With industrial expansion and increasing water demand, pollution caused by untreated wastewater has become a major environmental concern. This work focused on creating a membrane made from polyacrylonitrile and titanium dioxide (PAN/TiO2) through the spinning jet method. The characterization of the composited membrane was carried out by using XRD, FTIR, SEM, and FESEM techniques. The effectiveness of the fabricated composite membrane in treating grey water and its performance were experimented with on a laboratory scale. The Taguchi method was employed to design the performance experiments and optimize the effective parameters. The results indicated that decreasing PAN concentration and increasing rotation speed resulted in smaller nanofiber diameters, while adding TiO2 enhanced membrane hydrophilicity. The smallest achieved nanofiber diameter was 439 nm. The tests showed a maximum porosity of 71% and a minimum pore size of 0.511 & micro;m. The laboratory results were analyzed using Minitab Software, which identified that the optimal conditions for the process were 13 wt% PAN concentration, 5500 rpm rotation speed, 5 wt% TiO2 concentration, and 2 bar pressure. In this case, the membrane efficiency in greywater treatment was 62.3%, based on COD rejection. PAN/TiO2 membranes show promise for grey water treatment.

In the present work, the energy and exergy analysis was carried out for a diesel engine fueled with soybean oil biodiesel and its blends at different temperatures and two speeds (1200 and 1600 rpm). To simulate the combustion process, a single-zone combustion model was developed. A comprehensive MATLAB-based simulation tool incorporating multiple combustion by-products was developed to perform detailed energy and exergy evaluations. Simulated in-cylinder pressure profiles for pure diesel fuel were benchmarked against experimental observations, demonstrating strong correlation and reliability. The model also provided insights into both instantaneous and cumulative forms of energy and exergy at various crank angles for three biodiesel blend ratios—B20, B40, and B100. The results indicate that the total exergy of B100 is approximately 50

Biochar production through biomass pyrolysis offers a sustainable approach to reducing reliance on conventional energy sources while mitigating global warming potential. However, identifying the optimal operational parameters, biomass characteristics, and feedstock types remains highly complex. In this study, seven machine learning (ML) models-RT, RBF, MLP, MLR, GPR, ANFIS, and SVM-were developed and applied to a dataset of diverse biomass feedstocks to predict biochar yield. Model performance was evaluated using the same dataset. The Support Vector Machine (SVM) model achieved the highest accuracy with the lowest error (RMSE = 2.61), followed by the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) models. Multiple Linear Regression (MLR), Gaussian Process Regression (GPR), ANFIS, and RT showed lower predictive performance. Using the optimized SVM model, 44 three-dimensional response surface plots were generated to illustrate both individual and interactive effects of feedstock properties and pyrolysis parameters on biochar yield. These plots revealed the complex relationships between variables and emphasized the importance of parameter optimization. Finally, genetic algorithm (GA) optimization indicated that a model-predicted theoretical maximum biochar yield could reach 100% by adjusting feedstock properties (increasing fixed carbon, decreasing volatile matter, and raising ash content) and process conditions (faster heating rate). This surpassed the best experimental result of 95.89% yield obtained from bamboo biomass.

The growing interest in ammonia as a zero-carbon fuel for internal combustion engines has highlighted its potential, particularly in large-displacement engines. Despite its environmental advantages, the use of ammonia introduces considerable challenges in terms of combustion dynamics and pollutant formation. This research uses computational fluid dynamics (CFD) modeling through CONVERGE software to evaluate how varying the share of ammonia, diesel injection duration, and injection timing affects engine behavior under high-load conditions. The findings reveal that introducing a 10% ammonia blend results in peak pressures surpassing those of conventional diesel combustion. While ammonia tends to delay ignition and reduce the heat release rate, optimizing injection timing and shortening injection duration improves premixed combustion characteristics. Notably, nitrogen oxide (NO) emissions are substantially decreased by as much as 92%, with higher ammonia content, likely due to thermal DeNOx reactions. However, shortening injection at higher ammonia levels elevates NO output, and advancing injection timing has limited impact on this trend.

Diesel engines are a major source of nitrogen oxides, carbon dioxide, and particulate matter emissions. While biodiesel blends offer potential emission reductions, challenges remain in viscosity, flash point, cold weather performance, and combustion characteristics. This study examines the performance and emission behavior of biodiesel–diesel blends to enhance efficiency and reduce environmental impact. Multiscale entropy analysis was employed to assess combustion instability and complexity, focusing on the influence of fuel composition and engine speed at full load. Experimental investigations were conducted using biodiesel derived from tomato, papaya, and apricot, blended with diesel. The tested fuels included binary and ternary biodiesel–diesel blends with varying levels of complexity. Results indicate that at optimal operating conditions, biodiesel blends enhance energy and exergy efficiency while exhibiting higher carbon dioxide and nitrogen oxide emissions compared to pure diesel. Hydrocarbon emissions decreased under optimized conditions, while fuels with lower chemical complexity demonstrated improved torque output. Diesel, characterized by greater combustion complexity, resulted in lower exergy and useful work. These findings contribute to the understanding of biodiesel application in compression ignition engines, providing insights into performance optimization and emission control strategies. Keywords: Biodiesel blends; combustion stability; engine emissions; energy efficiency; exergy analysis.

This study investigates the numerical simulation of cracking furnaces and the feasibility of coke combustion in the De-Coke flow, utilizing computational fluid dynamics (CFD) and energy-exergy analysis. Employing the Euler-Lagrange approach, we simulate the motion of coke particles within the model. A turbulent model is applied to assess the combustion processes, while non-premixed models simulate fuel and coke particle interactions. Additionally, we incorporate the Discrete Ordinates Model for radiation and the Discrete Phase Model for coke particle motion simulation. Results indicate that injecting coke particles with dry air leads to a 100% conversion rate. However, increasing the temperature of the De-Coke stream from 454 K to 654 K yields only a slight increase in coke conversion from 52 to 55%, suggesting that sufficient time and temperature are crucial for complete combustion. The energy and exergy efficiency of the combustion furnace during the cracking process stand at 44.8% and 29%, respectively, compared to 93.24% and 96.2% during the coil cracking process. Furthermore, the destruction exergy for the combustion furnace is approximately 36%, whereas the coil experiences destruction exergy of less than 4%. Although energy and exergy distributions reveal similar trends for both conventional and burning-coke De-Coke processes at the coil, the burning-coke method offers increased destruction exergy and enhanced heat transfer, albeit at the cost of efficiency in energy and exergy transfer to the coil compared to conventional methods.

This study investigates the effects of gasoline-premixed fuel on emissions and combustion characteristics in a compression ignition engine. A multi-cylinder, four-stroke diesel engine was analyzed using both experimental and computational methods. Emission and combustion parameters were measured at varying loading conditions for two gasoline–diesel blends and compared with pure diesel at a constant engine speed. Numerical simulations were conducted using the AVL Fire-CHEMKIN coupler for emission and combustion modeling, while CHEMKIN was used for chemical reaction modelling. Simulated results were validated against experimental data, showing minor deviations in mean effective pressure and emissions. The in-cylinder pressure data exhibited strong agreement with experimental results. The gasoline–diesel blends demonstrated longer ignition delays compared to pure diesel, influencing combustion characteristics. Additionally, the mole fraction of unburned hydrocarbons increased with gasoline blending. These findings provide insights into alternative fuel applications for compression ignition engines, contributing to advancements in fuel efficiency and emission reduction strategies. Keywords: Computational fluid dynamics ; diesel engine emissions; diesel engine performance; premixed gasoline fuel

Ammonia is considered an attractive alternative fuel for power generation in the context of global decarbonisation efforts. This study examines the advancements in ammonia combustion technology for spark ignition (SI) and compression ignition (CI) engines. An extensive analysis of the characteristics of ammonia (NH3) combustion, a fuel free of carbon, is provided in this paper. Since ammonia burns similarly to fossil fuels and emits less CO2, CO, NOx, soot, and hydrocarbon (HC) pollutants, NH3 is a desirable substitute fuel that can be stored and transported using existing commercial infrastructure. It also comes with productivity from renewable sources. However, unlike traditional hydrocarbon fuels, NH3 exhibits unique combustion characteristics, highlighting the challenges of using it as a fuel for internal combustion (IC) engines. This paper critically reviews the challenges of NH3 blended with diesel, biodiesel, dimethyl ether, and some other alternative fuels in IC engines. The literature reports mixed findings on this topic. Many studies have not demonstrated NH3 as a substitute fuel for IC engines yet. In addition, ammonia's toxicity and unusual/complex combustion characteristics hinder its use as a fuel substitute in IC engines. Further research is required to overcome challenges associated with using NH3 as a fuel for IC engines. This study identifies and discusses these challenges.

Industrial wastewater treatment increasingly relies on membrane separation, with ceramic membranes offering many advantages such as thermal stability and pH resistance. The resistance of ceramic membranes to extreme pH conditions indicates their ability to maintain structure and performance when exposed to highly acidic or alkaline environments. A high-permeability ceramic nanofiltration membrane was developed, boasting excellent rejection rates through a multilayer asymmetric design. Initially, two tubular porous supports, mullite and mullite-alumina, with a weight percent of 50, were fabricated using the extrusion method. Subsequently, a colloidal sol of titania (TiO2) and titania-zirconia (TiO2- ZrO2) was prepared via the sol-gel method and coated on the ceramic supports using the dip-coating method. After analyzing the membrane microstructure using SEM, XRD, and BET, the efficiency of the membranes in treating synthetic oily wastewater was evaluated. The results underscore the significant impact of the Donnan exclusion mechanism on the rejection of nanofiltration (NF) membranes. An increase in pressure led to a rise in rejection rates up to 7 bars. The Chemical Oxygen Demand (COD) rejection for mullite-titania zirconia (MTZ) and mullite-alumina-titania zirconia (MATZ) membranes was 98.65 % and 98 %, respectively. The pure water permeability test results for mullite and mullite-alumina supports, as well as MTZ and MATZ membranes, were recorded as 254, 382, 70, and 89 L bar-1m-2h- 1, respectively.

In this chapter, initially, the main processes globally used to produce hydrogen from the hydrocarbon feedstock are introduced. The production processes, including main unit operations, will be described in detail, and process data will be presented. The overall energy and exergy analysis will be carried out on each production process to estimate and compare energy and exergy efficiencies. The primary source of energy and exergy loss in each production process will be determined and discussed, and then practical solutions to reduce such losses will be proposed. The carbon capture, utilization and storage process is integrated into hydrogen production processes to generate blue hydrogen.

Ammonia has emerged as a promising carbon-free alternative fuel for internal combustion engines (ICE), particularly in large-bore engine applications. However, integrating ammonia into conventional engines presents challenges, prompting the exploration of innovative combustion strategies like dual-fuel combustion. Nitrous oxide (N2O) emissions have emerged as a significant obstacle to the widespread adoption of ammonia in ICE. Various studies suggest that combining exhaust gas recirculation (EGR) with adjustments in inlet temperature and diesel injection timing can effectively mitigate nitrogen oxides (NOx) emissions across diverse operating conditions in dual-fuel diesel engines. This study conducts a numerical investigation into the impact of varying inlet charge temperatures (330K, 360K, and 390K) and EGR rates (0%, 10%, and 20%) on the combustion and emission characteristics of an ammonia/diesel dual-fuel engine operating under high-load conditions, while considering different shares of ammonia energy. Computational fluid dynamics (CFD) simulations are executed using Converge software. Subsequently, multi-linear regression models are developed, utilizing ammonia share, inlet charge temperature, and EGR rate as independent variables, and emission parameters as dependent variables. The best-fitted regression model can be employed to analyze the response surface of performance parameters. The optimal CO2 reduction, approximately 30%, is observed under the conditions of (390K, 40% NH3, and EGR20), as indicated by the results. Furthermore, under the conditions of (360K, 20% NH3, and EGR20), the findings indicate a notable reduction of NO2, approximately 65% compared to diesel. Additionally, the findings suggest that NH3 reduction peaks at higher temperatures, with approximately a 50% decrease observed.

Background: One of the most important processes of industrial hydrogen production is steam methane reforming (SMR). However, the biggest drawback of steam reformer processes is high energy consumption. In methanol production units, 40% of the energy consumed in the steam reformer is provided by methane burning. The best solution to reduce the consumption of methane gas is to use the waste gases of the units.Innovation: To boost the thermal performance of the furnace, as well as the reduction in natural gas utilization, the effects of the kinds of fuel in an industrial unit are investigated. Furthermore, the waste gas is studied to whether it can be used as fuel in an SMR or not.Significance: CFD is one of the most powerful tools for simulation of the industrial by which a new unit can be set up or the performance of the old units can be developed. Additionally, the effect of diverse parameters on industrial processes can be examined, and the optimal operating conditions of the industrial unit can be found. Methods: In this study for five different cases of fuel, the furnace of an industrial SMR unit, at the operating conditions, was simulated using Computational Fluid Dynamics, (CFD) and the results were validated by the industrial data. Moreover, regarding the higher thermal efficiency of the furnace and the lower consumption of natural gas, two cases called design, and the suggested modes, were investigated and suggested mode was proposed as the most suitable fuel.Finding: Based on the results, removing purge gas and adding waste gases with lower hydrogen content are recommended. Compared with the operational fuel, the suggested mode decreases the flue gas temperature by 11.78 K and increases the temperature of the first row of the reformer tubes by about 4.17 K, while declining the natural gas molar flow rate by 32%. A 64% reduction in hydrogen content of the suggested mode leads to an increase 10% flame length and 14% enhancement of adsorbed radiative heat flux. Moreover, in the suggested mode it is possible to recycle the purge gas to the methanol synthesis reactor and enhance the methanol production to 1% which is 50 ton/day.

In this research, single and multi-bed adsorption columns for oily wastewater treatment were investigated both experimentally and numerically. For this purpose, two mineral adsorbents, namely natural zeolite and calcined bentonite, were used. The adsorbent characteristics were analyzed by XRD, BET, and SEM. Adsorption isotherm and single fixed-bed adsorption column performance for both adsorbents were experimentally assessed at different concentrations. In addition, single- and multi-fixed-bed column applicability with two different configurations, series and parallel connections, were simulated. The experimental results showed that Freundlich and Langmuir isotherms had the best performance to describe the adsorption of calcined bentonite and natural zeolite, respectively. Moreover, natural zeolite has better performance for oily wastewater treatment than calcined bentonite. The maximum capacity of calcined bentonite and natural zeolite was obtained at 3.06 mg/g, and 5.37 mg/g, respectively. The simulation results indicated that the maximum separation yields of single fixed-bed, multi-fixed-bed with series connections, and multi-fixed-bed with parallel connections were 39.3%, 99.98%, and 74.58%, respectively. Adsorbent mass optimization indicated that the required adsorbent mass decreased by 33.1% when four beds were presented in an operation instead of a single bed. This research recommends a promising application of natural zeolite as an economic adsorbent in multi-bed adsorbers for oily wastewater treatment.

Tomato seed oil biodiesel (TSOB) could be considered as a second generation and clean-burning renewable substitute for petroleum diesel. It is about 72% by weight of tomato waste, which contains an average of 24% oil. This paper investigated the effects of four different Diesel-TSOB blends on the combustion performance of an indirect injection (IDI) diesel engine. In-cylinder pressure (CP) and combustion parameters at five different engine loads and seven speeds were experimentally measured. Then for 2D CFD simulation of the emissions and combustion processes, AVL FIRE software was used and the results evaluated with experimental data. The purpose of the study was to determine the combustion process and its effects on the performance and emissions of the engine. The outcomes for B10 at 100% load addressed that, the peak CP of about 67 MPa was found at 1200 rpm which occurred at 13° ATDC, while at 2200 rpm the peak CP was 69 MPa and occurred at 1° ATDC, and at 2400 rpm the peak CP was found to be about 66 MPa which occurred approximately at TDC. The simulated results found that the peak in-cylinder temperature of 1600° K corresponds to the 10% TSOB blend (B10) and the longest mixing-controlled period occurs for B10 at 27° CA. The simulation also showed that B5 had the longest jet penetration of about 44 mm (at about 100° CA) in comparison to 43 mm for B20, 41 mm for B10 and 39.8 mm for B0 (pure diesel) which occurred at less than 100° CA. The longest jet penetration duration of was found to be about 44 mm for B5 at about100° CA. The results showed that B10 has the biggest accumulative heat release (approximately 1900 J) and highest fuel energy efficiency. The 2-D CFD simulation revealed that the unburnt equivalence ratio in the main combustion chamber is lesser than in the spherical combustion chamber.

Biodiesel is considered as a renewable biofuel-based substitute for fossil diesel as the properties of biodiesel are similar to those of normal diesel fuel. However, biodiesel has some properties which a negative effect on engine combustion. Binary and ternary fuel blends (blends of biodiesels with the opposite properties) are the best environmentally friendly alternative in compression ignition engines. In this paper, the effects of binary and ternary blends of tomato, papaya, and apricot seed biodiesels on the energy and exergy balance as well as emissions on a compression ignition diesel engine were experimentally and theoretically investigated. The ob-tained results reveal that the maximum and minimum exergy efficiency are related to the biodiesel of tomato -papaya blend at about 29.63% and pure diesel at about 28.46% respectively. Also, the obtained results show that, compared to the tomato biodiesel-diesel blend, using the binary blends decreases the percentage of heat loss exergy by 5.5% and 3.3% on average for tomato-papaya biodiesel-diesel and tomato-apricot biodiesel-diesel, respectively. The results address that the energy percentage of exhaust emissions at the speed of maximum torque and maximum power averaged 30% while this fraction for exergy was about 13%. The emission results show that the minimum oxygen monoxide emissions, which is 0.3% less than that of diesel, is related to the tomato-apricot-papaya biodiesel-diesel ternary blend.

This study investigated the suitability of stone fruit seed as a source of biodiesel for transport. Stone fruit oil (SFO) was extracted from the seed and converted into biodiesel. The biodiesel yield of 95.75% was produced using the alkaline catalysed transesterification process with a methanol-to-oil molar ratio of 6:1, KOH catalyst concentration of 0.5 wt% (weight %), and a reaction temperature of 55 °C for 60 min. The physicochemical properties of the produced biodiesel were determined and found to be the closest match of standard diesel. The engine performance, emissions and combustion behaviour of a four-cylinder diesel engine fuelled with SFO biodiesel blends of 5%, 10% and 20% with diesel, v/v basis, were tested. The testing was performed at 100% engine load with speed ranging from 200 to 2400 rpm. The average brake specific fuel consumption and brake thermal efficiency of SFO blends were found to be 4.7% to 15.4% higher and 3.9% to 11.4% lower than those of diesel, respectively. The results also revealed that SFO biodiesel blends have marginally lower in-cylinder pressure and a higher heat release rate compared to diesel. The mass fraction burned results of SFO biodiesel blends were found to be slightly faster than those of diesel. The SFO biodiesel 5% blend produced about 1.9% higher NOx emissions and 17.4% lower unburnt HC with 23.4% lower particulate matter (PM) compared to diesel fuel. To summarise, SFO biodiesel blends are recommended as a suitable transport fuel for addressing engine emissions problems and improving combustion performance with a marginal sacrifice of engine efficiency.

The structure of the human brain reflects multifarious random influences of terrestrial and phylogenetic history, yet the higher mental functions correlated with this unique cerebral neurophysiology are generally assumed to embody universals common to intelligences independent of biological substrate.