Some Comparison of Solutions by Different Numerical Techniques on Mathematical Biology Problem

We try to compare the solutions by some numerical techniques when we apply the methods on some mathematical biology problems. The Runge-Kutta-Fehlberg (RKF) method is a promising method to give an approximate solution of nonlinear ordinary differential equation systems, such as a model for insect population, one-species Lotka-Volterra model. The technique is described and illustrated by numerical examples. We modify the population models by taking the Holling type III functional response and intraspecific competition term and hence we solve it by this numerical technique and show that RKF method gives good results. We try to compare this method with the Laplace Adomian Decomposition Method (LADM) and with the exact solutions

Heat transfer and fluid flow analysis of pebble bed and its verification with artificial neural network

The advancement of sophisticated packed beds has significant implications for the development of new equipment for associated industries. Determining the heat transfer and fluid flow properties of the functional material in the form of a pebble bed is crucial during the design phase of a solid-type ceramic breeding blanket in a fusion reactor. In order to efficiently construct and operate the breeder blanket, the goal of this study is to explore the features of heat transmission and fluid flow. Initially, the heat transfer and fluid flow analyses were carried out independently to benchmark the results using models and experiments using a stainless steel pebble bed with a diameter of 2 mm. Following that, a combined simulation analysis of heat transfer and fluid flow was carried out to demonstrate the system's effective operation for Li2TiO3. A model of an artificial neural network (ANN) has also been employed to forecast the results. The results of simulations are within 5% of the expected values made using ANN

A case study of thermal mixing behavior of hot and cold fluid in T-junction with/without mixing jets

Three-dimensional numerical simulations are performed to study the turbulent mixing of hot and cold fluids at a T-junction with unique branch pipe extended mixing jets. The major aim of the current research is to compare the performance of two distinct designs for thermal mixing and flow characteristics of a T-junction. We investigate the effects of the momentum ratio and temperature difference of mixing fluids on temperature gradients for proposed configurations of T-junctions. The finding demonstrated that a T-junction with jets appears to mix hot and cold fluids more homogeneously. The addition of the mixing jets significantly lessens the internal wall's temperature gradients and improves the efficacy of thermal mixing. The thermal mixing efficiency for T-junctions with mixing jets increased by 25%, 42%, and 50%, respectively. At the same momentum ratio, the length of the thermal mixing in the T-junction with mixing jets is dramatically reduced by 77%, 79%, and 83%. The stress distribution is also determined using thermo-mechanical coupled analysis. The result shows the reduction in peak stresses substantially with the mixing jet T-junction. The current study will help the researcher to evaluate safety issues in high-temperature applications and better understand thermal mixing, flow characteristics, and thermal cracks

Analysis of effective thermal conductivity of pebble bed by artificial neural network and its computational and experimental verification

While dealing with a solid-type ceramic breeding blanket for a fusion reactor, it is critical to determine the basic and thermal properties of the functional material in the form of a pebble bed. In the form of pebbles, lithium ceramics serve as the tritium breeder material in the fusion blanket. Effective thermal conductivity (keff) is one of the important thermal properties for the design and useful parameter to determine the performance of the blanket component. Artificial Neural Networks (ANN) are a popular machine learning technique for tuning between input and output parameters. These networks can learn from examples (data set) and apply them when a homogeneous event arises, making them able to work through genuine-time events. Hence, it can save a lot of time and money for doing repetitive experiments and high-end simulations. This will aid in the creation of a huge database on the pebble bed's keff, which will be useful in the design and development of fusion blankets. The findings of simulations and experiments are compared to those predicted by the ANN model for the pebble bed's thermal conductivity.At IPR, a test setup for experiments has been developed using the steady-state and axial heat flow approach. keff of Li2TiO3 has been measured for the pebbles of diameter of 0.8–1.2 mm having packing fraction of ∼62% and using helium environment at different temperatures ranging from 100 °C to 600 °C at constant atmospheric pressure. keff has been compared with pebble bed of stainless steel pebbles of different diameters (1, 2, 3, 1&3, & 2&3 mm) as well. DDPM-DEM model has been used to generate the pebble bed and ANSYS-CFD simulations using FLUENT have been performed to validate the results. The projected values using ANN are within 5% of the results obtained from simulations and experiments. The details of the DDPM-DEM and ANN models, FLUENT simulations, and experimental results will be discussed in this paper

Effect of hydroxyl content on the physical properties of calcium metaphosphate glasses

The hydroxyl (OH) content of calcium metaphosphate glasses has been controlled in the range 50-800 ppm by melting calcium dihydrogen phosphate in air, under vacuum and with fluoride addition. Density, refractive index and glass transition temperature of the glasses increase with decrease in OH content while the coefficient of thermal expansion remains almost unchanged. With gradual decrease in OH, the UV cutoff initially shifts towards shorter and finally towards longer wavelengths. IR spectroscopic study shows that the OH groups exist exclusively in the hydrogen bonded states, Correlations of the glass properties with OH content have been explained in terms of structural rearrangement leading to the change in P-O bond length and O-P-O/P-O-P bond angles of the PO4 tetrahedral units of (PO3-)(n) chains. These changes are caused due to conversion of non-bridging oxygens (NBOs) of the H-bonded OH groups into bridging oxygens (BOs) during progress of dehydroxylation

Pool Boiling Amelioration by Aqueous Dispersion of Silica Nanoparticles

Non-metallic oxide nanofluids have recently attracted interest in pool boiling heat transfer (PBHT) studies. Research work on carbon and silica-based nanofluids is now being reported frequently by scholars. The majority of these research studies showed improvement in PBHT performance. The present study reports an investigation on the PBHT characteristics and performance of water-based silica nanofluids in the nucleate boiling region. Sonication-aided stable silica nanofluids with 0.0001, 0.001, 0.01, and 0.1 particle concentrations were prepared. The stability of nanofluids was detected and confirmed via visible light absorbance and zeta potential analyses. The PBHT performance of nanofluids was examined in a customized boiling pool with a flat heating surface. The boiling characteristics, pool boiling heat transfer coefficient (PBHTC), and critical heat flux (CHF) were analyzed. The effects of surface wettability, contact angle, and surface roughness on heat transfer performance were investigated. Bubble diameter and bubble departure frequency were estimated using experimental results. PBHTC and CHF of water have shown an increase due to the nanoparticle inclusion, where they have reached a maximum improvement of ≈1.33 times over that of the base fluid. The surface wettability of nanofluids was also enhanced due to a decrease in boiling surface contact angle from 74.1° to 48.5°. The roughness of the boiling surface was reduced up to 1.5 times compared to the base fluid, which was due to the nanoparticle deposition on the boiling surface. Such deposition reduces the active nucleation sites and increases the thermal resistance between the boiling surface and bulk fluid layer. The presence of the dispersed nanoparticles caused a lower bubble departure frequency by 2.17% and an increase in bubble diameter by 4.48%, which vigorously affects the pool boiling performance

sj-docx-1-pie-10.1177_09544089221128472 - Supplemental material for Thermophysical and transient heat transfer characteristics of aqueous SiO₂ nanofluid in energy management applications

Supplemental material, sj-docx-1-pie-10.1177_09544089221128472 for Thermophysical and transient heat transfer characteristics of aqueous SiO2 nanofluid in energy management applications by Sayantan Mukherjee, Smita Rani Panda, Purna Chandra Mishra, Swarnendu Sen and Paritosh Chaudhuri in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p