Sharif Digital Repository

Road roughness-induced vibrations are the main source of fatigue damage accumulation in vehicles. Hence, road surface profile modeling and simulation are of high importance when it comes to vehicle fatigue damage assessment. This research focuses on uncovering the statistical distributions that describe the characteristics of road loads that affect fatigue damage accumulation. Particle filtering is deployed to estimate the log-volatility of the road surface profile by assuming a random walk behavior for the hidden log-volatility. The skew-normal distribution with three parameters is fitted to the estimated log-volatility. The inferred parameters are used for synthesizing artificial road... 

Data-to-Text Generation (D2T) is one of the most important sub-fields of Natural Language Generation where structured data is transcribed into natural language text. Several solutions have been proposed for D2T so far with relative success, including template-based, phrase structure grammar-based, and neural attention models. However, these methods also have problems such as grammatical flaws, limited naturalness, and semantic deficiencies. In this work, we propose a stochastic corpus-based model for the data-to-text generation that produces a tree-form structure for sentences based on dependency information. This information includes the dependency relations between words and meaning labels... 

Due to the accelerated climate change, it is anticipated that the number and severity of natural disasters such as hurricanes, blizzards, and floods will be increased in the coming years. In this regard, this paper presents a distribution system planning model to improve the system resilience against hurricane. A scenario-based mathematical model is proposed to capture the random nature of weather events. Moreover, a stochastic optimization model is developed to simultaneously harden the distribution lines and place different types of distributed generation (DG) units such as microturbines (MTs), wind turbines (WTs), and photovoltaic cells (PVs). The conditional value at risk (CVaR) is used... 

Over the past decades, there has been a dramatic increase in the frequency of natural disasters, which are the leading causes of large-scale power outages. This paper, therefore, assesses the significance and role of optimal tie-line construction in improving the service restoration performance of unbalanced power distribution systems in the aftermath of high-impact low-probability incidents. In doing so, a restoration process aware stochastic mixed-integer linear programming model is developed to find the optimal locations for new tie-line construction in unbalanced three-phase distribution systems. In particular, the restoration process of distribution systems, including the fault... 

Wind power producers have recently gained a significant penetration in the electric power network, which might cause some challenges for the system operation due to the uncertainties in the generated power. In this way, wind power owners may offer different services, such as providing reserve capacity besides their conventional role of delivering just energy. Currently, conventional generators are the main responsible for providing some reserve in case of uncertainty in renewable generation and demand changes. Therefore, this article introduces a novel approach that allows wind power producers to participate in both energy and reserve markets alongside conventional generators. A two-stage... 

This paper presents a new model to maximize the utilization of existing transmission system infrastructure by optimally sizing and siting the future developments of variable renewable energy sources (VRES). The model tries to maximize the integration of VRES in power systems with minimum expected energy curtailment without relying on new investments in the transmission systems. The proposed model is formulated as a linear stochastic programming optimization problem where VRES output scenarios are generated such that their spatio-temporal correlations are maintained. The Progressive Hedging Algorithm (PHA) with bundled scenarios is utilized to solve the proposed model for large-scale cases.... 

Stimulus presentation is believed to quench neural response variability as measured by fano-factor (FF). However, the relative contributions of within-trial spike irregularity and trial-to-trial rate variability to FF fluctuations have remained elusive. Here, we introduce a principled approach for accurate estimation of spiking irregularity and rate variability in time for doubly stochastic point processes. Consistent with previous evidence, analysis showed stimulus-induced reduction in rate variability across multiple cortical and subcortical areas. However, unlike what was previously thought, spiking irregularity, was not constant in time but could be enhanced due to factors such as... 

The objective of this paper is to provide a stochastic framework to optimally avoid collision between a maneuverable spacecraft and a space object or debris. The satellite collision can be caused through a cyber-attack on a satellite by colliding it with a considered strategic satellite. Consequently, it is highly imperative that critical operational space assets be provided with autonomous collision avoidance systems. The collision avoidance methodology proposed in this paper will reduce the collision probability to an acceptable level and protect the satellite against indirect kinetic cyber-attacks initiated by designing optimal collision avoidance maneuvers using a stochastic model... 

This research attempts to propose a new simulating model capable of generating synthetic stochastic earthquake scenario including both seismological, and acceleration signal properties. The Iranian plateau is selected as a mainland for developing the model due to the existence of high-quality earthquake databases. This model is composed of two sub-models. The first one generates random seismic event scenarios including mainshocks and aftershocks. The second one procreates 3-dimensional synthetic stochastic accelerograms for each of the previously simulated events. This scenario-based predictive model offers a powerful tool to the risk modelers interested in lifetime seismic risk assessment... 

Electric spring (ES) as a breakthrough in power electronics has led to a revolution in demand-side management. This paper presents flexible power management (FPM) of a networked microgrid (MG) in the presence of renewable energy sources (RESs) and flexibility sources (FSs). The FSs include the novel topology of the integrated unit of ES with electric vehicles (EVs) parking (IUEE) and incentive-based demand response program (DRP). The proposed FPM model is formulated as an optimization problem that minimizes the difference between the expected energy cost and the expected profit of FSs' flexibility subject to the AC optimal power flow (AC-OPF), RESs, FSs, and MG flexibility constraints. In... 

As a problem, generally, energy security components do not interfere with the calculation of the optimal energy supply situation. Energy security indices so-called ‘passive indices’ cannot illustrate comprehensive optimal situation. In this paper, we are looking to find a solution to make a framework of the impact of energy security on energy supply in order to obtain comprehensive analysis of the economic optimal point. Method is based on the competition of energy costs to meet demand during the study period. Threats that have been addressed in the energy security are seen as risky and stochastic parameters in the model. The nature of these parameters is of uncertainty type, therefore,... 

As multi-hop wireless networks are attracting more attention, the need to evaluate their performance becomes essential. In order to evaluate the performance metrics of multi-hop wireless networks, including sending and receiving rates of a node as well as the collision probability, a model based on Stochastic Reward Nets (SRNs) is proposed. The proposed SRN models a typical node in such networks, considered as a general template to be applied to any wireless node. The SRN model of a single node is designed to take transmission effects of all neighboring nodes into account, while ignoring the ones whose transmission has no effect on the node under-study. Applying the proposed SRN to each node... 

In this paper, the evolution of elastic–plastic damage in the composite laminates under fatigue conditions is modeled. Continuum damage mechanics (CDM) has been coupled with the bridge micromechanics model to estimate the fatigue damage and life for laminated composite structures. Based on the elastic–plastic bridging model, three damage variables are defined. These variables estimate the fiber, matrix, and fiber/matrix damage response at the ply scale. To model the beginning of plastic deformation, a yield function is utilized, and evolution equations of the damage variables are obtained. Then the developed deformation plastic model is calculated. The model parameters are calibrated by... 

Companies depend on mining data to grow their business more than ever. To achieve optimal performance of Big Data analytics workloads, a careful configuration of the cluster and the employed software framework is required. The lack of flexible and accurate performance models, however, render this a challenging task. This paper fills this gap by presenting accurate performance prediction models based on Stochastic Activity Networks (SANs). In contrast to existing work, the presented models consider multiple work queues, a critical feature to achieve high accuracy in realistic usage scenarios. We first introduce a monolithic analytical model for a multi-queue YARN cluster running DAG-based Big... 

This paper presents a new model for optimal scheduling of renewable-based multi-energy microgrid (MEM) systems incorporated with emerging high-efficient technologies such as electric vehicle (EVs) parking lots, power-to-gas (P2G) facility, and demand response programs. The proposed MEM is equipped with wind energy, multi-carrier energy storage technologies, boiler, combined heat and power unit, P2G, EVs, and demand response with the aim of total operational cost minimization. Meanwhile, the system operator can participate in three electricity, heat, and gas market to meet local demands as well as achieve desired profits through energy exchanges. The proposed MEM is exposed to high-level... 

Due to the wide applications of three-dimensional graphene (3DG) foam in bio-sensors, stretchable electronics, and conductive polymer composites, predicting its mechanical behavior is of paramount importance. In this paper, a novel multiscale finite element model is proposed to predict the compressive modulus of 3DG foams with various densities. It considers the effects of pore size and structure and the thickness of graphene walls on 3DG foams' overall behavior. According to the scanning electron microscope images, a unit cell is selected in the microscale step to represent the incidental arrangement of graphene sheets in 3DG foams. After derivation of equivalent elastic constants of the... 

Capacitance-Resistive Model (CRM), as a fast yet efficient proxy model, suffers from some limitations in modeling relatively complex reservoirs. Some current improvements on this proxy made it a more powerful simulator with updating parameters over time. However, the model's intrinsic uncertainty arisen from simplifying fluid-flow modeling by some limited number of constant parameters is not addressed yet. In this study, this structural limitation of CRM has been addressed by introducing a time-correlated model error, including stochastic and non-stochastic parameters, embedded into this proxy's formulation. The error term's non-stochastic parameters have been tuned to be used in forecasting... 

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.... 

Carbon nanotubes (CNTs) are promising candidates for high-resolution mass nanosensors owing to their unique vibrational behavior. The structural characteristic (e.g. defect type and density) and working temperature have a significant effect on the natural frequency of CNT-based sensors. Herein, a stochastic approach based on novel finite element and molecular mechanics simulations is implemented to model the effect of temperature and structural characteristics of single-wall CNTs including defects (vacancy defect with different densities) and chirality (zigzag and armchair) on their vibrational behavior. The results show that the vacancy defects exert a significant deterioration of the... 

This paper presents a two-stage stochastic planning model for transmission systems and distributed energy resources (DERs) considering power system resiliency. The model takes into account both normal and emergency conditions as well as the duration of each condition. The proposed model is formulated as a mixed-integer linear program to minimize the total investment cost of transmission lines and DERs, expected values of generators' operation cost in normal and emergency situations, and load shedding cost in emergency condition. The emergency scenarios are considered as moderate, severe, and complete damage states, which have different recovery times for transmission assets. The Benders...