Browse Topic: Quality, Reliability, and Durability

Items (10,141)
This paper presents an automated framework for security compliance and quality assurance in DevSecOps CI/CD pipelines, specifically designed for safety-critical avionics software. The framework integrates regulatory compliance checks, security validation, and robust verification directly into the software development lifecycle, supporting continuous integration and delivery for aerospace applications. Automated processes such as code compilation, coding standards compliance, Cyclomatic Complexity Measurement, Sources Line of Code and CRC validation on target hardware are seamlessly orchestrated to maintain consistency and reliability. The system generates comprehensive compliance reports, highlights coding standard violations and security issues, and notifies relevant stakeholders to facilitate timely resolution and corrective actions. As new code is checked in, the framework automatically initiates all verification and compliance tasks, ensuring that every software update is
Bhagwat, Shashank RaviChangappa, Naveen KumarNath, Sunny
Aerospace manufacturing operates within an intricate ecosystem where quality, compliance and traceability are critical to success. Conventional digital thread frameworks provide connectivity but remain largely passive, lacking the intelligence to autonomously manage complex non-conformities across the product lifecycle. This paper introduces an Agentic Digital Thread powered by Agentic AI, designed to transform non-conformity management into an adaptive, self-orchestrating system that actively drives decision-making and corrective actions [1, 4]. The proposed architecture employs a Master Agent to coordinate workflows and maintain end-to-end data continuity, while specialized Agents autonomously manage domain-specific tasks. In the pre-manufacturing phase, these agents proactively validate requirements, material conformity and process planning through integration with PLM, MES, ERP, QMS and supplier systems. In the post-manufacturing phase, the framework extends to concession
Veluri, SastryGopala Krishnan, Kannan
The mechanical performance of short fiber-reinforced plastic (SFRP) components is highly sensitive to fiber orientation, which is significantly influenced by the injection gate location during the molding process. Traditionally, gate placement decisions are driven by warpage minimization strategies, often overlooking mechanical performance under diverse load cases. This research introduces an automated workflow within Digimat-MS that integrates injection gate optimization into the early design phase, leveraging Integrated Computational Materials Engineering (ICME) principles. The proposed methodology enables engineers to upload either Marc, Abaqus or Ansys input decks, select a component of interest, assign material cards, and define gate scenarios. A Design of Experiments (DOE) is then executed locally or remotely, allowing Digimat to evaluate multiple gate configurations. The system aggregates results and identifies optimal gate locations based on the initiation of failure under
Kauthale, TanmayMadhavan, VinaySoni, Ganesh
Aircraft lighting systems play a vital role in ensuring operational safety, visibility, and regulatory compliance. Exterior lighting systems are essential for aircraft identification, navigation, collision avoidance, and ground operations under varying environmental conditions. These systems typically include navigation lights, anti-collision lights, landing and taxi lights. An aircraft lighting system comprises light sources, optical elements, electronic control units, power interfaces, wiring harnesses, and mechanical mounting structures. Among these components, optics are critical as they control light distribution, intensity, color accuracy, and efficiency while withstanding harsh aerospace environments such as vibration, thermal cycling, and aerodynamic loads. Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. The use of high-performance optical polymers such as Cyclo Olefin Polymers (COP
Vialta, FredericoS, NikhilKatageri, PraveenSP, PradeepSingh, Abhimanyu Kumar
Abstract: This research paper investigates the performance of FKM (Fluorocarbon) seal material when exposed to a 50:50 ethylene glycol-water mixture. The study aims to determine the volume change percentage and Hardness change of FKM elastomers under standardized testing conditions. The experimental approach follows ASTM D471 and ASTM 2240 guidelines, focusing on weight and hardness measurements of the test samples to establish a success criterion. The results provide critical insights into the chemical compatibility and durability of FKM elastomers in Aerospace and industrial applications where ethylene glycol-water mixtures are commonly used. The findings contribute to enhanced material selection and design considerations for sealing applications subjected to glycol-based fluids. Samples of FKM material were immersed in the fluid at controlled temperatures and durations, simulating real-world operational conditions. The primary metric of interest, volume change percentage and
Yarolkar, MakrandPatil, SandipSingh, Tanul
Using vibration data to estimate buckling loads is proven effective for a wide range of structures, including rods, plates, and shells. The Arbelo formulation of the vibration correlation technique improves prediction reliability for cylindrical and spherical shells. In this study, we introduce a simplified variant of the Arbelo approach that provides higher prediction accuracy while requiring significantly lower pre-load levels. We define a new parameter, the Stiffness Decay Index (SDI), to characterize stiffness degradation by normalizing the loaded natural frequency with respect to the unloaded state. This metric enables accurate buckling prediction without causing structural damage or permanent deformation. We evaluate SDI numerically and experimentally for multiple isotropic geometries and demonstrate its advantages over the Arbelo method, particularly for ellipsoidal domes subjected to external pressure. We conduct experiments on rods, plates, oblate shells, and beverage cans to
Rangarajan, GopikrishnaV, VishwajithRaju, GangadharanDinavahi, Ramkrishna
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 reliability program standard and implementation guidelines. The committee was formed as a cross section of international representatives from commercial industries and governments. The G-11SW committee has developed a standard (JA1002) and these implementation guidelines (JA1003) that are consistent with a SAE G-11 system level reliability program standard (JA1000) and guidelines (JA1000-1), augmented by necessary software-specific information. The G-11SW committee believes these documents reflect the best current commercial practices, and meet the objectives of the United States Department of Defense Acquisition Reform initiative and the North Atlantic Treaty Organization (NATO) Reliability Program. The JA1002 program standard is intended to be
G-41 Reliability
The importance of reliability in design engineering has significantly grown since the early Sixties. Competition has been a primary driver in this growth. The three realities of competition today are: world class quality and reliability, cost-effectiveness, and fast time-to-market. Formerly, companies could effectively compete if they could achieve at least two of these features in their products and product development processes, often at the expense of the third. However, customers today, whether military, aerospace, or commercial, have been sensitized to a higher level of expectation and demand products that are highly reliable, yet affordable. Product development practices are shifting in response to this higher level of expectation. Today, there is seldom time, or necessary resources to extensively test, analyze, and fix to achieve high quality and reliability. It is also true that the rapid growth in technology prevents the accumulation of historical data on the field performance
G-41 Reliability
This SAE standard establishes the requirement for suppliers to plan a reliability program that satisfies the following three requirements: a. The supplier shall ascertain customer requirements b. The supplier shall meet customer requirements c. The supplier shall assure that customer requirements have been met
G-41 Reliability
This SAE Standard establishes the requirement for suppliers to plan a reliability program that satisfies the following three requirements: a. The supplier shall ascertain customer requirements; b. The supplier shall meet customer requirements; c. The supplier shall assure that customer requirements have been met. This document applies to the specification, design and development, and assurance of any product. This document does not specify the method to be included in the program. Rather, the content of each program must be tailored to satisfy customer requirements using the most appropriate means.
G-41 Reliability
This SAE Standard provides a framework for the management of software reliability within system reliability requirements. It is based around the Software Reliability Plan and Software Reliability Case and emphasizes the importance of evaluating progress towards meeting software reliability requirements throughout the project life-cycle.
G-41 Reliability
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Li, XingyuLin, ShizhongShao, ZhanCui, ShichengChen, RuiduanLuo, He
The reliability of welded joints is a vital factor in modern manufacturing, directly affecting product performance and durability. This study investigates methods to enhance the mechanical and metallurgical quality of butt joints in AISI 304L stainless steel welded by the gas tungsten arc (GTA) process. A systematic experimental design was implemented using the Taguchi method with an L9 orthogonal array, considering welding current, gas flow rate, and travel speed as the main parameters. To determine overall weld performance, the joints were characterized by measuring ultimate tensile strength (UTS), yield strength, percentage elongation, and examining their microstructural morphology. An experimental strategy based on the Taguchi approach has been implemented. The welding performance of the material was investigated, and the process parameters were optimized using multiresponse optimization through principal component analysis (PCA), incorporating an orthogonal array design, signal-to
Ghosh, NabenduRoy, Angshuman
This standard establishes the common requirements for training of DPRV personnel for use at all levels of the aerospace engine supply chain. This standard shall apply when an organization elects to delegate product release verification by contractual flow down to its suppliers (reference 9100 and 9110 standards) and to perform product acceptance on its behalf. It is intended that organizations specify their DPRV requirements through the application of AS9117. While the delegating organization will use the AS13001 standard as the baseline for establishing DPRV process and product training, it may include additional contractual training requirements to meet its specific needs. The DPRV training material was primarily developed for aerospace engine supply chain requirements. However, this standard may also be used in other aerospace industry sectors where a DPRV process requiring specific training can be of benefit.
G-22 Aerospace Engine Supplier Quality (AESQ) Committee
This FMEA standard describes potential failure mode and effects analysis in design (DFMEA), supplemental FMEA-MSR, and potential failure mode and effects analysis in manufacturing and assembly processes (PFMEA). It assists users in the identification and mitigation of risk by providing appropriate terms, requirements, rating charts, and worksheets. As a standard, this document contains requirements—”must”—and recommendations—”should”—to guide the user through the FMEA process. The FMEA process and documentation must comply with this standard as well as any corporate policy concerning this standard. Documented rationale and agreement with the customer are necessary for deviations in order to justify new work or changed methods during customer or third-party audit reviews.
Automotive Quality and Process Improvement Committee
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
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, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
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, DanielKumaraswamy, Samanth
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, RunleiWang, NingZhang, Zhihao
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 RezaMahadevan, ShabinZwirglmaier, KilianStafford, Jeff
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, HyosigSenkowski, AndresGona, KiranSaroha, LalitBoraiah, Mahesh
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, AlexanderLounsberry, ToddMadin, TrevorLangmeyer, GregoryFadler, GregorySkinner, ShaunHorton, Damien
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, PayasSauceda, JeremiasTamrawi, Ahmed
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, VinayaYoo, Dong YeonChavare, Sudeep
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, HiralPandey, AshutoshKhajeh Hosseini D, Navvab
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, MichaelGeier, BertramHofstetter, MartinHirz, Mario
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
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-YoungDaya, RohilKamasamudram, Krishna
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, HeMounir, Adil
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, SeiyaZheng, ShengchaoFujioka, IbukiBeppu, Taro
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, AnastasiosJangid, Kuldeep
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, ShubhamRamakrishnan, SankaranDemiri, AlbionKhapane, Prashant
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, ManishRaja, VinayakGudiyella, Soumya
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, AlaaAsar, MonaSerpento, StanSheta, Mai
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 AhmadKhan, Noor ZamanPali, Harveer Singh
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, AlaaAsar, MonaTaha, NahlaSheta, Mai
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, MichaelGittleman, Michele
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, XinCai, XinLin, Rui
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
Gasoline direct injection (GDI) engines are the most common technology on American roadways in 2025, and soon, an industrywide gasoline quality standard will better reflect their unique operational needs. Here's why that's important. It's no secret that fuel economy has been one of the greatest driving forces of automotive evolution over the past several decades. As corporate average fuel economy (CAFE) standards have grown increasingly lofty, OEMs eke out new efficiencies from every area of the vehicle. One of those areas, of course, is the engine, and many OEMs have deployed gasoline direct injection (GDI) technology, which is becoming the most common engine technology on American roadways. But while GDI engines proliferate, varying fuel additization throughout North America has not necessarily kept pace with their unique needs and can, in fact, hinder those engines from meeting and sustaining their full fuel economy potential.
Blackburn, Brett
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