Ignition Point Research Articles

Study on controlling factors and developing a quantitative assessment model for spontaneous combustion hazard of coal gangue

Developing a quantitative hazard assessment model for spontaneous coal gangue combustion is imperative to ensuring the safety of coal mining operations. In this study, eight types of coal gangue from different coalfields were used to determine the controlling factors for spontaneous combustion. A variety of physical and chemical characterization methods were employed to investigate the physical and chemical characteristics of the samples. Based on the experimental results, six key parameters were identified, namely the aliphatic C–H components, pyrite sulfur content, physical oxygen absorption capacity, ash content, ignition point temperature, and activation energy for thermal decomposition. The results show that the spontaneous combustion hazard of coal gangue is positively correlated with the first three of these and is negatively correlated with the rest. Using the entropy-weight method combined with the analytic hierarchy process, appropriate weighting factors for each parameter were obtained and used to establish a quantitative assessment model for the spontaneous combustion hazard of coal gangue. This model is expected to enhance the current industrial best practices for the prevention and control of spontaneous coal gangue combustion.

Conversion of Low-Density Polyethylene (LDPE) and Mixed Low-Density Polyethylene with Polyethylene Terepthalate (LDPE and PET) into Hybrid Fuel

This research aims to provide the recycling techniques of low-density polyethylene (LDPE) and mixture of polyethylene terephthalate (PET) with low-density polyethylene (LDPE) waste. As a means of converting abundant waste to wealth, pyrolysis of LDPE and mixed LDPE - PET was carried out in a batch reactor made of stainless steel at temperatures between 450 – 460OC. The vapor produced from melting the waste was condensed to form the liquid hydrocarbon (fuel oil) product. The effect of reaction time and product yield were investigated. The physicochemical properties of the pyrolysis oil measured include density, specific gravity, flash point, color, fire point, flammability and viscosity. For the LDPE the flash point, fire point, density, specific gravity, and viscosity was found to be 39.5 oC, 48 oC, 8.1872, 0.793g/cm, 0.775g/cm3, and 1.566 cSt respectively while for the Mixture of LDPE with PET the flash point, fire point, density, specific gravity, viscosity and Sulphur content was found to be 44 oC, 48 oC, 8.1872, 0.7837g/cm, 0.7916 g/cm3, 1.1660 cSt and 8.1872 respectively. These values were found to be within the range of kerosene values. The fuel was tested in both kerosene lamp and petrol generator.

Numerical study of the cooling capacity of several alternative liquids in zig-zag cooling system of a power transformer

Mineral oil is the usual coolant of the power Transformers. Nonetheless, the high risk of fire of this liquid due to its low ignition point and its scarce biodegradability has promoted the development of dielectrics alternative fluids with better physical-chemical properties. However, these new liquids have to be as good coolants as mineral oil in order to maintain the power transformer performance. This numerical study analyzes the coolant capacity of some of these new commercial liquids (a natural ester, a synthetic ester, and a silicone oil) by using the zig-zag cooling system of the low voltage winding of a real power transformer. Two types of thermal-fluid studies (parametric and time-dependent studies) have been made by using a 3D model of this system. The comparison of temperatures obtained from the parametric study (different inlet flow rates) allow us to say that the worst coolant is the silicone oil. Also, it can be say that a significant increase in the inlet flow rate produces mild drops of hot-spots temperatures and no modification in the initial temperature distribution. For the time dependent study (25% of overload during 1 hour), the hot-spot temperature exceed the limits, which negatively affects the aging speed of the insulating paper and therefore the transformer lifetime.

Drought-related wildfire accounts for one-third of the forest wildfires in subtropical China

The threat of wildfires to human safety and ecosystem services is widely known to increase due to climate change characterized by drought. In subtropical China, seasonal drought during the non-monsoon period contributes to increase of fire risk. However, both the relationship between drought and wildfire and the extent of drought effect are poorly understood. Based on satellite active fire detections and monthly drought metrics, we quantified the impact of drought on forest wildfire frequency in subtropical China during 2001–2020, using a Bayesian hierarchical modelling framework. We observed excess wildfire, defined here as above normal wildfire activity level, is significantly correlated to drought across subtropical China, and drought-wildfire relationship showed threshold behavior that the probability of excess wildfire increased significantly when the vapor pressure deficit (VPD) crossed 0.24 standard deviations of its long-term average. From 2001 to 2020, excess wildfire caused by drought accounted for approximately 31 % of the total number of forest fire points during the fire season (November to May). The drought-related excess wildfire was concentrated in 2007–2010 and 2014, and their spatial distribution showed a dipole between the western and eastern subtropical China in individual years. Moreover, we evaluated the spatiotemporal sensitivity of wildfire to drought by Bayesian model coefficients. There was higher sensitivity than average level of the entire region in 54 % of subtropical China, especially in northwestern Yunnan. Our results indicate that drought plays a dominant role on wildfire regime at the regional scale in subtropical China. As the drying trend intensifies in the future, wildfires will show different patterns due to the large differences in the sensitivity of wildfire to drought in subtropical China.

Forest fire risk mapping with Landsat 8 OLI images: Evaluation of the potential use of vegetation indices

Fire is one of the most important natural catastrophes threatening the forest ecosystem. The severity and frequency of forest fires are increasing daily due to the increase in population in vulnerable areas and the effects of global climate change. Creating fire risk maps and using them to take the required protective actions to prevent fires will decrease the adverse effects of forest fires. This study focused on producing and comparing fire risk maps based on four vegetation indices, the Normalized Burn Ratio (NBR) index, Normalized Burn Ratio Thermal (NBRT) index, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI) and data gathered with the use of remote sensing devices. The Muğla Regional Directorate of Forestry, which is in the Mediterranean climate zone and has experienced mega-fires, was selected as the case study area. Fire risk maps were prepared for the four vegetation indices from Landsat 8 OLI satellite images. Receiver operating characteristic curves and 195 fire ignition points that occurred in 2021 from July 5 to the end of the year were used to assess the accuracy of fire risk maps. Most fire ignition locations (>90%) were in high- and extremely high-risk fire areas on the maps prepared according to the NBR, NDWI, and NDVI. The fact that almost all of the fires occurred in high-risk areas revealed that the study area was sensitive to fire and that the vegetation indices used to draw up the risk maps were highly accurate in predicting where fires might occur. The accuracy results showed that the area under the curve was 0.842 for the NBR, 0.835 for the NDWI, 0.812 for the NBRT, and 0.810 for the NDVI. The NBR approach was more precise than the other models in providing information for fire risk maps. Risk maps created with the NBR could help decision-makers to take precautions and minimize fire damage.

Fire resistance of 15 main economic tree species in Liangshan Prefecture, Sichuan, China.

Liangshan Prefecture is one of the three major forest areas in Sichuan Province and one of the three major disaster areas of forest fire. We measured the physicochemical properties and combustion performances of different organs (leaves and branches) of 15 main economic tree species in Liangshan, and analyzed the bioecology characteristics, silviculture characteristics and value characteristics of different tree species. We investigated the fire resistance of different tree species to screen out fire-resistant species suitable for economic forest development in Liangshan Prefecture, and improve the biological fire prevention ability. The seven physicochemical properties and combustion performances indices of 15 tree species showed significant differences. Except for crude ash and lignin, the weights of moisture content, caloric value, ignition point, crude fat, and crude fibre of leaves were higher than those of branches. Crude fibre index of leaves (9.6%) and the crude ash index of branches (9.9%) were the highest weight indices of the two organs, respectively. Based on the fire resistance, we divided all the species into three classes, i.e., class Ⅰ (excellent fire-resistance trees) Juglans regia and Morus alba; class Ⅱ (better fire-resistant trees) Sapium sebiferum, Mangifera indica, Phyllanthus emblica, Eriobotrya japonica, Ligustrum lucidum, Castanea mollissima, and Punica granatum; class Ⅲ (poor fire-resistant trees) Pinus armandii, Illicium simonsii, Morella rubra, Sapindus mukorossi, Olea europaea and Camellia oleifera. J. regia and M. alba had fireproof solid performance and could be used as the preferred species for fireproof economic forest in Liangshan region. It was suggested that to use class Ⅰ to Ⅱ fire-resistant tree species built the main fireproof isolated forest belt, and pay attention to fire prevention after planting class Ⅲ tree species in a large area.

Comparative Analysis of Physicochemical Properties of Oils from Groundnut, Melon, Watermelon and Orange Seeds

This study analyzed and compared the physicochemical properties of oils produced from groundnut, melon, watermelon and orange seeds. The moisture content, saponification value, iodine value, peroxide value, acid value, free fatty acid, ester value, refractive index, viscosity, density, specific gravity, cloud point, pour point, flash point and fire point of the oils were analyzed. There were no significant differences in iodine value, peroxide value, refractive index, viscosity, specific gravity, cloud point, pour point, flash point and fire point, while there were significant differences in the moisture content, saponification value, acid value, free fatty acid, ester value, and density, The results revealed that these oils contain low fatty acid value and they are good sources of edible oil as they have low acid value. These oils also have great potentials as industrially promising oils, with their high saponification and iodine values, they will be good raw materials for bio-lubricant production and for a variety of industrial applications.

Characterization of Oils from Sandbox, Melon and Watermelon Seeds

This study examined the physicochemical properties and phytochemical composition of oils from sandbox (Hura crepitans), melon (Citrullus colocynthis L) and watermelon (Citrullus lanatus) seeds. Physicochemical and phytochemical analyses of the oils were carried out using American Society for Testing and Materials (ASTM) and Association of Official Analytical Chemist (AOAC) standards procedures. Sandbox oil had highest saponification value, iodine value, acid value, ester value, viscosity, cloud point and pour point with lowest moisture content, free fatty acid, peroxide value, flash point and fire point when compare with oils from melon and water melon seeds. Oils from melon and water melon seeds have low acid value, which means it can be used as a good source of edible oil. The phytochemical screening of the oils revealed the presence of saponins, deoxysugar, terpenoids, cardinolides and steroids. These results revealed that oils from sandbox seed, melon and water melon seed have great potentials as industrially promising oils, with their high saponification and iodine values, they will be good raw materials for bio-lubricant production and for a variety of industrial applications.

Location prediction using forward geocoding for fire incident

Urban fires, although not a natural disaster, are a severe threat that often occurs in urban areas. Banjarmasin City, the capital of South Kalimantan Province and one of the most populous cities in Kalimantan, recorded 159 fire cases between 2020 and 2022, averaging nearly 53 cases yearly. In today’s digital era, people often share ongoing fire incidents using smartphones and update information on social media and online news. However, the resulting data could be more structured to serve as a dataset. This research addresses these issues by applying geocoding, a digital service that translates street addresses into geographic coordinates. This research uses three geocoders: Google Maps API, Bing Maps API, and Smart Monkey Geocoder. The accuracy of the three geocoders was tested using the Root Mean Square Error (RMSE) statistical method by comparing the geocoding results with valid locations. Prediction analysis was used to identify the next fire event through the density approach of the previous fire event points. This research is expected to provide insights into efficient data collection and structured data conversion, recommendations regarding the best geocoding service, and prediction of fire vulnerability locations based on recurring factors of fire incidents in the area. In conclusion, accurate data is the key to effective fire prediction.

Identification of forest fire points under clear sky conditions with Himawari-8 satellite data

ABSTRACT Since forest fire is one of the most dangerous natural disasters and presents serious threats to the local ecological environment, economic growth, and public safety, it is essential to carry out accurate and real-time forest fire monitoring. In this study, a forest fire monitoring method that combines a threshold-based algorithm and random forest (RF) model using Himawari-8 data is proposed. The threshold-based algorithm employs the solar zenith angle to adaptively determine the potential fire point judgement threshold to extract possible fire points. The RF model constructed with spectral features and spatio-temporal information is subsequently utilized to eliminate pseudo-fire points from the results of the threshold-based algorithm. To eliminate fire points in non-forest areas, post-processing is performed using land cover data. Five fire occurrence moments in the research area are selected to verify the identification accuracy. The results reveal that the overall accuracy and the overall comprehensive evaluation values are 97.36% and 0.913, respectively, which demonstrates that the proposed method is capable of accurately identifying forest fire points and providing an effective means for forest fire monitoring.

Forest Fire Risk Prediction Based on Stacking Ensemble Learning for Yunnan Province of China

Forest fire risk prediction is essential for building a forest fire defense system. Ensemble learning methods can avoid the problem of difficult model selection for disaster susceptibility prediction and can significantly improve modeling accuracy. This study introduces a stacking ensemble learning model for predicting forest fire risks in Yunnan Province by integrating various data types, such as meteorological, topographic, vegetation, and human activity factors. A total of 70,274 fire points and an equal number of randomly selected nonfire points were used to develop the model, with 70% of the data allocated for training and the remaining 30% for testing. The stacking model combined four diverse machine learning methods: random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP). We evaluated the model’s predictive performance using metrics like accuracy, area under the characteristic curve (AUC), and fire density (FD). The results demonstrated that the stacking fusion model exhibited remarkable accuracy with an AUC of 0.970 on the test set, significantly surpassing the performance of individual machine learning models, which had AUC values ranging from 0.935 to 0.953. Furthermore, the stacking fusion model effectively captured the maximum fire density in extremely high susceptibility areas, demonstrating enhanced generalization capabilities.

Preparedness of Rumah Ilmu Library in Facing Fire Disasters: Safety Education for Campus Society

Due to its contents and amenities, Rumah Ilmu, a library building at Universitas Negeri Semarang, is vulnerable to fire disasters. The goal of this study is to analyse the safety aspects of Rumah Ilmu building. In this study, a qualitative methodology and a descriptive strategy were applied and a direct interview with the informants was conducted to collect the data needed. This study was carried out between February and March of 2023. Rumah Ilmu building has met all the government's standards with the fulfilment of 10 components (71.42%), However, 3 components (21.42%) consisting of fire extinguishers, evacuation directions, and assembly points have been implemented but have not met the standards, and 1 component (7.16%) has not been implemented at all, namely the main gate. Suggestions for the preparedness of the Rumah Ilmu in dealing with disasters include increasing the number of fire extinguishers, sprinklers, and rescue facilities, such as installing emergency lighting, adding an area for assembly points, checking periodically related to exit door locking, and arranging an evacuation plan. Additionally, disaster mitigation education should be provided through training, educational videos, and posters to staff and visitors.

Experimental Tests on In Situ Combustion Using Dynamic Ignition Simulation System in High-Temperature and High-Pressure Conditions

The study of crude oil oxidation characteristics is fundamental to the design of ignition in situ combustion. Experimentation is the most crucial method for studying the oxidation characteristics of crude oil. Aiming to address the challenges posed by high temperature, high pressure, and rapid temperature changes during the combustion of crude oil, a dynamic simulation system for high-temperature and high-pressure ignition is designed. In order to study the oxidation characteristics of the crude oil ignition process, we conducted experiments using a high-temperature and high-pressure dynamic ignition simulation device. The experiments focused on determining the ignition point of crude oil under different pressure conditions, oil–water ratios, heating rates, gas injection rates, and other relevant characteristics. The kinetic model for the oxidation process of crude oil ignition was established. The kinetic parameters were calculated for different ignition conditions and the apparent activation energy for each oxidation stage was determined. Additionally, the stability of in situ combustion was evaluated under various ignition parameters. The results show that the Arrhenius curves for crude oil exhibit noticeable differences in the HTO (high-temperature oxidation) and LTO (low-temperature oxidation) regions. The curves demonstrate good linearity in the HTO region, with correlation coefficients exceeding 0.9. Moreover, the apparent activation energies in the HTO region range from 8.01 to 26.7 kJ/mol. The apparent activation energies and finger front factors were calculated for the HTO stage under different pressure conditions. The results showed that, as the pressure increased, the autoignition point, inflection point temperature, and apparent activation energy of the crude oil decreased. This suggests that increasing the pressure can enhance the HTO of the crude oil. The spontaneous ignition point of the crude oil exhibited an upward trend as the heating rate increased. Additionally, the maximum temperature during the combustion process generally increased with the heating rate, reaching a maximum temperature of 453.1 °C. The tests demonstrated that the simulation system is capable of real-time monitoring and recording of oxidation parameters during the combustion process of crude oil. This system can provide essential data for project implementation and numerical simulation.

Characterizing Forest Fuel Properties and Potential Wildfire Dynamics in Xiuwu, Henan, China

As global climate change and human activities increasingly influence our world, forest fires have become more frequent, inflicting significant damage to ecosystems. This study conducted measurements of combustible materials (moisture content ratio, ignition point, and calorific value) across 14 representative sites. We employed Pearson correlation analysis to ascertain the significant differences in combustible properties and utilized entropy methods to evaluate the fire resistance of materials at these sites. Cluster analysis led to the development of four combustible models. Using BehavePlus software, we simulated their fire behaviors and investigated the effects of wind speed and slope on these behaviors through sensitivity analysis. The results revealed notable differences in the moisture content ratios among different types of combustibles, especially in sites 2, 3, 8, 9, and 13, indicating higher fire risks. It was also found that while humus has a higher ignition point and lower calorific value, making it less prone to ignite, the resultant fires could be highly damaging. The Pearson analysis underscored significant variations in the moisture content ratios among different combustibles, while the differences in ignition points and calorific values were not significant. Sites 5 and 6 demonstrated stronger fire resistance. The simulations indicated that fire-spread speed, fireline intensity, and flame length correlate with, and increase with, wind speed and slope. Sensitivity analysis confirmed the significant influence of these two environmental factors on fire behavior. This study provides critical insights into forest fire behavior, enhancing the capability to predict and manage forest fires. Our findings offer theoretical support for forest fire prediction and a scientific basis for fire management decision-making.

Validation of NWCG Wildfire Directional Indicators in Test Burns in Coastal California

One of the primary tools used for determining the origin of a wildfire is analyzing burn patterns formed during the fire progression. These patterns, called fire pattern indicators, are interpreted and used to document the direction of fire movement at specific points, creating a directional map back to the specific area of origin. This concept was first set forth in 1978 by a U.S. governmental organization, the National Wildfire Coordinating Group (NWCG). Their recommendations are currently (2016) in the third edition, and in our study, we examine these indicators. Specifically, the objective was to perform a validation exercise where controlled burns were conducted of natural vegetation plots but augmented with 32 identical sets of staged artifacts which would provide additional opportunities for fire movement to create observable directional fire pattern indicators. Three adjacent plots were burned, each using a single point ignition, all located on level, scrubland terrain. The burns were conducted in the fall season, under low to moderate burning conditions. The research was structured as a preliminary study, since only mild terrain and weather conditions were encompassed. The actual fire movements were documented by drone videos, additional ground-based videos, and still photography. Within the three burn plots, a total of 12 data sites out of 32 data sites were selected: each one containing 7 to 12 individual artifacts. Each artifact was photographically documented post-fire, and the actual fire movement direction at that location was established. Assessment entailed the use of four experienced wildland fire investigators, with each one independently assessing the direction and type of fire spread at each artifact using the photographic site evidence. An analysis was then conducted to make a statistical comparison between the actual fire movement direction and the direction estimates provided by the experts analyzing the photographic evidence and the limited information on conditions provided. The results indicate an average error of 103°. These results indicate that additional efforts are needed to study the scientific basis of the indicators and to evolve improvements in both the indicators and in the accompanying guidance to investigators.

Performance evaluation of natural Olea europaea (olive oil)-based blended esters with butylated hydroxyanisole and butylated hydroxytoluene: optimization using response surface methodology.

For power transformer applications, this study explores an alternative insulating liquid. With this aim, edible natural esters such as refined Olea europaea (olive oil), rice bran oil, soya bean oil, sunflower oil, and corn oil are investigated as suitable replacements for the mineral oil (MO) used in the transformer. In addition, olive oil and other natural esters are incorporated into the blend for further analysis to obtain a better insulating medium. Blended natural esters were also tested for performance enrichment by antioxidant inclusion. Butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT) were chosen as antioxidants for this study. In this study, we aimed to investigate the role of key input factors [A-speed, B-time, and C-temperature] on the output response [Y-breakdown voltage]. It was determined that the optimal conditions for [Y] are [A-699.91 rpm, B-49.95 min, and C-88.75 °C]. In order to ensure the desirable properties, the natural esters were subjected to certain experimentations such as breakdown voltage (BDV), viscosity, fire point (FeP), and flash point (FhP). From the results, it is observed that the natural esters and blended natural esters can be used in the transformer as an alternate insulating medium and that the antioxidants have a significant effect on the properties of natural ester combinations.

COMPARATIVE ANALYSIS OF COMBAT CAPABILITIES OF MODERN TANKS OF VARIOUS TYPES

Modern war is a test of the material and spiritual forces of the people, the state and its Armed Forces, which prompts each country to maintain its defense capability at a level that guarantees reliable protection of society. Analysis of the nature of armed conflict in recent decades shows a sharp increase in the impact of modern weapons and military equipment on the course and outcome of military operations. Currently, weapons and military equipment form the basis of the combat power of the armed forces of any state and are the determining factor in achieving success in war or armed conflict. Despite the rapid development of anti-tank weapons and the decrease in survivability on the battlefield, main battle tanks remain one of the decisive means of modern combined arms combat, which is characterized by dynamism, saturation and speed. They provide the combat stability of their own forces in defense and advance during the offensive, destroy enemy armored vehicles, fire points and living forces. A comparative analysis of the main characteristics of modern combat tanks, the advantages and disadvantages of various types of vehicles of foreign and domestic production, used by the Armed Forces of Ukraine for the defense of the state and countering the aggression of Russia against Ukraine, in order to improve the effectiveness of their use in different conditions of combat. Western models of modern tanks and the Ukrainian tank "Oplot" in some significant combat characteristics prevail over the modern Russian tank T-90, in particular: in the power of the engine and its reliability of operation (engine overheating and failure); in the effectiveness of optoelectronic counteraction to optical enemy means; in the effectiveness of dynamic protection and countering modern weapons; in the perfection of the fire control system; in the sufficiency of the armor of the machine; in the effectiveness of actions in urban conditions. Keywords: war, battle tank, tactical and technical characteristics, effectiveness, comparative analysis

OPTIMIZATION OF NATURAL CATALYSTS IN OIL PRODUCTION FROM PLASTIC WASTE PYROLYSIS

This study was conducted to determine the effect of the amount of catalyst on yield from the pyrolysis of Polypropylene (PP) type plastic waste and to determine the characteristics of plastic waste pyrolysis oil which includes the physical and chemical properties of pyrolysis oil. The physical properties tested include viscosity, fire point, flash point, pour point, density, and water content while the chemical properties are compounds contained in pyrolysis oil using Gas ChromatoChromatography -Massmetry (GCMS) and knowing its calorific value. The research was conducted on the type of High-Density Polyethylene (HDPE), namely Polypropylene (PP) which was hydrolyzed in a batch reactor using an incinerator where heating originated from outside using wood powder and LPG. The ratio of raw materials used is as much as 1 kg of plastic with a variation of zeolite catalyst 0.25; 0.5; 0.75; 1 in kg. The results showed that the more catalysts added, the more pyrolysis oil was produced. The results of measuring oil at LEMIGAS kinematic viscosity at 40oC are 1.556 cST, 42 oC fire point, PMCC 26 o C flash point, pour point -42 o C, density at 15 o C 0.7857 g / cm3, and water content is 507.54 ppm . While the hydrocarbon compounds produced are pentene, heptane, and cyclohexane which have flammable properties. The calorific value produced from this pyrolysis oil is 40.947 Mj / Kg. The maximum amount of plastic oil volume is obtained by using 1 kg of raw material with 1 kg of 955 ml zeolite catalyst.

Physicochemical Characteristics of Oils Extracted from Selected Underutilized Seeds in Ozoro, Delta State, Nigeria

This work focuses on extracting oil from five local seeds using n-hexane in a Soxhlet apparatus. This study was designed to establish the suitability of the oils for domestic and industrial uses. Before extracting the oil, the nearest part of the seeds was inspected. Oils were extracted from selected underutilized seeds such as cashew (CS), orange seed (ORS), watermelon seed (WMS), paw-paw seed (PWS) and cherry seed (CHS) using n-hexane. The oil was analyzed for colour; with conventional techniques, calculate the saponification value, iodine value, acid value, percentage of unsaponifiable matter, and heat of combustion. The findings for proximal structure showed that fat ranged from 7.09 to 60.68% and protein from 17.97 to 31.16%. The levels of acidity, peroxide, iodine, saponification, unsaponifiable materials, and Polenske and density ranged from 1.07 to 5.94 mg KOH/g, 1.89 to 4.00 Meq/kg, 93.18 to 275.55 (MgI<sub>2</sub>/g), 68.41 to 326.16 KOH/g, 2.57 to 7.22 %, 1.37 to 7.44 and 0.74 to 0.87 g/L respectively. Smoke, flash, and fire points range from 75 to 90 0C, 80 to 170 0C and 230 to 300 0C respectively. According to the fatty acid composition, oleic and linoleic acid ranges were 17.14 and 60.63%, respectively. These criteria' values fell within the FAO's recommended range for edible oils. The samples used in the research oils are of high quality and suggested for use in industrial and culinary applications.

Study on the catalysis of copper-based compounds on coal spontaneous combustion and its mechanism

ABSTRACTTo study the effect of the copper element in coal on the spontaneous combustion process of coal, corresponding copper-containing compounds were added to the coal-based on their occurrence state, and thermodynamic experiments and in-situ diffuse reflectance infrared spectroscopy experiments were conducted. Thermodynamic oxidation experiments have shown that the catalytic effects of Cu (NO3)2, CuCl2, CuCl, and Cu2O on three types of coal with different degrees of metamorphism are mainly reflected in the accelerated oxidation stage. After adding copper-containing compounds, the ignition temperature of coal decreased by 22.1°C to 134.4°C, the heat release increased by 1.33 to 3.19 times, and the CO emission and oxygen consumption rate also increased. CuCl has the greatest impact on the ignition point temperature of coal and increases the oxygen consumption rates of DNH and TS by 2.32 and 1.51 times that of raw coal. CuCl2 has the strongest catalytic effect on coal oxidation heat release. Through in-situ diffuse reflectance infrared spectroscopy experiments, it was found that the reaction rate of fatty hydrocarbons in the oxidation process of three types of coal with the addition of copper-containing compounds increased to 1.3–3 times that of raw coal, and the oxidation rate of oxygen-containing functional groups also significantly increased, while the cracking temperature of aromatic structures significantly decreased. This is because copper ions, as strong free radicals, induce free radical chain reactions in coal and exhibit a strong promoting effect on the coal oxygen reaction process.