cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29900013.v1
title: Effect of different functional groups of octane boosters on anti-knocking performance and fuel efficiency

description: A series of compounds possessing high octane numbers, including alcohols, ethers, benzenes, and cycloalkanes, are used as octane boosters for gasoline. In this paper, the research (RON) and motor (MON) octane number of gasoline fuel with octane boosters were measured using a standard cooperative fuel research (CFR) engine. The brake specific fuel consumption (BSFC) and the combustion process of these blends were measured on an engine bench. The results highlighted the synergistic effect (measured value higher than calculated value) of ethanol in gasoline fuel, with an increase in RON of 3.7 for every 10 vol/% increase, and had low octane sensitivity to gasoline. Cyclopentane had a significant antagonistic effect (measured value lower than calculated value). 1,2-Xylene had the lowest octane sensitivity to gasoline fuel, with an octane sensitivity (OS) of 5.7 at 30 vol/%. The BSFC of ethanol was 2.06% higher than others, but the economic cost was 14.15% lower due to the price. There were limited effects of octane boosters on the combustion, all of which had appropriate content to improve the combustion process. In developing high anti-knocking fuels, a comprehensive decision can be made by considering the effects of octane boosters, combustion, toxicity, price, and cost.
DOI: 10.6084/m9.figshare.30294326
title: Fuel oil recovery from waste polybutylene plastic using microwave-assisted pyrolysis

description: Microwave-assisted pyrolysis of plastics has emerged as a promising technology for sustainable oil recovery, while also addressing environmental pollution. In this study, the microwave-assisted pyrolysis of waste polybutylene was investigated for the first time, focusing on the recovery of fuel oil. The effects of polybutylene size (0 - 2, 2 - 4, 4 - 6, 6 - 8, and 8 - 10 mm), microwave power (500, 550, 600, 650, and 700 W), and pyrolysis temperature (420, 440, 460, 480, and 500 °C) on products distribution, oil composition, and higher heating value (HHV) of the pyrolysis oil were detailed. The results revealed that increasing polybutylene size, microwave power, and pyrolysis temperature initially promoted an increase in oil yield, followed by a subsequent decline. The oil yield was in the range of 58.6–87.1 wt.%, with a HHV range of 44.93–47.07 MJ/kg. The maximum oil yield was achieved at a polybutylene size of 4–6 mm, microwave power of 600 W, and pyrolysis temperature of 480°C, with the corresponding oil exhibiting a HHV of 46.59 MJ/kg. The oil was dominated by alkane (12.52–27.68 area%), alkene (26.01–51.18 area%), alkyne (0.17–2.49 area%), cycloalkane (25.79–51.15 area%), cycloalkene (1.08–6.22 area%), and the carbon numbers mainly distributed in C5-C18 (65.39–80.79 area%). This study provided valuable insights and supporting data for the efficient recovery and sustainable utilization of waste polybutylene via microwave-assisted pyrolysis.
DOI: 10.6084/m9.figshare.30294326.v1
title: Fuel oil recovery from waste polybutylene plastic using microwave-assisted pyrolysis

description: Microwave-assisted pyrolysis of plastics has emerged as a promising technology for sustainable oil recovery, while also addressing environmental pollution. In this study, the microwave-assisted pyrolysis of waste polybutylene was investigated for the first time, focusing on the recovery of fuel oil. The effects of polybutylene size (0 - 2, 2 - 4, 4 - 6, 6 - 8, and 8 - 10 mm), microwave power (500, 550, 600, 650, and 700 W), and pyrolysis temperature (420, 440, 460, 480, and 500 °C) on products distribution, oil composition, and higher heating value (HHV) of the pyrolysis oil were detailed. The results revealed that increasing polybutylene size, microwave power, and pyrolysis temperature initially promoted an increase in oil yield, followed by a subsequent decline. The oil yield was in the range of 58.6–87.1 wt.%, with a HHV range of 44.93–47.07 MJ/kg. The maximum oil yield was achieved at a polybutylene size of 4–6 mm, microwave power of 600 W, and pyrolysis temperature of 480°C, with the corresponding oil exhibiting a HHV of 46.59 MJ/kg. The oil was dominated by alkane (12.52–27.68 area%), alkene (26.01–51.18 area%), alkyne (0.17–2.49 area%), cycloalkane (25.79–51.15 area%), cycloalkene (1.08–6.22 area%), and the carbon numbers mainly distributed in C5-C18 (65.39–80.79 area%). This study provided valuable insights and supporting data for the efficient recovery and sustainable utilization of waste polybutylene via microwave-assisted pyrolysis.
DOI: 10.6084/m9.figshare.30165378
title: Experimental investigation of combustion and emission characteristics of biodiesel-alcohol blends with identical C/H/O mass ratio

description: The effects of biodiesel-alcohol blends with varying volume ratios on diesel engine performance have been extensively studied. Isolating the impact of alcohol molecular structure from oxygen content presents a significant challenge due to concurrent changes in the C/H/O ratio with blend composition. This study introduces an elemental-constrained fuel blending approach to develop new fuel formulations based on an existing biodiesel-alcohol blend. Two blends with identical elemental mass ratios of biodiesel and ethanol (BE: C 72.74% wt, H 12.26% wt, O 15.00% wt) were prepared using biodiesel, methanol, butanol, and pentanol. Their cetane number, ignition delay, density, viscosity, and cold filter plugging point (CFPP) were measured. Combustion and emission performance were experimentally evaluated on a diesel engine test bench under 56 Nm, 140 Nm, and 224 Nm conditions. The results show close physiochemical properties and similar combustion performance among the three blends. However, significant variations were observed in gaseous and particulate emissions. The biodiesel-methanol-pentanol (BMP) blend reduced fuel consumption by 3.3% and 3.7%, NOₓ emissions by 0.84 g/kWh and 0.23 g/kWh and particle mass concentration by 10.9 mg/kWh and 67.9 mg/kWh, while it increased particle number concentration by 0.1 × 10<sup>7</sup> and 0.8 × 10<sup>7</sup> #/cm<sup>3</sup> at 56 Nm and 224 Nm loads, respectively.
DOI: 10.6084/m9.figshare.30165378.v1
title: Experimental investigation of combustion and emission characteristics of biodiesel-alcohol blends with identical C/H/O mass ratio

description: The effects of biodiesel-alcohol blends with varying volume ratios on diesel engine performance have been extensively studied. Isolating the impact of alcohol molecular structure from oxygen content presents a significant challenge due to concurrent changes in the C/H/O ratio with blend composition. This study introduces an elemental-constrained fuel blending approach to develop new fuel formulations based on an existing biodiesel-alcohol blend. Two blends with identical elemental mass ratios of biodiesel and ethanol (BE: C 72.74% wt, H 12.26% wt, O 15.00% wt) were prepared using biodiesel, methanol, butanol, and pentanol. Their cetane number, ignition delay, density, viscosity, and cold filter plugging point (CFPP) were measured. Combustion and emission performance were experimentally evaluated on a diesel engine test bench under 56 Nm, 140 Nm, and 224 Nm conditions. The results show close physiochemical properties and similar combustion performance among the three blends. However, significant variations were observed in gaseous and particulate emissions. The biodiesel-methanol-pentanol (BMP) blend reduced fuel consumption by 3.3% and 3.7%, NOₓ emissions by 0.84 g/kWh and 0.23 g/kWh and particle mass concentration by 10.9 mg/kWh and 67.9 mg/kWh, while it increased particle number concentration by 0.1 × 10<sup>7</sup> and 0.8 × 10<sup>7</sup> #/cm<sup>3</sup> at 56 Nm and 224 Nm loads, respectively.
DOI: 10.6084/m9.figshare.30016769
title: Transient prediction model for temperature in horizontal well drilling considering drill string and fluid dynamics

description: Accurately predicting temperature distribution in horizontal wells is essential for controlling bottom-hole temperatures and improving drilling efficiency. In this study, we developed a temperature field model based on energy conservation to examine the effect of frictional heat between the drill string and wellbore during horizontal drilling. The dynamic changes in the rheology of oil-based drilling fluids were also considered. Field data validated the model. The results indicate that frictional heat and fluid dynamics are critical factors in temperature prediction for horizontal wells. Findings also reveal that WOB significantly affects annular temperature distribution in the build section, whereas its effect on the vertical section is minimal. Increased rotary speeds enhance the frequency of contact between the drill string and wellbore, generating additional frictional heat and subsequently raising the annular fluid temperature. When WOB fluctuates between 50% and 200%, the associated change in bottom-hole temperature does not exceed 0.25%. When rotary speed adjusted within the range of 30% to 70%, it yields a temperature reduction rate of approximately 0.5%. The effect of various operational control parameters on the reduction of bottom-hole temperatures has been quantified. These parameters are ranked in terms of their effectiveness for temperature reduction as follows: inlet temperature &gt; circulation rate &gt; circulation time &gt; drilling fluid density &gt; WOB &gt; rotary speed. These findings provide theoretical guidance for predicting bottom-hole temperatures and optimizing drilling strategies.
DOI: 10.6084/m9.figshare.30016769.v1
title: Transient prediction model for temperature in horizontal well drilling considering drill string and fluid dynamics

description: Accurately predicting temperature distribution in horizontal wells is essential for controlling bottom-hole temperatures and improving drilling efficiency. In this study, we developed a temperature field model based on energy conservation to examine the effect of frictional heat between the drill string and wellbore during horizontal drilling. The dynamic changes in the rheology of oil-based drilling fluids were also considered. Field data validated the model. The results indicate that frictional heat and fluid dynamics are critical factors in temperature prediction for horizontal wells. Findings also reveal that WOB significantly affects annular temperature distribution in the build section, whereas its effect on the vertical section is minimal. Increased rotary speeds enhance the frequency of contact between the drill string and wellbore, generating additional frictional heat and subsequently raising the annular fluid temperature. When WOB fluctuates between 50% and 200%, the associated change in bottom-hole temperature does not exceed 0.25%. When rotary speed adjusted within the range of 30% to 70%, it yields a temperature reduction rate of approximately 0.5%. The effect of various operational control parameters on the reduction of bottom-hole temperatures has been quantified. These parameters are ranked in terms of their effectiveness for temperature reduction as follows: inlet temperature &gt; circulation rate &gt; circulation time &gt; drilling fluid density &gt; WOB &gt; rotary speed. These findings provide theoretical guidance for predicting bottom-hole temperatures and optimizing drilling strategies.
DOI: 10.6084/m9.figshare.30436923
title: Experimental study on microwave heating performances of soybean straw briquettes

description: Soybean straw briquettes were used in this study to explore the impacts of fuel length (10–50 mm) and microwave power (400–800 W) on the heating performances, with incremental steps of 10 mm and 100 W, respectively. The relationships between average heating rate and affect factors (fuel length and microwave power) were established. Also, the changes in the microstructure, specific surface area, and pore size of the soybean straw briquettes were presented. The results indicate that for fuel lengths of 10–50 mm, the average heating rate of the soybean straw briquettes were 20.83–53.53 °C/min. At microwave powers of 400–800 W, the average heating rates were 15.63–38.46 °C/min. After microwave heating, the microstructure of the soybean straw briquettes showed significant improvements. The specific surface area and pore volume exhibited a tendency that initially ascended and thereafter descended, while the average pore size followed the opposite trend when the fuel length or microwave power increased. At 600 W microwave power, 30 mm fuel length, and a final heating temperature of 250°C, the specific surface area and pore volume reached their maximum values of 0.769 m<sup>2</sup>/g and 0.0034 cm<sup>3</sup>/g, respectively, while the average pore size was minimized at 11.073 nm. These results demonstrate that microwave pretreatment significantly enhances the thermochemical conversion potential of soybean straw briquettes by optimizing pore structure and heating efficiency. The study provides critical theoretical guidance for scalable, energy-efficient biomass valorization, advancing sustainable bioenergy production aligned with carbon neutrality goals.
DOI: 10.6084/m9.figshare.30436923.v1
title: Experimental study on microwave heating performances of soybean straw briquettes

description: Soybean straw briquettes were used in this study to explore the impacts of fuel length (10–50 mm) and microwave power (400–800 W) on the heating performances, with incremental steps of 10 mm and 100 W, respectively. The relationships between average heating rate and affect factors (fuel length and microwave power) were established. Also, the changes in the microstructure, specific surface area, and pore size of the soybean straw briquettes were presented. The results indicate that for fuel lengths of 10–50 mm, the average heating rate of the soybean straw briquettes were 20.83–53.53 °C/min. At microwave powers of 400–800 W, the average heating rates were 15.63–38.46 °C/min. After microwave heating, the microstructure of the soybean straw briquettes showed significant improvements. The specific surface area and pore volume exhibited a tendency that initially ascended and thereafter descended, while the average pore size followed the opposite trend when the fuel length or microwave power increased. At 600 W microwave power, 30 mm fuel length, and a final heating temperature of 250°C, the specific surface area and pore volume reached their maximum values of 0.769 m<sup>2</sup>/g and 0.0034 cm<sup>3</sup>/g, respectively, while the average pore size was minimized at 11.073 nm. These results demonstrate that microwave pretreatment significantly enhances the thermochemical conversion potential of soybean straw briquettes by optimizing pore structure and heating efficiency. The study provides critical theoretical guidance for scalable, energy-efficient biomass valorization, advancing sustainable bioenergy production aligned with carbon neutrality goals.
DOI: 10.6084/m9.figshare.17293951
title: Synergistic effect of blast furnace slag on the pyrolysis process of oil-rich coal, tar product distribution and kinetic analysis

description: Low-rank coal is used as raw material, solid waste blast furnace slag (BFS) rich in metal oxides is selected as catalyst. Co-pyrolysis experiment is carried out and explore the influence of different BFS particle size and doping amount on coal pyrolysis. The catalyst is characterized by FT-IR, XRD, TG, and the contribution degree and mechanism of BFS to the increase of oil-rich kerosene products are clarified. The results show that BFS exhibits good activity. When the added amount of BFS is 9%, the tar yield is as high as 14.65%. When the particle size is 2–5 mm, the tar yield is 14.1%. Adding BFS catalyst can improve the tar yield. By controlling the particle size and addition amount, the composition of the tar can be adjusted to achieve directional pyrolysis. According to coal kinetic analysis, when the temperature is 350–600℃, the overall activation energy in the pyrolysis process is the highest, and the first reaction is the most active.
DOI: 10.6084/m9.figshare.17293951.v1
title: Synergistic effect of blast furnace slag on the pyrolysis process of oil-rich coal, tar product distribution and kinetic analysis

description: Low-rank coal is used as raw material, solid waste blast furnace slag (BFS) rich in metal oxides is selected as catalyst. Co-pyrolysis experiment is carried out and explore the influence of different BFS particle size and doping amount on coal pyrolysis. The catalyst is characterized by FT-IR, XRD, TG, and the contribution degree and mechanism of BFS to the increase of oil-rich kerosene products are clarified. The results show that BFS exhibits good activity. When the added amount of BFS is 9%, the tar yield is as high as 14.65%. When the particle size is 2–5 mm, the tar yield is 14.1%. Adding BFS catalyst can improve the tar yield. By controlling the particle size and addition amount, the composition of the tar can be adjusted to achieve directional pyrolysis. According to coal kinetic analysis, when the temperature is 350–600℃, the overall activation energy in the pyrolysis process is the highest, and the first reaction is the most active.
DOI: 10.6084/m9.figshare.30315548
title: Intelligent prediction of short-term photovoltaic power output based on PSO-RF and LASSO-penalized multi-kernel learning-based robust regression algorithm

description: The utilization of solar energy plays a significant role in alleviating the energy crisis and promoting sustainable development. However, photovoltaic (PV) power generation is impacted by several complex factors that cause discontinuity and randomness problems. This paper presents a novel approach to improving the precision of PV power forecasting, based on a LASSO-penalized multi-core learning-based robust regression algorithm with random forest (RF) optimization. This was further enhanced using particle swarm optimization (PSO). Initially, the PSO-RF was employed to identify the key variables influencing the PV output power. Second, the issue of a shallow Gaussian multi-core structure was addressed by employing the multi-kernel learning (MKL) method, which was used to construct a highly robust depth mapping kernel based on the multi-layer information of deep neural networks. A multiscale Gaussian kernel was combined with a kernel matrix to create an improved kernel. This paper presents a novel computational approach based on local quadratic approximation for solving models. The findings indicate that the robust multi-core sparse prediction model developed in this paper achieves enhanced prediction accuracy and robustness. Regarding the coefficient of determination, the PSORF-LPMKLRRA model achieves the highest value of 0.998, demonstrating a closer approximation to 1 than the alternative predictive models.
DOI: 10.6084/m9.figshare.30315548.v1
title: Intelligent prediction of short-term photovoltaic power output based on PSO-RF and LASSO-penalized multi-kernel learning-based robust regression algorithm

description: The utilization of solar energy plays a significant role in alleviating the energy crisis and promoting sustainable development. However, photovoltaic (PV) power generation is impacted by several complex factors that cause discontinuity and randomness problems. This paper presents a novel approach to improving the precision of PV power forecasting, based on a LASSO-penalized multi-core learning-based robust regression algorithm with random forest (RF) optimization. This was further enhanced using particle swarm optimization (PSO). Initially, the PSO-RF was employed to identify the key variables influencing the PV output power. Second, the issue of a shallow Gaussian multi-core structure was addressed by employing the multi-kernel learning (MKL) method, which was used to construct a highly robust depth mapping kernel based on the multi-layer information of deep neural networks. A multiscale Gaussian kernel was combined with a kernel matrix to create an improved kernel. This paper presents a novel computational approach based on local quadratic approximation for solving models. The findings indicate that the robust multi-core sparse prediction model developed in this paper achieves enhanced prediction accuracy and robustness. Regarding the coefficient of determination, the PSORF-LPMKLRRA model achieves the highest value of 0.998, demonstrating a closer approximation to 1 than the alternative predictive models.
DOI: 10.6084/m9.figshare.29437393
title: Numerical investigation on the lean-burn methanol in the main chamber with different active pre-chamber geometries and initial temperature

description: Methanol, a promising alternative fuel, has garnered extensive attention within the international internal combustion engine community. Nevertheless, its application in such engines faces challenges, including difficulties with cold starting under light load conditions, combustion instability, and elevated unconventional emissions. The pre-chamber jet ignition technology, which enhances ignition energy and accelerates flame propagation, emerges as an efficacious solution to these issues. Accordingly, the research presented in this paper focuses on analyzing the effects of the active pre-chamber’s structural design and initial temperature on ignition jet behavior. Furthermore, it explores the dilution limit of jet-ignited methanol. Findings reveal that the concentration stratification and flame propagation process are substantially affected by the length-to-diameter ratio of the pre-chamber, with those having a smaller aspect ratio exhibiting higher combustion efficiency, jet flow rate, and turbulence intensity. An increase in the initial temperature markedly enhances the jet’s flow velocity and reactivity intensity. The combustion speed and heat release rate are observed to rise with the augmentation of the main chamber mixture’s equivalence ratio. Specifically, a pre-chamber with an aspect ratio (L/D) of 1 achieved a 17% higher combustion efficiency compared to L/D = 3, while the jet velocity peaked at 510 m/s for L/D = 1, compared to 440 m/s for L/D = 2 and 470 m/s for L/D = 3. An increase in the initial temperature from 600 K to 800 K markedly increased the OH radical mass fraction by 35%. The combustion speed and heat release rate were observed to rise with the augmentation of the main chamber mixture’s equivalence ratio. However, when the equivalence ratio falls below 0.3, the ignition delay period of the main chamber lengthens, giving rise to issues such as misfires and diminished combustion stability.