Flow assurance in pipeline in presence of hydrate / Sheida Shahnazar Nezhad Khalesi

At low temperature and high pressure thermodynamic conditions, if certain guest molecules are trapped in water cages, non-stoichiometric ice-like particles named as “hydrate”, can be formed. Hydrates formation and the associated slugging or clogging of transportation pipeline are major concerns to oil and gas industry. Safety concern associated with transport line blockage perhaps is the most significant reason for understanding hydrate. Over the history of gas and oil transportation there have been many equipment damage accidents or even personnel injury due to hydrate plug formation. The most common preventive tool for hydrate occurrence is injection of thermodynamic inhibitor such as mono-ethylene glycol (MEG) and methanol as the most utilized chemical. However, during transportation and storage of natural gas, the throughout prevention of hydrate formation is often impractical or too expensive to be accomplished. Thus, engineers are shifting their attention to managing hydrate particles in flow rather than completely preventing their formation based on this fact that hydrate risk management is considerably more economical than trying to keep flow condition out of hydrate formation region. Hydrate risk management by the slurry flow method is an approach which was recently proposed to industry. Therefore, the theoretical works which are done in this area are extremely limited. Hence, flow assurance partners of offshore projects are not willing to use “Cold Flow Technology” yet which is a method that allows the formation of hydrate while assuring its flow ability. Therefore, it seems vital to improve the hydrate slurry flow models in order to encourage industry to utilize this technique as a less expensive and more environmental friendly method. This study discussed available models and compared their various solutions. In this project, gas-slurry one dimensional flow is coupled with hydrate kinetic model in order to investigate the flow behavior of liquid-solid-gas in pipeline. First, two models are developed for estimating hydrate equilibrium condition and is compared to some of the most popular techniques. This part is of great importance because it reveals the exact length of pipeline where hydrate forms. As the next step, two phases are assumed: the first phase is continuous oil with dispersed water particles in it, and the second phase is gas. The conversion of gas molecules to hydrate solid particles is modeled via the most suitable hydrate crystal kinetic model. Several kinetic models are developed over the past decades, both mass transfer and heat transfer limited models. The most suitable one should be picked based on the case studies and be coupled with flow equations. The two-phase flow model is solved by numerical techniques and predicts the pressure drop of the pipe zone where the flow condition falls beyond hydrate curve and its formation occurs. Then the velocity decrease and pressure drop is calculated and the flow is characterized under hydrate formation condition

Study of HLA-A, B, C alloantigens in a population of the Isfahan province

A random panel of 500 healthy unrelated subjects from Isfahan province were HLA typed for A, B and C locus antigens. The lymphocytes were separated from 5 ml of whole peripheral blood and HLA-A, B, C typing were performed on them, using the standard two stage microlymphocytotoxic NIH technique. The antigens HLA-A1, A2, A3, A9, HLA-B5, B35, HLA-CW4 had the higher frequency than other HLA antigens among the population studied. The distribution of HLA class I antigens in Isfahan is similar with their distribution in Tehran and Mashhad

Progress on synthesis, functionalisation and applications of graphene nanoplatelets

Carbon is the fifteenth most abundant element in Earth's crust, and the fourth most abundant element in the universe. Carbon nanostructures, or nanocarbons, i.e. the low-dimensional nanomaterials, are being extensively researched for the past two decades because of their unique structure and electronic properties, prompting a huge interest in its fundamental research and applications in molecular electronics, materials science, energy storage and conversion, bio-medicine, sensing, and bio-sensing. Graphene was recently touted as a wonder material, because of its high-mechanical strength, high-electron mobility, lightness, flexibility, single-atom thickness, and near-transparency. These properties make graphene a very promising material for composites, thin films, electromagnetic shielding, barrier films, and sensors. This review focuses on the latest progress on the preparation and functionalisation of graphene nanoplatelets, and discusses its potential applications, future prospects, and challenges in the context of theranostic applications

Proposing Of A New Soft Computing-Based Model To Predict Peak Particle Velocity Induced By Blasting

Estimation of ground vibration induced by blasting operations is an important task to control the safety issues at the surface mines and civil projects. By reviewing the previous studies, some empirical and soft computing models have been proposed to estimate blast-induced ground vibrations. The main goal of this research is to propose a new predictive model in the field of ground vibration estimation. For this aim, the group method of data handling (GMDH) model which is a type of neural network, is proposed with respect to input parameters including the stemming length, powder factor, burden to spacing ratio, distance from the blast-face, blast-hole depth and maximum charge per delay. Also, the peak particle velocity, as the most common descriptor for evaluating the ground vibration, was selected as the output. The required datasets were collected from a quarry in Penang, Malaysia, using 102 blasting operations. Several criteria such as root mean square error (RMSE) and coefficient of determination (R2) were utilized to determine the reliability of the GMDH. Based on the obtained results, the GMDH forecasting technique with R2 of 0.911 and RMSE of 0.889 can be presented as a powerful technique in predicting the blast-induced ground vibration

Structure, mechanism, and performance evaluation of natural gas hydrate kinetic inhibitors

Ice-like crystal compounds, which are formed in low-temperature and high-pressure thermodynamic conditions and composed of a combination of water molecules and guest gas molecules, are called gas hydrates. Since its discovery and recognition as the responsible component for blockage of oil and gas transformation line, hydrate has been under extensive review by scientists. In particular, the inhibition techniques of hydrate crystals have been updated in order to reach the more economically and practically feasible methods. So far, kinetic hydrate inhibition has been considered as one of the most effective techniques over the past decade. This review is intended to classify the recent studies regarding kinetic hydrate inhibitors, their structure, mechanism, and techniques for their performance evaluation. In addition, this communication further analyzes the areas that are more in demand to be considered in future research

A new developed approach for the prediction of ground vibration using a hybrid PSO-optimized ANFIS-based model

Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R2) of 0.984] performed better than the ANFIS with RMSE of 1.61 and R2 of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations