Aircraft Engineering and Aerospace Technology最新文献

Purpose

This study aims to investigate the effect of countersunk rivet head dimensions on the fatigue performance of the riveted specimens of 2024-T3 alloy.

Design/methodology/approach

The relationship between rivet head dimensions and fatigue behavior was investigated by finite element method and fatigue test. The fatigue fracture of the specimens was analyzed by scanning electron microscopy.

Findings

A change of the rivet head dimensions will cause a change in the stress concentration and residual normal stress, the stress concentration near the rivet hole causes the fatigue crack source to be located on the straight section of the countersunk rivet hole and the residual normal stress can effectively restrain the initiation and expansion of fatigue cracks. The fatigue cycle will cause the rivet holes to produce different degrees of surface wear.

Originality/value

The fatigue life of the specimens with the height of the rivet head of 2.28 mm and 2.00 mm are similar, but the specimens with the height of the rivet head of 1.72 mm were far higher than the other specimens.

Purpose

The purpose of this paper is to present and implement a task allocation method based on game theory for reconnaissance mission planning of UAVs and USVs system.

Design/methodology/approach

In this paper, the decision-making framework via game theory of mission planning is constructed. The mission planning of UAVs–USVs is transformed into a potential game optimization problem by introducing a minimum weight vertex cover model. The modified population-based game-theoretic optimizer (MPGTO) is used to improve the efficiency of solving this complex multi-constraint assignment problem.

Findings

Several simulations are carried out to exhibit that the proposed algorithm obtains the superiority on quality and efficiency of mission planning solutions to some existing approaches.

Research limitations/implications

Several simulations are carried out to exhibit that the proposed algorithm obtains the superiority on quality and efficiency of mission planning solutions to some existing approaches.

Practical implications

The proposed framework and algorithm are expected to be applied to complex real scenarios with uncertain targets and heterogeneity.

Originality/value

The decision framework via game theory is proposed for the mission planning problem of UAVs–USVs and a MPGTO with swarm evolution, and the adaptive iteration mechanism is presented for ensuring the efficiency and quality of the solution.

Purpose

Loitering aerial vehicle (LAV) swarm safety flight control is an unmanned system control problem under multiple constraints, which are derived to prevent the LAVs from suffering risks inside and outside the swarms. The computational complexity of the safety flight control problem grows as the number of LAVs and of the constraints increases. Besides some important constraints, the swarms will encounter with sudden appearing risks in a hostile environment. The purpose of this study is to design a safety flight control algorithm for LAV swarm, which can timely respond to sudden appearing risks and reduce the computational burden.

Design/methodology/approach

To address the problem, this paper proposes a distributed safety flight control algorithm that includes a trajectory planning stage using kinodynamic rapidly exploring random trees (KRRT*) and a tracking stage based on distributed model predictive control (DMPC).

Findings

The proposed algorithm reduces the computational burden of the safety flight control problem and can fast find optimal flight trajectories for the LAVs in a swarm even there are multi-constraints and sudden appearing risks.

Originality/value

The proposed algorithm did not handle the constraints synchronously, but first uses the KRRT* to handle some constraints, and then uses the DMPC to deal with the rest constraints. In addition, the proposed algorithm can effectively respond to sudden appearing risks by online re-plan the trajectories of LAVs within the swarm.

Purpose

Climate change significantly impacts global temperatures, posing challenges to various sectors, including aviation. The purpose of this study is to assess the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences.

Design/methodology/approach

This study examines the effects of rising temperatures on aircraft engine performance using real-time data from a Boeing 787-8 equipped with GEnx-1B engines, which are collected via Flight Data Recorder of the engines and were analyzed for the take-off and cruise phases on the ground. Exhaust gas temperature (EGT), fuel flow and take-off weights were evaluated.

Findings

The analysis revealed a significant increase in EGT at the cruising altitude of 38,000 ft during the summer months compared to expected standard atmospheric values. This increase, averaging over 200 °C, is attributed to global warming. Such elevated temperatures are likely to accelerate the degradation of turbine components, resulting in increased fuel consumption: higher EGT signifies inefficient engine operation, resulting in more fuel burned per unit thrust; early engine aging: elevated temperatures accelerate wear and tear on turbine components, potentially reducing engine lifespan and increasing maintenance costs and enhanced atmospheric pollution: incomplete combustion at high EGTs generates additional emissions, contributing to local air quality concerns.

Practical implications

The research findings have practical implications for understanding the potential operational challenges and environmental impacts of climate change on aircraft engine performance. This lets us explore mitigation strategies and adapt operational procedures to ensure sustainable regional aviation practices.

Originality/value

This research enhances environmental consequences by assessing the impact of climate change on aircraft performance.

Purpose

This study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated features engineering (AFE).

Design/methodology/approach

The main concept of engine health status prediction was based on three case studies and a validation process. The first two were performed on the engine health status parameters, namely, performance margin and specific fuel consumption margin. The third one was generated and created for the engine performance and safety data, specifically created for the final test. The final validation of the neural network pattern recognition was the validation of the proposed neural network architecture in comparison to the machine learning classification algorithms. All studies were conducted for ANN, which was a two-layer feedforward network architecture with pattern recognition. All case studies and tests were performed for both simple pattern recognition network and network augmented with automated feature engineering (AFE).

Findings

The greatest achievement of this elaboration is the presentation of how on the basis of the real-life engine operational data, the entire process of engine status prediction might be conducted with the application of the neural network pattern recognition process augmented with AFE.

Practical implications

This research could be implemented into the engine maintenance strategy and planning. Engine health status prediction based on ANN augmented with AFE is an extremely strong tool in aircraft accident and incident prevention.

Originality/value

Although turbofan engine health status prediction with ANN is not a novel approach, what is absolutely worth emphasizing is the fact that contrary to other publications this research was based on genuine, real engine performance operational data as well as AFE methodology, which makes the entire research very reliable. This is also the reason the prediction results reflect the effect of the real engine wear and deterioration process.

Purpose

The altitude and weather conditions affect directly fuel consumption and engine efficiency of the aircraft engines. The thermo-physical properties of the weather of altitude play a significant role in this process. Unfortunately, engine performance based on altitude conditions also causes waste heat and environmental pollution due to engine entropy generation. However, environmental impact assessment is needed to improve environmental sustainability. This study aimed to analyse the energy and environmental performance of a piston engine based on altitude conditions.

Design/methodology/approach

This study is based on the entropy approach, and it aims to assess the environmental impact of the engine. Exergy analysis with together two new indices to evaluate the environmental effects caused by the engine under altitude conditions was used.

Findings

The analysis reveals that the exergy efficiency of the piston engine is 23.9% on average for the three referenced altitudes, while the exergy efficiency difference between altitude boundary conditions is 11%. In addition, the entropy production of the engine is on average 10.55 kW/K. In this case, the environmental pollution potential resulting from the entropy production of the engine is on average 3.29 times higher due to reversible conditions, while the improvement rate was found to be 58%.

Originality/value

This analysis shows that engine efficiency increases as altitude increases. Similarly, it can also be said that the environmental impacts are reduced and the improvement of the engine has opportunities for operational processes. Besides, in the study, some suggestions for motor performance impact analysis were presented.