A polynomial regression model for stabilized turbulent confined jet diffusion flames using bluff body burners

AbstractThermal structure of stabilized confined jet diffusion flames in the presence of different geometries of bluff body burners has been mathematically modeled. Two stabilizer disc burners tapered at 30° and 60° and another frusted cone of 60°/30° inclination angle were employed all having the same diameter of 80(mm) acting as flame holders. The measured radial mean temperature profiles of the developing stabilizing flames at different normalized axial distances were considered as the model example of the physical process.A polynomial mathematical model of fourth degree has been investigated to study this phenomenon to find the best correlation representing the experimental data. Least Squares regression analysis has been employed to estimate the coefficients of the polynomial and investigate its adequacy. High values for R2>0.9 obtained for most of the investigated bluff burners at the various locations of x/dj prove the adequacy of the suggested polynomial for representing the experimental results. Very small values of significance F<(α=0.05) for all investigated cases indicate that there is a real relationship between the independent variable r and the dependant variable T. The low values of p<(α=0.05) obtained reveal that all the recorded parameters for all the investigated cases are significant

Application of energy management coupled with fuel switching on a hydrotreater unit

AbstractIn the last decades, saving energy and protecting environment became the most important topics for search and survey. The energy engineer for any chemical process is obliged by restrictions of “Kyoto Protocol” for limitation of carbon dioxide emissions from fuel combustion, so he does his best to reduce utility consumption and thus reduce gas emission. Proper designing of the heat exchanger network (HEN) for any process is an effective and successful method to minimize utility consumption and therefore minimize gas emission (mainly carbon gases (CO2) and sulfur gases (SOx)). Fuel switching coupled with energy targeting achieved the least gas emission. In this work we choose a hydrotreater unit of a petroleum refinery as a case study due to its effective role and its obvious consumption of utility. We applied the methodology of energy targeting through HEN design (using pinch technology) at several values of mean temperature difference (ΔTmin); where the maximum percentage of energy saving was 37% for hot and cold utility which directly leads to percentage reduction of gas emission by 29% for CO2 and 17% for SOx. Switching fuel oil to other types of fuel realized gas emission reduction percentage where the maximum reduction established was through natural gas fuel type and reached 54% for CO2 and 90% for SOx. Comparison between existing design and the optimum ΔTmin HEN led to few modifications with the least added capital cost for the hydrotreater existing design to revamp it through four scenarios; the first one depended on fuel switching to natural gas while the second one switched fuel to diesel oil, in the third scenario we applied heat integration only and the fourth one used both of heat integration and fuel switching in a parallel way

Use of SiO2 - TiO2 Nanocomposite as Photocatalyst for the Removal of Trichlorophenol: A Kinetic Study and Numerical Evaluation

A series of silica-titania nanocomposite materials with different silica–titania ratios was prepared in presence of a novel ethoxylated sulphanilamide of molecular weight 1053 by the sol-gel method. Several characterisation techniques were adopted such as thermal analysis (differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA)), N2-adsorption-desorption, X-ray diffraction (XRD), Fourier transform infrared (FTIR), and transmission electron microscopy (TEM) connected with energy dispersive spectroscopy (EDS). The surface acidity was investigated by pyridine adsorption using FTIR spectroscopy. The photocatalytic activity and the adsorptive ability of the composites were evaluated based on the photodegradation of 2, 4, 6- trichlorophenol (TCP) under UV irradiation with a wavelength of 254 nm. The maximum TCP adsorption onto the composites was measured in darkness. The results showed that there was no adsorption of TCP on pure SiO2. The 10% TiO2-SiO2 catalyst showed the highest rate of TCP removal among the synthesised composites. The removal % reached to 87 % after 90 min irradiation time. This activity was caused by the large surface area and pore volume as well as the formation of a mesoporous structure, as evidenced from the pore size distribution curve. Finally, the numerical evaluation of the photodegradation of TCP was conducted. Keywords: Nanocomposite, Ethoxylated sulphanilamide, Photocatalytic degradation, UV irradiation, 2,4,6-TCP, Numerical evaluation

Numerical Evaluation and Analysis for Hydrogen Production Via Ethanol Steam Reforming

In the present study, two series of Ni/Ce/ZrO2 catalysts were prepared. The first one is n% Ni/Ce0.74Zr0.26O2 (n = 0, 2, 10 and 20 wt %). The second is 10%Ni / m (Ce/ZrO2) (m = 0, 4, 6 and 8). Catalysts have been investigated for ethanol steam reforming (ESR) to produce hydrogen. The reaction was studied in an atmospheric flow system, the temperature range was 200-600 ºC and water/ethanol (6, 8, 10 molar ratio). The effect of using H2O2 as an oxidant in auto-thermal reforming of ethanol has been also investigated (at 400 ºC, and H2O2/ethanol ratio = 8) to get highest hydrogen selectivity with lower CO ratio. Numerical evaluation and analysis have been performed for the above obtained results. It has been observed that the ethanol conversion, hydrogen production and some of the various investigated relations are functions of more than one independent variable. So, the response surface methodology (RSM) has been employed to evaluate these relations. Key Words: Numerical analysis, Response surface methodology, Ethanol steam reforming, Ni/Ce/ZrO2 catalysts

Commercialization potential aspects of microalgae for biofuel production: An overview

Biofuels are particularly important as an alternative fuel option for transportation. The sustainability of biofuels will depend on the development of viable, sustainable technologies that do not appear to be yet commercially viable. Successful development of algae-based biofuels and co-products industry requires the optimum combination of technical innovations in systems and processes, coupled with economic feasibility in the practical implementation and integrated scale-up for commercial production and marketing. This article discusses the importance of algae-based biofuels together with the different opinions regarding its future. Advantages and disadvantages of these types of biofuels are presented. Algal growth drives around the world with special emphasis to Egypt are outlined. The article includes a brief description of the concept of algal biorefineries. It also declares the five key strategies to help producers to reduce costs and accelerate the commercialization of algal biodiesel. The internal strengths and weaknesses, and external opportunities, and threats are manifested through the SWOT analysis for micro-algae. Strategies for enhancing algae based-fuels are outlined. New process innovations and the role of genetic engineering in meeting these strategies are briefly discussed. To improve the economics of algal biofuels the concept of employing algae for wastewater treatment is presented

Economic evaluation and sensitivity analysis of some fuel oil upgrading processes

Seven upgrading schemes, identified as high distillate production schemes have been proposed for upgrading of 3.50 × 106 t/y atmospheric residues. The seven schemes were evaluated using the discounting cash flow method. Economic parameters such as internal rate of return, IRR, payback period, PBP and net present value, NPV have been calculated for each option. All studied schemes proved profitable with IRR ranging between 25.2 and 33.7% with option 7 having the highest NPV, IRR and payback period. Sensitivity analyses were performed on this option. The parameters investigated are: sales price (Revenue); production rate (feed weight); feed cost; utilities cost; direct and indirect costs; tax% and discount rate%. Their impact on NPV and %IRR has been evaluated. Tornado diagrams were constructed to illustrate the effect of variation of different cost parameters on NPV and IRR. The single most effective input variable is Revenue on both NPV and IRR. With two-factor sensitivity analysis, the two most important input variables for NPV and IRR are revenue and utilities. Spider charts for option 7 have been created to show how the model’s outputs depend on the percentage changes for each of the model’s input variables

Enhanced predictive optimization of methane dry reforming via ResponseSurface methodology and artificial neural network approaches: insights using a novel nickel-strontium-zirconium-aluminum catalyst

This study investigates the molecular dynamics of methane dry reforming catalyzed by a novel nickel-strontium-zirconium-aluminum (5Ni+3Sr/10Zr+Al) catalyst, leveraging both Response Surface Methodology (RSM) and Radial Basis Function Neural Network (RBFNN) for predictive optimization. Focusing on the impact of operational parameters—hourly space velocity, reaction temperature, and CO2:CH4 mole ratio—on the conversion rates and formation of reaction components, we aim to predict optimal conditions and corresponding process variables. Through a comparison of a three-layer Feed Forward Neural Network, optimized at a 3:10:1 topology, with traditional RSM approaches, our findings highlight the superior predictive capabilities of ANN models. Notably, ANN demonstrated exceptional performance with R2adj and F_Ratio values significantly surpass those of RSM, alongside lower statistical error terms. This superiority is attributed to ANN's robust handling of nonlinear relationships between inputs and outputs, asserting its potential for enhancing predictive accuracy in chemical process optimization. At optimum predicted conditions like 1 CH4/CO2,750 °C reaction temperature, 12000 cm3g−1h−1 space velocity, NiSrZrAl outperformed with &gt; 85 % CH4 and CO2 conversion with H2/CO ∼1 up to 20 h time on stream. Our research underscores the importance of integrating advanced modeling techniques for the efficient and accurate prediction of catalytic reactions, offering valuable insights for future applications in chemical engineering and catalysis.<br/