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New technique is proposed for detection of nonlinearity in the structures.New indices for detection and also the level (severity) of nonlinearity are proposed.Validated with carefully chosen numerical and experimental investigations.An extended version is proposed for detection of nonlinearity using single sensor data. Most of the practical engineering structures exhibit a certain degree of nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. In this paper, we present a new technique based on null subspace analysis to detect the presence of nonlinearity and estimate the degree of nonlinearity in structures using ambient vibration data. Effectiveness of the proposed approach is demonstrated using carefully designed numerical examples and also using the experimental data. Extended version of the technique is presented to detect the nonlinearity using a single sensor data.

In this paper, a hybrid shuffled frog-leaping algorithm (SFLA) is presented for solving multi-objective optimal design of laminate composite structures. A customized neighborhood search algorithm, an adaptive search factor and a crossover operator are suitably incorporated in the proposed algorithm to improve the convergence characteristics apart from features like Pareto dominance, density estimation, and an external archive to store the non-dominated solutions to handle multiple objectives. The performance of the proposed algorithm is demonstrated by solving laminate composite plate, shell and stiffened shell (isogrid) problems. Further, superiority of the proposed algorithm is demonstrated by comparing with four popular meta-heuristic algorithms.

This paper presents a damage detection technique combining proper orthogonal decomposition (POD) with self-adaptive differential evolution algorithm for structural health monitoring considering environmental variability and measurement noises. The damage detection methodology consists of three stages. Identification of the exact time instant of damage and exact spatial location of damage using proper orthogonal modes constitutes the first two stages. The damage severity assessment is the third stage and is formulated as a constrained optimisation problem, solved using newly proposed self-adaptive differential evolution algorithm. Numerical simulation studies indicate that the proposed method is robust and can be used effectively in SHM applications.

Majority of the mesh-partitioning algorithms attempt to optimise the interprocessor communications, while balancing the computational load among the processors. However, it is desirable to simultaneously optimise the submesh aspect ratios in order to significantly improve the convergence characteristics of the domain decomposition based Preconditioned-conjugate-gradient algorithms, being used extensively in the state-of-the-art parallel finite element codes. Keeping this in view, a new distributed multi-objective mesh-partitioning algorithm using evolutionary computing techniques is proposed in this paper. Effectiveness of the proposed distributed mesh-partitioning algorithm is demonstrated by solving several unstructured meshes of practical-engineering problems and also benchmark problems.

This paper presents a multi-objective fuzzy logic controller (PSO-FLC) for active vibration control of seismically exited buildings by combining a new self configurable multi-objective PSO (particle swarm optimisation) algorithm with fuzzy logic controller. The rule base of the proposed PSO-FLC is tuned for optimal control performance by simultaneously optimizing displacement, drift ratio, acceleration and average control force. In addition, the proposed PSO-FLC algorithm also optimises the number as well as the optimal locations of the actuators. Six and 10 storey framed structures subjected to seismic excitations are considered as numerical examples to demonstrate the superior performance of the PSO-FLC algorithm over other control algorithms.

This paper presents a hybrid meta-heuristic algorithm called multiple start guided neighbourhood search (MSGNS) algorithm for combinatorial optimisation which combines the good features of popular guided local search algorithms like simulated annealing and tabu search. It has been organized as a multiple start algorithm to maintain a good balance between intensification and diversification. The proposed hybrid meta-heuristic algorithm has been employed to solve optimal stacking sequence design problem of laminate composite structures. First, the algorithm has been employed to solve the problem of optimal stacking sequence of a composite plate for which the results of various algorithms are available in the literature. This study is basically to validate and also to demonstrate the effectiveness of the proposed algorithm over several existing meta-heuristic algorithms. Later, a practical design example of fiber-reinforced composite cylindrical skirt of solid rocket motor of aerospace vehicle is investigated. A skirt is a potential element for weight reduction in rocket motors as it leads to reduction of the total weight of solid rocket motor. Due to its significance for solid rocket motors, it is proposed to optimise the weight as well as cost of the fiber-reinforced composite cylindrical skirt subjected to a buckling strength constraint and an overstressing strength constraint under aerodynamic torque and axial thrust. This is achieved by arriving at an optimal stacking sequence for the cylinder satisfying all the design constraints and also by employing multiple composite materials. Classical laminate theory combining with elastic stability theory of thin shells is used to arrive at buckling strength and overstressing strength of the fiber-reinforced composite cylindrical skirt. The Tsai-Wu failure criterion is employed to assess the first ply failure. Buckling strength and failure strength of the cylindrical skirt is described by using buckling load factor and overstressing load level factor. Numerical simulations carried out in this paper clearly demonstrate the superiority of the proposed MSGNS algorithm over the popularly used combinatorial algorithms like genetic algorithm and simulated annealing.

With the increased popularity of parallel and vector processors, much research has recently been devoted to the development of efficient algorithms for finite element analysis which exploit the capabilities of these new machines. This paper presents an approach for concurrent finite element analysis employing a ‘multi-frontal scheme’, a concurrent version of the popular frontal solver. The frontal solver coupled with mesh decomposition is well suited for implementation on parallel processors with ease of algorithmic portability across different classes of machines. Unlike the well-known substructure based concurrent approaches, the strategy proposed in this paper does not require the formation of the complete global stiffness matrix of the assigned submesh. Hence, this can be applied more efficiently for very large and complex structures. This multi-frontal based finite element algorithm has been implemented on Magnum IV, a shared memory parallel processing platform. A plate bending problem is taken as a numerical example. The numerical studies in this paper to study the performance of the concurrent code indicate that the proposed method is highly adaptive for concurrent processing.

Several concurrent algorithms for finite element analysis are available at present. Most research effort has been directed towards the development of concurrent algorithms (software) that will run as efficiently as possible on a particular hardware configuration. However, an important issue such as portability of algorithms across several parallel architectures has unfortunately not been given enough thought. In this paper, the development and implementation of a package called CONFESS (CONcurrent Finite Element Static analysis of Structures) is described. This concurrent finite element package is developed keeping software (or algorithmic) portability across different parallel architectures as the main objective. The basic strategy in this approach involves dividing the finite element mesh into a number of submeshes, solving all the submeshes concurrently by all the available processors. The processors all need to cooperate for a trivial amount of computation (interface nodal solution). Algorithmic details of the software package developed and issues related to portability are presented.