Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

     

Oligomeric Composition of Polyols From Fatty Acid Methyl Ester: The Effect of Ring‐Opening Reactants of Epoxide Groups

Commercial availability of fatty acid methyl ester (FAME) from palm oil targeted for biodiesel offers a good feedstock for the production of structurally well‐defined polyols for polyurethane applications. The effect of molecular weight (MW), odd and even carbon numbers, and the linear and branched structure reactants used in the ring‐opening reaction of epoxidized fatty acid methyl ester (E‐FAME) on the properties of polyols was investigated. Conversions of E‐FAME to PolyFAME polyols were confirmed by Fourier transform infrared analysis, oxirane oxygen content, and hydroxyl number. Gel permeation chromatography (GPC) calibrated against polyether polyols as a standard and vapor pressure osmometry were used for MW determination. GPC chromatograms of PolyFAME polyols clearly demonstrated the formation of oligomers during ring‐opening reactions. MW, and odd and even carbon numbers in a structure of linear diols and branched diol used in the syntheses of PolyFAME polyols did not have an effect on crystallinity, glass transition, or melt temperatures measured using Differential scanning calorimetry (DSC). PolyFAME polyols ring‐opened with water, methanol, and 1,2‐propanediol contained secondary hydroxyl groups, whereas PolyFAME polyols ring‐opened with linear diols contained a mixture of primary and secondary hydroxyl groups. It was found that the concentration of primary hydroxyl groups increased significantly by increasing the number of carbons from C2 to C3 in the linear diols. The viscosity of PolyFAME polyols also increased with the MW of linear diols used in the E‐FAME ring‐opening reaction. These findings would be beneficial for formulators in choosing the most cost effective polyols for polyurethane formulations.     

High-Performance Nanocatalyst for Adsorptive and Photo-Assisted Fenton-Like Degradation of Phenol: Modeling Using Artificial Neural Networks

High-performance activated carbon-zinc oxide (Ac–ZnO) nanocatalyst was fabricated via the microwave-assisted technique. Ac–ZnO was characterized and the results indicated that Ac–ZnO is stable, had a band gap of 3.26?eV and a surface area of 603.5?m²g^?1, and exhibited excellent adsorptive and degrading potentials. About 93% phenol was adsorbed within 550?min of reaction by Ac–ZnO. Impressively, a complete degradation was achieved in 90?min via a photo-Fenton/Ac–ZnO system under optimum conditions. An artificial neural network (ANN) model was developed and applied to study the relative significance of input variables affecting the degradation of phenol in a photo-Fenton process. The ANN results indicate that increases in both H₂O₂ and Ac–ZnO dosage enhanced the rate of phenol degradation. The highest rate constant at the optimum conditions was 0.093?min^?1 and it was found to be consistent with the ANN-predicted rate constant (0.095?min^?1).     

Modelling study of an upflow microbial fuel cell catalysed with anaerobic aged sludge

An electrochemical model for an upflow dual-chambered microbial fuel cell (MFC) process is proposed in this study. The model was set up on the basis of the experimental results and the analysis of biochemical and electrochemical processes in the MFC biocatalysed with anaerobic aged sludge and alternatively fuelled with a synthetic acetate-based and actual domestic wastewaters. Simulation of the process shows that the model describes the process reasonably well with correlation coefficients higher than 0.97. The analysis of model simulation illustrates how the current output depends mainly on the substrate concentration as well as other main variables. The relationship between the current output and over-voltage is revealed by the modelling study. For acetate-based wastewaters with initial chemical oxygen demand (COD) concentrations of 350, 700, 1050, and 1400 mg/L, maximum observed power densities were 290, 405, 448, and 525 mW/m² associated with maximum COD removals of 84%, 88%, 83%, and 82%, respectively.     

Effect of wettability on oil recovery and breakthrough time for immiscible gas flooding

The effect of wettability on oil recovery at higher water saturation is still not fully understood, especially in the case of mixed wettability. This study was conducted to examine the effects of wettability on oil recovery and breakthrough time through experiments for two wettability conditions (water-wet and mixed-wet) and three water saturations (20%, 40%, and 60%). Clashach sandstone core with a porosity of 12.8% and a permeability of 75 md was utilized as the porous media. Immiscible gas flooding was performed by injecting nitrogen gas into the core at room temperature and pressure. The results showed 54.3% and 48.8% of the initial oil in place (IOIP) as the ultimate oil recovery at 40% water saturation from mixed-wet core and water-wet core respectively. In contrast, the water-wet core displayed better results (32.6% of the IOIP) in terms of breakthrough time compared to the results of water-wet core (10.6% of the IOIP) at the same water saturation. In conclusion, oil recovery was found highly dependent on water saturation while breakthrough time was mainly affected by the wettability of the cores.     

Analysis of heavy metal pollution in soil using transversely excited atmospheric CO2 laser-induced plasma by trapping the soil in microstructured holes on metal subtargets

A unique technique for direct analysis of soil samples utilizing a special advantage of a transversely excited atmospheric (TEA) CO(2) laser-induced plasma generated at atmospheric pressure on a metal target has been developed. In this technique, a metal subtarget, such as nickel plate, structured with intentional microholes on its surface, each with dimensions of around 100 microm in diameter and depth, was used to selectively trap small sized soil particles by immersing the metal plate subtarget into the polluted soil sample. The trapped small soil particles on the metal subtarget were irradiated by a TEA CO(2) laser (10.6 microm, 1.5 J, 200 ns) at atmospheric pressure under defocused condition with a spot size of 3 mm x 3 mm. This trapping and confining scheme substantially suppresses the blowing off effect; thus, the trapped soil particles can effectively be dissociated and atomized in the microstructured holes. Using this method of a microstructured metal plate subtarget, quantitative analysis was carried out on loam soil samples polluted by Pb. A linear calibration curve was obtained with a detection limit of approximately 50 mg/kg. Preliminary quantitative studies were carried out for a quartz sand sample containing Cr and Hg, resulting in linear calibration curves with detection limits of approximately 25 mg/kg and 10 mg/kg, respectively, at this stage. This technique is promising as a potential field screening tool for soil analysis.     

An integrated technique using solar and evaporation ponds for effective brine disposal management

Desalination is a process that involves the removal of salts and non-ionic minerals from seawater to produce freshwater that is fit for human consumption. This process produces brine, which is typically redisposed into the sea. The relatively high salt concentration in the disposed brine increases the salinity of water and soil, which adversely affects the environment. However, brine is found to be rich in economically valuable minerals. In order to effectively manage the disposed brine, this study proposes an integrated technique using solar and evaporation ponds to filter valuable minerals from concentrated brine. The results of this study demonstrate that the proposed technique can be effectively employed for this purpose. Furthermore, this helps reduce desalination costs and complies with the notion of renewable energy production and eco-friendliness.     

Radiation modelling and performance evaluations of fixed,single- and double-axis tracking surfaces: a case study for Dhahran city,Saudi Arabia

This work overviews the solar radiation basics and insolation of different surfaces is presented. A complete solar radiation modelling and investigation on the effect of horizontal plate, yearly tilt, monthly tilt, and single-axis and double-axis tracking surface on the insolation are carried out to conduct performance evaluation using the case study in Dhahran city of Saudi Arabia. The increments received by insolation for the yearly tilt, monthly tilt, and single-axis and dual-axis tracking surface with respect to traditional flat-plate collector is estimated. The results show that the yearly optimal tilt angle due to the south is close to the 0.913 time latitude of Dhahran. It is found that the yearly irradiation gains using yearly and monthly optimal tilts relative to flat panel installation are 7% and 14%, respectively. The yearly insulation gains made by single-axis and dual-axis continuous tracking surfaces are 33% and 48%, respectively.     

Effects of Nonthermal Plasma Technology on Functional Food Components

Understanding the impact of nonthermal plasma (NTP) technology on key nutritional and functional food components is of paramount importance for the successful adoption of the technology by industry. NTP technology (NTPT) has demonstrated marked antimicrobial efficacies with good retention of important physical, chemical, sensory, and nutritional parameters for an array of food products. This paper presents the influence of NTPT on selected functional food components with a focus on low‐molecular‐weight bioactive compounds and vitamins. We discuss the mechanisms of bioactive compound alteration by plasma‐reactive species and classify their influence on vitamins and their antioxidant capacities. The impact of NTP on specific bioactive compounds depends both on plasma properties and the food matrix. Induced changes are mainly associated with oxidative degradation and cleavage of double bonds in organic compounds. The effects reported to date are mainly time‐dependent increases in the concentrations of polyphenols, vitamin C, or increases in antioxidant activity. Also, improvement in the extraction efficiency of polyphenols is observed. The review highlights future research needs regarding the complex mechanisms of interaction with plasma species. NTP is a novel technology that can both negatively and positively affect the functional components in food.     

Measurement of concrete strength using the emission intensity ratio between Ca(II) 396.8 nm and Ca(I) 422.6 nm in a Nd:YAG laser-induced plasma

An experiment to investigate the potential of a laser-induced plasma method for determining concrete compressive strength was conducted by focusing a Nd:YAG laser on concrete samples with different degrees of compressive strength. This technique was developed in light of the role of the shock wave in the generation of a laser-induced plasma. It was found that the speed of the shock front depends on the hardness of the sample. It was also found that a positive relationship exists between the speed of the shock front and the ionization rate of the ablated atoms. Hence, the ratio of the intensity between the Ca(II) 396.8 nm and Ca(I) 422.6 nm emission lines detected from the laser-induced plasma can be used to examine the hardness of the material. In fact, it was observed that the ratio changes with respect to the change in the concrete compressive strength. The findings also show that the ratio increases with time after the cement is mixed with water.