Volume 18, Issue 2

An integrated novel approach employing the Taguchi method and Aspen Plus software has been applied to evaluate a new configuration for the industrial process of Zn + Pb + Cu recovery from sphalerite ore, in order to minimize the toxic gas emission. The optimum operating condition achieved by the Taguchi method has been used as initial data for the process simulation. The impact of operating parameters on the process performance is considered. The optimum condition for the conversion of sulfide toxic gases to H 2 SO 4 have been found to be: acid concentration of 0.867 mol/L, reaction temperature of 120 °C, stirring speed of 400 rpm, leaching time of 120 min, sulfide ore particle size of 0.01 mm; solid-to-liquid ratio of 30 wt%, additives amount of 50 kg/ton and oxygen pressure of 200 psi. Under optimum condition, H 2 SO 4 production from sulfide toxic gases is 99%, the removal percentage of Fe, Co, Mn, Ni and Cd impurities is 99% and the recovery percentage of Zn + Pd + Cu is more than 97%.

In this work, a dynamic non-isothermal adsorption process of CH 4 and CO 2 in a fixed bed of SAPO-34 particles was modeled by coupled DEM-CFD. This Euler–Lagrange method gives access to specification of each adsorbent pellet including location, temperature and concentrations, and facilitates study of phenomena like adsorption. Transport phenomena including heat and mass transfer in fluid and between solid and gas were taken into account. Eventually the model was validated by experimental results of breakthrough curve. Especially near wall channeling effect and the role of inlet feed velocity on the bed efficiency were addressed in this work. Local and bulk porosity values calculated using DEM model showed an acceptable agreement with previous empirical equations. Results indicated that this coupled method can be applied as a promising tool to study the mass transfer zone and efficiency of the adsorption process. The results revealed that as the feed continues to flow into the column, the lower layers of the adsorbent particles become practically saturated and then the mass transfer zone starts moving upward to a region of fresher adsorbent in the column. Also, the results showed that, at a low inlet velocity with a low Peclet number ( Pe  = 0.195), channeling effect is reduced and the diffusion mechanism controls the mass transfer. However, HETP enhances with increase in the feed gas velocity ( Pe  = 2.25) as well as increase in deviation from plug flow regime, and consequently the adsorption efficiency decreases. HETP decreases drastically at the beginning with increase in interstitial velocity. Increase in the interstitial velocity beyond a particular value of 0.5 cm s −1 leads to increase in the HETP value. This trend and presence of a minimum in this graph were explained based on Van Deemter concept.

Sugarcane is a notable crop grown in the tropical region of the world. It is an abundant waste material of the sugar industry which is a low cost and low combustion fuel thus the bagasse can be exploited to manufacture adsorbents for water treatment. Because the presence of contaminants in polluted water is not uniform, pollutant species compete for active sites during the adsorption process. Investigation of the competitive adsorption of Zn(II), Cu(II), Pb(II), and Fe(II) in a quaternary solution using hybrid biochar developed from sugarcane bagasse (SCB) mixed Low-Density Polyethylene (LDPE) and pure SCB biochar is the main aim of this study. The biochar was developed using the retort carbonisation process and characterised via SEM (Scanning Electron Microscopy), BET (Branueur Emmett Teller) analysis, and FTIR (Fourier Transform Infrared Spectroscopy). Both biochar species mixture possessed some orbicular properties with mesoporous heterogeneous superficial morphology. The biomass biochar and hybrid biochar specific surface area are 533.6 m 2 /g and 510.5 m 2 /g respectively. For the two used adsorbents, >99% removal efficiency was recorded over the sphere for dosage investigation. Thus, this implies they are capable of removing heavy metals from the aqueous solution simulated. The Langmuir isotherm fitted best in each domain however there was an exception for Pb(II) ions in biomass biochar with the experimental adsorption capacity of ∼ 22 mg/g for the HMs. Based on the correlation coefficient ( R 2 ); the experimental data fitted the pseudo-first-order kinetic model well having a correlation coefficient value of greater than 0.9. The mechanism of adsorption for the HMs was chemisorption. This study has a three-pronged benefit of water treatment, resource conservation, and solid waste utilisation.

Photocatalytic degradation is one of the effective methods to remove various pollutants from domestic and industrial effluents. Several operational parameters can affect the efficiency of photocatalytic degradation. Performing experimental methods to obtain the percentage degradation (%degradation) of pollutants in different operating conditions is costly and time-consuming. For this reason, the use of computational models is very useful to present the %degradation in various operating conditions. In our previous work, Fe 3 O 4 /TiO 2 nanocomposite containing different amounts of silver nanoparticles (Fe 3 O 4 /TiO 2 /Ag) were synthesized, characterized by various analytical techniques and applied to degradation of 2,4-dichlorophenol (2,4-DCP). In this work, a series of models, including stochastic gradient boosting (SGB), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), the improvement of ANFIS with genetic algorithm (GA-ANFIS), and particle swarm optimization (PSO-ANFIS) were developed to estimate the removal percentage of 2,4-DCP. The model inputs comprised of catalyst dosage, radiation time, initial concentration of 2,4-DCP, and various volumes of AgNO 3 . Evaluating the developed models showed that all models can predict the occurring phenomena with good compatibility, but the PSO-ANFIS and the SGB models gave a high accuracy with the coefficient of determination ( R 2 ) of 0.99. Moreover, the relative contributions, and the relevancy factors of input parameters were evaluated. The catalyst dosage and radiation time had the highest (32.6%), and the lowest (16%) relative contributions on the predicting of removal percentage of 2,4-DCP, respectively.

In order to meet the environmental legislations related to sulfur content, it is important to find an alternative techniques for deep removal of sulfur components from fuels. So, in this study, a novel nano-catalyst based on iron oxide (Fe 2 O 3 ) as active component prepared over composite support ( γ -Alumina + HY-zeolite) is developed here for efficient removal of sulfur compounds from fuel via oxidation process. The precipitation method is employed first to prepare the composite support and then the impregnation method is utilized to generate a novel synthetic homemade (Fe 2 O 3 /composite support) nanocatalysts that has not been developed in the literature (iron oxide over composite support). The characterizations of the prepared catalysts display that the surface area of the catalyst increases with increasing the amount of Y-zeolite in composite support. The effectiveness of the catalysts is tested by utilizing oxidative desulfurization (ODS) operation under several operating conditions. The results of the experimental work show that the activity of oxidative desulfurization enhances with increasing Y-zeolite, temperature, and batch time under moderate operating conditions. The oxidative desulfurization efficiency followed the order: CAT-1 < CAT-2 < CAT-3. The CAT-3 performed the high removal of sulfur compounds (90.73%) at 100 min and 423 K. The best values of the kinetic parameters of the ODS process are then determined based on experimental data and model based techniques within gPROMS package. Finally, the reactor model is used to determine the optimal operating conditions while maximizing the removal of sulfur compounds leading to cleaner fuel. Where, 99.3% of the sulfur removal has achieved at batch time of 190.6 min, temperature of 543.56 K and initial sulfur content at 0.8668 wt% in the presence of CAT-3 based on the optimal kinetic parameters (order of reaction ( n ) of 1.9865719, activation energy (EA) at 29.942 kJ/mol and pre-exponential factor ( k 0 ) with 622.926 wt −0.9865719  min −1 ).

The thermal-hydraulic characteristics and performance of the circular and flattened straight tubes with longitudinal inward microfins are studied with isothermal wall condition and Reynold numbers (Re) between 10,000 and 30,000. The geometric models with fins (8, 12, and 16 fins) and three flattening ratios (1.4, 2, and 3.4) are considered for the simulation. The results indicate that the longitudinal microfins have a limited effect on the improvement of heat transfer, but the application of microfins increases the pressure drop significantly. Furthermore, an increase in Reynolds number increases the heat transfer characteristics. Therefore, a discriminative use of longitudinal microfins for circular tubes to improve thermal performance is advised. Flattening the microfin tubes has shown a significant increase in heat transfer coefficient and friction factor compared to circular cross-section tubes with microfins. The percentage gain in heat transfer with the flattening ratio of 3.4 is about 52% compared to the circular fin tube at Re = 30,000. A 61% increase in centreline velocity is observed at Re = 10,000. Area-based Enhancement Factor (AEF) and performance evolution factor (PEF) are more than 1 for flattened tubes with microfins. It shows an improvement in the overall thermal-hydraulic characteristics of tubes.

Kokoro as a broadly acknowledge maize snack is being consumed every day by both the children and grown-ups, but it is characterized by the low protein content required for survival. The blending of maize flour (MF), sesame flour (SF) and moringa flour (mF) to enhance the nutritional values of kokoro was optimize with response surface technique (RSM) and artificial neural network (ANN). MF, SF and mF were mixed at diverse proportion and the optimal blending ratio was gotten using D-optimal design method. The protein and carbohydrate actual contents were compared with their predicted values using RSM and ANN models. The performance of the developed RSM and ANN models were validated with coefficient of determination (R 2 ) and mean square error (MSE). The optimal blending ratio of MF: SF: mF was 54.11: 37.06: 8.83. The optimal blending ratio gave 25.53% of protein content and 45.99% of carbohydrate content. The statistical analysis of the experimental data obtained using different statistical techniques shows that regression models by RSM gave R 2 of 0.999 for protein yield and 0.983 for carbohydrate yield while ANN gave R 2 of 0.999 with MSE 9.24184 × 10 −1 . Therefore, it can be concluded from the results that both the RSM and ANN gave good prediction of the model.

We develop and investigate a model for sludge production in the activated sludge process when a biological reactor is coupled to a sludge disintegration unit (SDU). The model for the biological reactor is a slimmed down version of the activated sludge model 1 in which only processes related to carbon are retained. Consequently, the death-regeneration concept is included in our model which is an improvement on almost all previous models. This provides an improved representation of the total suspended solids in the biological reactor, which is the key parameter of interest. We investigate the steady-state behaviour of this system as a function of the residence time within the biological reactor and as a function of parameters associated with the operation of the SDU. A key parameter is the sludge disintegration factor. As this parameter is increased the concentration of total suspended solids within the biological reactor decreases at the expense increasing the chemical oxygen demand in the effluent stream. The existence of a maximum acceptable chemical oxygen demand in the effluent stream therefore imposes a maximum achievable reduction in the total suspended solids. This paper improves our theoretical understanding of the utility of sludge disintegration as a means to reduce excess sludge formation. As an aside to the main thrust of our paper we investigate the common assumption that the sludge disintegration processes occur on a much shorter timescale than the biological processes. We show that the disintegration processes must be exceptional slow before the inclusion of the biological processes becomes important.

The design of large-scale nanomaterial production is nowadays a major research topic that requires efficient tools for appropriate decision-making and process simulation is considered among the rational approach to address such difficult issue. The present study deals with process design and economic assessment of Molybdenum Disulfide (MoS 2 ) nanomaterials production at large-scale via solvothermal method basing on our previous bench scale results. The commercial simulator Aspen Plus was used for process modelling and assuming a plant capacity of 100 tonnes/year. The simulation results were used to perform the cost assessment and profitability analysis while taking into account two relevant cases with (Recycle Case) and without recycling of Ethylenediamine and Hydrazine (Base Case). Note that for the technological and economical assessment the effluent treatment system was not taken into account. The total capital investment was estimated to be ca.14.3 M$ for the base case and ca. 17.4 M$ for recycle case, while the total operating costs were about 2945 $ for the base case and 503 $ for the recycle case for the production of 1 kg of MoS 2 . Thus, in addition to intrinsic advantages associated with the easier preparation and lower environmental impact of solvothermal method, larger production with recycling option can make the process more economically profitable.

This article contributes to handling the Non-Minimum Phase (NMP) system with time delay in the existence of uncertainty and disturbances. The series cascade control scheme is used to overcome such problems. The secondary loop architecture in a series cascade scheme is formulated in the Internal Model Control (IMC) framework. The tuning of fractional-filter via a delayed version of Bodes’ ideal transfer function approach of primary loop controller in a series cascade arrangement shows the novelty of this work. The primary loop controller is designed in the IMC framework after accountability of inverse response and dead-time compensator. Furthermore, Particle Swarm Optimization (PSO) is adapted to accomplish the optimal value of controller settings. The Riemann sheet principle is used to determine stability. The sensitivity investigation is performed to know the robustness of the offered controller. For the effectiveness of the suggested scheme, two case studies are revealed in this paper.