Sharif Digital Repository

A model-based algorithm is proposed and tested using the simulator and operation data of a plastic pipeline prototype to locate multiple non-simultaneous leaks in the pipeline. A combination of an extended Kalman filter and obtained relations from the steady state response is used in order to tackle the problem of multi-leak localization. To achieve the mentioned relations, a real pipe with two leaks is equated to a virtual pipe with a single virtual equivalent leak  

This paper presents artificial neural network (ANN) meta-models for expensive continuous simulation optimization (SO) with stochastic constraints. These meta-models are used within a sequential experimental design to approximate the objective function and the stochastic constraints. To capture the non-linear nature of the ANN, the SO problem is iteratively approximated via non-linear programming problems whose (near) optimal solutions obtain estimates of the global optima. Following the optimization step, a cutting plane-relaxation scheme is invoked to drop uninformative estimates of the global optima from the experimental design. This approximation is iterated until a terminating condition... 

This paper presents a novel model-based algorithm which is able to detect and isolate major faults assigned to the gas exchange path of a gasoline engine both in the intake and exhaust sides. The diagnostics system is developed for detection and isolation of these faults: air leakage fault between the compressor and the air throttle, exhaust manifold pressure sensor fault, wastegate stuck-closed fault and wastegate stuck-open fault. Sliding mode observers (SMOs) are the core detection algorithms utilized in this work. A first order SMO is designed to estimate the turbocharger rotational dynamics. The wastegate displacement dynamics coupled to the exhaust manifold pressure dynamics is... 

In this article, a new algorithm for rather expensive simulation problems is presented, which consists of two phases. In the first phase, as a model-based algorithm, the simulation output is used directly in the optimization stage. In the second phase, the simulation model is replaced by a valid metamodel. In addition, a new optimization algorithm is presented. To evaluate the performance of the proposed algorithm, it is applied to the (s,S) inventory problem as well as to five test functions. Numerical results show that the proposed algorithm leads to better solutions with less computational time than the corresponding metamodel-based algorithm. © 2017 Taylor & Francis Group, LLC