Sharif Digital Repository

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's characteristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing functions which are widely accessible by researchers and this has led to an easy algorithm implementation. In this method, after polishing and quality control of images, using city-block distance function and watershed segmentation algorithm, pores and throats are detected and 3-D network is produced. This method can also be applied on 2-D images... 

Many quantum systems are being investigated in the hope of building a large-scale quantum computer. All of these systems suffer from decoherence, resulting in errors during the execution of quantum gates. Quantum error correction enables reliable quantum computation given unreliable hardware. Unoptimized topological quantum error correction (TQEC), while still effective, performs very suboptimally, especially at low error rates. Hand optimizing the classical processing associated with a TQEC scheme for a specific system to achieve better error tolerance can be extremely laborious. We describe a tool, AUTOTUNE, capable of performing this optimization automatically, and give two highly... 

Porosity and specific surface are two prominent factors in describing the hydraulic properties of porous media. Determination of these two important parameters leads to identify the capability of porous media to conduct the fluids. In the present study, a new relationship between porosity and specific surface of sandstones has been developed. Micro-CT data from 10 types of sandstones has been utilized in order to present a porosity-specific surface correlation. This correlation also contains the average grain radius of each rock obtained by image processing algorithms. Finally, the correlation is tested on the provided data to evaluate its precision. The simplicity and applicability of the... 

Plasma impulse technology (PIT) is one of the most innovative methods among the oil recovery enhancement (EOR) jobs. Although the low cost and persistent effects of this method has attracted researchers attentions to its self, the governing mechanisms of reservoir remediation in this method are still shrouded in mystery. This study presents a brief discussion on probable thermal mechanisms which govern the interaction between reservoir formation and plasma impulse jet. Minerals dissociation, opening the fused pathway and organic deposits melting seem to be of the most important thermal effects  

The applicability of Plasma Impulse Technology (PIT) in the enhancement of oil recovery has been proved in recent years. The priority of this environmental friendly treatment has been proved by the Russian operators which has applied this technology on many production and injection wells. This study presents a brief discussion on probable pressure based mechanisms which govern the interaction between reservoir formation and plasma impulse jet. High pressure of the ejected plasma may cause formation fracturing, damage removal due to pressure shocks and reservoir fluid resonance  

The grain-size distribution (GSD) of porous rocks is important in order to better understand their hydrodynamic behavior. Clear and precise GSD data can be used to computationally reconstruct rock structure for further analysis. In this study, three main algorithms for image analysis have been examined to estimate the GSD of clastic rocks. The main challenge in GSD determination from images is in detecting overlapping grains and measuring their size separately. In this study, three previously developed image processing algorithms are implemented on two-dimensional (2D) binary images of rocks in order to compare the obtained GSD from each of the methods, i.e., the mean intercept length... 

In the present paper, a dynamic modeling is presented for deposition of the mud solid particles over and through the porous sandstones during permeability plugging experiments. Scanning electron microscopy (SEM) coupled with image processing are utilized to find the porosity and pore size distribution of the mud cake. The structure of the porous rock as well as the mud cake are modeled via bundle of the curved tubes approach and deposition probability of the solid particles has been taken into the account through filtration theories. Four different sandstones in addition to four mud samples were utilized to measure and predict the volume of the expelled fluid during the 30 min of filtration... 

Changes of morphological parameters of oil shale under thermal conditions are investigated. Analyses are based on 26 micro-computed tomography (micro-CT) images of Green River immature shale rock available under creative commons license. Several image processing and characterization algorithms are applied to sequential high-resolution micro-CT images of oil shale samples undergoing pyrolysis. Pore-scale morphology is extracted and quantified, providing results for pore size, throat size, grain size, specific surface, coordination number, and fracture aperture. The results demonstrate critical increases of porosity, coordination number and fracture aperture in the temperature range from 390... 

Petrography and image analysis have been widely used to identify and quantify porous characteristics in carbonate reservoirs. This paper uses the thin section images of 200 carbonate rock samples to predict the absolute permeability using intelligent and empirical methods. For each thin section, several pore network parameters are extracted from thin section images of rocks including the average pore size, average throat size, average throat length and average 2-D coordination number of pore network. A neural-based model successfully predicts the permeability of samples using pore network parameters as the inputs. Second neural network is applied for predicting absolute permeability... 

Data science as a flourishing interdisciplinary domain of computer and mathematical sciences is playing an important role in guiding the porous material research streams. In the present narrative review, we have examined recent trends and issues in data-driven methods used in the image-based porous material research studies relevant to water resources researchers and scientists. Initially, the recent trends in porous material data-related issues have been investigated through search engine queries in terms of data source, data storage hub, programing languages, and software packages. Subsequent to a diligent analysis of the existing trends, a review of the common concepts of porous material... 

This paper presents a new decision making framework for supplier selectionin a make-to-order-system (MTO) while establishing an information loop between"sale"and"purchasing" functions which play important rolesin successful satisfying of customers. The order entry stage outputs, includingaccepted orders' requirements and their priorities are reflected into thesupplier selection phase; and in return, the outputs of the supplier selectionmodel are fed back into the sale department to revise the orders attributesaccording to the system's supplying capabilities. A ranking procedure usingFuzzy data-envelopment-analysis (DEA) and multi attribute utility model (i.e.similarity to ideal solution... 

This paper presents a meta-heuristic algorithm for solving bi-objective fuzzy job shop scheduling problems. These objectives are to minimize the makespan and minimize the early and late penalty. Processing time and due date are considered as fuzzy triangular numbers. This paper also introduces a novel use of data mining algorithm for solving of combinatorial optimization problems. The proposed algorithm combines genetic algorithms and an attribute-oriented induction algorithm, which is much quicker than previous methods providing the optimal solution. By considering the structure of proposed algorithm, the whole feasible solutions of a special job shop-scheduling problem are considered as a... 

A novel, simple and rapid spectrophotometric method for the determination of nitrophenol (NP) isomer mixtures based on the catalytic activity of gold nanoparticles is described. Gold nanoparticle (∼13 nm) solution was used to catalyze the reduction of NP isomers to aminophenols with an excess amount of NaBH4. The second-order data were obtained by spectrophotometrically monitoring the reduction process of NP isomers. So, multivariate curve resolution optimized by alternative least squares (MCR-ALS) was used to analyze such data. MCR-ALS, an appropriate second-order method, can exploit the so-called 'second order advantage' (the ability to determine in the presence of uncalibrated... 

This study describes spectrometric monitored kinetic processes to determine the size of citrate-capped Au nanoparticles (Au NPs) based on aggregation induced by L-cysteine (L-Cys) as a molecular linker. The Au NPs association process is thoroughly dependent on pH, concentration and size of nanoparticles. Size dependency of aggregation inspirits to determine the average diameters of Au NPs. For this aim the procedure is achieved in aqueous medium at pH 7 (phosphate buffer), and multivariate data including kinetic spectra of Au NPs are collected during aggregation process. Subsequently partial least squares (PLS) modeling is carried out analyzing the obtained data. The model is built on the... 

In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied... 

Herein, a magnetic zirconium-based metal-organic framework nanocomposite was synthesized by a simple solvothermal method and used as an adsorbent for the removal of direct and acid dyes from aqueous solution. To enhance its adsorption performance, poly(propyleneimine) dendrimer was used to functionalize the as-synthesized magnetic porous nanocomposite. The dendrimer-functionalized magnetic nanocomposite was characterized by field-emission scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption/desorption isotherms, and vibration sample magnetometer. The obtained results revealed the successful synthesis and functionalization of the... 

Given the emergence of the Internet of Things (IoT) Cyber-Physical Systems (CPSs) and their omnipresence, reducing their power consumption is among the major design priorities. To reduce the power consumption of such systems, we propose the use of a signal-dependent sampling method in a bottom-up fashion, which can lead to up to a 94% reduction in the overall system power with negligible or no loss in performance. Moreover, the proposed technique provides further flexibility for self-aware CPSs to dynamically adjust the number of data samples that are needed for processing (and consequently reduce the power consumption) based on the application at hand and the desired trade-off between...