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Announcements for SAE Mobilus

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Vertical Flight Society Technical Papers - Coming Soon to Mobilus
Vertical Flight Society papers coming soon to SAE Mobilus. In partnership with the Vertical Flight Society (VFS), SAE Mobilus will be hosting more than 17,000 technical papers and proceedings from VFS. Click here to see a sample of the content covering decades of rotorcraft and vertical flight technologies.
Important Update – Accessibility Enhancements on SAE Mobilus
We’re pleased to share that SAE Mobilus has recently completed a comprehensive set of accessibility improvements across the platform. As a result, Mobilus is now aligned with WCAG 2.2 Level AA standards in most key categories. These updates are part of our ongoing commitment to ensuring the platform is accessible to all users. Enhancements include improvements to keyboard navigation, screen reader compatibility, visual contrast, error handling, and overall usability across core areas of the site. An updated Voluntary Product Accessibility Template (VPAT v2.5 – March 2026) is now available, providing a detailed overview of our accessibility conformance. You can access the VPAT directly within the Help section. Accessibility is a continuous effort. We will continue to evaluate and improve the platform to better support all users and meet evolving standards. If you have any feedback or experience any accessibility issues, we welcome your input. - The SAE Mobilus Team
SAE AI Chat — Update and What's Next
* Important Update - SAE AI chatbot Beta program * The SAE AI Chatbot Beta program - Phase 1 will end on March 31, 2026. Following this date, the AI chatbot capabilities will be temporarily unavailable as we begin development of a significantly enhanced version. We sincerely thank all Phase 1 Beta participants for their engagement and valuable feedback - your insights have played an important role in shaping the next phase of this experience. The upcoming version of the SAE AI Chatbot will expand content coverage beyond current standards, incorporating additional critical resources from our digital library. It will also be made available to a broader audience across Mobilus. Want to be part of what's next? Register your interest here to receive updates and be considered for early access. For additional information, visit the FAQs. — The Mobilus Team
SAE International Digitization and AI Policy
SAE International prohibits the entry of SAE Content into any form of Artificial Intelligence (AI) tools, such as ChatGPT, OpenAI, or Microsoft Copilot. Additionally, creating derivatives of SAE Content using AI is also prohibited without express written permission from SAE International. In the case of such use, SAE International will suspend access to SAE Content, and further legal action will be considered.
Welcome to the new SAE Mobilus®
  Welcome to the new era of SAE Mobilus®, redesigned with a modern, intuitive web interface featuring enhanced search capabilities to help you stay informed and easily discover content. Login today: To access content within your subscription and make the most of the platform, please log into your subscription and your personal My Library (sign up is free) located in the top right corner of the screen.   Key Features Intuitive User Interface: We've listened to our customers and tied this to the best practices in the industry to offer an improved, intuitive, and desirable website experience for our users.​ Improved In-app Discoverability: Enhanced search and expanded menu featuring search suggestions that allow for quick discovery of content.​ Announcements: Stay up to date on new features through a dedicated announcements page. Most recent announcements also get featured on the homepage.​ Enhanced Browse capabilities: Browse through over 200,000 publications that are now classified into categories commonly used across the industry. Deep-dive further into any topic or sub-topic of interest to make the most for your corporate projects or research.​ Smart Automation: "Meta Tags" on each result will help you find content related to your search.​ My Library: My dashboard is rebranded as My Library with powerful features to help you make the most out of the platform Mobile Friendly: Upgraded navigation on mobile devices​ Training Available SAE’s Customer Success team is dedicated to delivering the best platform experience possible. Through monthly trainings and short, on-demand video tutorials, find answers to your questions here: SAE Mobilus Spotlight training - Available monthly, hosted live by SAE’s Customer Success team Mobilus Minute – 2-minute videos, available on-demand   Need some troubleshooting help? Access our FAQs by visiting our Help section: https://saemobilus.sae.org/help/home Resources to help you navigate the new platform are available here, where you can find links to quick start guides and video tutorials on features like My Library, Announcements, Saved Search, Login and new features. Have feedback that you'd like to share with us? Please submit your feedback to the Mobilus team through the blue Knowledge bot in the bottom right hand corner of the new platform.

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Recent SAE Edge™ Research Reports

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Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster ResponseEPR202501711/24/2025
The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the advanced air mobility and drone industry further enable the development of modern, safe, and practical WIG platforms. Click here to access the full SAE EDGETM Research Report portfolio.
Next-gen AI for Aerospace EngineeringEPR20250169/22/2025
Despite growing investments, the widespread adoption and scalable deployment of generative artificial intelligence (AI) remains a challenge due to data trustworthiness, regulatory uncertainty, interpretability, and ethical governance. The need to accelerate automation and maintain the human-in-the-loop demonstrates broader questions of responsibility and transparency. Next-gen AI for Aerospace Engineering investigates the transformative role of GenAI within aerospace engineering, examining its shift from conventional workflows toward more AI-driven solutions in design, manufacturing, and maintenance. It emphasizes GenAI’s emerging ability to automate repetitive mundane tasks, reduce design complexity, and optimize engineering pipelines. The report underscores the need for validation methods that must align AI-generated outputs with physics-informed models, integration with legacy engineering tools (e.g., computational fluid dynamics, finite element analysis, digital twins), and mitigation of algorithmic biases. Click here to access the full SAE EDGETM Research Report portfolio.
Sustainable Circular Future Mobility: Environmental Impact of Next-gen VehiclesEPR20250159/22/2025
The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and actionable solutions to help stakeholders better navigate the transition toward a circular future for mobility. It further highlights the overlooked complexities in the Global South, emphasizing the importance of ethical market expansion and localized mobility strategies. Click here to access the full SAE EDGETM Research Report portfolio.
Safety Impacts of Active Safety and Driving Automation FeaturesEPR20250138/13/2025
Advanced technologies that assist the human driver or reduce (or even eliminate) the human driver’s role are becoming increasingly prevalent in new light-duty vehicles used by the general public. These technologies are divided between Active Safety features that monitor the human driver and vehicle motion and act intermittently to mitigate and avoid crashes, and Driving Automation features that assume some or all of the dynamic driving task from the human driver. Both types of technologies have the potential to reduce injuries and save lives by reducing the frequency and/or severity of crashes. Safety Impacts of Active Safety and Driving Automation Features addresses the current capabilities and future potential for Active Safety and Driving Automation features to reduce crash frequency and severity and provides an overview of the state of the industry for both types of features, including current deployments, trends, and anticipated rollouts. Gaps in knowledge, unsettled issues, and suggestions for future research will also be discussed. Click here to access the full SAE EDGETM Research Report portfolio.
Small, Mobile, and Autonomous Agricultural RobotsEPR20250128/13/2025
The automation of labor-intensive picking and planting operations is having an immediate impact in the agricultural indutry. In its simplest form, robotic automation can reduce the labor and soil disturbance while enabling organic soil cover and increasing species diversification through precision approaches to planting, weeding, and spraying. With this, pesticides and fertilizers can be applied in a more targeted way, and with machinery visiting fields more frequently, earlier and more targeted intervention can occur before pests become established. Small, Mobile, and Autonomous Agricultural Robots identifies issues that need to be resolved fo for this technology to thrive, including improving methods of acquiring and labeling training data to facilitate more accurate models for specific applications. It also discusses concepts such as general-purpose mechanical platforms for use as carriers of agricultural automation systems with high stability, positional accuracy, and variable track, as well as the economics of moving capital intensive automation systems toward a service-provision business model. Click here to access the full SAE EDGETM Research Report portfolio.
Hybrid Data- and Physical Model-driven Safe and Intelligent Motion Planning and Control for Autonomous VehiclesEPR20250147/18/2025
Autonomous vehicle motion planning and control are vital components of next-generation intelligent transportation systems. Recent advances in both data- and physical model-driven methods have improved driving performance, yet current technologies still fall short of achieving human-level driving in complex, dynamic traffic scenarios. Key challenges include developing safe, efficient, and human-like motion planning strategies that can adapt to unpredictable environments. Data-driven approaches leverage deep neural networks to learn from extensive datasets, offering promising avenues for intelligent decision-making. However, these methods face issues such as covariate shift in imitation learning and difficulties in designing robust reward functions. In contrast, conventional physical model-driven techniques use rigorous mathematical formulations to generate optimal trajectories and handle dynamic constraints. Hybrid Data- and Physical Model-Driven Safe and Intelligent Motion Planning and Control for Autonomous Vehicles presents a hybrid framework that combines data-driven insights with the robustness of physical models. It identifies key challenges in fusing these disparate methods and outlines potential solutions in developing robust fusion strategies, establishing generalized mixed dynamics models, and designing multi-objective robust control systems. In addition, the report explores future research directions to enhance learning efficiency, improve adaptability to rare but critical scenarios, and ultimately pave the way for secure, efficient, and human-like autonomous driving systems. Click here to access the full SAE EDGETM Research Report portfolio.
Product Assurance in the Age of Artificial IntelligenceEPR20250115/21/2025
Driven by the vast consumer marketplace, the electronics megatrend has reshaped nearly every sector of society. The advancements in semiconductors and software, originally built to serve consumer demand, are now delivering significant value to non-consumer industries. Today, electronics are making inroads into traditionally conservative, safety-critical sectors such as automotive and aerospace. In doing so, electronics—now further propelled by artificial intelligence—are disrupting the functional safety architectures of these cyber-physical systems. Electronics have created the world of cyber-physical systems, raising broader concerns about the broader category of product assurance. Product Assurance in the Age of Artificial Intelligence continues the work of previous SAE Edge Research Reports in examining open research challenges arising from this shift, particularly in automotive systems, as core electronic technologies (e.g., the combination of software and communications) have even redefined what it means to be a "product." Click here to access the full SAE EDGETM Research Report portfolio.
Edge Artificial Intelligence in Connected, Cooperative and Automated MobilityEPR20250095/20/2025
With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial intelligence (AI) is instrumental in processing such data, and in that context, “edge AI” is a more recent type of implementation. Edge AI involves AI algorithms in edge computing devices, which requires hardware operating close to where data is generated. This report explores the potential of edge AI in CCAM. Different perspectives on edge AI for CCAM are explored and definitions drafted. Primary applications are explored, and an outlook on further advancements in applications is presented. The report includes a discussion on the benefits, risks, and challenges related to the use of edge AI in this domain. Major issues such as privacy and cybersecurity are considered, as are misconceptions. Furthermore, potential learning benefits, using experiences gained in other sectors, are introduced. NOTE: SAE Edge Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.
Leveraging Advanced Data Technologies for Smart Traffic ManagementEPR20250085/20/2025
The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and educational programs in leveraging AI for transportation applications are emphasized in this report. Click here to access the full SAE EDGETM Research Report portfolio.
Space-based Solar Power for Instantaneously Dispatchable Renewable Power on EarthEPR20250054/24/2025
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

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Passenger Vehicle Systems
SAE International Journal of Passenger Vehicle Systems
Electrified Vehicles
SAE International Journal of Electrified Vehicles
Advances and Current Practices in Mobility
SAE International Journal of Advances and Current Practices in Mobility
Sustainable Transportation, Energy, Environment, & Policy
SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy
Transportation Cybersecurity and Privacy
SAE International Journal of Transportation Cybersecurity and Privacy
Connected and Automated Vehicles
SAE International Journal of Connected and Automated Vehicles
Vehicle Dynamics, Stability, and NVH
SAE International Journal of Vehicle Dynamics, Stability, and NVH
Transportation Safety
SAE International Journal of Transportation Safety
Alternative Powertrains
SAE International Journal of Alternative Powertrains
Commercial Vehicles
SAE International Journal of Commercial Vehicles
Passenger Cars - Mechanical Systems
SAE International Journal of Passenger Cars - Mechanical Systems
Passenger Cars - Electronic and Electrical Systems
SAE International Journal of Passenger Cars - Electronic and Electrical Systems
Engines
SAE International Journal of Engines
Aerospace
SAE International Journal of Aerospace
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing

Recent Books

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Composite Materials Handbook Volume 5 - Revision BR-4608/27/2026
The fifth volume of this compendium publishes technical guidelines and properties of ceramic matrix composite material systems. The content includes information on material selection, processing, characterization, testing, data reduction, design, analysis, quality control, application, case histories, and lessons learned of typical ceramic matrix composite materials. Initial Release of Volume 5 superseded Mil-HDBK-17-5 dated June 17, 2002. The Composite Materials Handbook, referred to as CMH-17, is an engineering reference tool that provides comprehensive, practical engineering guidelines that have proven reliable for the design, fabrication, characterization, test, and maintenance of polymer matrix, metal matrix, ceramic matrix, structural sandwich, and non-metallic AM materials. CMH-17 provides information and guidelines necessary to design and fabricate end items from composite materials. The compendium includes reliable data, linked to control of processes and raw materials, to provide material property basis values and design information that promotes the safe use of ceramic matrix composites in aerospace applications. CMH-17 provides information and guidelines necessary to design, fabricate, and maintain components from composite and non-metallic additively manufactured (AM) materials. In support of this purpose, the handbook constitutes an overview of the field of advanced materials technology and engineering. It is used by engineers worldwide in designing and fabricating products made from composite materials.
July 2026 AMS IndexAMSJULY-20267/22/2026
Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume IB-994_VOLUME17/1/2026
The Metallic Materials Properties Development and Standardization MMPDS-2026 supersedes MMPDS-25 and prior editions of the MMPDS Handbook as well as all editions of MIL-HDBK-5, Metallic Materials and Elements for Aerospace Vehicle Structures Handbook that were maintained by the U.S. Air Force. The last edition, MIL-HDBK-5J was cancelled by the U.S. Air Force in March 2006. This document contains design information on the mechanical and physical properties of metallic materials and joints commonly used in aircraft and aerospace vehicle structures. All information contained in this Handbook has been reviewed and approved using a standardized process. The development and ongoing maintenance process involves certifying agencies, including the FAA, DoD, and NASA, and major material suppliers and material users worldwide. The information and procedures in this Handbook are continuously reviewed and modified or removed as determined to be appropriate. With advances in materials and fastener systems, and with the review process of existing information, periodic updates of the MMPDS should be expected. As such, it is recommended that the latest version of the MMPDS be used. Volume II: Process Intensive Materials and Joining Technologies.
Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume IIB-994_VOLUME27/1/2026
Volume II publishes the framework for generating and analyzing the data so that material sponsors can generate the right data, knowing how it will be analyzed by the Battelle Memorial Institute. MMPDS-2026 Volume II Process Intensive Materials and Joining Technologies does not currently have any material properties, focusing on additive manufacturing of metallic materials. MMPDS-2026 Volume II focuses on non-conventional processes and will be published each year. Volume I: Conventional Materials and Joint Allowables.
1D and MultiD Modeling Techniques for IC Engine Simulation Second EditionR-5805/29/2026
The internal combustion (IC) engine remains the most widely used thermal machine in the world and will continue to play a central role in global mobility for decades to come. Even as alternative powertrains expand, optimized IC engines—often integrated within hybrid and electrified architectures—are essential to achieving low fuel consumption, near-zero pollutant emissions, and reduced carbon dioxide output. Advances in combustion strategies, synthetic fuels, turbocharging, and aftertreatment systems are driving this evolution. This fully revised and expanded second edition reflects the rapid progress made in engine modeling and simulation over the past two decades. One-dimensional (1D), three-dimensional (3D), and coupled 1D–3D modeling techniques have become indispensable tools in modern engine design, enabling engineers to evaluate performance, efficiency, and emissions through advanced virtual engine environments. Bringing together contributions from leading international researchers and industry experts, this book presents the most significant and recent developments in IC engine simulation. Topics include 0D, 1D, quasi-3D, and full 3D modeling approaches; turbocharging and aftertreatment systems; co-simulation and real-time applications; hydrogen and two-stroke engines; and advanced thermal modeling techniques. Designed for engineers, researchers, and graduate students, this second edition serves as a comprehensive reference for understanding, comparing, and applying state-of-the-art IC engine modeling methodologies in an evolving mobility landscape. Chapter topics include: • state of the art of 1D thermo-fluid dynamic simulation models • virtual engine development: 1D- and 3D-CFD up to full engine simulation • advanced 0D and quasiD thermodynamic combustion models for SI and CI engines • compressor and turbine (turbocharger, supercharger, or turbocompounding device) as boundary conditions for 1D simulations • 3D-CFD combustion models for SI and CI engines • model order reduction for real-time simulation and control applications • modeling of EGR systems •1D engine model in XiL application-a simulation environment for the entire powertrain development process • coupling of 1D and 3D fluid dynamic models for hybrid simulations • extending the 1D approach to the simulation of 3D components: the quasi-3D approach • 1D simulation models for aftertreatment components• 3D simulation models for after-treatment systems • modeling of IC engine silencers and tailpipe noise: 1D and 3D approaches • hydrogen-fueled internal combustion engines • optimization of the gas exchange process in advanced 2-stroke engines • IC engine 0D/1D thermal modeling
Variable Compression Systems for Future Engines and FuelsR-5534/30/2026
Variable Compression Engines: Enabling Net Zero explores variable compression ratio (VCR): one of the most promising—and historically elusive—advancements in internal combustion engine (ICE) technology. Long recognized for its thermodynamic benefits, VCR has challenged engineers for decades due to its mechanical complexity. Today, as the global mobility landscape demands ever higher efficiency, lower emissions, and greater fuel flexibility, VCR has emerged as a viable and transformative solution. This book delivers a comprehensive and authoritative examination of VCR technology, quantifying its efficiency and CO2-reduction potential while surveying the wide range of mechanisms conceived, developed, and tested over more than a century of engine innovation. By combining historical insight with modern analysis, the authors reveal the remarkable ingenuity of past and present engine designers—and demonstrate that VCR is not only feasible, but increasingly essential. Positioned squarely within the context of global decarbonization, the book argues for a realistic, inclusive pathway to net-zero emissions—one in which ICEs continue to play a critical role. VCR technology enables higher efficiency across almost all operating conditions, supports advanced combustion strategies, and allows engines to operate effectively on a broad spectrum of low- and zero-carbon fuels, from biofuels to synthetic e-fuels. With VCR now in high-volume production and poised for broader adoption across automotive, heavy-duty, and marine applications, this timely volume is an essential resource for OEMs, suppliers, policymakers, researchers, and students seeking practical, scalable solutions for a sustainable energy future. Chapter topics include: • compression ratios and fuels • compression ratio limits • cylinder head VCR • cylinder block VCR • connecting rod variable compression • piston VCR • cranktrain and linkages VCR • modulated crankshaft eccentricity VCR • axial or barrel engine VCRs • high power and downsized engines • impact of VCR systems on engines • VCR applications for the future • variable compression for future engines and fuels • VCR cost–benefit analysis
Aerospace Standards Index - 2026ASIN20262/25/2026
This valuable resource lists all Aerospace Standards (AS), Aerospace Recommended Practices (ARP), Aerospace Information Reports (AIR), and Aerospace Resource Documents (ARD) published by SAE. Each listing includes title, subject, document number, key words, new and revised documents, and DODISS-adopted documents. AMS Index - Now Available!
Business Reliability Growth for Automotive Engineering, Volume 4R-5522/17/2026
In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book include: • Holistic reliability across design, manufacturing, supply chain, and marketing. • Advanced experimental designs, including split-plot and fractional factorial methods. • Fault tree analysis (FTA) and FMEA for failure prediction and prevention. • Supply chain optimization through multivariate process control. • Production and field reliability using design for testability and diagnostics. • Electric vehicle system and battery reliability analysis. • Marketing reliability driven by voice of customer and data-based value analysis. This book is an essential resource for engineers, operations leaders, and technical managers who want to build resilient systems, unlock innovation, and achieve long-term competitive advantage through disciplined, data-driven reliability.
Fundamentals of Sustainable Aviation FuelsR-5471/22/2026
As global energy demands rise and environmental challenges intensify, the aviation industry faces a critical need to redefine how it powers the skies. Fundamentals of Sustainable Aviation Fuels presents a comprehensive, research-driven exploration of the transition from fossil-based fuels to renewable alternatives that promise to reshape the future of air transportation. This book bridges the gap between academic knowledge and industrial application, offering a detailed overview of the science, technology, and policy driving the adoption of Sustainable Aviation Fuels (SAFs). From understanding feedstocks and conversion pathways to evaluating production technologies, emissions performance, and life-cycle impacts, the text equips readers with a holistic understanding of SAFs within today’s global energy landscape. Across five insightful chapters, readers will find a clear roadmap: the evolution and importance of SAFs; production methods and technological foundations; environmental performance and emissions reduction potential; safety, certification, and market integration; and future projections supported by international initiatives and regulatory frameworks. By combining technical depth with practical relevance, Fundamentals of Sustainable Aviation Fuels serves as both a foundational reference and a forward-looking guide for researchers, policymakers, industry professionals, and students. It underscores that achieving sustainability in aviation depends not only on innovation but also on global collaboration, paving the way toward cleaner skies and a resilient, low-carbon future for air travel.
SAE International’s Dictionary of ADAS and Connected VehiclesR-5591/20/2026
The convergence of Advanced Driver Assistance Systems (ADAS) and connected vehicle technologies is ushering in a transformative era of automotive innovation—one that is fundamentally enhancing vehicle safety, efficiency, reliability, and the overall driving experience. SAE International’s Dictionary of ADAS and Connected Vehicles stands as the definitive reference for this rapidly evolving domain, meticulously compiled to clarify and standardize the language shaping modern mobility. Inside, readers will find clear, authoritative definitions encompassing the full spectrum of technologies that enable connected and automated driving—including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) communication systems. This comprehensive resource translates complex engineering terminology into accessible language, enabling engineers, researchers, policymakers, educators, and enthusiasts to share a common technical foundation. Reflecting the latest global standards, research, and innovations, this dictionary bridges the gap between theory and application. It fosters interdisciplinary collaboration, supports safer system design, and provides clarity for those engaged in regulatory development or technology deployment. As the pace of mobility innovation accelerates, precise and accessible communication becomes indispensable. SAE International remains committed to advancing global transportation knowledge—empowering professionals to navigate, contribute to, and shape the future of intelligent, connected, and sustainable mobility with confidence and clarity.

Recently Published

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Research on Intelligent Switching and Control Strategy of Air-Sea Amphibious WIG Craft Based on Multi-Sensor Fusion2026-99-061911/6/2026
Aiming at the core problems of abrupt changes in dynamic characteristics and poor smoothness in mode switching during the cross-medium operation of amphibious wing-in-ground (WIG) craft, this paper develops an intelligent switching and control system based on multi-sensor fusion. The system integrates measurement data from the Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and Light Detection and Ranging (LiDAR) to construct a state observation module for mode switching decision-making. On this basis, a fuzzy switching logic centered on flight altitude and sea state characteristics is proposed, and a hybrid control strategy combining Linear Quadratic Regulator (LQR) and Proportional-Integral-Derivative (PID) is designed to realize the smooth transition between water surface and flight modes. Numerical simulations conducted in Python demonstrate that the proposed control scheme can accurately determine the mode switching timing, stabilize the pitch angle fluctuation within ±3° during the transition process, and effectively enhance the ability of WIG craft to operate autonomously and stably of the WIG craft in complex sea conditions.
Zhang, Qihao, Yan, Yifei, Cao, Fengshuo, Xiong, Yueling, Liu, Qing, Deng, Yanpeng, Wu, Peng
Air Target Trajectory Prediction Method Based on MSD-Transformer2026-99-060411/6/2026
The prediction of air target trajectories is important. It is necessary to integrate time-series data in the motion of air targets, such as timestamps, spatial coordinates, kinematic parameters, etc. To cope with the challenges of air target trajectory prediction in complex electromagnetic environments, this paper proposes the MSDTransformer model. The SMSAE and DDE modules are introduced, and this method improves the performance of air-target trajectory prediction. The sensitivity analysis of system hyperparameters verifies the rationality of model parameter configuration. The experimental results show that, among the simulated air target data, MSD-Transformer achieves lower prediction errors and demonstrates strong overall performance, compared with 5 main methods (iTransformer, Informer, PatchTST). It can support the understanding and prediction of target situations, provide an accurate basis for the analysis of the intentions of air targets and the prediction of the evolution of situation evolution, and then improve the situation awareness ability. It has important application value for trajectory prediction in modern aerospace surveillance and situation awareness.
Zhang, Yongzhuang, Sun, Peng, Zhang, Jieyong, Yang, Guangwei, Jiang, Jianxiong, Li, Tianxin, Zhong, Yun
Reproducing Capture Control in a Novel Hardware-in-the-Loop Simulation System2026-99-060111/6/2026
In space gravitational wave detection, the verification of the mass release capture phase determines subsequent mission advancement. Existing control algorithms are primarily validated through simulation, though ground-based experimental verification remains indispensable. This paper develops a two-stage torsion pendulumbased ground hardware-in-the-loop (HIL) simulation system to simulate and verify the position and attitude degrees of freedom of the test mass. An Expansive State Observer and State Feedback Control (ESO-SFC) disturbance rejection and capture controller based on an ESO and SFC was designed and compared with a PID controller. Numerical simulation results demonstrate that the ESOSFC controller outperforms the PID controller. Experimental validation was conducted on a HIL simulation system. Results confirmed the system's capability to achieve capture functionality while validating the effectiveness of both the ESO-SFC and PID control algorithms. The ESO-SFC demonstrated superior control performance to PID, with experimental outcomes consistent with simulation results. This provides a reference for test mass release capture control algorithms.
Ping, Shanyan, Ren, Yuqi, Cui, Bing, Zhang, Chu, Xia, Yuanqing, Duan, Li, Kang, Qi
2026 International Conference on Artificial Intelligence, Autonomous Systems, and Aerospace (AIAS 2026)2026-99-060011/6/2026
TOC
Tobolski, Sue
Autonomous Obstacle Detection and Landing Site Selection Method for Complex Lunar Approach Phases2026-99-063511/6/2026
In response to the challenges of autonomous obstacle detection and landing site selection during the soft-landing approach phase of the Chang'e probes, this paper proposes a method based on Fractal Brownian Motion (FBM) for local lunar terrain reconstruction and obstacle identification. Using passive optical imagery and incorporating statistical models of crater morphology and distribution, the method approximates the 3D structure of candidate landing areas and estimates local slopes. Combined with texture analysis (TA) via K-means clustering evaluated by silhouette coefficients, and by integrating slope and roughness metrics, feasible landing zones are autonomously identified. Simulation results demonstrate that the proposed approach can rapidly reconstruct terrain and select suitable landing areas, showing good mission adaptability.
Zhu, Hanxi, Wu, Peng, Wu, He, Li, Yixiu, Tang, Weipeng, Deng, Yanpeng
DoS Attacks-Resistant Fusion Filtering for Nonlinear Rectangular Descriptor Systems with Uncertain Attack Probability2026-99-063111/6/2026
This paper investigates the design problem of a fusion filtering algorithm for nonlinear networked rectangular descriptor systems with multi-source information. A set of independent Bernoulli random variables is introduced to characterize the phenomenon of denial of service (DoS) attacks, where the attack probability consists of a nominal probability and an uncertain term with a known upper bound (UB). Firstly, a full-order transformation method is introduced to transform the rectangular descriptor system into a non-descriptor system, where the local filters are constructed. Then, by employing the elementary inequality, the upper bounds on both the prediction error covariance and the filtering error covariance are derived and characterized by matrix difference equations. The local filter gain is designed by minimizing the obtained UB of the filtering error covariance. Subsequently, based on the covariance intersection fusion rule, a new fusion filtering algorithm is presented for addressing the descriptor system. Lastly, the effectiveness of the proposed algorithm is verified through a simulation experiment.
Feng, Qiushi, Zhang, Wenxin, Luo, Ruonan, Hu, Jun, Wu, Zhihui
An Enhanced Mamba Integrating Dynamic Compression Ratio Channel Attention and Progressive Projection for Multivariate Time Series Forecasting2026-99-064011/6/2026
Time series forecasting is a practical cornerstone for decision-making in diverse fields including finance, energy management and meteorology, yet conventional Transformer-based models are plagued by high computational complexity inherent in their attention mechanism, as well as poor efficiency in capturing long-range dependencies when processing long-sequence time series data. Meanwhile, the recently proposed Mamba model built on a linear-complexity state space model has achieved strong performance in long-sequence modeling tasks, but the vanilla Mamba model still has obvious limitations in time series forecasting scenarios, including insufficient discriminability of channel features, unsatisfactory prediction accuracy, and information loss during feature transmission in the encoder layer. To address these issues, this paper proposes An Enhanced Mamba Integrating Dynamic Compression Ratio Channel Attention and Progressive Projection for Multivariate Time Series Forecasting, which incorporates three core improvement strategies: a lightweight dynamic compression ratio channel attention, a residual-optimized encoder, and a progressive prediction head. These strategies realize adaptive weighting of channel features, lossless information transmission in the encoder and gradual refinement of forecasting results respectively. Extensive experiments on multiple public time series datasets show that compared with the vanilla Mamba model and mainstream Transformer-based forecasting methods, the proposed model achieves significant improvements in prediction accuracy, along with stronger robustness and higher practical application value.
Zhu, Yongdong, Zou, Lei, Li, Na, Wang, Chenxi
Vehicle Detection from UAV Perspective Based on GBC-YOLOv5s in the Low-Altitude Economy2026-99-064311/6/2026
This paper presents GBC-YOLOv5s, a lightweight vehicle detection model designed for unmanned aerial vehicle (UAV) applications in the growing low-altitude economy sector. By utilizing the baseline YOLOv5s architecture, we integrated three structural enhancements to achieve an optimal trade-off between algorithmic precision and processing expenses. First, ghost convolution is used to exploit feature map redundancy, substantially cutting both parameter count and computational overhead. Second, a Bi-Level routing attention (BRA) mechanism is integrated. This allows the model to capture global context along with fine-grained local features of vehicle targets effectively. Third, standard upsampling is replaced with content-aware reassembly of features (CARAFE). This better preserves feature details, which proves particularly important for detecting small objects. Testing was conducted on a custom UAV-based vehicle dataset. GBC-YOLOv5s achieves 86.6% average precision (AP) with only 4.7 M parameters. This represents a 34.7% reduction from the original YOLOv5s with 7.2 M parameters. The accuracy drop is merely 0.2%. Ablation experiments validate both the individual impact and synergistic nature of each proposed module. Results show that GBC-YOLOv5s reaches a practical balance between performance and efficiency. It offers a workable solution for real-time vehicle detection on resource-limited UAV platforms and intelligent traffic monitoring applications.
Zhang, Qingpei, Yu, Tianhao, Zhao, Zheming
Compensation Strategy-Based Gaussian Approximation Fusion Filtering for Multi-Sensor Nonlinear Systems Subject to Markov DoS Attacks2026-99-061411/6/2026
The research concentrates on the Gaussian approximation fusion filtering (GAFF) issue for multi-sensor nonlinear systems under Markov denial of service (DoS) attacks. This paper aims to propose a fusion filtering algorithm for the addressed systems to cope with DoS attacks within the Gaussian approximation filtering framework, where the attacks follow the Markov property. In particular, a prediction compensation strategy is adopted to reduce the impact caused by the attacks as much as possible. In light of the available measurements, the Gaussian approximation local filtering unified framework is given, where the Gaussian weighted integrals are addressed by means of the cubature Kalman method. By using the sequential inverse covariance intersection fusion criterion, the GAFF algorithm is obtained to improve estimation accuracy. Finally, a simulation experiment with comparison tests is introduced to validate the effectiveness of the proposed GAFF method.
Luo, Ruonan, Hu, Jun, Jia, Chaoqing, Dao, Wen
Coupling Effect Analysis of Disturbance from Rotating Components in Flexible Satellites2026-99-061011/6/2026
This study investigates the coupling effect between rotating components of a satellite equipped with flexible appendages and the satellite’s unconstrained modes. A modal synthesis method based on mixed coordinates is adopted to establish the dynamic model of a satellite with multiple flexible appendages. The vibration equations under the excitation of disturbance torques induced by rotating components are derived for the flexible appendages in an unconstrained state. The on-orbit unconstrained modal frequencies and their mode shape vectors are calculated. Based on this, the analytical expressions for the satellite’s unconstrained modal responses and attitude angular velocity under the influence of driving disturbances from rotating components are obtained. Furthermore, the coefficient matrix that characterizes the amplification of attitude angular velocity induced by flexible vibration is analyzed when the drive frequency of rotating components is coupled with the satellite’s unconstrained modal frequencies. Taking a sun-synchronous orbit satellite with a single solar array as an example, the on-orbit unconstrained modal frequencies as a function of solar array angles are calculated. By applying harmonic disturbance torque generated by a rotating component, the attitude angular velocity and constrained modal coordinates are obtained through simulation. When the drive frequency of the rotating component matches the satellite’s unconstrained modal frequency, the corresponding mode shape (eigenvector) is analyzed. Based on the eigenvector values, the constrained mode of the solar array exhibiting the maximum coupling vibration is identified. The amplification coefficient matrix of attitude angular velocity resulting from coupling with the drive disturbance of the rotating component is validated. The damping coefficient associated with the unconstrained mode is estimated using the simulation data.
Sun, Shang, Niu, Wenting, Zhang, Kaicheng, Yang, Yulong, Zhang, Yanzhao
Knowledge-Driven Aerial Swarm Target Intent Recognition Method for Few-Shot Scenarios2026-99-062311/6/2026
With the continuous advancement of collaborative unmanned aerial vehicle (UAV) swarm applications, the importance of intent recognition for aerial swarms in UAV management and control has become increasingly evident. To address the shortcomings of existing intent recognition methods, this paper proposes a knowledge-driven aerial swarm target intent recognition method designed for few-shot scenarios. First, a target trajectory clustering algorithm is designed by combining trajectory similarity measurement (which considers directional features) with density peaks clustering. This algorithm groups targets exhibiting the same or similar motion trends, thereby transforming the swarm target intent recognition problem into a swarm member intent recognition problem, which reduces the complexity of intent recognition. Second, considering the behavioral dynamics inherent in aerial swarm collaborative applications, a target intent inference model is constructed based on a Dynamic Bayesian Network (DBN). Utilizing the characteristic information of swarm targets at different time points, this model achieves intent inference and recognition through a hierarchical process: “sub-intent inference → accumulation of historical sub-intent sequences → intent inference.” Finally, simulation experiments are conducted to verify the feasibility and effectiveness of the proposed method.
Jiang, Jianxiong, Gui, Yang, Sun, Peng, Yang, Xinyu, Yang, Guangwei, Zhong, Yun
Onboard AI-Driven Autonomous Tasking for Rapid Wildfire Response with a LEO Wide-Swath Observation Satellite2026-99-060911/6/2026
Low Earth Orbit (LEO) remote sensing satellites exhibit significant limitations in emergency response operations, primarily due to the constraints of orbital mechanics and a traditional reliance on ground-involved, open-loop operational models. Current response latencies often span several hours, rendering acquired data less effective for disasters with rapid temporal dynamics. We propose a new intra-pass autonomous reaction application mode to solve this key problem in emergency response. We build the mode on an agile satellite platform operating in an 800 km sun-synchronous orbit. We equip the platform with two core sensors through an innovative design. The two sensors are an optical camera with 0.5-meter resolution and a forward-looking infrared camera. The infrared camera has a 600-kilometer swath and a 10-meter nadir resolution. We take onboard artificial intelligence technologies as the research core. The technologies support real-time and autonomous analysis of forward-looking infrared image data. This analytical capability facilitates the real-time detection and autonomous confirmation of stochastic events, such as wildfires, by leveraging onboard artificial intelligence (AI) to perform real-time analysis of IR imagery. This subsequently triggers immediate autonomous re-tasking for high-resolution follow-up observation within the same orbital pass. We establish an optimization model for the satellite system. The model is used to solve the key balance problem between the sensor forward-looking angle, achievable reaction time, and actual detection resolution. We conduct a detailed engineering time budget analysis for the whole satellite operation system. Analysis results show that a specific forward-looking angle must be set for the infrared camera to obtain a 70-second autonomous response window of the satellite. The 70second window contains 30 seconds for AI cognitive analysis, a maximum of 33.6 seconds for platform attitude maneuvering, and 10 seconds for platform stability adjustment. The minimum forward-looking angle required for the infrared camera is about 33.6 degrees. The ground sampling distance of the infrared camera will decrease to 12.2 meters at this angle. The resulting 12.2-meter ground sampling distance (GSD) remains sufficient to meet the practical requirements of early-stage detection. The proposed Intra-Pass Autonomous Reaction (IPAR) mode reduces emergency response times from hours to seconds, significantly enhancing the proactive observation capabilities of LEO platforms.
Qiu, Hu, Zhao, Xinwei, Liu, Dongfusheng, Wang, Honghai
Energy Management for Series Hybrid Aircraft Based on a Dual Adaptive Equivalent Fuel Minimization Strategy2026-99-060311/6/2026
Series hybrid tiltrotor aircraft operate under highly dynamic and multi-phase flight missions. This paper addresses the resulting energy management challenge. Moving beyond the direct application of existing optimization algorithms, this study proposes a novel codesign framework that synergizes offline global optimization with online fuzzy adaptive control. The key theoretical innovation lies in transforming the online, real-time optimization problem of determining the optimal equivalent factor into an offline global optimization problem for the parameters of a fuzzy-PI controller. This is achieved through a hybrid particle swarm optimization and genetic algorithm (PSOGA), which optimizes the controller's scaling factors and gains. The optimized controller embeds mission-level economic information into the online generation of the equivalent factor, so that the power-split decision is determined not only by the instantaneous operating conditions, but also by the overall economic objective of the mission. Simulation results under typical and stochastic flight conditions validate the framework's effectiveness. Compared to benchmark strategies, the proposed PSOGA-Fuzzy-A-ECMS achieves a 6.7% improvement in fuel economy while robustly maintaining the battery state of charge within a safe and stable range. This study provides a systematic and theoretically-grounded design paradigm for real-time energy management in complex, time-varying systems.
Wang, Zhihao, Wang, Xiangyang
Swarm Cooperative Strategy for Multi-UAV Based on Adaptive Boundary Discretization and Distributed Particle Swarm Optimization2026-99-062111/6/2026
In traditional multi-unmanned aerial vehicles (UAVs) cooperative strategies within complex irregular regions, the low coverage efficiency, boundary constraint failure, and insufficient robustness bring the challenges. This paper proposes a cooperative search-andattack algorithm, which integrates adaptive mission area discretization and distributed intelligent particle swarm optimization (DIPSO). An adaptive grid model is constructed with ray casting algorithm to discretize arbitrary polygonal mission areas precisely. It can effectively reduce the invalid searches in non-mission zones by abandoning the traditional rectangular assumption. Moreover, a multi-objective fitness function (MOFF) is designed by incorporating coverage ratio, path length, collision penalty, and load balancing. With the discrete path manipulation operators (PMOs) and dynamic learning factors, the proposed method achieves distributed trajectory planning in convex polygonal spaces. Simulation results demonstrate that compared with counterparts, the proposed method performs closer boundaries to actual ones. Furthermore, it achieves 100% coverage while shorten the mission time significantly, validating its adaptability in various convex polygonal scenarios.
Zhou, Yunbo, Zhang, Di, Xia, Wei
Experimental Investigation on the Failure Behavior of TMC Open-Hole Panels under Tensile Loading2026-99-060211/6/2026
Investigating the load-bearing capacity of Titanium Matrix Composites (TMCs) open-hole panels and their mechanically connected components is of great significance for the application of titanium matrix composites in the aerospace field. This paper investigates the failure behavior of TMC open-hole panels with a [45°/45°/-45°/-45°] laminate configuration under tensile loading. Tensile tests were conducted in conjunction with finite element modeling to analyze the damage evolution process and identify the failure modes of the tensile samples. The results show that the simulation outcomes exhibit good consistency with the experimental results, providing a foundation for the structural optimization and theoretical study of TMC open-hole panels.
Gao, Ximan, Jia, Qiuyue, Liu, Shanshan, Meng, Fanling
Research on Lightweighting Wheel Hub for New Energy SUVs Based on ANSYS Workbench2026-99-190411/6/2026
In recent years, the sales volume of new energy vehicles (NEVs) in China has maintained a steady growth trend, and consumers have paid increasing attention to vehicle range. Against this backdrop, the demand for lightweighting of various core components of NEVs has significantly increased. As a key component of automobiles, the wheel hub accounts for a relatively large proportion of the unsprung mass, and its lightweighting is of great significance for improving the driving range and enhancing vehicle performance. In this paper, sunflower and bridge truss are integrated as design elements, and a small-sized new energy sports utility vehicle (SUV) is selected as the reference vehicle model to design a lightweight wheel hub. Creo is used for 3D modeling of the wheel hub, and static stress, radial fatigue, bending fatigue, and modal simulations are performed in ANSYS Workbench. The results show that all wheel hub performance indicators meet the service requirements. Meanwhile, the quality evaluation indicates that the weight of the designed wheel hub is 10.95 kg, which is 3.90 kg lighter than the original wheel hub, representing a weight reduction of 26.3% compared with the original one, thus meeting the lightweighting standards.
Li, Chang
Research on Quantification Methods for Nonlinear Forming Length of Ultra-Thin Flat Wires in Flat Wire Motors2026-99-191311/6/2026
Because of the imprecision of length quantification in the manufacturing of flat wire windings for flat wire motors, empirical allowances have long been a common practice in production, which in turn leads to considerable material waste and elevated production costs. This paper presents an integrated solution that fuses material experiments, reverse engineering, simulation iteration and parametric design, realizing accurate prediction and quantitative calculation of winding forming length. First, high-precision elastic-plastic constitutive relationships of flat wires are acquired through room-temperature uniaxial tensile tests. On this basis, reverse engineering is applied to derive the initial geometric characteristics and process motion paths of flat wire windings from the 3D model of finished products. Next, an innovative closed-loop iterative compensation algorithm is constructed, with the forming height of the innermost flat wire layer serving as an absolute reference; finite element simulation is then utilized to dynamically optimize the forming length of each flat wire layer. Finally, a parametric design system with a visual interactive interface is developed, which enables an intelligent workflow where precise cutting lengths and equipment motion curves are automatically generated upon input of key design parameters. Production validation results show that this method drastically reduces the length allowances of flat wires, markedly lowers the production scrap rate, and shortens the process debugging cycle of new motor models by more than 80%.
Li, Wenbin, Zhu, Ye
XGBoost–Bayesian Optimization Method for Multi-Blade Centrifugal Fan2026-99-192111/6/2026
To overcome the trade-off between airflow rate and efficiency in a multi-blade centrifugal fan for automotive air-conditioning systems, as well as the low optimization efficiency of conventional simulation- or experiment-based approaches resulting from the large number of impeller design parameters, a surrogate-model-based optimization framework coupled with an intelligent optimization algorithm is proposed for impeller design. Latin hypercube sampling was employed to generate 120 samples within the design space, and an XGBoost model was integrated with a Bayesian optimization strategy to perform the optimization process. Validation results indicate that the prediction error of the surrogate model is less than 3%. Under the final optimized impeller configuration, the airflow rate is increased by 22% at the design operating condition, while the total pressure efficiency is improved by approximately 20%, satisfying the prescribed design requirements.
Yan, Yaqin, Yue, Chen
Aeroseek: Exploring LLM-Enhanced Monte-Carlo Path Planning for UAV Navigation2026-99-061311/6/2026
While Unmanned Aerial Vehicles (UAVs) hold immense potential for transforming the low-altitude economy, developing an agent that combines both intelligence and flexibility remains a significant challenge. To this end, we propose a novel aerial navigation system, Aeroseek, to search for executable paths that coherently transition from cognitive understanding to physical movement, enabling more autonomous and flexible navigation with instruction guidance. Specifically, given a navigation instruction, we follow a fast-andslow thinking procedure inspired by human pilots by breaking down complex decisions into manageable sub-tasks and initiating motion planning immediately upon the completion of each sub-task for realtime movement. By integrating a multi-branch Chain-of-Thought, Aeroseek is capable of combining reasoning with spatial recognition and self-verification to search for robust sub-goals under expected constraints. For sub-goal navigation, we introduce Online Kinodynamic Monte-Carlo Path Planning (OnKi-MCPP), a novel motion planning approach handling both kinodynamic constraints and path search, while ensuring obstacle avoidance for UAVs. Benefiting from the proposed two-tier searching protocol, Aeroseek demonstrates comprehensive capabilities in processing complicated instructions and adapts to dynamic aerial conditions. Extensive experiments demonstrate the advantages of Aeroseek across tasks of varying complexity.
Luo, Guoan, Xu, Tian, Zhou, Jiacong, Wang, Xianyun
Design and Analysis of a Continuous Drying Process and Equipment for 3D Hollow Polyester Fiber Production2026-99-190311/6/2026
In the production of polyester fibers from recycled polyethylene terephthalate (rPET), the drying and crystallization of plastic bottle flakes are crucial for ensuring the consistency and strength of the finished fibers. Traditionally, rPET production lines still rely on vacuum drum dryers, which have been suffering from issues including agglomeration, uneven heating, and high energy demand. In this work, we developed a novel continuous system that is capable of achieving a total throughput of 1300 kilograms per hour. The design consists of a pulsating fluidized-bed crystallizer and two cylindrical drying towers operating in parallel. Structural performance of the main systems was analyzed using finite element analysis under material load, thermal expansion, and internal air pressure. Airflow behavior and temperature distribution inside the units were studied using Computational Fluid Dynamics (CFD) models, where the flake bed was treated as a porous medium based on experimental bulk density and pressure drop. Results showed that the drying tower maintained a minimum safety factor above 3 under full-load conditions, while the crystallizer also remained well within allowable stress limits. Additionally, flow-field analysis results indicated stable countercurrent airflow, adequate mixing near the inlet region, as well as acceptable axial temperature gradients for moisture removal below 50 ppm. Compared with conventional drum drying, we believe the continuous configuration simplifies operation and reduces heat loss. Our design approach has been combined with analytical calculations on structural and flow simulation, and can be beneficial when applied to similar rPET drying applications.
Wu, Ye, Wu, Tianqi, Ge, Yuchen, Ni, Hongjun, Tan, Linwei, Lv, Shuaishuai
Study on the Severity of Aircraft Ice Protection System Performance in the Icing Envelope2026-99-061111/6/2026
In the process of design and verification of the aircraft ice protection system, a prediction model of ice protection system performance based on Severity Index(IPSI) is proposed, which quantifies the relationship between input and output energy of the ice protection system. In this research, a theoretical calculation method is developed, and the water total collection coefficient and convective heat transfer coefficient on the skin surface were obtained using CFD calculations and rapid neural network prediction methods. The consistency between IPSI and ice protection system performance is verified through an aircraft wing ice protection wind tunnel test. The results show that the lower the slat skin temperature in the ice protection area, the higher the IPSI value, which means the more severe the ice protection system performance. The ice protection performance severity analysis method is carried out for the cases in the CCAR/FAR/CS-25 continuous maximum(CM) envelope of an aircraft, and the IPSI values of each case at some altitudes are calculated, as well as the distribution of the ice protection system performance severity cases in the CM altitude-temperature envelope. The ice protection system performance severity cases are not the highest or lowest atmospheric static temperature in the CM envelope, in which atmospheric static temperature ranges from -8°C to -23°C from low altitude (1500 ft) to high altitude (22000 ft). When the flight speed is constant, and the atmospheric static temperature is gradually reduced, the IPSI value decreases. When the atmospheric static temperature is constant, and the flight speed increases gradually, the IPSI value increases. The influence of water evaporation heat transfer on ice protection performance severity is greater than that of convection heat transfer. The total air temperature for the most severe condition is always 0°C at every altitude. The IPSI calculation model can be used to quickly predict the severity of ice protection system performance in other ice protection areas of aircraft, even wind blades.
Hu, Weixue
Design of a Gantry-Type Intelligent Grasping Device for Logistics Warehousing Based on MaixCam2026-99-192511/6/2026
Traditional warehousing suffers from low efficiency, high manual error rates, substantial labor costs, and complex deployment, while existing sorting devices remain poorly adaptable for small- and medium-sized operations. To address these issues, this paper presents an intelligent gantry-type grasping device for logistics warehousing based on the MaixCam. The device integrates mechanical design, computer vision, and electronic control. An Arduino Mega2560 serves as the main control board, with 57-series and 42-series stepper motors and servo motors driving the gantry and gripper. The mechanical structure adopts a miniaturized gantry architecture constructed from alloy steel, enabling operation in confined workspaces. A YOLOv5s model with transfer learning was trained for cargo box recognition using a dataset of 654 images collected under various lighting conditions and backgrounds. The model achieves a recognition accuracy of 93%–96% with inference times of 10–14 ms at 25–28 FPS. The proposed device provides a viable solution for automated sorting in small-to medium-sized warehouses, balancing recognition performance, power consumption, and cost.
Xiang, Chang’an, Zhou, Dan, Fan, Zhiwei
A Method for Disordered Circlip Recognition Based on Improved YOLOv11 and Association Strategy2026-99-062211/6/2026
To realize automated grasping of randomly placed C-type circlips in automotive and mechanical assembly processes, this paper proposes an identification method based on the improved YOLOv11 algorithm and an exclusive association strategy. First, a detail enhancement convolution (DEConv) module is introduced into the C3k2 module of the YOLOv11 network to enhance the ability to capture the edges and high-frequency details of the circlips; Second, the parallel patch-aware attention (PPA) module is adopted in the detection head instead of the traditional convolution, and through multi-branch fusion and channel-spatial attention mechanism, it adaptively focuses on the key areas of small targets; Finally, the normalized Wasserstein distance (NWD) loss function is used instead of the IoU loss to alleviate the gradient disappearance problem in the positioning of small targets and improve the model’s detection accuracy. Based on precise detection, this paper innovatively proposes a circlip-hole association strategy based on multi-level spatial constraints, achieving accurate pairing of randomly placed circlips through bounding box-inclusive attribution judgment, distance screening, and selection of the best circlip-pair. Experimental results show that compared with the original YOLOv11 model, our model improves the mAP50 and mAP50-95 significantly by 5.7% and 3.3%, respectively; its association accuracy reaches above 95%, and the average processing time is 142 ms. Both in terms of accuracy and speed, our model meets the requirements of industrial real-time grasping and provides reliable prior information for the subsequent precise clamping of the robotic arm.
Wang, Chuang, Li, Jiyan, Wang, Yongming, Tan, Libin
Study on Contact Stress Distribution at Curvic Couplings Fitting Surface under Pretightening Force2026-99-192411/6/2026
The curvic coupling configuration serves as a foundational element for the joining and torque transmission of aero-engine rotors. The uneven contact stress distribution at its fitting surface can cause tooth surface wear and failure, which in turn leads to the vibration of the entire engine. The curvic couplings are fixed by the pretightening force. The pretightening force greatly influences the contact stress distribution characteristics at the fitting surface. The influence of the pretightening sequence and times on the contact stress distribution characteristics under pretightening force is analyzed in this paper. To reduce the non-uniformity of the contact stress profile, a pretightening force correction model under different pretightening conditions was established. The impacts of the pretightening forces before and after correction on the homogeneity of the contact stress profile were compared. The results show that multi-time pretightening and an appropriate pretightening sequence improve the contact stress profile characteristics. Applying the corrected pretightening force significantly reduces the non-uniformity of the contact stress profile. Specifically, applying the corrected pretightening force multiple times in sequence is effective in further reducing the dispersion of contact stress distribution at the fitting surface. Pretightening in a diagonal sequence is more efficient in improving the homogeneity of contact stress. The research will contribute to precision manufacturing as well as the regulation of aero-engine rotor systems.
Liu, Enxiao, Zhang, Meng, Dong, Jiaxu, Li, Zhibin, Tong, Jinyu, Zheng, Jinde, Liu, Yongmeng
The Structure Design of the Rail Car with the Secondary Buffering System2026-99-192311/6/2026
To address the poor cushioning performance of traditional rail car systems, this study proposes a track rail car equipped with a two-stage buffer system. Based on the dynamic principles of the two-stage buffer system, SolidWorks was used to model both the rail car body and its buffer components. The force distribution on the rail car under identical impact loads served as the evaluation metric for cushioning performance. Through theoretical calculations, the optimal spring stiffness configuration that minimized car body stress was identified. Motion simulation software was employed to conduct dynamic analysis and modeling of these configurations. Following this, 3D printing and assembly were performed, with experimental testing conducted on the assembled rail car to compare the effects of different spring types and damping mechanisms on cushioning performance. Performance parameters were optimized accordingly. Results demonstrated that, based on the optimal stiffness combination of the secondary buffering system, a friction damper could be added to further optimize buffer performance.
Zhang, Chi, Yao, Hai