Sharif Digital Repository

Derivation of the probability density evolution provides invaluable insight into the behavior of many stochastic systems and their performance. However, for most real-time applications, numerical determination of the probability density evolution is a formidable task. The latter is due to the required temporal and spatial discretization schemes that render most computational solutions prohibitive and impractical. In this respect, the development of an efficient computational surrogate model is of paramount importance. Recent studies on the physics-constrained networks show that a suitable surrogate can be achieved by encoding the physical insight into a deep neural network. To this aim, the... 

Many modern industrialized systems such as aircrafts, rotating turbines, satellite booms, etc. cannot perform their desired tasks accurately if their uninhibited structural vibrations are not controlled properly. Structural health monitoring and online reliability calculations are emerging new means to handle system imposed uncertainties. As stochastic forcing are unavoidable, in most engineering systems, it is often needed to take them into the account for the control design process. In this research, smart material technology is utilized for structural health monitoring and control in order to keep the system in a reliable performance range. In this regard, a reliability-based cost... 

Reliability evaluation is a key factor in serviceability and safety analysis of air vehicles. Structural health monitoring methods have grown to a degree of maturity in many industries. However, there is a challenging interest to tie in SHM with reliability assessment. In this respect, consideration of stochastic structural dynamics with SHM data and random loadings opens a new chapter in failure prevention. The current study focuses on the stochastic behavior of structures as a way to relate SHM data with reliability. In this respect, uncertain factors such as atmospheric turbulence, structural parameters, and sensor outputs are considered in the process of reliability assessment. Firstly,... 

The utility of probability density evolution method for reliability-based active vibration control of a cantilevered flexible beam is experimentally investigated. In this respect, an optimal linear quadratic regulator (LQR) is utilized together with an observer to design an online full-state feedback controller. In order to design a well-performing controller and to simulate the controller performance, a system model is obtained via identification techniques. Reliability tests are consequently performed to verify the effectiveness of the presented reliability assessment method as a foundation for reliability-based control. Subsequently, a hybrid metaheuristic optimization scheme of... 

Reliability evaluations play a significant role in engineering applications to ensure the serviceability and safety of advanced structures such as those made of composites. Here, a dynamic reliability evaluation analysis based on the probability density evolution Method (PDEM) has been adapted to assess the reliability of composite structures under uncertainties within the material properties and the external loadings. A Back-Propagation Neural Network approach is employed to identify the system's nonlinear structural response, which is often the case under large deformations. To exemplify, a split Hopkinson pressure bar system was employed to mimic the mechanical behavior of a... 

Reliability evaluations play a significant role in engineering applications to ensure the serviceability and safety of advanced structures such as those made of composites. Here, a dynamic reliability evaluation analysis based on the probability density evolution Method (PDEM) has been adapted to assess the reliability of composite structures under uncertainties within the material properties and the external loadings. A Back-Propagation Neural Network approach is employed to identify the system's nonlinear structural response, which is often the case under large deformations. To exemplify, a split Hopkinson pressure bar system was employed to mimic the mechanical behavior of a... 

Reliability evaluations play a significant role in engineering applications to ensure the serviceability and safety of advanced structures such as those made of composites. Here, a dynamic reliability evaluation analysis based on the probability density evolution Method (PDEM) has been adapted to assess the reliability of composite structures under uncertainties within the material properties and the external loadings. A Back-Propagation Neural Network approach is employed to identify the system's nonlinear structural response, which is often the case under large deformations. To exemplify, a split Hopkinson pressure bar system was employed to mimic the mechanical behavior of a...