Search Results (98)

Petroleum oily sludge (OLS), a hazardous by-product of the petroleum industry, and high-alkali lignite (HAL), an underutilized low-rank coal, pose significant challenges to sustainable waste management and resource efficiency. This study systematically investigated the combustion behavior, reaction pathways, and gaseous-pollutant-release mechanisms across varying blend ratios, utilizing integrated thermogravimetric-mass spectrometry analysis (TG-MS), interaction analysis, and kinetic modeling. The key findings reveal that co-combustion significantly enhances the combustion performance compared to individual fuels. This is evidenced by reduced ignition and burnout temperatures, as well as an improved comprehensive combustion index. Notably, an interaction analysis revealed coexisting synergistic and antagonistic effects, with the synergistic effect peaking at a blending ratio of 50% OLS due to the complementary properties of the fuels. The activation energy was found to be at its minimum value of 32.5 kJ/mol at this ratio, indicating lower reaction barriers. Regarding gas emissions, co-combustion at a 50% OLS blending ratio reduces incomplete combustion products while increasing CO₂, indicating a more complete reaction. Crucially, sulfur-containing pollutants (SO₂, H₂S) are suppressed, whereas nitrogen-containing emissions (NH₃, NO₂) increase but remain controllable. This study provides novel insights into the synergistic mechanisms between OLS and HAL during co-combustion, offering foundational insights for the optimization of OLS-HAL combustion systems toward efficient energy recovery and sustainable industrial waste management. Full article

A thorough understanding of fuel behaviour is essential for designing and operating thermochemical systems. Thermogravimetric analysis (TGA) is among the most widely used fuel characterization methods, offering parameters like reactivity and ignition temperature, and enabling comprehensive fuel behaviour assessment through combined indices. This study critically examines the applicability of TGA-based indices for predicting coal performance in industrial processes such as gasification and combustion, where devolatilization, ignition, and burnout stages are key. TGA-derived data are compared with results from established methods, including drop tube furnace (DTF), pulse ignition (PI), and entrained flow reactor (EFR) tests. Findings indicate that the Volatile Matter Release Index (D₂) effectively predicts DTF behaviour (R² = 0.938, max residuals: 4.1 pp), proving useful for fast devolatilization analysis. The Flammability Index (C₁) and Ignition Index (C₃) correlate well with PI results (R² = 0.927 and 0.931, max residuals: 53.3a °C), making them reliable ignition indicators. While TGA tools showed limited accuracy in burnout prediction, the proposed Modified Burnout Characteristic Index (B_1′) achieved reasonable performance (R² = 0.734, max residuals: 0.062%∙°C⁻¹). Overall, selected TGA-based indices offer strong predictive potential for key thermochemical conversion stages. Full article

The production of solid biofuels from torrefied biomass holds significant potential for renewable energy applications. Durable pellet formation from severely torrefied biomass is hindered by the loss of natural binding properties, yet studies on mild torrefaction that preserves sufficient binding capacity for pellet production without external binders or changes to die conditions remain scarce. This paper investigated the production of fuel pellets from torrefied biomass without using external binders or adjusting pelletization parameters. Experiments were conducted using a mild torrefaction temperature (230 °C and 250 °C) and shorter residence time (10, 15, and 30 min). The torrefied materials were then subjected to pelletization using a single-pellet press; and the influence of torrefaction on the mechanical durability, hydrophobicity, and fuel characteristics of the pellets was examined. Results indicated that the mass loss ranging from 10 to 20% among the mild torrefaction treatments was less than the typical extent of mass loss due to severe torrefaction. Pellets made from torrefied biomass (torrefied pellets) had improvement in the hydrophobicity (moisture resistance) when compared to pellets made from untreated biomass (untreated pellets). Improved hydrophobicity is important for storage and transportation of pellets that are exposed to humid environmental conditions, as it reduces the risk of pellet degradation and spoilage. Thermogravimetric analysis of the pyrolysis and combustion behaviour of torrefied pellets indicated the improvement of fuel characteristics in terms of a much higher comprehensive pyrolysis index and greater thermal stability compared to untreated pellets, as evidenced by the prolonged burnout time and reduced combustion characteristics index. Residence time had a more significant impact on pellet durability than temperature, but the durability of the torrefied pellets was lower than that of the untreated pellets. Further research is required to explore the feasibility of producing binder-free durable pellets under mild torrefaction conditions. Overall, the study demonstrated that mild torrefaction could enhance the fuel quality and moisture resistance of biomass pellets, offering promising advantages for energy applications, despite some trade-offs in mechanical durability. Full article

Straw biomass is a renewable but problematic fuel due to its high alkali and chlorine content, which can cause slagging and corrosion during combustion. To mitigate these issues, this study investigates the influence of aluminosilicate additives on the thermal behavior and combustion characteristics of straw biomass. Laboratory-scale testing is carried out using thermogravimetric analysis under atmospheric air, showing the TG, DTG, and DSC profiles of samples (kaolinite, halloysite, straw biomass, and straw biomass with 4 wt.% of halloysite). Additionally, the main combustion parameters, like the ignition temperature, the maximum peak temperature, the burnout temperature, and some combustion indexes, are presented. The results show the effect of a heating rate in the range of 5–20 °C/min. Moreover, in this study, two non-isothermal model methods (Kissinger and Ozawa) are used to estimate energy activation. While halloysite slightly affects the combustion indexes and marginally reduces energy activation, its overall influence does not significantly alter combustion efficiency. These findings support the potential and safe use of halloysite for the biomass combustion process. Full article

The accelerated urbanisation that is occurring in many regions of the world is resulting in a corresponding increase in the volume of sewage sludge. This sludge is then stored in specialised landfills, the area of which is increasing annually. One of the methods of utilising this sludge is through its combustion in power plants, where it serves to generate heat. However, due to the low calorific value of sewage sludge, it is recommended to combust it in conjunction with high-calorific fuel. To improve energy efficiency of sewage residue biomass utilisation by co-combustion with coal, it is necessary to determine the main combustion parameters and mass fraction in the mixture. The objective of this study is to estimate the primary parameters of combustion of sewage sludge and coal by employing the synchronous thermal analysis method, in addition to determining the concentrations of gaseous substances formed during the combustion process. A comprehensive technical and elemental analysis of the fuels was conducted, and their thermal properties were thoroughly determined. The inorganic residue from sewage sludge combustion was analysed by scanning electron microscopy for the content of trace elements and basic oxides. Thermogravimetric analysis (TGA) of fuels was conducted in an oxidising medium, utilising a 6 mg suspension with a heating rate of 20 °C/min. The profiles of TG, DTG, and DSC curves were then utilised to determine the ignition and burnout temperatures, maximum mass loss rate, combustion index, and synergistic effects. The mixture of coal with 25% sewage sludge was found to have the most energy-efficient performance compared to other mixtures, with a 3% reduction in ignition temperature compared to coal. Concentrations of carbon dioxide, carbon monoxide, nitrogen oxides, and sulphur oxides were also determined. Full article

Enhancing the operational flexibility and environmental performance of coal-fired boilers under wide-load conditions presents a critical challenge in China’s low-carbon transition, particularly for low-quality coals (LQCs) with abundant reserves, poor combustibility, and high NO_x emissions. To overcome the intrinsically low reactivity of LQC, peak-shaving performance and combustion behavior were systematically investigated on an MW-grade pilot-scale test platform employing the fuel modification strategy in this study. Stable fuel modification was achieved without any auxiliary energy for LQCs and Shenmu bituminous coal (SBC) across a load range of 20~83% and 26~88%, respectively, demonstrating the excellent fuel reactivity and strengthened release control of volatile and nitrogenous species. The modified LQC exhibited ignition, combustion, and burnout characteristics comparable to Shouyang lean coal (SLC), enabling a “dimensionality-reduction utilization” strategy. The double-side fuel modification device (FMD) operation maintained axially symmetric temperatures (<1250 °C) in horizontal combustion chambers, while single-side operation caused thermal asymmetry, with peak temperatures skewed toward the FMD side (<1200 °C). Original NO_x emissions were effectively suppressed, remaining below 106.89 mg/m³ (@6%O₂) for LQC and 122.76 mg/m³ (@6%O₂) for SBC over broad load ranges, and even achieved ultra-low original NO_x emissions (<50 mg/m³). Distinct load-dependent advantages were observed for each coal type: SBC favored high-load thermal uniformity and low-load NO_x abatement, whereas LQC exhibited the inverse trend. These findings underscore the importance of a load-adaptive coal selection and FMD operation mode. This study provides both theoretical insights and engineering guidance for retrofitting coal-fired power units toward flexible, low-emission operation under deep peak-shaving scenarios. Full article

The increasing severity of climate-related workplace hazards challenges occupational health and safety, particularly for Public Health and Safety Inspectors. Exposure to extreme temperatures, air pollution, and high-risk environments heightens immediate physical threats and long-term burnout. This study employs Artificial Intelligence (AI)-driven predictive analytics and secondary data analysis to assess hazards and forecast burnout risks. Machine learning models, including eXtreme Gradient Boosting (XGBoost 3.0), Random Forest, Autoencoders, and Long Short-Term Memory (LSTMs), achieved 85–90% accuracy in hazard prediction, reducing workplace incidents by 35% over six months. Burnout risk analysis identified key predictors: physical hazard exposure (β = 0.76, p < 0.01), extended work hours (>10 h/day, +40% risk), and inadequate training (β = 0.68, p < 0.05). Adaptive workload scheduling and fatigue monitoring reduced burnout prevalence by 28%. Real-time environmental data improved hazard detection, while Natural Language Processing (NLP)-based text mining identified stress-related indicators in worker reports. The results demonstrate AI’s effectiveness in workplace safety, predicting, classifying, and mitigating risks. Reinforcement learning-based adaptive monitoring optimizes workforce well-being. Expanding predictive-driven occupational health frameworks to broader industries could enhance safety protocols, ensuring proactive risk mitigation. Future applications include integrating biometric wearables and real-time physiological monitoring to improve predictive accuracy and strengthen occupational resilience. Full article

The impetus of the present work is to propose a comprehensive methodology for the numerical evaluation of drying/curing, as one of the most complex and energy-consuming stages in the paint shop plant, to guarantee a decrease in energy costs without sacrificing the final paint film quality and manufacturability. Addressing the complexities of vehicle assembly, such as intricate geometry and multi-zoned ovens, our approach employs a sophisticated conjugate heat transfer (CHT) algorithm, developed under the OpenFOAM framework, providing efficient heat transfer with the accompaniment of the Large Eddy Simulation (LES) turbulence model, thereby delivering high-fidelity data. This algorithm accurately simulates turbulence and stress in the oven, validated through heat sink cases and closely aligning with experimental data. Applying modifications for the intake supply heated airflow rate and direction leads to optimal recirculation growth in the measured mean temperature within with the curing oven and along the car body surface, saving a significant amount of energy. Key adjustments in airflow direction improved temperature regulation and energy efficiency while enhancing fluid dynamics, such as velocity and temperature distribution. Furthermore, the study integrates machine learning to refine the oven’s heat-up region, which is crucial for preventing paint burnout. A data-based model using a variational auto-encoder (VAE) and an artificial neural network (ANN) effectively encodes temperature and velocity fields. This model achieves an impressive 98% accuracy within a 90% confidence interval, providing a reliable tool for predicting various operational conditions and ensuring optimal oven performance. Full article

The fir-tree blade tenon is an important connection part of the turbine blade; its machining quality directly affects the life and power of the aeroengine. At present, the machining of the blade tenon requires multiple profile grinding processes. This study highlights the whole profile of the grinding processes of K4002 nickel-based superalloy blade tenons in ultrasonic vibration-assisted grinding (UVG). A probability superposition method was utilized to calculate the undeformed chip thickness and contact rate considering the random distribution of the abrasive grains and the overlap of the grinding trajectories. Subsequently, the grinding force, grinding temperature and surface integrity of the blade tenons in conventional grinding (CG) and UVG were investigated. The results indicate that the ultrasonic vibration causes intermittent cutting behavior which can reduce the contact rate to 0.6 at most. The grinding force, grinding temperature and surface integrity are deeply affected by the fir-tree shape of the blade tenon. The maximum grinding force occurs at the start of the full contact stage; surface burnout easily occurs in the middle top area of the blade tenon. Compared to CG, the use of UVG leads to an average reduction in the grinding force and temperature by 20% and 23%, respectively, improving the surface burnout of the K4002 superalloy. Full article

As part of the transition to low-carbon energy and for the sustainable utilisation of resources, it is necessary to seek a replacement for solid fossil fuels, but unfortunately, it is impossible to completely abandon them for various reasons at the moment, so only partial replacement with new, high-calorific, biomass-based fuels is possible. The purpose of this work is to determine the typical parameters of the co-combustion of carbonisate, coal and their mixtures, taking into account the synergetic effects influencing the combustion intensity of the mixture. Carbonisate was obtained in the process of the gasification of pinewood through the counter-blowing method at a temperature of 800–900 °C, while air was used as an oxidant. Basically, this method of gasification is used for coal in order to obtain high-calorific coke for the metallurgical industry. Also, in this study, for the first time, carbonisate was obtained from 50% pinewood and 50% lignite. The O/C and H/C ratios were determined for carbonisate. A technical and elemental analysis of the investigated fuels was carried out. A thermal analysis in oxidising medium was applied to determining the typical combustion parameters in the process of slow heating of the fuels under study. According to the results of this thermal analysis, typical heating parameters such as the ignition temperature, burnout temperature, maximum mass loss rate, combustion index, etc., were determined. It was noted that the calorific value of carbonised wood is two times higher than that of coal. The combustion index of carbonisates is 2.5–36% lower compared to that of coal. According to the results of the analysis of the interaction of the components among themselves (in the process of their joint combustion), the presence of synergetic interactions between the components was determined, which affected the change in the combustion intensity and heat release intensity. The results of this study may be useful for retrofitting coal-fired boilers to run on a mixture containing carbonisate and lignite. If carbonisate is produced from biomass, the resulting gas could be used as an energy fuel by burning it in a coal-fired boiler. Full article

This study investigated the influence of particle size on combustion performance using equivalent characteristic spectrum analysis (ECSA) on a TG-MS platform. The experiments were conducted at heating rates of 10 °C/min and 20 °C/min for three granular coal types with particle sizes of 1 mm, 4 mm, and 8 mm. The results showed that the ignition temperature, burnout temperature, and burnout time generally increased with particle size, while the combustion characteristic index for the 8 mm particles was 28.81% lower than that for 1 mm particles. The particle size effects were more pronounced at lower heating rates. Combustion kinetics revealed that the pre-combustion endothermic stage had a significant impact on the ignition temperature, followed by the volatilization stage. For Shenmu bituminous coal (SBC), a 1 kJ/mol reduction in apparent activation energy during the endothermic stage increased the ignition temperature by 13.02 °C (10 °C/min) or 17.11 °C (20 °C/min). Similar trends were observed for Datong bituminous coal (DBC) and Jincheng anthracite coal (JAC). A gas product analysis indicated that the peak release temperatures rose with particle size, and particle size variations affected the maximum release rates and combustion stage duration. Smaller particles generally released less NO during combustion. Full article

This study focused on evaluating the combustion ignition, burnout, stability, and intensity of Hwange coal and Pinus sawdust blends within a drop tube furnace (DTF) through modelling. The cocombustion of coal with biomass is gaining attention as a strategy to improve fuel efficiency and reduce emissions. Hwange coal, a key energy source in Zimbabwe, produces significant emissions, while Pinus sawdust offers a renewable alternative with favourable combustion properties. Optimising cocombustion performance is highly dependent on understanding various mass- and energy-conservation-related parameters in detail, hence the motivation of this study. The fuels of interest were blended through increasing the Pinus sawdust mass percentages up to 30%. A DTF that is 2 m long and 0.07 m in diameter was modelled and validated successfully using particle residence time and temperature profiles. An increase in blending resulted in an increase in combustion intensity, as made apparent by the heat of reaction profiles, which were also shown to be dependent on the kinetic rate of the reaction between CO and O₂ to form CO₂. The burnout rate profiles demonstrated that as blending increased, heat was released more abruptly over a short distance; hence, combustion became less stable. The burnout rate profiles were shown to be dependent on the kinetic rate of reaction between char and O₂ to form CO. The effect of DTF wall temperatures (1273, 1473, and 1673 K) was also studied, with the results showing that at a low temperature, the reaction zone was delayed to a distance of 0.8 m from the injection point, as compared to 0.4 m at 1673 K. In summary, this study demonstrated that combustion ignition, burnout, and intensity increased with the blending ratio of Pinus sawdust, whilst combustion stability decreased. Full article

This paper reports studies on the thermal chemistry of the flash pyrolysis (heating rate of 20,000 °C/s up to 800 °C) of non-fossil fuel carbon (NFF-C) waste (or refuse-derived fuel, RDF) in the context of using this as an alternative reductant for blast furnace ironmaking. Gas chromatography–mass spectrometry (GCMS) analysis linked to the pyrolyser was used to simulate the thermal processes that take place during injection in the blast furnace raceway, where material experiences extreme temperature (ca. 1000 °C) over very short residence times (<300 ms). Species identification and qualitative analysis of evolved species generated are reported. Whilst the pyrolyser uses flash heating of a static sample, a drop tube furnace was also employed to study a sample moving rapidly through a pre-heated furnace held at 1000 °C to enable reductant burnout rates to be measured. The overarching aim of this piece of work is to study the suitability of replacing fossil fuel with non-recyclable plastic and paper as blast furnace reductants. Full article

The catalytic performance of mixed metal oxides in the combustion of paper industrial waste (bark, paper sludge, and waste paper reject) was investigated. The mixed metal oxide catalyst with, SiO₂, Al₂O₃, Fe₂O₃, and CaO percentages of 78.57, 9.28, 4.28, and 7.85, respectively, was prepared by mixing iron mill scale, clinker, used cement, and bentonite clay, which were employed as metal oxide precursors. An analysis of the combustion behavior of bark, paper sludge, and waste paper reject with and without a mixed metal oxide catalyst, using the thermogravimetric analysis technique, showed that the ignition temperature remained unchanged after the addition of the catalyst. In contrast, the burnout temperature was reduced from 616.9 to 482.6 °C, 682.0 to 672.5 °C, and 678.1 to 669.9 °C for bark, paper sludge, and waste paper reject, respectively. These results indicated that adding a mixed metal oxide catalyst enhanced the combustion reactivity via the accelerated char combustion of biomass. Furthermore, the products formed during the combustion process with and without a catalyst were investigated in a packed-bed reactor. The gaseous products (H₂, CO, CH₄, C₂H₄, C₂H₆, and CO₂) were observed during the combustion process of bark, paper sludge, and waste paper reject at 700 °C, both with and without a mixed metal oxide catalyst. However, higher H₂ and CO₂ compositions, which are attributed to the catalyst addition, were found in the presence of a catalyst, which improved the tar decomposition and the water–gas shift reaction. Full article

In the domain of metal casting, investment casting is recognized for its proficiency in producing high-quality castings. This method involves the utilization of a melt out, burnout, or soluble patterns to create ceramic molds. The present investigation explored the potential of utilizing fused deposition modeling (FDM) patterns fabricated from polyvinyl alcohol (PVA). An examination of the structural characteristics and properties of several commercially available PVA filaments, along with an evaluation of the as-printed samples, were provided in this study. It was demonstrated that commercial PVA filaments may contain additives that can lead to elevated ash content following pattern burnout and reduced strength in as-printed samples. Experiments on PVA dissolution in water revealed that, for high dissolution rates of the pattern, not only high temperature, but also water medium mixing was necessary. The colloidal silica binder, a common component in ceramic mold manufacturing, exhibited effective wetting properties of the patterns, while generally preventing significant dissolution, which can adversely impact pattern quality. The PVA filaments under investigation were utilized to fabricate patterns for the impeller cast parts. Subsequent to this, ceramic molds were obtained, and castings made of nickel superalloy were produced. The investigation revealed that the Bambu Lab filament, which is PVA without additives, exhibited the lowest defect rate in both the mold and the casting. In summary, this study demonstrates that the 3D printing of investment casting patterns holds considerable promise as a rapid casting technique. Full article