Engine Failure Research Articles

Fault-tolerant control of nonlinear cluster system for fixed-wing UAV piston engine faults based on hierarchical architecture

Due to the information exchange between fixed-wing UAV clusters, the fault and disturbance information generated when the actuator, including the engine, is transmitted from the faulty UAVs to the healthy UAVs. Given this situation, this paper proposes a cluster fault-tolerant control strategy based on hierarchical architecture. Firstly, this paper analyzes the influence of vibration caused by engine failure on fixed-wing UAVs and illustrates the necessity of considering this factor with simulation experiments. Secondly, this paper designs a hierarchical architecture, which divides the distributed control of the fixed-wing cluster system into consistency control of the upper layer and fault-tolerant tracking control of the lower layer, so that the fault information will only exist in the faulty UAVs, ensuring that the healthy UAVs will not be affected, thus avoiding the occurrence of fault propagation and improving the overall fault tolerance of the cluster. Finally, by analyzing the stability of the Lyapunov function, it is shown that this method can still follow the leader in systems with the followers' failures, and the effectiveness of this method is verified by comparing simulation results.

Investigating Post-fire Critical Area of ship base on Numerical Fire Simulation

Abstract Ship fires are recognized as significant maritime incidents that can lead to substantial losses, including loss of life. In events where fires severely compromise a vessel’s structural integrity, the costs associated with comprehensive repairs can be exorbitant, placing considerable pressure on shipowners. Ensuring post-fire structural integrity is paramount. Therefore, it is essential to provide technical considerations that aid shipowners and classification societies in identifying critical areas of a ship’s structure that require replacement. This study aims to investigate the post-fire critical areas of ship structures through numerical fire simulations. By leveraging the properties of steel, which can undergo microstructural changes when subjected to high temperatures and rapid cooling, critical structural areas can be identified based on fire-induced heat exposure. A specific case study involving a fire incident aboard a 7,500 GT bulk carrier, triggered by the failure of an auxiliary engine, is examined. The simulations utilize on-site data and actual post-fire conditions to draw robust conclusions. The insights derived from this research are expected to enhance the understanding of the impacts of fire on ship construction and facilitate more efficient and accurate post-fire inspections.

Recognition and location of rotor–stator rub-impact failure of aircraft engine with periodicity feature of vibration signals

To precisely recognize and locate a rub-impact fault of aircraft engine, an approach combining Hilbert envelope (HE), adaptive motion window (AMW), and margin factor (MF) (HE-AMW-MF) was presented. HE can reflect the change rule and tendency of vibration signals and simplify the complexity of calculation of fault diagnosis. Therefore, the paper starts with the calculation of HE of signal and takes it in place of original signal for subsequent analysis. As vibration signal caused by rub-impact fault is often accompanied by periodic impact, the paper takes advantage of the characteristic of periodic impact (collision period instead of rotation period) to adaptively determine a length and step size of motion window and exactly distills the rub-impact fault characteristics of each period. Due to the sensitivity of margin factor (MF) to the trait of wearing and impact, it is brought in to represent the fault feature information contained in signal in each motion window. Equally, mean value of all MFs is calculated and built into feature vector to reduce an interference of noise. Finally, the feature vector is combined with classification algorithms (k-nearest neighbor, KNN; support vector machine, SVM; convolutional neural network, CNN) to recognize a rub-impact fault and its location. After comparative analysis with typical method, the result indicates that the proposed HE-AMW-MF method can identify and locate the rub-impact fault more precisely, and the precision is 32.0% and 36.2%, 22.5% higher than typical comparison method.

Perspectives on Recent Developments and Directions in Tissue Engineering and Regenerative Medicine.

This perspective article draws on lessons learned at the 7th TERMIS World Congress held in Seattle, Washington in June 2024. This gathering of prominent researchers and translational scientists in tissue engineering and regenerative medicine (TERM) from around the world provided a forum to consider the impact of tissue engineering and its future directions. New frontiers are considered in the context of global challenges, including clinical translation and recent advances in pediatric tissue engineering, supercritical fluid technology for scaffold fabrication and sterilization, and learning from successful failures in tissue engineering and regenerative medicine. Bench-to-bedside translational strategies, inclusive research strategies, regulatory hurdles, and ethics linked to navigating responsibilities and innovations, are identified as important drivers in the field.

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.

Modernizando o PAEO - Modernização do Programa de Análise Espectrométrica de Óleo

The article discusses the importance of the Spectrometric Oil Analysis Program (PAEO) in preventing failures in aircraft engines. The PAEO analyzes metallic particles in lubricating oil to identify wear and potential defects. Despite its success, the program faces challenges such as sample transit time and the need for modernization of analysis methods. Suggestions include the informatization of the process and decentralization of laboratories, which could increase efficiency and reduce response time. The adoption of new technologies is crucial to ensure safety in aviation, especially in a context of increasing complexity of aerial means.

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.

Study on Dynamic Strength Characteristics of Sand Solidified by Enzyme-Induced Calcium Carbonate Precipitation (EICP).

Saturated sand foundations are susceptible to liquefaction under dynamic loads. This can result in roadbed subsidence, flotation of underground structures, and other engineering failures. Compared with the traditional foundation reinforcement technology, enzyme-induced calcium carbonate precipitation technology (EICP) is a green environmental protection reinforcement technology. The EICP technology can use enzymes to induce calcium carbonate to cement soil particles and fill soil pores, thus effectively improving soil strength and inhibiting sand liquefaction damage. The study takes EICP-solidified standard sand as the research object and, through the dynamic triaxial test, analyzes the influence of different confining pressure (σ3) cementation times (CT), cyclic stress ratio (CSR), dry density (ρd), and vibration frequency (f) on dynamic strength characteristics. Then, a modified dynamic strength model of EICP-solidified standard sand was established. The results show that, under the same confining pressure, the required vibration number for failure decreases with the increase in dynamic strength, and the dynamic strength increases with the rise in dry density. At the same number of cyclic vibrations, the greater the confining pressure and cementation times, the greater the dynamic strength. When the cementation times are constant, the dynamic strength of EICP-solidified sand decreases with the increase in the vibration number. When cementation times are 6, the dynamic strength of the specimens with CSR of 0.35 is 25.9% and 32.4% higher than those with CSR of 0.25 and 0.30, respectively. The predicted results show that the model can predict the measured values well, which fully verifies the applicability of the model. The research results can provide a reference for liquefaction prevention in sand foundations.

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.