Search Results (62)

As the core component of electrified railway power supply systems, the fatigue performance and reliability of catenary support structures are directly related to the operational safety of high-speed railways. To address the problem of structural fatigue damage caused by increasing train speed and high-frequency operation, this study develops a refined finite element model including a support structure, suspension system and support column, and the dynamic response characteristics and fatigue life evolution law under train operation conditions are systematically analyzed. The results show that under the conditions of 250 km/h speed and 100 times daily traffic, the fatigue lives of the limit locator and positioning support are 43.56 years and 34.48 years, respectively, whereas the transverse cantilever connection and inclined cantilever have infinite life characteristics. When the train speed increases to 400 km/h, the annual fatigue damage of the positioning bearing increases from 0.029 to 0.065, and the service life is shortened by 55.7% to 15.27 years, which proves that high-speed working conditions significantly aggravate the deterioration of fatigue in the structure. The reliability analysis based on Monte Carlo simulation reveals that when the speed is 400 km/h and the daily traffic is 130 times, the structural reliability shows an exponential declining trend with increasing service life. If the daily traffic frequency exceeds 130, the 15-year reliability decreases to 92.5%, the 20-year reliability suddenly decreases to 82.4%, and there is a significant inflection point of failure in the 15–20 years of service. Considering the coupling effect of environmental factors (wind load, temperature and freezing), the actual failure risk may be higher than the theoretical value. On the basis of these findings, engineering suggestions are proposed: for high-speed lines with a daily traffic frequency of more than 130 times, shortening the overhaul cycle of the catenary support structure to 7–10 years and strengthening the periodic inspection and maintenance of positioning support and limit locators are recommended. The research results provide a theoretical basis for the safety assessment and maintenance decision making of high-speed railway catenary systems. Full article

In order to study the generation, management, and disposal status of waste mineral oil in China’s railway transport industry, this article takes the Beijing Railway Bureau and its subordinate Tangshan Locomotive Depot as the research objects and comprehensively applies the survey, case study, and statistical analysis methods to analyze the source of the generation of railway waste mineral oil, the distribution of the disposal enterprises and locomotive depots, the management mode, and the economic and environmental benefits of recycling waste engine oil. The results show that waste oil mainly originates from locomotive overhaul and maintenance. There is significant regional imbalance in the generation and disposal capacity of railway waste oil. The Beijing Railway Bureau can achieve the timely disposal of waste mineral oil and reduce transport risks. Waste mineral oil management integrates generation, storage, transfer, and disposal. If cooperation is initiated with waste oil disposal enterprises, the use of recycled oil can save up to RMB 178,600/year and reduce carbon emission by 76.42 tCO₂/year for this locomotive depot. In view of the current situation, the railway industry should improve the management and disposal deficiencies and explore the new model of waste oil reduction, reuse, and recycling. Full article

To extend the time between the overhauls of helicopters, a novel collaborative methodology that takes into account uncertain misalignment errors by considering the shape and performance of the gear is built. Firstly, the digital characteristics of contact patterns, such as the reference point and direction angle, are extracted. Secondly, an optimization model calculates the equivalent misalignment by minimizing deviations in the reference point and direction angle between two contact patterns. This equivalent misalignment accounts for uncertainty misalignment errors introduced by complex gear support deformation. Thirdly, the ease-off is utilized to derive the pinion target surface that can sustain meshing performance under an equivalent misalignment, similar to the original gear in real conditions. This way it integrates with the optimization theory for flank reconstruction to redesign the pinion surface. Simulations reveal that the critical digital characteristics of the contact path on the original gear under the equivalent misalignment mirror those of the original gear in real conditions. Moreover, the surface parameters of the redesigned pinion result in an identical surface under a different equivalent misalignment, maintaining similar contact and dynamic performance. This proposed collaborative design approach, considering the shape and performance while accounting for uncertain misalignment errors through ease-off, greatly improves the gear transmission behavior. Full article

Evolutionary processes involving sustainability are here expressed in units of classical mechanics, where newly evolved traits are distance, segments of evolutionary trees are time, and species as entire character sets are mass. Data arranged on a morphological evolutionary tree (caulogram) allow precise calculations of evolutionary velocity, acceleration, momentum and force, with force interpretable as resistance to environmental change. Stem-taxon trees of species of the moss family Streptotrichaceae and Pottiaceae tribe Pleuroweisieae were developed as sets of minimally monophyletic genera, and annotated with numbers of newly evolved traits per species. Calculations provided evidence that precise and comparative measures of the results of sustainable evolutionary processes may be calculated, and, as directly derived from expressed traits, are also accurate and informative about processes leading to resilience across multiple extinction events. The two groups evidenced similar, gradual evolutionary rates, implying that similar evolutionary processes occur across 110 my for Streptotrichaceae and 66 my for Pleuroweisieae, although habitats differ. Extension of sets of new traits per species into the past imply origination of the oldest extinct recognizable progenitors near the Permian–Triassic extinction event, when a cut-off in all data imply a complete over-haul of the character set for both groups, i.e., a major change in evolutionary mass. Speciation occurs in bursts. Extinction is gradual, the negative of acceleration. The rates of origination of genera over time for both groups are nearly the same as those previously proposed for genera of extinct horses. Plateaus in graphs of species per genus imply ancient quadratic patterns of speciation. The combination of process-governed stability through stasis of morphological traits, and of resilience as the ability to survive multiple extinction events has apparently little changed, and both contribute to sustainability over geologic time. Full article

A predictive health modeling framework was developed for a family of turbofan engines, focusing on early detection of performance degradation. Turbine Gas Temperature (TGT) was employed as the primary indicator of engine health within the model, due to its strong correlation with core engine performance and thermal stress. The present research uses engine health monitoring (EHM) data acquired from in-service turbofan family engines. TGT is typically measured downstream of the high-pressure turbine stage and is regarded as the key thermodynamic variable of the gas turbine cycle. Three new training approaches were proposed using data segmentation based on time between major overhauls and compared with the conventional train–test split method. Detrending was employed to effectively remove trends and seasonality, enabling the ML-based model to learn more intrinsic relationships. Large generalized models based on the entire engine family were also investigated. Prediction performance was evaluated using selected machine learning (ML) models, including both linear and nonlinear algorithms, as well as a long short-term memory (LSTM) approach. The models were compared based on accuracy and other relevant performance metrics. The prediction accuracies of ML models depend on the selection of data size and segmentation for training and testing. For individual engines, the proposed training approaches predicted TGT with the accuracy of 4 ^∘C to 6 ^∘C in root mean square error (RMSE) by utilizing 65% less data than the train (80%)–test (20%) split method. Utilizing the data of each family engine, the large generalized model achieved similar prediction accuracy in RMSE with a smaller interquartile range. However, the amount of data required was 45–300 times larger than the proposed approaches. The sensitivity of prediction accuracy to the size of the training dataset offers valuable insights into the framework’s applicability, even for engines with limited data availability. Uncertainty quantification showed a coverage width criterion (CWC) between 29 ^∘C and 40 ^∘C, varying with different family engines. Full article

In order to accurately grasp the operational state of DC protection devices in converter stations, a DC protection device state assessment method based on the variable weight theory and correlation degree analysis is proposed. Constructing condition assessment indicators for DC protection device of converter stations containing overhaul in-formation, operation information and defect information, when the actual value of the indicator exceeds the specified range of values, the DC protection device is directly judged to be in ‘alarm’ status; when the actual value of the indicator is within the specified range of values, Analytic Hierarchy Process (AHP) and variable weight theory are combined to adjust variable weights of assessment indicators in real time. At the same time, the correlation between the indicators and each state level is calculated, and the correlation of the indicators and their corresponding weights are weighted and summed to obtain the comprehensive correlation of each state level of the DC protection device, and the correlation of each state level of the DC protection device is calculated, using the principle of maximum correlation, the DC protection device status is obtained. Example analyses show that the method is simple and easy to implement and can accurately assess the operational state of the DC protection device in converter stations. Full article

This article continues the authors’ research on NOMEX^® 910 cellulose–aramid insulation saturated with modern electrical insulating liquids, which is increasingly used in the construction of high-power transformers The increase in technical requirements and environmental awareness influences, nowadays, shows that, during the overhaul and modernization of power transformers, petroleum-based mineral oils are increasingly being replaced by biodegradable synthetic esters (oil retrofilling). As a result of this process, the solid insulation of the windings are saturated with an oil–ester liquid mixture with a percentage composition that is difficult to predict. The purpose of the research described in this paper was to test the effect of the degree of mixing of synthetic ester with mineral oil on the diagnostic measurements of NOMEX^® 910 cellulose–aramid insulation realized via the polarization PDC method. Thus, the research conducted included determining the influence of such factors as the degree of mixing of synthetic ester with mineral oil and the measurement temperature on the value of the recorded time courses of the polarization and depolarization current. The final stage of the research involved analyzing the extent to which the aforementioned factors affect parameters characterizing polarization processes in the dielectric, i.e., the dominant dielectric relaxation time constants τ₁ and τ₂, and the activation energy E_A. The test and analysis results described in the paper will allow better interpretation of the results of diagnostic tests of transformers with solid insulation built on NOMEX^® 910 paper, in which mineral oil was replaced with synthetic ester as a result of the upgrade. Full article

Background: An effective risk assessment and management methodology is essential to minimize/mitigate health risks associated with firefighting activities. The use of a self-contained breathing apparatus (SCBA) is mandatory during structure fires to protect firefighters from hazardous fire effluents, yet the protectiveness of the SCBA system has rarely been evaluated. Objective: This study characterizes, for the first time, the levels of 18 polycyclic aromatic hydrocarbons (PAHs) inside the SCBA facemask, during 7 structure-firefighting exercises and estimates associated respiratory risks. Methods: Cotton disk samples were collected via passive air sampling and analyzed using liquid chromatography with fluorescence and UV–Vis detection. Results: Levels of total PAHs (∑PAHs: 9.17–29.6 ng/m³) and ∑PAHs_carcinogenic (0.41–5.73 ng/m³) were below the occupational limits defined by governmental agencies. The low-molecular-weight PAHs were predominant (79.5–91.4%), and the (possible/known) carcinogenic naphthalene (0.26–2.00 ng/m³), anthracene (0.088–0.31 ng/m³), chrysene (0.046–0.39 ng/m³), benzo(b+j)fluoranthene (0.18–0.40 ng/m³), and benzo(a)pyrene (0.041–0.18 ng/m³) were detected in all samples. The respiratory health risk analysis demonstrated negligible risks associated with the inhalation of PAHs. A health principal component analysis could identify firefighters at increased respiratory risk. Conclusions: The effectiveness of SCBA was demonstrated, reinforcing the need to ensure its correct use during all the phases of structure fires, including during overhaul. Full article

This paper introduces a token-based digital currency (TBDC) model for standardizing service delivery in an aviation technical support as a service (ATSaaS) platform. The model addresses the challenges of service standardization and valuation by integrating cost, time, and quality parameters into a unified framework. Unlike traditional cryptocurrencies, this specialized digital currency incorporates intrinsic service valuation mechanisms that dynamically reflect the worth of aviation technical support services. The research presents a mathematical formulation for token value calculation, including a Service Passport framework for comprehensive documentation and a systematic approach for service integration. The model is validated through a numerical case study focusing on maintenance, repair, and overhaul services, demonstrating its effectiveness in generating fair token values across diverse service types. The study introduces optimization techniques using machine learning to enhance token calculations, successfully standardizing heterogeneous services while maintaining flexibility and transparency. Implementation challenges and future developments are identified. The TBDC model provides a foundation for transforming aviation technical support services, particularly benefiting small airlines through improved efficiency, standardization, and accessibility. Full article

In the current study, the authors have listed the causes of common failures in hydro turbine blades. In the following, coatings, as one of the practical solutions that can be utilized in the hydropower industry, were selected for further investigation. In this regard, nanocoating technology is used to prevent the above-mentioned failures, as well as to extend the service lifetime of turbine blades, to increase the inspection time, i.e., the overhaul intervals, and to reduce repair costs. Therefore, firstly, the raw materials of runner blades in different types of turbines were checked. The collected data revealed that this equipment is usually made of stainless steel (i.e., 304 and 316L). Therefore, the main focus of the current research was a general investigation of the effects of different nanocoatings on the material properties, including the wear, corrosion, and erosion, of 304 and 316L steels. Finally, a coating process used in this industry that is suitable for overhaul rather than initial construction was investigated. The advantages of using nanocoatings compared to traditional coatings in this industry were enumerated. In addition, the effects of single-layer and multi-layer coatings with different compositions on the corrosion, wear, and erosion properties of each of these stainless steels were discussed. Eventually, considering the gaps in past research and summarizing the collected results, a future research direction was proposed, including different combinations of materials to create new nanocoatings (with different percentages of nano alumina and titanium carbide). Full article

Brake testing of vehicles is one of the most important tests performed in technical–mechanical overhaul workshops (TMOWs). During this test, fine and ultrafine particles are emitted, exposing workers to health risks. A mixed descriptive observational study was conducted in 10 TMOWs in Armenia (Colombia), where particle sampling was performed using the NIOSH 0600 method. One third of the samples were sent for SEM analysis to determine their chemical composition and particle size. The average occupational exposure was 24.31 mg/m³, almost 10 times higher than the threshold limit value for ultrafine particles. The range of particle sizes was from 1.12 to 54.33 µm, with an arithmetic mean of 14.89 µm. The ultrafine size ranged from 198 nm to 798 nm. Traces of components of refractory materials, fiberglass, wollastonite, and thermoplastics, among others, typical of brake pads, were found. This research allows us to confirm the presence of fine and ultrafine particles in TMOW brake tests. Therefore, we recommend improvement actions based on epidemiological surveillance programs of the respiratory health of workers. Full article

The aviation industry faces considerable challenges in maintenance management due to the complexities of data standardization, data sharing, and predictive maintenance capabilities. This paper introduces a unified ecosystem for data sharing and AI-driven predictive maintenance designed to address these challenges by integrating real-time and historical data from diverse sources, including aircraft sensors, maintenance logs, and operational records. The proposed ecosystem enables predictive analytics and anomaly detection, enhancing decision-making processes for airlines, maintenance, repair, and overhaul providers, and regulatory bodies. Key elements of the ecosystem include a modular design with feedback loops, scalable AI models for predictive maintenance, and robust data-sharing frameworks. This paper outlines the architecture of a unified aviation maintenance ecosystem built around multiple data sources, including aircraft sensors, maintenance logs, flight data, weather data, and manufacturer specifications. By integrating various components and stakeholders, the system achieves its full potential through several key use cases: monitoring aircraft component health, predicting component failures, receiving maintenance alerts, performing preventive maintenance, and generating compliance reports. Each use case is described in detail and supported by illustrative dataflow diagrams. The findings underscore the transformative impact of such an ecosystem on aviation maintenance practices, marking a significant step toward safer, more efficient, and sustainable aviation operations. Full article

The study site, a major teaching hospital in Dublin, Ireland, addressed significant challenges within its dermatology service through a comprehensive improvement initiative using a person-centred Lean Six Sigma methodology. Initially, the hospital’s dermatology department faced excessive outpatient waiting times, with 3736 patients awaiting appointments, and 1615 waiting over 12 months. The person-centred Lean Six Sigma approach, which combines Lean techniques to reduce non-value add and Six Sigma methods to eliminate variation through a person-centred lens, was applied to overhaul the referral, triage, and scheduling processes. Key interventions included standardising triage categories, centralising the triage process, and redistributing referrals equitably among consultants. A new centralised triage system was established, leading to a more efficient allocation of appointments and better management of urgent cases. Post-implementation data showed a 40% reduction in the overall waiting list and a 60% reduction in the number of patients waiting over 12 months. The initiative significantly decreased the wait times across all urgency categories, with the most notable improvements in soon and urgent referrals. These changes were also the impetus for a follow-up design-led innovation phase, where the team worked with partners across the educational and healthcare system to enable disruptive change. The success of this project provides a scalable model for improvements in similar healthcare settings. Full article

Utilizing spent refractory material (SRM), generated after the overhaul of aluminum electrolytic cells, as a raw material for producing Al-Si alloys presents an efficient approach towards achieving full resource utilization of SRM. However, a bottleneck restricting this technology has become the dissolution of SRM. Based on the heat and mass transfer mechanism, the shrinkage core model of SRM particle dissolution was established. The effects of alumina concentration, silica concentration, electrolyte superheat, particle temperature, and turbulent kinetic energy dissipation rate on the mass dissolution rate and dissolution time of SRM particles were investigated. Calculation results and experimental data were compared to confirm the accuracy of the established model. The results show that by maintaining low alumina and silica concentrations, increasing the electrolyte superheat and particle preheating temperature, and increasing the electrolyte turbulent kinetic energy dissipation rate, SRM particles can dissolve faster. The dissolution of agglomerated particles is greatly influenced by the turbulent kinetic energy dissipation rate and superheat. The present research provides promising guidance for practical application in predicting particle dissolution time, controlling process parameters, and accelerating the dissolution of SRM particles. Full article

In the present study, the feasibility to achieve localized induction heating and debonding of multi-material composite structures is assessed in testing coupons prepared by Automated Fiber Placement (AFP) and extrusion-based additive manufacturing (AM) technologies. Nano-compounds of Polyether-ketone-ketone (PEKK) with iron oxide nanoparticles acting as electromagnetic susceptors have been processed in a parallel co-rotating twin-screw extruder to produce filament feedstock for extrusion-based AM. The integration of nanocomposite interlayers as discrete debonding zones (DZ) by AFP-AM manufacturing has been investigated for two types of sandwich-structured laminate composites, i.e., laminate-DZ-laminate panels (Type I) and laminate-DZ-AM gyroid structures (Type II). Specimens were exposed to an alternating magnetic field generated by a radio frequency generator and a flat spiral copper induction coil, and induction heating parameters (frequency, power, heating time, sample standoff distance from coil) have been investigated in correlation with real-time thermal imaging to define the debonding process window without compromising laminate quality. For the optimized process parameters, i.e., 2–3 kW generator power and 20–25 mm standoff distance, corresponding to magnetic field intensities in the range of 3–5 kA m⁻¹, specimens were effectively heated above PEKK melting temperature, exhibiting high heating rates within the range of 5.3–9.4 °C/s (Type I) and 8.0–17.5 °C/s (Type II). The results demonstrated that localized induction heating successfully facilitated debonding, leading to full unzipping of the debonding zones in both laminate structures. Further insight on PEKK nanocomposites debonding performance was provided by thermal, morphological characterization and non-destructive inspection via X-ray micro-computed tomography at different processing stages. The developed framework aims to contribute to the development of rapid, on-demand joining, repair and disassembly technologies for thermoplastic composites, towards more efficient maintenance, repair and overhaul operations in the aviation sector and beyond. Full article