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All-Optical Scalable Multi-stage Interconnection Network for Data Centers
, M.Sc. Thesis Sharif University of Technology ; Koohi, Somayeh (Supervisor)
Abstract
According to the increasing amount of data exchanged among data centers, the need for speeding up and bandwidth and reduced power consumption has been increased. The information show that about 77% of the data is moved into the data centers. On the other hand, 10% of data center’s power consumption is used to data transmission. Improving the interconnection network of data centers can play an important role in reducing power consumption and speeding up. In recent years, optical interconnects have gained attention as a promising solution. Nevertheless, offering an all-optical and efficient architecture is an important issue. In this study, we intend to provide a multi-stage, all-optical...
Adopting Dynamic Topology for Energy Management in Optical Interconnection Networks in Data Centers
, M.Sc. Thesis Sharif University of Technology ; Koohi, Somayeh (Supervisor)
Abstract
Today with the deployment of cloud computing and web applications; We need to have powerful datacenters with provisioning high bandwidth. Current data centers with electronic network interconnects, using excessive power to provisioning requisite bandwidth. Nevertheless, interconnecting networks in data centers isn’t in maximum efficiency and many components of them aren't used efficiently. So it is necessary to use an optical network with dynamic provisioning variable bandwidth and energy management. In this approach, our proposed architecture is designing topology with adopting dynamically for energy management in optical interconnect networks in data centers. To achieve this we can study...
fTemporal green's dunction of an RLC resonator with arbitrary time-varying capacitance using differential transition matrix
, Article Iranian Conference on Electrical Engineering, ICEE ; Issue 2024 , 2024 ; 21647054 (ISSN) ; Mehrany, K ; Memarian, M ; Sharif University of Technology
IEEE
2024
Abstract
Time-varying electromagnetic structures and circuits have gained unprecedented research attention in the past decade enabling new phenomena with important applications. The different scenarios share a common ground, the effect of time-varying resonances. In this paper an analytical time-domain Green's function for a simple RLC circuit with an arbitrary time-varying capacitance is presented. The idea of the proposed method is to substitute the rapidly varying amplitudes of capacitor charge or inductor current with two slowly varying equivalent amplitudes, reminiscing the WKB approach but with time-varying amplitudes. This differential transition matrix method based formalism is general for...
Reciprocity condition in synchronously time-periodic bianisotropic materials
, Article Physical Review B ; Volume 106, Issue 21 , 2022 ; 24699950 (ISSN) ; Memarian, M ; Mehrany, K ; Rejaei, B ; Sharif University of Technology
American Physical Society
2022
Abstract
In this paper, a sufficient reciprocity condition for general time-periodic modulated bianisotropic media is extracted from first principles. Reciprocity of various cases of significant importance, including stationary bianisotropic media, time-varying (TV) isotropic media, TV anisotropic media, and TV bianisotropic media, are investigated using this condition. We prove that synchronous time modulation of stationary bianisotropic yet reciprocal media (chiral, pseudochiral, and achiral) does not lead to nonreciprocity, unless the modulation function breaks time reversal symmetry. This is in contrast to recently published research. The theoretical results are validated using in-house finite...
Virtual reservoir computer using an optical resonator
, Article Optical Materials Express ; Volume 12, Issue 3 , 2022 , Pages 1140-1153 ; 21593930 (ISSN) ; Jabbari, A ; Mehrany, K ; Memarian, M ; Sharif University of Technology
The Optical Society
2022
Abstract
Reservoir computing is a machine learning approach that enables us to use recurrent neural networks without involving the complexity of training algorithms and make hardware implementation possible. We present a novel photonic architecture of a reservoir computer that employs a nonlinear node and a resonator to implement a virtual recurrent neural network. This resonator behaves as an echo generator component that substitutes the delay line in delaybased reservoir computers available in the literature. The virtual neural network formed in our implementation is fundamentally different from the delay-based reservoir computers. Different virtual architectures based on the FSR and the Finesse of...
Novel Optical Implementations of Reservoir Computing with Single or Limited Number of Neurons
, M.Sc. Thesis Sharif University of Technology ; Mehrany, Khashayar (Supervisor) ; Memarian, Mohammad (Supervisor)
Abstract
Artificial neural networks are systems based on the brain’s functionality which in many cases are able to process highly complex computational tasks like speech recognition, image recognition ,and time series prediction. Due to the complexity of training algorithms in recurrent neural networks, reservoir computers have significant importance in machine learning.Due to low power consumption and crosstalk, high bandwidth and high-speed computing in optics, reservoir computing has proceeded to optical implementations. A reservoir computer consists of three layers: the input layer, reservoir, and output layer. A recurrent neural network is usually used as the reservoir in reservoir computers....
Analysis of Electromagnetic Effects in Time-varying Bi-Anisotropic Media
, Ph.D. Dissertation Sharif University of Technology ; Mehrany, Khashayar (Supervisor) ; Memarian, Mohammad (Supervisor)
Abstract
In recent years, the growing research on time-varying linear media has enabled the emergence of novel and versatile wave propagation phenomena that offer significant advantages over conventional static structures. Electromagnetic effects such as non-reciprocity and isolation without the need for magnetic bias field and with optical integration capabilities, frequency conversion without the need for nonlinear elements, and parametric amplification are among the key breakthroughs in this field. These phenomena arise from the interaction of electromagnetic waves with media whose fundamental parameters—namely permittivity, permeability, or electrical conductivity—vary in time. Most existing...
Feasibility Analysis of Backflow Detection in Lobe Blowers in Khuzestan Steel Plant using Condition Monitoring Techniques
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mohammadi, Somayeh (Supervisor)
Abstract
Lobe blowers are positive displacement machines (PDM) that are widely used in various industries. The efficiency of lobe blowers depends on the clearance between fixed and moving parts. If the clearance between the parts increases, backflow occurs, which means that the flow returns from the high-pressure zone of the outlet to the low-pressure zone of the inlet, and this makes the blower not have the initial efficiency and work with a lower capacity than its design. This research is carried out with the aim of checking the feasibility of backflow detection using two condition monitoring methods, including ultrasonic and thermography techniques. The sample of this research includes seven...
Comparison of Vibration and Ultrasonic Signal Performance in Predicting the Remaining Useful Life of Rolling Element Bearings
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mohammadi, Somayeh (Supervisor)
Abstract
The prediction of Remaining Useful Life (RUL) has become a critical tool in enhancing the availability of rotating machinery. By knowing the remaining time before a bearing failure occurs during operation, significant reductions in unplanned production downtimes and associated costs can be achieved. In this study, by analyzing the time signals of vibration and ultrasonic data related to the bearing of a 4.1 MW electromotor from installation to replacement, and by investigating the behavior trends and correlation between extracted features, RMS has been ultimately identified as the health indicator in both vibration and ultrasonic techniques for monitoring the bearing’s condition. First,...
Intelligent Fault Diagnosis of Rolling Bearings under Diverse Operating Conditions with Limited Vibration Data Using Meta-Learning Algorithms
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mohammadi, Somayeh (Supervisor)
Abstract
Rotating machinery is a critical component in many industries, and its failure can lead to process interruptions and significant economic losses. Rolling bearings, as key elements of these machines, account for approximately 45–55% of failures. Therefore, timely detection of bearing faults plays a crucial role in reducing maintenance costs and improving safety. However, achieving timely fault detection is challenging due to weak signals and the presence of noise, which necessitates the use of advanced algorithms with strong diagnostic capabilities. Despite the considerable success of deep learning models in pattern recognition, their application to fault diagnosis of rotating machinery faces...
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mohammadi, Somayeh (Supervisor)
Abstract
Bearings play a critical role in the functionality of rotating equipment across various industries, accounting for approximately 50% of equipment failures due to bearing malfunctions. Accurate life prediction of bearings is essential not only for preventing unexpected breakdowns and subsequent damage but also for minimizing unnecessary replacements of functional bearings, which can lead to increased operational costs. With the rise of artificial intelligence, numerous predictive models have been developed; however, many of these require extensive datasets, which are often unavailable in industrial settings. Data collection is typically irregular, based on the sensitivity of the equipment,...
Identification of Possible Failures in Online Data of Gas Turbines based on Information Fusion using Artificial Intelligence
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mohammadi, Somayeh (Supervisor)
Abstract
Gas turbines' safe operation depends on the monitoring of performance thresholds and equipment limitations. This is accomplished through online data monitoring using sensors, with the collected data processed by monitoring software supplied by turbine manufacturers to extract information on operating conditions. The thresholds are usually set during manufacturing under standard conditions and saved in the control software. As the turbine ages and undergoes maintenance, these thresholds and operating conditions may change, requiring expert analysis to determine safe operating limits. Technological advancements have enabled the processing of operational data to establish patterns and create...
Reliability and Redundancy Analysis at a Methanol Plant in the Khark Petrochemical Complex: Investigation, Modeling, and Improvement
, M.Sc. Thesis Sharif University of Technology ; Mohammadi, Somayeh (Supervisor) ; Saniee Monfared, Mohammad Ali (Supervisor)
Abstract
Today, reliability assessment of production systems is crucial for ensuring continuous production and minimizing operational and maintenance (O&M) costs. One way to assess reliability at the system level is to create a reliability block diagram (RBD) and estimate the failure rates of equipment over their operational periods. This approach has been utilized in this thesis, focusing on assessment of the reliability of various units within the methanol plant at Khark Petrochemical Complex. In this context, understanding the condition of the equipment criticality is essential for constructing the reliability block diagram. The Crespo model and total criticality per risk (CTR) measure have been...
The Investigation of the Effectiveness of Engine Oil Filter Particle Analysis in Enhancing the Efficiency of Diesel Engine Condition Monitoring Programs
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Masoodi, Alireza (Supervisor) ; Mohammadi, Somayeh (Co-Supervisor)
Abstract
Over the years, as machines have been invented, their maintenance and repair have consistently been regarded as critical concerns. Oil analysis techniques are an effective method for monitoring the condition of mechanical equipment. Since filters in these devices continually absorb and remove a significant portion of particles from the lubricant, the selection of appropriate filters is crucial. While filters positively affect machine performance, they can also negatively impact oil condition monitoring. To mitigate this negative effect and improve the predictive accuracy of equipment health monitoring, oil filter analysis was conducted. In this research, analytical ferrography tests were...
Nanoparticle-based optical sensor arrays
, Article Nanoscale ; v. 9 , 2017 , pages 16546 – 16563 ; 2040-3364 ; Bigdeli, Arafeh ; Ghasemi, Forough ; Golmohammadi, Hamed ; Abbasi-Moayed, Samira ; Farahmand Nejad, M. Amin ; Fahimi-Kashani, Nafiseh ; Jafarinejad, Somayeh ; Shahrajabian, Maryam ; Sharif University of Technology
Royal Society of Chemistry
2017
Abstract
As in many other methods that have integrated nanoparticles (NPs), the chemical nose/tongue strategy has also progressed greatly since the entrance of NPs into this field. The fascinating tunable physicochemical properties of NPs have made them powerful candidates for array-based sensing platforms and have enabled the development of real-time, sensitive and portable systems that are able to target complex mixtures of analytes. In particular, the unique optical properties of NPs have a key role in providing promising array-based sensing approaches. This review will describe the main aspects and processes of most common NP-based optical sensor arrays. The fundamental steps in the design of a...