In-service Operation Research Articles

An Engine Deterioration Model for Predicting Fuel Consumption Impact in a Regional Aircraft

A deterioration cycle model is presented, designed to consider the turbomachinery efficiency losses that are expected during real engine in-service operations. The cycle model was developed using information from practical experience found in the literature to account for both short- and long-term deterioration effects; the former occurring during the first flight cycles, the latter due to regular in-service operation. This paper highlights the importance of analyzing the inter-turbine temperature margin (ITTM) to track engine deterioration to determine the extent of an in-service engine life. The proposed model was used to assess the ITTM and fuel consumption impact in the CRJ-700 regional aircraft (powered by two CF34-8C5B1 engines) for three representative missions: short (0.4 h), average (1.4 h), and long (2.5 h), considering different levels of engine deterioration, from the new engine level up to fully deteriorated. The fuel consumption at the new engine level (zero deterioration) was validated against a real-time engine model embedded in a Level-D flight simulator, the so-called Virtual Research Flight Simulator located at the Laboratory of Applied Research in Active Control, Avionics, and AeroServoElasticity. The errors found in this validation for the trip mission fuel consumption in the short, average, and long missions were −3.6, +0.9, and +0.6%, respectively. The cycle model predictions suggest the ITTM for a new engine is 55.2 °C, whereas for a fully deteriorated engine, it is 26.4 °C. Finally, in terms of fuel consumption, the results presented here show that an average CF34-8C5B1 engine shows an increase in the cumulative fuel consumption of 2.25% during its life in service, which translates to a 4.5% impact in aircraft fuel consumption.

Code-Mixing As a Communicative Strategy Among International Passengers and Employees in Hasanuddin International Airport Makassar

The use of English in service operations is very necessary in communicating with service users who not only come from Indonesia but also from abroad. Therefore, the use of English is very important in-service operations at the airport. This research aims to analyze code mixing as a communication strategy among passengers and employees at Hasanuddin International Airport. The design of this research was qualitative research. It is called collaborative qualitative because the research directly involves employees and international passengers as respondents. The research results show that there are three types of code mixing, namely alternation, congruence, and lexicalization. Respondents participated in interviews, which yielded information about the variables that influence the use of code mixing in textual communication regarding code mixing as a communication strategy between employees and international passengers. There are seven factors that cause code mixing, namely (1) lack of mastery, especially mastery of English, (2) intention to increase prestige, (3) wanting to show off one's skills, (4) searching for identity, (5) habits, (6) want to joke (make jokes) and (7) relaxed conversation situation (formality). It can be concluded that this research identifies three forms of code mixing, namely substitution, congruence and lexicalization and this is influenced by several factors in the occurrence of code mixing among employees and international passengers

High Temperature Oxidation of Zircaloy-4 Under Conditions Simulating a Loss of Cooling Accident in Spent Fuel Pools Examined with Raman Imaging and 18o Tracer Techniques

Since the Fukushima accident, an increased attention is continuously paid to the vulnerability of the Spent Fuel Pools (SFPs). In SFPs, for different reasons, degradation of the fuel rods induced by oxidation in air-steam mixtures after dewatering is a major safety concern: (i) the cladding material is the only barrier left against fission product dissemination, (ii) the heat released by the oxidation reactions can overcome the residual decay heat of the fuel and may become the main driving force to the accident escalation, (iii) hydrogen production is a strong concern because of the presence of steam, (iv) presence of air in the atmosphere is known to be an aggravating factor because of the “catalytic” role of nitrogen on the oxidation mechanism.In this study, high temperature oxidation tests in oxygen, air and air - steam atmospheres were performed with Zircaloy-4 cladding tubes and plates specimens. Because spent fuels are concerned, the presence of the corrosion oxide scale formed in reactor during in-service operation was also considered. The tests described in this study were restricted to the 700 – 950°C range, and mostly performed at 850°C. Raman imaging was used to examine the specimens after the oxidation tests, either directly at the oxide surface, or on metallographic preparations for cross-section examinations.We first used new opportunities given by Raman imaging to analyze, at least qualitatively, the structural and mechanical phenomena involved in this particular corrosion phenomena. Indeed, this method can provide information on the nature of phases that are present in the scale and on the stress level with sub-micron spatial resolution. The different methods used to extract this information that is present in the Raman data will be described and discussed.Moreover, isotopic substitution was also considered. Actually, Raman spectroscopy has also the ability to quantitatively extract the 18O distribution in a zirconia oxide scale after a two stage experiment with a fair accuracy. Raman imaging gave clear evidence for different characteristic distributions of 18O in the scales. Some of them have been correlated with the development of cracks and porosity in the oxide which allows the corroding medium to penetrate locally in the scales. Nitrogen appears to have no or limited influence on the oxygen diffusion, but is observed to reach the metal/oxide interface much faster than oxygen. Thus, we also emphasize the potential of this method to investigate the 18O distribution in such complex corrosion scales.

Real-time deformation and stress response of the planar SOFC during sintering

The thermal-mechanical response of the anode-supported planar solid oxide fuel cell (SOFC) during sintering is important for its manufacturing and in-service operation. The integrated micro/nano-indentation and finite element (FE) modeling method was used to characterize the Young’s modulus, yield stress and creeping for the NiO-3YSZ anode and 8YSZ electrolyte at room temperature. Based on the real-time full-field deformation of the half-cell SOFC which was measured using the 3D digital image correlation (DIC), the FE simulation was used to estimate the stress response in a manner of sensitivity study. It shows that the half-cell SOFC warps towards the anode substrate during heating and points in the opposite direction during cooling. The warping deformation of FE simulation matches well with the DIC measurement. In addition, the maximum tensile stress in the electrolyte coat of the half-cell SOFC plate is about 207 MPa if assuming temperature-independence of creeping for the SOFC materials.

Comprehensive damage and deformation mechanisms during out-of-phase thermal mechanical fatigue of the fourth-generation single crystal superalloy

To shed light on the stability and reliability of the fourth-generation single crystal (SX) superalloy during in-service operation, out-of-phase (OP)- thermal mechanical fatigue (TMF) experiments were systematically carried out. The TMF behavior, deformation and damage mechanisms were thoroughly investigated. The results showed that at comparatively low strain ranges (0.5% and 0.6%), the dislocation movements were basically concentrated in γ matrix and the TMF life was basically governed by high-temperature oxidation. More locally, the fatigue cracks initiated from the spalling of surface oxides, while the discontinuous Al2O3 layer could only provide limited protective resistance to crack propagation. Additionally, deformation twins could nucleate in the vicinity of micropores or crack tips, which further induced more complex defects and accelerated the fatigue fracture of the alloy. Nevertheless, as the strain range reached 0.8% and 0.9%, the nucleation and extension of micro-twins were independent on the defects, the mechanisms of twinning-shearing and anti-phase boundary (APB)-shearing were observed throughout the specimen. Under these conditions, the fatigue cracks basically initiated from the severe plastic deformation, which resulted in the much-reduced TMF life of the specimen. Ultimately, salutary guidance for the further application of fourth-generation SX superalloys was rationally summarized.

Real-Time Malfunction Detection of Maglev Suspension Controllers

This study aims to develop a track-side online monitoring system for malfunction detection in the suspension controllers of maglev trains during their in-service operation. The hardware module of the system includes two arrays of accelerometers deployed on an F-type rail and a data acquisition unit. The software module of the system consists of codes for three functions: (i) the identification of time intervals in relation to the passage of each suspension controller via synchrosqueezing transform; (ii) the extraction of a feature index (FI) sequence synthesized by modulating the response amplitude, frequency, and running speed; and (iii) the formulation of a Bayesian dynamic linear model for real-time malfunction detection in maglev suspension controllers. For verification of the proposed monitoring system and malfunction detection algorithm, full-scale tests have been conducted on an maglev test line using the devised system, where a maglev train was run at different speeds with malfunction occurring in the suspension controllers. The malfunction detection results of the proposed approach are exemplified via comparison with the recorded suspension gaps after the trial run of the maglev train. The fidelity of the results obtained using the extracted FI sequence and using the raw monitoring data are compared. The superiority of the proposed malfunction detection algorithm is also discussed via comparison with the results of the different train speeds.

Standards relevant to automated driving system safety: A systematic assessment

Automated Driving Systems (ADSs) in road vehicles, which can undertake the dynamic driving task without requiring a human driver, are on the verge of large-scale deployment. Assurance frameworks for vehicle systems have traditionally been underpinned by standards. Some commonly adopted standards will provide barriers to the market deployment of ADSs, particularly the inherent capability of ADSs to have their driving functionality changed using Machine Learning (ML) during in-service operation. New standards specific to ADSs are being adopted, but some of these also present challenges for ML-enabled system changes. Then there are emerging cross-sector AI and ML standards that will have implications for the automotive industry and regulators.This paper summarises an in-depth assessment of standards that are anticipated to play an important role in the safety assurance of ADSs. Summarised findings are provided, including key themes, covering issues such as the use of ADS safety cases that are strengthened by adopting complementary standards, ensuring safety assurance models cover the whole ADS lifecycle, and the use of a systems engineering approach that treats safety as a dynamic control problem and appropriately integrates software engineering standards. Other themes were more specific to ML, including the need for rigorous change processes, horizonal AI and ML standards to be appropriately considered by automotive manufacturers and regulators, and authorities to be clear on whether online changes that can occur autonomously without human oversight are allowed or not. The findings, themes and recommendations in this paper are intended to inform future safety assurance frameworks for ADSs.

Method using singular value decomposition and whale optimization algorithm to quantitatively detect multiple damages in turbine blades

Renewable energy has increased in recent years with a consequential increase in equipment maintenance. Maintenance costs can be reduced by structural health monitoring techniques especially for wind turbine (WT) blade damages. However, the majority are not suitable for on-line measurements and quantitative detections. A quantitative damage detection method is developed to identify multiple damages in a WT blade under in-service operation conditions. Firstly, singular value decomposition is applied to reveal singular information in the operating deflection shape (ODS), which can be treated as damage locations. Secondly, whale optimization algorithm is utilized for a damage severity decision about the natural frequency database between damage severities and natural frequencies, which are constructed by finite element method (FEM) simulations on the detected damage locations in the WT blade. The procedure is applied to FEM numerical simulations of a single WT blade with two and three damages. By adding a certain noise to the simulation dataset, the robustness of the present method is validated. Furthermore, the laser scanning vibrometer is employed to test the ODS as well as natural frequencies of WT blades to testify the performance of the multiple damage detection method. Results show that the present method is effective for the detection of multi-damage in WT blades with a certain noise robustness.

Perspective on pulse compression favorable infrared imaging techniques for non-destructive testing and evaluation of solids

Abstract Inspection reliability of sub-surface defects is imperative for safer functionality of critical components/materials/structures used in a wide variety of applications in various industries. The need for reliable, fast, remote, safe inspection and evaluation methods for detection of hidden defects increases in parallel with the demand for more sustainable solutions which helps in inherent modifications in design and manufacturing specifications. During in-service operation, the hidden defects are typically originated from various loading conditions leading to catastrophic failure. This perspective explores the best possible reliable, fast, remote, safe, and easy to implement for field inspection and evaluation experimental method and the associated post-processing approach using InfraRed Imaging (IRI) for Thermal Non-Destructive Testing and Evaluation (TNDT&E) of Glass Fibre Reinforced Polymer (GFRP) materials having delamination defects. This perspective further explores the state-of-the-art infrared imaging modalities used in TNDT&E by highlighting their advantages and limitations in terms of the detection sensitivity and depth resolvability to detect the subsurface defects located at interior of material. Most of the proposed experimental and post-processing techniques presented in the literature for TNDT&E, explore the observed spatial thermal contrast over the defective region of sample to provide the depth resolvability from the reconstructed thermograms even though it is obtained from the temporal data processing on the captured image sequence. This perspective provides an insight on the state-of-the-art research in the field of thermal/infrared non-destructive testing and evaluation and associated post-processing approaches to visualize the hidden subsurface defects not only resolved by spatial thermal gradients but also simultaneously provide temporal thermal gradients to locate defective regions.

Toward an Operations-Dedicated Model for Space Systems

Current trends in the aerospace industry for the digitization of data, tools, and services call for novel solutions that can keep track of the latest technological advancements. Moreover, the increasing drive toward model-based approaches imposes the use of models for the development of complex systems, such as satellites. New types of methods and tools are needed in order to manage the still-growing complexity of embedded systems and their corresponding models. This paper addresses issues related to space systems (in-service) operations and proposes a multimodel approach to address them. The multimodel approach aims at facilitating the task of operational diagnosis by creating a monitoring and diagnosis-dedicated system model derived from existing system design (architecture, functional behavior, and safety) models. The purpose of the diagnosis-dedicated model is to enable the codesign of the system and its diagnosis tools in order to improve the performance of diagnosis activities and the system’s availability. This paper demonstrates the interests of the suggested approach with regard to the limitations of current practices.

Viscoplastic model-based analysis of in-service oscillation temperature and thermal stress in a rotating component

The thermal gradient in the rotor is a key influential factor in thermal stress. Steam temperature fluctuations cause temperature oscillations in the rotor, leading to variation in the thermal gradient and finally changing the rotor's thermal stress behavior. This study aimed to identify the influence of steam temperature fluctuations on the rotor's oscillation temperature and thermal stress behavior. Thus, the extent to which the rotor temperature is influenced by steam temperature fluctuations and the associated temperature change behavior in the rotor could be predicted in detail. The convective heat transfer between the steam and the rotor is characterized by the third boundary condition, and the thermal stress is described with a viscoplastic constitutive model with damage. Realistic in-service operating data during startup and steady-state operation phases were chosen to investigate the oscillation temperature and thermal stress induced by steam temperature fluctuation in a steam turbine rotor. With the benefits to the rotor design and power plant operation, the temperature fluctuating amplitude range was categorized into four groups by transient thermomechanical finite-element analysis, and the temperature differences in the rotor between sets of two adjacent locations are listed to demonstrate the heat congestion.

Exploration of the Challenges Facing In-service Training Operation in Public Secondary Schools in Tanzania

The study explored challenges that face operations of in-service training in public secondary schools in Mbeya district, Tanzania. Specifically it identified challenges facing the operation of in-service training and established possible strategies that are used to enhance effective implementation of in-services training. Methodologically, the study was guided by pragmatism paradigm that employed mixed research approach and convergent parallel research design. The data to respond this study were collected through questionnaire and interview methods. A total of 110 respondents were involved in this study as sample size. Descriptive and thematic analysis was used to analyse data from questionnaire and interview. The study findings revealed that in-service training were offered with intention of enhancing their professional competence and development, however, the operation of in-service training programme are continuous facing several challenges including poor planning of training programmes, lack of clear follow-up strategies and insufficient funding of programmes. Moreover, it was identified various strategies that could enhance effective implementation of teachers’ in-service which were allocating enough budget, providing enough time for in-service training and formulation of good education policies for the operation of in-service training in public secondary schools. The study concludes that in-service training is among the good programme for improving competencies of teachers however, it has been facing with varying challenges. Finally, the study recommends to the government, stakeholders and school administrators of public secondary school to pull up together and provide directly and indirectly adequate resources to enhance operation of in-service training by mitigating those unveiled challenges.

Electrochemical Impedance Analysis for Corrosion Rate Monitoring of Sol-Gel Protective Coatings in Contact with Nitrate Molten Salts for CSP Applications.

The protective behaviour of ZrO2-3%molY2O3 sol-gel coatings, deposited with an immersion coating technique on 9Cr-1Mo P91 steel, was evaluated with corrosion monitoring sensors using the electrochemical impedance spectroscopy technique. The tests were carried out in contact with solar salt at 500 °C for a maximum of 2000 h. The results showed the highly protective behaviour of the coating, with the corrosion process in the coated system being controlled by the diffusion of charged particles through the protective layer. The coating acts by limiting the transport of ions and slowing down the corrosive process. The system allowed a reduction in the corrosion rate of uncoated P91 steel. The estimated corrosion rate of 22.62 μm·year-1 is lower than that accepted for in-service operations. The proposed ZrO2-3%molY2O3 sol-gel coatings are an option to mitigate the corrosion processes caused by the molten salts in concentrated solar power plants.

Quantifying fuel-saving benefit of low-rolling-resistance tyres from heavy goods vehicle in-service operations

It is important to understand real-world performance of fuel-saving technologies for heavy goods vehicles (HGVs). This paper concerns applying data mining to quantify the fuel-saving benefit of a low-rolling-resistance (LRR) tyre using in-service operational data. Two HGVs of the same specification were employed, with one using LRR tyres and the other conventional tyres. A smartphone-based data logger was developed to collect data from the HGVs’ operations on publics roads for three months. Data from vehicle Controller Area Network, smartphone sensors, weather and elevation databases were collected. A data mining methodology was developed to mine data segments representing dynamically similar driving conditions between the two HGVs, and compare their fuel consumption rates through fitting data to a theoretical vehicle fuel consumption model. It was found that at a 95% confidence level the LRR tyres exclusively brought about a fuel-saving benefit between 6.89% and 8.37% in typical UK motorway driving conditions.

Safety assurance for automated driving systems that can adapt using machine learning: A qualitative interview study

Introduction: Automated Driving Systems (ADSs) present significant unresolved challenges for traditional safety assurance frameworks. These frameworks did not envisage, nor readily support, automated driving without the active involvement of a human driver, or support safety-critical systems using Machine Learning (ML) to modify their driving functionality during in-service operation. Method: An in-depth qualitative interview study was conducted as part of a broader research project on safety assurance of ADSs that can adapt using ML. The objective was to capture and analyze feedback from leading global experts, from both regulatory and industry stakeholders, with the key objectives of identifying themes that could assist with the development of a safety assurance framework for ADSs, and providing a sense of the level of support and feasibility for various safety assurance concepts relevant to ADSs. Results: Ten themes were identified from an analysis of the interview data. Several themes support a whole-of-life safety assurance approach for ADSs, with strong support for ADS developers to be required to produce a Safety Case, and for ADS operators to maintain a Safety Management Plan throughout an ADSs operational life. There was also strong support for in-service ML-enabled changes to be allowed within pre-approved system boundaries, although there were mixed views on whether human oversight of such changes should be required. Across all themes identified, there was support for progressing reform within current regulatory frameworks, without requiring wholesale changes to current frameworks. The feasibility of some themes was identified as presenting challenges, particularly with the ability for regulators to develop and maintain an appropriate level of knowledge, capability and capacity, and with the ability to effectively articulate and pre-approve boundaries within which in-service changes can occur without additional regulatory approval. Conclusions: Further research on the individual themes and findings would be beneficial to support more informed reform decisions.

Prolonged in situ self-healing in structural composites via thermo-reversible entanglement

Natural processes continuously degrade a material’s performance throughout its life cycle. An emerging class of synthetic self-healing polymers and composites possess property-retaining functions with the promise of longer lifetimes. But sustained in-service repair of structural fiber-reinforced composites remains unfulfilled due to material heterogeneity and thermodynamic barriers in commonly cross-linked polymer-matrix constituents. Overcoming these inherent challenges for mechanical self-recovery is vital to extend in-service operation and attain widespread adoption of such bioinspired structural materials. Here we transcend existing obstacles and report a fiber-composite capable of minute-scale and prolonged in situ healing — 100 cycles: an order of magnitude higher than prior studies. By 3D printing a mendable thermoplastic onto woven glass/carbon fiber reinforcement and co-laminating with electrically resistive heater interlayers, we achieve in situ thermal remending of internal delamination via dynamic bond re-association. Full fracture recovery occurs below the glass-transition temperature of the thermoset epoxy-matrix composite, thus preserving stiffness during and after repair. A discovery of chemically driven improvement in thermal remending of glass- over carbon-fiber composites is also revealed. The marked lifetime extension offered by this self-healing strategy mitigates costly maintenance, facilitates repair of difficult-to-access structures (e.g., wind-turbine blades), and reduces part replacement, thereby benefiting economy and environment.

Structural performance prediction based on the digital twin model: A battery bracket example

Battery bracket for new energy commercial vehicles is subjected to variable loads and battery temperature changes both during the design road test phase and in-service operation. Therefore, their structural performance must be evaluated in real-time for reliability design and health monitoring. With the rapid development of industrial digitization, the digital twin has become an indispensable technology. This paper proposes a digital twin approach for predictive monitoring of the performance of mechanical structures. Taking the structural performance for the battery bracket of new energy commercial vehicles as an example, this paper builds a unit-level digital twin model—DTMAR. It comprises the numerical model, NN-RSR model, and hybrid machine learning model. The results reveal that the DTMAR model can efficiently and accurately calculate and predict the structural performance. This can not only provide constructive guidance for optimal design of the next generation product structure, but also aid in evaluating the structural reliability of the battery bracket of new energy commercial vehicles and improve their driving safety.

Finite element analysis of CFRP composite under low velocity impact to improve the impact strength

Composites are widely used in many applications like aerospace, shipping automobiles, etc due to their good mechanical properties. Identifying the damage is the main concern in composites as it is not visible to naked eyes. In-service maintenance or operations, composites may be impacted by the foreign object which decreases the strength of the structure. To rectify this problem a lot of research is going on to evolve a methodology to identify damage in the composite. In this research paper, we tried to study the different design or architecture which will enhance the structural integrity of the laminate structure by changing the different parameters of the design of composites. In the first part of the article, numerical simulation results are validated with previously published research papers, and in the second part, the effect of parameters like stacking sequence, boundary conditions, projectile energy, geometry of impactor and impact angle, etc. are analyzed to improve the resistance to low velocity impact.

Modeling and Verification of an Acquisition Strategy for Wheel Loader's Working Trajectories and Resistance.

To overcome the difficulty of collecting the working resistance and working trajectory of a wheel loader, this paper constructs a statics model of the bucket working resistance and a kinematics model of the working trajectory in the shoveling process and analyzes the key parameters of measuring the working resistance and working trajectory. Based on this, a working resistance and working trajectory acquisition strategy is proposed. To verify the effectiveness of the acquisition strategy, the in-service operation data of fine sand and loose soil shoveled by the wheel loader are collected and analyzed. Then, the test-fitted working resistance and working trajectory are obtained, and the working trajectory is input into the RecurDyn–EDEM co-simulation model to obtain the simulation-fitted working resistance. Considering the complex working conditions of the wheel loader, it is difficult to obtain accurate working resistance, and the actual working resistance is also a relative value. Therefore, a strong correlation between the two curves indicates that the acquisition strategy of the wheel loader’s working trajectory and working resistance proposed in this paper is feasible.

Experimental estimation of the residual fatigue life of in-service wind turbine bolts

This study presents an experimental methodology aimed at estimating the residual fatigue life of in-service wind turbine bolts. The main objective is to assess the residual life of the bolts to plan their replacement and to avoid unexpected breakages of wind turbine blade connections. To develop the methodology, M16 bolts of quality 10.9 with controlled predamage were used, simulating in-service operating conditions. The fatigue tests were carried out taking care to place the nut at the point on the bolt that produces the highest damage at the same point where the predamage was performed. In addition, the influence of a possible angular positioning error on the residual fatigue life has been investigated. The residual fatigue life is estimated from the difference in fatigue life of new bolt tests and the fatigue life of predamaged bolt tests, simulating service conditions. Special care has been taken to guarantee that the most damaged zone of the bolt in service is also in the position that produces the highest damage during tests. An experimental procedure for determining the fatigue life of a new bolt from tests conducted on a bolt under the same operating conditions was developed. The developed methodology has been applied to M20 bolts belonging to real turbines in service.