This study develops a neural network system to monitor the safety of a bridge structure. A truck of constant mass is driven at constant speed through the target bridge. Then, the maximal and minimal values of the bridge elongations are processed by a monitoring system to evaluate the current condition of the bridge. The monitoring system is composed of parallel backpropagation neural networks. Each neural network monitors a part of the bridge. The neural networks are trained using simulation data. The numerical example shows that the monitoring system is effective in the damage detection of the bridge.

The A36 structural steel shows significant Baushinger effect under cyclic loading. Present paper modifies the anisotropic endochronic model to describe the behaviors of the A36 structural steel subjected to cyclic loading. The deformation induced anisotropy has been considered to modify the definition of the intrinsic time. Also, the different hardening functions are used with respect to the mechanical behavior under loading and unloading condition, respectively. Then, the presented constitutive equations are used to describe the mechanical behaviors of the A36 structural steel under different cyclic strain paths. The theoretical results are compared with the experimental data. The test investigated includes several different cyclic uniaxial and axial-torsional loading experiments from Hong and his co-workers. It is shown that the present model is capable of describing the anisotropic behaviors of A36 structural steel well.

A technique for inverting residual stress based on a theory of acoustoelasticity is presented. A general incremental constitutive relation is first derived for a pre-stressed material subjected to an additional infinitesimal elastic deformation. The theory is then employed on using ultrasonic means to evaluate residual stresses of residually stressed materials. The residual stresses are assumed to be homogeneous in materials as usual. The only major assumption in this formulation is that the additional deformations caused by ultrasonic evaluating process are infinitesimal and elastic. No assumption on the origin of residual stresses is needed, nor the assumption on the possible existence of “natural state” of the materials. Successful inversion of residual stresses are demonstrated through a preliminary numerical experiment.

A three-dimensional Navior-Stokes analyzer based on control volume method is developed to simulate the complex flow field within a turbomachinery. With VKI-CT2 turbine blade as the test model, numerical results are compared with experimented data and shows the existence of separation-transition bubble and the interaction of shock with turbulent boundary layer flow. The governing Navier-Stokes equations are solved by an improved numerical method that uses an upwind flux-difference split scheme for spatial descretization and an explicit optimally smoothing multi-stage scheme for time integration. Turbulent stresses are approximated by modifying Baldwin-Lomax algebraic, k-ε, R-k-ε and RNG k-ε turbulence models. According to the results of this research, this analyzer can indeed effectively modulate and simulate the aerodynamic characteristic of the transonic turbine rotor near the endwall.