Browse Topic: Collaboration and partnering

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Model-Based Flight Test Methodology Research for Transport Category Aircraft Stall2026-99-2340To be published on 10/30/2026
Model-based approaches have brought about a qualitative leap in enhancing flight test safety, improving the efficiency of concurrent engineering, and enabling knowledge reuse and sharing. Focusing closely on the engineering application of model-based methods in the field of stall flight testing, this paper systematically reviews the stall airworthiness certification requirements for transport-category aircraft. It proposes a stall flight test process model based on functional flow models and investigates a model-based design method for stall flight test point matrices. Furthermore, an improved practical approach for multi-disciplinary collaborative modeling, simulation, and compliance data analysis in stall flight testing is presented. Taking a specific aircraft type's stall flight test as an example, this paper provides a detailed description of model-based application cases across the pre-flight, in-flight, and post-flight phases.
Liu, Xu, Ding, Junliang
Research on Network Attack and Defense Technology in LEO Large-Scale Constellation Networking2026-99-298710/19/2026
With the rapid development of LEO large-scale constellations, space networks evolved into a critical domain of cyber confrontation. The heterogeneous architecture, open inter- satellite links and limited on-board processing capability introduce serious security risks. Aiming at advanced persistent threat (APT), data poisoning and spear phishing, this paper analyzes new attack mechanisms in LEO constellation networking, satellite-ground collaboration and communication - computation convergence scenarios. A satellite-ground-link collaborative active defense model is proposed to improve the security and stability of LEO constellation systems.
Guan, Mengmeng, Xia, Ming, Fang, Liang, Li, Ruxue, Lv, Xing
Robust Cross-Modal UAV Detection via Bidirectional Collaborative Energy Field under Weak Calibration2026-99-299210/19/2026
The precise detection and localization of 'low-slow-small' (LSS) unmanned aerial vehicles (UAVs) pose significant challenges in terminal defense scenarios. These non-cooperative targets have extremely sparse representations in radar point clouds because of their minimal radar cross-sections and appear as textureless, blurred patches in visual images. Furthermore, traditional multi-modal fusion paradigms rely heavily on rigid geometric projection matrices, which frequently fail under the mechanical vibrations, thermal deformations, and extrinsic perturbations inherent in rapid deployment environments, which often results in severe feature misalignment and contamination. To overcome these critical bottlenecks, we present an end-to-end cross-modal detection framework built on Bidirectional Collaborative Energy Fields (Co-Field). By redefining the 3D object detection task as an energy field reconstruction process within a latent multimodal feature space, we entirely remove the need for absolutely precise extrinsic parameters. Our framework uses a novel bidirectional mutual-guided interaction mechanism. Specifically, a vision-guided radar branch employs deformable cross-attention to adaptively aggregate highly discrete radar geometric features around visual semantic centers, achieving a feature-level soft alignment that implicitly compensates for calibration drift. Concurrently, a radar-corrected vision branch utilizes radar-derived geometric occupancy probabilities as depth anchors to gate and calibrate visual features, effectively suppressing the inherent divergence of monocular depth estimation. Ultimately, the framework regresses the target's precise 3D states and fine-grained categories directly from the extrema of the reconstructed collaborative energy field, circumventing complex heuristic post-processing. Experiments on the curated MMAUD dataset show that the proposed Co-Field method achieves better robustness. It remains highly effective even under severe calibration errors up to 10 degrees and achieves a 74.2% recall rate at extreme sparse distances ranging from 70 to 100 meters, and consistently outperforms state-of-the-art rigid and soft fusion baselines.
Peng, Chao, Shao, Peng, Ding, Qiao, Chen, Xiaoqing, Han, Aojia, Xu, Yuelei
Collaborative Design of Low Earth Orbit Multi-Layer Constellations for Coverage and Networking Performance2026-99-290710/19/2026
With the growth of global communication demand, multi-layer Low Earth Orbit (LEO) satellite constellation has become an important part of the next generation network. The multi-layer hybrid constellation can effectively improve the coverage performance and network connectivity through the cooperative work of satellites with different orbital heights. In this paper, a dynamic model of constellation topology is established for multi-layer LEO constellations. The index system of coverage and networking is constructed by using the strategy of fixed neighbor inter-satellite link (ISL) in the same layer and the nearest neighbor dynamic inter-layer link (ILL) between layers. Through simulation, the performance of single-layer and multi-layer constellation configurations is compared. The influence of design parameters such as orbital altitude, number of ILLs and inter-layer satellite resource allocation on the indexes of multi-layer constellation is analyzed. The simulation results show that the multi-layer constellation is superior to the single-layer constellation in terms of coverage continuity and network capacity with a fixed total number of satellites. As the number of ILLs increases from 1 to 5, the average shortest path length (ASPL) and the average inter-satellite propagation delay decrease, and the network capacity is significantly improved. Reasonable inter-layer resource allocation and link configuration can effectively improve the networking performance of multi-layer constellations.
Wu, Kejie, Chen, Quan, Li, Linhua, Liu, Erjiang
Global Task Graph-Based Multi-Agent Offloading for Dependency-Aware Satellite Edge Computing2026-99-296310/19/2026
Satellite edge computing (SEC) enables low-latency services by leveraging Low Earth Orbit (LEO) satellites. However, emerging applications increasingly generate dependency-aware tasks with complex precedence constraints, leading to challenging multi-DAG (directed acyclic graph) offloading under dynamic satellite environments. To address this issue, we propose a global task graph (GTG)-based multi-agent offloading frame-work named GTG-MARL, for dependency-aware task execution in regional satellite-ground collaborative networks. Specifically, we construct a GTG by merging multiple DAGs to capture both intra-task dependencies and inter-task coupling, thereby achieving unified dependency-aware modeling. Then, a graph neural network (GNN) is lev-eraged to encode the GTG into dependency-aware subtask embeddings. To handle dependency-aware offloading in dy-namic environments, we develop a multi-agent reinforce-ment learning framework based on generalized proximal policy optimization, where each LEO satellite acts as an agent for decision-making while a centralized critic stabilizes offline learning to eliminate real-time on-orbit communication overhead. During the execution phase, only the light-weight trained actors are deployed on satellites for on-orbit inference. Extensive experiments demonstrate that the pro-posed method significantly reduces task completion delay compared to state-of-the-art baselines, validating the practi-cal efficiency and low synchronization cost of the proposed framework for regional SEC deployment.
Geng, Zeao, Zhao, Lu, Jin, Huiying, Jiang, Ping, Cai, Hui, Zhou, Jian
Adaptive Slicing and High-Reliability Transmission Method for Spacecraft On-Orbit Data2026-99-292210/19/2026
Spacecraft On-orbit data are characterized by large volumes, stringent timeliness requirements, and heterogeneous data values, posing significant challenges to traditional satellite-ground transmission systems. To improve transmission efficiency and reliability under dynamic link conditions, this paper proposes an adaptive data slicing and collaborative reliability enhancement method. First, a joint evaluation model integrating Data Impact and Link Health is developed to evaluate data importance and transmission conditions. Based on the evaluation results, the slice size, priority allocation, and redundancy configuration are dynamically optimized. Second, a distributed collaborative verification mechanism combining Reed–Solomon erasure coding and multi-node arbitration is introduced to enhance data integrity and recovery capability. Furthermore, a mission-driven elastic scheduling strategy is designed to facilitate efficient resource allocation in multi-user transmission scenarios. Experiments were conducted on 100 telemetry files with a total volume of 1.9 GB in a simulated satellite-ground communication environment. Experimental results demonstrate that the proposed method improves average throughput by 25.3% and achieves a reconstruction success rate of 99.7% across 1,000 packet-loss reconstruction trials.
Li, Cheng, Liu, Peng, Chen, Xi, Cui, Yan, Li, Han, Li, Xian, Wang, Zhihui, Yi, Xiu
Optimizing Data Delivery for Ground Vehicle Teams2026-01-75399/22/2026
The radio-based wide area network (WAN) that forms the command-and-control backbone for deployments of multiple ground vehicles is a classic DIL (disconnected, intermittent, limited) communications infrastructure for bandwidth-intensive services like video streams, situational awareness feeds, and command-and-control messages. This paper describes an inter-vehicle network architecture that leverages the radio-aware routing features of an existing vehicle Ethernet switch/router to provide mission-optimized, fault-tolerant data delivery while minimizing both network overhead and vehicle SWaP requirements.
Al-Gharaibeh, Jafar, Bonney, Jordan
The Impact of Observability Constraints on the Planning for Employment of Robotic and Autonomous Systems2026-01-75149/22/2026
Employment of Robotic and Autonomous Systems requires a different paradigm of mission planning. The GTRI Missioneer for Organic Collaborative Kill-Chains (MOCKS) effort was developed to mature the concepts of mission planning in light of autonomy, where the decision making is distributed across the battlespace and each individual entity has limited awareness of global state. The paper presents some initial characterizations of the impact of constraints on periods out of communication, or no-comms windows, on the number of resources required for missions of a certain operational area. This metric, along with the foundational metric of remaining effective range margin are foundational to robust a priori planning.
Spratley, Michael
Comparative Evaluation of Cad Systems as Engineering Design Architectures2026-01-75469/22/2026
There is a need for advanced collaboration tools to meet the needs of increasingly complex engineering design challenges and of global design teams. Specifically, virtual design reviews are a means by which teams can obtain a better understanding of a product’s design. Many CAD systems have integrated cloud features, which can be utilized to perform design reviews within these systems. The focus of this paper is to evaluate CAD systems in three CAD architectures: traditional, cloud-enabled, and cloud-native, to assess their capabilities and highlight areas of improvement for CAD developers. Using a list of previously generated requirements, CAD systems were evaluated on how well they met each requirement to determine how they can foster collaborative work. While cloud-native CAD systems performed the best against the requirements, no CAD system was able to fully meet all requirements, showcasing multiple areas for future development.
Hughes, Katelynn, Petty, Emily, Mocko, Gregory M.
Design and Analysis on a Traction-type Power-assisted Follow-up Vehicle for Emergency Rescue2026-99-15479/11/2026
To address problems in China’s emergency rescue scenarios—such as limited functionality, insufficient mobility, poor adaptability to complex terrain, the labor-intensive nature of manual carrying, and the lack of flexibility of fully automatic carts—a traction-type emergency rescue power-assisted follow-up vehicle was designed and developed. With the core design goals of “lightweight, high mobility, and human-machine collaboration”, this power-assisted follow-up vehicle has multiple advantages. At the structural level, it supports rapid folding and unfolding, enabling convenient operation and adaptation to transportation needs in various emergency rescue scenarios. In terms of material selection, it balances strength and lightweight properties, and its key components possess anti-cutting and flame-retardant capabilities, allowing adaptation to the harsh environment of emergency rescue. The power system adopts modular replaceable batteries and is equipped with a high-performance control unit, motor, and shock-absorbing suspension design. This enables normal operation in a variety of complex terrains. The control system is centered on human-machine collaboration. It features simple operation and automatic adjustment of operating status, effectively reducing the operational burden and physical exertion of rescuers. Meanwhile, it supports the master-slave expansion function, allowing flexible switching from a two-wheel structure to a four-wheel structure to meet diverse rescue needs such as material transportation and casualty transfer. This power-assisted follow-up vehicle can effectively solve the material transportation problem in the “last few kilometers” of emergency rescue.
Xu, Jiang, Hou, Yumeng, Yang, Han
DisReID: Single Domain Generalizable Person Re-ID Method for Highway Construction & Operation2026-99-15309/11/2026
With the advancement of computer vision technologies and the widespread deployment of video surveillance systems, traffic safety and the development of intelligent highways have been significantly enhanced. As a key component of the intelligent video analysis module in smart highways, person re-identification (re-ID) addresses critical challenges, including cross-segment tracking of pedestrians illegally using emergency lanes, multi-camera joint searches for lost persons in service areas, and trajectory tracing of individuals involved in traffic accidents. These functions directly support the core goals of "safety assurance and efficient service" for smart highways. However, due to the complexity of the application scene, its generalization to unseen environments remains a core challenge. This problem is formally studied under the setting of Single-Domain Generalizable Person Re-identification (SDG re-ID), which aims to train a model on a single source domain that can perform well on arbitrary unseen target domains. To handle this issue, this paper proposes a novel Disentangled Augmentation re-ID Framework (DisReID) that disentangles and augments both structure and style. Specifically, DisReID consists of two modules: Structure-aware Viewpoint Simulation (SVS), a novel pre-processing technique that simulates cross-camera perspective changes by perspective transformation, diversifying geometric structure without harming identity semantics; and Style-Dominant Frequency Perturbation (SFP), which selectively focuses on the style-dominant frequencies and applies perturbation to enable controllable style augmentation while preserving structure cues. Furthermore, to alleviate the BN-induced domain bias, we introduce a simple yet effective test-time adaptation strategy, termed Cluster Fine-tuning (CF), that performs unsupervised clustering on target-domain features to assign pseudo-labels and subsequently fine-tunes the model, enhancing adaptability to unseen domains. Extensive experimental results on four public datasets demonstrate that our DisReID achieves superior generalization performance compared to the state-of-the-art methods. This work provides key technical support for the large-scale application of re-ID in smart highways, advancing the goal of "full-domain perception and intelligent collaboration".
Pan, Hong, Yu, Fangying
Dimensional Adaptability and Traffic Organization Analysis of Ships in Group Lockage2026-99-15109/11/2026
Aiming at the technology of electric intelligent working boat towing 4 ships in group lockage during the construction period of the Gezhouba Shipping Capacity Expansion Project, this paper, starting from ship dimensions, conducts an adaptability analysis on electric intelligent working boat towing ships in group lockage for all ships passing through Gezhouba No. 1 and No. 2 Ship Locks throughout 2024, based on the two-dimensional packing model, ship lock chamber scheduling model and algorithms, navigation scheduling rules and safety management regulations, the results show that ships unsuitable for being towed in group lockage through Gezhouba No. 1 Ship Lock account for approximately 26% of the total number of ships passing through it, while those unsuitable for being towed in group lockage through Gezhouba No. 2 Ship Lock account for approximately 57% of its total passing ships. Meanwhile, ships passing through the three Gezhouba ship locks on a specific day are selected, and an adaptability analysis on the dimensional suitability of electric intelligent working boat towing these ships in group lockage is carried out under the scenario where these ships only pass through Gezhouba No. 1 and No. 2 Ship Locks. The results show that the number of ships with suitable dimensions for group lockage accounts for the majority of the ships passing through the locks on a selected specific day. On this basis, combined with the operation modes of Gezhouba No. 1 and No. 2 Ship Locks, an analysis is carried out on the traffic organization, potential risks, corresponding countermeasures, and the required quantity of electric intelligent working boats for towing ships in group lockage, targeting the three main collaborative operation modes. The results can provide a basis for the future practical application of electric intelligent working boat towing ships in group lockage during the construction and operation periods of the Gezhouba Shipping Capacity Expansion Project.
Huang, Shaowen, Yang, Xi, Wang, Jian
Analysis of Latency-Influencing Factors in Vehicle-Road-Cloud Integrated Systems Based on Fault Tree Analysis and Analytic Hierarchy Process2026-99-15439/11/2026
Vehicle–road–cloud integrated systems have great potential in terms of improving traffic efficiency and achieving intelligent automatic driving through the integration of on–board terminals, roadside facilities, and cloud computing. However, their operational capabilities are heavily reliant on ultra-low-latency collaborative communication. This paper constructs a latency fault tree model to comprehensively analyze multi-source triggering paths of computation delay and reveals the formation mechanism of the delay path from “germination–induction–evolution”. On this basis, the Analytic Hierarchy Process is used to construct a three-level evaluation framework, and the influencing factors are quantitatively evaluated using NS-3 simulation data of the 004-V2X Communication Performance Testing Dataset. The result shows that the weight value of the network communication layer is the largest, 0.498, which shows that the bottleneck of performance in network communication is the wireless link quality. The cloud processing layer is second 0.327, which is dominated by the computational complexity and resource allocation policy. The impact of the onboard terminal layer is the smallest, 0.175. The FTA–AHP framework supported by empirical data can find the key factors affecting delay, which can help engineering optimization. It is noted that the AHP consistency check (CR) just checks the inner transitivity of expert judgment (i.e., the matrix consistency), while it cannot assure the objectivity and the bias elimination. We reduce the subjectivity by combining multiple experts, anchoring judgment with the simulation data, and performing a sensitivity check on the perturbation of the weights.
Xu, Yunchuan, Wang, Xiaomeng, Wang, Yan
Research on Multi-Condition Topology Optimization of Transport Ship Pillar Structure2026-99-12289/4/2026
Structural optimization in shipbuilding represents a significant research focus within the fields of naval architecture and marine engineering. This study investigates multi-condition topological optimization for the deck pillar region of a transport ship's sectional structure. A mechanical model incorporating six typical load conditions was developed, and the Analytical Hierarchy Process (AHP) was employed to quantify the weighting coefficients for each condition. This enabled multi-condition collaborative topological optimization of the pillar layout. The optimized configuration underwent model reconstruction and finite element verification. Results demonstrate that the proposed multi-condition collaborative topology optimization method effectively balances structural performance and weight reduction requirements while satisfying strength specifications. This method yields optimal pillar layouts meeting multi-condition constraints, providing a reference for multi-condition topology optimization studies in ship structures.
Pei, Zihao, Wei, Yi, Feng, Ruge, Liu, Kun
Automotive Engineering: September 202626AUTP099/3/2026
Bespoke at scale: How generative AI is rewriting the economics of manufacturing automation The economic logic behind factory software upgrades is breaking down. Navigating an increasingly complex engine oil landscape As the impending ILSAC GF-8, dexos 1 Gen 4, and a hybrid specification continue to obscure the North American landscape, passenger car engine oils need additive solutions that can help simplify blending operations and optimize product portfolios. High-temperature joint reliability Why preload retention matters more than fastener grade. Designing out corrosion at the wheel The case for advanced powder coatings. Editorial Where to? The challenges of automated driving around the world The Navigator Is China really our biggest automotive security threat? Better safety through collaboration at Toyota research center ATS 2026: automated driving is changing The software-defined technician: Manufacturing's next human capital revolution Aumovio says system can BAC with non-invasive finger touch How conveyors have carved a role in mastering manufacturing 2027 Mercedes-Benz S-Class: Same as ever, which is very good 2026 Lucid Gravity: Highly efficient luxury hauler Product Briefs Spotlight: Adhesives and coatings; sustainable materials Q&A How an automotive startup uses and doesn't use customer data
A Biohybrid Micro Swimmer Unaffected by CoatingTBMG-555368/1/2026
A team of researchers at the Max Planck Institute for Intelligent Systems (MPI-IS) in Stuttgart developed a biohybrid micro swimmer covered with magnetic material, whose swimming ability is largely unaffected by the coating. The team from the Physical Intelligence Department at MPI-IS published their work in the journal Matter, which covers a wide range of materials science research.
Microwaves Enable 3D Printing of High-Performance CeramicsTBMG-555448/1/2026
3D printing could change how we build parts for jet engines and power plants, but the process leaves microscopic holes that cause the materials to shatter. Published in International Journal of Extreme Manufacturing, Professor Fangyong Niu’s team in Dalian University of Technology have fixed the problem by doing something unconventional: They added a microwave.
Solid-State System Efficiently Generates Purified OxygenTBMG-555398/1/2026
Innovators at NASA Johnson Space Center, in collaboration with innovators at American Oxygen, have developed a solid-state system and process that separates oxygen from ambient air and compresses the resulting purified oxygen — with a significant reduction in power consumption compared to prior state-of-the-art. It is based upon a proven solid oxide electrochemical oxygen separation and compression technique that derives purified oxygen from ambient air and compresses it using an electrochemical pumping method.
Prototype Reflectarray Antenna Demonstrates Low-SWaP Anti-Jam Tactical SATCOM26AERP08_108/1/2026
This prototype array uses a small, lightweight, low-power, and low-cost aperture. Massachusetts Institute of Technology Lincoln Laboratory, Lexington, MA Preventing adversaries from interfering with communications is crucial to national security. Tactical satellite communications (SATCOM) focus on securing reliable communications channels against adversaries in contested environments. In support of this mission, a team from MIT Lincoln Laboratory is building a prototype antenna characterized by low size, weight, power, and cost (SWaP-C). Threats in contested environments - specifically proliferated low-Earth orbit (pLEO), where satellites must be as low-SWaP as possible because of the high volume of satellites present - are signal jamming and signals intelligence. Mitigating these threats through methods such as changing the shape of antenna beams in real time so that the ground user's signals can't be interfered with and preparing for future advanced capabilities are key to ensuring that satellites stay in communication with users on the ground.
Introducing the Modern Virtual Test Environment: Reducing Friction in RDT&E26AERP08_038/1/2026
Federal research, development, test, and evaluation (RDT&E) teams are operating in a data environment that looks nothing like it did a decade ago. Modern systems generate enormous volumes of information across sensor feeds, high-resolution video, telemetry, analytics outputs, and generative AI. Yet as data grows, the speed of insight often slows. There's a growing gap between the volume of data collected and its effective use in legacy testing environments. At the heart of the issue is coordination. Surveillance and sensing, planning, live experimentation, and post-test analysis are frequently managed in separate systems, teams, and locations, making it difficult to securely integrate and analyze data at speed.
Multi-Layer, Reconfigurable Batteries That Can Bend, Adapt, and Tune Their Own VoltageTBMG-555508/1/2026
A research team led by Professor Lin Gui at the Institute of Physics and Chemistry, Chinese Academy of Sciences, reports the first fabrication of multi-layer flexible batteries using a combination of liquid metal microfluidic perfusion and plasma-based reversible bonding techniques.
Modelling Failure Propagation in Material-Driven Collaborative Manufacturing Networks Using Cellular Automata2026-99-01207/31/2026
Collaborative manufacturing networks enhance production efficiency but are increasingly vulnerable to cascading failures due to their complex interdependencies, particularly in critical processes like gear manufacturing. This study addresses this challenge by proposing a dynamic modelling framework based on Cellular Automata. Utilizing manufacturing resource and task scheduling data, a material flow-driven Directed Acyclic Graph (DAG) is constructed to capture the network’s hierarchical topology. Key innovations include state transition rules with memory effects, where dynamic failure probability integrates neighbouring node states and historical failure records, governing normal node failure, recovery, and re-failure (with an attenuation factor reflecting enhanced resilience). The case study focusing on the gear manufacturing industry, through simulations on a 100-node gear production network, reveals spatiotemporal failure propagation patterns. By implementing resource redundancy configuration and material flow optimization, iterations generally converge around 35 steps, demonstrating significant self-recovery potential and strong network robustness in collaborative manufacturing networks. This approach provides a scientifically grounded tool for identifying cascading risks in collaborative manufacturing networks.
Bai, Hao, Kou, Zhida, Liang, Jingya, Zhang, Cheng
Implementation Strategies of Requirements Engineering in Commercial Aircraft Airframe Forward Design2026-99-01837/31/2026
Focusing on the requirements engineering activities, this study analyzed the problems in the implementation process of the forward design practice of commercial aircraft airframe, introduced the breakthrough methods, including the convergence and integration with the traditional design process, the supporting work organization model, process optimization, and specification, and proposed the airframe stakeholder need capture model based on the theory of systems engineering. Practice has shown that the requirements engineering implementation strategy introduced in this paper can effectively resolve conflicts and redundancies between the requirements system and the original top-level document system requirements. It ensures clear requirements sources, sufficient basis, reasonable allocation, controllable changes, adequate change assessments, clear design status, and controllable design risks. It effectively overcomes human resource bottlenecks during the early stage of requirements engineering implementation while cultivating talent reserves for systems engineering implementation, saving approximately 23.5 person-years in labor costs. It significantly optimizes non-value-added processes, reducing approximately 100 reports. It unifies the team’s understanding of requirements work, improves coordination efficiency, and significantly improves the requirements validation rate between aircraft-level and system-level requirements by an average of approximately 46%. It assists stakeholders and engineers in systematically and scientifically capturing product requirements during the design phase, with original product design specifications covering approximately 70% of subsystem specifications on average. Given its generality across the airframe forward design domain, the airframe requirement management paradigm established by this implementation strategy holds significant importance for the comprehensive and in-depth application of systems engineering methods in commercial aircraft development.
Sun, Luyan, Chang, Liang
Design and Development of a Durability Test Device for the Surface of Elderly-Friendly Mattresses2026-99-01397/31/2026
A test device for detecting the durability of the surface of elderly-friendly mattresses was designed and developed, which has functions such as force value monitoring, displacement monitoring, data recording, and hardness grade determination. Through the collaborative work of the mechanical system and the control system, high-precision reciprocating rolling tests and hardness grade determination on the mattress surface are realized. The verification test results show that the relative standard deviation (RSD) value of the mattress hardness grade test results is less than 10%, indicating that the detection data obtained by using this device is stable, meets the design requirements, and has operability.
Wang, Jin, Feng, Panpan, Shen, Guofeng, Zhang, Lei
Reliability Evaluation of CNC Machine Tools from a Design Team Perspective2026-99-01947/31/2026
Reliability evaluation aims to quantify the reliability level of equipment and to verify its compliance with reliability requirements. Existing reliability evaluation methods primarily rely on operational phase data, which means reliability evaluation may lag behind actual needs. In practice, both users and design teams are more concerned with how to estimate CNC machine tools’ reliability before they are put into operation. Moreover, current reliability evaluation methods usually ignore the design team’s influence on CNC machine tool reliability. To overcome these limitations, this study proposes a novel reliability evaluation method that accounts for the influence of the design team on the reliability of CNC machine tools. By analyzing the impact of the design team’s technical capabilities and reliability capabilities on CNC machine tool reliability, a set of quantifiable evaluation indicators was established. Then, the weight coefficients of all indicators were determined using the expert scoring method. Finally, all data were integrated using the vector projection method, which enabled a quantitative reliability evaluation of CNC machine tools from different design teams within the same category. Additionally, the proposed method was applied to conduct practical case studies on multiple CNC external cylindrical grinding machine tools designed by different design teams, thereby validating the feasibility of the proposed method. The reliability evaluation results not only determine the reliability level of each CNC machine tool but also identify the weak points in the technical capabilities and reliability competencies of each design team. This study concludes by discussing the significance of this approach for enhancing the reliability capabilities of design teams and its practical implications for end users.
Sun, Dongyang, Zheng, Weixu, Chu, Hongyan, Xu, Jingjing, Cheng, Qiang
Design of a Digital Twin Interactive System for a 3D Printer2026-99-08597/30/2026
This paper takes a 3D Printer proposed by the project team in the early stage as the research object, constructs a digital twin entity including 3D models and data models in order to develop a digital twin interactive software. By activating the real-time correlation between 3D models and data models, valuable data exchange can be achieved between the digital twin entity and the physical entity, and valuable data can be used to drive both to refresh their operating status.
Li, Qi, Wu, WenKai, Lang, ZhiQi, Jiao, HongCheng, Jing, Tao, Zhao, HanTao, Dong, Shen, Shi, Lei
North American CAV Performance Data StandardWP-00157/22/2026
As the deployment of connected and automated vehicles (CAVs) expands, the need for a consistent, cross-industry approach to performance relevant CAV data exchange is becoming more pressing. Vehicle developers, infrastructure owners and operators (IOOs), and technology providers generate and consume data that support safety, mobility, and operational efficiency, yet much of the data remains fragmented, inconsistently formatted, and difficult to reuse across systems. To address these gaps, the Society of Automotive Engineers (SAE) and the Canadian Standards Association (CSA) convened a multi-stakeholder workshop on November 3, 2025, with participants representing original equipment manufacturers (OEMs), automated driving system (ADS) developers, state and local agencies, standards bodies, and technology partners. The workshop focused on identifying challenges, clarifying needs, and outlining a path toward a North American CAV Performance Data Standard. Key themes from the workshop included: -The need for a shared data language to support safe and interoperable CAV operations. -The lack of consistent formatting, labeling and visibility regarding who produces and consumes data. -A “start small, iterate and scale” approach beginning with well-defined use cases. -The need for technical harmonization and governance structures that build trust and support sustained coordination. This white paper summarizes the key findings and outlines a practical approach to developing a Version 0.1 base-layer data standard that can support measurable progress in 2026 and beyond.
Nesheli, Mahmood
Privacy-Preserving UAV-Based Traffic Data Acquisition Platform2026-99-05957/10/2026
This paper puts forward a Privacy-Preserving UAV-Based Traffic Data Acquisition Platform to address 1) privacy leakage, 2) limited scenario coverage, and 3) low traffic data utilization efficiency in urban traffic monitoring environments. Our system integrates three innovations: 1) Dynamic Privacy Masking (DPM) and Dual-Track acquisition (DTC), which hides sensitive information (e.g., faces, license plates or LPL) in real-time while preserving critical traffic data (e.g., vehicle density, speed), 2) traffic data Localization (DL) and Privacy-Enhanced Federated Learning (FEFL), enabling cross-regional collaboration without raw traffic data sharing by perturbing neural network updates with differential privacy (DP), and 3) Ground-Air Collaboration (GAC) and VPF (VPF), combining UAVs with ground sensors and digital twins (DTs) to cover blind spots (e.g., tunnels, extreme weather). Experimented on UA-DETRAC and CitySim traffic data-sets, the platform achieves 92% privacy compliance (GDPR/PIPL), 87.5% mAP accuracy, and 85% road network coverage, outperforming other methods (e.g., FedUAV, static blurring). It supports applications such as traffic flow optimization, accident prevention, and regulatory alignment.
Zhang, Shilin, Yan, Ming
SAE TOMORROW TODAY - What Baja SAE Teaches That College Can?t135746/26/2026
What does it really take to engineer under pressure? From mud-soaked vehicles and broken suspensions to team dynamics and split-second decisions, Baja SAE has become a proving ground for the next generation of engineering leaders. By challenging engineering students to design, build, and race single-seat off-road vehicles capable of surviving extreme terrain, Baja SAE requires every team to use the same 14 hp Kohler engine -- creating an even playing field and putting the focus on innovation, durability, and teamwork. Listen in as Honda's Adam Hussemann and TTX Company's Jason Rounds pull back the curtain on the intense, unpredictable world of Baja SAE competitions and how they prepare students for careers in manufacturing, mobility, and beyond. After hearing this conversation, you'll understand why more and more companies value Baja experience just as much as a perfect GPA. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
SAE TOMORROW TODAY - Turning Streetlights Into EV Chargers135706/8/2026
What if the streetlights in your neighborhood could charge your EV overnight? Voltpost is making this vision a reality by transforming existing lampposts into modular, upgradeable EV charging stations managed by a mobile app. By partnering with utilities, the company is accelerating EV charging infrastructure deployment by retrofitting what's already in place. Listen in as we sit down with James Everley, Director of Business Development, to explore how Voltpost's streetlight EV charging solutions blend seamlessly into the urban landscape. From pricing that respects overnight charging habits to design choices that fit historic districts, you'll discover why low-power, on-street Level 2 charging is a critical piece of the broader EV ecosystem. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
Augmented Reality and Multimodal Interfaces for Astronaut Training and In-Orbit Operations2026-26-07966/1/2026
Augmented Reality (AR) and multimodal human–machine interfaces (MMI)— combining visual overlays, voice, gesture, eye- tracking, and biometric sensing—are maturing into flight-relevant technologies capable of transforming astronaut training and in-orbit operations. These interfaces can reduce task time, lower procedural errors, and mitigate cognitive workload, thereby strengthening crew autonomy and mission safety. Global operational experiences from International Space Station (ISS) augmented- reality trials and related international programs are synthesized to inform the proposed system architecture and validation framework: (i) an overview of India’s current AR/MMI-related ecosystem relevant to human spaceflight, including astronaut training pipelines and research collaborations; (ii) a mission-grade AR/MMI system architecture and multimodal fusion/decision logic suitable for human-rated operations; (iii) algorithms and programming examples for AR-driven finite-state-machine (FSM) procedures and workload-sensitive adaptation; and (iv) simulation-backed datasets across representative procedures indicating approximately 20 to 30 percent task-time reduction and approximately 40 to 50 percent error- rate reduction under controlled conditions (based on ten procedures and twenty-four simulated sessions for workload analysis). The findings reinforce that AR/MMI deployment can improve training throughput, reduce crew fatigue, and increase safety margins when designed with evidence gating, conservative confidence thresholds, and robust fallback modes. Recommendations include establishing a Human Space Flight Centre (HSFC) AR/MMI laboratory, conducting structured A/B validation trials, and committing resources for progressive demonstrations aligned with future in-orbit operations.
Yadav, Anoop Singh
Predictive Obsolescence Management2026-26-07806/1/2026
In the field of Aerospace, which has a long Life-Cycle process [20-30Years], Component Obsolescence has become a major problem as it prevents Maintenance & sustenance of a product with committed life-cycle period. Obsolescence Management plays a vital role by deriving strategic plans on proactive obsolescence where the system needs to be supported for several decades. This abstract analyzes the obsolescence challenges in the Aviation industry especially in Avionics System impacted by component obsolescence and present the possible proactive obsolescence management in terms of Engineering, Technology, and business/cost elements. The Obsolescence problem cannot be avoided but the impact of obsolescence and mitigate the risk can be minimized by planning and managing response. The obsolescence risk assessment for the Bill Of Materials (BOM) is a paramount activity to manage obsolescence proactively and cost-effectively. Digital Transformation of analyzing the component obsolescence status and integrated with statistical model to predict the End of Life (EOL) of sub-system/System. The EOL predictions would aid Obsolescence management plan, with mitigation strategies including Form-Fit-Function (FFF) replacements, component life extension through refurbishment, Lead-Free Control plan, component counterfeit and collaborative frameworks for modular, open-standard designs. This approach aimed at reducing unplanned costs by up to 40% on DMSMS (Diminishing Manufacturing Sources and Material Shortages) Management Plan, aligning with IEC 62402 (International standard for obsolescence management) and ARINC 662-1 (Guidelines for obsolescence management in commercial aircraft).
Dharmananyala, Rohith, Munirathnam, Krishna, Marokeyfrancis, Joisyjose, Sadashivaiah, Nagesh, Kondamari, Harshitha
Transforming Aircraft MRO with Agentic AI and Context Engineering2026-26-07886/1/2026
Aircraft Maintenance, Repair, and Overhaul (MRO) operations are highly complex, involving coordination among multiple stakeholders including airlines, MRO providers, OEMs, and regulatory authorities. A significant challenge in this space is managing unplanned events such as Aircraft on Ground (AOG) conditions, where delays can lead to major financial losses to airlines and safety risks. Engineers must quickly diagnose the damage, evaluate compliance against regulatory limits, coordinate with OEMs, and make critical decisions—all while navigating a fragmented ecosystem of disconnected systems, diverse document types, and time-sensitive processes. This paper presents a real-world, intelligent MRO solution that addresses these challenges through the use of Agentic AI and context engineering. The system is designed to automate and augment key MRO workflows such as damage detection, repair pathway selection, compliance verification, and supplier coordination. At its core, the solution is powered by a set of autonomous agents—each responsible for specific tasks like interpreting repair manuals, evaluating damage severity, or communicating with OEM portals. A key innovation of this system is its use of context engineering, which enables agents to share a unified, real-time view of the aircraft condition, document references, decisions made, and deadlines involved. This shared memory—dynamically updated using modern data stores and retrieval systems—ensures that agents and human experts operate with full situational awareness. The solution facilitates measurable improvements in reducing aircraft downtime, speeding up OEM coordination, and ensuring real-time continuous regulatory compliance. Engineers can take faster, more informed decisions with confidence, while human-in-the-loop oversight was preserved for critical steps such as compliance sign-off and final approvals. Overall, this intelligent MRO system transforms static, document-heavy processes into a dynamic, context-aware workflow. It brings together agent collaboration, regulatory alignment, and real-time information flow to solve one of the most pressing operational problems in aviation today. By improving inspection-to-repair cycles, enhancing SLA adherence, and enabling traceable, data-driven decision-making, this work lays the foundation for the next generation of digital MRO ecosystems that are efficient, safe, and scalable.
Abburu, Sunitha, G.V.V., Ravi Kumar, Poovalingam, Sundaresan, Vaderahobli, Devaraja Holla
Zero Waste Manufacturing in Aerospace: Circular Design Approaches from Concept to End-of-Life2026-26-07756/1/2026
Achieving zero-waste manufacturing in aerospace requires a shift from end-of-pipe waste mitigation toward circular design principles embedded early in product development. This paper presents a practical framework for integrating circularity into aerospace systems through five design pillars: design for modularity and disassembly, material substitution to enhance recyclability, waste segregation and characterization, component-level circularity readiness scoring, and collaborative supplier engagement. To operationalize this approach, a Circularity Readiness Assessment Tool (CRAT) is developed to evaluate design alternatives against criteria such as disassembly ease, material recyclability, manufacturing waste potential, end-of-life recovery pathways, and supplier take-back mechanisms. The framework supports multi-criteria decision-making by complementing traditional aerospace design drivers including weight, performance, cost, and safety. The methodology is demonstrated through a case study of an aircraft seating system. Scenario-based analysis indicates that targeted circular design interventions can reduce material waste and lifecycle carbon emissions while maintaining functional and regulatory requirements. Emphasizing practical engineering workflows rather than exhaustive lifecycle modeling, this work provides a scalable foundation for embedding circular design into aerospace product development and advancing zero-waste manufacturing objectives.
S, Chaitra
Glaring Vulnerabilities Discovered in Satellite CommunicationsTBMG-553116/1/2026
With $800 of off-the-shelf equipment and months’ worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking.
Advanced Materials Open New Possibilities for Medical DevicesTBMG-553336/1/2026
Materials innovations are shaping the next generation of medical devices. In this Q&A, Jeremy Schaffer, director of research and development at Fort Wayne Metals, discusses how advances in titanium, nickel-titanium, surface engineering, and smart materials are helping device developers improve performance, miniaturization, durability, and patient outcomes. He also addresses sustainability, scale-up challenges, and the collaborations needed to move promising materials from research into real-world medical use.
European Researchers Develop Self-Healing Composite Material for SpacecraftTBMG-553066/1/2026
Healable spacecraft structures could soon be possible thanks to cutting-edge composite technology. Swiss companies CompPair and CSEM, and Belgian company Com&Sens have partnered with the European Space Agency (ESA) to modify their self-healing carbon fiber product for use in space transportation.
Grain-of-Salt-Sized Neural ImplantTBMG-552846/1/2026
Researchers at Cornell University, working with collaborators, have created an extremely small neural implant that can sit on a grain of salt. Despite its size, the device can wirelessly transmit brain activity data from a living animal for more than a year.
NAWCWD Engineers Turned a Threat Simulator into an Offensive Electronic Attack WeaponTBMG-552996/1/2026
Keith Yuen, a supervisory engineer at Naval Air Warfare Center Weapons Division (NAWCWD) spent years building a jammer designed to defeat America’s own radars. The harder his team made it for friendly pilots to see through the jamming, the better they were doing their job.
How Robotic Micro-Actuators Are Enhancing Bone HealingTBMG-552676/1/2026
Smart implants that not only stabilize a fracture but also monitor the healing process from day one — and deliver targeted support when required — are currently being developed at Saarland University by a team of engineers, medical researchers, and computer scientists. The engineering team led by Paul Motzki is contributing shape-memory micro-actuators with integrated sensing capabilities, while Bergita Ganse and her research group provide the medical expertise in fracture healing.
Glaring Vulnerabilities Discovered in Satellite Communications26AERP06_096/1/2026
Researchers discover texts, phone calls, military communication, internal corporate networks all easily eavesdropped on using off-the-shelf equipment. University of California San Diego, La Jolla, CA With $800 of off-the-shelf equipment and months' worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking. Close to half of the communications beamed from satellites to the ground that the researchers were able to listen in on were not encrypted. This included sensitive data including cellular text messages, voice calls, as well as sensitive military information, data from internal corporate and bank networks, and the in-flight online activity of airline passengers.
European Researchers Develop Self-Healing Composite Material for Spacecraft26AERP06_116/1/2026
Researchers from CompPair and the European Space Agency have developed a new composite material for spacecraft with an embedded healing agent. European Space Agency, Paris, France Healable spacecraft structures could soon be possible thanks to cutting-edge composite technology. Swiss companies CompPair and CSEM, and Belgian company Com&Sens have partnered with the European Space Agency (ESA) to modify their self-healing carbon fiber product for use in space transportation. Project Cassandra - an abbreviation for Composite Autonomous Sensing and Repair - includes sensors and a heating element within a composite carbon-fiber material, allowing spacecraft to autonomously repair initial stages of damage.
SAE TOMORROW TODAY - Can Airports Become Innovation Labs?135685/21/2026
What if your airport was a living laboratory for innovation? Listen in as we sit down with Brian Cobb, Chief Innovation Officer at Cincinnati/Northern Kentucky International (CVG) Airport, to explore how CVG operates as a "city within a city," deploying emerging technologies to improve passenger experience, strengthen operational resilience, and reimagine the modern airport. Discover how CVG is advancing innovation through real-time TSA wait times, robotics testing, and the growing role of AI, autonomy, and cybersecurity. Get even more insight as Brian takes the stage as keynote speaker at the 25th anniversary of AeroTech(R) this June. He'll explore what's next for aviation innovation, from connected robotics and autonomous workflows to the standards and cross-industry collaboration needed to make it all work safely. To learn more and register, visit sae.org/events/aerotech. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
Low Voltage Ride Through Strategy for Grid-Forming Converters Based on Adaptive Line Impedance and Current Constraint2026-99-07365/15/2026
To address the challenge of balancing voltage support and current limitation in grid-forming converters (GFCs)—a challenge induced by the uncontrollability of active power during transient faults in microgrids and weak grids—a low voltage ride through (LVRT) strategy utilizing adaptive virtual impedance with a variable resistance-to-inductance ratio is proposed. This strategy is designed to maximize the satisfaction of reactive power support and current limiting characteristics. By adaptively generating virtual impedance based on changing line parameters, the method enables adaptation to large disturbance conditions involving variations in line impedance and Short Circuit Ratio (SCR). First, a transient model of the virtual impedance for GFCs is established to clarify the transient instability mechanism. During the transient period, the power loop is controlled to prevent power angle divergence. Second, the influence mechanism of virtual impedance on reactive current and output current during transients is analyzed. By integrating inrush current limitation and LVRT requirements, an adaptive virtual impedance control strategy is formulated to achieve collaborative optimization of transient LVRT and current limiting. Finally, the effectiveness of the proposed control strategy is verified through MATLAB/Simulink simulation experiments.
Pang, Bo, Yang, Xiangzhen, Liu, Fang
Saving Lives at Sea and on LandTBMG-551675/6/2026
A boat can sink in under a minute, stranding passengers miles from land and leaving them virtually invisible amid the vast expanse of water. Survival can depend on emergency supplies such as a personal locator beacon (PLB) and emergency position-indicating radio beacon (EPIRB) to alert search and rescue teams. When a competitive fishing trip went wrong for Easton Barrett and his friends 40 miles off the Gulf Coast of Mississippi in 2024, a PLB helped the U.S. Coast Guard rescue the people clinging to coolers and treading water after being head-butted by sharks.
Cooperative UxS Autonomy with Graph Neural NetworksF-0082-2026-01245/5/2026
This paper presents a spatio-temporal graph neural network (STGNN) centric approach to enable heterogeneous agents to collaborate and cooperate for different types of missions. The STGNN-centric approach and corresponding autonomy are encapsulated in the Advanced Graph-enabled Network Technology for Collaborative Autonomous Agents (AGENTCA) technology. Various decentralized and distributed control architectures are reported in the literature, but in some instances these approaches do not leverage the inherent graph network which can increase scalability to larger teams and algorithmic efficiency. Specifically, in this paper advances in artificial intelligence are leveraged to parameterize and encode optimal, or nearly optimal, swarm control techniques. For this work, the team focused on developing a diffusion-based STGNN swarm controller using imitation learning. An expert, centralized swarm control law was used to guide the STGNN during the learning process. The STGNN controller enables the swarm to follow a leader while avoiding static and dynamic obstacles and maintaining a desired separation distance from neighbors and obstacles. The approach is demonstrated in simulation with hundreds of agents and in flight tests with up to thirteen test vehicles.
Cooper, Jared, Lu, Chang-Tien, Chen, Siji, Carson, Andrew, Peters, Andrew, Olowin, Aaron, Ennasr, Osama, Lichter, Matthew
2025 Student Design Competition Undergraduate Winner: University of Maryland Draco Design Pioneering Hydrogen-Electric VTOLF-0082-2026-03455/5/2026
The University of Maryland undergraduate team presents Draco in response to the 42nd Student design Competition RFP "Pioneering Hydrogen-Electric VTOL". Draco uses a simple, effective configuration: a single main rotor helicopter with compounded wings. Through calculations and trade studies, the team was able to design a rotorcraft capable of performing the prescribed mission with maximized loiter endurance, while meeting all design constraints and requirements.
Renz, Sam, Cotoia, Colby
2025 Student Design Competition Graduate Winner: University of Maryland Wyvern Design Pioneering Hydrogen-Electric VTOLF-0082-2026-03445/5/2026
In response to the 42nd (2025) Annual VFS Student Design Competition, the Graduate Student Design Team from the University of Maryland introduces Wyvern, a novel hydrogen-powered electric compound rotor-craft engineered for maximum loiter and operational safety. Named after a mythical dragon that defies convention by not breathing fire, Wyvern only breathes water vapor by forgoing hydrocarbon combustion in favor of the quiet and clean power of hydrogen. This design reflects not only an aeronautical solution to an engineering challenge but a greater aspiration to reshaping how practical and clean vertical flight can be achieved.
Basak, Kumardip, Ogle, William
Synthesis of Whirl Flutter Predictions from Multiple Independent Analysis SolversF-0082-2026-00735/5/2026
A new approach that enables the synthesis of fully coupled system dynamics is described in this paper. The approach facilitates collaboration between solver developers by explicitly avoiding inter-code coupling and instead uses a generic interface that enables inputs to be set and flags outputs available to other solvers. The assembly of a fully coupled linearized system matrix is obtained entirely from the existence of coupling maps, and does not rely on user intervention. Tiltrotor whirl flutter in cruise conditions is systematically investigated by careful examination of results obtained through various combinations of domain synthesis and obtained from the Hermes coupling framework. Investigated solver domains include nonlinear rotor dynamics, nonlinear aerodynamics, and linear structural dynamics. Utilized software modules include RCAS; Project Chrono, a purpose-built lifting line aerodynamics solver; and FuselageSolver for linear structural dynamics. Aeroelastic predictions are synthesized and verified for a pitch/plunge airfoil and a low-speed wing. Rotor aeroelastic effects are verified by coupling rotor dynamics with rotor aerodynamics. Structure-to-structure results are synthesized by coupling both RCAS and Project Chrono rotor dynamics models to a pylon structure modeled in FuselageSolver. Finally, full whirl flutter predictions are synthesized by coupling Project Chrono, lifting line aerodynamics, and FuselageSolver, as well as an RCAS model without the wing/pylon structure to FuselageSolver. Results indicate that the new synthesis approach is viable and accurate.
Reveles, Nicolas, Van Damme, Christopher, Robinson, Joseph, Tuman, Matthew, Hansen, Josh
Enabling certified GoogleTest for safety-critical embedded software26AUTD05_135/1/2026
Software is driving major changes in automotive design. The rise of the software-defined vehicle, combined with increasing automation, is dramatically increasing software complexity. Automotive teams must deliver larger volumes of safety-critical code on tighter schedules while maintaining strict compliance with functional safety standards. In this environment, effective testing and verification are more important than ever. Development teams are increasingly adopting shift-left testing strategies, where defects are identified early at the unit level before software progresses down the development pipeline. Detecting issues earlier reduces risk, lowers remediation costs, and improves development velocity.
Camacho, Ricardo
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