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In order to solve the problems of poor weight estimation accuracy and difficult layout design trade-offs in the concept demonstration and overall program definition stage of civil aircraft, Aircraft Layout, a civil aircraft overall program structure rapid design software, is used to establish a numerical calculation-based layout program rapid design simulation platform. Based on the forward fuselage structure, this paper gives the results of rapid modeling and finite element simulation and analysis of the forward fuselage isotropic section of a certain type of aircraft, which provides a reference for the optimization design of the structural components of the forward fuselage section of a certain type of aircraft in the conceptual scheme design stage.

To address the issue of large-scale noise clusters and small-scale scattered noise in the point cloud of aircraft wing-fuselage docking surfaces, this paper proposes a multi-scale hybrid filtering denoising method. By utilizing the k-means++ clustering algorithm and introducing a density weight factor along with a dynamic neighborhood radius mechanism, large-scale noise clusters are effectively segmented and removed. Additionally, adaptive radius filtering is employed to eliminate residual fine noise, achieving a hierarchical denoising process across different scales. Validation using actual measurement data from a certain aircraft wing-fuselage docking surface demonstrates that this method outperforms traditional statistical filtering and singleradius filtering in denoising effectiveness, providing a high-quality data foundation for subsequent assembly accuracy control.

Composite fuselage shape control is a representative black-box optimization problem, where the fuselage shape is a high-dimensional functional response with strong spatial correlations and each evaluation is costly. Existing functional Bayesian optimization methods for this problem often suffer from prohibitive computational burdens due to high dimensionality and inadequate representations of spatial correlations in fuselage shapes. To address these limitations, this study proposes a B-spline empowered functional Bayesian optimization (BFBO) method, in which fuselage shapes are represented using low-dimensional B-spline control points and their correlations are modeled using a multivariate Gaussian process (MGP). Based on the predictive distribution of control points, a generalized chi-square expected improvement criterion is derived to guide the optimization process. Numerical results show that BFBO achieves improved performance in terms of convergence speed and optimization accuracy, demonstrating its effectiveness for fuselage shape control and its potential as a practical optimization framework for the design and manufacturing of engineering systems involving functional responses.

Out-of-autoclave (OoA) curing, as a low-cost and scalable means for generating large carbon fiber/epoxy fuselage skins, still suffers from a narrow process window and vulnerability to interlaminar defects, which limits it from true engineering use. To solve the above issue, this paper presents a multi-stage hybrid simulation-inversion integrated model based on multimodal data (CureDef-ML). This multi-authored study utilizes the Kamal-Sourour thermal chemical reaction model, adds a local void evolution mechanism, and implements stochastic perturbation modeling of prepreg permeability to better inform the description of micro uncertainties present within the curing process. In addition, a three-dimensional finite element thermal conduction solver is fused with a time-evolving Graph Neural Network (GNN) for real-time retrieval of the interaction character of the microstructure at the interlaminar interfaces. For defect prediction, spatial graphs are dynamically evolving to make probabilistic inferences of the defect area with regard to potential voids, interlaminar delaminations, and obtain an “early-warning” for defects. Finally, the determined task of diagnosing the process window is framed as a constrained optimization problem in the TPVH space negotiated by reward-driven reinforcement learning agents to dynamically and adaptively regulate the curing process path. Altogether, the CureDef-ML model can increase the feasible process window by 34.2%, demonstrating significant benefits when compared to current industrial standard processes.

Aircraft crash analysis and design methods are important aspects of aircraft design. A full-scale finite element model of the B737-200 fuselage section containing 6 frame sections with an auxiliary fuel tank is developed using the explicit finite element code, Pamcrash, to perform simulated analysis. The simulation result outputs the fuselage’s maximum deformation. Seat tracks’ acceleration responses are compared with the drop test to determine the method’s correctness. This method is then applied to simulate the crash of an airplane fuselage section with an auxiliary fuel tank in the cargo compartment at a velocity of 9.144m/s to provide reference for engineering applications.

This study aims to examine the rotor surface pressure distribution, the rotor’s effects on the wing and fuselage, and the surrounding flow field structure during the operation of a tilt-rotor Unmanned Aerial Vehicle (UAV). Using Fluent software, numerical simulations are performed to analyze the flow field around the rotor and the pressure variations across its surface, under three operational scenarios: vertical climb, rotor tilt, and high-speed level flight. The findings indicate that the rotor’s surface pressure is predominantly concentrated at the leading edge across all three conditions, although the pressure distribution varies along the blade surface. Additionally, the rotor’s influence on the wing and fuselage is more pronounced during the rotor tilt and high-speed level flight conditions.

With the development of large fuselage assembly tooling widely used in aircraft manufacturing, safety and deformation are given great importance. For a better understanding of the deformation mechanism of assembly tooling under a non-homogeneous temperature field, the deformation of panel assembly tooling for a civil aircraft under a temperature gradient is studied in this article. The thermo-mechanical modelling method is established, and a user subroutine is developed based on ABAQUS. The distribution of the temperature field and stress-strain fields is obtained and analyzed. The main results of this study are: (1) The temperature gradient can greatly affect the deformation of assembly tooling. The maximal vertical displacement Uy is 0.197 mm at room temperature, and under horizontal and vertical temperature gradients, it increases by 246% and 238%, respectively. (2) The deformation is mainly caused by thermal expansion strain, which is one order of magnitude larger than elastic and thermal creep strain. (3) Although a temperature gradient causes stress increase, the stress is less than the yield strength of the material, and no plastic deformation is generated. The safety can be guaranteed under a considered temperature gradient. (4) During large-scale assembly tooling design and material optimization, the material with a lower thermal expansion coefficient is suggested.

Hybrid hydrogen fuel cell (HH2FC) aircraft is one of the viable technological pathways to reduce carbon emissions in the aviation industry. For a configuration with aft-fuselage propulsion, a novel method is established for the initial sizing of the HH2FC aircraft in a situation where empirical data is lacking. The carbon emission reduction capabilities and potential for reducing fuel and carbon tax costs can be preliminarily assessed by the proposed initial sizing method. A case study on a narrow-body aircraft indicates that, at the current technological level, the carbon emissions and cost of the HH2FC aircraft will increase to achieve the same payload and range as the conventional aircraft. However, with the improvement of hydrogen technologies, such as fuel cell power density and hydrogen tank gravimetric density, HH2FC aircraft will reduce 6.6% carbon emissions compared to conventional aircraft. As a result, both economic and environmental benefits can be achieved in the future.

This study focuses on the flight test design for helicopter emergency flotation systems, and conducts modeling and simulation analyses of post-inflation deployment flight dynamics characteristics. First, CFD software is employed to compute the aerodynamic characteristics of the fuselage in both the deployed and folded states of the flotation airbags, thereby obtaining the corresponding fuselage aerodynamic data. Subsequently, a flight dynamics model of a single-rotor with a tail rotor helicopter in the emergency flotation configuration was established in Simulink. The Simulink Linear Analysis Tool was then employed to simulate and analyze the equilibrium characteristics of the helicopter under various flight conditions after the flotation airbags were deployed. Finally, the influence of the emergency flotation configuration’s aerodynamic characteristics on the pitch inputs and attitude angles required for stable flight following airbag deployment was summarized.

This research work focuses on fluctuating load spectrum generation and fatigue analysis of a wing‐fuselage attachment lug joint, in accordance with the requirements outlined in 14 CFR Part 25 for transport category aircraft. The study involves the generation of a fatigue load spectrum using an exceedance curve, followed by finite element analysis of a simple round‐ended lug. The exceedance curve is a statistical tool used to represent the probability of a variable exceeding a particular threshold over a specified time period. It is particularly useful in fatigue analysis as it helps quantify the likelihood of stress levels surpassing critical limits, aiding in the assessment of structural integrity and durability. The CAD model of the lug is created in CATIA, and the corresponding FE model is obtained using Altair HyperMesh. The investigation pertains to a turboprop aircraft weighing approximately 25,000 kg and accommodating 70–90 seats, with ATR 72 and Dash Q 400 being the prominent choices in this category within India. Mission Profiles for these aircraft are obtained from the Directorate General of Civil Aviation (DGCA) website, utilizing scheduled flight data. To ensure the structural integrity of the lug, a static analysis is performed for FE model convergence, leading to the determination of stress concentration factors. Subsequently, fatigue analysis is conducted using Nastran Embedded Fatigue (NEF), considering constant amplitude loading with stress ratios of −1 and 0.1. the fatigue life of the component is predicted based on Goodman and Gerber failure criteria. The analysis yields crucial insights into the fatigue life of the lug and its damage accumulation over time. The CAD model of the lug is created in CATIA, and the corresponding FE model is obtained using Altair HyperMesh. The investigation pertains to a turboprop aircraft weighing approximately 25,000 kg and accommodating 70–90 seats, with ATR 72 and Dash Q 400 being the prominent choices in this category within India.