Browse Topic: Management and Organizations

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The History of the International Powered Lift Conference Across Five Decades of V/STOL Progress2026-01-0662To be published on 07/01/2026
This year, SAE International hosts the 2026 edition of the International Powered Lift Conference (IPLC), which focuses on the latest developments in vertical and/or short takeoff and landing (V/STOL) aircraft research, concepts and programs. IPLC is a joint technical meeting, held approximately biennially, co-sponsored by the American Institute of Aeronautics & Astronautics (AIAA), the Royal Aeronautical Society (RAeS), SAE International and the Vertical Flight Society (VFS). Because each technical society hosts IPLC only once a decade, staff turnover at the societies creates a lack of knowledge and historical context of the event. This paper provides a formal record of the history and legacy of the IPLC, and its progress in highlighting the technical and programmatic progress of V/STOL over the ages.
Hirschberg, Michael J.
Passenger Car Powertrain for Voltages above 800V2026-37-0020To be published on 06/09/2026
The EU-funded innovation project High-Voltage fast-charging Efficient electric vehicle Powertrains (HiVEP) develops new technologies for mass-market electric vehicles (EVs) by advancing architectures operating above 800 V. These architectures integrate silicon carbide (SiC)-based power electronics, rare-earth-free electric machines with active winding reconfiguration, high C-rate batteries, and optimised thermal management systems. HiVEP aims to deliver sub-10-minute fast charging, reduce energy consumption by at least 25%, extend range by 20%, and cut system costs by up to 20% in volume production. This article expands on the project objectives, methodological approach and expected key innovations as well as technical, environmental, and societal impacts. The discussion situates HiVEP within the European research and innovation landscape, emphasising its role in accelerating adoption of sustainable mobility solutions.
Schernus, Christof, Nada, Shady, Neuhaus, Christoph, Ewald, Jens, Swierc, Daniel, Kallur-Krishnamoorthy, Rajesh, Vasiliadis, Harilaos
A Parametric Cradle-to-Grave Life Cycle Assessment Tool for Comparative Evaluation of Passenger Car CO₂ Emissions2026-37-0040To be published on 06/09/2026
This work presents the development of a flexible and user-oriented software tool for the cradle-to-grave Life Cycle Assessment (LCA) of passenger cars, enabling robust comparisons of greenhouse gas emissions across heterogeneous vehicle configurations. The tool supports informed decision-making by quantifying and visualizing environmental impacts associated with alternative mobility choices over the full vehicle life cycle, including production, use, maintenance, and end-of-life stages. A key contribution of the proposed framework is its high degree of configurability and readability. All parameters describing the vehicle and its usage can be freely modified, including powertrain type, dimensions and weight, ownership profile (new or second-hand vehicles, partial ownership periods, leasing scenarios), annual mileage, vehicle lifetime assumptions, and the carbon intensity of fuels or electricity sources. Country-specific energy mixes are explicitly considered, allowing the same vehicle
Gastaldi, Chiara, Cibrario, Luca
An open-source framework to Automate Virtual Optimization of Internal Combustion Engine Calibration Maps through shape-based strategy2026-37-0001To be published on 06/09/2026
The automotive industry is facing increasingly stringent regulatory constraints, driving the need for faster and more efficient powertrain development. This results in higher systems complexity, making internal combustion engine calibration progressively more challenging to meet performance and emissions targets. This, combined with the manual nature of traditional calibration workflows, leads to a time‑consuming process that heavily relies on human expertise. Although virtualization can reduce development time and costs, the overall workflow remains largely dependent on manual decision‑making and iterative refinement. In this context, this work presents a virtual calibration framework based on a genetic algorithm, aimed at the automated optimization of engine calibration maps to satisfy performance and emissions constraints, while reducing manual effort. Each calibration map is represented through a polynomial parameterization. Specifically, a generic three‑dimensional polynomial with
Romano, Gianvito, Aglietti, Filippo, Spedicato, Tonio, cozza, Ivan Flaminio, Capra, Andrea
Rapid Fuel Distribution Prediction in RCCI Marine Engines Using CFD-Informed, Active Learning Framework2026-37-0017To be published on 06/09/2026
Accurate prediction of in-cylinder fuel distribution (FD) is fundamental to reduced-order combustion modeling and emissions prediction, yet remains computationally prohibitive with high-fidelity CFD alone. This work develops a CFD-informed machine-learning surrogate for spatial FD in a large-bore diesel engine, based on a Wärtsilä W20 injector and representative engine conditions. A fully coupled injector–spray–engine CFD framework under engine-like RCCI inert conditions determines the needle-lift profile and resolves the combined effects of injector geometry, needle dynamics, and operating conditions on in-cylinder flow, capturing physical phenomena not reproducible by isolated free-spray simulations. A high-fidelity database is generated using Latin Hypercube Sampling, from which FD is extracted at 15 CAD before top dead center within an annular multi-zone (MZ) representation consistent with reduced-order combustion models. A multi-output Random Forest (RF) surrogate, augmented with
Moradi, Jamshid, Salahi, Mahdi, Heidarabadi, Shadab, Andwari, Amin, Konno, Juho, Wik, Christer, Mikulski, Maciej
Integration of energy consumption simulation in optimal charging planning for battery electric long-haul trucks2026-37-0019To be published on 06/09/2026
Vehicle fleet decarbonization is a key objective for the coming years, with electrification representing the primary pathway to achieving the targets set by the European Union. The share of battery electric trucks in new registrations has been gradually increasing especially in light and medium size trucks. The replacement rate of diesel long-haul trucks with zero emission trucks is still low due to challenges posed by added complexity and limitations of battery charging. Depot overnight charging is not sufficient to cover the energy needs of a truck covering large distances and careful planning of the route using public charging infrastructure is crucial for an optimized route minimizing extra costs and range anxiety. The current work aims to develop a methodology to propose the optimal charging locations for a given route of a battery electric truck based on nearby stations along the route. Our study uses an open-source optimization algorithm for the fixed route vehicle charging
Perdikopoulos, Michail, Doulgeris, Stylianos, Livitsanos, Georgios, Kazakis, Thomas, Mellios, Giorgos, Ntziachristos, Leonidas
Investigation into Cooling Loss Reduction Associated with Changes in In-Cylinder Flame Distribution by Offset Orifice Nozzle2026-37-0003To be published on 06/09/2026
Recently, an increase in compression ratio has been widely recognized as one of the essential technologies for improving the thermal efficiency of heavy-duty diesel engines. However, a higher compression ratio tends to result in increased cooling loss, which could diminish the thermal efficiency gains. Therefore, novel approaches which can reduce cooling loss while maintaining or improving thermal efficiency are required. In our previous studies, it was found that an offset orifice nozzle, in which the orifices are drilled with a small offset from the radial center of the nozzle, improves thermal efficiency and reduces cooling loss simultaneously. However, key factors contributing to the significant reduction in cooling loss have not been sufficiently clarified. This study aims to investigate the mechanism of cooling loss reduction associated with changes in flame distribution when using an offset orifice nozzle in heavy-duty diesel engines, based on in-cylinder combustion observations
Mukayama, Tomoyuki, Enomoto, Yoshiteru, Mikami, Naotaka, Nomoto, Shigeru, Uchida, Noboru
Alcohol-Based Energy Carriers in Transportation: Status, Standards, and Outlook2026-37-0042To be published on 06/09/2026
The global transport sector accounts for approximately 28% of total energy consumption and 15.8% of greenhouse gas emissions worldwide, with road transport alone responsible for 11.8%. As the world seeks pathways toward carbon neutrality, methanol and ethanol emerge as promising alternative energy carriers capable of leveraging existing logistics infrastructure while reducing dependence on fossil fuels. This review examines the production pathways, lifecycle considerations, and costs associated with both alcohols. Global methanol production reached 111 million metric tons in 2022, and global ethanol production totaled approximately 93.3 million metric tons in 2024. In comparison, the yearly production of gasoline and diesel amounts to over 2 billion metric tons per year. The review evaluates fuel requirements across multiple transport modes, including passenger vehicles, light- and heavy-duty vehicles, maritime shipping, aviation, and rail, and assesses regulatory frameworks governing
Fitz, Patrick, Fellner, Felix, Rößlhuemer, Raphael, Härtl, Martin, Jaensch, Malte
Non-Intrusive Fatigue Detection and Alerting for Pilots2026-26-0793To be published on 06/01/2026
Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by limiting pilot's flying hours and controlled rest requirements. Despite regulations on flying hours and optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time, annunciate in cockpit and transmit the information to airliners post-flight for appropriate fatigue risk management. There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot
Nyamagoudar, Vinayak, P R, Namratha, Ramachandran, Venkataramani
Assessment of Injection Gate Location effects on Mechanical Performance of Short Fiber Reinforced Plastic Components using Digimat2026-26-0746To be published on 06/01/2026
The mechanical performance of short fiber-reinforced plastic (SFRP) components is highly sensitive to fiber orientation, which is significantly influenced by the injection gate location during the molding process. Traditionally, gate placement decisions are driven by warpage minimization strategies, often overlooking mechanical performance under diverse load cases. This research introduces an automated workflow within Digimat-MS that integrates injection gate optimization into the early design phase, leveraging Integrated Computational Materials Engineering (ICME) principles. The proposed methodology enables engineers to upload either of 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 simulate and evaluate multiple gate configurations. The system aggregates results and identifies optimal gate locations based on the initiation of
Kauthale, Tanmay, Madhavan, Vinay, Soni, Ganesh
Development of Graphene filled Polypropylene Nanocomposite for Aerospace Application2026-26-0739To be published on 06/01/2026
Polypropylene, a commodity plastic, is the semi-crystalline thermoplastic widely used in high volume for general purpose applications. Polypropylene is the macro molecules of soft and weak backbone, which by reinforcement of fillers in different forms such as fiber, spheroids, nanotubes, flakes, etc., can influence its mechanical, thermal, electrical, creep resistance, and flame resistance properties for use in aerospace applications. Currently, polycarbonate and nylon plastics are used in aerospace applications, however, they are expensive compared with polypropylene. In this thesis, efforts are put to study the effect of reinforcement fillers in the properties of polypropylene composite, primarily the mechanical and flammability properties. The matrix element, polypropylene co polymer and reprocessed polypropylene blended in equal ratio, are coupled with the dispersing phases such as graphene, mica, fumed silica, and polydimethylsiloxane polymer. Effect of graphene as reinforcing
Govindaraju, Parthasarathy
Computational Study of Laminar and Turbulent Shock Wave Boundary Layer Interactions at Mach 52026-26-0728To be published on 06/01/2026
Shock wave boundary layer interaction (SWBLI) is a key phenomenon in high-speed aerodynamics, influencing aerodynamic efficiency, stability, and thermal loading. This study employs the SU2 solver to investigate SWBLI in laminar and turbulent regimes. Initially, two-dimensional turbulent cases for a flat plate and three different wedge angles (6°, 10°, and 14°) are validated against experimental data to ensure numerical accuracy. The analysis then focuses on laminar interactions, where low-momentum boundary layers are more susceptible to shock-induced adverse pressure gradients, leading to flow separation, recirculation bubbles, and delayed recovery. Reynolds number effects are examined by systematically reducing freestream pressure and temperature, thereby altering both shock strength and viscous properties. Results indicate that lower Reynolds numbers generate weaker shocks and shorter separation bubbles with earlier reattachment, whereas higher Reynolds numbers produce stronger
B, Nishma K., Sivasubramanian, Jayahar
Accelerating aircraft verification and certification through an integrated virtual and physical testing approach2026-26-0710To be published on 06/01/2026
Aircraft verification and certification entails a variety of testing tasks and requires coordination among numerous stakeholders across different disciplines to ensure alignment on requirements. Historically, certification strategies have relied on both physical testing and high-fidelity simulation. The integration of these complementary approaches is essential to address their respective blind spots and to support credible certification evidence. A key challenge lies in the rigorous correlation of simulation models with physical test data. Flutter verification, for instance, is a critical component in defining the aircraft’s flight envelope and plays a foundational role in certifying safe operational boundaries. In this work, the process of freedom from flutter verification starting from the pre-test analysis is demonstrated. This work introduces a novel approach to combining simulation and test data with the aim to accelerate and streamline the verification process leading to more
Hallez, Raphael, Yadabettu, Dayanand Kumar, de Boer, Jens, Aspasiou, Vicky
Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction2026-26-0718To 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 constrain the failure envelope, and (2) a data-driven Recurrent Neural Network (RNN) (specifically, an LSTM) for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, synthetic run-to-failure dataset under varying operational loads
Mohamed, Abbas
Risk-Driven Program Management Framework - Abstract2026-26-0716To be published on 06/01/2026
Avionics programs face increasing complexity due to evolving safety, certification, and cybersecurity requirements. Conventional program management approaches, focused mainly on cost and schedule, often overlook the dynamic and interdependent risks inherent in developing safety-critical systems. This gap results in late surprises, inefficient resource use, and challenges in achieving certification milestones. This paper introduces a risk-driven program management framework tailored for avionics, where risk identification, assessment, and mitigation are embedded within the governance model rather than treated as a parallel activity. The framework integrates industry standards such as DO-178C, DO-254, DO-326A, and ARP4754A, ensuring alignment with regulatory expectations while promoting a holistic view of program health. A key feature of the approach is the use of digital dashboards and predictive analytics to transform static risk registers into actionable tools. These dashboards
Rahul, Saurabh, Benikireddy, Raghunatha
Zero Waste Manufacturing in Aerospace Circular Design Approaches from Concept to End-of-Life2026-26-0775To be published on 06/01/2026
Achieving zero waste in aerospace manufacturing demands a fundamental shift from traditional end-of-pipe solutions to circular design principles embedded from the earliest stages of product development. This paper presents a practical framework for integrating circularity into aerospace systems, emphasizing design strategies that minimize material waste, facilitate disassembly, and enable component recovery throughout the product lifecycle. The approach is structured around five key pillars: 1. Design for Modularity and Disassembly 2. Material Substitution to Enhance Recyclability 3. Waste Segregation and Characterization in Manufacturing Processes 4. Component-Level Circularity Readiness Scoring 5. Collaborative Supplier Engagement to Establish End-of-Life Pathways To support implementation, a Circularity Readiness Assessment Tool has been developed, enabling engineers to evaluate designs against circularity criteria such as disassembly ease, material recyclability, and supplier
S, Chaitra
Implementation of Wireless IoT Technology in EVAC Slide Emergency Systems2026-26-0792To be published on 06/01/2026
Emergency evacuation slides (EVAC slides) are critical safety devices used on aircraft to enable rapid egress during emergencies. While these slides provide a quick and reliable escape route, communication between separated slides during evacuation remains a challenge. Often, during raft deployment over water, slides may drift apart, impeding communication among evacuees and rescue personnel, potentially compromising safety. Existing aircraft EVAC systems on the market lack integrated wireless communication, relying on visual or shouted voice signals, which are unreliable in noisy or chaotic conditions. With the rise of the Internet of Things (IoT), wireless sensor networks have become effective tools for monitoring and communication in various safety and industrial applications. This paper explores the integration of wireless IoT technology into EVAC slide systems to facilitate inter-slide communication and monitor critical parameters, such as slide air pressure and the floating
Sengodan, Rajkumar, Talore, Suresh
Automated health surveillance system for passenger2026-26-0794To be published on 06/01/2026
Ensuring passenger safety and comfort remains a top priority in the aviation industry, particularly during in-flight medical emergencies involving cardiac and respiratory complications. The absence of immediate medical intervention and the limitations of current aircraft health monitoring systems pose significant risks. Existing systems primarily depend on manual observation and basic sensors, lacking continuous health assessment, data analytics, and adaptive response mechanisms. This paper proposes a Smart Passenger Health Monitoring System that integrates Heart Rate (BPM), Electrocardiogram (ECG), and Peripheral Capillary Oxygen Saturation (SpO₂) monitoring into a single intelligent framework. The system utilizes high-precision biomedical sensors for continuous data acquisition, while an embedded microcontroller processes physiological parameters in real time to detect abnormalities. Upon identifying potential distress, the system triggers an automated seat adjustment mechanism that
S, Tejashree, D, Kousalya
Automated Flight Maneuver Recognition for Intelligent Flight Simulator2026-26-0713To be published on 06/01/2026
The rapid growth in the number of aircrafts and pilots emphasizes the need for an AI-enabled training framework that can offer precise, automated examination of flight maneuvers, thereby optimizing the pilot’s training efficiency and minimizing iterations of the conduct of flight maneuvers thereby reducing the training time of the pilot for a flight. This paper introduces a novel hybrid methodology to intelligently detect manoeuvres performed during a flight using signal processing and machine learning techniques. A general framework is developed that can be used for all kinds of flight phases and aircraft types. The framework is implemented in a two-step approach. Firstly, Continuous Wavelet Transform (CWT) of the signals of interest for different manoeuvres are generated, to find the time at which a manoeuvre happens during a sortie. CWT looks at the energy levels in the transformed signal and uses smart thresholding technique to pick out only the parts with high energy, to extract
Sahu, Akash, C, Poornima, C, Aravindh, Kaliyari, Dushyant, TK, Khadeeja Nusrath
Automating Compliance Workflows in Aerospace Systems: A Scalable Framework for Specification Review and Requirement Mapping2026-26-0714To be published on 06/01/2026
Compliance verification in aerospace systems often relies on labor-intensive workflows that demand extensive manual effort to produce structured review documentation and requirement matrices. These processes can span dozens of hours per review, are vulnerable to inconsistencies due to non-standardized annotations, and depend heavily on individual interpretation of fragmented technical sources. With a growing backlog of review tasks and a steady influx of new requests, the need for scalable automation has become increasingly urgent. This study presents a modular automation framework designed to streamline compliance assessments through intelligent document parsing, requirement extraction, and matrix generation. The system integrates optical character recognition, computer vision, and natural language processing techniques to process both scanned and digital documents. By digitizing data across multiple hardware configurations and automating extraction from diverse technical records, the
Mirani, Harsh, Baviskar, Yash G.
Enabling Circularity in the Aerospace Maintenance Ecosystem through Generative-AI Driven Back-to-Birth Traceability of Life-Limited Engine Parts2026-26-0719To 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 the 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
Bhate, Ujwal, Jain, Dilip Kumar, Kulkarni, Ninad, Kalaiyarasan, Aravindh, Jha, Ashish, Shenoy, Karthik
Digitalization of Mechanical Labs for Enhanced Traceability and Virtual Verification2026-26-0715To be published on 06/01/2026
Digitalization is the process of leveraging digital technologies to transform business operations, processes, and models, enabling organizations to improve efficiency, create new value, and enhance customer experiences. It is essential as it enables data-driven decisions and reduces product development time. It’s easier to Digitalize new products however, transforming existing products and processes is a challenging task, as constituents are in various phases of lifecycle. Also, the existing/ legacy data acts as a starting point for future programs. Currently, teams are spending hours to weeks finding the right processes and data, costing $~14,000 per test based on labor hours. To tackle this challenge, Mechanical labs are digitalizing their data and processes alongside physical tests via 3DEXPERIENCE application to capture data in digital models and ensure traceability for which Requirement Functional Logical Physical (RFLP) framework is leveraged. This traces Requirements to its
Karpur, Anoop, Inapakolla, Bharat Kumar, Harris, Jason
System and Method of Strain Emulation using a Beam Load Cell Test Setup2026-26-0743To 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
Evaluating Volume and Hardness change in Fluorocarbon and Ethylene Propylene Rubber Elastomers: Effects of Fluid Aging2026-26-0758To be published on 06/01/2026
Abstract: This research paper investigates the performance of FKM (Fluorocarbon) seal material when exposed to a 50:50 ethylene glycol-water mixture. The study aims to determine the volume change percentage and Hardness change of FKM elastomers under standardized testing conditions. The experimental approach follows ASTM D471 and ASTM 2240 guidelines, focusing on weight and hardness measurements of the test samples to establish a success criterion. The results provide critical insights into the chemical compatibility and durability of FKM elastomers in Aerospace and industrial applications where ethylene glycol-water mixtures are commonly used. The findings contribute to enhanced material selection and design considerations for sealing applications subjected to glycol-based fluids. Samples of FKM material were immersed in the fluid at controlled temperatures and durations, simulating real-world operational conditions. The primary metric of interest, volume change percentage and
Yarolkar, Makrand, Patil, Sandip, Singh, Tanul
Augmented Reality and Multimodal Interfaces for Astronaut Training and In-Orbit Operations2026-26-0796To be published on 06/01/2026
Augmented Reality (AR) and multimodal human–machine interfaces (HMI)—combining visual overlays, voice, gesture, eye-tracking, and biometric sensing—are now maturing into flight-relevant technologies capable of transforming astronaut training and in-orbit operations. These interfaces reduce task time, lower error rates, and mitigate cognitive load, thereby strengthening both crew autonomy and mission safety. For India, the timing is critical: Gaganyaan human spaceflight program is approaching decisive crewed missions in the late 2020s, and the Bharatiya Antariksh Station (BAS) is targeted for the 2030s. AR/MMI can be positioned not as an accessory but as a core enabling system for training throughput, real-time crew support, and resilient station operations. This paper provides (i) an overview of India’s current scenario, including Gaganyaan astronaut training ecosystems, IIT Madras collaborations on AR/VR, and Vyommitra humanoid readiness; (ii) synthesis of global case studies—NASA
Yadav, Anoop Singh
Adaptive HVAC Strategies for Enhanced Cabin Thermal Comfort, Air Quality and Energy Efficiency2026-26-0791To be published on 06/01/2026
Passenger comfort within vehicle and aerospace cabins relies on finely tuned management of temperature, air quality, and energy use. This paper proposes an integrated HVAC framework that combines zonal climate control, intelligent airflow distribution, and real-time sensor data to maintain thermal balance across different cabin zones. Leveraging predictive thermal load modeling and machine learning, the system anticipates environmental changes—such as sudden shifts in external temperature or passenger load—and proactively adjusts heating and cooling outputs. Simultaneously, air quality is enhanced through a multistage filtration system, active air purification technologies, and dynamic CO₂ concentration monitoring. Comfort assessment integrates PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) indices to adapt environmental conditions based on passenger feedback and physiological needs. Simulations and early-stage prototypes improve energy savings and improve
Mudavath, Lehitha Sai, Patil, Ashish, Saha, Sudipta
Advancing Aerospace Interiors: Evaluation of the In-House Polymer Pellet Additive Manufacturing System2026-26-0765To be published on 06/01/2026
The Elektra printer is an open-source, pellet-based (FGF) 3 axis additive manufacturing system developed by Collins in collaboration with Pollen AM to enable large-scale, cost-efficient 3D printing using standard polymer pellets. In alignment with the Make in India program, Elektra represents a significant step toward localized, industrial-scale additive manufacturing that delivers affordability, flexibility, and performance for aerospace and allied industries. The system provides four major advantages. First, it enables cost-effective part production by leveraging standard injection molding grade thermoplastic pellets instead of expensive proprietary feedstocks. Second, its large build volume (800mm*800mm*400mm) supports the manufacture of tools, fixtures, and structural parts often restricted by conventional systems. Third, Elektra is compatible with a broad range of engineering and high-performance polymers that are flame retardant, ensuring adaptability for multiple use cases
Kini, Aditya Deepak, Sundar, Santosh
AI-Led Sustainability Strategy: Driving Product Value from Birth to Disposal2026-26-0781To be published on 06/01/2026
Product development in Aerospace, Oil & Gas, Turbomachinery and Aviation sectors are associated with complex engineering challenges and long lead time to materialize products. More so in Aerospace and Aviation sectors, unlike other sectors, they are highly cost intensive, consuming few millions of dollars for introducing minor modifications to billions of dollars for a major modifications along with regulatory constrains. In addition, the product development cycle is spread over years ranging from a couple of years for minor modification to nearly a decade or more for major modifications. The profitability of the product is derived through its Safety, Reliability and Availability in operation. The product is maintained in service until it sustains value in its operation and is discarded if the value deteriorates and the cost of upkeep exceeds the product value. Product Value in the present context is not the price tag but encompasses intangible elements like brand value, reputation etc
Srinivasan, Karthik, G.V.V., Ravi Kumar, Vaderahobli, Devaraja Holla, Bhate, Ujwal, Veluri, Sastry
TRANSFORMING AIRCRAFT MRO WITH AGENTIC AI AND CONTEXT ENGINEERING2026-26-0788To be published on 06/01/2026
Aircraft Maintenance, Repair, and Overhaul (MRO) operations are highly complex, involving coordination among multiple stakeholders including airlines, MRO providers, OEMs, and regulatory authorities. A significant challenge in this space is managing unplanned events such as Aircraft on Ground (AOG) conditions, where delays can lead to major financial losses to airlines and safety risks. Engineers must quickly diagnose the damage, evaluate compliance against regulatory limits, coordinate with OEMs, and make critical decisions—all while navigating a fragmented ecosystem of disconnected systems, diverse document types, and time-sensitive processes. This paper presents a real-world, intelligent MRO solution that addresses these challenges through the use of Agentic AI and context engineering. The system is designed to automate and augment key MRO workflows such as damage detection, repair pathway selection, compliance verification, and supplier coordination. At its core, the solution is
Abburu, Sunitha, G.V.V., Ravi Kumar, Poovalingam, Sundaresan, Vaderahobli, Devaraja Holla
Integrating Human Factors and Predictive Modeling for Enhanced Aviation Safety: A Data-Driven Approach to Risk Mitigation and System Design2026-26-0795To be published on 06/01/2026
The evolution of the aviation industry from manual control to highly automated and autonomous systems has brought human factors to the forefront of safety, design, and operational efficiency. This paper presents an integrated analysis combining machine learning techniques with statistical modeling to assess the impact of human-system interaction on aviation incident outcomes. The first phase of this research involved a longitudinal dataset covering aircraft design evolution, training programs, and incident records. Using classification algorithms, including XGBoost, the study achieved an accuracy of 81.82% in predicting incident likelihood. Performance metrics such as F1-scores (0.85 for “Incident” and 0.78 for “No Incident”) highlighted the model’s robustness in identifying risk patterns associated with human factors and system complexity. In the second phase, 50 plus detailed aviation incident reports were analyzed using logistic regression, t-tests, and Cook’s Distance to identify
Valiyaparambil, Praveen
Agentic Digital thread for self-healing non-conformities in aerospace product manufacturing lifecycle2026-26-0763To be published on 06/01/2026
Aircraft manufacturing involves a complex ecosystem where quality, traceability and compliance are paramount. Managing non-conformities both before and after manufacturing requires a digitally connected data framework that ensures seamless data flow, decision-making and corrective actions across different functions like sourcing, materials, engineering and production. The advent of agentic AI brings more autonomous solutions through drastically reduced human prompts. This paper presents a comprehensive Agentic Digital thread framework for managing pre and post manufacturing non-conformities, enabling real-time visibility and control from design to delivery. The Agentic digital thread transforms from being passive connectivity layer into living intelligence ecosystem that continuously learns, adapts, and improves in real time Pre-manufacturing nonconformity management focuses on early detection of issues through Agentic AI in sourcing, materials and design through integration of PLM
Veluri, Sastry, Gopala Krishnan, Kannan
Predictive Obsolescence Management2026-26-0780To be published on 06/01/2026
This abstract is towards Aerospace Sustainability - End-of-Life Management for Aerospace Assets. In the field of Aerospace, which has a long Life-Cycle process [20-30Years], Component Obsolescence has become a major problem as it prevents Maintenance & sustenance of a product with committed life-cycle period. Obsolescence Management plays a vital role by deriving strategic plans on proactive obsolescence where the system needs to be supported for several decades. This abstract analyzes the obsolescence challenges in the Aviation industry especially in Avionics System impacted by component obsolescence and present the possible proactive obsolescence management in terms of Engineering, Technology, and business/cost elements. The Obsolescence problem cannot be avoided but the impact of obsolescence and mitigate the risk can be minimized by planning and managing response. The obsolescence risk assessment for the Bill Of Materials (BOM) is a paramount activity to manage obsolescence
Dharmananyala, Rohith, Munirathnam, Krishna, Marokeyfrancis, Joisyjose, Sadashivaiah, Nagesh, Kondamari, Harshitha
Integrating Formal Methods into Model Based Systems Engineering(MBSE) to Mitigate Requirement Escapes2026-26-0712To be published on 06/01/2026
The industry is undergoing a significant digital transformation in the way system requirements are defined, communicated, and managed. Major original equipment manufacturers (OEMs) are moving toward fully model-based development processes, with plans to deliver requirements exclusively in the form of system models. It is no longer sufficient to manage requirements using traditional document-based approaches; instead, organizations must adopt tools and processes that enable the consumption, interpretation, and implementation of model-based requirements. Preparing to meet this industry direction is critical to maintaining competitiveness and alignment with our customers’ expectations. Model-Based Systems Engineering (MBSE) plays a central role in this transition. MBSE enables engineers to define, analyze, and manage system requirements, architectures, behaviors, and verification strategies within a cohesive model-based framework. It supports traceability, promotes consistency across
Gupta, Chandan, Nakkeeran, Rupashree
Wear Resilience Characteristics of 2% Silicon Nitride Strengthened AZ31 Magnesium Composite2026-26-0740To be published on 06/01/2026
To develop magnesium matrix composites, ceramic silicon nitride (Si3N4) particles are used to strengthen the magnesium (AZ31) matrix by adding 2 wt.%. The composite is developed by disintegrated melt deposition vacuum stir casting method. Microstructural studies reveal the presence of Si3N4 particles and their uniform distribution. A L9 orthogonal array planned using Taguchi’s experimental design is chosen for three wear parameters axial load (AL), rotational speed (RS), and time duration (TD) for trials as per G99 standard in pin-on-disc apparatus. Experimental outcomes show a rise in axial stress; wear loss increases dramatically. Because the area of contact shrinks as sliding speed increases, wear loss diminishes dramatically. When the AL is low, CoF increases, and when the AL is large, CoF drops. When the sliding speed is increased, CoF decreases. To optimize multiple responses effectively, the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) was
Senthilkumar, N., Dhinakar Raj, C K
Understanding and Modeling Effectiveness of Predictive Risk Notifications for Early Assistance for Safe Driving: A Public Road Testing Study09-14-01-00264/10/2026
While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information. Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in
Maruyama, Masaki, Koyama, Keiichiro, Ezaki, Toru, Sakamoto, Junichi, Sawada, Yuta, Matsuoka, Takahiro
Enhancing the Aerodynamic Performance of Diffusers in High-performance Vehicles Using Trapped Vortex Cavities2026-01-50274/9/2026
Motivated by the inclusion of active flow control provisions in the 2026 Formula One regulations, and building upon previous studies of Trapped Vortex Cavity (TVC) implementation in inverted front wings, this paper investigates the effectiveness of TVC as a flow control mechanism applied to vehicle diffusers. Both active and passive configurations were considered for three diffuser geometries: a base straight-line diffuser, an inverted airfoil-shaped diffuser, and a diffuser inspired by a Formula One car. The study employed numerical simulations to evaluate the aerodynamic performance and the potential benefits of integrating TVC systems. Across all types of diffusers, the implementation of a circular TVC cavity resulted in a significant improvement in the lift-to-drag ratio (CL/CD). In the active flow control configuration, a 10% improvement was observed in the straight diffuser under a limited mass-flow rate. With optimized cavity positioning and radius, the airfoil-shaped and
Ming Kin, NG, Teschner, Tom-Robin
Forensic Acquisition and Analysis of Unsupported Lexus Infotainment Modules via CMD42 Bypass and Data Carving2026-01-05404/7/2026
Crashes involving passenger vehicles increasingly include vehicles equipped with infotainment systems that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered information is both accurate and
Burgess, Shanon
A Large Language Model-Based Database for Analyzing the Battery Critical Minerals Supply Chain2026-01-04714/7/2026
Global geopolitical volatility is recognized as a critical threat to the resilience of the electric vehicle battery supply chain. Static, manually updated databases are inadequate for capturing the sector’s rapid dynamics, resulting in significant information gaps for strategic planning. To address this, an Artificial Intelligence-driven methodology is proposed for constructing a comprehensive and dynamic database. An automated pipeline was implemented. First, real-time textual data are collected from curated news and industry sources using specialized web crawlers. Then, the unstructured data obtained undergo preprocessing, including deduplication and cleansing, to ensure quality. A core innovation involves the application of Large Language Models (LLMs) for deep semantic parsing and extraction of structured information. These models are utilized to accurately identify key entities—such as corporations, facilities, and production capacities—and to delineate complex multi-tier
Zhu, Juntong, Luo, Wei, Zhang, Xiang, Yang, Zhifeng, Ou, Shiqi(Shawn), He, Xin
A Novel Spot Joint Finite Element for Rapid Stress Analysis of Fasteners in Automotive Structures2026-01-01824/7/2026
Due to the spot weld and mechanical fastener share the similar characteristics to join sheets together with differences in deformation behavior around joint region, a novel spot joint element (user-defined element) consists of regular Mindlin shell elements and equations for different kinematic constraints is proposed to simplify the spot joint representation in lightweight automotive structures. The novel spot joint element can not only provide accurate deformation behavior around joint region but also output mesh-insensitive structural stresses at virtual nodes with the use of traction-based structural stress method for fatigue failure analysis. In this investigation, the structural stress distributions around joint circumference in the lap-shear specimens with spot weld or fastener are first calculated to validate the accuracy of the novel spot joint element. Then, the structural stresses along different cross-sections emanating from joint are also calculated for the specimens with
Wu, Shengjia, Zhang, Lunyu, Dong, Pingsha
Accelerating Electrification through Modular Propulsion: GM’S Strategy for BEV and BET Platforms2026-01-04104/7/2026
General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical
Liu, Jinming, Sevel, Kris, Anwar, Mohammad, Oury, Andrew, Welchko, Brian, Gagas, Brent
Benchmarking Driver Responses in Head-On Conflicts: Expanding the Framework for TTC, Affordances, and Uncertainty2026-01-05344/7/2026
Head-on emergency events present unique challenges for evaluating both human and automated-vehicle (AV) performance because they do not conform to a direct stimulus–response sequence. Instead, driver behavior in these scenarios follows a stimulus–wait–response pattern governed by time-to-conflict (TTC), uncertainty, and environmental affordances. Prior research has often failed to distinguish between conflict types, resulting in generalized reaction-time assumptions that do not account for contextual uncertainty. This study integrates simulator and naturalistic driving data from a four-part research program to establish objective benchmarks for driver responses in head-on encounters. When an encroaching vehicle crossed the centerline 2.5 s before impact, drivers initiated braking with a weighted average of approximately 1.0 s before impact. When the encroaching vehicle crossed or was first observed at approximately 3.5 s before impact, braking typically began with a weighted average of
Muttart, Jeffrey, Dinakar, Swaroop, Maloney, Timothy, Adikhari, Bikram, Gernhard-Macha, Suntasty
Operational Feasibility of Battery Swapping in U.S. Transit: A Case Study of King County Metro2026-01-04024/7/2026
Battery swapping technology has emerged as a promising alternative to conventional charging for electric bus fleets, offering rapid turnaround times and improved vehicle availability. This paper utilizes existing bus routing information to perform an initial site evaluation for battery swapping stations. A Seattle-based public transit agency—King County Metro, a partner on this project—is used as a case study. Using General Transit Feed Specification (GTFS) data from King County Metro, a MATLAB model was built to reconstruct blocks and layovers, extracts dwell-time opportunities, and performs block-distance and block-time analyses to understand operational rhythms. based bus model was developed that maps route mileage, efficiency, and layover availability for battery swap decisions, using a look-ahead rule that defers battery exchanges whenever the next feasible layover can still be reached while respecting a minimum state-of-charge. The workflow estimates how many swaps each block
Vadlapatla, Taraka Rishi, Jankord, Gregory, D'Arpino, Matilde
Standardization of On-Vehicle Measurement of BEV Thermal System Energy Consumption and Range Impacts2026-01-01324/7/2026
This paper presents research and digital twin modeling results to support work on a methodology to properly account for the energy consumed by the thermal system of a BEV, for use within both existing Petroleum-Equivalent Fuel Economy (PEFE) calculations, and the proposed addition of hot and cold weather range values to the consumer-facing Monroney label [1]. Properly accounting for thermal system impacts would incentivize minimizing energy consumption of these systems, since 1) BEV PEFE is a direct input to an OEMs overall CAFE performance, and 2) the values on the Monroney label has some impact on consumer vehicle choice. The impetus for this work was Final Rules issued by the EPA and NHTSA in early 2024 eliminating A/C Efficiency Credits for BEVs from the 2027 MY, thus eliminating regulatory incentives to minimize energy consumption of these systems. Higher energy consumption will produce a number of negative secondary effects, including higher real-world greenhouse gas emissions
Taylor, Dwayne
Introduction to Catesby Aero Research Facility, CARF, the Coast-Down Tunnel Proving Ground2026-01-06114/7/2026
This paper reports on the Catesby Aero Research Facility (CARF), which began commercial operation in 2019, and summarizes facility characteristics and associated measurement technologies, with an emphasis on vehicle-mounted component-force measurement devices. CARF is a proving ground converted from a former railway tunnel approximately 2.74 km in length and surfaced with high-quality tarmac. The road-surface quality was specified to be comparable to that of SUBARU's proving ground and was achieved using established construction methods. The course is approximately straight with a small longitudinal grade. Key course specifications include an approximately 40 m2 blockage area, a 6 m road width (maximum 8.4 m), flatness σ < 0.5 mm, and a gradient of 0.57%. Relative to outdoor coast-down testing, the tunnel length enables continuous measurement to very low speeds, thereby improving repeatability. A six-component force sensor integrated into the hub unit enables on-road measurement of
Shimoyama, Hiroshi
Efficient Embedded Control of Nonlinear Systems for Software-Defined Vehicles2026-01-00754/7/2026
Software-defined vehicles (SDVs) are reshaping automotive control architectures by shifting intelligence to embedded systems, where computational efficiency is paramount. This paper presents a systematic evaluation of control strategies (PID, LQR, MPC) for the classical control problem involving inverted pendulum on a cart under strict embedded constraints representative of software-defined vehicle ECUs. The objective is to evaluate and compare the performance of advanced control algorithms under varying control objectives when deployed on microcontrollers with constrained computational and memory resources, representative of the limitations encountered in embedded platforms used for SDVs. Furthermore, the study illustrates systematic optimization strategies that enable these algorithms to achieve real-time execution within such resource-constrained environments. Each control strategy is implemented with careful consideration of algorithmic complexity, real-time responsiveness, and
Vupparige, Varun, Pandya, Vidit
Optimizing Joint Efficiency in Stainless Steel-Aluminum Alloy FSW Joints through Advanced Parameter Control2026-01-02284/7/2026
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
Integrating Optimization and Model Fidelity Selection Methods for Real-Time Driver-in-the-Loop Vehicle Simulators2026-01-06214/7/2026
Automotive OEMs perform extensive prototype testing to configure vehicles for objective criteria (performance), and subjective criteria (handling and comfort). To reduce testing time and costs, OEMs rely on real-time Driver-In-the-Loop Simulators (DIL) running complex Multi-Body Dynamics (MBD) models. Recent advances in simulation technology have increased model accuracy but also operating costs, possibly limiting the viability of real-time DIL applications. Running high fidelity MBD models in real-time is computationally intensive and often requires re-configuration, CAE model de-contenting, and solver setting optimization, which can introduce significant analysis errors. This presents a core challenge: selecting model fidelity levels that result in computationally efficient simulations, while maintaining sufficient predictive accuracy. This study introduces a methodology that integrates optimization algorithms with decision-making techniques to select the right fidelity within a
Balchanos, Michael, Emara, Mariam, Zarate Villazon, Angel, Mavris, Dimitri
Backlash Evasion Strategy for Enhancing Vehicle Cornering Performance2026-01-06404/7/2026
This study presents a torque distribution control strategy for EVs with e4WD powertrain to overcome the trade-off between ensuring vehicle acceleration and deceleration responsiveness and mitigating backlash shock in the driving system. The deterioration of the drivability which occurs from the intrinsic hardware characteristics of the drivetrain is prevented by designing a response-priority drive mode in which neither front or rear motor torque is allowed to change its sign. Instead, in such drive mode, the front motor torque is only allowed to perform regenerative braking while the rear motor torque is only allowed to produce positive acceleration torque. In order to avoid sacrificing the maximum acceleration by applying such strategy, the mode transition function is implemented as well. In addition, in order to prevent backlash impact due to drivetrain compliance, variable offset torque based on drivetrain compliance model is evaluated in real time and applied to each motor command
Oh, JIWON, Lee, Ho Wook
Aerodynamic Proximity Effects between the DrivAer and AeroSUV Standard Models, Part 1 – Same-Lane Interactions2026-01-06054/7/2026
In this paper, the effects of aerodynamic interactions on the drag of a longitudinally-arranged two-vehicle system are examined by considering the influence of separation distance, cross winds, vehicle size and shape. Testing was undertaken at 30% scale in a large wind tunnel with road-representative freestream turbulence. Separation distances of 0.5, 1.0, and 2.0 vehicle lengths (L) were examined over a range of yaw angles between ±15°. A highlight of the current study is the characterization of platoon drag-reduction benefits for different sizes and shapes of the lead and follower models, by using a DrivAer model and an Aero-SUV model, each with slant-back (Notchback or Fastback) and square-back (Estateback) variants, providing four distinct model pairings. Drag reduction for the lead model appears to be affected mainly by the size of the follower model, while the follower model shows a much greater sensitivity to shape of the lead model. Larger drag reductions were observed at most
McAuliffe, Brian, Ghorbanishohrat, Faegheh
Advancing Electric Drive Unit Design with Smoothed Particle Hydrodynamics2026-01-04134/7/2026
Thermal and lubrication management is critical for the performance characteristics of Electric Drive Units (EDUs) in electrified powertrains. Accurate assessment of lubrication flow, particularly in terms of wetting behavior and churning losses, is essential for optimizing EDU performance across various driving conditions. This study presents a comprehensive numerical investigation of lubrication flow behavior within an EDU using an advanced Smoothed Particle Hydrodynamics (SPH) method. The mesh-free SPH approach provides significant advantages in modeling intricate oil dynamics, such as oil splashing, and the behavior of oil in contact with rotating components. The primary focus of this study is to investigate the phenomena of oil splashing, wetting behavior characterized by the Wetting Fraction(WF), and churning losses within the gearbox environment. Key flow characteristics such as oil distribution, particle trajectories, torque resistance due to fluid drag, and oil volume fraction
Chintala, Paramesh, Inada, Jorge, Flores Solano, Cesar Alfonso, Gingade, Suresh
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