Sharif Digital Repository

Acknowledging the conditionality of model-based evidence facilitates the dialogue between model developers and model users, especially when models are used to guide decisions at the science-policy interface. In general, model users have limited access to verify the realism of a model, being only exposed to model plausibility and trustworthiness; instead, modellers have an an array of validation and verification techniques available. In the end, model credibility is what both developers and users aim for, also in the interest of shielding from the possible pitfall of over-interpreting the model results. To this end, in this contribution we discuss sensitivity auditing, an extension of... 

In this research, theory of fuzzy sets is used to deal with the uncertain nature of soil parameters and the inaccuracy involved in the analysis simultaneously. Soil parameters are defined using suitable fuzzy sets and the uncertainty inherent in the value of factor of safety is assessed. It is believed that this approach accounts for the uncertainty in soil parameters more realistically compared to the conventional probabilistic approaches reported in the literature. The proposed method is applied to a case study and the results are discussed subsequently  

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... 

Purpose: Tackling the challenges of water scarcity requires comprehensive management according to financial, environmental and social issues. This paper aims to develop a planning approach for systematic decision-making and pay attention to uncertainties in water demand management and supply investment. Design/methodology/approach: This study presents a multiobjective optimization model to manage water resources based on the balance of supply and demand. The objectives of the model include economic, social and environmental (sustainable development) factors. The model achieves an optimal urban water portfolio by using a scenario tree. Findings: The mathematical goal programming (GP) in a... 

Kinematic accuracy of the robot end-effector is decreased by many uncertainties. In order to design and manufacture robots with high accuracy, it is essential to know the effects of these uncertainties on the motion of robots. Uncertainty analysis is a useful method which can estimate deviations from desired path in robots caused by uncertainties. This paper presents an applied formulation based on Direct Linearization Method (DLM), for 3D statistical uncertainty analysis of open- loop mechanisms and robots. The maximum normal and parallel components of the position error on the end-effector path are introduced. In this paper, uncertainty effects of both linear and angular variations in... 

We discuss the prospect of extracting the values of the mixing parameters δ and θ13 through the detection of cosmic neutrinos in the planned and forthcoming neutrino telescopes. We take the ratio of the μ-track to shower-like events, R, as the realistic quantity that can be measured in the neutrino telescopes. We take into account several sources of uncertainties that enter the analysis. We then examine to what extent the deviation of the initial flavor composition from we : w μ : wτ 1 : 2 : 0 can be tested  

Chatter suppression is an important topic in any type of machining process. In this paper, orthogonal cutting process is modeled as a single degree of freedom dynamic system. A nonlinear delay differential equation is presented that models flank wear of the tool. Uncertainties in cutting velocity, tool wear size and parameters of the dynamic model are included in the model of cutting process. The force provided by a piezo-actuator is taken as the control input of the system. A sliding mode control scheme is used and an effective control law is derived which suppresses the chatter vibration. Results for two distinct cases of a sharp tool and a worn tool are presented and compared which shows... 

Microgrids have emerged as a practical solution to improve the power system resilience against unpredicted failures and power outages. Microgrids offer substantial benefits for customers through the local supply of domestic demands as well as reducing curtailment during possible disruptions. Furthermore, the interdependency of natural gas and power networks is a key factor in energy systems’ resilience during critical hours. This paper suggests a probabilistic optimization of networked multi-carrier microgrids (NMCMG), addressing the uncertainties associated with thermal and electrical demands, renewable power generation, and the electricity market. The approach aims to minimize the NMCMG... 

This study is an attempt to investigate and analyze uncertainty through the Glue method in parts of Tabriz, Iran, using the SWMM urban flood model. In order to quantify the uncertainty, the initial range of input parameters including curve number, impenetrability percentage, penetrability level’s coarseness coefficient, and impenetrability level’s coarseness coefficient are defined and the GLUE algorithm is used to conduct primary sampling operation from parametric space using Latin hypercube sampling method. Considering the simulation results and the observed values of synchronized events, about %20 of the total outputs and generated parameters series have been excluded as acceptable... 

The interaction between a lake and groundwater has important implications to the quantity and quality of water in both environments. Quantification of lake-groundwater interaction (LGI) has been challenging in regions with limited in-situ data. LGI can be quantified by physically-based models, direct measurement of seepage, measurements of conservative chemical or isotopic tracers, and lake water balance. Despite the accuracy of the methods based on hydrochemical or isotopic measurements and analysis, they require extensive field data that are costly to collect in large lakes. Instead, the data required to quantify LGI by the lake water budget method can be obtained via typical ground... 

In this study we use polynomial chaos expansion (PCE) to perform uncertainty analysis for seawater intrusion (SWI) in fractured coastal aquifers (FCAs) which is simulated using the coupled discrete fracture network (DFN) and variable-density flow (VDF) models. The DFN-VDF model requires detailed discontinuous analysis of the fractures. In real field applications, these characteristics are usually uncertain which may have a major effect on the predictive capability of the model. Thus, we perform global sensitivity analysis (GSA) to provide a preliminary assessment on how these uncertainties can affect the model outputs. As our conceptual model, we consider fractured configurations of the... 

Fluid flow modeling in porous media has many applications in waste treatment, hydrology and petroleum engineering. In any geological model, flow behavior is controlled by multiple properties. These properties must be known in advance of common flow simulations. When uncertainties are present, deterministic modeling often produces poor results. Percolation and Random Walk (RW) methods have recently been used in flow modeling. Their stochastic basis is useful in dealing with uncertainty problems. They are also useful in finding the relationship between porous media descriptions and flow behavior. This paper employs a simple methodology based on random walk and percolation techniques. The... 

This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two-country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model-averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show... 

A new risk-constrained bidding curve construction method is presented in this paper. A Day-ahead energy market has been chosen for competition of GenCos and the Information Gap Decision Theory (IGDT) is used for modelling the Day-ahead market price uncertainty and its corresponding risk. The bilateral contracts of the GenCo are also considered in the proposed framework. A Bi-level optimization problem is incorporated in the proposed method to guarantee a pre-specified level of revenue. The proposed IGDT based method constructs the non-decreasing bidding curve while dispatching units based on the uncertain forecasted prices of the next-day market. The verification of the proposed method is... 

The Higgs boson was postulated nearly five decades ago within the framework of the standard model of particle physics and has been the subject of numerous searches at accelerators around the world. Its discovery would verify the existence of a complex scalar field thought to give mass to three of the carriers of the electroweak force-the W+, W-, and Z 0 bosons-as well as to the fundamental quarks and leptons. The CMS Collaboration has observed, with a statistical significance of five standard deviations, a new particle produced in proton-proton collisions at the Large Hadron Collider at CERN. The evidence is strongest in the diphoton and four-lepton (electrons and/or muons) final states,... 

This paper presents a novel model for designing a reliable network of facilities in closed-loop supply chain under uncertainty. For this purpose, a bi-objective mathematical programming formulation is developed which minimizes the total costs and the expected transportation costs after failures of facilities of a logistics network. To solve the model, a new hybrid solution methodology is introduced by combining robust optimization approach, queuing theory and fuzzy multi-objective programming. Computational experiments are provided for a number of test problems using a realistic network instance  

This paper presents stability analysis of a distributed generation (DG) controller (1), in an islanded mode, based on the Mapping Theorem and the Zero Exclusion Condition, and validates the results based on a laboratory scale experimental setup. The DG unit is interfaced to the host system through a voltage-sourced converter (VSC). The control strategy regulates the load voltage at the desired value in the islanded mode, despite uncertainties in the load parameters. The frequency of the island is controlled in an open loop manner by an internal oscillator. The experimental results show that the controller provides robust voltage control for a wide range of load parameters, and even maintains... 

This paper presents stability analysis of a distributed generation (DG) controller [1], in an islanded mode, based on the Mapping Theorem and the Zero Exclusion Condition, and validates the results based on a laboratory scale experimental setup. The DG unit is interfaced to the host system through a voltage-sourced converter (VSC). The control strategy regulates the load voltage at the desired value in the islanded mode, despite uncertainties in the load parameters. The frequency of the island is controlled in an open loop manner by an internal oscillator. The experimental results show that the controller provides robust voltage control for a wide range of load parameters, and even maintains... 

Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties, high investment costs, and long period investment return cause the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new approach for transmission expansion planning (TEP) in order to maximize private investment absorption. The robust optimization method is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load. The genetic algorithm (GA) is, also, utilized as the methodology to solve the...