Sharif Digital Repository

In the context of sustainable clean hydrogen production pathways, photovoltaic-electrolyzer systems are one of the most promising alternatives for acquiring hydrogen from renewable energy sources. In fact, determining the optimal set of design and operating variables are always a key issue while coupling directly renewable electricity sources to PEM electrolyzers. Few previous studies have attempted to find the optimal size and operational condition of directly coupled photovoltaic-electrolyzer (PV/El) systems in order to maximize the hydrogen production or to minimize energy transfer loss between photovoltaic devices and the electrolyzer. Nevertheless an easy and efficient approach still... 

Photovoltaic-electrolyzer systems are one of the most promising alternatives for obtaining hydrogen from a renewable energy source. Determining size and the operational conditions are always a key issue while coupling directly renewable electricity sources to PEM electrolyzer. In this research, the multi objective optimization approach based on an imperialist competitive algorithm (ICA), which is employed to optimize the size and the operating conditions of a directly coupled photovoltaic (PV)-PEM electrolyzer. This allows the optimization of the system by considering two different objectives, including, minimization of energy transfer loss and maximization of hydrogen generation. Multi... 

Hydrogen is an important storage medium and can be produced by the water electrolysis. In this research, energy transfer loss between a photovoltaic (PV) unit and electrolyzer is minimized by optimizing the size and operating condition of an electrolyzer directly connected to a PV module. In directly coupled photovoltaic-electrolyzer (PV/EL) systems, there is a mismatch between output PV's maximum power point characteristic and input PEM electrolyzer's characteristic. With proper sizing optimization methods, it is possible to directly couple photovoltaic-electrolyzer systems. The evolutionary optimization algorithms like genetic algorithm (GA), particle swarm optimization (PSO) and... 

Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of Service Composition and Optimal Selection (SCOS) is an important issue for practical implementation of cloud manufacturing. In this paper, a new Mixed Integer Programming (MIP) model for solving the SCOS with transportation consideration has been proposed. This model minimizes both manufacturing and transportation costs subject to some constraints such as necessity of transportation between manufacturing resources and the requirements specified... 

This paper presents a synthesis strategy for impact force localization and identification of framed structures in time-domain using a two-step wavelet-based fitness evaluation scheme in conjunction with genetic and water cycle algorithms. For this purpose, a straightforward approach is developed for sensitivity analysis of accelerations and spatial signal connecting the peak values. The proposed scheme is capable of using diverse scales of wavelet functions at considerably small sampling rates. A decimal genetic algorithm (GA) coding system and a recently developed water cycle algorithm (WCA) are improved to be used for impact localization and identification, respectively. The fitness... 

Hydrogen is considered to be the fuel of the future. It is a cleaner alternative to the fossil fuels we consume every day. Of all the different hydrogen production pathways that exist, producing the gas by utilizing the power generated by renewable energy sources has been a topic of interest for many researchers across the world. The following work focuses on minimizing the energy loss by optimizing the size and the operating conditions of an electrolyzer directly connected to a photovoltaic (PV) module at different irradiance. The hydrogen, in the proposed system, is produced using a proton exchange membrane (PEM) electrolyzer. A nonlinear method is considered, because of the complexity of... 

The purpose of this paper is to develop a multi-item economic order quantity (EOQ) model with shortage for a single-buyer single-supplier supply chain under green vendor managed inventory (VMI) policy. This model explicitly includes the VMI contractual agreement between the vendor and the buyer such as warehouse capacity and delivery constraints, bounds for each order, and limits on the number of pallets. To create a kind of green supply chain, tax cost of green house gas (GHG) emissions and limitation on total emissions of all items are considered in the model. A hybrid genetic and imperialist competitive algorithm (HGA) is employed to find a near-optimum solution of a nonlinear... 

Refractive index (RI) provides valuable information about various reservoir engineering calculations, making it a key parameter for characterizing crude oils. Determination of this index through experiment is capital-intensive, time consuming, and also toil. Hence, it is essential to search for an efficient and accurate estimation of crude oil RI. In this study, an intelligent approach, based on optimized support vector regression (SVR), is introduced to find a quantitative correlation between crude oil RI and SARA (saturate, aromatic, resin, and asphaltene) fraction data. Optimization of SVR is implemented through three searching approaches, viz. hybrid of grid and pattern search (HGP),... 

Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root... 

A novel optimization method based on Imperialist Competitive Algorithm (ICA) for simulating endurance time (ET) excitations was proposed. The ET excitations are monotonically intensifying acceleration time histories that are used as dynamic loading. Simulation of ET excitations by using evolutionary algorithms has been challenging due to the presence of a large number of decision variables that are highly correlated due to the dynamic nature of the problem. Optimal parameter values of the ICA algorithm for simulating ETEFs were evaluated and were used to simulate ET excitations. In order to increase the capability of the ICA and provide further search in the optimization space, this... 

Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root...