasi-static loading. The GAs, by the application of its operators like reproduction, cross-over, mutation and elitist strategy, optimize the ply-orientations in laminates so as to have minimum FI of Tsai-Wu first-ply failure criterion. The GA optimization procedure has been implemented in MATLAB and interfaced with commercial software ABAQUS using python scripting. FI calculations have been carried out in ABAQUS with user material subroutine (UMAT). The GA's application gave reasonably well-optimized ply-orientations combination at a faster convergence rate. However, the final optimized sequence of ply-orientations is obtained by tweaking the sequences given by GA's based on industrial practices and experience, whenever needed. The present study of conversion of an all metallic structure to partial CFC structure has led to 12% of weight reduction. Therefore, the approach proposed here motivates designer to use CFC with a confidence.

In the UDSM era, crosstalk is an area of considerable concern for designers, as it can have a considerable impact on the yield, both in terms of functionality and operating frequency. Methods of crosstalk analysis are pessimistic in nature and the effort is ongoing to come up with techniques that make the analysis as realistic as possible. Using information from timing analysis is one such technique where we use data about overlap in switching among nets to identify those that can potentially switch together. Existing techniques tend to look at the set of a victim and associated aggressor nets in isolation, and select a subset of aggressors based on the absolute timing windows of these nets, thus ignoring the information associated with the fanin of these nets. In reality, however, some of these nets may never switch together because the reconvergence of those nets has not being factored in. Ignoring this correlation can cause false failures being flagged, leading to increased design cycles and conservatism in the design. We propose a technique where the correlation due to reconvergence can be captured in terms of relative switching windows. We apply this technique to real designs and show that this leads to more realistic analysis for crosstalk, and that we can see a reduction in the number of violations reported. We also analyze the effective of the method statistically.