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

Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction

2026-26-0718

To be published on 06/01/2026

Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds, and (2) a data-driven Recurrent Neural Network (RNN), specifically a Long Short-Term Memory (LSTM) network, for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, high-fidelity synthetic run-to-failure dataset under varying

Mohamed, Abbas

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

2026-26-0736

To be published on 06/01/2026

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

Aircraft Cabin Diagnosis – Inspection of the Aircraft Cabins and Seats Using AI

2026-26-0789

To be published on 06/01/2026

Aircraft interior defects, including seat structural damage, cushion degradation, liquid contamination, and foreign object presence, contribute to increased maintenance burden, extended ground time, and operational inefficiencies. Current inspection practices rely predominantly on manual visual checks, which are time-intensive and limited in detecting concealed anomalies. This paper presents a non-contact, AI-enabled inspection framework integrating millimeter-wave (mmWave) radar sensing with high-definition optical imaging for automated aircraft seat condition assessment. The proposed system captures interior scans when the aircraft is unoccupied and compares them against a digitally established baseline reference obtained under certified, defect-free conditions. Data fusion and machine learning algorithms analyze deviations to identify surface and subsurface defects at seat-level resolution and generate zone-based maintenance maps. The primary technical contribution lies in combining

Nagoal, Chandrasekhar Reddy, Prathipati, Krishna Chaitanya, Kandukuri, Ravindra

Effect of Fluid Flow/Time Duration on Static Voltage Generation for Aerospace Hose Assembly

2026-26-0757

To be published on 06/01/2026

Static electricity is an electrical imbalance on the surface of a material which can interact with other components having same or different materials. Fluid flow within the hose assembly generates static voltage due to friction caused by fluid flow in pipes, that needs to be appropriately quantified and dissipated. Accumulation of such static charge may lead to sudden discharge leading to spark generation. Spark generation around fuel flow might lead to system failure and failure in aircraft engines. Test experiments were conducted to analyze static voltage generated in hose assembly due to fuel flow with the objective that voltage achieved is within the acceptable range to avoid ESD (Electrostatic Discharge) failure. Procedure includes flow rate monitoring and voltage measurement using fuel as test fluid. The testing revealed that the curvature of the hose affects the readings, highlighting the importance of consistent meter alignment. Using a grounding strap is essential to prevent

Waghmare, Shashank

Enabling Circularity in the Aerospace Maintenance Ecosystem through Generative-AI Driven Back-to-Birth Traceability of Life-Limited Engine Parts

2026-26-0719

To be published on 06/01/2026

Circular-economy principles are increasingly central to aerospace sustainability strategies, aiming to extend asset life, improve asset valuations, and enhance benefits to stakeholders in the part ownership and maintenance lifecycle. In aircraft engines, achieving circularity hinges on safe reuse, repair, and recirculation of high-value components. Life-Limited Parts (LLPs) are among the most critical in this context, but their reuse is strictly contingent on complete Back-to-Birth (BtB) traceability. Any gap in BtB records—often due to fragmented data across multiple airline operators, shop visits, document formats, and time expanse—renders otherwise serviceable LLPs unusable, leading to premature scrappage and lost circular value. This paper presents a Generative AI (GenAI)-driven methodology to reconstruct and validate complete LLP BtB histories from heterogeneous, unstructured, and legacy maintenance datasets. By combining aerospace domain-trained language models with embedded life

Bhate, Ujwal, Jain, Dilip Kumar, Kulkarni, Ninad, Kalaiyarasan, Aravindh, Jha, Ashish, Shenoy, Karthik

System and Method of Strain Emulation Using a Beam Load Cell Test Setup

2026-26-0743

To be published on 06/01/2026

This novel method deals with emulation of Strain of a Structural Measurement System which includes software validation, acceptance tests and training. Current methods for simulating strain and force data for developing and verifying data acquisition (DAQ) software typically rely on costly electronic simulators or specialized hardware, making it challenging and expensive for developers, researchers, and small organizations to test their solutions under realistic conditions. To verify DAQ software, multiple specialized hardware solutions are deployed, that include Electronic Simulators, Commercial DAQ Modules and Hydraulic/Pneumatic test rigs. These technologies pose a challenge with limited flexibility and scalability options for small-scale prototyping, especially in budget-constrained scenarios. The sensors on these equipment may or may not be company approved inducing acceptance challenges. Our invention is an inexpensive, scalable, and mechanically simple alternative. Using a 3D

Murthy, Harsha, Bhat Venkatesh, Aditi, K Padmanabhan, Rahul, Madhu, Sheetal, Garag, Naveen

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

2026-26-0711

To be published on 06/01/2026

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

Aircraft Ground Deicing Training and Qualification Program

AS6286E (Current)

5/27/2026

This document establishes the minimum training and qualification requirements for ground-based aircraft deicing methods and procedures. All guidelines referred to herein are applicable only in conjunction with the applicable documents. Due to aerodynamic and other concerns, the application of deicing fluids shall be carried out in compliance with engine and aircraft manufacturers’ recommendations. The scope of training should be adjusted according to local demands. There are a wide variety of winter seasons and differences of the involvement between deicing operators, and therefore, the level and length of training should be adjusted accordingly. However, the minimum level of training shall be covered in all cases. As a rule of thumb, the amount of time spent in practical training should equal or exceed the amount of time spent in classroom training.

G-12T Training and Quality Programs Committee

Using a System Reliability Model to Optimize Maintenance Costs A Best Practices Guide

JA6097_201905 (Current)

5/26/2026

SAE JA6097 (“Using a System Reliability Model to Optimize Maintenance”) shows how to determine which maintenance to perform on a system when that system requires corrective maintenance to achieve the lowest long-term operating cost. While this document may focus on applications to Jet Engines and Aircraft, this methodology could be applied to nearly any type of system. However, it would be most effective for systems that are tightly integrated, where a failure in any part of the system causes the entire system to go off-line, and the process of accessing a failed component can require additional maintenance on other unrelated components.

HM-1 Integrated Vehicle Health Management Committee

Software Supportability Program Standard

JA1004_201205 (Current)

5/26/2026

In 1994 the SAE G-11 Reliability, Maintainability, Supportability, and Logistics (RMSL) Division chartered a software committee, G-11SW, to create several software standards and guidance documents across the RMSL spectrum, including a software supportability program standard. The committee was formed as a cross section of international representatives from commercial industries and governments. The G-11SW committee has attempted to develop a standard that is consistent with a SAE G-11 system level supportability program standard and augmented by necessary software-specific support information. The G-11SW committee believes this document reflects the best current commercial practices, and meets the objectives of the United States Department of Defense Acquisition Reform initiative. This document is performance based and is intended to be used by industries to address market demands for supportable software products that facilitate system evolution, time to market, and implementation of

G-41 Reliability

Design and Run-Time Information Exchange for Health-Ready Components

JA6268_202303 (Current)

5/26/2026

This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given

HM-1 Integrated Vehicle Health Management Committee

Multi-Objective Reactive Power Optimization Method for the Distribution Grid with Distributed Generator

2026-99-1702

5/22/2026

To enhance the economic efficiency and operational security of distribution grids, this paper develops a reactive power optimization model that incorporates distributed power sources. The model aims to minimize the costs of reactive-load compensation equipment, reduce voltage deviations, and lower network losses while satisfying operational constraints. To overcome the common drawbacks of the standard genetic algorithm—such as limited optimization precision and a tendency to converge to local optima—four improvement strategies are introduced. These include an enhanced encoding scheme, an initial population generated via opposition-based learning, an elite retention strategy, and the adaptive adjustment of crossover and mutation rates. Together, these modifications strengthen the algorithm’s global search capability. The proposed approach is validated using the IEEE30 node system. Compared with both the conventional genetic algorithm (GA) and an adaptive genetic algorithm, the improved

Wang, Maoze, Xiao, Wenyu, Liu, Yujia, Xu, Zhengwei, Xia, Yinyong

Guide to Engine Lubrication System Monitoring

AIR1828D (Current)

5/15/2026

This SAE Aerospace Information Report (AIR) provides information and guidance for the selection and use of technologies and methods for lubrication system monitoring of gas turbine aircraft engines. This AIR describes technologies and methods covering oil system performance monitoring, oil debris monitoring, and oil condition monitoring. Both on-aircraft and off-aircraft applications are presented. A higher-level view of lubrication system monitoring as part of an overall engine monitoring system (EMS) is discussed in ARP1587. The scope of this document is limited to those lubrication system monitoring, inspection, and analysis methods and devices that can be considered appropriate for health monitoring and routine maintenance. This AIR is intended to be used as a technical guide. It is not intended to be used as a legal document or standard.

E-32 Aerospace Propulsion Systems Health Management

Research on Fault Diagnosis Agent of Monorail Crane Based on Knowledge Graph and Lightweight Large Model

2026-99-0741

5/15/2026

The monorail crane is important in mining operations, and its operation affects both safety and efficiency. Currently, fault diagnosis for monorail cranes has several challenges, such as heterogeneous mixing of multimodal data, poor use of knowledge, low real-time requirements, and high deployment costs for large-scale models. To solve these problems, we present an agent framework using a multimodal knowledge graph and a lightweight large model. In particular, we construct a fault knowledge graph for monorail cranes, organizing professional knowledge about components, failure modes, symptoms, and maintenance. By employing retrieval-augmented generation (RAG) technology, the knowledge graph is merged with the Qwen lightweight large model (low-rank adaptation) for fine-tuning to develop a diagnostic agent with task planning, tool invocation and memory. The experimental results show that the agent framework reduces “machine hallucination” and outperforms conventional diagnostic accuracy

Zhang, Yixuan, Xue, Shun, Bi, Xiang, Wei, Xing, Kang, Ranyu, Jue, Jie, Cheng, Liruiran

CauExecutor: A Causal Executor for Causal Effect Estimation

2026-99-0721

5/15/2026

Causal inference from observational data, particularly the estimation of a treatment’s causal effect on an outcome, has long been challenging, primarily because it hinges on correctly identifying confounders. This is typically accomplished in two main ways within causal inference frameworks: either by using causal discovery algorithms to recover the underlying causal structure through a causal graph, or by assuming that the relevant confounders are already known. Both approaches have been shown to be unreliable or simply infeasible in practical applications. Although large language models (LLMs) are advancing rapidly, their emerging capabilities in causal inference have only recently begun to receive significant attention. Nevertheless, LLMs currently lack the ability to directly interpret structured tabular data, which is widely used in causal inference. To address this limitation, we introduce a novel framework, CauExecutor, for causal inference. Our framework enables a novel

Yang, Jiaoyun, Chen, Jinxi, Yin, Yue, Liu, Li, Li, Lian, An, Ning

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

Crowd Counting Network for Risk Early Warning in Exhibition Scenarios

2026-99-0705

5/15/2026

As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to

Zhang, Jin, Zhang, Wanyue, Yuan, Jingjing, Chen, Zhen, Gu, Dazhi

Cabbage Cleaning Device Based on Fischertechnik Model

2026-99-0734

5/15/2026

This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD

Chen, Yuhui, Zhang, Yixuan, Ruan, Jia, Zhu, Huayun, He, Lianzheng, Zhao, Ping

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

Compound, Cleaning, Foaming, for Aircraft Surfaces

AMS79_017 (Current)

5/11/2026

This SAE Standard specifies requirements for a foaming liquid cleaning compound which, when diluted with water 1:9 v/v, is suitable for cleaning the soiled exterior of Service aircraft. The cleaning compound may be applied by spraying, either as foam or liquid, by brushing or by swabbing. The surfaces to be cleaned may be unpainted metal or surfaces painted with glossy or matt schemes, including strippable acrylic paint complying with DTD 5599. This Standard includes tests to limit specific forms of corrosion that affect aircraft structural materials.

AMS J Aircraft Maintenance Chemicals and Materials Committee

Fire Prevention on Forestry Machinery

J1212_202605 (Current)

5/7/2026

This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.

MTC4, Forestry and Logging Equipment

Airborne Icing Tankers

ARP5904A (Current)

5/7/2026

This SAE Aerospace Recommended Practice (ARP) document establishes criteria and recommended practices for the use of airborne icing tankers to aid in design and certification of aircraft ice protection systems and components. Several icing tankers are described, along with their capabilities and suggested use. Sample data for these tanker spray systems are included, shown with 14 CFR Parts 25 and 29, Appendix C icing envelopes for continuous maximum and intermittent maximum icing conditions. (Note: In the remainder of this document, the phrase “Appendix C icing envelopes” will be used for brevity.) This ARP is intended as a guide toward standard practice and is subject to change to keep pace with experience and technical advances.

AC-9C Aircraft Icing Technology Committee

Can Multi-Fingered Robots Transform Shipboard Operations and Autonomous Maintenance?

26AERP05_12

5/1/2026

USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics. University of Southern California, Los Angeles, CA In dynamic, unstructured environments like ship decks and even home kitchens, robots today still struggle to perform precision tasks such as tightening bolts or handling wires. This makes critical ship maintenance tasks difficult. USC researcher, Erdem Bıyık, aims to advance robots' finger manipulation and integrate human feedback to enable real-time learning for robots in an upcoming three-year, $750,000 project funded by the Office of Naval Research (ONR).

Directional Stiffness Decoupling in Meta-Wheels via Three-Dimensional Discrete Curved Spokes

15-19-01-0005

4/22/2026

Meta-wheels—non-pneumatic wheels whose performance is governed by structural geometry rather than internal pressure—offer new opportunities for directional stiffness control. Yet achieving independent tuning of longitudinal, lateral, and vertical stiffness within a single wheel architecture has remained challenging due to the inherent coupling in conventional radial and planar curved spokes. In this study, we introduce a three-dimensional (3D) discrete curved-spoke design that provides explicit geometric control through two independent parameters: the in-plane curvature angle (α) and the out-of-plane inclination angle (β). Using spoke-level and full-wheel finite-element (FE) simulations, supported by a simplified cantilever-beam analytical model, we show that these two geometric parameters govern stiffness in fundamentally different ways. The curvature angle α serves primarily as a geometric softener, reducing stiffness in all directions while maintaining a high top-loading ratio (TLR

Han, Heeseung, Liu, Zhipeng, Ju, Jaehyung

J1939 Digital Annex

J1939DA_202601 (Current)4/10/2026

This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.

Truck and Bus Control and Communications Network Committee

J1939 Digital Annex

J1939DA_202604 (Historical)4/10/2026

This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.

Truck and Bus Control and Communications Network Committee

Fast and Robust CFD Simulation Method for Water Management in Automotive Interior Design

2026-01-0487

4/7/2026

Understanding the fluid flow behavior over and into narrow gaps is crucial for many industrial applications, particularly in the automotive sector. Evaluating the potential of water ingress into narrow pathways and towards components is of great importance to design the water management of such components. The employment of CFD simulations supports the evaluation of potential water ingress into such gaps. Lagrangian based tools are used in a variety of simulation scenarios of fluid flow, especially due to their ability to easily simulate free surfaces with strong curvatures. In our previous work, a validated simulation setup was developed using the meshless simulation tool MESHFREE from Fraunhofer ITWM [8] for simulating water entering small gaps. Especially for industrial use cases, the computation time of several days is too expensive. Thus, we enhanced this approach to a fast and robust CFD simulation that realizes industrial use cases within appropriate time. The development was

Zrnic, Dino, Konstantinovics, Athena, Kospach, Alexander, Rugerri, Evelyn, Loy, Michael, Bäder, Dirk, Michel, Isabel

Curb Impact: Non-linear Structural FE Analyses in Multibody Dynamics Models

2026-01-0219

4/7/2026

In a few extreme customer abuse load cases such as curb impact and potholes, automotive structures see non-linear (plastic) deformations as well as large rigid body motion. The load cases can be simulated by a few tools: crash analysis tools such as LS-Dyna, non-linear structure analysis tools, or multi-body dynamics (MBD) analysis tools like Ansys Motion. The three simulation tools have pros and cons, respectively. In this study, a curb impact simulation was performed using the multi-body dynamic approach with nonlinear structural analysis capabilities included in Ansys Motion. The tool demonstrated the simulation was completed faster than other MBD tools due to smartly recycling the system Jacobian matrix when structural deformation was not significant. The results were compared with structural analysis and correlated reasonably well. The post-impact suspension alignment changes can also be simulated for reviewing design requirements. This approach proposes a new way to simulate

Hong, Hyung-Joo, Kim, Wangoo

The Cure for Overgrown Process Garden or Why Engineers Have Given Up with ASPICE

2026-01-0067

4/7/2026

The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. Such degradation can be attributed to new additions to the processes and introduction of FuSa and Cybersecurity standards. The processes try to keep up with the shift from the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for

Weber, Matthias, Kmiec, Mateusz, Romijn, Marcel, Nedkov, Detelin

Culture Clashes: LLM Support in the Engineering of Safety-Critical Systems

2026-01-0110

4/7/2026

The proven usefulness of large language models (LLMs) as tools for software development and the recent rapid increase in their capabilities have made it possible and attractive to extend their scope of application to almost all tasks in the engineering of complex and even safety-critical systems. While these tools promise substantial efficiency gains and improved engineering productivity, they remain prone to errors, and the generated artifacts may not meet the stringent quality requirements for safety-critical systems. In this paper, we systematically analyze potential applications of LLMs throughout the engineering lifecycle of safety-critical systems and identify associated risks as well as practical approaches to risk mitigation. We classify LLM-supported use cases according to LLM autonomy, impact, and artifact observability, and compare the corresponding mitigation strategies with established approaches used for traditional engineering automation. In addition, we examine the

Thomas, Carsten, Wagner, Michael

Optimizing Weld Placement in Automotive Structures Using Topology and Multi-Disciplinary Approaches

2026-01-0514

4/7/2026

This work presents two approaches for weld optimization aimed at reducing manufacturing cost and process time, while meeting structural performance requirements in automotive structures. The first approach uses topology optimization to identify the most efficient weld layouts. A design space is generated along mating flanges, joints, and panel interfaces, where potential weld locations are defined. Welds are treated as discrete design variables, and the topology optimization systematically evaluates their contribution to global stiffness and load path integrity. Non-critical welds, those with minimal impact on stiffness, durability, or crashworthiness, are eliminated, resulting in a minimized weld pattern that maintains structural performance. The second approach applies Multi-Disciplinary Optimization (MDO) to balance weld reduction with performance targets across multiple domains, including linear and non-linear stiffness, crashworthiness, and fatigue. Using a preprocessing tool

Koppaka, Vinaya, Yoo, Dong Yeon, Chavare, Sudeep

A Quantitative Approach for Mapping and Assessing Diesel Particulate Filter Regeneration Events in Diesel Engines

2026-01-0377

4/7/2026

Regeneration of diesel particulate filters (DPFs) is crucial for maintaining the performance of diesel engines and minimizing harmful particulate matter (PM) emissions from exhaust. However, conventional regeneration strategies often suffer from incomplete soot removal and inefficient monitoring. These issues lead to increased exhaust back pressure, reducing engine efficiency, and potentially damaging the particulate filter. In this paper, an approach is proposed for mapping and quantifying the real-world DPF regeneration process for diesel engines complying with the stringent emission standards. We introduce a novel metric, the differential pressure drop percentage (DPDP), to detect regeneration events and quantify soot burn quality. The proposed method utilizes real-time sensor data obtained through the vehicle’s On-Board Diagnostics (OBD) system. The algorithm processes sensor data and robustly maps the regeneration quality. The performance of regeneration event detection and soot

Bagga, Harleen Kaur, Nagare, Mukund B., Patil, Bhushan D., Ravishankar, Hariharan, Melapudi, Vikram, Vanderheide, Craig, Patil, Abhijit

Innovation Powered by High-Fidelity Multiphysics Modeling: A Holistic System Optimization of BorgWarner’s Next Generation Integrated Drive Modules

2026-01-0497

4/7/2026

In the stringent market of BEV, the development of integrated Drive Modules (iDM) fitting environmental and customer needs is mandatory. It is important to extract the best from the less. To achieve those goals, a deep insight into complex multiphysics phenomena occurring in an iDM has been achieved by accurate and validated models. This engineering methodology is applied through the development of BorgWarner products, comprising non-exhaustively iDM 180-HF, Externally Excited Synchronous Machine and Multi-Level Inverter. The paper will review the methodology development for deeper understanding involving in-house technical excellence and complemented by strategic partnerships with academic institutions and start-ups. It will present the approach of integrating advanced multiphysics models with high-quality experimental validations, specifically on loss evaluation on electrical machines and inverters. Complex models involving multiphysics such as thermal/fluid coupling or electric

Leblay, Arnaud, Bourniche, Eric, Bossi, Adrien, David, Pascal, Nanjundaswamy, Harsha

Optimal Vehicle Sampling for Fleet-Wide Emissions Monitoring using Submodular Maximization

2026-01-0283

4/7/2026

This article addresses the problem of optimal vehicle sampling for fleet-wide in-use emissions monitoring, a necessity driven by the absence of direct emissions sensors in modern production vehicles and the variable impact of in-use changes and operational factors (mileage, time-in-service, workload) on emissions performance across a fleet. Recognizing that comprehensive fleet testing is impractical due to significant downtime and cost, we propose a novel approach to identify a small, yet optimally informative subset of vehicles for sampling. The proposed approach leverages submodular function maximization, a technique rooted in optimal experimental design, specifically D-optimal design, to maximize the determinant of the information matrix (e.g., of XTX, where X is the regressor/design matrix in the case of a linear in parameters model). This approach ensures that the collected data yields maximum information for refining and building accurate models for emissions changes. We compare

Zhang, Jiadi, Li, Xiao, Kolmanovsky, Ilya, Tsutsumi, Munecika, Nakada, Hayato

Sensitivity Analysis and Development Approach of HV Battery Lifetime for Complete Vehicle Integration

2026-01-0395

4/7/2026

The lifetime and aging of the high voltage battery is one of the major discussion points for the end-customer to decide between buying a car with an electric powertrain or still using a conventional powertrain. Therefore, the provision of adequate vehicles to the end-customer, the aging of the high voltage battery become an important topic for the complete vehicle development. In addition, also legal regulations (e.g. EU7) will preset minimum requirements for the warranty of the high voltage battery. These circumstances define the lifetime / aging of the HV battery to be a complete vehicle development target, which needs to be developed. The paper will present a method for the development process of a lifetime target from complete vehicle perspective. The method is based on the generation of a representative monthly power profile and temperature profile. Depending on a monthly user routine, ambient temperature profile and charging behavior, the vehicle specific battery power profile

Martin, Michael

Advanced Wheel Attachment Loosening Identification through Algorithmic Gear Error Analysis and Probabilistic Assessment

2026-01-0590

4/7/2026

At present, tire failures directly affect road safety, and the number of incidents caused by them is gradually increasing. Examining wheel attachment loosening on time is vital for vehicle safety. Tire-related incidents not only put people in peril but also have a detrimental effect on the economy. Therefore, the goal of this research is to develop a new and effective method for identifying wheel attachment loosening. A novel gear error reduction approach, distinct from traditional methods, combines advanced computing and probabilistic analysis. This paper involves three key components: extracting looseness eigenvalues, calculating ring gear errors, and computing the tire loosen probabilities. Gear errors derived from the Kalman filter and adjusted for speed, eigenvalues were calculated, and a tire loosening probability analysis was performed. Real-car trials across speeds and roads confirm its accuracy and reliability. This technology can improve automotive safety and maintenance

Liu, Jianjian, Zhang, Zhijie, Wang, Zhenfeng, Ma, Guangtao, Shi, Meijuan, Liu, Jing, Zhao, Binggen, Lu, Yukun

A Shared Autonomy Architecture: Utilizing an Advanced Personalized Control System (APeCS) and Shared Autonomy Arbiter (SAB)

2026-01-0147

4/7/2026

The shared autonomy framework has become an option with great potential in the field of autonomous vehicles. Human and machine control decisions typically demonstrate strengths in different scenarios. As a result, the robustness of systems can be enhanced by the collaboration between humans and autonomy. A shared autonomy architecture that takes into account both human and environmental factors was proposed in this work. The authority distribution between the human operator and the autonomy algorithm was determined by the Shared Autonomy Arbiter (SAB). Designed with a two-tier structure, the SAB incorporated a policy-level decision module, as well as a numerical-level arbitration tuning module. A fuzzy inference system (FIS) was incorporated to enhance the noise tolerance of the policy selection module. Furthermore, the human factor was taken into account by applying a projection to the users’ control input. The human operator’s control decision was projected by the Adaptive

Sang, I-Chen, Norris, William, Patterson, Albert, Sreenivas, Ramavarapu S., Soylemezoglu PhD, Ahmet, Nottage, Dustin S.

Optimizing Joint Efficiency in Stainless Steel-Aluminum Alloy FSW Joints through Advanced Parameter Control

2026-01-0228

4/7/2026

The present study investigates optimization of ultimate tensile strength (UTS) in FSW of AA2024-T3 and SS304 in a butt joint configuration. An L18 mixed-level orthogonal array was used to design 18 experiments, varying tool rotational speed (450, 560, and 710 rpm), traverse speed (20, 25, and 40 mm/min), and pin offset (1 and 1.5 mm toward the Al side). The tool rotational speed had the greatest influence on UTS, contributing nearly one-third of the total variance, followed by pin offset and traverse speed. The optimal combination, 450 rpm, 20 mm/min, 1.5 mm offset, yielded a UTS of 344.7 MPa and a joint efficiency of 78.3%. At this setting, peak temperatures reached ~356 °C, ensuring sufficient plasticization and uniform mixing of the Al–SS interface, producing a refined stir zone with an average grain size of 4.2 μm. Fracture analysis revealed ductile failure at the optimal parameters, whereas suboptimal conditions resulted in brittle or mixed fractures due to either insufficient or

Mir, Fayaz Ahmad, Khan, Noor Zaman, Pali, Harveer Singh

A Scalable and Accessible Remote Testing Framework for Automotive Development

2026-01-0191

4/7/2026

With the rise of software-defined vehicles and the emergence of cyber threats to vehicular systems, developing teams are compelled to conduct extensive testing on both virtual and physical prototypes at an accelerated pace. This new development landscape necessitates diagnostic tools that are both precise and adaptable. However, proprietary systems dominate this field, often hindering accessibility for students and researchers due to high costs and restrictive licensing. This paper presents the design and implementation of an open-source, low-cost remote testing system tailored for automotive development and diagnostics. The proposed system utilizes Arduino and Raspberry Pi processing units, along with relay-based switching modules, to provide secure remote control of vehicle components through a web-based dashboard equipped with authentication, scheduling, and real-time synchronization capabilities. The tested prototype showcased robust scalability, secure session handling, and

Pries, Andrew, Mohammad, Utayba

Enabling Sustainable E-Mobility: An Edge–Cloud Collaborative Framework for Battery Lifecycle Health Management in Electric Vehicles

2026-01-0460

4/7/2026

The rapid adoption of electric vehicles (EVs) is a cornerstone of the transition to sustainable transportation. However, uncertainty regarding battery degradation remains a significant obstacle, hindering vehicle energy efficiency, operational safety, and the recovery of end-of-life value. Accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are therefore critical for sustainable vehicle lifecycle management. This study proposes an edge–cloud collaborative intelligent framework for in-vehicle deployment that leverages a Transformer-based architecture to jointly model SOH and RUL. The cloud-side model retains the full configuration to capture long-term degradation trajectories for high-accuracy RUL prediction. A lightweight edge-side model, engineered via pruning and knowledge distillation, delivers millisecond-level inference for real-time SOH estimation onboard the vehicle. To ensure efficiency, only four core health indicators are

Gao, Weimin, Lv, Zhilong, Ou, Shiqi(Shawn)

Development and Application of SAE J3260 & J3290 Recommended Practice for Minimizing Spread of Infections in Motor Vehicles

2026-01-0128

4/7/2026

The onset of the COVID-19 pandemic in early 2020 introduced an unprecedented disruption to global industries, including automotive service and maintenance. As technicians and service shops struggled to balance operational continuity with safety, uncertainty surrounded best practices for servicing potentially dangerous vehicle cabins and air conditioning systems. This paper traces the evolution of these early efforts, from initial confusion and informal guidance to the establishment of the SAE Cabin Disinfection Practices Committee (SAE TEVCDPC) and the eventual publication of SAE J3260 and SAE J3290. It also considers work done by ASHRAE (the American Society of Heating, Refrigerating and Air-Conditioning Engineers), which simultaneously worked on ASHRAE Standard 62.1 and 241. These standards, along with contributions from subject matter experts, formalized the automotive industry’s response to infection control in vehicle environments, integrating scientific understanding with

Schaeber, Steven, Mathur, Gursaran, Taylor, Dwayne

An Efficient Approach to Key Negotiation in an Automotive Environment

2026-01-0087

4/7/2026

Negotiating Keys for applications such as message authentication within a vehicle presents many problems as, in designing the algorithm; the algorithm must be able to be utilized by small, fixed-point processors. In addition, if there is a desire to do this algorithm in the manufacturing environment, there are severe time constraints placed on how long this algorithm can take, as there are strict station time requirements, which are expensive to change, and any time utilized in the plant can negatively affect vehicle throughput. Additionally, negotiating these keys between many ECUs can greatly increase the time required to negotiate a common key using standard multi-party Diffie-Hellman. Timing would also be an issue in the case of using pair-wise Diffie-Hellman for encryption and distribution of keys utilizing a key master. To solve these problems in multi-party key negotiation, we have utilized the Elliptic Curve variation of the Burmester-Desmedt (ECBD) algorithm. ECBD is

Van Dam, Theo, Mazzara, Bill

Using Waste to Purify Water

TBMG-54871

4/1/2026

Using waste to purify water may sound counterintuitive. But at TU Wien, this is exactly what has now been achieved: a special nanostructure has been developed to filter a widespread class of harmful dyes from water. A crucial component is a material that is considered waste: used cellulose, for example, in the form of cleaning cloths or paper cups. The cellulose is utilized to coat a fine nanofabric to create an efficient filter for polluted water.

SAE TOMORROW TODAY - Powering Utilities Toward Net Zero

135613/31/2026

What does it really take to build a clean energy future -- and who's stepping up to lead it? Listen in as we sit down with Steven Clarke, Program Director, Climate and Energy, Ceres, to explore how the organization is driving real-world climate solutions for Fortune 500 companies, investors, and policymakers though science-based, data-driven insights. From tackling water risk and data center cooling to scaling wind off the coast of New England, you'll learn how Ceres is transforming utilities, accelerating electrification, and reshaping entire industries for a cleaner, more resilient energy system. This conversation is proof that sustainability isn't just about responsibility, it's about opportunity. 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

Patterson, Lori

Battery Industrial, Lead-Acid Type, for Use in Electric Powered Ground Support Equipment

ARP1817B (Current)

3/25/2026

This SAE Aerospace Recommended Practice (ARP) describes an industrial battery, lead-acid type, for use in electric powered ground support equipment.

AGE-3 Aircraft Ground Support Equipment Committee

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