Sharif Digital Repository

The building sector is a major source of energy consumption and greenhouse gas emissions in urban regions. Several studies have explored energy consumption prediction, and the value of the knowledge extracted is directly related to the quality of the data used. The massive growth in the scale of data affects data quality and poses a challenge to traditional data mining methods, as these methods have difficulties coping with such large amounts of data. Expanded algorithms need to be utilized to improve prediction performance considering the ever-increasing large data sets. In this paper, a preprocessing method to remove noisy features is coupled with predication methods to improve the... 

The main objective of this work is minimizing the cost of electricity of solid oxide fuel cell stacks by decelerating degradation mechanisms rate in long term operation for stationary power generation applications. The degradation mechanisms in solid oxide fuel cells are caused by microstructural changes, reactions between lanthanum strontium manganite and electrolyte, poisoning by chromium, carburization on nickel particles, formation of nickel sulfide, nickel coarsening, nickel oxidation, loss of conductivity and crack formation in the electrolyte. The rate of degradation mechanisms depends on the cell operating conditions (cell voltage and fuel utilization). In this study, the degradation... 

In the present study a comprehensive thermodynamic model and degradation based optimization framework for energy management of anode supported solid oxide fuel cell (SOFC) stacks are carried out. The optimization framework determines optimum operating conditions to maximize system productivity (energy generation over system lifetime) considering degradation mechanisms. The main degradation mechanisms in anode supported SOFCs are nickel coarsening and oxidation. In this study, the optimum operating conditions regarding these degradation mechanisms to achieve maximum productivity at different target lifetimes are derived. The results show that target lifetime has a significant impact on system... 

In this paper a scheduling optimization framework is developed to enhance power plants operational decision making process. The proposed framework optimizes plant schedule including operating conditions and maintenance intervals simultaneously and on an hourly basis. In a long term operation plant performance deteriorates due to components aging. This study employs equivalent operating hour (EOH) approach to describe components aging impact on the plant performance deterioration and consequently plant long term profit. Modeling of components aging increases system simulation accuracy in long term operation and the optimum decision variables would be more reliable and realistic. Validity and... 

System health management based on condition monitoring is of great value and significance for improving system performance and reliability. As more data from condition monitoring is obtained, the efficiency of system health monitoring improves. However, increasing the amount of data by installing new sensors on system components is restricted by a variety of factors such as budget, weight and space allowance. Therefore, sensor selection in the most optimal manner in order to achieve maximum valuable information from system is an important issue. In this study, a novel concept is introduced that can be used in sensor combination optimization problems. This concept employs failure modes and... 

Ni-TiN nanocomposite coatings were prepared by using electrochemical deposition in a Watt's bath containing TiN particles to increase the hardness of Ni. The effects of deposition current density, electrolyte agitation speed and the number of particles in the solution on the amount of incorporated particles in the coating process were investigated. The optimum deposition current density of 4 A dm-2 and agitation speed of 450 rpm were obtained. The effect of sodium dodecyl sulphate (SDS) anionic surfactant on the amount of particles in the coatings was investigated. It was observed that the maximum amount of incorporated particles, with a value of 7.5% by volume, was created in the current... 

Central heating system faults affect building energy consumption and indoor thermal comfort significantly. The interdependencies among system components and multiple failure modes present a challenge for system health diagnostics and prognostics. A reliable diagnosis and prognosis can only be ensured when all component conditions are monitored with minimum uncertainty. In this regard, sensors should be selected based on their priority in providing system health information. Currently, most of the research on sensor optimization models optimize sensors position and orientation. However, in this study sensor type is optimized as well. In addition, the proposed method is based on the Bayesian... 

We theoretically study a Kitaev chain with a quasiperiodic potential, where the quasiperiodicity is introduced by a Fibonacci sequence. Based on an analysis of the Majorana zero-energy mode, we find the critical p-wave superconducting pairing potential separating a topological phase and a non-topological phase. The topological phase diagram with respect to Fibonacci potentials follow a self-similar fractal structure characterized by the box-counting dimension, which is an example of the interplay of fractal and topology like the Hofstadter's butterfly in quantum Hall insulators. © 2017 The Physical Society of Japan  

Transferring large models in federated learning (FL) networks is often hindered by clients' limited bandwidth. We propose $ extsf {FedAA}$ , an FL algorithm which achieves fast convergence by exploiting the regularized Anderson acceleration (AA) on the global level. First, we demonstrate that FL can benefit from acceleration methods in numerical analysis. Second, $ extsf {FedAA}$ improves the convergence rate for quadratic losses and improves the empirical performance for smooth and strongly convex objectives, compared to FedAvg, an FL algorithm using gradient descent (GD) local updates. Experimental results demonstrate that employing AA can significantly improve the performance of FedAvg,... 

Natural convection in a porous enclosure in the presence of thermal dispersion is investigated. The Fourier–Galerkin (FG) spectral element method is adapted to solve the coupled equations of Darcy’s flow and heat transfer with a full velocity-dependent dispersion tensor, employing the stream function formulation. A sound implementation of the FG method is developed to obtain accurate solutions within affordable computational costs. In the spectral space, the stream function is expressed analytically in terms of temperature, and the spectral system is solved using temperature as the primary unknown. The FG method is compared to finite element solutions obtained using an in-house code... 

Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

Object-oriented frameworks are widely used to develop new applications. They provide reusable concepts that are instantiated in application code through potentially complex implementation steps such as subclassing, implementing interfaces, and calling framework operations. Unfortunately, many modern frameworks are difficult to use because of their large and complex APIs and frequently incomplete user documentation. To cope with these problems, developers often use existing framework applications as a guide. However, locating concept implementations in those sample applications is typically challenging due to code tangling and scattering. To address this challenge, we introduce the notion of... 

This paper studies the energy-limited performance of multi-relay networks. Taking the properties of the power amplifiers (PAs) into account, we derive closed-form expressions for the optimal power allocation, the outage probability and the throughput in the cases with a sum consumed energy constraint. Moreover, we analyze the diversity and the multiplexing gains of the PA-aware systems. Finally, we investigate the performance of large-scale multi-relay networks and develop efficient multi-relay systems with low cooperation overhead. The numerical and the analytical results show that the inefficiency of the PAs affects the outage probability and the throughput of the multi-relay systems... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

We address the noninvasive temperature estimation from pulse-echo radio frequency signals from standard diagnostic ultrasound imaging equipment. In particular, we investigate the use of a high-resolution spectral estimation method for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach, employing generalized second-order statistics, is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods Seip and Ebbini (1995). Furthermore, temperature estimates from the new algorithm are compared with results from the more commonly used echo shift method described in Simon...