A comprehensive review of renewable energy resources for electricity generation in Australia

Recently, renewable energy resources and their impacts have sparked a heated debate to resolve the Australian energy crisis. There are many projects launched throughout the country to improve network security and reliability. This paper aims to review the current status of different renewable energy resources along with their impacts on society and the environment. Besides, it provides for the first time the statistics of the documents published in the field of renewable energy in Australia. The statistics include information such as the rate of papers published, possible journals for finding relative paper, types of documents published, top authors, and the most prevalent keywords in the field of renewable energy in Australia. It will focus on solar, wind, biomass, geothermal and hydropower technologies and will investigate the social and environmental impacts of these technologies.     

Green synthesis of zinc oxide nanoparticles using Amygdalus scoparia Spach stem bark extract and their applications as an alternative antimicrobial,anticancer, and anti-diabetic agent

For the first time in this study, Zinc oxide nanoparticles were biosynthesized by the eco-friendly and cost-effective procedure using Amygdalus scoparia stem bark extract then used as antibacterial, antifungal, anticancer, and anti-diabetic agents. The characterization techniques confirmed the biosynthesis, crystalline nature, structure, size, elemental composition of ZnO NPs and bioactive compounds that exist in A. scoparia extract accounting for Zn²⁺ ion reduction, capping and stabilization of ZnO NPs. The ZnO NPs displayed remarkable inhibitory activity against E. coli, E. aerigenes, S. aureus, P. oryzae, F. thapsinum, and F. semitectum compared to antibiotic standards. The ZnO NPs showed significant inhibitory effects on cancer cell lines, while it had no toxic effect on Vero normal cell line. The ZnO NPs (30 mg/kg)-treated diabetic rats showed significantly higher levels of insulin and lower AST, ALT and blood glucose compared with the STZ induced diabetic group and other treated groups (P < 0.05). The ZnO NPs- and extract-treated rats showed significantly higher levels of IR, GluT2, and GCK expression and lower TNFα expression compared with the STZ induced diabetic rats. Our findings showed that ZnO NPs represented an outstanding performance for biological applications.     

Taguchi Optimization of Solvent-Antisolvent Crystallization to Prepare Ammonium Perchlorate Particles

The sphericity and size of ammonium perchlorate (AP) particles significantly influence the properties of composite propellants. As the AP particles become more spherical, the accumulation coefficient increases, the viscosity during casting decreases, and the particle loading and burning rate increase. Hence, the production of micronized AP particles with an average size between 1 and 20 μm is important to increase the loading percentage of AP in the composite propellant. Here, the Taguchi experimental design was used to optimize the solvent-antisolvent crystallization (SAC) process for the preparation of micronized AP particles with higher sphericity. SAC parameters such as the type of antisolvent, the solvent-to-antisolvent ratio, the antisolvent temperature, the stirring speed, and the retention time were investigated at four levels. The type of antisolvent and the solvent-to-antisolvent ratio were found to mainly contribute to improving the sphericity and size of the AP particles, respectively.     

Neuroscience and architecture: What does the brain tell to an emotional experience of architecture via a functional MR study?

Environment psychologically affects individuals. According to the base of cognitive psychology, there is a direct relationship between human behavior, environment, and emotional process. Assuming that pleasantness and unpleasantness are associated with peripheral nervous system activation, the current study aims to explore if the pleasant or unpleasant architectural places can stimulate the brain regions engaged in emotions or not. As the main contribution, we used functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) changes to effectively detect the brain's region that mainly responds to the emotional-perceptual processes. Based on the results of examining the emotional assessment model of “Pleasure-Arousal” applied to 140 students, 30 most-rated images representing 15 pleasant and 15 unpleasant places were shown to 32 participants in a 1.5-T MRI scanner. After applying standard preprocessing steps (re-alignment, slice-timing, co-registration, segmentation, normalization, and smoothing) to functional MR images, first-level analysis was applied to each subject. The results were evaluated using statistical corrections at different levels for female and male participants with the second-level analysis. In conclusion, it has been shown that there is a significant linkage between environmental experience and brain activation so that the architectural qualities can change blood flow in specific brain regions.     

An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Removal of bisphenol A and 17α-ethinyl estradiol from landfill leachate using single-walled carbon nanotubes

In this study, the adsorption of bisphenol A (BPA) and 17α-ethinyl estradiol (EE2) from landfill leachate onto single-walled carbon nanotubes (SWCNTs) was investigated. Different leachate solutions were prepared by altering the pH, ionic strength, and dissolved organic carbon (DOC) in the solutions to mimic the varying water conditions that occur in leachate during the various stages of waste decomposition. The youngest and oldest leachate solutions contained varying DOC and background chemistry and were represented by leachate Type A (pH = 5.0; DOC = 2500 mg/L; conductivity = 12,500 μS/cm; [Ca²⁺] = 1200 mg/L; [Mg²⁺] = 470 mg/L) and Type E (pH = 7.5; DOC = 250 mg/L; conductivity = 3250 μS/cm; [Ca²⁺] = 60 mg/L; [Mg²⁺] = 180 mg/L). These solutions were subsequently combined in different ratios to produce intermediate solutions, labeled B-D, to replicate time-dependent changes in leachate composition. Overall, a larger fraction of EE2 was removed as compared to BPA, consistent with its higher log K_OW value. The total removal of BPA and EE2 decreased in older leachate solutions, with the adsorptive capacity of SWCNTs decreasing in the order of leachate Type A > Type B > Type C > Type D > Type E. An increase in the pH from 3.5 to 11 decreased the adsorption of BPA by 22% in young leachate and by 10% in old leachate. The changes in pH did not affect the adsorption of EE2 in the young leachate, but did reduce adsorption by 32% in the old leachate. Adjusting the ionic strength using Na⁺ did not significantly impact adsorption, while increasing the concentration of Ca²⁺ resulted in a 12% increase in the adsorption of BPA and a 19% increase in the adsorption of EE2. DOC was revealed to be the most influential parameter in this study. In the presence of hydrophilic DOC, represented by glucose in this study, adsorption of the endocrine disrupting compounds (EDCs) onto the SWCNTs was not affected. In the absence of SWCNTs, hydrophobic DOC (i.e., humic acid) adsorbed 15-20% of BPA and EE2. However, when the humic acid and SWCNTs were both present, the overall adsorptive capacity of the SWCNTs was reduced. Hydrophobic (π-π electron donor-acceptor) interactions between the EDCs and the constituents in the leachate, as well as interactions between the SWCNTs and the EDCs, are proposed as potential adsorption mechanisms for BPA and EE2 onto SWCNTs.     

Predicting the compressibility factor of natural gas

Knowing compressibility factor (z-factor) values of natural gases is the basis of most petroleum engineering calculations. Shortage of available experimental data for the specified composition, temperature, and pressure conditions encourages researchers to propose efficient equations for calculating z-factor values.

This investigation presents a useful empirical model for determining natural gases compressibility factor values. The advantages of this correlation are that it is explicit in terms of z-factor and the results of calculating compressibility factor values by this method reveal the supremacy of the new equation over the other widely used correlations.     

Equivalent linear model for fully self‐centering earthquake‐resisting systems

Modern rocking and stepping cores have been known as the efficient self‐centering earthquake‐resisting systems (SC‐ERSs). The current article proposes an approximate equivalent linear (EL) model for rapid estimation of the SC‐ERS displacement. An equivalent damping ratio and effective stiffness are formulated for flag‐shaped hysteresis of a fully SC‐ERS. The approximate EL model is first established using secant stiffness and Jacobsen's damping model. Nonlinear response history analyses are carried out to compare exact and approximated peak displacements. Findings reveal that EL analysis of the SC‐ERS based on Jacobsen's damping leads to underestimation of the maximum inelastic displacement. Accordingly, a new optimal damping formula is proposed using a genetic algorithm and nonlinear regression analyses. The improved EL model is validated by practical examples, and the results show acceptable accuracy in design‐level displacement estimation.     

Permeability prediction and construction of 3D geological model: application of neural networks and stochastic approaches in an Iranian gas reservoir

Determination of petrophysical parameters by using available data has a specific importance in exploration and production studies for oil and gas industries. Modeling of corrected permeability as a petrophysical parameter can help in decision making processes. The objective of this study is to construct a comprehensive and quantitative characterization of a carbonate gas reservoir in marine gas field. Artificial neural network is applied for prediction of permeability in accordance with other petrophysical parameters at well location. Correlation coefficient for this method is 84 %. In the study, the geological reservoir model is developed in two steps: First, the structure skeleton of the field is constructed, and then, reservoir property is distributed within it by applying new stochastic methods. Permeability is modeled by three techniques: kriging, sequential Gaussian simulation (SGS) and collocated co-simulation using modeled effective porosity as 3D secondary variable. This paper enhances the characterization of the reservoir by improving the modeling of permeability through a new algorithm called collocated co-simulation. Kriging is very simple in modeling the reservoir permeability, and also, original distribution of the data changes considerably in this model. In addition, the SGS model is noisy and heterogeneous, but it retains the original distribution of the data. However, the addition of a 3D secondary variable in third method resulted in a much more reliable model of permeability.     

Numerical Investigation of Magnetic Field Effect on Heat Transfer and Entropy Generation in Channel; New Approach for Fluid and Length Scale Selections

In the present study, heat transfer and entropy generation of developing KOH-water solution is numerically examined by implementing a finite difference code to solve the governing equations. Effects of important parameters of heat transfer in both of the developing and fully developed regions are examined. The study reveals that alteration of the existing parameters could have considerable effects on the contribution of the heat transfer, friction, and magnetic field on the total entropy generation. Novelty of the present study lies on the proper fluid and length scale selection procedure which is adopted before the solution, being a guideline for the future fluid flow and heat transfer studies in the magneto-hydrodynamics (MHD). The investigations show that performing a study in the MHD flow of water base nanofluids in the length scales smaller than 0.1 m is not physically feasible, because the required magnetic field intensity is higher than the maximum generated by continuous fields.