جستجوی مقالات مرتبط با کلیدواژه « قابلیت اعتماد سازه ها » در نشریات گروه « عمران »

The Hasofer-Lind and Rackwitz-Fiessler (HLRF) algorithm, which is based on the first-order reliability method (FORM), is widely used to estimate failure probability, reliability index, and design point in structural reliability analysis. However, due to the high nonlinearity of the limit state surface, the HLRF algorithm can be unstable. To address this issue, this paper proposes an optimization method to locate and estimate the design point in the standard normal space and calculate the corresponding failure probability. The reliability problem is solved using sequential least squares programming (SLSQP) to improve accuracy, robustness, and efficiency. SLSQP replaces the quadratic programming problem with a linear least-squares problem, using a stable LDL factorization of the Hessian of the Lagrangian equation. The initial optimization problem is converted into a minimum distance optimization problem with a lower bound constraint. To eliminate linearization errors, the probability expectation method with rotation directions space is employed. The proposed algorithm is demonstrated in several benchmark numerical examples with both explicit and implicit limit state functions. Its fast convergence rate is a notable feature of the proposed algorithm, which enhances its competitiveness in structural reliability analysis.

In structural engineering, it is vital to design structures by providing pre-defined performance objectives economically. Reliability-based design optimization (RBDO) is looking for the best balance between safety and cost, by considering uncertainties in structural parameters and loading conditions. In recent decades, several methods have been used to solve RBDO problem. However, most of these methods suffer from high computational cost of solving the problem as a big challenge.In this paper, weighted simulation method, one of the newest and most effective methods for simulation-based reliability assessment methods, has been used for reliability analysis and evaluation of probabilistic constraints. The advantages of this method are a significant reduction in the computational cost and the proper accuracy of the final results.For minimizing the objective function, which is the weight of structure in this paper, Firefly algorithm (FA) is utilized. The FA is a stochastic metaheuristic approach based on the idealized behavior of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in way that it is associated with the objective function to be minimized. The numerical example results indicate that using the proposed method leads to the optimum design solutions better than other methods in the literature without violating reliability constraints.

The failure probability of structures are rather small and therefore calculation of structural reliability generally has a high computational cost. In order to reduce computational costs, this articles proposes a hybrid approach based on combination of the least squares support vector regression and two advanced Monte Carlo importance sampling and Latin hypercube sampling. Two frames and one truss example are used to evaluate the performance of the proposed algorithm. Results demonstrate that proposed method provides an accurate estimation of failure probability and that the computational costs are lower than those of other methods

Estimation of the first-order reliability method (FORM) for computation of structural failure probability is possible by using mathematical optimization methods. Computational time and global convergence of various optimization methods are criteria for evaluating an appropriate optimization method in the reliability analysis. In this paper, the Nonlinear Conjugate Gradient (NCG) methods have been established for determination of the structural reliability index for the first time. Seven NCG methods have been proposed based on appropriate formulation of the reliability analysis for calculation of the reliability index of structures. The ability and efficiency of these methods are checked in several examples. The convergence and CPU run-times of examples are compared together. The results illustrated that the NCG methods successfully are applied for computation of the reliability index and these methods have suitable efficiency and convergence for estimation of the failure probability of structures. In the basis of problem property has been obtained irregular convergence and run-times of various NCG methods.