Lubricating Oil Research Articles

Evolution of wetted and corroded areas on 8Cr4Mo4V bearing steel exposed to salt water contaminated lubricant oil

Relationship between wetted and corroded areas on 8Cr4Mo4V bearing steel during exposure to salt water contaminated lubricant oil was explored by Monte Carlo simulation and corrosion experiment. Results show that locally corroded areas are initially scattered then connected and eventually merged due to droplet coalescence, and are resulted from galvanic, uniform and filiform corrosions, respectively. Droplet coalescence also redistributes wetted areas and activates de-wetting which interrupts transformation towards corrosion. Role of droplet coalescence in evolution of corroded areas is addressed. Combining two Monte Carlo models varied with droplet relaxation helps to predict the corroded areas' distribution after long-term exposure.

Improving used Lubricant Oil Burner Performance: Effect of Swirled Flow of Internally Distributor Type on the Combustion and Flue Gas Temperature and Emission

This study aimed to experimentally investigate the combustion characteristics of used lubricant oil (ULO). A simple cylindrical burner of the natural draft vaporizing type, equipped with an internal air distributor, was designed and fabricated to achieve this objective. The burner’s efficiency was evaluated based on combustion temperature, flue gas temperature, and concentration levels. The key feature of this burner lies in the swirled flow of air combustion and ULO vapor within the combustion chamber, facilitated by the swirled flow air distributor type. Various air-fuel ratios (ϕ), ranging from 0.5 to 4, were considered in characterizing the burner’s performance. The results revealed increased combustion and flue gas temperatures in the radial airflow types. The highest temperatures achieved using the radial flow type are 930 oC and 410 oC for combustion and exhaust gas temperature, respectively. In contrast, the combustion chamber and exhaust gas temperatures are 980 oC and 465 oC for the swirled flow type, respectively. It was found that there is a decrease in the emission of CO and CO2 by volume under optimum conditions. This decrement was attributed to the swirled flow effects, which promoted a better mixture of air combustion and ULO vapor during combustion.

Prediction of inlet gas volume fraction of rotary vane pump under variable operational conditions with 1DCNN-TL model utilizing vibration signals

The Rotary vane pump (RVP) exhibits promising potential in the lubricating oil system of aircraft engines. The entrainment of air into the lubricating oil flowing through the pump affects the suction and discharge flow rates of the RVP. Therefore, understanding the inlet gas volume fraction (IGVF) of the RVP is crucial to assess its capability to deliver sufficient lubricating oil for ensuring the safe operation of aircraft engines. This study presents a one-dimensional convolutional neural networks (1DCNN)-based transfer learning (TL) (1DCNN-TL) prediction model to predict IGVF for the RVP using experimental data from gas-liquid two-phase flow in the RVP. The model is pre-trained using the vibration signals under a specific differential pressure between the pump inlet and outlet to enable predictions of the IGVF under varying differential pressures. The 1DCNN serves as pre-trained model for analyzing the outcomes of different transfer tasks. The effect of different frozen layer numbers on training time and prediction accuracy of the neural network is explored. Subsequently, the influence of varied source domain data on prediction accuracy is investigated, revealing that for optimal TL results, stable condition data at 200 kPa should be preferred as the source domain. Then the 1DCNN-TL prediction model of IGVF of RVP under variable operational conditions is determined. The results indicate varying iteration convergence rates of the pre-trained model under a differential pressure of 200 kPa across different transfer tasks, with a final goodness of fit exceeding 0.958 after fine-tuning the model. The model demonstrates the high prediction accuracy and applicability, which can contribute to improving the reliability and safety of aircraft engines.

Dehydration of turbine engine lubricant oil using cellulose hydrogel

Contamination of oils by water is a recurring problem in the industry and can damage engines and equipment. Oil dehydration systems with hydrogels have shown promise for the removal of free, soluble, and emulsified water. This work evaluates, in an unprecedented way, the dehydration of turbine lubricating oil using a cellulose hydrogel. The synthesis of the hydrogel was confirmed by the formation of specific functional groups. The hydrogel was characterized through high-resolution SEM, EDS, FTIR, BET, TGA, DVS and swelling degree. The oil was evaluated regarding its composition and physicochemical properties. The performance of the hydrogel in the treatment of water-in-oil emulsion was analyzed in batch and continuous flow systems. A fixed bed apparatus was specially designed and sized according to the industry's specifications to simulate on-site application. The batch treatment was evaluated using orbital and full tumbling inversion mixing systems, both reaching removal efficiency of around 47 %. Mixing by full tumbling allowed greater stability of the emulsion and control of the water concentration, but it required a longer time to enable adequate water uptake by the hydrogel. The efficiency of the hydrogel in the continuous flow system was affected by retention time and inlet water concentration. With a retention time of 12 min, it was possible to treat 1 L of oil, reducing the water concentration from 412 ppm to 197 ppm and the turbidity from Haze 6 to Haze 1. Thus, the cellulose hydrogel was efficient in dehydrating turbine lubricating oil, opening up the possibility of expanding its use to industrial facilities.

Experimental study on emissions and particulate characteristics of diesel engine fueled with plastic waste oil, acetone-butanol-ethanol and diesel blends

Plastic waste poses a significant environmental challenge due to its non-biodegradable nature and accumulation in landfills. Converting plastic waste into usable fuel could offer a promising solution for mitigating these issues while addressing the emission-related challenges of diesel engines. This study investigates the impact of plastic waste oil (WPO) obtained through pretreatment and catalytic pyrolysis, blended with acetone-butanol-ethanol (ABE) and diesel fuel, on diesel engine. The aim was to evaluate how these blends affect gaseous emissions, organic compounds, and particle-bound carbon, focusing on their potential to reduce harmful pollutants compared to pure diesel fuel. The results indicated that the ABE5W15D blend significantly reduced smoke and CO emissions by 35.7 % and 17.43 %, respectively, with a slight decrease in HC emissions. However, the ABE20W blend showed elevated NOx levels due to higher ignition delay and increased cylinder pressure. Compared to pure diesel (D100), ABE10W10D and ABE5W15D blends reduced total polycyclic aromatic hydrocarbons (PAHs) emissions by 26.8 % and 37.4 %, respectively. Naphthalene was the dominant PAH, remarkably increasing with W20D use, while longer-chain alkanes associated with lubricant oil had higher W20D emissions. The ABE5W15D blend notably reduced organic carbon (OC) emissions by approximately 38.26 % compared to D100. ABE20D exhibited lower elemental carbon (EC) emissions than D100, although it had higher EC than OC. The W20D blend resulted in larger particle diameters, whereas ABE10W10D showed lower particle counts in the 7–15 nm range. In conclusion, blending plastic waste oil with ABE and diesel fuel can effectively mitigate certain pollutants, depending on the blend composition.

An improved YOLOv8-CGA-ASF-DBB method for multi-class wear debris recognition of online visual ferrograph image

Abstract The analysis of wear based on On-Line Visual Ferrograph (OLVF) provides crucial insights for the analysis of wear faults in mechanical equipment.However, online ferrograph analysis has been greatly limited by the low imaging quality and recognition accuracy of particle chains and high hubbles when analyzing lubricant oils in practical applications. To address this issue,this paper proposes an enhanced OLVF wear image detection model based on YOLOv8 and applies it to the multi-class intelligent recognition of ferrograph images .The Cascade Group Attention(CGA) module is introduced enhance the diversity of features and improve computational efficiency. The fusion of attention scale sequence is introduced to achieve precise and rapid recognition of small targets. This Diverse Branch Block(DBB) module is introduced efficiently extracts features without compromising reasoning speed during training. For verification , a test of the bridge transmission box was conducted based on OLVF, and 992 ferrograph images were collected. Experimental results reveal that the improved algorithm achieves an accuracy of 94.53% on the dataset of bridge transmission box ferrograph wear debris images collected through OLVF. This represents a 5.2% increase in recognition accuracy compared to the original algorithm, while maintaining a processing time of only 0.69ms per image. These findings provide compelling evidence for the significant enhancements in both recognition accuracy and processing speed achieved by the improved algorithm, thereby establishing its considerable value for engineering applications.

Impact of Extended Intervals on Diesel Engine Performance with 15W-40 DH1 Lubricant Oil

Engine lubricant oil is crucial for minimizing friction between moving components within an engine, directly influencing the engine's reliability and lifespan. Determining the appropriate oil replacement intervals is essential, as extending these intervals necessitates more rigorous monitoring of both oil quality and engine condition. This study investigated the performance of SAKAI 15W-40 DH1 engine oil in the SAKAI Vibrating Roller SV526 over varying operational periods: 125 hours, 250 hours, 375 hours, and 500 hours. The research involved analyzing oil samples for viscosity, metal additives, total base number (TBN), and contaminants using Fourier Transform Infrared Spectroscopy (FTIR). Additionally, key engine performance indicators, including fuel consumption, valve clearance, and compression pressure, were measured. The findings revealed a gradual decrease in oil viscosity from 13.48 cSt to 11.56 cSt, approaching the minimum acceptable threshold of 11.45 cSt. Concurrently, the Fe content in the oil increased to 11 ppm, indicating wear, while the valve clearance in cylinder number three expanded to 0.48 mm, and compression pressure dropped from 31 kg/cm² to 28 kg/cm². Despite these changes, the oil remained within the standard operational limits, and the engine continued to perform adequately. However, based on the observed trends, extending the oil replacement interval to 500 hours cannot be conclusively recommended, as the oil's condition and engine performance may begin to decline beyond this point.

UV-driven self-replenishing liquid-infused surface with promising anti-algal adhesion performance.

Slippery liquid-infused porous surfaces (SLIPSs) inspired by Nepenthes have attracted much attention owing to their potential application in various cutting-edge fields. However, the performance of SLIPSs is impeded by surface damage and lubricant depletion, thereby limiting their further application. Herein, a UV-responsive slippery surface (SMEMG) was fabricated by introducing the UV-responsive functional group coumarin into the polymer side chain through random copolymerization, followed by crosslinking, curing and impregnation with vegetable oil. The self-healing ability and lubricant self-replenishing performance of the SMEMG were investigated. The results show that upon exposure to UV light, the damaged surface substrate can be repaired through a reversible photodimerization reaction between coumarin groups. Meanwhile, the lubricant oil within the bulk of the SMEMG substrate can be extruded to the surface during the photodimerization reaction, facilitating the recovery of surface wettability. The SMEMG exhibited excellent self-cleaning and anti-algal properties as well as durability in a harsh environment, demonstrating its promising application in marine anti-fouling.

Research on the prediction algorithm of aero engine lubricating oil consumption based on multi-feature information fusion

Research on the prediction algorithm of aero engine lubricating oil consumption based on multi-feature information fusion

Study on the Effect of Operating Conditions on the Friction Pair Gap in a Wet Multi-Disc Clutch in a Helicopter Transmission System

The friction pair gap affects not only the temperature increase of the multi-disc wet clutch, but also the efficiency of the helicopter transmission system. Consequently, a rotational–axial engagement and disengagement-coupled kinetic model of a wet multi-disc clutch considering asperity contact, hydrodynamic lubrication, spline resistance, and a separating spring model are developed in this paper. The effects of operating conditions on the dynamic characteristics of the wet clutch are investigated. Further, the gap deviation coefficient is proposed to characterize the dynamic behavior of the friction pair gap. As the control oil pressure increases from 1.3 MPa to 1.7 MPa, the gap deviation coefficient increases by 8.6%. Moreover, as the rotation speed increases from 888 rpm to 2488 rpm and the lubricant oil temperature increases from 25 °C to 85 °C, the gap deviation coefficient decreases by 1.1% and 4.44%, respectively. Therefore, an appropriate increase in lubricant oil temperature and rotation speed can facilitate the friction pair gap to be more uniform. These results are useful for the development of optimal control strategies for aviation wet clutch systems.

Analysis of Damage to Main Bearing on The Diesel Generator Motors at KM Sabuk Nusantara 89

Main bearings are made from special metal materials that are resistant to hot engine friction. The main bearing has holes in several parts which function to allow fluid (lubricating oil) to flow. Metal sitting is two plates that have a very smooth surface and consist of several layers of metal that have different hardness. The main bearing is a very vital part to support the performance of the crankshaft. The aim of this research is to determine the factors that cause damage to main bearings in diesel generator motors. The research method used is a qualitative descriptive method using observation, interviews and documentation methods and using the fishbone analysis method. The results obtained from this research show that the causes of damaged main bearings in diesel generator motors are decreased lubricating oil pressure, lack of understanding of maintenance procedures and fatigue of the seated metal component materials.

Assessment of overall remaining useful life of lubricants by integrating oil quality and performance

Effective lubricant health monitoring programs are essential for extending the lifespan of both the lubricant and machinery. An accurate and reliable remaining useful life (RUL) prediction is necessary for maintenance decision support. The degradation of used lubricating oil information trends evaluated using used oil analysis results is necessary. This study addresses the need for a comprehensive tool to consolidate oil analysis parameters and determine the remaining useful life (RUL) of used lubricating oil (ULO). A Performance Rating Index (PRI) was developed by integrating various oil degradation testing parameters, including membrane patch colorimetry for varnish and sludge potential, along with viscosity, foaming stability, water separability, air release properties, oxidation stability, rust prevention, and copper strip corrosion. The integration of routine and performance test results of a turbine oil at 25,480 operating hours exhibited a PRI of 48.5. Correlating with the ASTM degradation alarm limits of 50 %, the PRI results provide clear maintenance actions before the original equipment manufacturer's recommended overhaul. The PRI approach supports proactive maintenance by facilitating early oil replenishment, extending RUL, and reducing waste oil.

Insights in the wettability of hard chromium coated steel for cold rolling applications

The use of toxic Cr (VI) in the chrome plating process poses significant health risks, highlighting the urgent need to find sustainable alternatives for many applications such as cold rolling. Understanding key properties of functional chrome coating in lubricated industrial processes, especially its wetting properties that can support lubrication, low friction, and durability, is essential for the development of safer coating processes. However, the wetting properties of hard chromium coating are not fully understood. This study investigates the wetting characteristics of chromium coatings in comparison to uncoated steel. The study explores the dynamic wetting behavior by conducting contact angle measurements with water and lubricant oil, determining surface free energy using the sessile drop method, and characterizing the surface through X-ray photoelectron spectroscopy analysis. The findings reveal that a standard hard chrome coating exhibits superior wettability by both water and oil and higher surface energy compared to uncoated steel. The research, supported by theoretical modelling, highlights that factors are not limited to chromium alone, but rather involve a multilayer system that includes chromium oxide and organic contaminations, which have a substantial impact on surface properties and wettability. Increased levels of organic contamination on the chrome-coated surface, are shown to result in weaker intermolecular interactions with the contacting fluid, leading to reduced surface affinity to water and consequently result in higher contact angles. Our findings provide critical insights into the intricate nature of chromium coatings and lay foundations for developing sustainable alternatives.

Influence and optimization of dual-orifice jet nozzles on oil capture performance of under-race lubrication with a radial oil scoop for high-speed bearings in aero-engine

The objective of this research is to determine the influence of dual-orifice jet nozzles on the oil–air flow dynamics and oil capture performance in the under-race lubrication for high-speed bearings and to identify the optimal design parameter combinations for optimizing the oil capture performance. An experimental setup for under-race lubrication is specifically designed, complemented by a multiphase computational fluid dynamics model to elucidate the oil–air flow behavior. The response surface methodology is combined with a multi-objective particle swarm optimization algorithm to perform multi-objective optimization of the oil capture performance. The findings indicate that oil capture efficiency initially rises to a peak and subsequently declines with increasing orifice spacing, identifying an optimal orifice spacing that maximizes efficiency. While the oil flow rate from dual-orifice jet nozzles is lower than twice that of single-orifice jet nozzles, appropriate parameter matching allowed for an increase in both captured lubricant oil and efficiency. Optimized configurations achieved substantial enhancements in oil capture efficiency, with the greatest improvement exceeding 16%, all while maintaining precise oil supply to the high-speed bearings.

Evaluating Household Hazardous Waste Generation, Composition, and Health Risks in an Urban Municipality

This study aimed to assess the generation rate and composition of household hazardous waste (HHW) in Nakhon Si Thammarat Municipality, Thailand. A questionnaire survey was conducted to collect data on HHW generation and disposal practices from households in the municipality. Soil samples were collected and analyzed for heavy metals (cadmium, chromium, mercury, nickel, and lead) and PCBs contamination. The potential health risks from ingestion exposure associated with heavy metals and polychlorinated biphenyls (PCBs) contamination in the soil were evaluated. The result revealed that in 2023, the HHW generation rate was 11.95 kg/household/year, with the highest percentages occurring of electronic waste (17.40%), fluorescent lamps (16.98%), spray cans (12.38%), cleaning products (11.30%), and engine oil and lubricant oil products (9.87%). The majority of residents (92.90%) disposed of hazardous waste and general waste together in public waste containers. However, the health risk assessment indicated that the levels of heavy metals and PCBs in the soil were within the safe acceptable range for residents, with a total lifetime cancer risk from ingestion exposure of less than 1E-06 for both adults and children. The findings highlight the need for improved waste separation practices and the implementation of effective hazardous waste management strategies to minimize potential health risks and environmental impacts. This study serves as a basis for developing targeted interventions and policies to enhance household hazardous waste management in the municipalities and similar urban areas in Thailand. Doi: 10.28991/HEF-2024-05-03-011 Full Text: PDF

Experimental Study on Tribological, Rheological and Bio-degradability Characteristics of Canola Oil with TiO2 Nanoparticles as Bio-nanolubricants

In response to growing environmental concerns about the adverse effects of conventional lubricants, there has been a surge in the demand for eco-friendly alternatives. Biodegradable lubricants, crafted from renewable sources, represent a sustainable solution to address these environmental apprehensions. This research describes the tribological, rheological properties and biodegradability of rapeseed oil with 0.25 to 1.25 weight percent TiO2 nanoparticles as additives. The lubricant samples were prepared using a magnetic stirrer and an ultrasonic device. Friction and wear properties such as coefficient of friction and wear scar diameter were determined using a four-ball tester. In comparison with SAE20W40, samples 1 (0.25 weight percentage of TiO2) and sample 2 (0.5 weight percentage of TiO2) shown remarkably improved tribological performance, with 73.32% and 66.76% decreases in coefficient of friction (COF), respectively. Shear stress, shear rate and dynamic viscosity are analyzed using a rheometer. The acquired results are juxtaposed with both pure canola oil and various mineral oils for comparison. The nano-lubricant synthesized in this study emerges as a viable alternative to SAE10, DXT3 (steering fluid), and SAE20W50 grade oils, demonstrating lower friction and a reduced wear scar diameter. Biodegradability tests were performed on all generated samples using the Biochemical Oxygen Demand (BOD) apparatus, and all samples exhibited a BOD to Chemical Oxygen Demand (COD) ratio better than 0.5, indicating biocompatibility. The findings of the research investigation indicate that the combination of canola oil with TiO2 blends holds significant promise as an alternative to conventional synthetic lubricant oils.

The pyrolytic distillation of waste lubricants with waste oilfield scale into value-added fuel

The ever-increasing generation of waste materials has become a major environmental concern, highlighting the need for sustainable waste management strategies. This study explores the catalytic pyrolysis of waste lubricant oils using a waste oilfield scale as a low-cost solid catalyst to produce value-added fuel products. The pyrolytic distillation of waste engine oil was carried out in a manual distillation unit, employing a calcium carbonate (CaCO3) scale as a catalyst under various reaction conditions. Distillation experiments were conducted at 300 °C, 320 °C, and 350 °C, with and without adding NaOH and CaCO3 catalysts. The distillate fractions were characterized, and their properties were compared to standard fuel specifications. The results demonstrated that increasing the pyrolysis temperature and employing CaCO3 as a catalyst significantly enhanced the distillate yield and improved key fuel properties. At 350 °C, the distillate yield reached 56 % with 4 g of CaCO3, exhibiting desirable density (0.8049 g/cm3), viscosity (2.31 cSt at 40 °C), sulfur content (0.43 wt%), and a calorific value of 43,152 kJ/kg. Further, the distillate fractions were separated into gasoline (80–150 °C), kerosene (180–270 °C), and gas oil/diesel (270–350 °C) ranges, with the diesel fraction showing a promising cetane number of 51. The catalytic pyrolysis fuel (CPF) obtained from distillation with 4 g CaCO3 at 350 °C, followed by bleaching with CaO, exhibited excellent properties, including a density of 0.8297 g/cm3, viscosity of 2.71 cSt at 40 °C, pour point of −12 °C, sulfur content of 0.201 wt%, and a calorific value of 43,961 kJ/kg. The GC analysis revealed a paraffin-rich composition in the desired fuel ranges, contributing to the desirable fuel properties.

Performance assessment of the multi-nozzle injection MQL system for cleaner machining of hardened AISI D2 steel concerning power consumption

ABSTRACT Sustainable hard machining is a pressing need in manufacturing industries for techno-social, economic and environmental benefits to machine difficult-to-cut materials. Thus the present study investigates finish turning of hardened AISI D2 steel using a MTCVD coated carbide insert (TiN-TiCN-Al2O3) with geometry CNMG120408FW and grade WK05CT under a multi-nozzle MQL system using LRT 30 mineral oil (50 ml/hr flow rate, 6 bar compressed air pressure, 30 mm nozzle distance from tool tip) for minimal quantity lubrication at both the rake and flank zones for assessment of machinability. Flank wear lies between 0.79 and 0.155 mm and within the failure criterion limit of 0.2 mm. Arithmetic surface roughness trials have been within 0.361–0.877 microns and within the 1.6 microns acceptable range. The cutting temperature has been between 80.7°C and 226.9°C and even below 200°C in the majority of runs. The cutting power lies within 0.432kW–0.804kW. The optimal parametric combination has been found to be d=0.1 mm, f=0.05 mm/rev and v=80 m/min respectively and improvement has been observed over dry cutting. RSM models are found to be statistically significant. Application of multi-nozzle MQL in machining of hardened steel outperformed through machinability assessment and may be adopted in shopfloor for sustainability..

Microscopic Aggregation and Film‐Forming Characteristics of Lubricant Additives on Oil–Water Interface: MD Simulation and Experiments on Water Separability

ABSTRACTThe anti‐emulsification property of lubricating oil is an important index to measure the quality of oil. In this paper, the behaviour of surfactants such as lubricating oil additives at the oil–water interface and the influence of the position of ethylene oxide (EO) and propylene oxide (PO) in the block polyether demulsifier on the demulsification effect were investigated by molecular simulation and experimental verification. The properties of seven lubricating oil additives with different functions and two pairs of isomers were investigated by molecular simulation, and their demulsification effects were verified by experiments. Some simulation results such as interface thickness and density distribution can accurately predict the experimental demulsification effect. Moreover, it was found that the position isomerism of surfactants affected the demulsification performance by changing the lipophilic balance and interface properties. The demulsification performance of sequenced copolymers is generally better than that of anti‐sequenced copolymers. The accurate prediction of molecular dynamics simulation makes the selection of lubricating oil demulsifier more extensive and has practical application value.

Fast dentification of overlapping fluorescence spectra of oil species based on LDA and two-dimensional convolutional neural network

Although most petroleum oil species can be identified by their fluorescence spectra, overlapping fluorescence spectra make identification difficult. This study aims to address the issue that fluorescence spectroscopy is ineffective in identifying overlapping oil species. In this study, an equivalent model of overlapping oil species with fluorescence spectra was established. The linear discriminant analysis (LDA)-assisted machine learning (ML) algorithms K nearest neighbor (KNN), decision tree (DT), and random forest (RF) improved the identification of fluorescent spectrally overlapping oil species for diesel-lubricant oils. The identification accuracies of two-dimensional convolutional neural network (2DCNN), LDA combined with the ML algorithms effectively all 100 %. Furthermore, Partial Least Squares Regression (PLSR) algorithm, Support Vector Regression (SVR) algorithm, DT regression algorithm, and RF regression algorithm were also used to identify the lubricant concentration in diesel-lubricant oils. The coefficient of determination of the DT was 1, and the root-mean-square error was 0, which identified the concentration of lubricant oils in them accurately and without error.