Sharif Digital Repository

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... 

Outsourcing as a useful strategy in the industry can be integrated into scheduling problems. Moreover, batch outsourcing is a practical assumption owing to the logistics issues for transferring the parts between the manufacturer and the subcontractors. However, this assumption is rarely addressed in the scheduling literature. In this paper, a novel single machine scheduling problem with the option of batch outsourcing is studied. The objective is to minimize the sum of the total completion time of the jobs and the total outsourcing cost. To solve the problem, first, two mixed-integer linear programming (MILP) models, named MP1 and MP2, are developed, which respectively use a straightforward... 

The use of ZrO2 nanoparticles is common in the Cu matrix to manufacture Cu/ZrO2 nanocomposites. Many approaches and parameters produce Cu/ZrO2 nanocomposites with an appropriate wear rate and other properties. Hence, proposing an accurate and reliable model was imperative. The main goal of this paper is to find out the best models among the ant colony optimization (ACO), gene expression programming (GEP), artificial bee colony (ABC), and gray wolf optimization algorithm (GWOA) to predict the wear rate of/ZrO2 nanocomposites. To the best of our knowledge, this is the first research that predicts Cu/ZrO2 nanocomposites wear rate using group modeling. To develop models, 105 data were collected... 

The reaction progress variable is a crucial concept in the advanced flamelet combustion models. As a controlling variable, a well-defined progress variable must consider the essential features of the combustion process. It is usually a heuristically defined linear combination of some major chemical species mass fractions. However, such a simple definition could lead to inaccurate results for the fuel-rich reactive mixtures or complicated fuels, due to the vast number of chemical species in the combustion process. In this paper, a new method for generating a reaction progress variable is proposed through solving a constrained optimisation problem. The proposed method uses a genetic algorithm... 

Marketing managers concern that Word-of-Mouth (WOM) can affect the efficiency of sales promotion policy. Sales promotion might also amplify the strength of WOM which further complicates decision-making. In this study, we deploy an agent-based simulation optimization framework to find an efficient sales promotion plan in the presence of WOM for launching re-purchasable products. In this model, consumers' purchase decisions are influenced by price history, availability and satisfaction of the consumers, and positive/negative WOM. We show that taking WOM on board while determining the promotion plan can significantly increase the net present value. However, amplifying WOM might damage the... 

Heat-bath algorithmic cooling (HBAC) techniques are techniques that are used to purify a target element in a quantum system. These methods compress and transfer entropy away from the target element into auxiliary elements of the system. The performance of algorithmic cooling has been investigated under ideal noiseless conditions. However, realistic implementations are imperfect, and for practical purposes, noise should be taken into account. Here we analyze HBAC techniques under realistic noise models. Surprisingly, we find that noise can, in some cases, enhance the performance and improve the cooling limit of HBAC techniques. We numerically simulate the noisy algorithmic cooling for the two... 

There is limited research that considers the sustainability aspect of the projects’ schedule. The present study proposes a model to cover this gap by considering sustainable development criteria. A multi-objective model with four objective functions, including minimizing cost, risk, and socio-environmental impacts, has been presented to decrease the project’s delay. Since some of the parameters are considered under conditions of uncertainty for the proximity of problems to real projects, the robust programming method is used to deal with the uncertainty, and the epsilon-constraint method was applied to solve the multi-objective model. Several scenarios are also defined to analyze the... 

In recent years, the management of health systems is a main concern of governments and decision-makers. Home health care is one of the newest methods of providing services to patients in developed societies that can respond to the individual lifestyle of the modern age and the increase of life expectancy. The home health care routing and scheduling problem is a generalized version of the vehicle routing problem, which is extended to a complex problem by adding special features and constraints of health care problems. In this problem, there are multiple stakeholders, such as nurses, for which an increase in their satisfaction level is very important. In this study, a mathematical model is... 

This paper proposes an Age-Dependent Clustering (ADC) structure to be used for prognostics. To achieve this aim, a step-by-step methodology is introduced, that includes clustering, reproduction, mapping, and finally estimation of Remaining Useful Life (RUL). In the mapping step, a neural fitting tool is used. To clarify the age-based clustering concept, the main elements of the ADC model is discussed. A Genetic algorithm (GA) is used to find the elements of the optimal model. Lastly, the fuzzy technique is applied to modify the clustering. By investigating a case study on the health monitoring of some turbofan engines, the efficacy of the proposed method is demonstrated. The results showed... 

Utilization of heat storage units in solar energy systems can resolve the challenge of fluctuation and uncertainty of the solar energy. Phase change materials (PCMs) are used as the storage media for solar energy storage systems. In this research, a system including of a solar collector and a PCM-based cascaded energy storage unit was numerically investigated. Air was used as the heat transfer fluid (HTF) and three paraffin-based materials (RT50, RT65, and RT80) were used as PCM for the energy storage unit. The investigated system mainly operates between 15 °C and 90 °C and considering different PCMs, the selected PCMs were appropriate. Paraffin-based PCMs also present acceptable thermal... 

Electric spring (ES) as a novel concept in power electronics has been developed for the purpose of dealing with demand-side management. In this paper, to conquer the challenges imposed by intermittent nature of renewable energy sources (RESs) and other uncertainties for constructing a secure modern microgrid (MG), the hybrid distributed operation of ESs and electric vehicles (EVs) parking lot is suggested. The proposed approach is implemented in the context of a hybrid stochastic/robust optimization (HSRO) problem, where the stochastic programming based on unscented transformation (UT) method models the uncertainties associated with load, energy price, RESs, and availability of MG equipment.... 

With the current focus on energy and the environment, efficient integration of renewable energies, especially solar energy into power systems, is becoming indispensable. Moreover, to fully capture solar potentials and to recognize the unique characteristics associated with solar energy in power systems reliability assessment, a profound investigation is needed. Accordingly, this paper attempts to establish a comprehensive analytical approach for modeling the reliability of a hybrid system (Photovoltaic (PV) system with Energy Storage System (ESS)). To this end, the output of the PV system is modeled by a multi-state model, and the ESS system is modeled as a two-state Markov model. Moreover,... 

The paper aims to present a supply model to satisfy the required household final energy carriers, freshwater and industrial cooling loads for a deprived area of access that is located in hot and humid climate. To this aim, a multi-generation hybrid solar thermophotovoltaic integrated system with capability of adjusting heat to power ratio dynamically is introduced. Appropriate analytical tools are developed to obtain the optimal capacity of any systems and energy flows subject to the technology and demand constraints, the financial limitation and the constraints defined by the politicians and local government. The demand constraints are identified through the field studies and the comfort... 

The present work is comprised of two main parts. In part 1 the Co-Ni/γ-Al2O3 catalyst was prepared using a sol-gel procedure. Then the effect of calcination variables including the calcination temperature and time on the catalytic performance for production of light olefins was investigated and optimized. The obtained results have shown that the catalyst which was calcined at 550 °C for 6 h has revealed the better catalytic performance for production of light olefins. In part 2 the effect of process conditions including the reaction temperature, H2/CO feed ratio and total reaction pressure on the catalytic performance (CO conversion%, (C2-C4) selectivity% and C5+ selectivity%) was... 

Greenhouses require energy in order to provide a proper environment for crop production. Utilizing solar energy in solar greenhouses is a sustainable solution to face this problem. In this study, a solar greenhouse concept is considered, and a dynamic thermal model is developed to predict the inside air temperature. The model is integrated into an optimization procedure to find the optimal greenhouse design that has the best thermal performance by adjusting its structural parameters. This optimization procedure provides a tool to find the optimal solar greenhouse design for each climate condition and predict its performance. For instance, for the case study of Tehran (Iran), the optimal... 

This study proposes a computer modeling approach to find the optimal damping coefficients of the viscoelastic ankle-foot prostheses for each specific amputee. A two-dimensional locomotion model was developed for a transtibial amputee and personalized using his body measures and the reference gait pattern of an equivalent able-bodied subject. By employing the forward dynamic simulation, the amputee’s locomotion was synthesized for different prosthetic settings to find the optimal damping coefficients, based on a kinematics and a total work cost function. Results indicated a good agreement between the model predictions and the experimental observations. © 2018, © 2018 RESNA  

This article presents a mixed-integer linear stochastic model for the optimal expansion planning of electricity distribution networks and distributed generation (DG) units. In the proposed framework, autonomous DG units are aggregated and modeled using the well-known energy hub concept. In this model, the uncertainties of heat and electricity demand as well as renewable generation are represented using various scenarios. Although this is a standard technique to capture the uncertainties, it drastically increases the dimensions of this optimization problem and makes it practically intractable. In order to address this issue, a novel iterative method is developed in this article to enhance the... 

This study is a novel attempt in developing of an Artificial neural network (ANN) model integrated with a thermodynamic equilibrium approach for downdraft biomass gasification integrated power generation unit. The objective of the study is to predict the net output power from the systems derived from various kinds of biomass feedstocks under atmospheric pressure and various operating conditions. The input parameters used in the models are elemental analysis compositions (C, O, H, N and S), proximate analysis compositions (moisture, ash, volatile material and fixed carbon) and operating parameters (gasifier temperature and air to fuel ratio). The architecture of the model consisted of one... 

Due to the increasing need for drinking water in the world, various membrane processes have been developing significantly over the past several years. The process of membrane distillation is one of the non-isothermal processes that cause steam to pass from the membrane due to the difference in temperature and the resulting difference in vapor pressure. Due to the lack of precision in the amount of flux and thermal efficiency in various operating conditions the membrane distillation process still needs development. This article attempted to examine the effects of flowrate, temperature, and module length on the performance of the membrane distillation process using computational fluid dynamics... 

Sophisticated surgeons are widely indicating the use of surgical robots in order to reject human error, increase precision, and speed. Among well-known robotic mechanisms, parallel robots are broadly more investigated regarding their special characters as higher acceleration, speed, and accuracy, and less weight. Specific surgical procedures confine, and restrict their workspace, while controlling and validating the robots are complicated regarding to their complex dynamic. To this end, in this paper, a 6-DOF robot, with rotary manipulators, is designed and controlled. Addressing nonlinearity of parallel robots, an innovative methodology is formulated to robustly penalize the error of...