Sharif Digital Repository

This study aims to develop the Consistent Fish-Bone (CFB) simplified model for efficient estimation of Engineering Demand Parameters (EDPs) in irregular steel Moment Resisting Frames (steel-MRFs). To achieve this goal, some modifications based on the energy consistent approach have been applied to the Improved Fish-Bone (IFB) simplified model previously presented for reinforced concrete MRFs. These modifications include: 1) adding truss elements to the IFB model to consider the effect of flexural deformations and determining their areas by balancing the overturning moment and the strain energy due to the axial deformation of columns in the original steel-MRF with the overturning moment and... 

Soft Computing (SC) is defined as a group of computational techniques that solve complex problems independent of mathematical models. SC techniques including artificial neural networks (ANNs), fuzzy systems (FSs), evolutionary algorithms (EAs), etc., can solve problems that either cannot be solved by the analytical/conventional methods or require a long computation time. Due to their features, SC techniques are nowadays widely used in scientific and industrial researches. SC techniques have also been included in many types of research related to nuclear power plants (NPPs). In this paper, the applications of SC techniques in NPPs, according to published articles, are presented. The... 

Atherosclerotic plaques and thrombosis are chronic inflammatory complications and the main manifestations of cardiovascular diseases (CVD), the leading cause of death globally. Achieving non/minimal-invasive therapeutic means for these implications in the coronary network is vital and has become an interdisciplinary concern. Accordingly, smart drug delivery systems, specifically based on micro- and nanoparticles, as a promising method to offer non/minimal-invasive therapeutic mechanisms are under active research. Notably, computational models enable us to study, design, and predict treatment strategies based on smart drug delivery systems with less time and cost compared with conventional... 

Given the various advantages of electric vehicles compared to conventional gasoline vehicles in terms of energy efficiency and environmental pollution (among others), this paper studies the factors affecting customers’ willingness to purchase electric vehicles. An integrated discrete choice and agent-based approach is applied to model the customers’ choice for the valuation of electric vehicles based on the internal reference price. The agent-based model evaluates customers’ preferences for a number of personal and vehicle attributes, according to which vehicle they chose. Data from 376 respondents are collected to estimate a random-parameter logit model where customers are asked to reveal... 

Earthquakes can cause significant damage to vulnerable residential buildings and cause irreversible adverse economic, social, and socioeconomic consequences. Implementing hazard mitigation policies can enhance homeowners' willingness to adopt hazard mitigation measures such as seismic retrofits or insurance. Several past studies have proposed models that aimed to explain individuals' hazard mitigation behavior. Despite their advantages, these decision-making models are subject to limitations. This manuscript proposes a new decision-making model that addresses the shortcomings of previous models. The proposed decision-making model is then incorporated at the core of an agent-based model to... 

In this article, a computational model is presented for the analysis of coupled thermo-hydro-mechanical process with phase change (evaporation/condensation) in fractured porous media in order to model multiphase fluid flows, heat transfer, and discontinuous deformation by employing the extended finite element method. The ideal gas law and Dalton's law are employed to consider vapor and dry air as miscible gases. To take into account the phase change, latent heat and specific vapor enthalpy are incorporated into the physical model. The set of governing equations consists of linear momentum for the solid-phase, energy balance equation and mass conservation equations of water species (liquid... 

Nonpharmaceutical measures such as social distancing can play an important role in controlling the spread of an epidemic. In this paper, we use a mathematical model combining human mobility and disease spreading. For the mobility dynamics, we design an agent-based model consisting of pedestrian dynamics with a novel type of force to resemble social distancing in crowded sites. For the spreading dynamics, we consider the compartmental susceptible-exposed-infective (SEI) dynamics plus an indirect transmission with the footprints of the infectious pedestrians being the contagion factor. We show that the increase in the intensity of social distancing has a significant effect on the exposure... 

Making proper decisions in today's complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling (ABM). ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making (DM) aspect to ABM can support the decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In... 

Socio-ecological systems include diverse resources of complexity involving complicated interactions, feedback, dynamic behavior patterns, heterogeneity in agents’ characteristics and behaviors, as well as system uncertainties. Agent-based modeling is introduced as a tool to simulate different levels of stakeholders and interactions, including individual, group, and institutional agents in complex socio-ecological systems. In the present study, an agent-based model was developed to explore sustainable solutions in uncertain conditions for groundwater restoration of a critical aquifer in the Lake Urmia Basin, Iran. Different projects for aquifer restoration such as wells monitoring, license... 

The high concentration of zinc metal ions in Aβ aggregations is one of the most cited hallmarks of Alzheimer's disease (AD), and several substantial pieces of evidence emphasize the key role of zinc metal ions in the pathogenesis of AD. In this study, while designing a multifunctional peptide for simultaneous targeting Aβ aggregation and chelating the zinc metal ion, a novel and comprehensive approach is introduced for evaluating the multifunctionality of a multifunctional drugs based on computational methods. The multifunctional peptide consists of inhibitor and chelator domains, which are included in the C-terminal hydrophobic region of Aβ, and the first four amino acids of human albumin.... 

The Minimum Maximum Outdegree Problem (MMO) is to assign a direction to every edge in an input undirected, edge-weighted graph so that the maximum weighted outdegree taken over all vertices becomes as small as possible. In this paper, we introduce a new variant of MMO called the p-Split Minimum Maximum Outdegree Problem (p-Split-MMO) in which one is allowed to perform a sequence of p split operations on the vertices before orienting the edges, for some specified non-negative integer p, and study its computational complexity. © 2020 Elsevier B.V  

The primary source of surgical site infection is the deposition of flakes released from the exposed skin of surgical staff or the patient on the exposed surgical wound. In this study, a computational model for simulating air ow and thermal conditions in an operating room is developed, and transport and deposition of particulate contaminants near the wound are analyzed. The results show the formation of a thermal plume over the wound tissue, which is typically at a higher temperature than the surrounding. The thermal plume protects the wound from the deposition of contaminants. In addition, the computational model predicts an optimum value for the inlet air velocity that is mainly maintaining... 

Alzheimer’s disease (AD) is an irreversible neurological disorder that progresses gradually and can cause severe cognitive and behavioral impairments. This disease is currently considered a social and economic incurable issue due to its complicated and multifactorial characteristics. Despite decades of extensive research, we still lack definitive AD diagnostic and effective therapeutic tools. Consequently, one of the most challenging subjects in modern medicine is the need for the development of new strategies for the treatment of AD. A large body of evidence indicates that amyloid-β (Aβ) peptide fibrillation plays a key role in the onset and progression of AD. Recent studies have reported... 

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped... 

This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM... 

The electric power industry is the main part of Science development, and today, with the advent of technology, the demand for electric power has been expanded. On the other hand, smart grids are developing heavily. One of the notable features of these networks is the presence of a plug-in hybrid electric vehicle (PHEV). The addition of these cars to the network has its own advantages and disadvantages. One of the most important issues in smart grids is network management and control of critical system parameters. In this paper the effect of these cars on the grid is investigated. These vehicles impose an increase in production capacity in the uncontrolled charge mode. They also have the... 

The electric power industry is the main part of Science development, and today, with the advent of technology, the demand for electric power has been expanded. On the other hand, smart grids are developing heavily. One of the notable features of these networks is the presence of a plug-in hybrid electric vehicle (PHEV). The addition of these cars to the network has its own advantages and disadvantages. One of the most important issues in smart grids is network management and control of critical system parameters. In this paper the effect of these cars on the grid is investigated. These vehicles impose an increase in production capacity in the uncontrolled charge mode. They also have the... 

Cellular learning automata (CLA) is a distributed computational model which was introduced in the last decade. This model combines the computational power of the cellular automata with the learning power of the learning automata. Cellular learning automata is composed from a lattice of cells working together to accomplish their computational task; in which each cell is equipped with some learning automata. Wide range of applications utilizes CLA such as image processing, wireless networks, evolutionary computation and cellular networks. However, the only input to this model is a reinforcement signal and so it cannot receive another input such as the state of the environment. In this paper,... 

This review aims to propose the integrative implementation of microfluidic devices, biomaterials, and computational methods that can lead to a significant progress in tissue engineering and regenerative medicine researches. Simultaneous implementation of multiple techniques can be very helpful in addressing biological processes. Providing controllable biochemical and biomechanical cues within artificial extracellular matrix similar to in vivo conditions is crucial in tissue engineering and regenerative medicine researches. Microfluidic devices provide precise spatial and temporal control over cell microenvironment. Moreover, generation of accurate and controllable spatial and temporal... 

An important aspect of corrosion prediction for oil/gas wells and pipelines is to obtain a realistic estimate of the corrosion rate. Corrosion rate prediction involves developing a predictive model that utilizes commonly available operational parameters, existing lab/field data, and theoretical models to obtain realistic assessments of corrosion rates. This study presents a new model to predict corrosion rates by using artificial neural network (ANN) systems. The values of pH, velocity, temperature, and partial pressure of the CO2 are input variables of the network and the rate of corrosion has been set as the network output. Among the 718 data sets, 503 of the data were implemented to find...