Sharif Digital Repository

The purpose of the present study is to develop the neutron diffusion solver and neutron noise simulator based on the Boundary Element Method (BEM). The 2-D, 2-G neutron/adjoint diffusion equation and corresponding neutron/adjoint noise equation were solved using the mentioned method. The developed neutron static and noise simulator based on the finite element method gives accurate results when the more number of the elements is used. The motivation of the present research is to use the boundary element method to reduce the computational cost. The boundary element method attempts to use the given boundary conditions to fit boundary values into the integral equation, rather than values... 

The value-based seismic design framework is a new design method that efficiently balances the construction resources and the seismic consequences, through reliable evaluation of the building performance at an affordable computational cost. This paper employs the value-based design approach to optimize the cross-section proportions of the steel wide-flange members. An optimization problem is proposed within the framework of value-based design. Construction cost and seismic consequences are selected as the value components. Moreover, the minimum code requirements are formulated as the design constraints. FEMA-P58 framework is exploited for the prediction of the seismic consequences including... 

Recent studies have indicated the need of considering aftershocks in the seismic design/assessment of structures. This article investigates the effect of sequential mainshock and aftershock earthquakes on eccentrically braced steel frames with vertical energy-absorbing links. To achieve this, 4, 8 and 12-storey frame buildings are modelled in Perform3D® software considering non-linear behaviour of materials and components. The frames are subjected to a set of 12 main earthquake records corresponding to the required hazard level, and then subsequent aftershocks are applied using incremental dynamic analysis (IDA). To reduce the computational cost, an alternative approach is also adopted by... 

Peridynamics is a nonlocal theory of solid mechanics which is suitable for modeling discontinuities and fractures without requiring external theories. In the original peridynamic equation of motion, the internal forces are integrated over the entire domain of the body. Although this equation complies perfectly with physical principles, its heavy calculations make it practically impossible to use. To avoid this difficulty, we can benefit from a special case of the peridynamic equation of motion in which the integration domain of the internal forces is limited to the family of particles. A limitation of this special equation, which is the most common equation in the peridynamic literature, is... 

With the advent of cloud computing and Internet of Things and delegation of data collection and aggregation to third parties, the results of the computations should be verified. In distributed models, there are multiple sources. Each source creates authenticators for the values and sends them to the aggregator. The aggregator combines the authenticated values and creates a verification object for verifying the computation/aggregation results. In this paper, we propose two constructions for verifying the results of countable and window-based countable functions. These constructions are useful for aggregate functions such as median, max/min, top-k/first-k, and range queries, where the... 

Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir's performance. Afterward, one needs to simulate the flow to predict the reservoir's dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 and K. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction "p"at a constant rate Q/h,... 

Given a social network modeled as a weighted graph GG, the influence maximization problem seeks kk vertices to become initially influenced, to maximize the expected number of influenced nodes under a particular diffusion model. The influence maximization problem has been proven to be NP-hard, and most proposed solutions to the problem are approximate greedy algorithms, which can guarantee a tunable approximation ratio for their results with respect to the optimal solution. The state-of-the-art algorithms are based on Reverse Influence Sampling (RIS) technique, which can offer both computational efficiency and non-trivial (1-1/e-ϵ)-approximation ratio guarantee for any epsilon >0ϵ>0.... 

One of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning-based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of... 

One of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning-based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of... 

The ubiquity of broadband digital communications and mass storage in modern society has stimulated the widespread acceptance of digital media. However, easy access to royalty-free digital media has also resulted in a reduced perception in society of the intellectual value of digital media and has promoted unauthorised duplication practices. To detect and discourage the unauthorised duplication of media, researchers have investigated watermarking methods to embed ownership data into media. However, some authorities have expressed doubt over the efficacy of watermarking methods to protect digital media. The paper introduces a novel method to discourage unauthorised duplication of digital... 

Pretrained representations have recently gained attention in various machine learning applications. Nonetheless, the high computational costs associated with training these models have motivated alternative approaches for representation learning. Herein we introduce TripletProt, a new approach for protein representation learning based on the Siamese neural networks. Representation learning of biological entities which capture essential features can alleviate many of the challenges associated with supervised learning in bioinformatics. The most important distinction of our proposed method is relying on the protein-protein interaction (PPI) network. The computational cost of the generated... 

Horizontal Ground Heat Exchangers (HGHE) as a means of exploiting geothermal energy has come to the fore for a few decades. Various analytical and Computational Fluid Dynamics (CFD) methods have been proposed to predict the performance of the HGHEs. The available analytical approaches are fast; however, they are based on various simplifications and assumptions, affecting their accuracy. On the other hand, CFD methods are more accurate, but their computational cost is a burden. Therefore there is an acute need for an accurate and fast method for predicting the long-term performance of HGHEs. To this aim, this study puts forward a novel hybrid analytical-numerical model for predicting the... 

A novel functional form for approximating the conditional scalars in turbulent reacting flows is introduced based on the Bernstein polynomial. Multi-scalar measurement data of turbulent premixed and non-premixed flames are used to demonstrate that the new functional form provides an excellent reduced-order model for the conditional scalars. This model order reduction technique can be used to improve the accuracy, reduce the computational cost and enhance the spatial localization of the Conditional Source-term Estimation (CSE) model. CSE is a turbulence-chemistry interaction model similar to the Conditional Moment Closure (CMC) model, except that the conditional scalars are estimated from the... 

In the last decade various crypto-currencies opened new doors to a decentralized electronic monetary system. Emergence of new Blockchain platforms, such as Ethereum, introduced new features for the implementation of decentralized software or smart contracts. The applications of blockchain technology for secure and efficient information systems is rapidly increasing. However, due to the limitations of this platform including high computational and storage cost, it is not possible to run sophisticated and computationally expensive software on the blockchain. In this paper, a new framework for execution of smart programs on blockchain called the Smart Program Runner Framework (SPRF) is...