Engine Wear Research Articles

Assessing Aircraft Engine Wear through Simulation Techniques

In the field of aeronautical engineering, understanding and simulating aircraft engine performance is critical, especially for improving operational safety, efficiency, and sustainability. At Safran Aircraft Engines, we were able to demonstrate the effectiveness of using time series collected from the engines after each flight to build a digital twin that provides a dynamic virtual model able to mirror the real engine’s state by using a transformer-based conditional generative adversarial network. This virtual representation allows for advanced simulations under diverse operational scenarios like flight conditions and controls, aiding in understanding the impact of different factors on engine health. It is, therefore, possible for us to provide virtual flights performed by our engines in their actual state of wear. This research paper presents a machine learning model that effectively simulates and monitors the state of aircraft engines in real-time, enabling us to track the evolution of the engines’ health over their life cycle. The model’s adaptability to incorporate new data ensures its applicability throughout the engine’s lifespan, marking a step forward in proactive aeronautic maintenance and potentially enhancing engine longevity through timely diagnostics and interventions.

Modelling the impact of reducing lubricant viscosity on a conventional passenger car fuel economy and wear protection

This study explores how reducing lubricant viscosity affects fuel economy in passenger cars through experimental characterization and semi-predictive modelling. Thus, three engine oils (0W-20, 5W-30, and 5W-40) were tested for their rheological and tribological properties. Data were introduced into a detailed GT-Suite model of a turbocharged gasoline SUV. Simulations over six different driving cycles, including European homologation and real-driving conditions, used a fast-running model (FRM) to assess engine friction and wear protection. Results showed that lower viscosity oils, especially 0W-20, significantly reduced frictional losses, enhancing fuel economy. However, lower viscosity also increased contact friction under high power demand, raising durability concerns. A comprehensive evaluation of lubricants performance, offering insights into the trade-offs between fuel economy improvements and potential durability risks.

Identification of the Problem in Controlling the Air–Fuel Mixture Ratio (Lambda Coefficient λ) in Small Spark-Ignition Engines for Positive Pressure Ventilators

The air–fuel ratio is a crucial parameter in internal combustion engines that affects optimal engine performance, emissions, fuel efficiency, engine durability, power, and efficiency. Positive pressure ventilators (PPVs) create specific operating conditions for drive units, characterized by a reduced ambient pressure compared to standard atmospheric pressure, which is used to control carburetor-based fuel supply systems. The impact of these conditions was investigated for four commonly used PPVs (with internal combustion engines) in fire services across the European Union (EU), using a lambda (λ), carbon dioxide (CO2), carbon monoxide (CO), and hydrogen carbon (HC) analyser for exhaust gases. All four ventilators were found to operate with lean and very lean mixtures, with their lambda coefficients ranging from 1.6 to 2.2. The conducted tests of the CO2, CO, and HC concentrations in the exhaust gases of all four fans show dependencies consistent with theoretical analyses of the impact of the fuel–air mixture on emissions. It can be observed that as the amount of burned air decreases, the values of CO and HC decrease, while the concentration of CO2 increases with the increase in engine load. Such an operation can accelerate engine wear, increase the emission of harmful exhaust gases, and reduce the effective performance of the device. This condition is attributed to an inadequate design process, where drive units are typically designed to operate within atmospheric pressure conditions, as is common for these engines. However, when operating with a PPV, the fan’s rotor induces significant air movement, leading to a reduction in ambient pressure on the intake side where the engine is located, thereby disrupting its proper operation.

Turbofan engine health status prediction with neural network pattern recognition and automated feature engineering

PurposeThis study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated features engineering (AFE).Design/methodology/approachThe main concept of engine health status prediction was based on three case studies and a validation process. The first two were performed on the engine health status parameters, namely, performance margin and specific fuel consumption margin. The third one was generated and created for the engine performance and safety data, specifically created for the final test. The final validation of the neural network pattern recognition was the validation of the proposed neural network architecture in comparison to the machine learning classification algorithms. All studies were conducted for ANN, which was a two-layer feedforward network architecture with pattern recognition. All case studies and tests were performed for both simple pattern recognition network and network augmented with automated feature engineering (AFE).FindingsThe greatest achievement of this elaboration is the presentation of how on the basis of the real-life engine operational data, the entire process of engine status prediction might be conducted with the application of the neural network pattern recognition process augmented with AFE.Practical implicationsThis research could be implemented into the engine maintenance strategy and planning. Engine health status prediction based on ANN augmented with AFE is an extremely strong tool in aircraft accident and incident prevention.Originality/valueAlthough turbofan engine health status prediction with ANN is not a novel approach, what is absolutely worth emphasizing is the fact that contrary to other publications this research was based on genuine, real engine performance operational data as well as AFE methodology, which makes the entire research very reliable. This is also the reason the prediction results reflect the effect of the real engine wear and deterioration process.

Aircraft engine dust ingestion at global airports

Abstract. Atmospheric mineral dust aerosol constitutes a threat to aircraft engines from deterioration of internal components. Here we fulfil an overdue need to quantify engine dust ingestion at airports worldwide. The vertical distribution of dust is of key importance since ascent/descent rates and engine power both vary with altitude and affect dust ingestion. We use representative jet engine power profile information combined with vertically and seasonally varying dust concentrations to calculate the “dust dose” ingested by an engine over a single ascent or descent. Using the Copernicus Atmosphere Monitoring Service (CAMS) model reanalysis, we calculate climatological and seasonal dust dose at 10 airports for 2003–2019. Dust doses are mostly largest in Northern Hemisphere summer for descent, with the largest at Delhi in June–August (JJA; 6.6 g) followed by Niamey in March–May (MAM; 4.7 g) and Dubai in JJA (4.3 g). Holding patterns at altitudes coincident with peak dust concentrations can lead to substantial quantities of dust ingestion, resulting in a larger dose than the take-off, climb, and taxi phases. We compare dust dose calculated from CAMS to spaceborne lidar observations from two dust datasets derived from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). In general, seasonal and spatial patterns are similar between CAMS and CALIOP, though large variations in dose magnitude are found, with CAMS producing lower doses by a factor of 1.9 to 2.8, particularly when peak dust concentration is very close to the surface. We show that mitigating action to reduce engine dust damage could be achieved, firstly by moving arrivals and departures to after sunset and secondly by altering the altitude of the holding pattern away from that of the local dust peak altitude, reducing dust dose by up to 44 % and 41 % respectively. We suggest that a likely low bias of dust concentration in the CAMS reanalysis should be considered by aviation stakeholders when estimating dust-induced engine wear.

DIESEL ENGINE WEAR DURING WARMING UP

DIESEL ENGINE WEAR DURING WARMING UP

ANALYSIS OF LUBRICANT OIL DEGRADATION AND SOUND PRESSURE LEVEL FOR CI ENGINE USING BLEND FUELS

Long-term engine running has been the subject of extensive research on the deterioration of engine oil. In contrast, it is not fully clear what effect synthetic and biofuels will have. Modern engines, traditional fuels and lubricants should be used to provide a research basis for characterizing novel fuel-related phenomena in engines. This study makes an effort to characterize how lubricating engine oil behaves over the course of its service life using data on friction and wear. Every 20 hours, oil samples from the engine were obtained to evaluate its chemical makeup. On a reciprocating test rig, friction and wear measurements were taken. Kinematic viscosity, density, and wear metals such as cadmium (Cd), cobalt (Co), and lead (Pb) were measured for the lubricant oil analysis. In general, n-pentanol aids in the reduction of engine wear debris, contamination, and lubricating oil oxidation. According to the findings of this study, a D60WCO20Pe15 ternary combination can be used in a diesel engine without any alteration. The sound pressure level (SPL) increased by 7.8 dB at engine speed of 1300 RPM in the case of the DF95WCO5. However, when compared to base line, the average SPL of D60WCO20Pe15 ternary blend was 4.3 dB lower.

An investigation of the longevity wear assessment during the utilisation of biofuel-diesel blends in a diesel engine: a case study of crude palm and crude jatropha oil

A longevity test was conducted to evaluate the impact of biofuels on engine degradation. Two varieties of blended fuel were generated by adding crude palm oil or crude jatropha oil to B5 diesel. The amounts of additional crude oil were 5, 10, and 15%. The testing period lasted 600 h, which is equivalent to 3–5 years of actual service. Before and after the test, the dimensions of engine elements were measured to determine the level of wear. Inspecting engine components revealed that combining crude bio-oils in proportions ranging from 0 to 15% increased engine wear. Components located in the combustion chamber exhibited greater wear when blended fuels were used, whereas fuel pump and injector components, which were not exposed to the heat, exhibited lower levels of wear. Even though engine wear was observed when mixed fuels were used, the vast majority of wear rates were incredibly low, ranging from 0.001 to 0.002 mm per 100 h. The only exception to this rule was the piston attrition rate, which was measured at 0.007 mm per 100 h. It can be concluded that engine wear is negligible when biofuel is blended with diesel in a ratio not exceeding 15% compared to B5 diesel.

Effects of fuel composite additives on the vibration, wear and emission performances of diesel engines under hot engine tests

Diesel engines applied for ships are currently facing an escalating demand for energy conservation and emission reduction, which has driven the application of fuel composite additives. Nevertheless, adverse phenomena affecting engine reliability have been observed in practical engine applications with unclear mechanisms. The present study investigated the vibration, wear, and emission performances of three types of composite additives with detergent and synergist function in a diesel engine. Vibration acceleration, cylinder temperature, NOx emission quantity, as well as the wear characteristics of cylinder liner-piston ring (CLPR) friction pairs were selected as characterization parameters. The results revealed that components of additives have a certain impact on vibration, wear, combustion, and emission performance. Specifically, additives of Type Ⅰ containing aviation kerosene and Type Ⅱ containing 2-Ethyl 1-hexanol and 2-Ethylhexyl nitrate compound in diesel were susceptible to cause aggravated engine vibration and thus lead to excessive wear. Furthermore, Type I exacerbates the thermal stress and worsens combustion stability, resulting in increased mechanical vibrations, cylinder temperature, and NOx emission. In contrast, addition of Type Ⅲ containing 2-nitro-propane and toluene results in improved reliability, demonstrating a 7.6% reduction in mechanical vibration energy and a 27.4% decrease in wear mass losses of piston rings, while effectively mitigating abnormal wear on the liner surface. Likewise, it also it also facilitates a mild combustion process and achieves better emission reduction results by reducing the NOx emission by 11.5% while slightly lowering the cylinder temperature by 0.74%.

Rapid Investigation of Blisk Mistuning Via Piezoelectric-Induced Stiffness Perturbations

Abstract Manufacturing tolerances and engine wear produce slight variations in the nominally identical blades of a bladed disk, or blisk. In theory, the vibrational energy of a tuned blisk is evenly distributed among the identical blades. Mistuning arises when blades are not exactly identical, producing vibration localization at one or more blades that can lead to premature failure via high-cycle fatigue. Blisk designers must consider how expected manufacturing variations and potential engine wear affect blade vibration and lifetime. However, a single experimental blisk can only capture a single mistuned configuration, making experimental assessment of mistuning both cost- and time-prohibitive. This paper investigates piezoelectric-induced stiffness perturbations as a potential approach that enables rapid testing of a wide range of mistuned configurations in a lab environment. Integrating piezoelectric material onto the blisk produces a continuous range of effective blade stiffness values. Piezoelectric stiffness perturbations alter the relative stiffnesses of all blades, changing the mistuned configuration. Simulations of a lumped blisk model characterize piezoelectric mistuning to motivate use in experimental preliminary testing of blisks. Optimization of the piezoelectric stiffness perturbation enables testing of desired mistuned amplitude distributions. Finally, benchtop testing of an academic blisk validates the ability of piezoelectric stiffness perturbations to change the mistuned configuration without any mechanical adjustments. Overall, piezoelectric mistuning enables rapid investigation of a theoretically infinite number of mistuned configurations with only one experimental blisk.

1.4-Dioxane and the Phenolic Compound Against UV Irradiation of Diesel

During storage and transportation, some classes of hydrocarbons in diesel fuel can undergo chemical transformations over time due to ambient temperature, sunlight, and oxygen in the air. As a result of these reactions, there are changes in the composition of the fuel, such as sediment, color change, turbidity, which have a negative effect on the physico-chemical indicators of the fuel. Such a change can cause engine wear and adversely affect engine efficiency, performance, emissions, and durability. The main objective of this study is to investigate antioxidant additives to delay the aging process in diesel fuels. The compounds 1,4 dioxane and 3-hydroxy-1-(2-hydroxyphenyl)-3-(4-nitrophenyl)-propane-1- one were selected for this study. UV rays have been used to stimulate the aging process. As a result of research, the use of 1,4-dioxane has significantly improved the chemical stability, density, and kinematic viscosity of fuel and its use in diesel fuel has shown greater stabilization potential.

Renewable Energy for Desalinization using Reverse Osmosis

This paper presents a proposal for fulfilling the energy demands of small desalination facilities in remote areas, by using a combination of renewable energies. The integrated system consists of photovoltaic modules, wind turbine, diesel generator, battery bank for energy storage and a reverse osmosis desalinization unit. A central aspect is the automation of the overall system to improve reliability and ensure that the water demand is fulfilled. For this, variations in the supply of renewable energy, water demand and maintenance operations of desalination plant are taken into account using short-term predictions. The key objectives are maximise the use of renewable energies, reduce fuel dependency and engine wear and tear due to incomplete combustion.

Enhancing Aircraft Safety through Advanced Engine Health Monitoring with Long Short-Term Memory.

Predictive maintenance holds a crucial role in various industries such as the automotive, aviation and factory automation industries when it comes to expensive engine upkeep. Predicting engine maintenance intervals is vital for devising effective business management strategies, enhancing occupational safety and optimising efficiency. To achieve predictive maintenance, engine sensor data are harnessed to assess the wear and tear of engines. In this research, a Long Short-Term Memory (LSTM) architecture was employed to forecast the remaining lifespan of aircraft engines. The LSTM model was evaluated using the NASA Turbofan Engine Corruption Simulation dataset and its performance was benchmarked against alternative methodologies. The results of these applications demonstrated exceptional outcomes, with the LSTM model achieving the highest classification accuracy at 98.916% and the lowest mean average absolute error at 1.284%.

A comprehensive study on the impact of waste plastic oil on engine wear

A comprehensive study on the impact of waste plastic oil on engine wear

A Comprehensive Study on the Impact of Waste Plastic Oil on Engine Wear

A Comprehensive Study on the Impact of Waste Plastic Oil on Engine Wear

Effect of laser wavelength on the quantitative analysis performance of indirect ablation LIBS for analyzing the metals in lubricating oil.

For monitoring the lubricant quality and engine wear status, indirect ablation laser-induced breakdown spectroscopy (LIBS) was introduced to determine the metal elements in lubricating oil. Due to the different transmittance values of oil at different laser wavelengths, the effect of the laser wavelength on the detection performance of indirect ablation LIBS was studied. Under optimal parameters, the calibration curves were established for 10 metal elements with laser wavelengths of 1064, 532, and 355 nm. The obtained results show the average limit of detection (LoD) and the average relative standard deviation (ARSD) of spectral intensity for 1064, 532, and 355 nm are 15.942, 56.804, and 25.077 mg L-1, and 2.874%, 9.253%, and 12.649%, respectively. In addition, the average R2, the average relative error (ARE), and the root mean square error of cross validation (RMSECV) for a laser wavelength of 1064 nm are 0.991, 9.045%, and 18.379 mg L-1, which are better than those at 532 nm and 355 nm. Therefore, the laser wavelength affects the quantitative analysis performance of indirect ablation LIBS for the analysis of metal elements in lubricating oil and the optimal wavelength is 1064 nm.

Studies on Engine Oil Degradation Characteristics in a Field Test with Passenger Cars

Nowadays, a car’s engine oil change interval is an essential factor in reducing wear. The correct choice depends on various factors. This study analyzes the changes in the composition of three different engine oils (0W30, 5W30, and 5W40) during the generally accepted oil change interval (15,000 km) in gasoline and diesel cars during the post-warranty period. Commercially available low-level biofuel blends (B7 and E10) were used to power test vehicles in a field test. Engine oil samples were taken every 3000 km for more detailed analysis and tested in an accredited laboratory. The contaminants in the engine oil were determined using several testing methods: spectrometric analysis, gas chromatography, etc. Studies have shown that all used cars have an increase in the number of iron particles, an increased concentration of silicon, and also an increase in the number of nickel particles above 12,000 km. Tests also showed a sharp drop of molybdenum anti-friction additives 4.5 times and a gradual increase in fuel concentration for the Opel Insignia over 12,000 km, but over 9000 km, a significant increase in the concentration of chromium particles. Based on this research results, it is preferable to choose a maintenance interval of no more than 12,000 km for cars during the post-warranty period. In this way, the intensity of engine wear can be reduced due to the loss of adequate protective properties of the engine oil.

A Review on Oil-Soluble Polyisobutylene-Based Dispersant for Colloidal Stabilization

Oil soluble polymeric-based dispersants have been extensively used in engine oil lubrication formulation due to their inherent properties, such as modifiable viscosity, compatibility, and effectiveness. However, the underlying mechanism of how the dispersant stabilizes soot particles in engine oil is still not fully understood, and discovering this mechanism is crucial for engine oil formulation technology. This review discusses the interactions between colloidal particles induced by two PIBSA-derived dispersants, namely PIBSI and PIBSAE. The effectiveness of these dispersants in stabilizing colloidal particles in oil systems depends on the chemical functional groups present on the main chain. The spectrum of colloidal interactions, ranging from Derjaguin, Landau, Verwey and Overbeek (DLVO) to non-DLVO theory, is predominantly influenced by the equilibrium between dispersant concentration and the overall system viscosity. This phenomenon can eventually reverse colloidal stabilization and result in more serious issues, such as engine wear and tear.

Development of charge-transfer interatomic potential for O-Fe-P-Zn systems and its application to tribochemical reactions between ZnDTP-derived tribofilm and iron oxide

ZnDTP (zinc dialkyl-dithiophosphate) is added to lubricants to reduce wear in automobile engines. However, the atomistic understanding of its formation and effect on wear resistance remains incomplete. We have developed a charge-transfer interatomic potential for O-Fe-P-Zn systems to reproduce the tribochemical reactions between zinc phosphate and iron oxide. Since our potential function can handle a mixed system of covalent and ionic bonds, it can successfully reproduce structural changes in phosphate chains at the interface. To increase the potential’s accuracy and robustness, we employ three types of training data: target structures of stable crystalline and molecular structures, standard structures of various crystal structures covering a wide range of coordination numbers and bond angles, and annealed random structures with various compositions. The developed potential well reproduces energies, forces, and atomic charges for O-Fe and O-P-Zn systems as well as polyphosphate chain structures. We then apply this developed potential to ZnDTP-derived tribofilm on iron oxide, revealing that the long-chain phosphate turns into a dense network of short chains under high shear and normal stress conditions. Fe atoms are incorporated into the zinc metaphosphate network, creating a hard Fe/Zn mixed layer. Our results indicate that the short-chain layer acts as an easily sheared lubricant while the Fe/Zn mixed layer prevents wear on the iron oxide substrate.

Development of diagnostic parameters for assessing the operation of a diesel engine on site

The paper aims to develop the on-site diagnostic parameters for assessing the operation of engines through the content (g/ton) of wear elements and contaminants in used oil. Here, it refers to heavy-machinery vehicles used in various industries of Mongolia such as agriculture, railway, building and road construction, mining etc. This study analyzed the results of measurements in the used oil samples from 20 diesel engines over a maintenance period of 5-6 years using spectral analysis. It focuses on three key goals: determining the content of wear elements and contaminants in used oil (g/ton), studying the intensity of engine wear during one period of maintenance, and using non-parametric statistical methods to develop the on-site diagnostic parameters based on the concentration of wear elements and contaminants in the samples of used oil.
 The diagnostic parameters determined as a result of this study can enable technicians to perform diesel engine maintenance based on the actual technical condition of the engine, rather than relying solely on the manufacturer's recommended maintenance schedule, reduce the repair cost by addressing the aspects before serious breakdowns or delays occur and improve overall the engine performance, resulting in significant benefits for the transportation and heavy-machinery industries.