Fiber reinforced polymer (FRP) has been proved to be effective to improve the structural strength and ductility for column structures. An experimental study was conducted to investigate the compressive performance of FRP confined glued-laminated timber (GLT) and cross-laminated timber (CLT) columns. A total of 60 column specimens of two dimensions in height using different FRP types, FRP thickness, and laminate types were tested under cyclic axial compression loads. This study focuses on the compressive capacity and ductility of the new FRP composited timber structure. For this purpose, a loading protocol was designed, including a force-dependent pre-load and an amplitude-increasing displacement-dependent cyclic compression load. The results showed that the ultimate compression load of specimens was considerably promoted by the FRP sheets. Wrapping FRP sheets led to an average improvement of 29% and 24% for the FRP confined CLT and GLT specimens, respectively, compared to the initial stiffness of unreinforced specimens. Using the FRP sheets, the energy dissipation capacity of CLT and GLT specimens was increased by 358% and 266%, respectively. In general, GLT specimens had a higher energy dissipation rate compared to the CLT specimens, while CLT specimens showed a better potential for sustained energy consumption if confined with sufficient FRP sheets.

The existing safety analysis methods for the assessment of the aerostatic stability of long-span symmetry cable-stayed bridges have difficulties in meeting the requirements of engineering applications. Based on the finite element method and the inverse reliability theory, an approach for the probabilistic safety analysis of the aerostatic instability of long-span symmetry cable-stayed bridges is proposed here. The probabilistic safety factor of aerostatic instability of long-span symmetry cable-stayed bridges was estimated using the proposed method, with Sutong Bridge as an example. The probabilistic safety factors for the aerostatic instability of Sutong Bridge were calculated using the finite element inverse reliability method, based on the FORM approach. The influences of the mean value and the coefficient of variation of random variables, as well as the iterative step length of finite difference, on the probabilistic safety factors of aerostatic instability of Sutong Bridge were analyzed. The results indicated that it is necessary to consider the uncertainties of random variables in probabilistic safety factor assessments of aerostatic instability in cable-stayed bridges using the proposed method, which could be recommended for the assessment of safety factors involved in the aerostatic instability of long-span symmetry cable-stayed bridges. The randomness of the parameters had an important influence on the probabilistic safety factor of the aerostatic stability of Sutong Bridge. Neglecting the randomness of these parameters may result in instability of the structure.

Reliability theory is the core basis of engineering design, mainly including forward reliability theory and inverse reliability theory. Forward reliability theory is used to obtain the reliability index using the known design parameters, that is, it is a mapping function that translates the design parameters to the reliability index. Inverse reliability theory is used to obtain the design parameters using the known reliability index, that is, it is a mapping function that translates the reliability index to the design parameters. In other words, forward reliability theory and inverse reliability theory together constitute a method of dual mapping, which is the specific application of symmetry theory in the reliability field. In this paper, a new inverse reliability analysis method is proposed, which can satisfy the requirements of the target reliability index while obtaining the design parameters, without additional calculation and verification of reliability. The method simplifies the reliability inverse problem to the problem of the nonlinear equation, which is solved by identifying the design parameters, and finally obtains the design parameters by iterating the reliability index for each design parameter to gradually approach the target reliability index. For high-dimension and complex problems, the Levenberg–Marquardt method is introduced to avoid the problem of sensitivity to initial values and iterative divergence when identifying the design parameters. The implicit limit state function problem is solved by the interactive operation between ANSYS software and MATLAB software using finite element theory. The accuracy of the proposed method in this paper is verified by several numerical examples, the applicability of the implicit limit state function is verified by a single-story frame structure, and the engineering applicability of the proposed method is demonstrated with a bamboo bridge.

Due to the limitations of the bridge deck modeling and wind tunnel installations, the parametric uncertainties of aerostatic displacement-dependent wind loads have become an urgent problem for reliability analysis in bridge engineering. Computational fluid dynamic (CFD) simulations were conducted to investigate the distribution model of aerostatic coefficients. The Monte Carlo simulation (MCS) was used to generate random samples of stream-lined box cross-sections. Among these samples, wind attack angles of −8°–8° were considered, and the sample size of each angle group was set as 30. Then, the statistical properties for the variation and distribution of aerostatic coefficients were discussed. In addition, sub-samples with sizes of 5–20 were randomly sampled from the initial sample group to evaluate the influence of the sample scale. The coefficient of variation (COV) of aerostatic coefficients with respect to geometric uncertainties increased up to 0.217, which occurred at −7° wind attack angle. Lognormal distribution models obtained by hypothesis tests maintained a low deviation for estimating the distribution of aerostatic coefficients. The sample size had a significant effect on quantifying the error between empirical and theoretical distribution models. Simulation method proposed in this paper provides a systematic approach for probabilistic problems involving fluid-structure interaction and parametric uncertainties.