Nowadays, the use of smart materials in structures is a major concern to structural engineers. The act of benefiting from numerous advantages of these materials is the main objective of researches and studies focused on seismic and structural engineering. In the present study, in addition to the development of finite element models of several steel frames using ABAQUS software, the effect of shape memory alloys (SMAs) on superelastic behavior and the various types of eccentric braces will be checked. Moreover, it was observed that the use of SMAs within various types of bracing systems of steel frames leads to a decrease in the reduction factor of the frames. Also, the eccentric bracing in which SMAs are utilized in the middle of bracing led to the highest effect on reduction of lateral drift of the frames and decrease of reduction factor. The obtained results indicated that the application of smart materials led to increasing of strain energy and base shear of the first plastic hinge, which is followed by a decrease in the reduction factor of the frame.
In this paper, several analytical models are presented for the optimal design of a trapezoidal composite channel cross-section. The objective function is the cost function per unit length of the channel, which includes the excavation and lining costs. To define the system, design variables including channel depth, channel width, side slopes, freeboard, and roughness coefficients were used. The constraints include Manning’s equation, flow velocity, Froude number, and water surface width. The Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm was used to solve the optimization problem. The results are presented in three parts; in the first part, the optimal values of the design variables and the objective function are presented in different discharges. In the second part, the relationship between cost and design variables in different discharges is presented in the form of conceptual and analytical models and mathematical functions. Finally, in the third part, the changes in the design variables and cost function are presented as a graph based on the discharge variations. Results indicate that the cost increases with increasing water depth, left side slope, equivalent roughness coefficient, and freeboard.
This research examines the probabilistic safety assessment of the historic BISTOON arch bridge. Probabilistic analysis based on the Load-Resistance model was performed. The evaluation of implicit functions of load and resistance was performed by the finite element method, and the Monte-Carlo approach was used for experiment simulation. The sampling method used was Latin Hypercube. Four random variables were considered including modulus of elasticity of brick and in filled materials and the specific mass of brick and infilled materials. The normal distribution was used to express the statistical properties of the random variables. The coefficient of variation was defined as 10%. Linear behavior was assumed for the bridge materials. Three output parameters of maximum bridge displacement, maximum tensile stress, and minimum compressive stress were assigned as structural limit states. A sensitivity analysis for probabilistic analysis was performed using the Spearman ranking method. The results showed that the sensitivity of output parameters to infilled density changes is high. The results also indicated that the system probability of failure is equal to rhofsystem=1,55x10-3. The bridge safety index value obtained is betat=2.96, which is lower than the recommended target safety index. The required safety parameters for the bridge have not been met and the bridge is at the risk of failure.
An elaborate safety assessment of the Pine Flat (PF) concrete gravity dam (CGD) has been conducted in this paper. Structural analysis was performed by taking into account the uncertainties in the physical and mechanical properties of the dam body materials and the reservoir water level. The coefficient of variation of 5 and 10 percent and the Gaussian distribution (GAUS) are assigned to random variables (RVs). Sensitivity analysis (SA) of the RVs is done, and important parameters introduced. SA is done to identify the most influential RVs on the structural response. Also, the modulus of elasticity of concrete is the most effective parameter in response to horizontal deformation of the dam crest. The concrete density and US hydrostatic pressure height are the most effective parameters, and the Poisson's ratio is the insignificant parameter on the dam response. To be confident in the safety of the dam body under usual loading, including the dam weight and the upstream (US) hydrostatic pressure, the reliability index (RI) has been obtained by Monte Carlo simulation. The RI for the coefficients of variation of 5 and 10 percent were obtained at 4.38 and 2.47, respectively. If the dispersion of RVs is high, then the dam will be at risk of failure.
The safety assessment of the Pacoima arch dam is investigated in this paper. A Load – Resistance (L-R) method was used to ensure that the dam is safe or if it is at risk of failure. The "probabilistic design system" ANSYS finite element software was used to calculate the probability of failure. The Monte Carlo (MC) method with 50,000 iterations utilized for simulation and the Latin Hypercube method were used for Sampling. Input random variables with normal distribution and coefficient of variation of 15% due to uncertainties were considered and the six random variables used are the concrete modulus of elasticity, Poisson's ratio of concrete, concrete mass, up-stream normal water level of the reservoir, and the allowable tensile and compressive strength of the concrete. Linear elastic behavior was assumed for the constitutive law of concrete material and if the stress exceeds the allowable stress of the concrete this is considered as a failure limit state. The maximum and minimum principal stresses were considered as the output parameter. Dam body safety was investigated only under self-weight and upstream hydrostatic pressure at the normal water level [...]
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