Partial differential equations modeling of bio-convective sutterby nanofluid flow through paraboloid surface

Design of battery shell stamping parameters for vehicles based on fusion of various artificial neural network models

The application of neural network model in engineering prediction is frequent. The BPE shell material was optimized, and the reliability of the new material was verified by modal simulation. The accuracy of finite element modeling was ensured by constrained mode experiments, and all variables were preprocessed by Latin hypercube sampling. The design parameters were determined by Monte Carlo simulation. Four different neural networks, including back propagation (BP), radial basis function (RBF), extreme learning machine (ELM) and wavelet neural network (WNN), are used to train and learn the dataset. The BPE weight reduction ratio was 14.3%, the stress was reduced by 18.6%, deformation displacement was reduced by 14.2%, and the first-order mode was increased by 29.1%.

Reclamation of iron and copper from BCL slag in Botswana

High-grade copper ores have been depleted over the years, making it a challenge in the mining industry. This investigation focused on a methodology to recover iron (Fe) and copper (Cu) from a copper/nickel slag obtained from the Bamangwato Concession Limited (BCL) mine in Botswana. In this modified flotation approach, the Response Surface Methodology (RSM) was used in conjunction with the Central Composite Design (CCD) and Analysis of Variance (ANOVA) to obtain the best optimal flotation conditions for the recovery of iron and copper. Using the RSM - CCD methodology, the optimal predicted responses were illustrated by a coefficient of determination R2 = 0. 9839 for recovery for Fe and 0.9655 for recovery for Cu. The recovery of copper increased with the increasing dosage of Na2S and collector dosage, while the increase of pH, had a decrease in recovery of copper due to the decline in the stability of the froth, which led to the resistance to form stable bubbles for efficient recovery of copper. Selective flotation of copper and iron was achieved by varying the Na2S dosage to achieve maximum recovery. Under these flotation conditions of PAX (800 g/t), pH (8), -75 μm, sulfurizing agent (Na2S, 1000 g/t), flotation time of 8 min, pH regulator of NaOH and H 2 S O 4 and Methyl Isobutyl Carbinol (MIBC) from the experimental runs merited a grade upgrade of Cu in froth concentrate from 0.581 mass% to 0.884 mass%. An enrichment ratio of 2 was realised, with the recovery of Cu being 62%, whereas Fe in the froth concentrate increased from 69.8 mass% to 71.8 mass%. The main aim was to upgrade the grade and recovery of copper and iron to enhance the recovery for copper and iron in the next experimental stage of leaching.

Effect of non-uniform heat rise/fall and porosity on MHD Williamson hybrid nanofluid flow over incessantly moving thin needle

In this work, a novel enhanced model of the thermophysical characteristics of hybrid nanofluid is introduced. An innovative kind of fluid called hybrid nanofluid has been engineered to increase the heat transfer rate of heat and performance of thermal system. A growing trend in scientific and industrial applications pushed researchers to establish mathematical models for non-Newtonian fluids. A parametric study on theheat transfer and fluid flow of a Williamson hybrid nanofluid based on AA7075-AA7072/Methanol overincessantly moving thin needle under the porosity, Lorentz force, and non-uniform heat rise/fallis performed. Due to similarity variables, the partial differential equations governing the studied configuration undergo appropriate transformation to be converted into ordinary differential equations. The rigorous built-in numerical solver in bvp4c MATLAB has been employed to determine the numerical solutions of the established non-linear ordinary differential equations. It is worthy to note that velocity declines for both AA7075/Methanol nanofluid and AA7075- AA7072/Methanol hybrid nanofluid, but highervelocitymagnitudes occur for theAA7075/Methanol whilethe Williamson fluid parameters increased. It is alsoconcluded that as the porosity parameter isincreased, the flow intensity decreases gradually. It is worthy to note that for both non-uniform heat-rise and fall parameters, the temperature of the fluid gets stronger. Mounting valuesof needle thickness parameter leads to reduction in fluid speed and temperature. It is noticedthat as volume fractions of both types of nanoparticles are augmented then fluidvelocity and temperature amplify rapidly. A Comparison of current and published results is performed to ensure the validity of the established numerical model.

A paradigmatic approach to the molecular descriptor computation for some antiviral drugs

In theoretical chemistry, topological indices are commonly employed to model the physico-chemical properties of chemical compounds. Mathematicians frequently use Zagreb indices to calculate a chemical compound's strain energy, melting point, boiling temperature, distortion, and stability. The current global pandemic caused by the new SARS-CoV-2, also known as COVID-19, is a significant public health concern. Various therapy modalities are advised. The issue has become worse since there hasn't been enough counseling. Researchers are looking at compounds that might be used as SARS and MERS therapies based on earlier studies. In several quantitative structure-property-activity relationships (QSPR and QSAR) studies, a variety of physiochemical properties are successfully represented by topological indices, a sort of molecular descriptor that just specifies numerical values connected to a substance's molecular structure. This study investigates several irregularity-based topological indices for various antiviral medicines, depending on the degree of irregularity. In order to evaluate the effectiveness of the generated topological indices, a QSPR was also carried out using the indicated pharmaceuticals, the various topological indices, and the various physiochemical features of these antiviral medicines. The acquired results show a substantial association between the topological indices being studied by the curve-fitting approach and the physiochemical properties of possible antiviral medicines.