Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

An array-compensated spherical reflector antenna for a very large number of scanned beams

There are many stringent demands imposed on the applications of spaceborne antenna systems. One of the most challenging demands is the generation of multiple beams with the ability to scan a very large number of beamwidths. Since the parabolic reflectors have limitations in this application, a 35-m spherical reflector antenna is proposed for a geostationary radar antenna at Ka-band (35.6 GHz) due to its inherent capability of scanning the beams to very large number of beamwidths. The utility of using planar array feeds for correcting spherical phase aberrations is investigated to overcome the performance degradation effects. Two different methodologies are developed for the array excitation coefficients determination based on phase conjugate matching and the results are compared. Using the compensating feed array, the radiation characteristics of the compensated spherical reflector are simulated for no scan and large scan cases and the results are compared with the uncompensated case to show performance improvement. In order to demonstrate the technological readiness of the concept a 1.5-m breadboard model is designed to be built for experimental measurements. Some important mechanical design tolerances and realistic array feed topologies are investigated. The antenna concept developed in this paper is advocated to be used in the next generation of geostationary satellite antenna systems for remote sensing radar applications.     

Weekly storage of coolness in heavy brick and adobe walls

Weekly storage of coolness in heavy walls (walls with large thermal inertia or large characteristic time constants or low Fourier numbers) was investigated numerically by considering one-dimensional heat conduction through the walls. The study consisted of first analyzing the heat flow through a single wall and considering various boundary conditions on the inside. The boundary conditions were: constant inside air tempeture throughout the day, variable inside air temperature on a 24-hour cycle, and variable inside air temperature on a 48-hour cycle. Next, the heat flow through walls was studied through a thermal network analysis of a simple building. In this case it was assumed that the ambient air temperature (following a periodic distribution) was increased suddenly and followed this new distribution for many days thereafter.It was concluded that walls with high thermal inertia or time constant can store coolness for several days. The larger the time constant of the wall (for example adobe as compared with brick) the longer it takes for the wall temperature to reach a steady periodic distribution after the change has occurred. However, because of low thermal conductivity of adobe, the retrieval of the stored coolness in these walls is slow, and the mean daily temperature of the room air in the adobe building does not change appreciably beyond seven days after the change. Increase of the wall thickness beyond 50 cm does not improve the thermal performance of the building significantly.     

Hot-nanoparticle-mediated fusion of selected cells

Complete fusion of two selected cells allows for the creation of novel hybrid cells with inherited genetic properties from both original cells.Alternatively,via fusion of a selected cell with a selected vesicle,chemicals or genes can be directly delivered into the cell of interest,to control cellular reactions or gene expression.Here,we demonstrate how to perform an optically controlled fusion of two selected cells or of one cell and one vesicle.Fusion is mediated by laser irradiating plasmonic gold nanoparticles optically trapped between two cells (or a vesicle and a cell) of interest.This hot-particle-mediated fusion causes total mixing of the two cytoplasms and the two cell membranes resulting in formation of a new hybrid cell with an intact cell membrane and enzymatic activity following fusion.Similarly,fusion between a vesicle and a cell results in delivery of the vesicle cargo to the cytoplasm,and after fusion,the cell shows signs of viability.The method is an implementation of targeted drug delivery at the single-cell level and has a great potential for cellular control and design.     

Prediction of carbon dioxide separation from gas mixtures in petroleum industries using the Levenberg–Marquardt algorithm

In this study, two mathematical models for hydrate formation process to separate carbon dioxide by a combination of two different kinds of organic and surfactant promoters are presented. Promoters such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate, and dodecyl trimethyl ammonium chloride as surfactant promoters; also, tetrahydrofuran, cyclopentane, 1,3-dioxolane, and 2-methyl tetrahydrofuran as organic promoters have been used in recent years. The results showed that a combination of 3000 ppm of surfactant promoters and 4 wt% organic promoters had the highest separation rate of carbon dioxide and; consequently, the investigated models were based on this optimum condition. As a matter of fact, by using these simulations the hydrate formation behavior was predicted with high accuracy; moreover, conducting consuming experiments is not essential anymore. To sum up, in the present research both Vandermonde matrix model and Levenberg-Marquardt algorithm were applied to predict the hydrate formation behavior; in addition, their results were precisely considered and validated with experimental data.     

Asphaltene precipitation and deposition in oil reservoirs – Technical aspects,experimental and hybrid neural network predictive tools

Precipitation of asphaltene is considered as an undesired process during oil production via natural depletion and gas injection as it blocks the pore space and reduces the oil flow rate. In addition, it lessens the efficiency of the gas injection into oil reservoirs. This paper presents static and dynamic experiments conducted to investigate the effects of temperature, pressure, pressure drop, dilution ratio, and mixture compositions on asphaltene precipitation and deposition. Important technical aspects of asphaltene precipitation such as equation of state, analysis tools, and predictive methods are also discussed. Different methodologies to analyze asphaltene precipitation are reviewed, as well. Artificial neural networks (ANNs) joined with imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) are employed to approximate asphaltene precipitation and deposition with and without CO₂ injection. The connectionist model is built based on experimental data covering wide ranges of process and thermodynamic conditions. A good match was obtained between the real data and the model predictions. Temperature and pressure drop have the highest influence on asphaltene deposition during dynamic tests. ICA-ANN attains more reliable outputs compared with PSO-ANN, the conventional ANN, and scaling models. In addition, high pressure microscopy (HPM) technique leads to more accurate results compared with quantitative methods when studying asphaltene precipitation.     

The effects of post annealing on the mechanical properties, microstructure and texture evolutions of pure copper deformed by twist extrusion process

X-ray diffraction peak broadening analysis showed that performing a proper heat treatment between the twist extrusion passes of commercially pure copper decreased the coherent domain size and increased the microstrain. Moreover, SEM micrographs illustrated that annealed material contained new formed grains that could not grow due to lack of sufficient time. Under such circumstances, the ultimate strength was elevated about 45 MPa. The deformed material showed texture of simple shear deformation, changing by applying the post annealing.     

Prediction of bulk modulus and volumetric expansion coefficient of water for leak tightness test of pipelines

To determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks, the calculation of pressure/temperature changes is required for test sections. In these calculations, bulk modulus and volumetric expansion coefficient of fresh or sea water must be taken into account. In this study, a simple-to-use correlation is developed to predict the bulk modulus and volumetric expansion coefficient of both fresh and sea water as a function of temperature and pressure. The proposed correlation helps to cover the bulk modulus and volumetric expansion coefficient of both fresh and sea water for temperatures less than 50 °C (40 °C for sea water) as well as pressures up to 55,000 kPa (550 bar). The results can be used in follow-up calculations to determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks. The proposed correlation showed promising results with average absolute deviations for volumetric expansion coefficient and bulk modulus of water being around 0.58% and 0.08% respectively. The novel correlation is easy to use and will prove to be of immense value for project engineers to test the critical limits accurately.     

An adaptive latency mitigation scheme for massively multiuser virtual environments

As massively multiuser virtual environments (MMVEs) expand in terms of size and user population, they tend toward using P2P architectures as a way to provide scalability without the need for large centralized resources. Distributed hash table (DHT)-based networks have been introduced as a promising option for overlay-based distributed massively multiuser virtual environment applications. However, overlay latency stretch seriously affects MMVE performance where QoS is crucial for real-time user collaboration. This work includes a series of efforts in the alleviation of such undesired latency. Our approach to latency mitigation consists of two phases. First, we propose a position-based ID assignment approach to minimize message hop-count by exploiting the clustered pattern of traffic exchange among MMVE users. Second, we introduce a new ant-based distributed neighbor selection scheme that can be used by MMVE users to select the best neighbors within their areas of interest. In order to evaluate the performance of this heuristic approach, we model the neighbor selection problem in the form of a network flow problem and use its solution as an optimality bound to compare the results. Simulation results demonstrate that the proposed algorithms will compensate for DHT latency stretch to a high extent and the performance of the resulting system would closely follow the optimal bound while communication overhead is negligible.     

A comparative study between gravel and rubber drainage columns for mitigation of liquefaction hazards

Liquefaction is one of the most destructive natural hazards that cause damage to engineering structures during an earthquake. This study aims to examine the effect of rubber and gravel drainage columns on the reduction of liquefaction potential of saturated sandy soils using a shaking table. Experiments were carried out in various conditions such as construction materials, different arrangements and diameters of drainage columns. Effects of the relative density and the input motion on the base test were investigated as well. The results demonstrate that rubber drainage columns have slightly better performance compared to gravel drainage columns at high relative density and high input acceleration. Soil improvement using gravel drainage columns, which leads to reduction in liquefaction effects at moderate input acceleration and low relative density, is a more effective method than that using rubber drainage columns. By increasing the number and diameter of gravel and rubber drainage columns, deformations due to liquefaction are reduced. The drainage rate of gravel drains is higher than that of rubber drains after shaking. Totally, the outcomes indicate that densification is the most important factor controlling liquefaction.