Technical Papers - SAE Mobilus
SAE Technical Papers are written and peer-reviewed by experts in the automotive, aerospace, and commercial vehicle industries and provide the latest advances in technical research and applied technical engineering information.
Assembly sequence planning is a crucial part of process preparation in aircraft final assembly. A scientifically designed assembly sequence can significantly improve assembly efficiency and reduce costs in aircraft production. Efficient planning not only streamlines the workflow but also minimizes potential errors and rework, which are critical in high-stakes aviation manufacturing. This paper examines the constraint relationships in aircraft assembly from the perspectives of cabin constraints and system constraints, covering both spatial layout restrictions and functional logical dependencies to ensure the comprehensiveness of constraint analysis. It establishes a directed graph for the aircraft assembly outline and generates the corresponding adjacency matrix, which converts the complex constraint relationships into a structured mathematical expression for easier subsequent algorithmic processing. The Warshall algorithm and Johnson algorithm are used to check and extract contradictory constraints from the directed graph. The adjacency matrix is then employed to calculate the reachability matrix, which helps identify redundant constraints and reduces the computational effort in assembly sequence planning. Finally, the optimized constraint relationships are used to calculate the aircraft’s final assembly sequence, which generates a Gantt chart for assembly sequence planning, guiding the on-site assembly order and accelerating aircraft development efficiency. The integrated approach effectively addresses the key challenges in complex aircraft assembly sequence planning.
To safely, efficiently, and high-quality complete the mechanical testing of batch-produced manned spacecraft during the China Space Station (CSS) phase, a series of optimization measures were proposed based on system engineering principles. These measures cover the entire mechanical testing process from preparation to implementation, including: establishing a standardized mechanical testing documentation system; reducing the number of mechanical sensors that do not affect result evaluation; pre-identifying and measuring background noise; digitizing test notching and evaluation methods; and standardizing and automating testing procedures. Additionally, targeted measures for test safety and quality control were implemented, including regular inspections of reusable spacecraft components, strict control of test hazards and operational risks, and standardized management of ground support equipment (GSE) through regular inspections. The proposed optimization and control measures have been validated through applications in batch-produced manned spacecraft during the CSS phase. The results show that: the generalization rate of mechanical testing documentation exceeds 80%; the number of mechanical sensors has been reduced by more than 10%; the test preparation period has been shortened by over 4 days; test efficiency has been improved by 30%; the single-direction test duration has been reduced by more than 50%; and the total test cycle has been shortened by 25%. These results indicate that the proposed optimization and control measures are reasonable and feasible, which effectively reduces redundant test operations and items, lowers potential test risks, improves test efficiency, shortens the overall test cycle, enhances test safety, and ensures the high-quality completion of mechanical testing for batch-produced manned spacecraft.
With the continuous improvement of performance requirements for aviation equipment, the importance and complexity of hydraulic systems as the core carrier of flight control are becoming increasingly prominent. The cleanliness of aircraft hydraulic pipelines directly affects the reliability and flight safety of hydraulic systems, and it is necessary to use specialized cleaning and testing equipment during design and manufacturing to achieve efficient cleaning. The design of traditional cleaning equipment relies on experience-driven development, with mechanical, hydraulic, and electrical systems developed independently. There are problems such as unclear requirement definitions, low efficiency of interdisciplinary collaboration, and lagging validation, making it difficult to achieve the goal of forward design. Therefore, this study introduces Model-based Systems Engineering (MBSE) method in the development process of pipeline cleaning test equipment, proposes a modeling process based on RFLP (Requirements-Function-Logical-Physical), and uses SysML system modeling language to construct a top down design model system for aircraft hydraulic pipeline cleaning equipment. Through requirement analysis modeling, functional behavior definition, and system architecture design, the significant advantages of MBSE method in the development of complex aviation test equipment have been verified, effectively improving the bold design capability and top down design efficiency. MBSE method can not only improve the design efficiency of equipment, but also promote the intelligent and efficient operation of equipment, which has important significance for the development of intelligent manufacturing and electromechanical integration technology.
Extreme winter weather often leads to ice accretion on transmission lines. Manual removal is inefficient, costly, and poses safety risks. To address this issue, this paper presents the design of a de-icing robot to replace manual operations for transmission line de-icing. The main content focuses on the detailed structural design of the robot, including the mobile platform, de-icing mechanism, and adaptive adjustment module. Finite element simulations are conducted on key components to verify the structural rationality and the correctness of material selection. The proposed de-icing robot enhances the safety of the de-icing process, improves operational efficiency, and provides a valuable reference for transmission line de-icing methods, demonstrating significant practical value.
As special pressure-bearing vessels, spherical tanks are widely used in chemical, oil refining, and other fields. However, their safe operation faces the dual challenges of structural failure and leakage diffusion. Meanwhile, due to its low lower explosive limit and the low ignition energy required, propane will evaporate rapidly after leakage to form an explosive mixed gas, which may further trigger severe accidents such as combustion and explosion. Therefore, this paper takes a 3000 m3 propane spherical tank as the research object, comprehensively applies the finite element analysis method, and systematically researches stress distribution, aiming to provide theoretical support for the safety design of spherical tanks and accident prevention and control.
With the complexity of chemical warfare threats and the diversification of battlefield environments, traditional toxic agent detection methods are facing bottlenecks such as response delays, coverage blind spots, and personnel safety risks. This research focuses on the application of unmanned aerial vehicle (UAV) carried toxic agent sensor systems, aiming to analyze the methods of mounting and deploying the sensors on the UAVs, and to construct a rapid response, high-precision, and highly resistant toxic agent monitoring system. Its significance lies in two aspects: 1. Tactical value: It breaks through the time and space limitations of manual reconnaissance, realizes real-time dynamic perception and early warning of toxic agent contamination, and provides key decision-making support for battlefield command; 2. Application expansion: The research results can be transferred to counter-terrorism, nuclear, biological, and chemical emergency response fields, providing theoretical support and engineering paradigms for the development of unmanned and intelligent chemical defense equipment.
This study proposes an intelligent automotive roof frame design method based on the middle layer and component technology on CATIA. It aims to solve core roof modeling issues: determining geometric input quantity but uncertain attributes (tangent vectors, normal vectors, number of curve segments, number of surface patches, and boundaries), high manual interaction dependence, and poor knowledge reuse, to realize efficient design knowledge reuse. Methodologically, it builds a feature-driven parametric template, develops a knowledge rule-embedded componentized UDF library (reducing repeated modeling and geometric reconstruction needs), and integrates knowledge engineering for geometric input verification and operation direction control, eliminating curve/surface attribute uncertainty impacts. Verification shows the template stably generates roof crossbeams under simple/complex inputs, improving model robustness and reuse rate, reducing design workload, shortening verification cycles, and providing an extensible solution for white body design.
Impact testing utilizing instrumented hammers and accelerometers is a widely adopted technique in dynamic testing. The mass loading effect of the accelerometer alters the dynamic response of the test structure, leading to deviations between the measured frequency response functions (FRFs) and their true values. Furthermore, the effects on the FRFs are contingent upon the positioning of the accelerometer, thereby causing the measured FRFs between two points to fail to meet the principle of reciprocity. This paper investigates the compensation method for the mass of a single accelerometer in impact testing. Compensation formulas for both origin–FRF and cross–FRF are derived using the frequency domain substructure decoupling method. Numerical simulations on a cantilever beam and experimental tests with milling tools validate the proposed methodology. The compensation formulas for FRFs presented in this paper are expected to enhance the measurement accuracy of FRFs in modal testing of small structures, particularly relevant for lightweight components in aerospace, aircraft, and transportation systems, where precise dynamic characterization is critical.
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