Thermal Conductivity Analysis of Ethylene Glycol/H2O- Based MgFe2O4 Ferrofluid

The current investigation aims to synthesize MgFe2O4 magnetic nanoparticle and measure the thermal conductivity of MgFe2O4 ferrofluid. Prepared MgFe2O4 nanoparticle's structural characterization, the concentration of constituents, and surface morphology were analyzed using XRD, EDAX, and TEM respectively. This study also analyses the influence of magnetic flux on the thermal conductivity of MgFe2O4/ EG: H2O (60:40) based ferrofluids formed by the two-step method. Thermal conductivity of ferrofluid measured at different volume fractions (ranging from 0.01% to 0.20%) show that thermal conductivity augmented with an escalation in volume fraction and the highest enhancement of 10.32% was reached at 0.20% volume fraction. Results indicate that the applied magnetic flux improves the thermal conductivity of ferrofluid from 10.32% to 14.75% at 0.20% volume fraction and 350 Gauss Magnetic flux.

Гибридный металлополимер как потенциальная активная среда оптоакустического генератора

A hybrid material was studied, consisting of polydimethylsiloxane and silver nanoparticles distributed throughout its volume, its optical and thermodynamic characteristics were calculated for different volume fractions of silver content. It is theoretically shown that this material with a volume fraction of silver of about 30% can be used as an active medium for an optoacoustic transducer with an operating frequency range of about 10 MHz.

Tensile and Liquid Absorption Properties of Polyester-based Composites as Alternative Marble Materials

Three polyester-based composite materials were prepared with different volume fractions of three types of fillers (i.e. cement, gypsum and limestone) with the aim of improving the tensile and liquid absorption properties of the former for the synthetic marble industry. The tensile strength, modulus of elasticity, toughness, ductility and liquid absorption percentage of the composites were characterized. Results revealed an increase in the modulus of elasticity, tensile strength and toughness of all prepared composites, as well as a decrease in their ductility, with increasing filler amount. The liquid absorption values of all composites increased with increasing filler content. The composites were able to absorb water extensively but absorbed benzene, kerosene and gasoil minimally.

An Innovative Methodology for Estimating Rock Mechanical Properties from Weight or Volume Fractions of Mineralogy and its Application to Middle East Reservoirs

The influences of mineralogy on rock mechanical properties have profound application in oil and gas exploration and production processes, including hydraulic fracturing operations. In conventional resources, the rock mechanical properties are predominantly controlled by porosity; however, in unconventional tight formations, the importance of mineralogy as a function of rock mechanical properties has not been fully investigated. In unconventional tight formations, mechanical properties are often derived from mineralogy weight fraction together with the best estimate of porosity, assumption of fluid types, the extent of pore fillings, and fluid properties. These properties are then adjusted for their volumetric fractions and subsequently calibrated with acoustics or geomechanical lab measurements. A new method is presented that utilizes mineralogy weight fractions (determined from well logs or laboratory measurements). This process uses public domain information of minerals using Voigt and Reuss averaging algorithms as upper and lower bounds, respectively. An average of these bounds (also known as Hill average) provides a representative value for these parameters. Further, based on isotropic conditions, all the elastic properties are calculated. A typical output consisting of bulk-, shear-, and Young's - modulus, together with Poisson's ratio obtained from traditional methods of volume fractions and this new method using weight fractions is discussed and analyzed along with the sensitivity and the trends for individual rock properties. Furthermore, corresponding strengths, hardness, and fracture toughness could also be estimated using well known public domain algorithms. Data from carbonate reservoirs has been discussed in this work. This method shows how to estimate grain compressibility that can be challenging to be measured in the lab for unconventional tight rock samples. In low-porosity samples, the relative influence of porosity is negligible compared to the mineralogy composition. This approach reduces several assumptions and uncertainties associated with accurate porosity determination in tight rocks as it does not require the amount of pore fluids and fluid properties in calculations. The grain-compressibility and bulk-compressibility (measured by hydrostatic tests in the laboratory on core plugs or calculated from density and cross-dipole log) are used to calculate poroelastic Biot's coefficient, as this coefficient will be used to calculate in-situ principal effective stresses (overburden, minimum horizontal, and maximum horizontal stresses), which are, together with rock properties and pore pressure, constitutes the geomechanical model. The geomechanical model is used for drilling, completions, and hydraulic fracture modeling, including wellbore stability, and reservoir integrity analyses.

Optimization of the TiO2 nanofluid as a coolant in the VVER-1000 nuclear reactor based on the thermal reactivity feedback coefficients via the genetic algorithm

The purpose of this study is to display the neutronic simulation of nanofluid application to reactor core. The variations of VVER-1000 nuclear reactor primary neutronic parameters are investigated by using different volume fraction of nanofluid as coolant. The effect of using nanofluid as coolant on reactor dynamical parameters which play an important role in the dynamical analysis of the reactor and safety core is calculated. In this paper coolant and fuel temperature reactivity coefficients in a VVER-1000 nuclear reactor with nanofluid as a coolant are calculated by using various volume fractions and different sizes of TiO2 (Titania) nanoparticle. For do this, firstly the equivalent cell of the hexagonal fuel rod and the surrounding coolant nanofluid is simulated. Then the thermal hydraulic calculations are performed at different volume fractions and sizes of the nanoparticle. Then, using WIMS and CITATION codes, the reactor core is simulated and the effect of coolant and fuel temperature changes on the effective multiplication factor is calculated. For doing optimization, an artificial neural network is trained in MATLAB using the observed data. The different sizes and various volume fractions are inputs, fuel and coolant temperature reactivity coefficients are outputs. The optimal size and volume fraction is determined using the neural network by implementing the genetic algorithms. In the optimization, volume fraction of 7% and size 77 nm are optimal values.