Sharif Digital Repository

There are different flow regimes in multiphase flows through the pipes, which affect the flow structure and other important fluid parameters. Each of these flow regimes are considered to be suitable or not in different industries. So it is needed to provide the situation of suitable flow regimes formation and to prevent the others from development. One of the main parameters affecting the flow regimes development is considered to be the passing flow’s channel section are or the pipe diameter. This project is defined to investigate the effect of changing pipe diameter on the formation of flow regimes in an air-water upward two-phase flow, experimentally. Therefore, a vertical pipe of 6 meters... 

Nowadays, research in the field of software architecture has become an important topic as a key element in software processes. Software Development Methodologies are not excluded. Importance and the need to improve and maintain methods, training new people and producing reasonable documents have highlighted the role of software architecture, especially in the methods that do not good predictions for these cases. In this project a solution would be introduced that we can extract the architecture of a methodology by using in hand techniques and tools. Then we would map the extracted architecture to architectural styles. So in addition of the benefit of using an architecture based design, we... 

Recently, isogeometric methodology has been successfully implemented in one-step inverse analysis of sheet metal stamping processes. However, these models are not capable of analyzing forming processes which require severe deformation and/or several forming stages. This paper presents a multi-step inverse isogeometric methodology to enhance the precision of one-step models in predictions of the initial blank, strain distributions, and drawability of the formed parts. This methodology deals with the minimization of potential energy, deformation theory of plasticity, and considering membrane elements. The presented methodology utilizes the NURBS basis functions to create the final, middle, and... 

Quality of Experience (QoE) indicates the overall quality of one service such as Voice over IP (VoIP) from users' point of view by considering several systems, human, and contextual factors. QoE measurement and prediction are more challenging than Quality of Service (QoS) which is only related to network parameters. There exist various objective and subjective methods for QoE prediction. This research investigates various features affecting QoE by proposing a comprehensive subjective evaluation by employing a large number of users. We show that many unconsidered factors including speaker specifications and signal properties, such as signal-to-noise ratio (SNR), can affect QoE so that the SNR... 

Condition monitoring of machinery is of significant economic importance to mitigate production losses resulting from downtimes. Unforeseen failure of roller element bearings is the most common issue observed in industrial units. However, detecting and tracking the progression of these failures through machine vibration monitoring and predicting the deterioration of these rotating components are viable solutions. Numerous studies have focused on using laboratory accelerated life test data for fault detection and remaining useful life prediction of these components. While online monitoring of all equipment in the industry may not be feasible, and conditions in the field differ from laboratory... 

Intelligent predictive maintenance is recognized as a cornerstone of Industry 4.0, where intelligent software is employed for the early detection of faults and the prevention of unexpected failures. Recent research indicates that the integration of multi-sensor data for fault diagnosis of gearboxes and bearings, using artificial intelligence models, has been successful. However, conventional methods face several challenges. These include an over-reliance on the signal characteristics of a single sensor and the impracticality of applying intelligent learning methods, particularly deep learning, despite their high potential, due to the unavailability of sufficiently large and diverse...