Browse Topic: Electrical, Electronics, and Avionics

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Conceptual Design and Aerodynamic Configuration of the Relithia Nova: A 2000kg Hybrid-Electric STOL Aircraft2026-01-0660To be published on 07/01/2026
This paper presents the conceptual design of the Relithia Nova, a hybrid-electric Short Take-Off and Landing (STOL) aircraft engineered to provide essential connectivity to remote regions with limited aviation infrastructure, such as the South Pacific and Caribbean. Designed with a Maximum Take-Off Mass (MTOM) of 2,000 kg, the aircraft accommodates six occupants, including the pilot, and is optimized for operations on short, unprepared airstrips up to 2,000 ft elevation. The Relithia Nova employs a series-hybrid propulsion architecture featuring two wing-mounted turboshaft engines coupled with electric generators that drive propulsive rotors via a high-capacity lithium-ion energy storage system. This configuration ensures sustained power for high-lift generation while reducing emissions. Aerodynamically, the aircraft utilizes a high-aspect-ratio wing (AR=8.67) based on the NACA 23012 airfoil, chosen for its favorable lift-to-drag characteristics in subsonic flow (Mach 0.23 cruise
Chikwanha, Hendrick Tafadzwa
Development of a Diesel Combustion System for Next‑Generation Heavy‑Duty Engines Using a Synergistic Analysis‑and‑Testing Approach2026-37-0004To be published on 06/09/2026
Regulators and policymakers have introduced increasingly stringent limits on tailpipe CO₂ and pollutant emissions to accelerate the decarbonization of heavy-duty vehicle applications. The development of innovative propulsion technologies — such as advanced combustion systems, low-friction reciprocating components, and improved aftertreatment solutions — combined with hybridization and the adoption of alternative fuels (e.g., biogas, HVO, green hydrogen), represents a key pathway for meeting future emission and GHG targets. In this study, advanced combustion systems were developed for a 13‑liter diesel engine for heavy-duty truck applications, with the objective of complying with forthcoming Euro VII regulations while maximizing thermal efficiency. The combustion system architecture—including open-bowl geometry with high aspect ratio, injector nozzle with wider spray opening angle, and reduced swirl ratio—was optimized using a Machine Learning–algorithm trained on high-fidelity 3D CFD
Belgiorno, Giacomo, Centini, Maria Pia, Pezza, Vincenzo, Cozza, Ivan F., Pesce, Francesco C., Vassallo, Alberto, Colombo, Giovanni, Gallo, Alessandro, Mirzaeian, Mohsen, Borg, Jonathan
Enabling Flexibility Services through Interoperable V2X Infrastructures: Advanced Modeling and Operational Validation in the FLEXV2X Project2026-37-0024To be published on 06/09/2026
The integration of Electric Vehicles (EVs) as active grid resources represents a pivotal shift towards decarbonisation. However, the implementation of effective Vehicle-to-Everything (V2X) services faces technical challenges regarding interoperability, predictive management, and battery health preservation. This work presents a comprehensive system design and research methodology developed within the framework of the FLEXV2X project, aimed at addressing interdependencies within a unified bidirectional charging ecosystem. The proposed scientific framework addresses two complementary timescales. At the device level, the study details the modelling and optimisation of bidirectional converters, focusing on control algorithms designed to ensure robust dynamic response and efficiency. Building upon this hardware foundation, the paper describes a system-level optimisation strategy. By employing open-source cyber-physical modelling, the architecture simulates complex EV-grid interactions. This
Lutzemberger, Giovanni, Barater, Davide, Ceraolo, Massimo, Fera, Cesare, Leaver, Ian, Pasini, Gianluca
Impact of Compression Ratio and Stroke on Hydrogen Requirement for Emission Optimized Operation of an Ammonia-Fuelled Spark-Ignition Engine2026-37-0030To be published on 06/09/2026
Ammonia-fuelled engines have emerged as a promising route toward net-zero emission targets due to ammonia’s carbon-free nature, ease of storage, and established handling infrastructure. However, the low burning speed and narrow flammability limits of ammonia pose a significant combustion challenge, which can be addressed through hydrogen co-fuelling. For practical implementation, on-board hydrogen production via thermal catalytic cracking of ammonia is an attractive solution, as it eliminates the need for external hydrogen storage and associated handling and capital costs. Previous studies by the present authors identified a lean operating strategy that achieves an equal molar ratio of NOx and unburned ammonia (NH3), enabling complete conversion to nitrogen and water vapour when coupled with a Selective Catalytic Reduction (SCR) system. This strategy was further validated using cracked ammonia-derived hydrogen in place of bottled H2 through an on-board cracker, thereby representing a
Yadav, Neeraj Kumar, Ambalakatte, Ajith, Geng, Sikai, Gopakumar Suja, Gagan, Birch, Alexander, Cairns, Alasdair, Harrington, Anthony, Hall, Jonathan
Forecasting Electric Vehicle Fleet Growth and Energy Requirements in the UK2026-37-0043To be published on 06/09/2026
With the United Kingdom (UK) goal to achieve a fully decarbonised energy sector by 2035 and achieve net zero greenhouse gas emissions by 2050, the transition of the UK’s passenger car fleet to battery electric vehicles (BEVs) plays a crucial role in reaching this goal. This study evaluates the environmental and energy impact of large-scale BEV adoption by modelling future uptake scenarios using historical fleet data combined with assumed impact of future policy such as the 2030 ban on the sale of new petrol and diesel vehicles. The results have shown a large-scale adoption is possible by 2040, predicting almost 37 million BEVs on the road. However, the associated electricity demand is predicted to rise to nearly 110 TWh annually, signifying the need for rapid development in renewable energy generation. Although BEVs significantly reduce transport sector emissions, the overall climate impact is dependent on a continued effort of grid decarbonisation.
Burke, Bradley, Kateregga, Sunny, Sodre, Jose Ricardo
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
Thermal and Emission Characterization of Cylindrical Lithium-Ion Batteries under Thermal Abuse Using a Climate Chamber2026-37-0023To be published on 06/09/2026
Thermal safety in lithium-ion batteries is a critical aspect due to their increasing use in energy storage systems and electric vehicles. To investigate thermal abuse conditions, numerous studies on cylindrical cells employ specialized equipment to accurately measure temperature and pressure during thermal runaway events. However, such tests typically require robust, dedicated, and high-cost facilities, which limit their availability in conventional laboratory environments. In this context, the present study proposes and evaluates an experimental methodology based on the use of a climate chamber combined with an instrumented reduced-volume container, to reproduce severe external heating conditions. The thermal behavior and gas emissions associated with thermal runaway events were characterized in six cylindrical lithium-ion batteries of two different chemistries. Initially, the experimental setup was validated using a reference cell to verify the methodology and the measurement systems
Penagos Vásquez, Diego Alejandro, Marco-Gimeno, Javier, Monsalve-Serrano, Javier, Garcia, Antonio, Perez Balastegui, Jose
Analysis of a sorption energy storage system for cabin air heating and dehumidification in electric vehicles2026-37-0034To be published on 06/09/2026
This work investigates the integration of a Sorption Thermal Energy Storage (TES) into the Air Conditioning (AC) system of electric vehicles. The proposed device reduces the energy demand for cabin heating under winter conditions, leading to a driving range increase. The TES dehumidifies the cabin air through a desiccant bed (zeolite 4A), preventing window fogging, enabling higher air recirculation rates, and consequently reducing the required heating power. An experimentally validated numerical model was used to analyze the adsorption and regeneration processes and to identify suitable operating conditions. Regeneration was found to be effective at moderate temperatures (around 120°C), with a counter-current airflow configuration providing faster and more efficient desorption compared to parallel-flow operation. A simplified model integrating TES, AC unit and cabin was developed and used to compare different configurations. Heating energy consumption with and without TES under
Verlingieri, Rebecca, Calabrese, Luigi, Freni, Angelo, Marocco, Luca, Scudeler, Gabriele, De Antonellis, Stefano
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
Low-Voltage Electric Vehicle with a Reconfigurable Powertrain Architecture for Urban and Extra-Urban Mobility2026-37-0025To be published on 06/09/2026
The growing penetration of electric mobility in urban environments calls for vehicle solutions that balance accessibility, safety, and operational flexibility. However, high upfront costs and the widespread oversizing of battery systems remain significant barriers to large-scale adoption, particularly for short-range use cases. To address these limitations, this paper presents the Low Voltage Reconfigurable Electric Vehicle (LVREV), a modular vehicle concept designed to bridge the gap between L7e and M1 categories. The proposed architecture integrates a low-voltage electrical system (<60 V), a reconfigurable powertrain, and a modular, swappable battery, enabling mission-adaptive performance while reducing cost, weight, and energy consumption. The vehicle architecture features a dual 52 V inverter system coupled with a six-phase permanent magnet synchronous motor, optimized through model-based design and genetic algorithms. Energy storage consists of two independent swappable battery
Tramacere, Eugenio, Favelli, Stefano, Galluzzi, Renato, Tonoli, Andrea
Automated Design Sustainability Evaluation Framework: a CAD-Integrated Tool for Real-Time Costing and LCA in Automotive Engineering2026-37-0044To be published on 06/09/2026
As the automotive industry faces increasingly rigorous environmental regulations and an approaching obligation for Digital Product Passports (DPPs), incorporating sustainability metrics into the early design phase has become a necessity. Traditionally, Life Cycle Assessment (LCA) and manufacturing cost estimation are performed during or after the design phase using specific methods and tools, resulting in costly iterations and delayed decision-making. This paper introduces a preliminary computational tool that combines 3D CAD and spreadsheet software via VBA integration. The framework automates the generation of an “Extended Bill of Materials” by extracting geometric and manufacturing data directly from CAD models. This tool’s classification logic is a key innovation that intelligently processes CAD features to identify component categories, such as sheet metal, machined parts, or plastic injections. This automated recognition allows the framework to implement specific algorithmic
Guadagno, Maurizio, Cecconi, Leonardo, Berzi, Lorenzo, Delogu, Massimo
Experimental investigation on cold start and warm-up phases for an ethanol fueled SI engine.2026-37-0031To be published on 06/09/2026
Engine operation during the initial warm-up period is characterized by pronounced thermal non-uniformities, which have a direct impact on fuel efficiency, combustion stability, tailpipe emissions and engine long-term reliability. For these reasons, accelerating the warm-up process represents an effective strategy to improve both environmental impact and overall engine performance. This paper presents an experimental study carried out on a 1.2 liter, naturally aspiered, four-cylinder SI engine equipped with a Port Fuel Injection (PFI) system. The engine is fueled with standard gasoline and an ethanol-gasoline blend containing 30% ethanol by volume (E30), with the aim of assessing the influence of fuel formulation on thermal evolution after a cold start. Each test begins with the engine at ambient temperature and is continued until thermal equilibrium is established. Experiments are carried out at a single steady operating point of 2000 rpm and 20 Nm, selected to reproduce representative
Falbo, Luigi, Falbo, Biagio, Perrone, Diego, Castiglione, Teresa
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
Enabling Digital Transformation in Aerospace: Automated Model Based Engineering2026-26-0722To be published on 06/01/2026
Model-based development (MBD) and testing are critical for airborne software compliance with DO-178C and its supplement DO-331, which specifically addresses model-based approaches for software levels A through D. Traditional manual methods for MBD and testing are time-consuming and prone to variability, impacting consistency, accuracy, and certification timelines as avionics systems grow in complexity. This paper presents an automation framework designed to align with DO-331 objectives by leveraging fine-tuned large language models (LLMs) to automate the generation of high-level textual requirements and low-level model-based requirements. From these, comprehensive test cases are automatically derived, covering normal, edge, mutant, and dynamic scenarios to ensure thorough validation of model behavior. Utilizing Boeing AI, the framework extracts requirements and key parameters from documentation, enabling automated specification analysis and test script generation that simulate real
Lalchandani, Tushar, Purushothaman, Kalaivani, Jeppu, Yogananda, Vijaya Kumar, Shree Harsha, Natarajan, Akilandeswari
Neural Network-Enabled Synthetic Air Data System: Development and Validation2026-26-0720To be published on 06/01/2026
Synthetic Air Data System (SADS) provides a smart solution that can be used to predict critical air data parameters in the absence of conventional air data sensors. Traditional air data sensors, such as pitot-static tubes and vanes, are generally expensive, require regular maintenance, and can fail in harsh weather conditions. In addition, these sensors, along with their processor and computers, add weight to the aircraft. To address these issues, a synthetic air data system is proposed using a Recurrent Neural Network (RNN). Several flight variables were checked for Pearson correlation coefficient with respect to the angle-of-attack and angle-of-sideslip, and thereafter, input features were selected based on the thresholding technique. The proposed neural network has two hidden layers and regularization technique was implemented by adding two dropout layers to each hidden layer to prevent overfitting of the model. The neural network was trained using actual flight test data
Sahu, Sanju, C, Poornima, Kaliyari, Dushyant, TK, Khadeeja Nusrath, Hebbar, Archana
Automating DO-178C Verification & Security Compliance in DevSecOps CI/CD Pipelines for Safety Critical Avionics Software2026-26-0717To be published on 06/01/2026
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 Ravi, Changappa, Naveen Kumar, Nath, Sunny
Impact Study of Terrestrial Jamming on GNSS receiver on-board Launch Vehicles and Mitigation Techniques2026-26-0766To be published on 06/01/2026
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO's new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO's LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analysed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise ratio and corresponding change in RF AGC gain is also observed. The issue is
A, Mohammed Basim, O T, Anand Shankara, V S, Biju, V Gopal, Biju, V S, Vinoj, K, Balan, C, Radhakrishna Pillai
Electric Health-Monitoring Wiring (E-Wiring) for Aircraft2026-26-0785To be published on 06/01/2026
Modern aircraft depend on extensive electrical wiring networks for power distribution, avionics, and control systems; however, these wiring systems are vulnerable to wear, insulation degradation, and arcing over time, leading to safety risks and costly unscheduled maintenance. The proposed Electric Health-Monitoring Wiring (E-Wiring) system integrates temperature, current, insulation, vibration, and environmental sensors directly into aircraft wiring harnesses to enable continuous monitoring and intelligent fault detection. Data from these embedded sensors are processed through a distributed edge AI network, forming an Electrical Health Monitoring System (EHMS) capable of real-time diagnostics, predictive maintenance, and fault localization. The architecture comprises smart cable segments with sensor nodes, local harness gateways for edge processing, aircraft-level EHMS integration via AFDX/Ethernet, and cockpit or maintenance displays linked to ground-based cloud analytics for fleet
Tammana, Bala Sai Sri Rohit, Murthy, Harsha, Mendu, HarikaSivaniSunandha
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
Mitigation of Assembly-Induced Cracking in Cyclo Olefin Polymer (COP) Optics through Annealing and Step-Torquing Technique2026-26-0764To be published on 06/01/2026
Light Emitting Diode (LEDs) are the main source of light in Aircraft lighting systems and are mounted on a Circuit Board Assembly (CBA). For some applications, Optics are mounted concentric to these LEDs so that light is focused in the required areas. Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted as Optics due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively high notch sensitivity and the presence of residual molding stresses make them prone to crack initiation during mechanical fastening. In this case study, Optic was fastened directly onto the CBA using self-threading fasteners. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with aerospace durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and
S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen
Unified and Certifiable Cybersecurity Management Framework for IVHM2026-26-0767To be published on 06/01/2026
Commercial and military aircraft’s are increasingly rely on Integrated Vehicle Health Management (IVHM) as a critical enabler for predictive maintenance, operational efficiency, and mission availability. The evolution of IVHM data communication architecture- from legacy wire-based networks to wireless based architecture, involving onboard wireless sensor networks (WSN) and IP-based air-to ground communication networks, including satellite-enabled data links – introduces and expand multi domain, multi channel cyber-physical attack surfaces that challenge both functional, operational safety and continued airworthiness. DO-326A/ED-202A and DO-356A/ED-203A standards define aviation cybersecurity requirements within a safety-driven assurance context, and IEC 62443 standard offers a defense-in-depth, lifecycle-based control framework for industrial systems. A unified approach by mapping and harmonizing the complimentary aspects of these two standards has the potential to simplify and
Samudrala, Ramakrishna, Ramamurthy, Prasanna
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
Electric Air Mobility Using Fuel Cells2026-26-0774To be published on 06/01/2026
Electric air mobility (EAM) is redefining the future of aviation by presenting sustainable, efficient, and adaptable solutions for both urban and regional travel. Within this emerging field, aircraft powered by fuel cells are rapidly gaining recognition as a promising route toward cleaner skies. Hydrogen fuel cells, in particular, stand out due to their impressive energy density, quick refueling times, and the fact that they emit no pollutants during operation. This makes them an appealing replacement for traditional internal combustion engines, as well as an alternative to conventional battery-electric systems. This document delves into the core principles, benefits, challenges, and long-term prospects of adopting fuel cell technology for electric air mobility. It examines how these advancements could revolutionize aviation and significantly support the global push for decarbonization. Specifically, the study evaluates Proton Exchange Membrane (PEM) fuel cells operating at 60
Kari, Sreedhar, Kolipaka, Pradeep
Data-Driven Air Traffic Management: Forecasting Demand, Modeling Delay Propagation, and Demand Capacity Balancing2026-26-0772To be published on 06/01/2026
Air traffic management (ATM) systems must accurately estimate flight demand, analyze network delays, and optimize capacity. This research uses a global airline dataset with passenger information, airport characteristics (including geographic markers and continental classifications), flight scheduling data (timing and destination details), crew information, operational status records, and OpenSky Network real-time states data to create an intelligent ATM decision-support framework. Advanced machine learning (ML) methods like gradient boosting and sequential modeling are used to build network models of flight routes between origins and destinations, develop temporal demand patterns for individual airports, analyze delay factors, and predict congestion periods. The research uses mixed-effects statistical models using crew data to measure operational variability and demographic and nationality-based analysis to identify demand trends for improving staffing and security processing during
Senthilkumar, N., S, Gopalakrishnan, Gopinath, S
Electrical Harnessing in Satellite Launch Vehicles of ISRO – Methods for Sustainable, Safe, and Reliable systems2026-26-0779To be published on 06/01/2026
The electrical harness serves as the "neural network" for satellite launch vehicles, providing the interfaces for all guidance, health monitoring, and control systems during a mission. This system is composed of cables, and connectors. The wires are made of metallic conductors, typically copper plated with silver or gold to enhance conductivity and prevent oxidation. These conductors are insulated with polymeric materials such as PTFE, Kapton, ETFE, or TKT. Connectors, which are the interface points for electrical circuits, consist of gold or nickel-plated copper contacts housed within a shell. A typical launch vehicle contains an extensive network of electrical harnesses, with approximately 4,200 connectors and 110,000 meters of cable, which contributes to about 30% of the vehicle's total weight. The weight is mostly due to the polymeric insulation rather than the conductors. Challenges and Solutions for Sustainable Systems The paper highlights several key issues with current
K S, Nithish, TR, Binny, D S, Praveen Kumar
Evaluation of APNT systems to support PBN operations in lieu of GNSS over Indian air space2026-26-0769To be published on 06/01/2026
At present airborne navigation is primarily dependent on GNSS to enable Performance Based Navigation (PBN) services, both Area Navigation (RNAV) and Required Navigation Performance (RNP), to aviation users on a global scale. However, due to the apparent increase in the disruption of GNSS signals in the airspace due to radio frequency interference (RFI), in the event of loss of GNSS, this dependency may lead to inefficient use of airspace and potentially lead to service degradation. Thus, making the sole reliance on GNSS untenable highlighting the need for RNP services based on terrestrial sources. A key aspect of making PBN resilient to RFI and other GNSS threats is to evaluate the current capability and drive modernization of Alternate Positioning, Navigation and Timing (APNT) systems to support seamless RNP operations. Improvements in PNT integration with other aircraft systems and enhancements in RFI situational awareness provided to operators/flight crews are essential to fully
Narayanan, Shrivathsan, Kottackal, Sebin K, Roy, Joydeep
Hybrid Physics-Informed Neural Network and PID Control for Fault-Tolerant Autonomous Multi-copters2026-26-0770To be published on 06/01/2026
This paper addresses the critical challenge of fault-tolerant control in autonomous multi-copters, particularly under conditions of one or two rotor failures a scenario that often leads to severe instability and a complete loss of directional control due to unbalanced torque and resultant autorotation. Existing advanced control strategies, including optimal approaches such as LQR, typically require precise system modeling and state estimation, which are difficult to achieve in real-world, dynamic failure scenarios. Alternative methods like fuzzy logic, sliding mode control, and gain-scheduling either lack robust generalization or are impractical for enumerating all possible failure cases. In this work, a hybrid control framework integrating Physics Informed Neural Networks (PINN) with a standard PID controller is proposed for fault-tolerant operation of autonomous multi-copters subject to multiple actuator failures. PINNs incorporate governing physical laws as regularization in their
Charapalle, Samruddhi, Venugopalan, Nandagopalan, Nerkundram Muralidharan, Arun, Sundararaj, Laveen
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
Leveraging True Altitude Data to Improve Static Pressure Calibration from Dynamic Manoeuvres2026-26-0729To be published on 06/01/2026
Accurate calibration of aircraft air data systems is essential for reliable measurement of flow angles, altitude, and airspeed, particularly during dynamic flight manoeuvres where errors can become significant. Externally mounted vanes and probes are used to measure flow angles, local pressures and temperature, respectively. However, because these sensors are positioned close to the aircraft fuselage, they operate within disturbed local flow fields that differ notably from the free-stream conditions. As a result, their outputs require Position Error Corrections (PEC) to accurately estimate free-stream parameters such as pressure, temperature, and flow angles. The pre-flight PEC data or calibration tables for these sensors are generated based on the CFD predictions/wind tunnel experiments. All the flight-measured local variables from air data sensors need to pass through the air data computers, which contain these lookup tables, to obtain the free stream information. Despite the pre
TK, Khadeeja Nusrath, Patel, Dr. Ambalal V, J, Prabhavathi Bhai
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
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.
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
Comparative study between MQTT 3.1 and MQTT 5.0: Evaluating Theoretical Enhancements Through Practical Throughput Benchmarks for Aerospace IoT Systems2026-26-0711To be published on 06/01/2026
As aerospace platforms increasingly adopt connected architectures for avionics, telemetry, and predictive diagnostics, lightweight messaging protocols have become foundational. MQTT (Message Queuing Telemetry Transport), due to its simplicity and minimal network overhead, is widely used in both ground and onboard aerospace systems. With the release of MQTT 5.0, the protocol introduces a suite of new capabilities designed to enhance scalability, reliability, and diagnostics. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper presents a comparative evaluation of MQTT 3.1 and MQTT 5.0, exploring their theoretical differences — such as reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and enhanced error feedback — and their impact on system-level performance. We analyze these aspects using practical throughput benchmarks
Bhuyar, Prabhudev, M, Meghana, Kaniraja, Christina, Thomas, Tinto
A Clamping-Based Design Approach for Optical Assemblies in Aircraft Lighting: Eliminating Fastener-Induced Cracks and Validated by Thermo-Mechanical Testing2026-26-0750To be published on 06/01/2026
Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. Currently, Aircraft Lights are based on Light Emitting Diode (LED) technology, where they are mounted on a Circuit Board Assembly (CBA). For some applications, Total Internal Reflection (TIR) Optics are mounted concentric over these LEDs so that light is focused in the required areas. The use of high-performance polymers such as Cyclo Olefin Polymers (COP) for these Optics provides excellent light transmission and stability. Hence, there is a need to secure these Optics to CBA. A critical challenge is securing the Optics to CBA. In the initial design, Optic was fastened directly onto the CBA using self-threading fasteners. However, due to inherent properties of COP, this fastening method proved not ideal. During assembly, frequent crack initiation was observed around the fastener locations, raising concerns over durability, reliability, and
Vialta, Frederico, S, Nikhil, Katageri, Praveen, SP, Pradeep, Singh, Abhimanyu Kumar
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
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
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
AI Based Energy Sustained Series Hybrid Aircraft2026-26-0776To be published on 06/01/2026
This paper investigates the energy consumption characteristics of series hybrid aircraft with a focus on comparing conventional energy management approaches against an AI-powered optimization framework. The study comprehensively models the energy demands of a series hybrid aircraft across all major flight phases, including Idle & Ground Operations, Taxi, Takeoff, Climb, Cruise, Descent, Approach, Landing, and Rollout & Taxi. For each phase, detailed mathematical formulations are developed to capture power requirements and energy flow, incorporating real-time operational parameters to enhance the accuracy of the energy consumption estimations measured in kilowatt-hours (kWh). The AI-based optimization leverages advanced control strategies, specifically Model Predictive Control (MPC) and Reinforcement Learning (RL) algorithms, to dynamically manage the aircraft's energy systems. MPC is employed to predict and optimize future energy usage by solving constrained optimization problems over
Kanchagar, Amogha
Drilling Studies on Sustainable Lightweight Hybrid Polymer Matrix High Performance Nanocomposites2026-26-0732To be published on 06/01/2026
Worldwide, engineers are exploring the possibility of using polymer composites in their quest for lightweight materials. In an effort to create polymer composites that are less harmful to the environment, the use of biodegradable polymers has been investigated in recent years. Injection molding was used to create a biodegradable polymer composite containing 20 wt.% vetiver fibers (VFs) and 2 wt.% nano-silica (nSiO2) obtained from pearl millet. Parts for unmanned aerial vehicles, interior cabin panels, seating structures, and secondary structural components were made of this composite. Desirability analysis was used to examine and optimize machining (drilling) studies that were designed according to Taguchi's design (L9 orthogonal array). Surface roughness (Ra) and delamination factor (DF) were taken as outputs, while spindle speed (SS) ranging from 1000 to 3000 rpm, feed rate (FR) from 15 to 45 mm/min, and drill diameter (DD) from 6 to 10 mm were used as inputs. The developed
Senthilkumar, N.
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
Aircraft cabin Diagnosis - Inspection of the Aircraft cabins and seats using AI2026-26-0789To be published on 06/01/2026
Operational challenges related to aircraft interiors particularly damaged seats, compromised seat cushions, and liquid or food spillages have a direct impact on airline operations and passenger satisfaction. Allowing passengers to use defective seating not only degrades the travel experience but also risks damaging the airline’s reputation. Moreover, addressing these issues often results in increased aircraft ground time, contributing to significant financial implications for airline operators. To mitigate these challenges, a predictive maintenance approach leveraging artificial intelligence (AI) is proposed. This system utilizes radar scans and high-definition camera images captured when the aircraft is unoccupied to detect interior issues. The collected data is then compared against a baseline “master scan” taken under ideal, clean, and properly maintained conditions. Advanced AI algorithms analyze these comparisons to accurately identify problem areas, down to specific seat
Nagoal, Chandrasekhar Reddy, Prathipati, Krishna Chaitanya, Kandukuri, Ravindra
A GenAI-Based Approach for Real-Time Multilingual In-Flight Communication Systems.2026-26-0784To be published on 06/01/2026
In today’s global aviation industry, passenger experience is strongly influenced by effective communication. In-flight announcements, often limited to English and a single local language, can create confusion and stress for international travelers who may not be fluent in either. This communication gap not only impacts passenger comfort but also poses potential risks in conveying time-sensitive or safety-critical information. Recent advances in Generative Artificial Intelligence (GenAI), particularly in speech recognition, neural machine translation, and naturalistic text-to-speech, provide a pathway to overcome these challenges. This paper explores the concept of real-time multilingual in-flight announcements, delivered in each passenger’s preferred language through connected headphones or personal devices. The proposed system architecture integrates speech-to-text conversion, language translation, and speech synthesis with aircraft infotainment platforms. Potential applications range
Mishra, Ashwini, Kature, Kartik, Patil, Ashish
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
A Comparative Assessment of Fuel Cell and Battery Powertrains for Formula Student Electric Applications2026-01-5032To be published on 04/27/2026
The organizers of the most prominent Formula Student competitions have recently initiated a preliminary feasibility study on the application of hydrogen-based propulsion technologies in future single-seater race vehicles. These include electric powertrains with electrochemically converted hydrogen in fuel cell–powered vehicles, competing within the electric championship league. Based on the initial set of regulations, this study presents a model-based comparison between battery-powered (BEVs) and fuel cell–powered electric vehicles (FCVs) for Formula Student. The analysis is conducted using energy, power, and efficiency metrics from four candidate models of propulsion systems, implemented in an open and publicly available MATLAB script: two BEVs with varying battery capacities, and two FCVs employing different hybridization strategies. The aim of this study is to pinpoint and quantify the advantages and disadvantages of each technology for the Formula Student use case, and to identify
Martoccia, Lorenzo, Breda, Sebastiano, Fontanesi, Stefano, d’Adamo, Alessandro
TUBING, PLASTIC, EXTRA FLEXIBLE, CONVOLUTED, HELICAL, ETHYLENE TETRAFLUOROETHYLENE (ETFE), CLOSE CONVOLUTIONAS81914/5D (Current)4/25/2026
AE-8C1 Connectors Committee
Design and Handling Guide Radio Frequency Absorptive Type Wire and Cables (Filter Line, AS85485)AIR4465B (Current)4/25/2026
This document presents design and application information which will allow optimized utilization of filter line wire and cable purchased to AS85485. Filter line wire is defined and design information is presented. The electrical and mechanical performance characteristics of the wire, along with recommended harnessing methods and techniques, are also presented.
AE-8A Elec Wiring and Fiber Optic Interconnect Sys Install
Orchestrating Agents for Automotive Research2026-01-50314/24/2026
Automotive research landscape currently is driven by emerging technologies such as software-defined vehicles, advanced infotainment systems, and increasingly automated driving functions. This situation calls for a bigger need for efficient, comprehensive, and agile research methods. Traditional methods require significant manual effort, leading to information synthesis and dissemination bottlenecks. After doing a thorough research on how research is carried on in automotive companies, it is inferred that a lot of time is spent on gathering information and integrating it with proprietary knowledge rather than on analysis or synthesis of the information. There are tools and platforms with artificial intelligence (AI) advancement that help with deep research of a particular topic, and there are also tools and platforms that help with synthesis of proprietary information within automotive organizations. But there is a lack of a framework that dynamically integrates the aspect of deep
Vemuri, Pavan
CONTACTS, SOCKET, CRIMP REMOVABLE, CONNECTORS, ELECTRICAL, CIRCULAR, MINIATURE, COMPOSITE, HIGH DENSITY, QUICK COUPLING, ENVIRONMENT RESISTANT, (FOR AS29600 SERIES B)AS29600/23B (Current)4/22/2026
AE-8C1 Connectors Committee
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