Operational Parameters Research Articles

Refining and recycling waste lubricating oil “FODDA 320” by acid treatment

The disposal of waste oils has the potential to exert a detrimental impact on the environment and human health. To circumvent the disposal of substantial quantities, it is advised that they be regenerated. There are a number of regeneration processes that may be employed. The objective of the present study is to regenerate FODDA 320 used oil sourced from the Sonatrach complex in Skikda. The aim is to evaluate the impact of operational parameters on the efficacy of the method used to regenerate this oil using four acids. To achieve this, the following parameters were monitored: The impact of varying VAcid/VOil ratios on the efficacy of the treatment process and the influence of temperature on the efficiency of treating this oil were also investigated. A comparison of the physico-chemical characteristics of the treated oil samples, including density, viscosity, pour point, flash point, water content and ferrous debris, with those of the fresh oil samples revealed that sulphuric acid with a VAcid/VOil ratio of 1/10 yielded the best results.

Selection of Components and Methods of Modification of Soil Cement to Improve the Performance Properties of Subgrade

Purpose. The main objective of the scientific article is a reasonable selection of soil-cement reinforcing structural elements and methods of modifying the soil-cement structure to strengthen the subgrade for railroad tracks. Methodology. For the construction of soil-cement reinforcing elements for a combined railway track using drilling and mixing technology, a number of tasks were solved, including: a reasonable selection of the components and modifiers of the soil-cement element; determination of the properties of the components; establishment of operational requirements for soil-cement and its composition; design of optimal compositions with specified performance characteristics, taking into account the properties of soils and operating modes. Findings. The influence of soil-cement components on the rheological properties of soil-cement mixtures and the physical and mechanical properties of soil-cement was studied. Based on the data processing by statistical analysis, the optimal content of the constituent components of soil-cement mixtures was selected to ensure the technological and operational performance of soil-cement for different types of soils and to strengthen the soil base during track construction. The influence of mineral granular, fibrous and chemical modifiers on the properties of soil cement was investigated. Originality. The possibility of using vertical reinforcing elements made of soil cement with the necessary technological and operational parameters obtained by drilling and mixing technology to strengthen the subgrade, taking into account the stress-strain state and morphology of the soil bases, has been determined. Based on the study, the author made an attempt to select the components and develop optimal soil cement compositions for strengthening the subgrade of a railroad for a combined track. The directions of modification of soil cement with mineral, fiber and chemical additives are also considered. Practical value. The study makes it possible to obtain soil-cement elements of optimal composition and properties for different types of soils and stress-strain states in order to vertically strengthen the soil bases for the railway track. To modify the structure of soil cement and minimize cement consumption, it is proposed to use fiber fibers as modifying reinforcement components. To increase the density, crack resistance, strength, and modulus of deformability and improve the plasticity of the mixture, it is recommended to use chemical modifiers up to 0.3 % and to save cement – particles of fine industrial waste in the form of ground slag or stone grinding screenings in the amount of 20...30 %.

Optimization for the Process Parameters of Nickel-Titanium Nitride Composites Fabricated via Jet Pulse Electrodeposition.

The corrosion resistance of nickel-titanium nitride (Ni/TiN) composites is significantly influenced by the operation parameters during the jet pulse electrodeposition (JPE) process. The effect of current density, jet rate, TiN concentration, and duty cycle impact on the anti-corrosion property of Ni/TiN composites were investigated and optimized using the response surface method (RSM). After the optimization of the operation parameters, the corrosion current of Ni/TiN composites decreased from 9.52 × 10-5 A/cm2 to 4.63 × 10-5 A/cm2. The corrosion current of Ni/TiN composites decreased initially and then increased with an increase in current density, jet rate, TiN concentration, and duty cycle. During the jet electrodeposition process, the influence of the duty cycle on the corrosion current of Ni/TiN composites was comparatively insignificant, whereas the concentration of TiN had a significant effect on the corrosion current. The error rate between the predicted value and the measured result from the corrosion current of Ni/TiN composites was only 0.64%, indicating the high accuracy of fitting the model. Furthermore, X-ray diffraction (XRD) patterns and scanning electron microscope (SEM) images revealed that the optimized Ni/TiN composites comprised significant Ti content, fine nickel gain, and a compact, smooth structure. In addition, the electrochemical measured results demonstrated that the optimized Ni/TiN composites possessed a low self-corrosion current and high self-corrosion potential. These findings show that the optimized composites have a substantially greater corrosion resistance compared to two other unoptimized Ni/TiN composites.

Effect of Operational Parameters and Iron Ore Tailings Properties on Filter Cake Porosity

Objective: By evaluating operational filtration conditions, chemical, mineralogical, and particle size properties of the tailings, the study aimed to identify critical variables affecting porosity and provide predictive models for optimizing dewatering operations. Theoretical Framework: This research builds upon existing theories of solid-liquid separation and dewatering processes in mineral processing. Key references include classical works on filtration dynamics, particle size distribution, and cake porosity characterization. The study addresses gaps in literature regarding the relationship between tailings composition and filtration results. Method: The Leaf Test method was employed on 33 fresh slurry samples from the Brucutu plant to simulate industrial filtration conditions. Filtration cycle parameters such as cake formation and drying times were standardized. Porosity was calculated using Grace's equation and correlated with characterization data, including mineralogical composition, true density, and particle size. Statistical methods such as clustering, regression, and Random Forest modeling identified key predictors of porosity. Results and Discussion: The results indicated that porosity correlates strongly with silica content and certain mineralogical attributes, such as the presence of martitic hematite and quartz. Cluster analysis revealed two sample groups with distinct filtration characteristics. While operational parameters showed limited impact on porosity, the statistical models highlighted the significance of ore composition. Research Implications: This research provides a foundation for optimizing iron ore tailings filtration by identifying the key variables influencing porosity. The findings support more efficient dewatering techniques, contributing to sustainable tailings management. Further, the development of predictive models aids industrial operations in minimizing risks associated with tailings disposal. Originality/Value: This study is among the first to integrate statistical modeling and mineralogical characterization in exploring filter cake porosity. The results offer novel insights into the optimization of solid-liquid separation processes in the mining industry.

Recent Advances in Hydrothermal Oxidation Technology for Sludge Treatment

With the rapid development of urbanization and the widespread adoption of wastewater treatment facilities, the volume of sludge produced has steadily increased. Hydrothermal oxidation (HTO) technology offers an effective solution for sludge reduction, harmless disposal, and resource recovery, making it a highly promising method for sludge treatment. In recent years, HTO has attracted significant attention due to its efficiency and environmental benefits. This paper provides a detailed explanation of the fundamental principles of HTO in sludge treatment, with a focus on the removal of organic pollutants, nitrogen transformation, and phosphorus recovery. The influence of key operational parameters, such as reaction temperature, time, initial oxygen pressure, and pH, on the performance of HTO treatment is also explored. In addition, the research status of HTO sludge treatment and an example of product recovery after treatment are also discussed. It examines the challenges associated with scaling up HTO for large-scale sludge treatment, along with potential research directions for future work. Special attention is given to the innovation of catalysts, with the goal of achieving self-catalysis in sludge treatment. Moreover, considering that ammonia nitrogen (NH3-N) is a major intermediate product in HTO, its removal, as well as the prediction and planning of other unintended products, remains a key issue. Further areas of interest include improving sludge dewatering performance and enhancing the production of valuable single carboxylic acids, which can boost resource recovery efficiency. This paper also highlights the diversification of sludge applications after HTO treatment. By providing insights into future development trends, this review offers valuable references for further research and practical applications. The ultimate goal is to support the development of HTO as a sustainable and efficient solution for sludge treatment, addressing environmental concerns while maximizing resource recovery opportunities.

Integrating Biological Early Warning Systems with High-Resolution Online Chemical Monitoring in Wastewater Treatment Plants.

Detection of micropollutants (MPs) in wastewater effluents using traditional toxicity tests or chemical analysis with discrete samples is challenging due to concentration dynamics. This study evaluates a continuous monitoring approach for detecting MPs in wastewater effluents using a combination of biological early warning systems (BEWS). Three BEWS with Chlorella vulgaris, Daphnia magna, and Gammarus pulex were operated in parallel in a full-scale municipal wastewater treatment plant. Concentrations of MPs were monitored by simultaneous online chemical analysis using high performance liquid chromatography-high resolution mass spectrometry (MS2Field). Over 5 weeks, behavioral changes observed in the BEWS occasionally exceeded acute toxicity thresholds, triggering alarms. These changes were related to MPs identified by the MS2Field, to abiotic factors, or to operational parameters of the BEWS. For one toxic event, behavioral responses were linked to a pesticide, not authorized in Switzerland, at concentrations close to literature EC50 values. Verification tests confirmed that the pesticide in the effluent was the most likely cause for the organism response. The study demonstrates the potential of BEWS as a stand-alone technique for detecting contamination peaks in wastewater, and identifies key limitations and critical factors that need to be addressed to optimize the use of BEWS in wastewater monitoring.

Review of Thermal Calculation Methods for Boilers—Perspectives on Thermal Optimization for Improving Ecological Parameters

This article presents an overview of thermal calculation methods used in boilers powered by fossil fuels (solid, liquid or gas). The analysis was carried out mainly in terms of combustion chamber calculation methods. Changing standards and legal regulations regarding the use of fossil fuels in Europe and the world make it necessary to adapt calculation methods and boiler design to current requirements, and many of them are related to outdated boiler models or for fuels that are no longer so heavily used in industrial solutions. Current research and development trends implemented in the EU and in the world related to the issues of the European Green Deal, the Fit for 55 directive and other ecological trends in the energy sector make it necessary to verify and remodel the calculation methods used so far in terms of the thermal efficiency of the device, fuel consumption or the use of fuels not previously used in their wide range in a wider application. Hence, the knowledge and updating of the state of knowledge in the field of the thermal calculation of boilers in terms of their environmental performance is necessary and strongly sought after by researchers. It is undoubted that in the next few years, boilers will continue to be the main source of thermal energy, especially in the power industry or industry. A reasonable energy transition should be based on the direction of the thermal optimization of already functioning structures and adaptation of their operating parameters to the planned new ecological fuels in the sense of the intensification of energy converted from primary form to thermal energy, and in the last step, it should reorganize the energy and industrial sectors, leaving only these groups of devices treated as a stable and necessary source of energy. Therefore, it should be recognized that activities aimed at improving the thermal parameters of boilers should directly improve the thermal efficiency of the device, and this will translate into fuel savings and reduce their negative impact on the environment.

A Comprehensive Multi-Objective Optimization Study on the Thermodynamic Performance of a Supercritical CO2 Brayton Cycle Incorporating Multi-Stage Main Compressor Intermediate Cooling

This study proposes a supercritical carbon dioxide Brayton cycle incorporating multi-stage main compressor intermediate cooling (MMCIC sCO2 Brayton cycle), and conducts an in-depth investigation and discussion on the enhancement of its thermodynamic performance. With the aim of achieving the maximum power cycle thermal efficiency and the maximum specific net work, this study examines the variation of the Pareto frontier with respect to the number of intermediate cooling stages and critical operational parameters. The results indicate that the MMCIC sCO2 Brayton cycle offers significant advantages in improving power cycle thermal efficiency, reducing energy consumption, and mitigating the adverse effects associated with main compressor inlet temperature increasing. Under the investigated operational conditions, the optimal cycle performance is achieved with four intermediate cooling stages, yielding a maximum power cycle thermal efficiency of 67.85% and a maximum specific net work of 0.177 MW·kg−1. Cycles with two or three intermediate cooling stages also deliver competitive cycle performance, and can be regarded as alternative options. Additionally, increasing the turbine inlet temperature proves more effective for enhancing power cycle thermal efficiency, whereas increasing the turbine inlet pressure can substantially improve the specific net work. This study provides a feasible structural layout approach and research framework to improve the thermodynamic performance of the sCO2 Brayton cycle, offering a robust theoretical foundation and technical guidance for its implementation in power engineering.

马铃薯挖掘机仿真与试验

In this study, the potato excavator with loosening shovel was designed in order to solve the problems of serious soil obstruction and high excavation resistance during the potato harvest. Using EDEM discrete element simulation software, potato excavation simulation experiments were carried out on soil broken effects and excavation resistance. Through the comparative analysis with loosening shovel and without, the results showed that the increase of soil broken effects was close to 52%, and the excavation resistance decreased by 16.57%. Through the two-factor and three-level field orthogonal experiment with excavation depth and loosening depth as influencing factors, the optimal operating parameters was determined for potato excavators: the excavation depth was 23 cm and the loosening depth was 20 cm. At this time, the excavation potato rate was 98.21%, and the rate of damaged potato was 1.31%. The traction resistance was 1826 N, which met the requirements of relevant industry standards. Through comparative analysis of simulation experiments and field experiment, it was found that when the excavation depth was 23 cm and the loosening depth was 20 cm, the error value of traction resistance was 11.3% between simulation experiments and field experiments. The discrete element simulation analysis can provide a preliminary reference for potato excavation design.

THE INFLUENCE OF THE RESISTANCE OF THE NEUTRAL GROUNDING RESISTOR ON THE 20 KV VOLTAGE DISTRIBUTION MODES OF OPERATION

The article examines the impact of different modes of neutral grounding on the operating parameters of 20 kV distribution networks, in particular, the selection of the optimal resistor resistance for resistive neutral grounding. One of the main tasks is to improve the efficiency of distribution networks of the UES of Ukraine by switching from a voltage of 10 kV to 20 kV. This solution is aimed at reducing power losses, increasing the amount of transmitted energy and improving the operation of relay protection. In the context of such a transition, the choice of the method of grounding the neutral of the power transformer is particularly relevant, which significantly affects the reliability and safety of operation of electrical networks. In the study, an analysis of the effect of resistive grounding of the neutral of the transformer on the operating characteristics of the 20 kV network was performed, as well as determination of the optimal value of the resistance of the resistor. The article presents the results of a comparison of a network with an isolated neutral and resistive grounding. The main operating parameters, such as short-circuit currents, overvoltages on undamaged phases, power losses and operation of relay protection, which have a significant impact on the stability and safety of network operation, are analyzed. Modeling is performed using the PowerFactory software complex, which provides the ability to accurately reproduce the real operating conditions of electrical systems. To conduct the research, a simulation model of the distribution network was created based on a two-transformer 110/20 kV substation, which includes two sections with outgoing lines of different lengths and loads. Special attention was paid to the selection of the resistance of the neutral grounding resistor and its influence on network parameters. Four options were considered in the study: isolated neutral and resistive grounding with a resistance of 10 Ohm, 15 Ohm and 20 Ohm. It was established that in order to ensure stable and safe operation of the distribution network, it is important to correctly choose the neutral grounding method. The best option is resistive grounding with a resistance of 15 Ohms, which allows you to reduce power losses, provides a sufficient level of currents for the effective operation of relay protection, and minimizes the risks of overvoltages on undamaged phases. This study is important for increasing the reliability of the operation of distribution networks and the security of electricity supply, especially in the context of the modernization of Ukraine's UES networks.

A novel study of the impact of supply chain complexity on the bullwhip effect

Background: The coronavirus pandemic exposed global supply chain vulnerabilities, causing fluctuating demand for products. This resulted in the bullwhip effect, which posed a substantial challenge for supply chain management. This study focusses on the analysis of the effect of supply chain configurations and structure on the bullwhip effect.Objectives: The research quantitatively studies the effect of the strategic supply chain structure at the design phase on amplifying the bullwhip effect. Furthermore, it studies the expected interaction during operation, which may further amplify or dampen it.Method: The study introduces a simulation model and examines the influence of several design decisions and operations parameters and their interactions on the efficiency of supply chain operations. A simulation model is created for several supply chain configurations, each with distinct structure complexity. The bullwhip effect measures are collected and a factorial analysis is conducted to examine the interactions among the parameters and their impact on the performance.Results: The findings indicate that an increase in demand unpredictability results in a greater bullwhip effect, irrespective of the inventory strategy or structural intricacy. But the level of increase does not necessarily match the increase in complexity and can be amplified or damped by interactions between operating parameters.Conclusion: Supply network architects should consider the level of structural complexity to mitigate amplifications of demand variations and to optimise the supply chain’s overall operation.Contribution: The research represents a novel work to quantitatively link the bullwhip effect of a supply chain to the complexity of its supply chain structure.

Plasma‐Treated Liquids for Medicine: A Narrative Review on State and Perspectives

ABSTRACTPlasma‐treated liquids and their medical application have gained momentum in the fields of plasma science in recent years. Most research has been done in the field of cancer treatment. Another new and promising special field of CAP−liquid interaction is hydrogels, which can serve as localized reservoirs for the delivery of long‐lived reactive oxygen and nitrogen species and other active ingredients such as chemotherapeutic drugs. Identifying liquids and hydrogel compositions optimal for plasma treatment, for their reservoir function, and from a regulatory point of view for use in medicine, together with the chemical identification of biologically active molecules and interdependencies to plasma operation parameters, are the fundamental challenges in the field.

ASSESSMENT OF THE INFLUENCE OF ROAD EQUIPMENT PERFORMANCE ON THE EFFICIENCY OF ITS USE

The paper assesses the impact of road machinery performance on the efficiency of its use. It is accepted that the main operational parameters of road equipment for analyzing the technical condition and degree of use of machines include productivity, efficiency index, time for the technological process and losses. The influence of productivity on the strategy of machine operation, as one of the main parameters of the roadway arrangement process, is considered provided that road machines have not only different productivity, but also different rates of its change during operation. The analysis of the given dependencies and the given conditions for changing productivity has shown the impact of increasing and decreasing the rate of productivity decline on the optimal service life of the equipment. These results confirm the extremely important importance of measures aimed at maintaining high machine performance during their operation. The components of machine operating time are analyzed. It was found that the useful or effective working time is an estimated value that is the required time for a given volume of production at reference performance, that is, without loss of productivity and quality. The methods of monitoring the technical condition and the degree of use of road equipment in road construction are analyzed.

Development of a Low-Cost Automated Injection Molding Device for Sustainable Plastic Recycling and Circular Economy Applications

In response to the critical demand for innovative solutions to tackle plastic pollution, this research presents a low-cost, fully automated plastic injection molding system designed to convert waste into sustainable products. Constructed entirely from repurposed materials, the apparatus focuses on processing high-density polyethylene (HDPE) efficiently without hydraulic components, thereby enhancing eco-friendliness and accessibility. Performance evaluations identified an optimal molding temperature of 200 °C, yielding consistent products with a minimal weight deviation of 4.17%. The key operational parameters included a motor speed of 525 RPM, a gear ratio of 1:30, and an inverter frequency of 105 Hz. Further tests showed that processing temperatures of 210 °C and 220 °C, with injection times of 15 to 35 s, yielded optimal surface finish and complete filling. The surface finish, assessed through image intensity variation, had a low coefficient of variation (≤ 5%), while computer vision evaluation confirmed the full filling of all specimens in this range. A laser-based overflow detection system has minimized material waste, proving effective in small-scale, community recycling. This study underscores the potential of low-cost automated systems to advance the practices of circular economies and enhance localized plastic waste management. Future research will focus on automation, temperature precision, material adaptability, and emissions management.

Physics-based numerical evaluation of High-Temperature Aquifer Thermal Energy Storage (HT-ATES) in the Upper Jurassic reservoir of the German Molasse Basin

Abstract. Concepts of High-Temperature Aquifer Thermal Energy Storage (HT-ATES) (> 50 °C) are investigated in this study for system application in the Upper Jurassic reservoir (Malm aquifer) of the German Molasse Basin (North Alpine Foreland Basin). The karstified and fractured carbonate rocks exhibit favourable conditions for conventional geothermal exploitation of the hydrothermal resource. Here, we perform a physics-based numerical analysis to further assess the sustainability of HT-ATES development in the Upper Jurassic reservoir. With an estimated heating capacity of approx. 19.5 MW over half a year, our approach aims at determining numerically the efficiency of heat storage under the in situ Upper Jurassic reservoir conditions and projected operation parameters. In addition, the hydraulic performance of the HT-ATES system is further evaluated in terms of productivity and injectivity index. The numerical models build upon datasets from three operating geothermal sites at depths of approx. 2000–3000 m TVD, located in a subset of the reservoir dominated by karst-controlled fluid fluxes. Commonly considered as a single homogeneous unit, the 500 m thick reservoir is subdivided into three discrete layers based on field tests and borehole logs from the three considered sites. The introduced vertical heterogeneity with associated layer-specific enhanced permeabilities allows to examine potentially arising favourable heat transfer, and in combination with the facilitated high operation flow rates (100 kg s−1) to evaluate thermal recoveries in the multilayered reservoir. All simulations account for fluid density and viscosity variation based on thermodynamically consistent equations of state (EOS). Computation results reveal that the reservoir layering induces preferential fluid and heat migration primarily into the high-permeability zone, while thermal front propagation into the lower permeable rock matrix is inhibited. The simulations further display a gradual temperature increase in the warm wellbore and its surrounding host rock, and a consequent progressive improvement in the heat recovery efficiency. Despite the elevated permeability that may trigger advective heat losses, heat recovery factor values range from approx. 0.7 over the first year of operation to over 0.85 after 10 years of operation. An additional scenario is examined with fluid injection solely in the high permeable zone, in order to quantify potential enhancement in the recovery efficiency by omitting fluid injection in the lower-permeability layers where heat propagation is diminished. This is due to the geometrical shape of the thermally perturbed rock volume as heat losses occur during thermal equilibration between injected fluid and reservoir rock, as well as at the contact-surface area between propagating thermal front and adjacent rock matrix. Results suggest that under the stratified reservoir configuration, additionally constrained by the selected spatial distribution of rock properties, heat storage performed only into the upper high-permeability zone corresponds to an improved thermal performance. Simulation results further indicate that density-induced buoyant fluxes, which would considerably decrease thermal efficiencies are inhibited in the system, and the prevailing heat transport mechanism is forced convection.

Enhanced digital twin development for a conveyor belt system: integrating PLC control, CNN decision-making, Gradio-based HMI, and fuzzy logic

This paper introduces an advanced Digital Twin (DT) of a conveyor belt system, designed to enhance industrial automation and decision-making in the context of Industry 4.0. Built using Factory I/O, the DT simulates the physical conveyor's behavior, integrating seamlessly with a Programmable Logic Controller (PLC) for real-time control. A Convolutional Neural Network (CNN) enhances decision-making by analyzing conveyor activity, such as defect detection and sorting optimization. A Fuzzy Logic (FL) system also refines CNN outputs, improving reliability by incorporating factors like confidence scores and operational parameters. A Gradio-based Human-Machine Interface (HMI) offers an intuitive platform for real-time monitoring, interaction, and manual control. The system demonstrates robust synchronization between virtual and physical components, showcasing its ability to improve efficiency, accuracy, and adaptability in industrial processes. This work contributes to smart manufacturing advancements by combining DT technology, intelligent algorithms, and adaptive control for enhanced industrial supervision.

Combining CFD and AI/ML Modeling to Improve the Performance of Polypropylene Fluidized Bed Reactors

Polypropylene is one of the most widely used polymers in various applications, ranging from packaging materials to automotive components. This paper proposes the Computational Fluid Dynamics (CFD) and AI/ML simulation of a polypropylene fluidized bed reactor to reduce reactor loss and facilitate process understanding. COMSOL Multiphysics 6.2® solves a 2D multiphase CFD model for the reactor’s complex gas–solid interactions and fluid flows. The model is compared to experimental results and shows excellent predictions of gas distribution, fluid velocity, and temperature gradients. Critical operating parameters like feed temperature, catalyst feed rate, and propylene inlet concentration are all tested to determine their impact on the single-pass conversion of the reactor. The simulation simulates their effects on polypropylene yield and reactor efficiency. It also combines CFD with artificial intelligence and machine learning (AI/ML) algorithms, like artificial neural networks (ANN), resulting in a powerful predictive tool for accurately predicting reactor metrics based on operating conditions. The multifaceted CFD-AI/ML tool provides deep insight into improving reactor design, and it also helps save computing time and resources, giving industrial polypropylene plant growth a considerable lift.

Offshore Wind‐Hydrogen Systems Fault Detection Based on CNN‐BiLSTM‐AM Algorithm

ABSTRACTThis study presents a novel deep learning‐based approach for fault detection in offshore wind‐hydrogen systems. A fault detection model is developed using convolutional neural networks (CNNs), bidirectional long short‐term memory networks (BiLSTMs), and an attention mechanism (AM). The model is trained on a dataset generated through fault injection techniques, which simulate real‐world faults in the system. Key operational parameters, such as wind speed and hydrogen production rate, are used to detect faults effectively. This paper reduces reliance on actual experiments, and introducing artificial faults allows system performance assessment under different fault scenarios, lowering project risks and costs. This work facilitates automatic feature extraction and high‐precision classification of time‐series fault data, which covers a fully automated learning process from data to fault detection. The outstanding performance of the method is validated through computation and result comparison.

Possibilities of Improving the Emission Characteristics of Passenger Cars by Controlling the Concentration Levels of Combustion-Generated BTEX Components

Replacing the alkyl lead derivatives with aromatic hydrocarbons and additives in modern reformulated fuels to improve internal combustion engine performance, lower fuel consumption, increase power, and improve emission characteristics have resulted in the emission of large quantities of BTEX (benzene, toluene, ethylbenzene, and xylene) compounds into the atmospheric compartment. In this research, how the different working regimes of an experimental engine affect the BTEX compound concentration levels was observed to evaluate the quantities emitted during the movement of a passenger car in urban driving conditions. The target compounds were analyzed in exhaust gas samples using the Photovac Voyager-mobile GC (Waltham, MA, USA). This experimental research demonstrates that optimizing engine operational parameters significantly reduces the concentration levels of BTEX compounds in exhaust gas mixtures by adjusting specific working regimes, contributing to better emission characteristics and promoting sustainable transportation solutions. The most significant effect of the independent increase in air quantity in the feed mixture is realized through the decrease in concentration levels of toluene in the exhaust gas mixture of approximately 81%. A significant reduction in concentration levels is achieved with m,p-xylene (79%) and o-xylene (79%) as well, whilst the lowest effect has been noted with benzene (73%) and ethylbenzene (71%).

Mathematical modelling of the process line of a multifunctional fuel gas preparation unit (MGPU) to improve its accident-free operation

The purpose of the research is a comprehensive study of the process line of a multifunctional fuel gas preparation unit (MGPU), creation of a mathematical model capable of predicting and controlling gas dryness in the process of MGPU operation, as well as determination of optimal parameters of the unit operation to improve accident-free operation and high productivity of the equipment using treated gas.Methods. Mathematical modeling with the use of multiple regression model for prediction of dew point temperature and its influence on accident-free operation of the plant was carried out. The adequacy of the model was confirmed by the coefficient of determination and Fisher's criterion. An analysis of the limiting factors for the accident-free operation of the MGPU, including temperature, pressure and gas composition, is also presented. The accuracy of numerical modeling of the trouble-free operation of the MUPG process line based on the developed model of multiple regression of gas dryness was estimated using paired correlation coefficients and elasticity coefficients. Results. In the course of the work, the accident-free operation of the process line of MGPU was modeled based on the developed multiple regression model of gas dryness. The following interpretation of the model parameters is possible: increasing factor X1 by 1 leads to an average decrease in Y by 0.279; increasing factor X2 by 1 leads to an average increase in Y by 0.46; increasing factor X3 by 1 leads to an average increase in Y by 0.000418; increasing factor X4 by 1 leads to an average increase in Y by 13.288; increasing factor X5 by 1 leads to an average decrease in Y by 13.337; increasing factor X6 by 1 leads to an average decrease in Y by 0. According to the maximum coefficient β2=0.384 we can conclude that the factor X2 has the greatest influence on the result Y. Statistical significance of the equation was tested using the coefficient of determination and Fisher's criterion. According to the assessment of the accuracy of numerical modeling of the trouble-free operation of the MUPG process line, based on the developed model of multiple regression of gas dryness, a strong linear relationship between X1 and Y, a low linear relationship between X2 and Y, a low linear relationship between X3 and Y, a moderate linear relationship between X4 and Y, a moderate linear relationship between X5 and Y, moderate linear relationship between X6 and Y.Conclusion. It was found that in the investigated situation: "in the possibility of prediction and control of gas dryness: justification of the hypothesis about the possibility of prediction of dew point temperature and its influence on accident-free operation" the parameters of the model are statistically significant.