GA-SVR: a novel hybrid data-driven model to simulate vertical load capacity of driven piles

Piles are widely applied to substructures of various infrastructural buildings. Soil has a complex nature; thus, a variety of empirical models have been proposed for the prediction of the bearing capacity of piles. The aim of this study is to propose a novel artificial intelligent approach to predict vertical load capacity of driven piles in cohesionless soils using support vector regression (SVR) optimized by genetic algorithm (GA). To the best of our knowledge, no research has been developed the GA-SVR model to predict vertical load capacity of driven piles in different timescales as of yet, and the novelty of this study is to develop a new hybrid intelligent approach in this field. To investigate the efficacy of GA-SVR model, two other models, i.e., SVR and linear regression models, are also used for a comparative study. According to the obtained results, GA-SVR model clearly outperformed the SVR and linear regression models by achieving less root mean square error (RMSE) and higher coefficient of determination (R²). In other words, GA-SVR with RMSE of 0.017 and R² of 0.980 has higher performance than SVR with RMSE of 0.035 and R² of 0.912, and linear regression model with RMSE of 0.079 and R² of 0.625.

     

Biohythane production from organic waste: Recent advancements,technical bottlenecks and prospects

The availability of fossil fuels is a major factor that determines the economy of a country. However, possible exhaustion of fossil fuel deposits as well as increased pollution, and other adverse effects on the environment has prompted us to search for alternative fuels. This resulted in the development of hythane, a blend of hydrogen with methane, at concentrations of 10%–30%. The breakdown of organic substrates using sequential dark fermentation (DF) and anaerobic digestion (AD) leads to biohythane production. The quality and quantity of biohythane can be improved by altering the following aspects: selection, development, and/or genetic engineering of suitable microbial consortium; the use of cheap, appropriate substrates; improved design of bioreactors; and the implementation of two-stage fermentation system. This review focusses on the mechanism of biohythane production and the different aspects involved in increasing both its production rate and quality. A comparative study has also been done to demonstrate the superiority of biohythane over other biofuels.     

Biohydrogen production using horizontal and vertical continuous stirred tank reactor- a numerical optimization

This paper illustrates the method to predict the production of biohydrogen and biogas from the horizontal and vertical continuous mixed tank reactor using a numerical approach. Utilization of computational fluid dynamics on the estimation of bioreactor performance is very crucial owing to the uncertainty in the numerical results. Since there has been little work on CFD to determine the influence of hydraulic retention time, impeller speeds, vortex growth, and pH on biohydrogen yield rate the effort had been made. A series of simulations are done with optimal boundary conditions to ensure maximum hydrogen and biogas production rate. Two types of reactors HCSTR and VCSTR are operated at different impeller speed from 40 rpm to 120 rpm. Further, the rate of HRT and organic loading are varied. As the rpm of the impeller increase the rate of hydrogen and biomass production increases not later than 80 rpm. Meanwhile, the optimal range of HRT and pH are 4–8 h and 6.0–8.0. Running the impeller at optimized rate with derived conditions leads to high hydrogen and biogas production of 6 LH₂/Ld and 30 L/d. The obtained results are validated with the experimental findings to compare the uncertainty formed due to the numerical simulations. The optimum boundary condition obtained from the study is expected to provide the essential knowledge in establishing the full-scaled reactors.     

Pretreatment of second and third generation feedstock for enhanced biohythane production: Challenges,recent trends and perspectives

In the context of biofuel production and achieving sustainable bioeconomy, the use of lignocellulosic and algae biomass in anaerobic fermentation processes yields biohythane that has a typical composition of 10–15% H₂, 50–55% CH₄ and 30–40% CO₂. Using organic biomass-based substrates has been shown to minimize environmental impacts due to the versatile production of high-value products under normal operating conditions that are practically achievable. However, the biohythane yield depends on different factors such as the biomass type, the organic loading rate, soluble metabolic products formed, the type of fermentation (single/dual stage) and the pretreatment strategy adopted for the biomass. Different pretreatment strategies based on physical, chemical and biological processes have been proposed in the literature. In this review, improvements in biohythane yield as a result of these pretreatment strategies, the need/effect of inoculum enrichment, the effects of pH, temperature, trace element addition and organic loading rate has been reviewed. Finally, the major developments of improving biohythane yield due to the addition of co-substrates and the current trends are discussed.