Sharif Digital Repository

To mitigate global warming and fossil fuel shortages a novel oxy-fuel combustion power plant integrated with a power to gas system is proposed. A net-zero emission MATIANT cycle with inherent CO2 capture ability is selected as the power cycle also providing the CO2 and power demand of the power to gas system, which comprises a proton exchange membrane electrolyzer for hydrogen production and a Sabatier reactor for methanation. A techno-economic investigation, a multi-objective optimization, and a sensitivity analysis are carried out. A comprehensive economic method that covers all economic aspects is utilized, and a Sabatier reactor model which considers the possibility of the presence of... 

The usage of conventional fossil fuels has aided fast economic growth while also having negative consequences, such as increased global warming and the destruction of the ecosystem. This paper proposes a novel swarm-based metaheuristic method called Chimp Optimization Algorithm (ChOA) to tackle the environmental, economic dispatch issue and reducing the waste nonrenewable materials. In this regard, two objective functions named fuel cost function and emission cost function are proposed. Unique constrained handling also solves the challenge of multi-objective optimization. Standard IEEE 30 bus with six generators and a 10-unit system are used to demonstrate the usefulness of ChOA. The result... 

The renewed attention paid to rammed earth materials in recent decades is related to their sustainability, high thermo-buffering capacity and relatively low cost. The energy performance of rammed earth materials can be enhanced with stabilization. However, some of thermal enhancement methods have destructive side-effects. In the current study, the effect of three different methods was investigated on thirteen different alternatives of rammed earth materials to improve energy efficiency of buildings. These methods include using phase change materials, cementitious admixtures and external insulators. Thermo-dynamic parameters such as time lag, thermal conductivity and heat flux were measured... 

The vast nationwide COVID-19 vaccination programs are implemented in many countries worldwide. Mass vaccination is causing a rapid increase in infectious and non-infectious vaccine wastes, potentially posing a severe threat if there is no well-organized management plan. This paper develops a mixed-integer mathematical programming model to design a COVID-19 vaccine waste reverse supply chain (CVWRSC) for the first time. The presented problem is based on minimizing the system's total cost and carbon emission. The uncertainty in the tendency rate of vaccination is considered, and a robust optimization approach is used to deal with it, where an interactive fuzzy approach converts the model into... 

So the design and control of an accurate robot for this purpose is very critical for saving the patients. Modification of the model and designing two optimized nonlinear robust controllers for the first time for the parallel manipulator medical robot and cardiopulmonary resuscitation. The main objective of the current study in order to decrease the overshoot and increase the accuracy of the position and convergence speed and robustness to destructive factors affecting the precision of the robot. In this paper firstly, the kinematics and dynamics analysis of a translational parallel manipulator robot is presented and a non-linear model in the presence of uncertainties, disturbances, and... 

The selection of a suitable duty factor (DF) remains a major challenge in respiratory-gated treatments. Therefore, this study aims at presenting a new methodology for fast optimizing the gating window width (duty factor (DF)) in respiratory-gated proton partial breast irradiation (PBI). To do so, GATE Monte Carlo simulations were performed for various target sizes and locations in supine and prone positions. Three different duty factors of 20, 25, and 33% were considered. Sparing factors (SF) for four organs-at-risk (OARs) were then assessed. The weighted-sum method was employed to search for an optimal DF. The results indicate that an SF higher than unity was obtained for all plans. The SF... 

The wide range of wireless sensor network applications has made it an interesting subject for many studies. One area of research is the controlled node placement in which the location of nodes is not random but predetermined. Controlled node placement can be very effective when either the price of the sensor nodes is high or the sensor coverage is of a specific type and it is necessary to provide special characteristics such as coverage, lifetime, reliability, delay, efficiency or other performance aspects of a wireless sensor network by using the minimum number of nodes. Since node placement algorithms are NP-Hard problems, and characteristics of a network are often in conflict with each... 

Recently, many investigations have been studied on the effects of the uncommon extreme events like hurricanes in electrical distribution grids. These events leads to damage to distribution grid equipments, and they are cause widespread blackouts. This paper presents short-term resilience enhancement of the residential sections against hurricane at day-ahead. The lines outage in the electrical distribution grid is implemented as stochastic modeling by hurricane. The resilience enhancement is done in the multiple energy systems such as integrated gas, heat and electrical. The three-stage multi-objective functions optimization is proposed for resilience-oriented enhancement. The proposed... 

In this paper, the V-shape development model approach for designing an automotive floor panel made by laminated structure is investigated to attain the best trade-off between the system and subsystem level requirements while improving the local and global performance of the vehicle. For this purpose, the bending and torsional stiffness of the body structure, as well as mass, strength, and vibration attenuation of the floor panel, are considered as design objectives at the system and subsystem levels. A multi-objective discrete optimization of a laminated configuration is performed using the Taguchi-based grey relational analysis. Material grades and thicknesses of the sandwich panel face... 

Landfill leachate is a highly contaminated liquid generated in municipal solid waste landfills. The application of sulfate radical-based advanced oxidation processes (SR-AOP) in landfill leachate treatments is emerging due to their ability to degrade both organic refractory matters and ammonia nitrogen. In this paper, application of peroxymonosulfate (PMS), activated by Fe2+ and UV was used as an economical and environmentally friendly approach for treatment of landfill leachate. Chemical oxygen demand (COD) and ammonia removals were measured as the two primary responses of landfill leachate to UV/PMS/Fe2+ treatment system. The main parameters (pH, PMS/Fe2+ mass ratio, Fe2+ dosage) affecting... 

Abstract: Advancements in microscale technologies have prompted a demand for high precision micro-manipulation. Microgrippers are the primary means of conducting micro-scale operations, and they significantly affect the procedure's performance. This paper presents a novel optimized design for compliant microgrippers, intending to enhance functionality and durability. The mainframe of the proposed microgripper is based on a compact flexure-based compliant structure with four stages of movement amplification. Experiments were designed based on the L25 Taguchi orthogonal arrays. The experiments were conducted using the finite element method in Abaqus 6.14 workbench. Range of motion and maximum... 

Minimum cost of energy is the main goal of a wind farm layout optimization. This is achieved by maximizing the total energy while minimizing the total costs of the farm. In this study, two sizes of commercial turbines were considered to investigate the effect of a non-homogenous farm on the layout optimization process. A cost model consisting of turbines, cable, transformers, foundation, and service vehicle routes was developed. Using Genetic Algorithm and Artificial Neural Network, first the superiority of the new algorithm in turbines and cable layout was verified versus previous studies. Next, two cases were investigated, i.e. (1) a farm populated with identical turbines and (2) a farm... 

Freeze desalination (FD) works upon the separation of impurities from pure water during ice crystals formation. The required cold source could be supplied by the cold energy of liquefied natural gas (LNG). In the current study, freeze desalination of seawater is explored by directly exploiting the cold energy of LNG within an appropriate range of temperature after producing work in a power generation cycle. A detailed discussion has been given on the inlet temperature of LNG to the FD unit for the first time. The direct utilization has the privilege of eliminating the addition of a secondary refrigerant and its refrigeration cycle to the FD process. A multi-objective optimization is... 

The optimal energy consumption and production is one of main aims in the many countries to improve technical, economic and environmental issues by smart energy systems. This paper proposes a bi-stage multi-objectives optimization of the smart multi energy system with optimal coordination of active consumers than electrical and thermal prices in the day-ahead market. The optimization is implemented under uncertainty of demand and price for electrical and thermal energies. In the first stage, original electrical and thermal demand curves are optimized using demand shifting strategy based on energy prices. Then, optimized electrical and thermal demand curves are applied in the second stage for... 

The use of energy storage systems (ESS) and distributed generators (DGs) to improve reliability is one of the solutions that has received much attention from researchers today. In this study, we utilize a multi-objective optimization method for optimal planning of distributed generators in electric distribution networks from the perspective of multi-objective optimization. The objective is to improve the reliability of the network while reducing the annual cost and network losses. A modified version of the multi-objective sine–cosine algorithm is used to determine the optimal size, location, and type of DGs and the optimal capacity, location, and operation strategy of the ESS. Three case... 

This paper presents a multi-objective availability-redundancy allocation optimization model for a hyper-system. The hyper-system consists of B systems with shared resources. The structure of the systems is series-parallel subsystems consisting of multi-failure and multi-state components. The components may be purchased from different suppliers based on their price and discounts. It is assumed that technical and organizational activities continuously affect the components' failure rates and the subsystems' working conditions before starting the system's mission horizon. The model aims to find the optimal number and the type of the subsystems' components for all systems from each supplier and... 

Optimal planning of residential complex energy systems requires thorough mathematical modelling to address the interconnections between all the energy installations from the largest ones, shared by all the residents, to the smallest ones in each distinct unit. Besides, conflicting desires of investors and residents in various aspects such as reliability index make this problem more challenging. In response, this paper presents a thorough framework to obtain the optimum design and operation of a residential complex energy system from scratch. To address the appropriate interconnection between various components of such an energy system, a multi-layer energy hub structure is proposed. Besides,... 

This article proposes a new three-stage stochastic framework for dealing with predictable two-phase natural disasters in distribution systems. This framework is a multiobjective optimization, in which the amount of curtailed energy, the number of switching actions, and the vulnerability of operational components are selected as the main criteria for decision-making process. The optimization problem is formulated in the form of a stochastic mixed-integer linear programming (MILP) problem. In this article, a windstorm event followed by flooding is analyzed as a two-phase natural disaster. In this regard, the uncertainties associated with gust-wind speed, floodwater depths, and load demands are... 

Proliferation of Plug-in Hybrid Electric Vehicles (PHEVs) and integration of various distributed generation (DG) technologies have been recognized to play an undeniable role in modern power systems of the future. In order to effectively model the interactions of these two technologies, this paper develops a multi-criteria framework to coordinate the charging behaviors of PHEVs within an energy hub platform. In this regard, the desirable charging profiles from the viewpoint of both PHEV owners and hub manager are first captured and reported to the PHEVs Coordinator Entity (PCE). The PCE, then, runs an optimization framework in which several criteria including the PHEV owners’ convenience,... 

Vehicular edge computing is a progressing technology which provides processing resources to the internet of vehicles using the edge servers deployed at roadside units. Vehicles take advantage by offloading their computationintensive tasks to this infrastructure. However, concerning time-sensitive applications and the high mobility of vehicles, cost-efficient task offloading is still a challenge. This paper establishes a computation offloading strategy based on deep Q-learning algorithm for vehicular edge computing networks. To jointly minimize the system cost including offloading failure rate and the total energy consumption of the offloading process, the vehicle tasks offloading problem is...