This document applies to the development of Plans for integrating and managing COTS assemblies in electronic equipment and Systems for the commercial, military, and space markets, as well as other ADHP markets that wish to use this document. For purposes of this document, COTS assemblies are viewed as electronic assemblies such as printed wiring assemblies, disk drives, servers, printers, laptop computers, etc. There are many ways to categorize COTS assemblies1, including the following spectrum: At one end of the spectrum are COTS assemblies whose design, internal parts2, materials, configuration control, traceability, reliability, and qualification methods are at least partially controlled, or influenced, by ADHP customers (either individually or collectively) or by industry standards. An example at this end of the spectrum is a VME circuit card assembly. At the other end of the spectrum are COTS assemblies whose design, internal parts, materials, configuration control, and

APMC Avionics Process Management

Impact of User-Adjustable Vehicle-Dynamics Tuning on Vehicle Durability

2026-01-0194

4/7/2026

Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving

Demiri, Albion, Ramakrishnan, Sankaran, White, Dylan, Khapane, Prashant, Borton, Zackery

Open Source LLM Performance in Automating Embedded C Software Quality Improvements for Automotive

2026-01-0103

4/7/2026

The study presented in this paper explores the potential of five open-source Large Language Models (LLMs) with parameter counts between 32 billion and 49 billion to automate enhancements in code quality and developer productivity. The evaluated models – CodeLlama [1], Command-R [2], Deepseek R1-32B [3], Nemotron [4], and QwQ [5] - were assessed on their ability to refactor a large and complex automotive mechatronic C language function. This assessment focused on adherence to provided code quality standards and successful compilation of the refactored function within a larger code module. The evaluation also compared the impact of parameter count, hyperparameter tuning, model architecture, and fine-tuning. This comparison revealed that larger models showed superior overall performance, though with notable exceptions where smaller models performed better in specific rule categories. Additionally, hyperparameter tuning yielded modest improvements in performance. The study also highlighted

Struck, Daniel, Kumaraswamy, Samanth

Self-Supervised Gaussian-Based Framework for Robust Static-Dynamic Decomposition and Real-Time Urban Scene Reconstruction

2026-01-0010

4/7/2026

High-fidelity 3D reconstruction of large-scale urban scenes is critical for autonomous driving perception and simulation. Existing neural rendering methods, including NeRF and Gaussian-based variants, often face challenges like unstable geometry, noisy motion segmentation, and poor performance under sparse viewpoints or varying illumination. This paper presents a self-supervised Gaussian-based framework to address these challenges, enabling robust static–dynamic decomposition and real-time scene reconstruction. The proposed method introduces three innovations: (1) a semantic–geometric feature fusion module that combines semantic context and geometric cues for reliable motion prior estimation; (2) a cross-sequence geometric consistency constraint that enforces depth and surface continuity across time and viewpoints; (3) an efficient Gaussian parameter optimization strategy that stabilizes geometry by jointly constraining scale and normal updates. Experiments on the Waymo Open Dataset

Feng, Runlei, Wang, Ning, Zhang, Zhihao

Multi-Physics Topology Optimization and Neural Network–Based Design of Experiments for Lightweight Automotive Cast Components

2026-01-0510

4/7/2026

This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while

Kim, Hyosig, Senkowski, Andres, Gona, Kiran, Saroha, Lalit, Boraiah, Mahesh

The Necessity of a Holistic Safety Evaluation Framework for AI-Based Automation Features

2026-01-0522

4/7/2026

The intersection of Safety of Intended Functionality (SOTIF) and Functional Safety (FuSa) analysis of driving automation features has traditionally excluded Quality Management (QM) components from rigorous safety impact evaluations. While QM components are not typically classified as safety-relevant, recent developments in artificial intelligence (AI) integration reveal that such components can contribute to SOTIF-related hazardous risks. Compliance with emerging AI safety standards, such as ISO/PAS 8800, necessitates re-evaluating safety considerations for these components. This paper examines the necessity of conducting holistic safety analysis and risk assessment on AI components, emphasizing their potential to introduce hazards with the capacity to violate risk acceptance criteria when deployed in safety-critical driving systems, particularly in perception algorithms. Using case studies, we demonstrate how deficiencies in AI-driven perception systems can emerge even in QM

Abbaspour, Ali Reza, Mahadevan, Shabin, Zwirglmaier, Kilian, Stafford, Jeff

CuSCR Catalysts Under H ₂ -ICE Exhaust Gas Conditions

2026-01-0361

4/7/2026

In the near to mid-term, hydrogen internal combustion engines (H2-ICE) can be a bridge technology for reducing carbon emissions. A few challenges anticipated under lean-burn H2-ICE operation are the significant drop in turbo-out temperatures, combined with higher water content, and the possible presence of unburned hydrogen in the exhaust, which could have a potential impact on performance and durability of the downstream exhaust aftertreatment system, particularly oxidation and SCR catalysts, as these conditions can suppress low-temperature oxidation activity, perturb Cu-site speciation and redox cycling in SCR catalysts, and exacerbate hydrothermal aging under sustained wet operation. This study examines the impact of excess water and residual hydrogen on Cu-SCR durability, active site chemistry, and stability for the case with and without an upstream oxidation catalyst, through aging tests at 450 °C and 550 °C. Changes in Cu redox cycles were assessed through site quantification

Kim, Mi-Young, Daya, Rohil, Kamasamudram, Krishna

Data-Driven Objective Road-Driving Classification for Durable Design of Vehicles

2026-01-0181

4/7/2026

Design for durability in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality are rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for durability testing that accurately match the wide variations in real-world roads and driving. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing road response metrics like Vibration Dose Value (VDV) and statistical estimates of vehicle speed and acceleration. Data collected at the proving grounds on gravel roads, smooth roads, city-like roads

Shaurya, Shubham, Ramakrishnan, Sankaran, Demiri, Albion, Khapane, Prashant

Predicting Electric Vehicle Interior Noise Quality from Drive Unit End-of-Line Vibration Testing

2026-01-0223

4/7/2026

The Noise, Vibration, and Harshness (NVH) quality of electric vehicles (EVs) is heavily influenced by the performance of the electric drive unit. As a critical step in production, End-of-Line (EOL) testing of drive units is used to assess and control component-level NVH before vehicle assembly. However, the correlation between EOL test results and final vehicle interior noise quality, which directly impacts customer satisfaction, is not always fully understood. This paper presents a methodology for characterizing and predicting vehicle interior noise quality based on data from drive unit EOL vibration testing. Our study investigates the intricate relationship between drive unit assembly variations, component tolerances, and the resulting vibration response. We establish a robust correlation between these drive unit characteristics and both objective vehicle interior noise levels and subjective customer perception. The findings provide a framework for using EOL data to proactively

Arvanitis, Anastasios, Jangid, Kuldeep

Modeling Non-Uniform Temperature Distribution in Lithium-Ion Batteries

2026-01-0120

4/7/2026

Non-uniform temperature distribution within lithium-ion battery cells is a critical challenge that accelerates degradation, compromises safety, and reduces pack-level performance in electric vehicles (EVs). This work focuses on modeling and minimizing these thermal gradients through the structured optimization of a liquid-based Battery Thermal Management System (BTMS). A one-dimensional transient thermal model is developed to capture the axial temperature differentials (ΔT) in a cylindrical cell under dynamic drive-cycle loading, incorporating detailed heat transfer from the cell interior through thermal interface materials (TIM) and an aluminum cooling plate to the coolant. Using a Design for Six Sigma (DFSS) approach with an L18 orthogonal array, key control factors—including coolant flow rate, inlet temperature, TIM properties, and plate geometry—are systematically analyzed to identify configurations that optimally balance low average temperature with minimal internal temperature

El-Sharkawy, Alaa, Asar, Mona, Serpento, Stan, Sheta, Mai

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

Sensorless Estimation of In-Cabin CO ₂ Concentration for Model-Based Air Recirculation Control

2026-01-0130

4/7/2026

This paper introduces a sensorless approach for data-driven modeling of in-cabin CO2 concentration to optimize air recirculation flap control without the need for a dedicated CO2 sensor. Elevated CO2 concentrations, resulting from passenger exhalation, can impair occupants’ cognitive function and comfort. Current state-of-the-art solutions rely either on time-based control strategies, which lack responsiveness to actual cabin conditions, or on direct CO2 measurements via sensors, which increase system complexity and costs. In contrast, the proposed approach aims to replicate the benefits of sensor-based control without requiring physical sensors. In this study, a model-based methodology is presented, utilizing empirical CO2 measurement data collected from real-world test drives at varying occupancies, fan stages, vehicle speeds, and flap positions. Data acquisition involves a multi-gas analyzer positioned within the passengers’ breathing zone under controlled operation of the vehicle’s

Stürmer, Michael, Geier, Bertram, Hofstetter, Martin, Hirz, Mario

Enhancing LiDAR Performance under Fog with Adaptive Multi-Echo and Feature-Based Filtering

2026-01-0011

4/7/2026

LiDAR (Light Detection and Ranging) systems are essential for autonomous driving (AD) and advanced driver-assistance systems (ADAS), providing accurate 3D perception of the surrounding environment. However, their performance significantly deteriorates under adverse weather conditions such as fog, where laser pulses are scattered by airborne particles, resulting in substantial noise and reduced ranging accuracy. This scattering effect makes it difficult to detect objects within or behind particulate matter, posing a serious challenge for reliable perception in real-world driving scenarios. To address this issue, we propose an algorithm that combines adaptive multi-echo signal processing with a feature-integrated, rule-based denoising framework to enhance LiDAR performance in noisy environments. The multi-echo approach selectively utilizes meaningful signal returns by evaluating both intensity and relative echo positions. Based on predefined rules, the algorithm identifies the echo most

Kaito, Seiya, Zheng, Shengchao, Fujioka, Ibuki, Beppu, Taro

Mathematical Modeling of Trust Calibration for Human–Automation Safety

2026-01-0530

4/7/2026

Trust calibration is vital for safe human–automation interaction but remains largely qualitative. This study develops multiple quantitative frameworks modeling trust as a function of automation reliability. Four progressive models of binary, linear, triangular, and logistic formalize the calibrated trust zone, defining where human reliance aligns with system performance. The framework corrects major misconceptions: that trust is purely qualitative, that low trust–low reliability states are acceptable, and that overtrust and distrust pose equal risk. It establishes a minimum reliability threshold for meaningful trust and identifies distrust as the safer default in high-risk contexts. A case study on an empirical observation of 32 AI applications plotted in the trust–reliability space confirms the analysis, revealing a consistent distrust tendency where reliability exceeds user confidence and other observations. By quantifying trust through reliability, the study reframes it as a

Wen, He, Mounir, Adil

Application of Reliability Growth Methods in Conjunction with Design for Reliability Framework to Validate Heavy Truck Design

2026-01-0137

4/7/2026

Why field campaigns in the automotive industry have been going up over the years despite the strong development of technical knowledge, computational design tools and techniques to secure higher reliability standards since early stages of development phases? Uncertainties created by product complexity have been a factor that affects the ability of the manufacturers to prevent design failures before the product launch. Another factor is the shorter product development time, less test time to validate the product means that the new design will not have enough exposure to the real truck application and so some failures may not be able to be detected during the project. To deal effectively with uncertainties this study shows an application of reliability growth techniques in conjunction with DfR- Design for Reliability framework to validate the truck design in the customer application. The Crow - AMSAA method is applied to measure the reliability growth of the complete vehicle in various

Coitinho, Marcos

Predictive Modeling and Sensitivity Analysis of Thermal Runaway in 800V Lithium-Ion Battery Module Using DFSS Methodology

2026-01-0124

4/7/2026

Thermal runaway in high-voltage lithium-ion battery modules should focus on critical safety and design challenges in electric vehicle applications, which need predictive methods that enhance passenger safety and support regulatory compliance. The primary purpose of a lithium-ion battery in an electric vehicle is to provide reliable energy storage while maintaining safe operation under different operating conditions. This study proposes a Design for Six Sigma (DFSS) methodology to virtually predict and correlate thermal runaway and its propagation in an 800V high-power lithium-ion battery pack module. Conventional propagation analysis relies heavily on physical testing, whereas the DFSS-based virtual framework enables cost-effective evaluation at early design stages. Input factors included are heat transfer pathways, which are sensitive to the temperature changes, as well as thermal propagation time. Control factors are the design or process parameters that engineers use to establish

Dixit, Manish, Raja, Vinayak, Gudiyella, Soumya

An Updated Correlation Study between the Full-Size Wind Tunnels of General Motors, Ford Motor Company, and FCA US LLC

2026-01-0612

4/7/2026

As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - General Motors, Ford Motor Company, and FCA US LLC - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three

Nastov, Alexander, Lounsberry, Todd, Madin, Trevor, Langmeyer, Gregory, Fadler, Gregory, Skinner, Shaun, Horton, Damien

Minimal Binary Patching for Safety-Critical Systems

2026-01-0088

4/7/2026

Patching vulnerabilities in safety-critical domains such as automotive and aerospace is costly and complex. A small code modification can trigger a complete rebuild, producing a binary with widespread changes. This inflates patch size, complicates regression testing, and makes over-the-air (OTA) updates inefficient, as traditional binary patches often replace large portions of the executable. We present a binary rewriting–based experiment that shows the feasibility of a patch that updates only the affected bytes by computing the impact of a code change at the binary level. This produces minimal, localized patches rather than regenerated executables. The preliminary experiment shows that a single source change, which leads to thousands of modified bytes after recompilation, can be captured with only a few bytes using our method. For automotive and aerospace systems, this technique reduces patch size, conserves bandwidth, and minimizes disruption to certified software, offering a

Awadhutkar, Payas, Sauceda, Jeremias, Tamrawi, Ahmed

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

Application of DFSS for Optimizing Thermal Protection in Electric Vehicles during Battery Thermal Runaway Events

2026-01-0142

4/7/2026

Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics-based transient heat-transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L-18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin-floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant-egress safety requirements. Findings confirm DFSS as an effective framework for developing high

El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai

Numerical Framework for Predicting Power Loss and Oil Flow Dynamics in Dip-Lubricated Gear Systems

2026-01-0411

4/7/2026

Oil churning and windage power losses in dip-lubricated gearboxes can significantly affect overall transmission efficiency, particularly at high rotational speeds. As modern gearbox systems are pushed toward higher efficiency and reliability, understanding and predicting these losses becomes increasingly important. In addition to energy dissipation, the associated multiphase flow phenomena—such as oil splashing, thin film formation along gear surfaces, and aeration of the sump—strongly influence lubrication effectiveness, heat transfer, and component durability. Capturing these effects requires a robust numerical strategy that can resolve both power loss mechanisms and multiphase flow dynamics with sufficient accuracy. In this study, a single spur gear is numerically analyzed under varying oil depths and rotational speeds to quantify total power loss and investigate oil flow patterns. The computational approach employs a volume-of-fluid multiphase framework, and the predictions are

Mahyawansi, Pratik J., Haria, Hiral, Pandey, Ashutosh, Khajeh Hosseini D, Navvab

Maintaining a Healthy Safety Culture in Autonomous Vehicle Development and Operations

2026-01-0528

4/7/2026

Safety isn’t just the absence of accidents - it’s the presence of trust, empowerment, and accountability at every level. The result is a high-trust culture where process becomes practice and safety is a shared achievement. When people closest to the work feel supported to act on what they see, safety becomes the standard. Thus, the deployment of autonomous driving systems (ADSs) requires not only technical rigor but also a resilient organizational safety culture that supports continuous learning, accountability, and transparent communication. This paper examines how safety culture can be operationalized in ADS development and operations by integrating guidance from standards such as UL 4600 and best practices from SAE AVSC. UL 4600’s requirements for systematic hazard analysis, safety case maintenance, and safety performance indicators (SPIs) are used as a foundation for quantifying organizational behavior within a Just Culture framework. This work draws on Human and Organizational

Wagner, Michael, Gittleman, Michele

Study on the Regulation of the Three-Phase Microenvironment in Low-Platinum MEA

2026-01-0443

4/7/2026

With the growth of energy demand, fuel cells as efficient and clean energy devices, have attracted increasing attention. However, the high cost of membrane electrode assembly (MEA) restricts their large-scale application. Therefore, reducing the platinum usage and improving performance have become key research point. In this work, MEA was prepared and excellent performance of 1.52 W·cm-2 was achieved at a low platinum loading. The influence of different ionomer/carbon (I/C) ratio on the performance of fuel cells was systematically investigated. It was found that the performance of the MEA was the highest when the I/C ratio is 0.6. Quantifying hydrophilic and hydrophobic characteristics of catalyst layers with varying ionomer contents revealed that the proton conduction efficiency is optimal when the I/C ratio is 0.6. This balance established efficient proton conduction pathways, from the results of proton conduction impedance testing. SEM analysis demonstrated that pore structure

Li, Xin, Cai, Xin, Lin, Rui

Quality Assurance Sampling and Testing, Corrosion- and Heat-Resistant Steel and Alloy Forgings

AMS2374G (Current)

3/13/2026

This specification covers quality assurance sampling and testing procedures used to determine conformance to applicable material specifications of corrosion- and heat-resistant steel and alloy forgings.

AMS F Corrosion and Heat Resistant Alloys Committee

Aerospace & Defense Technology: March 2026

26AERD033/5/2026

Dassault Systèmes and NVIDIA Partner to Build Industrial AI Platform Powering Virtual Twins RISC-V: Bringing Greater Reliability, Safety, and Security to Military and Aerospace Systems The Enduring Value of Highly Optimized, Non-Standardized Systems Manufacturing Spotlight: Rugged Computing for Infinite Exploration Open Mission Systems: The Standard Driving Defense Innovation New CMOSS Chassis, Plug-in-Card Prototypes in Development for Army Vehicles How Forterra Is Enabling Modular Military Vehicle Autonomy Microchip’s New Processor Enables Scalable Computing Performance In-Memory Computing Chip Is a Processing Breakthrough for On-Device AI Applications

RISC-V: Bringing Greater Reliability, Safety, and Security to Military and Aerospace Systems

26AERD03_02

3/1/2026

Military and aerospace applications have become increasingly complex real-time systems. Multi-core SoCs improve performance but create new challenges in maintaining and verifying deterministic behavior. Connected systems require exceptional security to protect code from external cyberattacks. Evolving functional safety and reliability standards that keep raising the bar mean developers need to begin comprehensive testing sooner if they are going to meet tighter design schedules. Finally, certifying these complex systems has become even more difficult. To help OEMs meet these challenges, the RISC-V architecture has been designed with unique capabilities that support reliability and security in the development of safety-critical applications. With its open instruction set architecture, modularity, and extensibility, RISC-V accelerates the design of functionally safe systems while reducing the complexity, cost, and risk associated with certification to standards like DO-178C and ISO 26262

Manufacturing Spotlight: Rugged Computing for Infinite Exploration

26AERD03_04

3/1/2026

In the rapidly evolving aerospace and defense landscape, simply keeping pace with trends isn't enough. Technology is advancing faster than ever, and in mission critical applications, failure is not an option. Systems must endure harsh environments while meeting uncompromising quality standards - an imperative that demands relentless innovation. Enter the Coyotes: WOLF's specialists in next generation rugged embedded systems, small form factor design, and bold, practical ideas. Whether on Earth or in orbit, they expand what high performance embedded computing can do across ground, orbital, lunar and deep space operations. Their work spans R&D, rapid prototyping and new product development for edge computing and artificial intelligence (AI) enabled imaging.

Business Reliability Growth for Automotive Engineering, Volume 4

R-5522/17/2026

In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book

Chiang, Young J.

Counterfeit Materiel; Assuring Acquisition of Authentic and Conforming Materiel

AS6174B (Current)

2/17/2026

This SAE Standard provides requirements and guidance to: Develop a Materiel authenticity plan. Procure Materiel from reliable sources. Assure authenticity and conformance of procured Materiel, including methods such as certification, traceability, testing, and inspection appropriate to the Commodity/item in question. Control Materiel identified as counterfeit. Report Suspect or Counterfeit Materiel to other potential users and Authorities Having Jurisdiction.

G-21 Counterfeit Materiel Committee

Efficient Multi-Parameter Optimization of a Twist Beam Rear Axle for Electric Vehicles Using TOPSIS Method for Durability

2026-28-0067

2/12/2026

This study investigates the parameter optimization of a Rear Twist Beam (RTB) for an electric vehicle (EV) during the early stages of product development. Adapting an RTB design from an Internal Combustion Engine (ICE) vehicle platform presents several challenges, one of the challenges is accommodating increased rear vehicle load while minimizing cost, with maintaining existing rear hard points. To address this, we employed an experimental study for Computer-Aided Engineering (CAE) using the Taguchi DOE, which avoids costly physical durability tests. The key design parameters considered were the thickness and material grade of the RTB's components, specifically the cross beam, trailing arms, and reinforcements while preserving their original shapes. L8 Orthogonal array is constructed to design the experiment and identify the influence of the design parameters on durability performance, and the optimal combinations for maximizing durability are identified by using TOPSIS multi objective

Madaswamy, Arunachalam, Dhanraj, Sudharsun, Govindaraju, Karthik, Lokaiah, Srinivasan

Dual use Electric Vehicle Infrastructure for Enhancing Grid Resilience and Urban Sustainability

2026-28-0114

2/12/2026

The growing global adoption of electric vehicles (EVs) has resulted in a spike in the number of EV charging stations. As EVs have become more and more popular worldwide, a large number of EV charging stations are opening up to accommodate their demands. During grid failures, an EV charging station can also serve as a flexible load connected to the grid to balance out voltage fluctuations. An EV charging station when powered using a separate source, such as solar or wind, can function as a powerhouse, bringing electricity to the grid when it's needed. Therefore, instead of installing more equipment to sustain voltage, the current EV charging station can be efficiently used to meet the grid's needs during failures. These stations have the potential to be dynamic, grid-connected assets for sustainable cities and communities in addition to their core function of vehicle charging (SDG 11). Because of their dual purpose, they can serve as adaptable loads that reduce voltage variations during

R, Uthra, Rangarajan, Ravi, D, Suchitra, D, Anitha

A Data-Driven Method for Typical Landing Gear Structure Optimization Based on Neural Networks

01-19-01-0002

2/6/2026

The landing gear, as a crucial component of an aircraft, is pivotal for maintaining the safety and reliability of air travel. This study introduces a data-driven structural optimization method aimed at mitigating the peak strain on the landing gear’s rocker arm. The initial phase involves selecting nine design variables for parametric modeling to generate an initial dataset. Subsequently, the Maximum Information Coefficient (MIC) technique is used to conduct a parameter sensitivity analysis, enabling the identification and elimination of variables with minimal influence. A comparative analysis between the Genetic Algorithm–Backpropagation Neural Network (GA-BPNN) and BPNN reveals that GA-BPNN has a superior fitting capability on the enhanced dataset. By applying Particle Swarm Optimization (PSO), the optimal solution for GA-BPNN is identified. The implementation of this optimized method results in a 38.16% reduction in peak strain, validating its feasibility and reliability in

Chen, Hu, Shi, Shi, Wang, Meng, Fang, Xingbo, Wei, Xiaohui, Nie, Hong

Quality Assurance Sampling and Testing, Carbon and Low-Alloy Steel Forgings

AMS2372J (Current)

2/1/2026

This specification covers quality assurance sampling and testing procedures used to determine conformance to applicable specification requirements of carbon and low-alloy steel forgings.

AMS E Carbon and Low Alloy Steels Committee

The Critical Impact Of SAE Aerospace Standards: Certified AS1895/7 and /23 Metal Seals

26AERP02_09

2/1/2026

How engineers can ensure safety, reliability and quality in aerospace systems. Courbevoie, Île-de-France In an industry where failure is not an option and precision is paramount, aerospace manufacturers and suppliers are constantly seeking components and system solutions that deliver trusted reliability, performance, and compliance. Industry standards are a key part of achieving these high expectations, bringing together global leaders in the mobility industries to create defined, repeatable methods and consistent processes. One of these aerospace standards is AS1895 developed by SAE International - a critical standard due to the need for durable components that can withstand extreme conditions and offer high performance: high-temperature resistance, pressure sealing, and long service life with a cost-effective installation method. Leading aerospace companies such as Eaton and Honeywell have been manufacturing components that meet this standard for a long period of time.

Improvement Study of Style Steel Wheel Durability in Multiple Pothole Impacts

2026-26-0539

1/16/2026

This study focuses on improving the durability of steel wheel rims subjected to Multiple Pothole which is commonly found in Indian village roads — a critical scenario affecting vehicle safety and wheel lifespan. Initial steel wheel designs often face significant deformation or failure under repeated strikes and resulting in tyre air loss due to wheel bend, prompting the need for enhanced performance standards. In this research, a combination of finite element modelling, experimental impact testing, and material optimization strategies were employed to assess and improve the structural integrity of steel rims. Key parameters such as rim profile geometry & material composition were systematically varied to evaluate their influence on impact resistance. Results demonstrate that strategic design modifications and material enhancements can significantly increase the rim's ability to absorb energy and resist bending without substantial weight penalties. The findings offer practical

DEsigan, Lakshmipathy, P, Praveen, K, Chandramohan, C, Santhosh

Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization

2026-26-0396

1/16/2026

With increased deterioration of road conditions worldwide, automotive OEMs face significant challenges in ensuring the durability of structural components. The tyre being the primary point of contact with the road is expected to endure harshest of impacts while maintaining the other performance functions such as Ride & Handling, Rolling resistance, Braking. Thus, it is considered as the most challenging component in terms of design optimization for durability. The current development method relies on physical testing of initial samples, followed by iterative construction changes to meet durability requirements, often giving trade-off in Ride & Handling performance. To overcome these challenges, a frugal simulation-based methodology has been developed for predicting tyre curb impact durability before vehicle-level testing so that corrective action can be taken during the design stage.

Sundaramoorthy, Ragasruoban, Lenka, Visweswara

Ensuring Functional Safety in Electric Vehicle Inverters: A Case Study on ISO 26262 Implementation

2026-26-0158

1/16/2026

The transition to electric vehicles (EVs) has brought about significant advancements in automotive technology, with inverters playing a crucial role in converting DC power from the battery to AC power for the electric motor. Ensuring the functional safety of these inverters is paramount, as any failure can have severe implications for vehicle performance and passenger safety. This case study explores the successful implementation of ISO 26262 standards in the development and validation of EV traction inverters. This paper begins by outlining the functional requirements and safety goals specific to EV inverters, followed by a detailed analysis of the potential hazards and risks associated with their operation. Using ISO 26262 as a framework, we describe the systematic approach taken to identify, assess, and mitigate these risks. Key methodologies such as Hazard Analysis and Risk Assessment (HARA), Failure Mode and Effects Analysis (FMEA), and Fault Tree Analysis (FTA) are employed to

Ramachandra, Shwetha, V, Sushmitha

Multispeed EV Transmission – Gear Shift Simulation and Validation

2026-26-0157

1/16/2026

The advancement of electric vehicle (EV) transmission systems is currently a prominent trend aimed at decreasing carbon emissions and providing eco-friendly transportation alternatives. Most of the EV transmissions are single speed, but research conducted on multi speed EV transmissions show higher efficiency, good performance, high speed and torque demand when compared with single speed counterparts. Most of the multi speed EV transmissions that are developed are of non-synchromesh type, which have direct effect on NVH, driving dynamics and durability of drivetrain components. Due to aforementioned factors, gearshift analysis becomes critical for development. Simulation model is developed at early development phase for initial feedback. Using the feedback, drivetrain can be optimized furthermore and test on physical parts can be conducted for final verification. This paper provides a simulation based approach for modelling non-synchromesh two speed EV transmission using Simulation X

Kansagara, Smit, Thambala, Prashanth, Sutar, Suresh, Todtermuschke, Karsten, Patel, Hiral

Totem-Pole PFC and LLC Resonant Converter based 6.6kW On-Board Charger for LEV Applications

2026-26-0160

1/16/2026

As light electric vehicles (LEVs) gain popularity, the development of efficient and compact on-board chargers (OBCs) has become a critical area of focus in power electronics. Conventional AC-DC topologies often face challenges, including high inrush currents during startup, which can stress components and affect system reliability. Furthermore, DC-DC converters often have a limited soft-switching range under light load conditions, leading to increased switching losses and reduced efficiency. This paper proposes a novel 6.6 kW on-board charger architecture comprising a bridgeless totem-pole power factor correction (PFC) stage and an isolated LLC resonant DC-DC converter. The main contribution lies in the specific focus on enhancing startup behavior and switching performance. In PFC converters, limiting inrush current during startup is crucial, especially with fast-switching wide-bandgap devices like SiC or GaN. Conventional soft-start techniques fall short in of ensuring smooth voltage

Patil, Amruta, Bagade, Aniket

Tailgate Stiffness Mitigation and Engineering Strategy for Full Width Tailgate-Mounted Tail Lamp Integration

2026-26-0494

1/16/2026

The tailgate, as the rearmost vehicle opening, plays a pivotal role in defining the rear aesthetic theme while ensuring structural durability and maximizing luggage space. Contemporary automotive design trends highlight an increasing demand for Full width tailgate-mounted tail lamp configurations, which deliver a bold and dynamic visual appeal. Enhanced by animated lighting features, these designs cater to the preferences of Gen Z customers, becoming a decisive factor in purchasing decisions. However, integrating these complex tail lamp structures introduces significant engineering challenges, including increased X-dimension lamp volume, thereby providing reduced design space, and intricate mounting schemes constrained by panel stamping limitations. These factors necessitate the development of innovative joinery strategies and structural definitions to maintain durability targets, including achieving 25,000–30,000 slam cycles without failure, while preserving luggage space. This paper

Beryl, Joshua, Mohanty, Abhinab, Unadkat, Siddharth, Selvan, Veera

Design Solutions for Ice-Induced CNG Filling Failures- Field Issue Resolution through Filter Geometry and Seal Material Reengineering

2026-26-0515

1/16/2026

This study investigates the phenomenon of receptacle icing during Compressed Natural Gas (CNG) refueling at filling stations, attributing the issue to excessive moisture content in the gas. The research examines the underlying causes, including the Joule-Thomson effect, filter geometries, and their collective impact on flow interruptions. A comprehensive test methodology is proposed to simulate real-world conditions, evaluating various filter types, seal materials and moisture levels to understand their influence on icing and flow cessation. The findings aim to offer ideas for reducing icing problems. This will improve the reliability and safety of CNG refueling systems.

Virmani, Nishant, Sawant, Shivraj Madhukar, C R, Abhijith

Accelerating Product Development Life Cycle through Digitalization of Fatigue Life for Structural Components

2026-26-0496

1/16/2026

In today’s market, faster product development without compromising durability is essential. Durability assessment ensures a vehicle maintains structural integrity under normal and extreme conditions. Achieving this requires effective Road Load Data Acquisition, integrated with robust design practices and efficient validation processes. However, physical RLDA is time-consuming and costly, as it depends on prototype vehicles that are often available only in the later development stages. Failures identified during these late-stage tests can delay the product launch significantly. This study presents a full digital methodology of fatigue life estimation for suspension aggregates. A study has been demonstrated on Rear Twist Beam component of rear suspension. The approach integrates the digital RLDA methodology presented in literature and finite element analysis simulation process, enabling durability assessments entirely within the virtual domain. This approach demonstrates how digital RLDA

Kokare, Sanjay, Dwivedi, Sushil, Siddiqui, Arshad, Iqbal, Shoaib

Digital Control of Synchronous Rectification and Dead Time Configuration for Improving Efficiency and Longevity of DC Motors

2026-26-0089

1/16/2026

This paper elucidates the implementation of software-controlled synchronous rectification and dead time configuration for bi-directional controlled DC motors. These motors are extensively utilized in applications such as robotics and automotive systems to prolong their operational lifespan. Synchronous rectification mitigates large current spikes in the H-bridge, reducing conduction losses and improving efficiency [1]. Dead time configuration prevents shoot-through conditions, enhancing motor efficiency and longevity. Experimental results demonstrate significant improvements in motor performance, including reduced thermal stress, decreased power consumption, and increased reliability [2]. The reduction in power consumption helps to minimize thermal stress, thereby enhancing the overall efficiency and longevity of the motor.

Patil, Vinod, Kulkarni, Malhar, Soni, Asheesh Kumar

New Generation Natural Rubber-Based Bump Stopper with Improved NVH Characteristics

2026-26-0292

1/16/2026

In automotive suspension systems, components like bump stoppers and jounce bumpers play critical roles in controlling suspension travel and enhancing ride comfort. Material selection for these components is driven by functional demands and performance criteria. Traditionally, Natural rubber (NR) has traditionally been favored for bump stopper applications due to its excellent vibration absorption, tear resistance, cost-effectiveness, and biodegradability. However, in more demanding environments, it has been largely replaced by microcellular polyurethane (PU) elastomers, which offer superior durability, environmental resistance, and enhanced noise, vibration, and harshness (NVH) performance. This study revisits NR with the goal of re-establishing its viability by enhancing its performance to match or surpass that of PU. Through compound optimization and advanced material processing techniques, significant improvements have been achieved in NR’s mechanical strength, compression set

Murugesan, Annarajan, Hingalaje, Abhijeet, Perumal, Mathavan, Pawar, Rohit

Evaluation of Shear Trim Edge in HSLA Steel for Automotive Application

2026-26-0286

1/16/2026

Quality of the Shear Trimmed edge of HSLA 550 steels is significantly affected by process variations such as Shear Trimming Clearance, trim tolerance, burr height and clamping force. All these parameters largely influence the characteristics of the Shear Affected Zone, a region on sheet metal where it undergoes deformation during the trimming process. The Shear Affected Zone is predominantly vulnerable to failure due to work hardening and the effects of strain rate, induced by the tonnage during the trimming operation. To assess the edge ductility of these materials, Tensile, Fatigue Strength, Die Punch Clearance, Roughness and Hardness Tests are carried out. These tests are crucial for applications that demand high formability and resistance to edge failure. Virtual simulation of edge trimming operation using elastoplastic material models in LS-Dyna have been performed to gain insights into burr formation and damage evolution during shearing. These simulations act as a precursor to

Thota, Badri Vishal, Kashyap, Amit, Bhuvangiri, Jaydev

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