Your Destination for Mobility Engineering Resources

The intent of this specification is for the procurement of plain weave fabric epoxy prepreg product with 250 °F (121 °C) cure for aerospace applications; therefore, no qualification or equivalency threshold values are provided. Users that intend to conduct a new material qualification or equivalency program must refer to the production quality assurance section (see 4.3).
AMS P17 Polymer Matrix Composites Committee
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
This SAE Aerospace Information Report (AIR) supplements ARP4754B/ED-79B by identifying the crucial elements to be considered when constructing the development assurance plans described in Section 3 (Development Assurance Planning) of ARP4754B/ED-79B for integrated systems. Section 4.6.4 of ARP4754B/ED-79B expands the aircraft/system integration and verification activities by emphasizing testing during integration to investigate for unintended behaviors. However, guidelines are needed for planning that are specifically aimed at the aircraft level and at integrating across system functions and boundaries. Until such guidelines are more comprehensively provided, this AIR presents a collection of lessons learned from past certification programs involving integrated systems, and as such it may be considered in conjunction with Sections 3 and 4 of ARP4754B/ED-79B. ARP4761A/ED-135 elaborates the safety activities by adding processes and methods such as the Aircraft or System Functional Hazard
S-18 Aircraft and Sys Dev and Safety Assessment Committee
According to SAE6906, Force Protection and Survivability (FPS) is the Human Systems Integration (HSI) domain that facilitates system operation and personnel safety during and after exposure to hostile situations or environments. Force protection refers to all preventive measures taken to mitigate hostile actions against Department of Defense (DoD) and Department of Homeland Security (DHS) (e.g., U.S. Coast Guard, Customs and Border Patrol, Immigration and Customs Enforcement, etc.) personnel. Survivability denotes the capability of the system and/or personnel manning the system to avoid or withstand man-made hostile environments without suffering an abortive impairment of his/her ability to accomplish its designated mission. Damage due to enemy or fratricidal action, or even equipment failure, will endanger the warfighters' well-being and place them into a life-threatening situation.
G-45 Human Systems Integration
The purpose of this SAE Recommended Practice is to establish uniform test procedures for measuring and rating air delivery and cooling capacity of truck and off-road self-propelled work machines used in earth moving, agriculture, and forestry air-conditioner evaporator assemblies. It is the intent to measure only the actual cooling capacity of the evaporator. It is not the intent of this document to rate and compare the performance of the total vehicle air-conditioning system.
Truck and Bus Windshield Wipers and Climate Control Comm
This SAE Aerospace Recommended Practice (ARP) provides criteria for the design, installation, operation, and training aspects of head-up display (HUD) systems in transport category aircraft, with emphasis on pilot interface and operational requirements. The recommendations apply to permanently installed (including stowable) HUDs that display primary flight information, including those integrating enhanced flight vision system (EFVS) imagery. The intent is to ensure HUDs are designed and used in a manner that improves pilot situational awareness and flight technical performance across all phases of flight, up to and including low-visibility operations. While technical design standards (optical performance, hardware specs, etc.) are defined in documents like ARP5288 and AS8055, this document focuses on pilot usage considerations and human factors. HUD systems addressed here are typically designed to support a fail-passive operational concept applicable to Category III instrument approach
S-7 Flight Deck Handling Qualities Stds for Trans Aircraft
The intent of this specification is for the procurement of carbon fiber epoxy prepreg product with 250 °F (121 °C) cure for aerospace applications; therefore, no qualification or equivalency threshold values are provided. Users that intend to conduct a new material qualification or equivalency program must refer to the production quality assurance section (see 4.3).
AMS P17 Polymer Matrix Composites Committee
This method outlines the standard procedure for testing the hardness of bearing components. Bearings covered by this test method shall be any rolling element bearing used in airframe control.
ACBG Rolling Element Bearing Committee
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Implicit sentiment analysis of automotive user feedback is crucial for understanding user opinions. Automotive user feedback often express opinions in an indirect way and are accompanied by a dense array of industry terms. Therefore, without costly fine-tuning, both aspect identification and sentiment analysis are rather difficult. We propose a Pattern-Guided pipeline for implicit sentiment analysis to achieve the joint extraction of aspect and sentiment. This pipeline first performs Pattern Anchoring, mapping colloquial expressions and slang to the standardized vehicle component knowledge system. Then, using Knowledge-Augmented Prompting, these domain rules are injected into well-designed prompt templates. In this pipeline, the large language model (LLM) is applied to output JSON records suitable for comprehending, including aspects, sentiments, confidence levels, and brief reasons. To enhance stability, we employ an improved prompt and consistency-driven confidence fusion to generate
Chang, GengjiaDeng, ZuxingMa, AonanYao, JiangqiLi, XiaojianLi, Ling
Robotic ultrasound scanning technology is a research hotspot in the field of medical imaging, and can achieve standardized and high-precision data acquisition. However, large force tracking errors occur during scanning, especially in complex human tissues, which can severely degrade image quality and diagnostic accuracy. Therefore, we propose an adaptive speed-regulated impedance control strategy to address this challenge, which innovatively combines the spline real-time interpolation and impedance control for constant force tracking. Firstly, the discrete ultrasound scanning paths are fitted to generate a smooth and synchronized interpolation trajectory. Then, the speed of the reference trajectory is adjusted in real time based on the Taylor formula to reduce the force tracking error. Experimental verification was conducted, and the results showed that the force tracking error increases with the increase of trajectory speed. In addition, at high speeds (e.g., 10 mm/s), the mean
Min, KangZhang, LeShi, YudongFang, JinMo, HangjieLi, Xiaojian
As the “digital brain” and core foundational support for the development of intelligent transportation and connected vehicles, the performance of data centers directly determines the operational capability of intelligent transportation systems. In the process of advancing the vehicle-road-cloud collaborative architecture, the demand for high-performance computing power in data centers has experienced explosive growth. The substantial increase in computing tasks has posed severe challenges to thermal management, making efficient and reliable cooling systems an indispensable core component. Centrifugal compressor water-cooling units are the mainstream cooling solution for large-capacity scenarios, and their design optimization is crucial for improving the energy efficiency and performance of the entire cooling system. This paper proposes a one-dimensional performance prediction method for centrifugal compressors based on an empirical loss model, and realizes the iterative calculation of
Zhu, MinhaoJiang, BinLi, MinZeng, ZihuiGu, Yunhui
In recent years, large language models (LLMs) have shown great potential in many domains. However, their application in professional domains is often limited by problems like erroneous outputs and hallucinatory responses. Therefore, we present a framework that combines knowledge graphs (KGs) with local LLMs. The framework utilizes the factual information in KGs to improve the initial output of the LLMs, thereby reducing the factual errors in inference. In this paper, a domain knowledge graph is automatically constructed using textual data from the power industry. The KG contains 149,732 entities and 139,280 relationships. The proposed method is tested on EleQA, a public Q&A dataset of electricity regulations. Compared with the LLM-only baseline, the knowledge-graph-enhanced model achieves an improvement of 32.42%. Moreover, the framework shows strong adaptability and performs well on various LLMs. Our framework improves the accuracy and utility of large language models in the power
Chen, RuiduanLin, ShizhongShao, ZhanCui, ShichengLi, XingyuLuo, He
As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to
Zhang, JinZhang, WanyueYuan, JingjingChen, ZhenGu, Dazhi
End-to-end autonomous driving in urban environments faces three core challenges. First, camera and LiDAR sensor heterogeneity causes cross-modal perception inconsistencies and sensor fusion instability. Second, diffusion models suffer from training instability due to scale variance and distribution changes, which limits generalization. Third, traditional trajectory decoders lack structured interaction with semantic elements, thereby undermining planning rationality. To address these issues, CMFPNet introduces an integrated framework with three key modules. The HGCF-Backbone integrates LiDAR and camera features using channel focus, deformable cross-focus, and state space modeling to enhance semantic alignment. The NST module maps physical trajectories to normalized space, employing truncated diffusion sampling for stable generation in just 2–4 steps. The NDA models trajectory generation as a semantic narrative, utilizing a six-stage semantic attention flow incorporating BEV context
Qu, YanweiMo, Hangjie
In this paper, the design and process research of uniform filling linear trajectory for filament wound hydrogen storage tank with unequal polar holes are carried out. Firstly, by optimizing the slip coefficient, the winding angles of the left and right heads are smoothly and continuously transitioned to the cylindrical section. We study the necessary conditions for achieving the central angle of uniform filling, and calculate the tangent points of the trajectory line based on the continuous fraction principle. Meanwhile, the slip coefficients at the left and right ends that satisfy stable winding and uniform covering are determined. Based on the equal contour constraint conditions, we analyze the motion trajectory equation of the four-axis winding machine and convert it into the corresponding machine code for actual winding operations. Experimental results show that stable winding of fibers on the surface of the unequal-polar-hole mandrel is achieved, and uniform filling and winding
Chen, BaosenFu, JianhuiCao, XuewenYu, Libin
While large language models (LLMs) offer a convenient natural language interface for logistics optimization problems, it remains challenging to directly generate reliable mathematical models and executable code from unstructured text requirements. LLMs tend to produce invalid constraints or syntactically incorrect code. In addition, traditional logistics optimization methods lack the flexibility to adjust warehouse rules or operational goals without manual expert intervention. To address these issues, we propose LOOP (a Language-Model Orchestrated Optimization Pipeline), which automatically translates natural-language requirements into optimization algorithm code while retaining the rigor of classical models and solvers. LOOP leverages task-specific agents to construct accurate mathematical models and adopts a difference-driven code generation approach. First, it synchronizes model changes into executable code via semantic mapping and ensemble difference analysis. Second, it
Ding, RuiqingLi, QianyingLi, Xiaojian
Although carbon fiber-reinforced aluminum-lined hydrogen storage vessels (Type III) exhibit outstanding specific strength and specific stiffness, the constraints imposed by their design parameters on fatigue performance and ultimate load-bearing capacity remain incompletely elucidated. We propose a fatigue life prediction method for high-pressure vessels that couples progressive damage in the fiber composite with cumulative damage in the metallic liner, aimed at forecasting the fatigue performance of Type III pressure vessels under cyclic loading. Furthermore, a finite element analysis systematically investigates the influence of key design parameters, for nominal pressure, liner diameter and liner thickness, on fatigue performance and ultimate load-bearing capacity. Results indicate that fatigue life significantly decreases with increasing nominal pressure and liner diameter, with nominal pressure exerting a more pronounced effect. Notably, altering the autoclave pressure alone cannot
Bi, ZhihaiZhang, Qian
The rapid development of autonomous driving technology has brought emerging opportunities to optimize the omnidirectional vehicle driving performance. However, its compliance with driving habits directly determines its social acceptance. Therefore, how to balance consistency between performance improvement and driving habits has become an important bottleneck restricting the rapid promotion of autonomous driving technology. Manual driving vehicles mostly focus on the safety of both longitudinal and lateral movements, and cannot cope with the vertical movement, let alone the performance of economy, comfort, and efficiency. In this context, this paper proposes an anthropomorphic trajectory optimization method incorporating vehicle omnidirectional dynamic characteristics and corresponding driving habits. Firstly, this paper explores vehicle dynamic characteristics in longitudinal, lateral, and vertical directions, and reveals the coupling effect of motion states during driving
Liao, PengZhang, DefengNing, DonghongLi, SijiaWang, Tao
Surface electromyography (EMG) signals are essential for facilitating intuitive interactions between humans and bionic hands. However, their inherent non-stationarity, low signal-to-noise ratio, and significant inter-individual variability present considerable obstacles to precise decoding. To overcome these challenges, this study proposes a novel recognition framework combining wavelet packet decomposition and a dynamic graph convolutional-Transformer model. The process starts with multi-layer wavelet packet decomposition and adaptive threshold denoising, effectively removing noise while retaining critical signal features. Subsequently, a dynamic graph convolutional network is employed to capture spatial interactions among multi-channel electrodes, and a Transformer encoder models long-term temporal dependencies within the signals. By integrating these methods, the model generates a fused feature representation that incorporates both spatial and temporal correlations. Experimental
Huang, RuiZhao, YueYang, PenghuaZhu, JintaoXiong, Xibei
The design process of mining supports is often complicated due to their intricate structure and numerous dimensional dependencies, leading to a cumbersome modeling process and low design efficiency. To address these challenges, this paper introduces a parametric design system for mining supports built on the SolidWorks platform. The system integrates modular design concepts, module-matching principles, dimension-driven techniques, and API development. By adopting a modular assembly modeling approach, the system offers an efficient solution for managing the dimensional relationships between the various components of mining supports. Additionally, the system supports adaptive processing of 2D engineering drawings, facilitating the rapid design and manufacturing of mining supports. Engineering case studies demonstrate that this system enhances the design efficiency of mining supports by over 90%, significantly shortening the product development cycle, ensuring product quality, and
Rui, LichaoSong, JiahaoYang, ZhiqingLi, HelongDing, Lijian
Causal reasoning is the task to identify causal relations between a pair of events in a given context. However, causal reasoning in natural language remains a challenging task for large language models (LLMs), since they tend to mix correlation and causality and exhibit bias in their reasoning, especially by mistaking temporal proximity for causal relations. The problem is exacerbated by the models’ propensity to generate spurious justifications that confuses co-occurrence rather than actual causal relationships. Although CoT prompting has shown effectiveness in enhancing multi-step reasoning, it is prone to hallucination and spurious inferences, which generally dampens their capability to provide correct causal explanations. The variant of CoT, CoT-SC, is a more promising attempt at yielding consistent outputs by randomly sampling multiple reasoning paths, and voting for the most probable answer. However, for its implementation, CoT-SC also demands expensive computations. The
Yang, JiaoyunQi, BotaoLiu, LiLi, LianAn, Ning
Currently, with the continuous development of electric vehicles, DC microgrids have attracted widespread attention due to their flexible access methods and high energy transmission efficiency. However, since the distributed secondary control of DC microgrids relies on information exchange through communication networks, false data injection (FDI) attacks on these networks may cause control algorithms to fail, leading to voltage deviations, output current imbalance, and in severe cases, system instability. This study focuses on DC microgrids based on parallel DC–DC buck converters and proposes a distributed secondary control strategy based on a sliding mode observer to address FDI attacks. By treating the system's FDI attack signals as an extended state, an extended sliding mode observer is designed to track the attack signals. Based on the observed attacks, a control algorithm is proposed that compensates the control inputs through the observer, ensuring proportional sharing of bus
Sun, WeiChen, JingYu, JinzhuYuan, WeiboPeng, BoLin, Fei
This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while
Song, ZiangGao, WenxuanCao, XiaochuanZheng, XingZhao, Chong
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping