Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current

Girstmair, Josef

Standardized Equivalent Tire Load Measurements Delivered by Suppliers to an OEM Enabling Consistent and Comparable Simulation Input

2026-01-0699

6/20/2026

Part- or component-level tests are commonly performed by Tiers and OEMs to investigate the NVH behavior and loading mechanisms. However, because test bench dynamics differ from those of the actual vehicle environment, correlating measured sound, acceleration and forces between bench and vehicle often proves challenging. Blocked forces offer a way to address this issue, as they provide test bench and vehicle independent load representations. This effectively enables different Tiers to deliver consistent load data, which OEMs can then use to better tune excitation and noise transmission on their vehicles. This paper focuses on 2 test bench compensation techniques, involving pure test and a simulation models of the tire to obtain accurate blocked-forces. The compensation techniques are validated on four testbenches of different companies.

Reichart, Ron, de Klerk, Dennis

Ergonomic Assessment of Glove-Box Design in Passenger Vehicles for the Indian Scenario

15-19-02-0009

6/10/2026

Passenger vehicles experience severe packaging constraints around the instrument panel, rendering glove-box operation a critical yet ergonomically underexplored interaction. Although glove-box interaction occurs frequently during routine vehicle use, its potential implications for ergonomic risk remain largely unexamined in existing automotive research. To isolate the influence of driver-side packaging constraints from component-level design effects, this study adopts a comparative evaluation of driver and co-driver glove-box interaction as a built-in control condition. This study introduces a discomfort-based evaluation framework that integrates Digital Human Modeling with India-specific anthropometric datasets. A composite loss-function scoring model is developed to quantify functional usability differences across four glove-box configurations, defined by variations in latch placement (center or side) and storage-bin mechanisms (fixed or rotating). Indians are utilized to assess

Jujjavarapu, Sreeram, Rajakumaran, Sriram, Kota, Srinivas, Kotkunde, Nitin, Jasti, Naga Vamsi Krishna

Conducting Measurement Systems Analysis for Rotor Balancing Tasks

AIR6966 (Current)

6/10/2026

This AIR provides a general guideline on how to perform effective measurement systems analysis study (MSA) for rotor balancing tasks. The document also includes applicable data analysis methods and result interpretation.

EG-1A Balancing Committee

Optimal Charging Planning with Energy Consumption Simulation for Battery Electric Long-Haul Trucks

2026-37-0019

6/9/2026

Vehicle fleet decarbonization is a key objective for the coming years, with electrification representing the primary pathway to achieving the targets set by the European Union. The share of battery electric trucks in new registrations has been gradually increasing especially in light and medium size trucks. The replacement rate of diesel long-haul trucks with zero emission trucks is still low due to challenges posed by added complexity and limitations of battery charging. Depot overnight charging is not sufficient to cover the energy needs of a truck covering large distances and careful planning of the route using public charging infrastructure is crucial for an optimized route minimizing extra costs and range anxiety. The current work aims to develop a methodology to propose the optimal charging locations for a given route of a battery electric truck based on nearby stations along the route. Our study uses an open-source optimization algorithm for the fixed route vehicle charging

Perdikopoulos, Michail, Doulgeris, Stylianos, Livitsanos, Georgios, Kazakis, Thomas, Mellios, Giorgos, Ntziachristos, Leonidas

Passenger Car Powertrain for Voltages above 800V

2026-37-0020

6/9/2026

The EU funded innovation project High-Voltage fast-charging Efficient electric vehicle Powertrains (HiVEP) develops innovative technologies for mass-market electric vehicles (EVs) by advancing architectures operating above 800 V. These architectures integrate silicon carbide (SiC)-based power electronics, rare-earth-free electric machines with active winding reconfiguration, high C-rate batteries, and optimized thermal management systems. HiVEP aims to enable fast charging in less than ten minutes, reduce energy consumption by at least 25%, extend the driving range by 20%, and cut system costs by up to 20% in volume production. This article deals in detail with the project objectives, the methodological approach, and the expected key innovations, as well as the technical, environmental, and social impacts. The discussion situates HiVEP within the European research and innovation landscape, emphasizing its role in accelerating adoption of sustainable mobility solutions.

Schernus, Christof, Nada, Shady, Neuhaus, Christoph, Ewald, Jens, Swierc, Daniel, Kallur-Krishnamoorthy, Rajesh, Vasiliadis, Harilaos

Investigation into Increasing Authority Involvement in the Automotive Development Process by Applying Best Practices from Aviation

2026-01-5021

6/8/2026

This study examines the involvement of authorities in the development processes of aviation and automotive industries by comparing the depth, frequency, and stages of their engagement. The background of this work is an ongoing research initiative focused on transferring methods from aviation to automotive. The method used in this study is an investigation of best practices across both industries. Based on this investigation, two proposals were developed for managing complex technologies, such as autonomous systems. Both proposals advocate for increased authority involvement, particularly during the early stages of projects. One proposal recommends making this enhanced involvement mandatory, while the other suggests it as a guideline rather than a requirement. To assess the benefits of these proposals, a human-input–based feasibility quantification method was applied. This method assesses feasibility on a scale from 0 to 10, where 0 represents the lowest score, 5 is neutral, and 10 is

Akkus, Yusuf, Annighöfer, Björn

Integrating Human factors and Predictive Modeling for Enhanced Aviation Safety: A Data - Driven Approach to Risk Mitigation and System Design

2026-26-0795

6/1/2026

This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence

Valiyaparambil, Praveen

Mitigating Cracking in COP Optics through Annealing and Step-Torquing

2026-26-0764

6/1/2026

Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted in aerospace lighting systems due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively low toughness and the presence of residual molding stress make them prone to crack initiation during mechanical fastening. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and evaluate potential mitigation methods. The investigation revealed that residual stresses in the COP material, combined with localized stress concentrations during screw tightening, were the primary drivers of crack initiation. Two complementary process improvements were identified and validated as part of mitigation plan: (i) annealing of the

S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen

Wear Resilience Characteristics of Silicon Nitride Strengthened AZ31 Magnesium Composite

2026-26-0740

6/1/2026

To develop magnesium matrix composites, ceramic silicon nitride (Si3N4) particles are added to the magnesium (AZ31) matrix at 2 wt.%. The composite is produced via disintegrated melt deposition vacuum-stir-casting procedure. Microstructural studies reveal the presence of Si3N4 particles and their uniform spreading. An L9 orthogonal array, planned using Taguchi’s experimental design, is selected for three wear parameters; axial load (AL), rotational speed (RS), and time duration (TD) with trials as per the G99 standard in the pin-on-disc apparatus to assess the wear resilient of the composite. Experimental results show an increase in axial stress, and wear loss (WL) increases dramatically. Because the area of contact shrinks as RS increases, WL diminishes dramatically. When the AL is low, the friction coefficient (CoF) increases, and when the AL is large, CoF drops. When the RS is increased, CoF decreases. To optimize multiple responses effectively, the TOPSIS (Technique for Order

Senthilkumar, N., Dhinakar Raj, C K

AI-Led Sustainability Strategy: Driving Product Value from Birth to Disposal

2026-26-0781

6/1/2026

Aerospace products operate within highly complex, safety-critical environments and endure extended lifecycles, often spanning decades. Sustaining their operational value requires rigorous management of Safety, Reliability, and Availability (SRA), while global Environmental, Social, and Governance (ESG) mandates demand parallel progress toward sustainability goals. This paper introduces an AI-driven strategy that integrates these dual imperatives—Sustenance Management and Sustainability Management—within a unified Product Lifecycle (PLC) framework. The proposed approach leverages Artificial Intelligence across five PLC phases: Generative Design, Detailed Design & Verification, Manufacturing & Industrialization, Operations & Maintenance, and End-of-Life Circularity. Anchored by a certified Digital Thread, this framework ensures seamless, auditable data flow from concept to disposal. Using Life-Limiting Parts (LLPs)—such as high-stress turbine discs—as a case study, the paper demonstrates

Srinivasan, Karthik, G.V.V., Ravi Kumar, Vaderahobli, Devaraja Holla, Bhate, Ujwal, Veluri, Sastry

Retrofit Vibration Mitigation of Launch Vehicle Structures Using Thin Viscoelastic Coatings: Acoustic and Modal Study

2026-26-0736

6/1/2026

Acoustic-induced vibrations pose a significant risk to launch vehicle hardware and payload reliability during critical phases such as lift-off and transonic phase. Reducing such vibrations is especially challenging when the hardware has already been fabricated, limiting the possibility of structural redesign. This study demonstrates a practical post-fabrication solution using a thin viscoelastic polymer coating applied externally to fully assembled hardware. Comprehensive evaluations were conducted using both acoustic testing and Experimental Modal Analysis (EMA) before and after coating application. During acoustic test, a substantial decrease in structure response from 150Hz to 2000Hz, with a reduction of approximately 50% in the grms values was observed for the coated structure demonstrating significant vibration mitigation over a wide frequency range. In contrast, EMA measurements using impact excitation revealed that the response transfer functions did not show a significant

Avirah, Nohin K, Panda, Ajay Kumar, Shaikh, Altafhusen

Effect of Strap-On Geometry on the Aerodynamics of Multibody Launch Vehicle

2026-26-0727

6/1/2026

Strap-on boosters play a crucial role in heavy launch vehicles by providing additional liftoff thrust without major changes to the baseline design, enabling launch with existing propulsion systems. However, strap-on boosters introduce additional pressure drag and alter the overall aerodynamics of the vehicle. While efforts have been previously made to derive empirical relationships to predict the aerodynamics of different strap-on configurations, most are case-specific and primarily limited to estimating drag coefficients (CD). The present study focuses on geometric parameters of strap-on such as length, diameter and radial gap between strap-on and core. The results are used to derive an empirical relationship which can be applied during preliminary design stage of a launch vehicle to predict axial force coefficient (CA), normal force coefficient (CN) and pitching moment coefficient (CPM), which are required for mission design and structural load estimation. In the current study

Muraleedharan, Archana P., G, Ramana Bharathi, S, Gnanasekar

Transforming Aircraft MRO with Agentic AI and Context Engineering

2026-26-0788

6/1/2026

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

Abburu, Sunitha, G.V.V., Ravi Kumar, Poovalingam, Sundaresan, Vaderahobli, Devaraja Holla

Evaluating Volume and Hardness change in Fluorocarbon and Ethylene Propylene Rubber Elastomers: Effects of Fluid Aging

2026-26-0758

6/1/2026

Abstract: This research paper investigates the performance of FKM (Fluorocarbon) seal material when exposed to a 50:50 ethylene glycol-water mixture. The study aims to determine the volume change percentage and Hardness change of FKM elastomers under standardized testing conditions. The experimental approach follows ASTM D471 and ASTM 2240 guidelines, focusing on weight and hardness measurements of the test samples to establish a success criterion. The results provide critical insights into the chemical compatibility and durability of FKM elastomers in Aerospace and industrial applications where ethylene glycol-water mixtures are commonly used. The findings contribute to enhanced material selection and design considerations for sealing applications subjected to glycol-based fluids. Samples of FKM material were immersed in the fluid at controlled temperatures and durations, simulating real-world operational conditions. The primary metric of interest, volume change percentage and

Yarolkar, Makrand, Patil, Sandip, Singh, Tanul

Automating Compliance Workflows in Aerospace Systems: A Scalable Framework for Specification Review and Requirement Mapping

2026-26-0714

6/1/2026

Compliance verification in aerospace systems often relies on labor-intensive workflows that demand extensive manual effort to produce structured review documentation and requirement matrices. These processes can span dozens of hours per review, are vulnerable to inconsistencies due to non-standardized annotations, and depend heavily on individual interpretation of fragmented technical sources. With a growing backlog of review tasks and a steady influx of new requests, the need for scalable automation has become increasingly important. This study presents a modular automation framework designed to streamline compliance assessments through intelligent document parsing, requirement extraction, and matrix generation. The system integrates optical character recognition, computer vision, and natural language processing techniques to process both scanned and digital documents. By digitizing data across multiple hardware configurations and automating extraction from diverse technical records

Mirani, Harsh, Baviskar, Yash G.

Comparative Study between MQTT 3.1 and MQTT 5.0: Evaluating Theoretical Enhancements Through Practical Throughput Benchmarks for Aerospace IoT Systems

2026-26-0711

6/1/2026

As aerospace platforms adopt increasingly interconnected architectures for avionics, telemetry, and predictive diagnostics, lightweight publish–subscribe protocols have become integral to communication efficiency. The Message Queuing Telemetry Transport (MQTT) protocol is widely employed due to its small footprint and low network overhead. The release of MQTT 5.0 introduces new control features—reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and improved error feedback—aimed at enhancing scalability and diagnostic reliability. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper evaluates MQTT 3.1 and MQTT 5.0 within aerospace IoT contexts using a Raspberry Pi–based experimental framework. The analysis is done using practical throughput benchmarks implemented via popular open-source tools like Eclipse Mosquitto Clients

Bhuyar, Prabhudev, M, Meghana, Kaniraja, Christina, Thomas, Tinto

Assessment of Injection Gate Location Effects on Mechanical Performance of Short Fiber Reinforced Plastic Components Using Digimat

2026-26-0746

6/1/2026

The mechanical performance of short fiber-reinforced plastic (SFRP) components is highly sensitive to fiber orientation, which is significantly influenced by the injection gate location during the molding process. Traditionally, gate placement decisions are driven by warpage minimization strategies, often overlooking mechanical performance under diverse load cases. This research introduces an automated workflow within Digimat-MS that integrates injection gate optimization into the early design phase, leveraging Integrated Computational Materials Engineering (ICME) principles. The proposed methodology enables engineers to upload either Marc, Abaqus or Ansys input decks, select a component of interest, assign material cards, and define gate scenarios. A Design of Experiments (DOE) is then executed locally or remotely, allowing Digimat to evaluate multiple gate configurations. The system aggregates results and identifies optimal gate locations based on the initiation of failure under

Kauthale, Tanmay, Madhavan, Vinay, Soni, Ganesh

Development of Graphene Filled Polypropylene Nanocomposite for Aerospace Application

2026-26-0739

6/1/2026

Polypropylene, a commodity plastic, is the semi-crystalline thermoplastics widely used in high volume for general purpose application. Polypropylene is the macro molecules of soft and weak backbone, which by reinforcement of fillers in different forms such as fiber, spheroids, nanotubes, flakes, etc., can influence its mechanical, thermal, electrical, creep resistance, and flame resistance properties for use in aerospace applications. Currently, polycarbonate and nylon plastics are used in aerospace applications, however, they are expensive compared with polypropylene. In this thesis, efforts are put to study the effect of reinforcement fillers in the properties of polypropylene composite, primarily the mechanical and flammability properties. The matrix element, polypropylene co polymer and reprocessed polypropylene blended in equal ratio, are coupled with the dispersing phases such as graphene, mica, fumed silica, and polydimethylsiloxane polymer. Effect of graphene as reinforcing

Govindaraju, Parthasarathy

Vibration-Based Methods for Non-Destructive Prediction of Buckling Loads

2026-26-0737

6/1/2026

Using vibration data to estimate buckling loads is proven effective for a wide range of structures, including rods, plates, and shells. The Arbelo formulation of the vibration correlation technique improves prediction reliability for cylindrical and spherical shells. In this study, we introduce a simplified variant of the Arbelo approach that provides higher prediction accuracy while requiring significantly lower pre-load levels. We define a new parameter, the Stiffness Decay Index (SDI), to characterize stiffness degradation by normalizing the loaded natural frequency with respect to the unloaded state. This metric enables accurate buckling prediction without causing structural damage or permanent deformation. We evaluate SDI numerically and experimentally for multiple isotropic geometries and demonstrate its advantages over the Arbelo method, particularly for ellipsoidal domes subjected to external pressure. We conduct experiments on rods, plates, oblate shells, and beverage cans to

Rangarajan, Gopikrishna, V, Vishwajith, Raju, Gangadharan, Dinavahi, Ramkrishna

Zero Waste Manufacturing in Aerospace: Circular Design Approaches from Concept to End-of-Life

2026-26-0775

6/1/2026

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

S, Chaitra

Research on Temperature Measurement Requirements for Seasonal Thermal Energy Storage Water Pits

2026-99-1705

5/22/2026

Solar seasonal thermal energy storage technology is an important means to solve the problem of seasonal uneven distribution of solar resources, and as the core component, the thermal storage capacity of the water pit directly affects the performance of the whole system. Accurately mastering the water pit temperature is essential for scientifically evaluating its thermal storage capacity. Based on the thermal storage water pit simulation software developed in the laboratory, this study focuses on determining the optimal number of temperature measurement points required for seasonal thermal energy storage water pits under an accuracy requirement of ±0.1°C, and establishes the mathematical relationship between the number of measurement points and the height-diameter ratio (H/D) as well as the inlet position. The proposed method can cover the temperature measurement point design for cylindrical and frustum-shaped water pits, and can also be referenced for prism-shaped configurations

Niu, Pengbin, Ma, Jianfu, Wang, Fangxing, Qi, Shiyu

Research on the Construction Scheme of Offshore Approach Embankment Based on Marine Environmental Elements

2026-99-1707

5/22/2026

222

Fei, Chengpeng, Chen, Mingbo, Zhou, Fang, Wang, Shiyue, Zhou, Siyang, Zhang, Fang

Inflow-Dependent Sensitivity of Layout Optimization Performance: A Case Study of the Lillgrund Wind Farm

2026-99-1738

5/22/2026

Layout optimization is one of the most effective approaches to reduce the power loss induced by turbine wakes. However, the performance of a wind farm is strongly affected by the inflow direction. This paper conducted a sensitivity analysis on a realistic wind farm, Lillgrund Wind Farm, to investigate the sensitivity of inflow direction on the power production of the initial layout and optimal limits. A wake model considering ambient turbulence intensity is adopted together with the wake superposition method to efficiently resolve the flow field in the wind farm. The results indicate that the power production of the initial layout had a significant discrepancy under different inflow directions, and relies on the consistency of inflow direction and layout array directions. The feature of the two main directional sectors is observed from a realistic wind rose. Therefore, two-sector wind roses are adopted in optimization, and the angles of sectors vary among 51 cases. After optimization

Yang, Kun, Deng, Xiaowei

Assessment of Flexibility Adequacy in Power Systems and Flexibility Resource Allocation

2026-99-1717

5/22/2026

With the introduction of China’s dual-carbon goals (carbon peak and carbon neutrality), renewable energy has experienced rapid development in the country, particularly wind energy, which has established a pivotal role within the new energy sector. However, the inherent fluctuations in wind power generation pose significant challenges to maintaining grid stability and operational reliability. In power systems where the proportion of installed wind power capacity has significantly increased, the allocation of flexible resources becomes crucial. These resources help the system adapt to fluctuations in wind power generation and load demand, avoid wind power curtailment, and reduce costs. In addition, energy storage enhances grid flexibility and stabilizes renewable energy, but is constrained by high costs. Therefore, optimizing energy storage allocation and improving its economic efficiency have become urgent issues. This study focuses on flexibility adequacy assessment and resource

Peng, Jian, Wei, Jinpeng, Zhu, Zhengyin, Hu, Jianmin, Li, Yuxiang, Miao, Gang, Zhang, Huaide

The Impact of Air Pollution on Clouds and Precipitation over Land and Ocean

2026-99-1701

5/22/2026

This study aims to summarize the influence of air pollution on clouds and precipitation over the ocean and land. This paper summarizes global aerosol observation networks, including GAW and AERONET, as well as aerosol observation networks from various countries. Six typical regions, including North America, North Africa, South Africa, India, China, and the Indian Ocean, demonstrate aerosols’ seasonal and compositional variation patterns. This study also summarizes the impact of aerosols on the microphysical characteristics of stratiform clouds and precipitation mechanisms. The effect of aerosols on clouds varies across regions over land and ocean, and the impact of aerosols on the cloud water path differs significantly. Air pollution significantly affects precipitation by altering the microphysical properties of clouds, and this study is of great importance for understanding and predicting weather changes.

Wang, Mingxin

Simulation Study on the Impact of Porous Media Microstructure on Gasoline Particulate Filter Performance

2026-99-1740

5/22/2026

Stricter environmental legislation is driving ever-more-demanding performance targets for gasoline particulate filters (GPFs). This study constructs a multi-scale filtration model based on fractal characteristics, taking into account particle size distribution and particle deposition, to investigate the influence of the microstructure of porous media on GPF performance and analyze the impact of structural parameters on capture efficiency and pressure drop. The results show that: (1) Increasing the wall thickness can improve the capture efficiency and pressure drop, and a thicker wall has a stronger inertial interception capacity for larger particles. (2) A reduction in porosity markedly alters both filtration efficacy and flow pressure drop. For particles in the intermediate size range (0.1-0.5 μm), the capture efficiency of a low-porosity structure is more sensitive to the diffusion deposition of small particles, while the inertial collision efficiency of large particles is higher. (3

Xiong, Xianyang, Qing, Ze, Zhang, Jian, Li, Ting

Computational Analysis of Platform Motion and Wave Effects on the Aerodynamics and Wake of the IEA 22 MW Floating Wind Turbine

2026-99-1735

5/22/2026

This study investigates the unsteady aerodynamic response, wake evolution, and vortex dynamics of an ultra-large floating offshore wind turbine (FOWT) under coupled motion–wave conditions. A high-fidelity aero–hydrodynamic CFD model is employed for the IEA 22 MW reference turbine. Platform pitch and surge motions are prescribed via sinusoidal functions, and wave conditions are independently introduced by considering two representative sea states (H = 4 m and 7 m) and a no-wave case. Results show that pitch and combined pitch–surge motions significantly amplify unsteady aerodynamic effects, increasing peak power from 81.1 MW (P5S0) to 92.6 MW (P5S5), with periodic negative power output and severe dynamic stall. Under strong motion, waves further raise peak power to 93.4 MW (H7P5S5), indicating a coupled amplification effect. Dynamic stall is mainly triggered by pitch motion, expanding in scope and duration with motion amplitude; wave effects on stall remain limited. Platform motion also

Xie, Bin, Sun, Haiying, Chen, Ye

Research on Carbon Emission Reduction of Structural Assembly Construction Technology in Metro Station Engineering

2026-99-1731

5/22/2026

To reduce the carbon emissions during the construction period of metro stations, two structural prefabrication schemes with varying prefabrication rates, based on the top-down construction method, were proposed and analyzed for their ability to study the carbon reduction potential of structural prefabrication construction technology in metro station construction, in comparison to traditional open-cut cast-in-place methods. A BIM model of the envelope and main structure of a metro station under construction in Qingdao was established to analyses the carbon emission impact factors of the metro station in terms of the consumption of materials, personnel, machinery, and transportation of each subcomponent project. The results show that the structural assembly construction technology can greatly reduce the work of support installation and dismantling, formwork installation and dismantling, and reinforced concrete pouring in the enclosure structure. With the prefabrication rate increasing

Gao, Guangyi, Wang, Zheyong, Dong, Silong, Gou, Jiayuan, Li, Yangqing, Zeng, Tiesen

Multi-criteria Evaluation of Green Power Supply Paths for Pinglu Canal Project During Construction

2026-99-1710

5/22/2026

In the context of the global active response to climate change and the strong advocacy of green development, China’s energy industry is demonstrating a steadfast commitment to low-carbon transformation. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. The core objective of the Pinglu Canal Project, a pivotal initiative promoting green and low-carbon development in the region, is to establish a “net-zero carbon” initiative by facilitating the supply of green energy throughout its entire life cycle. This initiative is designed to promote a green and low-carbon transition. This paper conducts an in-depth study on the green power supply path during the construction period of the Pinglu Canal project, and proposes four practicable options. In order to scientifically and objectively determine the

Huang, Zeyi, Wei, Yuchen, Li, Xiayang, Wang, Cuixian

Research on Carbon Emission Calculation Algorithm for Trucks on Expressways in Xinjiang

2026-99-1718

5/22/2026

In the field of measuring carbon emissions from road traffic, the carbon emission factor method has remarkable advantages in terms of standardization, operational simplicity, and adaptability. Backed by the IPCC international standard framework, this method offers convenient access to a dynamic factor database and incorporates an adaptive adjustment mechanism for real-world scenarios, such as technological advancements and regional disparities. Against this backdrop, this study employs the carbon emission factor method to establish refined measurement models based on load capacity and fuel consumption, respectively. These models are then applied to quantify carbon emissions from trucks on specific sections of the G30 highway in Xinjiang. The load-based model calculates emissions by integrating truck axle weight and driving distance, while the fuel-based model analyzes fuel consumption data in conjunction with driving mileage. A comparison of the two models in terms of measurement

Li, Maowen, Han, Dongchen, Gao, Yansen, Bai, Haotian, Dai, Xiaomin

Research on the Statistical Method of Real Driving Emission Data of Commercial Vehicle under Low Load

2026-99-1721

5/22/2026

xxxx

Tang, Gangzhi, Liu, Jiajun, Wang, Shuaibin, Du, Baocheng, Deng, Xuefei

The Spatial-Temporal Evolution of Coupling Coordination Degree Development of Carbon Emission-Passenger-Freight in Five Northwest Provinces

2026-99-1716

5/22/2026

Taking China’s five northwestern provinces as the study area, this paper investigates the spatial-temporal interactions among carbon emissions, passenger transport, and freight transport from 2010 to 2020. An entropy-weighted composite index is constructed for each system and integrated into a coupling coordination degree model to quantify interaction. It is found that (1) the average annual growth of provincial coupling coordination degree is 4.7%, but the gradient difference between regions is significant, and the extreme difference of coupling coordination degree between east and west reaches 4.5 times in 2020; (2) Spatially, it shows a unipolar leading pattern, with Shaanxi achieving a significant decrease in carbon emission intensity and Qinghai achieving a lesser coupling coordination degree of 23% in Shaanxi due to the high proportion of highway freight transport and single energy structure; (3) the driving mechanism analysis shows that the improvement of transport network

Qian, Yongsheng, Li, Shaoyuan, Zeng, Junwei, He, Qingling

Analysis on the Technical Path and Engineering Application of Ship Carbon Capture

2026-99-1730

5/22/2026

This study focuses on the engineering application and performance evaluation of shipboard carbon capture systems. A process combining amine absorption and membrane separation was constructed, and the combined process was applied to a typical 7000 TEU container ship. After sea trials, the average carbon dioxide capture efficiency achieved by the system exceeded 87%, and the power consumption was maintained within an acceptable range. The integrated system greatly improved the EEXI and CII index levels and verified its economic feasibility in the medium and high carbon price scenario. The payback period of the investment costs was reduced to five years. After port coordination tests, the operability of ship-shore carbon dioxide transfer was verified, which promoted future scalability. The engineering layout, energy recovery design, and operation data worked together to provide a practical solution for maritime decarbonization. This study provides a valuable technical reference for the

Yang, Yongjian

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

Patterson, Lori

Diffusion Framework with Cross-Modality Fusion Perception for Autonomous Driving in Urban Traffic

2026-99-0749

5/15/2026

End-to-end autonomous driving in urban environments faces three core challenges. First, camera and LiDAR sensor heterogeneity causes cross-modal perception inconsistencies and sensor fusion instability. Second, diffusion models suffer from training instability due to scale variance and distribution changes, which limits generalization. Third, traditional trajectory decoders lack structured interaction with semantic elements, thereby undermining planning rationality. To address these issues, CMFPNet introduces an integrated framework with three key modules. The HGCF-Backbone integrates LiDAR and camera features using channel focus, deformable cross-focus, and state space modeling to enhance semantic alignment. The NST module maps physical trajectories to normalized space, employing truncated diffusion sampling for stable generation in just 2–4 steps. The NDA models trajectory generation as a semantic narrative, utilizing a six-stage semantic attention flow incorporating BEV context

Qu, Yanwei, Mo, Hangjie

Adaptive Speed-Regulated Impedance Control for Robotic Ultrasound Scanning: Reducing Constant-Force Tracking Errors

2026-99-0751

5/15/2026

Robotic ultrasound scanning technology is a research hotspot in the field of medical imaging, and can achieve standardized and high-precision data acquisition. However, large force tracking errors occur during scanning, especially in complex human tissues, which can severely degrade image quality and diagnostic accuracy. Therefore, we propose an adaptive speed-regulated impedance control strategy to address this challenge, which innovatively combines the spline real-time interpolation and impedance control for constant force tracking. Firstly, the discrete ultrasound scanning paths are fitted to generate a smooth and synchronized interpolation trajectory. Then, the speed of the reference trajectory is adjusted in real time based on the Taylor formula to reduce the force tracking error. Experimental verification was conducted, and the results showed that the force tracking error increases with the increase of trajectory speed. In addition, at high speeds (e.g., 10 mm/s), the mean

Min, Kang, Zhang, Le, Shi, Yudong, Fang, Jin, Mo, Hangjie, Li, Xiaojian

Pattern-Guided Implicit Sentiment Analysis: Knowledge-Augmented Prompting with Aspect-Sentiment Joint Extraction for Automotive User Feedback

2026-99-0753

5/15/2026

Implicit sentiment analysis of automotive user feedback is crucial for understanding user opinions. Automotive user feedback often express opinions in an indirect way and are accompanied by a dense array of industry terms. Therefore, without costly fine-tuning, both aspect identification and sentiment analysis are rather difficult. We propose a Pattern-Guided pipeline for implicit sentiment analysis to achieve the joint extraction of aspect and sentiment. This pipeline first performs Pattern Anchoring, mapping colloquial expressions and slang to the standardized vehicle component knowledge system. Then, using Knowledge-Augmented Prompting, these domain rules are injected into well-designed prompt templates. In this pipeline, the large language model (LLM) is applied to output JSON records suitable for comprehending, including aspects, sentiments, confidence levels, and brief reasons. To enhance stability, we employ an improved prompt and consistency-driven confidence fusion to generate

Chang, Gengjia, Deng, Zuxing, Ma, Aonan, Yao, Jiangqi, Li, Xiaojian, Li, Ling

Optimization of Adaptive Mesh Refinement Strategy for VOF-DPM Method

2026-99-0726

5/15/2026

When simulating spray atomization process involving VOF method, a core problem is the conflict between high grid detail and limited computer power. Although VOF and DPM methods have recently been coupled to reduce computational cost, their application in practical engineering calculations still imposes a considerable computational burden. To solve this, a better adaptive mesh refinement (AMR) plan is put forward. This plan uses a 0.2 mm initial grid (twice the usual 0.1mm) and allows refinement up to four levels. This improved technique makes high computational efficiency for large-scale simulations. Two types of nozzles are employed to evaluate the proposed method. However, for circular nozzles, the new method does not increase calculation speed, while lowers the accuracy of the simulation.In contrast, for square nozzles, it greatly boosts computation speed and keeping high accuracy. This makes the technique a useful tool for modeling transverse jet atomization in industry. Overall

Zhou, Taotao, Ma, Ming, Zhang, Haitao, Zhang, Fengan, Chen, Xianhui, Chen, Qi, Xia, Hongwei

Design and Performance Research of an Integrated Thermal Management System for Hybrid Electric Light Trucks

2026-99-0735

5/15/2026

Addressing issues in traditional hybrid light trucks—such as low overall energy utilization efficiency and performance degradation of key components under extreme operating conditions—this study presents a novel, high-efficiency, integrated vehicle thermal management system. By coupling various subsystems, the system achieves efficient and rational utilization of the vehicle’s overall energy consumption. Comparative simulation analyses were conducted under different ambient temperatures and initial state-of-charge (SOC) levels to verify the reliability of the designed integrated thermal management system. Results show the system can meet the temperature requirements of all components under both high and low-temperature conditions. Meanwhile, findings indicate that ambient temperature and power modes have a substantial impact on the temperature of each component, and there is potential for utilizing motor waste heat. These outcomes provide a reference for the subsequent optimization of

Meng, Shun, Zhang, Chunyu, Zhang, Yu, Zhang, Dong, Yao, Mingyao, Qiu, Liang, Wu, Yadong, Qian, Yejian

Time Series Causal Discovery Based on Data Augmentation and Causal Validation

2026-99-0703

5/15/2026

Causal discovery within time series is crucial for revealing the actual causal mechanisms in dynamic systems, and it has major impacts in various fields like economics, healthcare, and climate science. Even though it’s important, accurately figuring out causal relationships from observational temporal data is still quite a difficult task. Traditional Granger causality based methods are often limited by noise sensitivity, large amount of data, and the inability to distinguish between real causality and false correlation caused by hidden factors. In order to solve these problems, this paper presents CausalAugVeri, which is a new algorithm that cleverly mixes data augmentation with causal verification to make causal discovery more solid and precise. This work has three main points: First, we carefully check that using convolutional data augmentation techniques can greatly improve how well time series predictions work, giving a steadier base for detecting Granger causality. Second, the

Yang, Jing, Chen, Xiaotao, Qin, Xuanli, Xu, Xianjun, Hu, Zhangxiang

Visual–Language Model–Driven Annotation and Analysis of Maneuver Data for Enhanced Vehicle Safety

09-14-01-0032

5/4/2026

Vehicle maneuver data are essential for perception and planning in advanced driver-assistance systems (ADAS) and automated driving systems (ADS). While high-quality annotations improve machine-learning performance, existing maneuver datasets remain fragmented, labor-intensive to annotate, and inconsistent in semantic richness. Challenges persist in scalability, interpretability, and contextual labeling. This article establishes a structured framework for maneuver data analysis by combining a systematic review of existing resources with the development of a new multimodal dataset. First, we conduct a systematic review of publicly available datasets such as HDD, KITTI, BDD-X, D2CAV, Brain4Cars, DrivingDojo, and the Driving Behavior Database. We further evaluate the data modality and sensor configurations including event data recorders, onboard logging systems, and smartphone sensing. We then propose the Matt3r Data Collection System with modern metadata management, which integrates video

Bai, Ling, Yuan, Chongyu, Osman, Islam, Lin, Zirui, Mirab, Ghazal, Saheb, Amir, Parnian, Neda, Shapiro, Evgeny, Shehata, Mohamed S., Liu, Zheng

Increasing the Competency and Confidence of Older Drivers in the Use of Advanced Vehicle Technologies: The MOVETech Randomized Controlled Trial

09-14-01-0013

5/4/2026

Programs that teach older drivers how to confidently and competently use advanced vehicle technologies (AVTs) are limited. The MOVETech study evaluated a training program specifically designed to teach older drivers how to use these technologies. Participants (n = 119) were randomized to the intervention (training program) or control group (brochure). The intervention involved an in-person classroom education session on the use and benefits of AVTs, and an on-road driving session where participants drove along a pre-defined route in a dual-controlled vehicle with instruction on AVT use by a driving instructor. All participants completed in-person and telephone assessments at baseline and 3 months. Driving performance and on-road AVT competence assessments were the primary outcomes. Self-reported driving confidence, competence, and confidence in use of AVT, crashes, citations, and count of vehicle damage were the secondary outcomes. Program fidelity was also evaluated using a checklist

Nguyen, Helen, Ren, Kerrie, Coxon, Kristy, Neville, Nick, O’Donnell, Joan, Cheal, Beth, Brown, Julie, Keay, Lisa

Are Drivers More Distracted with Level 2 Automated Technologies? A Naturalistic Driving Study Analysis of Frequency, Duration, and Proportion of Time Drivers Engage in Secondary Tasks

09-14-01-0028

5/4/2026

This project was designed to better understand how the activation of SAE International Level 2 (L2) system features affect the duration of secondary task engagement. Four naturalistic driving datasets were used: one that included drivers without L2 experience, two that included drivers with L2 experienced, and one that included drivers of L0 vehicles. Dependent variables that were assessed include frequency of secondary tasks, duration of secondary task, and proportion of time that drivers engaged in cell phone tasks when L2 systems were active compared to when L2 systems were available but inactive. Results suggest that both the frequency and proportion of time drivers engaged in secondary tasks were significantly higher when L2 systems were active compared to when systems were available but inactive. Drivers without L2 experience took longer to perform tasks involving the center stack/instrument panel compared to experienced L2 drivers. These results suggest that drivers demonstrate

Klauer, Sheila, Dunn, Naomi, Anderson, Gabrial T., Barnes, Ellen, Han, Shu, Fincannon, Thomas, Weaver, Starla

Understanding and Modeling Effectiveness of Predictive Risk Notifications for Early Assistance for Safe Driving: A Public Road Testing Study

09-14-01-0026

5/4/2026

While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information. Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in

Maruyama, Masaki, Koyama, Keiichiro, Ezaki, Toru, Sakamoto, Junichi, Sawada, Yuta, Matsuoka, Takahiro

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