Sharif Digital Repository

This paper deals with vibrational behaviors of blades with cracks which are key components in rotating machines. However, since modelling and analysis of real blade is a complex problem, a simplified cantilever beam with both chordwise (in X-Y plane) and flapwise (in X-Z plane) motion are modeled instead. Finite Element Method (FEM) is used to model beam and to investigate its natural frequencies with a crack. Finally a limit function using modal data is developed and reliability analysis of beam model is performed. © 2017 IEEE  

Making proper decisions in today's complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling (ABM). ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making (DM) aspect to ABM can support the decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In... 

Optimizing highway alignment requires a versatile set of cost functions and an efficient search method to achieve the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. Moreover, because of the infinite number of possible solutions for the problem and the continuous search space, highway alignment optimization is a complex problem. In this study, a customized particle swarm optimization algorithm was used to search for a near-optimal highway alignment, which is a compound of several tangents, consisting of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet... 

In general, decomposition methods can facilitate the process of solving sophisticated and heterogonous problems in the area of software development and engineering. These approaches are assisting to decompose problems based on different disciplines, characteristics and functionalities that is results into increasing the computational efficiency (e.g. parallel processing/computing) and accelerate the software changing process, software modifications and error tracking. Essentially, these approaches contribute to the degree of modularity to decompose a complex problem into different sub-problems and to focus on local objectives. There are different approaches that are used to decompose a... 

Ambient Intelligence is the future of computing where devices predict what users need and help them carry out their everyday life activities easier. To make this prediction possible these environments should be aware of the context. Activity recognition is one of the most complex problems in context-aware environments. In this paper we propose a layered Dynamic Bayesian Network (DBN) to recognize activities in an oral presentation. The layered architecture gives us the opportunity to recognize complex activities using the classification results of sensory data in the first layer regardless of the physical environment. Our model is event-driven meaning the classification takes place only when... 

Soft Computing (SC) is defined as a group of computational techniques that solve complex problems independent of mathematical models. SC techniques including artificial neural networks (ANNs), fuzzy systems (FSs), evolutionary algorithms (EAs), etc., can solve problems that either cannot be solved by the analytical/conventional methods or require a long computation time. Due to their features, SC techniques are nowadays widely used in scientific and industrial researches. SC techniques have also been included in many types of research related to nuclear power plants (NPPs). In this paper, the applications of SC techniques in NPPs, according to published articles, are presented. The... 

Decision on the location of new wells through infill drilling projects is a complex problem that depends on the reservoir rock and fluid properties, well and surface facilities specifications, and economic measures. Conventional approach to address this is a direct optimization that uses the numerical flow simulation. However, this is computationally very extensive. In this study the authors use a hybrid genetic algorithm (HGA) optimization technique based on the genetic algorithm (GA) with helper functions based on the polytope algorithm and the neural network. This hybridization introduces hill-climbing into the stochastic search and makes use of proxies created and calibrated iteratively... 

Decision on the location of new wells through infill drilling projects is a complex problem that depends on the reservoir rock and fluid properties, well and surface facilities specifications, and economic measures. Conventional approach to address this is a direct optimization that uses the numerical flow simulation. However, this is computationally very extensive. In this study the authors use a hybrid genetic algorithm (HGA) optimization technique based on the genetic algorithm (GA) with helper functions based on the polytope algorithm and the neural network. This hybridization introduces hill-climbing into the stochastic search and makes use of proxies created and calibrated iteratively...