Fuel Communications最新文献

Crop residues are a major component of lignocellulosic biomass waste generated from the agriculture sector. Improper management of these wastes pollutes the environment, contaminates water bodies, and constitutes hazards to human health. The conversion of crop residues to biochar is an ecologically benign and sustainable management strategy for waste management. This review provides a novel insight into the techniques of converting various classes of crop residues such as straws, peels, bagasse, husks, shells, cobs, and stubbles to biochar for biofuel production. The updated information on the description, benefits, and drawbacks of various biochar production techniques including traditional, modern, and novel techniques are also surveyed. The study concluded on the effectiveness of biochar derived from crop residues as sustainable catalysts or support catalysts for biodiesel, biohydrogen, and biomethane production. The deployment of biochar derived from crop residue is cost-effective, eco-friendly, and contributes to environmental sustainability. More multidisciplinary investigations are required to harness the benefits derivable from the application of biochar for biofuel synthesis and confront the challenges associated with the biochar generation process to guarantee the intensification of biofuel production. The use of innovative technologies should be encouraged to guide future research toward ensuring cleaner, cost-effective, and ecological biochar utilization for biofuel production.

This work focuses on the properties of hydrolysis lignin biocarbons with a perspective on utilizing the biocarbons in pyrometallurgical processes. Even if the blast furnace and basic oxygen furnace (BF-BOF) process route was replaced by emerging technologies with lower CO₂ emissions in the future, the need for carbonaceous materials in the iron and steel making industry will still exist. Most of these applications do not require as high standards for the properties of carbonaceous materials as BF but the requirements are still similar to those for BF. The most important properties of carbonaceous materials are the mechanical strength and suitable reactivity. In the case of biocarbon, the apparent density is also considered important. The reactivity and strength properties are investigated with isothermal reactivity tests and compression strength tests for the non-gasified and pre-gasified biocarbon and reference coke samples. The mass loss rate of coke gasification (-0.069%/min) was considerably lower than that of least reactive biocarbon L1200 (-0.18%/min). Regarding the compression strength of the samples, the strength of coke dropped by 56.44% for the samples of pre-gasification level of 50% compared to non-gasified samples while the drop was only 40.68% for the L1200 biocarbon samples. The level of gasification was found to have direct correlation with pore area percentage with R² value 0.92 in case of L1200 and 0.98 in case of coke. Further, the pore area percentage correlated with the compression strength with R² of 0.93 in case of L1200 and 0.98 in case of coke.

In this paper, we develop a series of Artificial Neural Networks (ANN) using different chemical kinetic and thermodynamic input parameters to predict detonation cell sizes. The feedforward neural networks are trained and validated using available experimental data from the Caltech detonation database covering a wide variety of gaseous combustible mixtures at different initial conditions. For each combination of input parameters, a multiple-stage process is followed, which is described in detail, to first determine the best hyperparameters of the ANN (hidden layers, nodes per layer, etc.) and secondly to establish through a fitting process the optimal parameters for each specific network. The performance of the artificial neural networks with different input features is assessed using data from the same source, but that is kept independent and separate from the training and validation process of the ANN. It is found that ANN with three features can provide an accurate estimation of detonation cell size, while increasing the number of features does not improve the accuracy of the ANN. It is also found that the input parameters with the best performance relate indirectly to the stability parameter χ.

SiO₂np derived from rice husk were chemically connected to the surface of modified Calcium Oxide (CaO) in a straightforward manner to produce fatty acid methyl ester (FAME) from waste cooking oil (WCO) with great efficiency. After 3 h at a reaction temperature of 80° C, it was discovered that WCO could produce 97.8% yield of the FAME of the modified CaO, which is much greater than the yield of 83.5% over unmodified CaO under the same reaction circumstances. The results showed that following modification, well-dispersed CaO with relatively tiny particle sizes and large surface areas was produced. Additionally, the changed CaO with very little Ca(OH)₂ is produced during the modification process. The use of leftover modified CaO-nanoparticles as a heterogeneous transesterification catalyst has been identified after fourteen cycles.

Biomass plays an essential role in enhancing global energy security and decreasing carbon emissions as a promising renewable energy option. Comprehensive techno-economic assessments have been carried out to spark industry stakeholders' interest and increase their investment in biomass-based enterprises. To provide a more accurate and reliable feasibility estimate, the evaluation must also take into account a variety of uncertainties in the biomass conversion industry. This review aims to present an overview of the various types of methodologies or techniques used in the techno-economic assessment of the viability of biomass conversion processes, and highlight the uncertainties that need to be taken into account in the evaluation model. A systematic literature review is used where four electronic databases viz., Scopus, Web of Science, Dimensions, and PubMed were used to identify the most recent original research articles in peer-reviewed journals. A total of 346 studies, covering the period 2012–2022 were screened for relevance to the study. Seventy-eight records (n=78) which include only original research articles met the inclusion criteria. The review identified several financial factors and uncertainties that affect the economic performance of fast pyrolysis systems. Furthermore, upgrading the bio-oil to transportation fuels and value-added biochemicals can significantly improve the economic performance of fast pyrolysis plants as opposed to selling raw bio-oil.

There is much current interest in improving the efficiency gas turbines used in aircraft engines and thereby reducing their carbon emissions. The perforated combustor liners in gas turbine silencers absorb the sound associated with thermo-acoustic instabilities and thereby reduce them. A semi-empirical model has been developed to predict the absorption of perforated liners in the absence of bias flow as a function of frequency in terms of liner characteristic such as orifice diameter, thickness, spacing, orientation and perforation ratio and liner configuration which requires an additional model for the impedance of the cavity behind the liner. The expression used for impedance includes a cavity factor which corrects for the change in combustor liner diameter. Predictions of energy absorption coefficient spectrum are compared with data from measurements on several configurations of full-scale liners. It is found that predictions using the standard tangent term in the cavity impedance do not agree with data at frequencies below 500 Hz as well as predictions that use a cosine term instead. The resulting model, which is validated by the data comparisons, should be useful in optimising liner characteristics for manufacture.

KOH-modified metakaolin (KMK) was synthesized, characterized and utilized as a heterogeneous catalyst for biodiesel production from allamanda seed oil (ASO) for the first time. The effect of variables (temperature, time and catalyst concentration) affecting biodiesel production process was optimized using Box-Behnken design of response surface methodology. The biodiesel produced was consequently characterized to determine its fuel properties. Optimization results showed that maximum biodiesel yield of 90.67$\pm$0.14%. was achieved at fixed methanol/ASO molar ratio of 5:1 and at the optimum conditions of 52.5 °C reaction temperature, 180 min reaction time and 0.5 wt.% catalyst concentration. The properties of the produced biodiesel were comparable to the ASTM D6751 and EN 14214 specifications, thus indicating the suitability of the ASO biodiesel as a possible alternative to petroleum diesel.

Electromobility is the future main system for Swedish road transport that encourage sustainable urban transportation. However, emission impacts of applying electric vehicles (EVs) are currently controversial. This study evaluates and compares internal combustion engine vehicles (ICEVs) refer to both petrol and diesel-based engines and BEVs, focusing on environmental and energy impacts. The entire life cycle of vehicles production, fuel production and fuel use are considered and life cycle emissions impacts due to various electricity generation alternatives will be studied. LCA of BEV is also conducted under different recycling scenarios to determine what extent CO₂ can be further reduced owing to car and battery recycling. The results show that BEVs charged by natural-gas, and renewable electricity produce less emissions of CO₂, SO₂, PM, VOCs, NO_X and Sb than ICEVs but higher PO₄ emissions and need more energy. The largest fraction of CO₂ emissions for BEVs charged via renewable electricity is due to vehicle production (61-78% of BEV's life cycle CO₂ emissions). CO₂ emissions regarding to vehicle production for BEVs is 14.6 ton (60.8 gCO₂/km) which is 132% and 123% of that for petrol and diesel ICEVs, respectively. Human toxicity and eutrophication impacts highlight as potentially important categories for transition from ICEVs to BEVs due to high toxicity and PO₄ emissions in BEV production. By applying high scenario for car and battery recycling, CO₂ emissions in BEVs lifespan charged by renewable electricity can be reduced 50% (83 gCO₂/km); total PO₄ emissions can be also decreased 56% with production of 79 mgPO₄/km.

Coking coal is still on the list of critical raw materials in many countries since it is the main element integrated into the blast furnace. While the energy consumption and steelmaking efficiency in the furnace depends on the coke quality, understanding and modeling coking indexes based on their coal parent properties would be a substantial approach for the steelmaking industry. As an innovative approach, this short comminucation has been considered explainable artificial intelligence (XAI) for modeling coal coking indexes (Free Swelling index “FSI” and maximum fluidity “Log (MF)”). XAIs can convert black-box models into human basis systems and develop a significant learning performance and estimation accuracy. SHapley Additive exPlanations (SHAP), as one of the most recently developed XAI models in combination with eXtreme gradient boosting (XGBoost), were used to model coal samples from Illinois, USA. For the first time, FSI and Log (MF) treat as ordinal variables for modeling. Modeling outcomes relieved that SHAP-XGBoost could accurately show interdependency between features, demonstrate the magnitude of their multi relationships, rank them based on their importance, and predict the coking index quite accurately compared with conventional machine learning methods (random forest and support vector regression). These significant results would be opened a new window by applying XAI tools for controlling and modeling complex systems in the energy and fuel sectors.