Petroleum Products Research Articles

Сurrent state and prospects of the Sakhalin balneological potential in rehabilitation and health resort treatment

Aim. To assess the prospects for the use of mineral waters and therapeutic muds (peloids) of the Sakhalin region for treatment and prophylactic purposes on the basis of their balneological properties.Materials and methods. The results of balneological analyses of mineral waters and therapeutic muds of the island areas of the Sakhalin region and regulatory documents were used.Results. The mineral waters and therapeutic muds of the Sakhalin region as its major therapeutic resources are characterized. The main groups of mineral waters for internal and external use include siliceous thermal, iodobromic, arsenic, and boric waters. It is noted that unique deposits of Sakhalin-type mineral waters, such as acidic waters with a high content of metals, petroleum products, and organic substances, require additional research. The Sakhalin region is rich in all available types of therapeutic muds– silt sulfide, mound, peat, and sapropel.Conclusion. The Sakhalin region possesses a wide variety of balneological resources for health resort treatment and rehabilitation. Among them are the deposits of mineral waters and therapeutic muds that are promising for research and use in medical and wellness organizations.

Building models of technological processes based on neuro-fuzzy technology

The work considers the issues of formalization of the extraction process in the form of a generalized regression neural network model, which are the basis for solving the problem of analysis and synthesis of the extraction process control system for obtaining petroleum products. An adaptive learning algorithm for a neural network model has been developed that is characterized by high speed and accuracy. A comparative analysis of the developed model with existing ones was made, which showed the effectiveness of the proposed algorithm for building the architecture of neural network models and learning the weight coefficients of the model.

A comprehensive study on applications of nanomaterials in petroleum upstream and downstream industry.

Nanotechnology has emerged as a revolutionary technology that has been applied in the oil and gas industry for over a decade, spanning the upstream, midstream, and downstream sectors. Nanotechnology has made significant contributions to the exploration of crude oil and natural gas, both in underground and deep-water environments. It has also played a crucial role in improving the drilling process, enabling the extraction of oil and gas resources from beneath the Earth's surface. Nanoparticles, with their unique physical and chemical properties, such as high specific surface area, high pore volume, and small size, have demonstrated considerable potential in the oil industry. Extensive research has been conducted to explore various types of nanoparticles for advanced applications, including oil exploration, drilling, production, and enhanced oil recovery (EOR). Moreover, nanomaterials have found applications in downstream and intermediate sectors, such as crude oil refining, natural gas processing, and transportation and storage of petroleum products. Ongoing advancements in nanomaterial synthesis methods, the exploration of new nanomaterial uses, and understanding the remarkable properties of nanomaterials will continue to make them increasingly valuable in the oil and gas sector. The oil and gas industry recognises the potential of nanotechnology and nanoparticles and is investing significantly in research and development in this area. This comprehensive review aims to summarise successful applications of nanotechnology while addressing associated challenges. It serves as a valuable resource for future research and application endeavours in the field, highlighting the potential of nanotechnology in the oil and gas industry.

Insulation of feed water tank in arrangement of transportable boiler plant with direct-flow steam boiler

A transportable boiler plant is used to provide consumers with steam of high energy characteristics, while saving costs for the construction of stationary boiler houses. A transportable boiler plant can be placed in the conditions of the Far North on an oilfield site. It is therefore necessary to organize reliable and safe operation of the boiler house, consisting of a steam direct-flow boiler of the coil type, a feed pump, a feed water tank and other auxiliary elements of the thermal circuit. One of the important elements in the thermal circuit is the feed water tank, in which water accumulates after chemical purification. It is where the water is also heated, increasing the efficiency of the boiler. Methods for calculating the diameters of main steam pipelines and feed water pipelines are described. The theoretical foundations of the operation of the feed water tank, its use in thermal power plants, combined heat and power plants, district industrial and heating boilers using various thermal arrangements of the above-mentioned enterprises are considered. The operation of the feed water tank in the thermal circuit of a steam unit is discussed. A thermal circuit of an industrial boiler house has been designed to generate saturated steam for consumers using direct-flow steam boilers of the coil type. The diameters of the inlet and outlet pipelines of the storage tank are calculated. The effective thickness of thermal insulation required to minimize heat losses during operation of a transportable boiler plant has been determined. Modeling of the design of the feed water tank and heat losses through its surface is carried out. A 3D model of the designed tank is presented, as well as heat losses through the surface of the tank walls when using a thermal insulation material. The importance of using thermal insulation of various tanks for storing feed water, petroleum products, hydrocarbons and other various media is noted.

Оценка состояния урбаноземов по содержанию поллютантов

Abstract. The purpose of the study is to assess the ecological state of soils within urbanozems in relation to the degree of contamination with heavy metals using the example of the urban aggromeration of Orenburg. Methods. Sampling was carried out at 4 sites in the sanitary protection zone of industrial enterprises in Orenburg. Determination of mobile forms of heavy metals Cd, Co, Cr, Cu, Mn, Ni, Pb, Zn in the samples was carried out by atomic absorption spectrophotometry. In the studied areas, the pollution index or concentration coefficient was taken into account, while taking into account the reference values of heavy metals. Contamination with toxic elements of soils in the reference areas was determined using the PINemerow coefficient. The pollution index of urban areas was calculated as the arithmetic or geometric mean of PINemerow for all reference areas in the city. Statistical processing of the material was carried out using the universal program Statistica 10. The scientific novelty of the work lies in the fact that for the first time data were obtained characterizing the accumulation of heavy metals in the sanitary protection zones of industrial enterprises in the city of Orenburg, and they were ranked according to the pollution index. Results. The analysis of the data obtained made it possible to reveal an increased content of Pb, Zn in all soil layers in the reference plot No. 1. The soils of site No. 2 had an increased content of Cu, Pb, Zn in the soil horizon of 20-30 cm, Pb was also found at a depth of 0-10 cm, which is explained by the passage of a major highway near the enterprise. Soil samples at a depth of 0-10 cm of site No. 3 were contaminated by 4 parameters (Cd, Mn, Pb, Zn) and had an average degree of anthropogenic pollution, which is due to the fact that the surface soils of the sanitary protection zone of the site are located near the enterprise associated with the processing of petroleum products. On the contrary, the studied areas No. 1; 2 and 4 sanitary protection zones of enterprises can be classified as low pollution. On the territory of the sanitary protection zone of site No. 4, an increased accumulation of Mn was found in the surface layers of soils.

Obtaining fuel products by combined hydrogenation of coal and shale

Background: Coal and oil shale are one of the promising types of organic raw materials that can largely compensate and replace petroleum products and gas in the future. Unlike other types of solid fossil fuels oil shales contain significant amounts of hydrogen in organic matter. The possibility of obtaining liquid and gaseous hydrocarbons from a mixture of coal and oil shale similar in composition and properties to petroleum products and natural gas allows us to consider them as important strategic resources.
 Aim: This article is devoted to the study of the process of obtaining fuel products of co-hydrogenation of coal and shale.
 Materials and methods: Coal from the Taldykol deposit and slate from the Kiin deposit were taken as objects of research. The process of coal and shale liquefaction was carried out on a laboratory installation at a pressure of 5 MPa and a temperature of 425°C, a reaction time of 1 h. Gas chromatographic and elemental analyses were used.
 Results: The research results showed that the optimal amount of shale added to coal is 15.0%. The implementation of the co-hydrogenation process under these conditions has increased the yield of liquid products by 10%, namely fractions with a boiling point of up to 200°C from 14.9% to 15.3%, fractions with a boiling point of 200–370°C from 22.1% to 26.4%, fractions with a boiling point above 370°C from 34.6% to 38.8%. Solid residue with a boiling point above 370°C tested as an organic binder for road construction.
 Conclusion: The proposed process technology also makes it possible to obtain gasoline and diesel fractions, which after appropriate hydrotreating can be used as motor fuels. The addition of oil shale to coal allows the process to be carried out under optimal conditions with a high degree of conversion into liquid products without coke formation. The degree of transformation of the mixture of organic mass of shale and coal is much higher than just coal.

Study of the effectiveness of using a fine wastewater treatment plant at petrochemical production enterprises

The problem of treatment and neutralization of wastewater from chemical, petrochemical and oil refining industries is associated with the removing from them of suspended solid and plastic particles of pollution of various chemical natures, oil and petroleum products, heavy metals, surfactants, acids, alkalis, phenols and other harmful substances. To effectively treat water, various filters are used, which differ in parameters and characteristics. The purpose of this work is to determine the possibility of replacing cartridge filters used at PetroKazakhstan Oil Products LLP with easily regenerable bag filters. In the course of the research, it was found that the use of cartridge and bag filters contributes to more effective water treatment, in particular, from suspended sub- stances. When comparing them, we can say that the latter is advantageous in that it does not need to be changed when clogged, like a cartridge filter, but simply rinsed and used again in the technological chain. The bag element is quite simply washed in water, but if it is heavily clogged, it can be washed either in a solution of citric acid (20 g/l) or in an alkali solution (10 g/l).

Volatile organic compounds (VOCs) emissions from internal floating-roof tank in oil depots in Beijing: Influencing factors and emission reduction strategies analysis

The internal floating-roof tank is the main type of storage tank for refined oil products. The volatile organic compounds (VOCs) emission from the internal floating-roof tank plays a dominant role in the unorganized emission source of the oil depot. In this study, we selected six typical oil depots in Beijing to investigate VOC emission characteristics from the tank top vent hole using infrared imaging technology and flame ionization detector (FID). The results reveal that infrared thermal imager is efficient in quickly identifying the emission level of the tank discharge point. The ambient temperature and wind speed have a direct effect on sealing loss, the turnover can greatly influence the wall hanging loss, and the concentration of VOCs emitted from the tank top vent hole is negatively correlated with liquid height. Furthermore, the influence of accessories type of the internal floating-roof tank on the concentration of VOCs emission from the top vent hole is also studied when other parameters remain unchanged, and find the floating deck type and sealing mode have a significant influence on their VOCs emissions, of which the combination of pontoon type floating deck and secondary seal are effective in controlling the concentration of VOCs emitted from the tank top vent hole. Finally, based on our experimental results, several feasible emission reduction strategies are proposed in terms of source prevention and process control in order to achieve the fine management of the whole process. This paper provides important technical support and policy thoughts for VOCs emission control during oil storage.

Assessing the influence of political factors on the dynamics of exports of Russian oil and petroleum products based on the use of a combination of PESTE and SWOT analysis methods

The presented work opens a series of articles devoted to assessing the influence of external factors on the dynamics of Russian exports. In this and subsequent related works, the authors proposed to consider the external environment, which had a significant impact on the dynamics of Russian exports and the relative diffi culty of revising its structure, the basis of commodity exports of which in value terms are hydrocarbon energy carriers. This work represents a conceptual basis for the use of instrumental methods for assessing the infl uence of external factors, in this case, political ones, on sectoral aspects of Russian exports and, in particular, on the export of hydrocarbon energy resources. In the second part of this article, it is proposed to use a set of environmental analysis methods, the basis of which is the real estate market research presented in this article, which tests the possibility of combining PESTEL analysis methods with the results of SWOT analysis, which will allow, based on the use of point estimates, to describe the cumulative impact external factors on the dynamics of the main sectors of Russian exports. The novelty of the presented approach lies in the absence of a methodology for a comprehensive assessment of the infl uence of external factors on the dynamics of Russian exports using the selected tools, which seems useful and timely in light of the emergence of new political and economic factors that have a signifi cant impact on Russian foreign trade in general and on the dynamics of the carbohydrate energy market, in particular. The parameters for assessing external factors proposed by the authors were chosen by the author independently, taking into account the modern realities of the development of the world economy, which can also represent a separate point of novelty of the research conducted. The merit of the authors of this work lies in the fact that this work proposed their own vision of a comprehensive assessment of the influence of external factors on the dynamics of the country’s exports.

Impact Assessment of Vehicular Poly-Aromatic Hydrocarbon Emmissions on Cassava Leaves and Tubers along Owerri – Port Harcourt Highway, Nigeria

Poly-aromatic hydrocarbon (PAH) effluents arising from vehicular spent petroleum products on highways were assessed. Analysis of this impact on cassava leaves and tubers on highway using the method of AOAC, 1990 revealed xylene to be of highest concentration, 0.1449 and 0.1865mm/g in leaves and roots respectively. Other PAHs analyzed were found to contain as follows: acenapthylene (0.0003 and 0.0312mm/g), phenanthlene (0.0029 and 0.0003mm/g), anthracene (0.0067 and 0.0127mm/g), 1,2-benzathracene (0.0161 and 0.0126mm/g), benzo(k)fluorine (0.0001 and 0.223mm/g) and pyrene (0.0169 and 0.0329mm/g) for leaves and roots respectively. From these findings, the concentration of PAH is highest in cassava roots than leaves and this justifies its hazardous effects on humans. Therefore, environmental monitoring of poly aromatic hydrocarbons in food is imperative in evaluating the possible toxicity of the impact as well as the carcinogenic potential of these compounds to humans via intake.

Biodiesel quality improvement by mixing the Azadirachta indica and Moringa stenopetala seed oil (in situ hybridisation) via transesterification process

ABSTRACT Biodiesel is considered environmentally benign, biodegradable, and greener fuel derived from vegetable oils, animal fats, and algae, superseding petroleum products. Hybridisation of vegetable oil has not been widely examined to produce biodiesel with ameliorated quality. This study aims at hybridising Azadirachta indica and Moringa stenopetala seed oils to produce the hybrid biodiesel with improved quality. The Box-Behnken Design was used in design of the experiment and analysis of results. Catalyst dose, oil hybridisation ratio, and reaction time were experimental variables with 3 levels, whereas, agitation speed, oil-to-methanol molar ratio, and reaction temperature were constants. The oil hybridisation ratios were: 25% A. indica and 75% M. stenopetala oil, 50% A. indica and 50% M. stenopetala oil, and 75% A. indica and 25% M. stenopetala oil. Seventeen experimental runs were conducted and the quadratic model was developed at P < 0.0001(significant). The model was determined by analysis of variance (ANOVA) and determination coefficients at 5% LSD.

Study of a Method for Neutralizing the Hydrocarbon-based Drilled Cuttings

The results of studies of the mechanical and chemical-toxicological properties of hydrocarbon-based drilled cuttings during the firing process at various temperature conditions are presented. Changes in the mineralogical composition, gross content of heavy metals, content of chloride, phosphate, sulfate ions and petroleum products, as well as the level of toxicity were studied. The indicators of the neutralization product were determined: water absorption capacity, strength, loss of strength in a water-saturated state. A technological scheme for the process of neutralizing the drilled cuttings with production of an environmentally friendly building material that can replace a part of the imported natural materials is described.

Forecasting Petroleum Products Consumption in the Chadian Road Transport Sector using Optimised Grey Models

This study aims to estimate the demand for petroleum products (PP) in the Chadian road sector by 2030 and to determine which of the two models used is the most efficient. The methodology is based on two optimised Grey models, namely: the Sequential-GM(1,N)-GA and NeuralODE-GM(1,1) models.  These models reduce forecasting errors compared with the conventional Grey model. The forecasts confirm that both models are robust, with MAPEs of 1.16% and 2.5% respectively for gasoline and diesel obtained with the Sequential-GM(1,N)-GA, and 3.3% and 4.8% respectively for gasoline and diesel obtained with the NeuralODE-GM(1,1). We note that the Sequential-GM(1,N)-GA is more robust than NeuralODE-GM(1,1) with regard to MAPEs. The estimated consumption needs for gasoline and diesel in the road transport sector by 2030 are 294376818.5 and 381570061.5 litres respectively for the Sequential-GM(1,N)-GA and 264376818.5 and 375570061.5 litres for the NeuralODE-GM(1,1). Based on these results, securing the supply of PP in the road transport sector requires the development of the downstream petroleum sector. The development of alternative energies and the acquisition of hybrid vehicles. A policy encouraging mass transport in urban areas can considerably reduce energy consumption in this sector. This study adds to the literature through the simultaneous use of two new optimised grey models and their comparison in terms of predicting demand for PP in the Chadian road transport sector.

Forecasting High Speed Diesel Demand in India with Econometric and Machine Learning Methods

According to International Energy Agency (IEA), India is expected to surpass China by 2024 to become the second largest consumer of oil in the world followed by the United States. High-Speed Diesel (HSD) has the biggest share in the total petroleum products consumed in India accounting for around 38% of the total consumption. Considering the volatile global oil market and an oil import dependency ratio of more than 80% during the last four years, the probability of supply disruptions is high in the Indian context. As any uncertainty about the supply of diesel can affect the smooth functioning of the economy and may create inflationary pressures. Accurate forecasting of HSD demand will be essential for appropriate supply management arrangements. Artificial Neural Networks (ANN) with Multi-Layer Perceptron (MLP) and extreme learning machines is used for forecasting diesel demand in this study. Demand forecasting has been carried out using monthly HSD demand data drawn from the “Indiastat” database for the period 1991-2022. Comparison of ANN with traditional forecasting methods of Autoregressive Integrated Moving Average(ARIMA)and Exponential Smoothing has also been undertaken in this study. This study identifies the deep learning technique of ANN with MLP as the best diesel demand forecasting technique.

A Data Driven Machine Learning Model for Fault Detection in Industrial Pipelines

Industry 4.0 has marked a paradigm shift in the way production and manufacturing operates. Process monitoring and fault diagnosis are important for the safety and reliability of industrial processes especially for smart manufacturing. As a data-driven process monitoring methodology, multivariate statistical analysis techniques, such machine learning based approaches have become extremely critical for automation. Pipelines carrying oil and gas are essential for a nation's economic sustainability. In order to maximise their function and prevent product losses during the transportation of petroleum products, they must be carefully inspected. However, they are susceptible to failure, which could have negative effects on the environment, financial loss, and safety. Therefore, evaluating the pipe's state and quality would be crucial. Despite being time-consuming and expensive, a number of inspection procedures are used to assure the safety of pipelines. However, due to the time consumption and error prone nature of manual inspection, data driven models are being explored for forecasting failure in oil and gas pipelines. The proposed work presents a Bayesian Regularized classifier for forecasting failure and the results show that the proposed approach outperforms the existing baseline techniques in terms of forecasting accuracy. Keywords:- Industry 4.0, oil pipelines; failure forecasting, Bayesian Regularization, Confusion Matrix, Classification Accuracy.

Identification of organic chemical indicators for tracking pollution sources in groundwater by machine learning from GC-HRMS-based suspect and non-target screening data

In this study, the strong analytical power of gas chromatography coupled to a high resolution mass spectrometry (GC-HRMS) in suspect and non-target screening (SNTS) of organic micropollutants was combined with machine learning tools for proposing a novel and robust systematic environmental forensics workflow, focusing on groundwater contamination. Groundwater samples were collected from four different regions with diverse contamination histories (namely oil [OC], agricultural [AGR], industrial [IND], and landfill [LF]), and a total of 252 organic micropollutants were identified, including pharmaceuticals, personal care products, pesticides, polycyclic aromatic hydrocarbons, plasticizers, phenols, organophosphate flame retardants, transformation products, and others, with detection frequencies ranging from 3 % to 100 %. Amongst the SNTS identified compounds, a total of 51 chemical indicators (i.e., OC: 13, LF: 12, AGR: 19, IND: 7) which included level 1 and 2 SNTS identified chemicals were pinpointed across all sampling regions by integrating a bootstrapped feature selection method involving the bootfs algorithm and a partial least squares discriminant analysis (PLS-DA) model to determine potential prevalent contamination sources. The proposed workflow showed good predictive ability (Q2) of 0.897, and the suggested contamination sources were gasoline, diesel, and/or other light petroleum products for the OC region, anthropogenic activities for the LF region, agricultural and human activities for the AGR region, and industrial/human activities for the IND region. These results suggest that the proposed workflow can select a subset of the most diagnostic features in the chemical space that can best distinguish a specific contamination source class.

Evaluation of factors causing lateral migration of light non-aqueous phase liquids (LNAPLs) in onshore oil spill accidents.

Contamination of groundwater by harmful substances poses significant risks to both drinking water sources and aquatic ecosystems, making it a critical environmental concern. Most on-land spill events release organic molecules known as light non-aqueous phase liquids (LNAPLs), which then seep into the ground. Due to their low density and organic composition, they tend to float as they reach the water table. LNAPLs encompass a wide range of non-aqueous phase liquids, including various petroleum products, and can, over time, develop carcinogenic chemicals in water. However, due to frequent changes in hydraulic head, the confinement may fail to contain them, causing them to extend outward. When it contaminates water wells, people cannot reliably consume the water. The removal of dangerous contaminants from groundwater aquifers is made more challenging by LNAPLs. It is imperative to analyze the mechanisms governing LNAPL migration. As a response to this need and the associated dispersion of contaminants into adjacent aquifers, we have conducted a comprehensive qualitative literature review encompassing the years 2000-2022. Groundwater variability, soil structure, and precipitation have been identified as the three primary influential factors, ranked in the following order of significance. The rate of migration is shown to rise dramatically in response to changes in groundwater levels. Different saturation zones and confinement have a major effect on the lateral migration velocity. When the various saturation zones reach a balance, LNAPLs will stop moving. Although higher confinement slows the rate of lateral migration, it speeds up vertical migration. Beyond this, the lateral or vertical movement is also influenced by differences in the permeability of soil strata. Reduced mobility and tighter containment are the outcomes of migrating through fine-grained, low-porosity sand. The gaseous and liquid phases of LNAPLs move more quickly through coarse-grained soils. Due to the complexities and uncertainties associated with LNAPL behavior, accurately foreseeing the future spread of LNAPLs can be challenging. Although studies have utilized modeling techniques to simulate and predict LNAPL migration, the inherent complexities and uncertainties in the subsurface environment make it difficult to precisely predict the extent of LNAPL spread in the future. The granular soil structure considerably affects the porosity and pore pressure.

Preparation and Oil Adsorption of Cellulose-graft-poly(butyl acrylate-N,N'-methylene Bisacrylamide).

With the advancement of industrial economies, incidents involving spills of petroleum products have become increasingly frequent. The resulting pollutants pose significant threats to air, water, soil, plant and animal survival, as well as human health. In this study, microcrystalline cellulose served as the matrix and benzoyl peroxide (BPO) as the initiator, while butyl acrylate (BA) and N,N'-methylene bisacrylamide (MBA) were employed as graft monomers. Through free radical graft polymerization, cellulose-graft-poly(butyl acrylate-N,N'-methylene bisacrylamide) [Cell-g-P(BA-MBA)], possessing oil-adsorbing properties, was synthesized. The chemical structure, elemental composition, surface morphology and wetting properties of the graft polymerization products have been characterized, using infrared spectroscopy, elemental analysis, scanning electron microscopy and contact angle testing. The adsorption properties of Cell-g-P(BA-MBA) for various organic solvents and oils were then assessed. The experimental results demonstrated that Cell-g-P(BA-MBA) exhibited a maximum adsorption capacity of 37.55 g/g for trichloromethane. Adsorption kinetics experiments indicated a spontaneous and exothermic process involving physical adsorption, conforming to the Freundlich isotherm model. Furthermore, adsorption kinetics experiments revealed that Cell-g-P(BA-MBA) displayed favorable reuse and regeneration performance, maintaining its adsorption capacity essentially unchanged over fifteen adsorption-desorption cycles.

Enrichment of nitrogen compounds in heavy oils by complexation with ZrCl4 and detailed characterization using FT-ICR MS and ion mobility spectrometry

Nitrogen compounds in heavy oils have significant deleterious impacts on the petroleum products and processes. It is of great significance to characterize the structures of nitrogen compounds during hydrodenitrogenation (HDN) in heavy oils, but the low content of nitrogen compounds after HDN is not conducive to structural analysis. Zirconium tetrachloride (ZrCl4) was found as an efficient complexing agent to enrich both basic and non-basic nitrogen compounds in heavy oils. The molecular weight ranges of the basic and non-basic nitrogen compounds were similar before and after ZrCl4 enrichment. The distribution of carbon number and double bond equivalent (DBE) of basic N1 species in the enriched feedstock was very close to that of the original feedstock, while the basic N1 species in the enriched product behaved a higher DBE distribution. The non-basic nitrogen compounds with higher DBE in the feedstock and product were also more likely to be enriched. Moreover, multi-heteroatomic non-basic nitrogen compounds were more inclined to be enriched than the non-basic N1 species due to the possible synergism of multi-heteroatoms. The numbers of detected multi-heteroatomic non-basic N2, N1O1, and N1O2 compounds obtained by high resolution mass spectrometry increased by 40 to nearly 70 times. The double bond equivalent (DBE) of these refractory multi-heteroatomic non-basic nitrogen compounds in the deep HDN product was much lower than those in the feedstock, due to the hydrogenation saturation reaction during HDN. The representative core structures of refractory basic nitrogen compounds were deduced by ESI+ FT-ICR MS coupled with collision-induced dissociation (CID), and the side chains were proposed by ion mobility spectrometry (IMS). Two typical kinds of refractory basic N1 compounds were suggested in the HDN product. One was a compact structure with multiple naphthenic rings and short side chains. The other had a large molecular size with aromatic rings and long side chains. ZrCl4 as a complexing agent can effectively enrich nitrogen compounds in heavy oil, especially for the hydrotreated heavy oils. This enrichment method facilitates the structural characterization of refractory nitrogen compounds in heavy oil HDN process by FT-ICR MS and IMS. These results provide valuable information for the improvement of HDN processes and catalysts.

INFLUENCE OF ZnO, Al2O3, CeO2 NANOPARTICLE-ADDED JULIFLORA BIODIESEL HRF ON RCCI ENGINE’S PERFORMANCE

The increase in demand for petroleum fuels attracted the attention of the research community to identify a control measure for petroleum source depletion. On the other hand, the heavy usage and burning of petroleum products cause environmental pollutants like oxides of nitrogen, carbon monoxide, hydrocarbons, etc. Therefore, it is important to control all the problems caused by the increasing use of petroleum products, such as diesel, petrol, Kerosene, fuel oil, etc. This investigation aims to reduce the usage of fossil-based petroleum diesel by producing an effective substitute bio-diesel from Juliflora seeds, which exhibit similar properties to diesel. Furthermore, the operational and emission behaviors of the biodiesel in the Reactive Controlled Compression Ignition (RCCI) engine are analyzed by including nanoadditives such as ZnO, [Formula: see text] and [Formula: see text]. Furthermore, the obtained performance and emission results are optimized using a hybrid deep neural network (DNN) using the Aquila optimization algorithm (AOA). The algorithm chooses the diesel-biodiesel blend with 75 ppm of alumina nanoparticle as the optimum blend. This considered blend provided better performance and emission results at 72.86% loading condition. The obtained results are 28.19% for brake thermal efficiency (BTE), 446.14 g/kWh for brake-specific fuel consumption, 0.105% for carbon monoxide emission, 19.82 ppm of unburnt hydrocarbon, 457 ppm of NO[Formula: see text] emission and 21.98% of smoke emission.