Engine Failure Research Articles

Theoretical and experimental study on the mechanical measurement of rock tensile fracture by ring radial compression

Conventional Brazilian disc splitting tests are hampered by stress concentration at the loading points, leading to test outcomes that do not truly represent the engineering failure strength of rocks. To enhance the accuracy of these tests, the specimen shape has progressed from the Brazilian disc to a circular ring. This study presents a theoretical analysis of the compression deformation process in circular rings, followed by platform-radial compression tests conducted on various types of rocks and metals, employing the digital speckle correlation method alongside an improved mechanical extensometer. The findings indicate that circular ring specimens failed under a combination of tensile and compressive stresses. The main crack originates along the loading direction on the inner wall of the ring and propagates outwards, resulting in the failure of the entire ring structure. While maximum tensile strain may serve as an indicator of rock failure, tensile stress alone should not be considered a definitive criterion for failure.

Predicting bifurcation and amplitude death characteristics of thermoacoustic instabilities from PINNs-derived van der Pol oscillators

Self-sustained thermoacoustic oscillations as observed in low-emission combustion- involved gas turbines and aero-engines involve complicated thermal fluid–acoustics interaction and rich nonlinear dynamics. Such pulsating oscillations are known as thermoacoustic instability. When it occurs, large-amplitude limit cycle oscillations (LCOs) of thermodynamic parameters are frequently observed. These LCOs could cause overheating, flame flashback, and even engine failures. Thus it is critical to understand and predict the generation mechanisms and nonlinear dynamics behaviours, and then develop corresponding control approaches to prevent or control the onset of such instabilities. In this work, we develop and extend the classical van der Pol oscillators by integrating a physics-informed neural networks (PINNs) algorithm with a modelled nonlinear Rijke-type thermoacoustic combustor. The theoretical Rijke tube system (with Galerkin expansion and modified King's law implemented) and a CFD simulation model are applied to provide ‘training/calibration data’ for the extended van der Pol (EVDP)-PINNs model. The optimized EVDP oscillators are confirmed to be capable of capturing the key nonlinear characteristics by comparing the transient growth behaviours of thermodynamic perturbations and LCO amplitude and frequency. Further investigations are conducted to obtain Hopf bifurcation and amplitude death (AD) characteristics. Comparison is then made to the coupled EVDP systems. Quite similar Hopf bifurcation features, but differences in regions of AD, are observed. In general, we demonstrate an applicable approach to intelligently ‘learn’ a nonlinear thermoacoustic system and to create reliable EVDP oscillator systems, which have great potential to contribute to the development and testing of control approaches, such as the coupling described in this work, which may replace costly experimental tests.

Crack evolution and fractal characteristics of fractured red sandstone based on acoustic emission parameters

Rock is a widely used engineering material, and accurate understanding of its internal microcrack evolution process during loading can provide a theoretical basis for preventing instability and failure in rock engineering. The rock pressure test system and acoustic emission equipment were used to carry out uniaxial loading and acoustic emission monitoring tests on fractured red sandstone. Based on the RA and AF values of acoustic emission and the fractal theory, the internal crack patterns and evolution rules of red sandstone with different crack angles were explored. The results show that the compressive strength of red sandstone varies with the crack Angle in the shape of “U”, and there is an obvious stress drop after the elastic stage of 30° and 45° crack red sandstone, which has a good correspondence with the acoustic emission ringing count rate. During the loading process, the damage mainly caused by tension cracks first appears inside the rock, and then the tension cracks increase steadily and the shear cracks gradually increase, indicating that the rock enters the stage of fracture instability development. With the development of shear cracks, the peak strength is finally reached and the instability failure occurs. During the loading process of 30° fracture red sandstone, the corresponding stress drop phenomenon of “shear crack group” appears. According to the D/S statistical analysis of different crack samples based on acoustic emission ringing count, the fractal dimension presents a decreasing-rising-decreasing trend with the increase of crack inclination, which corresponds to the change of the complexity of crack development in rock.

Failure assessment of seam-welded pipe under fatigue and thermal loading

This paper presents an assessment of the failure of a seam-welded pipeline under fatigue and thermal loading. The investigation concentrated on analyzing several factors potentially influencing pipeline failure. Both experimental analysis and numerical simulations utilizing the finite element method (FEM) were conducted to understand potential failure modes of a seam-welded SS304L pipeline. The experimental and FEA analyses investigated various failure factors including weld defects, fatigue and thermal loading, residual stresses, and overloads. The study concludes that substandard welding procedures and inadequate post-weld treatment, coupled with elevated residual stresses in the heat-affected zone (HAZ) of the weld, were the primary contributors to failure. The paper systematically outlines the utilization of experimental and FE analyses in examining practical engineering failure instances. This approach strengthens the ability to avert failures and navigate risks with precision. Furthermore, the results highlight the critical significance of adhering to code and standard guidelines concerning pipe seam welds and post-weld treatment practices.

Experimental study on fluid-Induced vibration caused by backward erosion piping based on acoustic emission

Abstract Double-layer dike foundation is one of the most common stratum types with the highest probability of catastrophic failure in dike engineering, and the most important danger is backward erosion piping. The occurrence and development of piping need to be monitored by reliable technology. Therefore, the influence of different piping outlet forms on acoustic emission monitoring is explored by using a self-designed test device. The results show that the overall evolution process of ringing count and accumulated energy can be divided into two stages according to the time of piping. In the first and middle stages, the particle collision is caused by sand boiling at the outlet, and the measured value is small. In the later stage, piping channels appear, particle migration occurs, and the measured value is large. Moreover, the maximum impact value decreases with the increase of the piping outlet, and the cumulative energy growth rate of the three groups of tests in the early stage is the same, while the head difference required for the rapid growth stage is inversely proportional to the piping outlet.

Research on assisted recovery algorithm of stall state based on signal guidance

Abstract Given the lack of quantitative guidance in the current stall recovery process, which leads to the pilot’s misoperation or untimely recovery, referring to the energy control theory of complex state recovery, a stall state-assisted recovery algorithm based on pitch angle, engine thrust, and roll angle signal guidance was determined. The structure pilot model and the kinematics simulation model of aircraft at a high angle of attack were established. The effectiveness of the algorithm has been verified by simulation analysis. The man-machine closed-loop simulation analysis results show that the algorithm can guide the pilot in effectively recovering from stall conditions under different stall scenarios and engine failure conditions.

The Turbofan Engine Remaining Useful Life Prediction Using 1-Dimentional Convolutional Neural Network

Turbofan engines have been the dominant type of engine in aircraft for the last forty years. Ensuring the quality of these engines is crucial for flight safety, particularly for long-distance flights. However, their performance degrades over time, impacting flight safety. To address this issue, it is essential to predict potential engine failures by estimating the Remaining Useful Life (RUL) of the engines Deep learning, especially Convolutional Neural Networks (CNNs), has demonstrated exceptional proficiency in handling intricate, non-linear data, leading to improved RUL predictionsdue to their ability to process complex and non-linear data. In this project, a 1-D CNN is used to predict RUL using the NASA C-MAPSS FD001 dataset, which consists of 3 settings and 21 sensors, though sensors with stagnant readings are excluded. The dataset is normalized using min-max and z-score methods, and then segmented into sequences for input into the 1-D CNN model. Various training scenarios were evaluated, with the best RMSE of 3.26 achieved using 10 epochs, a learning rate of 0.0001, and z-score normalization. The results indicate that feature selection can produce a lower RMSE compared to scenarios without feature selection.

An improved similarity-based RUL prediction method considering degradation degree of multiple condition monitoring parameters for aero-engines

Abstract The aero-engine is the heart of an airplane. Predicting the remaining useful lifetime (RUL) of an aero-engine bears great significance, not only for improving the reliability and safety of the aero-engine but also for ensuring aircraft safety and performance. However, both issues, namely the selection of uncorrelated parameters for RUL estimation and the lack of a standard theoretical methodology for Health Index (HI) construction, inevitably impact the prediction accuracy. Here, we proposed an improved similarity-based RUL prediction method considering the degradation degree of multiple condition monitoring parameters for aero-engines. This method includes the improved minimum-redundancy maximum-relevancy approach for the quantitative selection of key parameters, and the similarity matching approach which takes into account the degradation degree of multiple parameters instead of constructing HI. The effectiveness of the proposed method was evaluated on turbine engine datasets. Experimental results show that (1) compared with other feature selection methods, the root mean square error (RMSE) of the proposed method is reduced by 12.3%; (2) compared with other RUL prediction methods, the RMSE of the proposed method is smaller than most methods but without a complicated training process. The results demonstrate that the proposed method achieves highly competitive prediction performance. By employing the proposed method, it is possible to significantly reduce the risk of engine failures, thereby improving safety and economic efficiency.

Experimental study on energy and damage evolution of dry and water-saturated dolomite from a deep mine

The deformation and failure of a rock is closely related to the strain energy consumption during the load process of rock. To investigate the effect of water on energy evolution and damage characteristics of dolomite samples from a deep mine, the uniaxial compression tests were carried out on dry and water-saturated dolomite samples at different burial depths (900 m–1200 m). The effects of water on the evolution characteristics of elastic and dissipative energy ratios ( Ue/ U and Ud/ U) during rock deformation and failure was analyzed. Based on the variation rate of damage factor ( Df), a new brittleness index is proposed, which can effectively characterize the brittleness characteristics of water-bearing dolomite. The results show that the uniaxial compressive strength and elastic modulus of the water-saturated dolomite are significantly reduced compared to dry sample. The energy and damage evolution process of dolomite can be divided into four stages: initial damage stage, stable damage stage, pre-peak accelerated damage stage and post-damage stage. The variation rate of damage factor of the rock samples in the stable damage stage and the pre-peak accelerated damage stage appeared to increase significantly after water saturation treatment. Compared with water-saturated samples, more pronounced energy hardening characteristics and brittleness characteristics were observed in dry samples. In addition, the possible impact on the stability of deep rock engineering after the deterioration of rock mechanical properties and energy storage properties caused by water was analyzed. Groundwater can somewhat reduce rock burst proneness. However, it also has the potential to lead to greater rock engineering destabilization and failure hazards.

Application of Privacy Engineering Techniques in Software Development for the National Privacy Commission

The study investigated the implementation of privacy engineering in software development at the National Privacy Commission (NPC) with a specific focus on the Data Breach Notification Management System (DBNMS). Objectives include identifying the factors that contribute to the success or failure of privacy engineering in the NPC's software development context, to provide valuable insights into the integration of privacy measures. This includes the development of actionable guidance for the effective integration of privacy and security in software engineering at the NPC, tailored specifically for NPC engineers and encompassing methodologies for incorporating privacy engineering throughout the software development life cycle. This is to empower NPC software engineers with practical tools and strategies to create a secure and privacy-respecting environment. Qualitative methodology and thematic analysis approach were utilized to assess the effectiveness of privacy engineering techniques. To gather insights, semi structured interviews were conducted with both internal and external stakeholders composed of software developers, data protection officers, and other internal and external users of the DBNMS. Evaluation yielded positive remarks both from internal and external participants. Factors that contributed to the success and failure of privacy engineering techniques in software development include rapid evolution of technology, lack of funds, and stakeholder engagement, among others. Overall, the findings are expected to contribute to the broader discourse on privacy engineering and have implications for policymakers, software development practitioners, and organizations looking to enhance their privacy practices in the digital age.

Failure probability of F-100 Pratt & Whitney-220E turbofan engine on F-16 fighting falcon aircraft

Engine failure is a condition where the engine operates outside normal conditions. One of the abnormal conditions that occurs can be caused by a fault that occurs in each engine module. Engine module is one of the components on an aircraft that functions for supports the aircraft to fly and controls all engine operations, wether on the ground and during flight. The problem can occur in each engine module at any time causing engine failure. Therefore, it is necessary to carry out further analysis to determine the cause of the failure that occurred, as well as to implement appropriate mitigation measures. The method used is the Fault Tree Analysis (FTA) method, which is a method for identifying risks that contribute to failure and determining failure probability. From the analysis using the qualitative fault tree analysis method 71 events were obtained with 35 basic events. Meanwhile, the quantitative analysis produces a cumulative probability failure of 0.747. The probability value has almost reached 1, therefore preventive maintenance has to be carried out to prevent functional failure.

Jet Fuel Contamination: Forms, Impact, Control, and Prevention

This paper describes commonly used processes to produce aviation fuel and alternative routes with potential production yields for sustainable aviation fuels (SAF) like HEFA and ATJ. It also presents the possible sources (crude oil, refinery processes), causes (filter clogging, engine failure), and forms of contamination in both conventional and alternatively produced aviation fuels. Special attention is focused on the threats of fuel contamination with solid particles/trace elements, water, microorganisms, and fatty acid methyl esters (FAME). This review also presents the standard and novel advanced methods (ICP-MS, MALDI, ViPA) for identifying contaminations in aviation fuel. It also identifies possible ways to control and eliminate the risk of contamination, such as the fallowing coherent JIG system to ensure the quality of aviation fuel. Another approach that is very interesting and worth considering for future development is the idea of predictive maintenance and machine learning in monitoring and detecting contamination.

Fatigue damage evolution behaviors and fractional fatigue mechanical model of monzogabbro under true triaxial disturbance test

The disturbance wave caused by excavation or blasting of underground surrounding rock causes fatigue degradation effect of rock and eventually leads to disasters. However, the fatigue damage characteristics and fatigue models of rock under true triaxial disturbance are scare. Therefore, a series of true triaxial disturbance tests were conducted to investigate the rock fatigue deformation, strength and damage behaviors under different conditions. The evolutions of static damage and fatigue damage are separated and investigated respectively. Fatigue deformation and damage of rock under true triaxial stress undergoes three stages: attenuation, constant velocity and acceleration stage. The crack initiation stress can be as the initial condition of the fatigue deformation; the fatigue critical stress σdc of rock entering the acceleration failure stage was proposed and explored, with increasing frequency, σdc increase slightly and with increasing σ2, σdc increase obviously. Then, a novel fractional fatigue mechanical model considering the fatigue damage and intermediate principal stress effects of rock under true triaxial disturbance was proposed. The theoretical results of the model agree well with the results of the tests. Finally, the sensitivity analysis of stresses and model parameters and the model predictions under other untesting conditions were carried out to improve the understanding and prediction level of fatigue failure in underground engineering.

A hybrid predictive maintenance approach for ship machinery systems: a case of main engine bearings

A hybrid maintenance strategy is proposed, combining reliability-centered and condition-based maintenance strategies to prevent engine failures. A case study on the lubrication deficiency of a ship's main engine bearings was conducted. The reliability-centered maintenance phase is based on reliability-increasing rules, equipment facts, and a knowledge base. Then, a strategy is developed where system parameters are continuously monitored. These parameters are evaluated in the inference engine, and maintenance recommendations are provided to the ship operator. The investment cost of th developed system is discussed using a real engine failure case. The study shows that the strategy can improve maintenance on existing ships and system reliability at low costs. The methodology offers a cost-effective approach for the sustainability of the main engine, as demonstrated by a real crankshaft failure report. Unlike existing practices, it provides influential maintenance decisions based on evaluating system parameters within four operation ranges. Simulations show it detects insufficient lubrication faults at low engine loads, superior to current applications. The proposed approach suits different types of existing and newly built ships, engines like dual-fuel, and technologies such as semi-autonomous ships.

Improving Marvel Hero Classification through Dataset Curation

lores the development of a computer vision model for classifying Marvel superheroes such as Black Widow, Hulk, Iron Man, and Spider-Man. Utilizing a curated dataset sourced from Kaggle, the research emphasizes the critical role of dataset quality in refining model accuracy. Insights gained include adjustments to neural network configurations and leveraging Edge Impulse for enhanced performance. The findings highlight effective strategies for optimizing classification accuracy in complex image recognition tasks.PART 2:This part explores the application of Bayesian logistic regression to model the relationship between temperature and the probability of O-ring failure. By leveraging Bayesian inference techniques, analyzing historical data to quantify the risk associated with temperature variations and emphasize the importance of probabilistic approaches in safety-critical decision-making.The Space Shuttle Challenger disaster on January 28, 1986, remains a poignant case study in aerospace engineering failure. The investigation concluded that the failure of O-ring seals in cold temperatures led to the tragic loss of the shuttle and its crew.

ТЕСТОВЫЙ КОНТРОЛЬ ТОПЛИВНЫХ НАСОСОВ СОВРЕМЕННОЙ АВТОТРАКТОРНОЙ ТЕХНИКИ

The article presents the results of a study of the energy balance when the technical condition of the fuel pump of agricultural machines changes. Over 30% of internal combustion engine failures occur in the fuel system. Timely diagnostics, repairs and maintenance work (the latter is often not provided for or not performed) of electric fuel pumps can increase the service life and service life. Calculation of the energy balance is a prerequisite for developing a new or upgrading an existing method for diagnosing a fuel pump. The importance of using current strength as a diagnostic parameter (when determining the technical condition) of the pump in the mode of creating maximum pressure in the fuel system is emphasized. Based on the research results, an additional diagnostic parameter can be the rate of increase in the pump supply current. Research has shown that with an increase in the hydraulic resistance of the fuel system by 90%, the average rate of current increase was 7.6 A/s. When the hydraulic resistance of the fuel supply system decreased by less than 10%, the average rate of current increase was 19.2 A/s. Current is a sensitive parameter that increases or decreases depending on the level of increase in hydraulic resistance or leaks in the fuel system. The pump power expended on hydraulic losses did not change significantly due to the constant value of the pump operating voltage. The ideas (methods, techniques) developed in the article are in good agreement with the issues of modeling processes in hydrodynamic tribocouplings of high-pressure fuel pumps, in particular for Common Rail systems. The research was carried out at the expense of the Russian Science Foundation grant No. 23-29-10042, Topic: Numerical modeling of processes in hydrodynamic tribocouplings of high-pressure fuel pumps for advanced high-pressure diesel engines https://rscf.ru/project/23-29-10042/.”

Bayesian inference for reliability of K-out-of-N: G repairable retrial systems with mixed standbys, switching failure and reboot delay

Existing reliability studies on K-out-of-N: G repairable retrial systems with mixed standbys mainly consider the case where the standby switching is completely reliable and the repair time follows an exponential distribution, and most of them directly analyze the system reliability indices based on probability theory. Given the existence of such phenomenon as standby switching failure in engineering, this paper proposes a novel reliability model of K-out-of-N: G repairable retrial system with switching failure, and performs statistical inference on the reliability to realize the modeling and evaluation of the system. The considered system consists of mixed standbys and a repairer with vacation. When an operating component fails, the warm standby one is switched to the operating one immediately, and the probability of switching failure during the switchover process is p. In the case where the repair time of failed components follows a general distribution, based on the supplementary variable method and recursive algorithm, the steps for calculating the system steady-state availability are presented. In the case of unknown parameters for repair time and retrial time, the Bayesian estimator of the steady-state availability under the squared error loss function and highest posterior density (HPD) confidence interval are obtained. In numerical simulation, the system reliability inference is realized by using the Monte Carlo (MC) method, and the validity of the inference method is analyzed.

Підвищення ефективності забезпечення працездатності транспортних засобів

Accidental failures, leading to unplanned repairs, significantly increase the cost of their elimination compared to planned measures. A significant part of such failures are not sudden in nature. Gradual failure is preceded by a gradual change in some parameters. The impact of gradual failures on the efficient operation of road freight transport is increasing. Despite the fact that the failure of the engine, clutch or automatic transmission is not dangerous to the life and health of people, their impact on the economic condition of the enterprise is significant. There is a trend of decreasing the size of the rolling stock fleet for most of the country's motor transport enterprises. Therefore, the importance of keeping each car in working condition increases. To increase the accuracy of the prevention of gradual and sudden-gradual failures, a forecasting method based on the diagnosis of trucks with a specialized diagnostic car scanner TEXA Navigator MULTIHUB is proposed. The selection of diagnostic parameters was carried out in accordance with the requirements for compliance with the accuracy, efficiency, and informativeness of the diagnostic parameters. The research was carried out on MAN TG-X, MAN TGA, VOLVO FH 12, DAF 105 XF, and DAF 106 cars. A sequential cylinder shutdown test was conducted to determine the compression and efficiency of all cylinders. A gradual change in the operating parameter is determined based on the obtained decrease in revolutions. In the next test, the correction of the injectors for the amount of fuel injected into the cylinders is checked. The reference value is taken as 0. The correction tolerance for increasing or decreasing the fuel supply time should be within +1 or –1. Based on the received data, the nozzle is determined, in the correction gradually increases, which signals a problem with the nozzle's operation. For the clutch, a test of the position of the start of switching on and off was carried out. By reducing the percentage of idling, you can determine the gradual engagement of the clutch. All the conducted tests make it possible to graphically display a change in a parameter or property and, using extrapolation, to predict the moment of failure. All cars carry out freight transportation in international traffic. Control parameters and data extrapolation made it possible to predict engine, clutch, and automatic transmission failures. Selected diagnostic parameters can be used to predict and prevent failures.

A Review of Training Procedures for Simulated Engine Failure after Take-Off Exercises with Twin-Engine Aircraft under 5700 kg

Engine failure after take-off (or one engine being inoperative) is an exercise conducted as part of multi-engine flight training and on-going competency checking. To prepare pilots to manage a real in-flight emergency, this exercise has traditionally been conducted immediately after take-off. This has led to increased risks of fatal accidents due to the reduced height at which these exercises are typically conducted. Yet, there is variation in the heights stipulated in training procedures published by different stakeholders worldwide. Additionally, the conduct of the exercise has resulted in fatal accidents worldwide. This paper aims to review the previous literature on aviation training and aviation occurrence data to determine what empirical data exists to support the method of conducting simulated engine failures. Peer-reviewed academic publications on aviation training, aviation occurrence databases such as aviation investigation reports, and guidance materials published by aviation authorities on simulated training exercises will be included in this paper. It was found that the previous research on these exercises has focused on the transfer of motion cues or pilot responses to abnormal situations, but did not include specific data comparing pilot performance at different heights above ground level. A review of aviation occurrences found that actual engine failures occurred at higher heights that those used in simulated engine failures. A comparison of the guidance published by aviation authorities identified variations in the minimum altitude published and differing justifications for the minimum height chosen. Future research is needed to compare pilot performance during simulated engine failures to determine the ideal height to conduct the exercise to be representative of an actual engine failure while maintaining safety margins.

Volcanic jets to commercial jets: synopsis and diagnosis

Aircraft encounters with volcanic ash have caused significant damage over the past 40 years, resulting in particular attention being given to the issue. We analyzed the volcanic ash-aircraft encounter database published by the USGS. We added new volcanic eruptions and parameters such as eruption types, and dry–wet. Then, we applied standard and advanced statistical methods.Over 130 encounters have been documented in the mentioned database, with volcanic ash causing severe abrasions to the windshield, airframe, wings, and engine components. In nine cases, aircraft engines failed. We applied the binary regression analysis and some laboratory melting experiments on volcanic ash. Besides phreatomagmatism, we use the term external water in this work to describe meteoric water that enters volcanic plumes through precipitation or melting ice on ice-capped volcanoes. We demonstrated that engine failure occurs when our regression analyses undergo dry-to-wet conditions. In other words, statistically, there is a positive correlation between wet ash encounters with aircraft and engine failure incidents. Moreover, experiments conducted at 900 °C and under 40 bar pressure showed increased sintering in the dry sample, while melting textures were more prevalent in hydrated samples. We concluded that despite the various eruptive dynamics of volcanic ash, the introduction of external water into the volcanic plumes, probably causing instantaneous hydration of volcanic ash, is a common factor in engine failure incidents. Thus, we have identified the reasons behind engine failures during encounters between aircraft and volcanic ash and the specific damage that can occur depending on the type of eruption involved.