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...