As technology continues to leap forward and innovations advance, the systems of civil aircraft are becoming increasingly sophisticated and complex. Accordingly, there is a rising amount of information to be processed by pilots in the cockpit, increasing their cognitive burden, which significantly threatens the safety of flight. Thus, designers have formulated cockpit layout principles relating to importance, frequency of use, functional grouping, and operation sequence on the basis of ergonomics, which can effectively reduce the cognitive burden for pilots. The degree to which the cockpit layout of a model conforms to the four design principles can indicate its ergonomic design level. In accordance with the concepts of the above four cockpit layout principles, evaluation methods for determining their respective conformity to the four design principles were proposed in this paper. These methods use the operational sequence of cockpit system controls used in the normal flight mission of the actual aircraft type as the evaluation data source. Subsequently, the total evaluation results for cockpit layout were obtained using the weighted accumulation method. Lastly, the process for evaluating the cockpit layouts of civil aircraft was illustrated using the cockpits of the A320 series and B737NG series as examples. Based on the final evaluation results, the feasibility and effectiveness of the proposed evaluation method was verified.

With the development of China’s economy, China’s aviation market has expanded, and related industries have also developed rapidly. For the long-term development of the industry, many countries and enterprises began to make demand forecasts with different levels for the product market. The same is true for China’s civil aircraft-related industries. There are a variety of predictive models, but not all of them are appropriate for the prediction of civil aircraft market demand. This paper introduces a variety of modelling methods for forecasting models, including time series forecasting models and causal analysis forecasting models. The contribution of our work is the adoption of a new coefficient determination method to establish a variable-weight combination forecasting model, which greatly improves the forecasting accuracy. In addition, we also propose a new and more stable prediction model, the chain prediction model. Simulation prediction is carried out for each model in this work. Through the analysis and comparison of the prediction results, we conclude that the prediction effects of the variable weight combination prediction model and the chain prediction model are superior to those of other single prediction models. The chain prediction model in particular has better performance in medium- and long-term prediction, compared with the other prediction models. Finally, the model is applied to predict the demand of Chinese civil aircraft in the next 20 years, which confirms that the Chinese civil aircraft market will expand in the future.

The numerical accuracy of drop process simulation and collision response for drones is primarily determined by the finite element modeling method and simplified method of drone airframe structure. For light and small drones exhibiting diverse shapes and configurations, mixed materials and structures, deformation and complex destruction behaviors, the way of developing a reasonable and easily achieved high-precision simplified modeling method by ensuring the calculation accuracy and saving the calculation cost has aroused increasing concern in impact dynamics simulation. In the present study, the full-size modeling and simplified modeling methods that are specific to different components of a relatively popular light and small drone were analyzed in an LS-DYNA software environment. First, a full-size high-precision model of the drone was built, and the model accuracy was verified by performing the drop tests at the component level as well as the whole machine level. Subsequently, based on the full-size high-precision model, the property characteristics of the main components of the light and small drone and their common simplification methods were classified, a series of simplified modeling methods for different components were developed, several single simplified models and combined simplified models were built, and a method to assess the calculation error of the peak impact load in the simplified models was proposed. Lastly, by comparing and analyzing the calculation accuracy of various simplified models, the high-precision simplified modeling strategy was formulated, and the suggestions were proposed for the impact dynamics simulation of the light and small drone falling. Given the analysis of the calculation scale and solution time of the simplified model, the high-precision simplified modeling method developed here is capable of noticeably reducing the modeling difficulty, the solution scale and the calculation time while ensuring the calculation accuracy. Moreover, it shows promising applications in several fields (e.g., structure design, strength analysis and impact process simulation of drone).

Fiber-reinforced composite panels have become the primary load-bearing structures in aircraft due to their exceptional stiffness, specific strength, and mechanical properties. Owing to the high cost of experimental testing, numerical simulation is considered an effective method for rapidly modeling impact behavior and predicting complex internal failure mechanisms within composites. This study utilizes a combined approach of finite element simulation and experimental research to explore the low-velocity blunt-body impact behavior of composite laminates (CLs). The simulated peak impact force and pulse width demonstrated errors within 5.83% and 4.95% of the experimental results, respectively. This study provides effective support for investigations into the low-velocity blunt-body impact performance of CLs.

Commonality Benefit Analysis for Maintenance Technical Publications of Civil Aircraft Based on Learning Effect: The maintenance technical publications of civil aircraft are important engineering information for maintaining the continued airworthiness of aircraft, strictly guiding the maintenance of aircraft, and seriously affecting the efficiency of aircraft maintenance. The commonality between maintenance technical publications corresponding to different aircraft types brings primitive experience to aircraft operators for the maintenance of newly introduced types, which can accelerate the adaptation of maintenance personnel and reduce the maintenance time of aircraft. To quantify the commonality of maintenance technical publications, we constructed a commonality evaluation system for maintenance technical publications by combining the Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation Method. Then, a commonality benefit evaluation model of maintenance technical publications is established by analyzing the impact of commonality on the learning effect, which can analyze and calculate the monthly maintenance time savings of newly introduced models after the effects of commonality. The commonality benefit analysis for maintenance technical publications in this paper is mainly for aircraft operators, which can provide the reference for their decision to introduce new aircraft types.

As aviation technology advances, numerous new aircraft enter the market. These not only offer airlines technological and fuel efficiency advantages but also present the challenge of how to conduct pilots’ aircraft-type transition training efficiently and economically. To address this issue, this study designed a methodology to quantitatively assess the similarity in panel display control design and standard operating procedures (SOPs) between aircraft types. Then, by combining the results of a questionnaire survey on A320, A330, B737, and B777 transition training and training cost data, it was verified quantitatively that inter-aircraft similarity has a positive impact on reducing the difficulty and cost of transition training. Taking the similarity in aircraft types as a feature, the KNN algorithm was used to successfully construct a difficulty prediction model for the training program of aircraft-type transition training. To overcome the limitation of insufficient training cost data volume, this study adopts the transfer learning method to construct a prediction model of the transition training cost, and the final significant prediction accuracy proves the effectiveness of the method. The research in this paper not only provides strong data support for the resource planning and cost management of airlines’ aircraft-type transition training but also provides new research perspectives and methodological guidance for the field of aviation training.