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The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation.

The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

Composite materials, pioneered by aerospace engineering due to their lightweight, strength, and durability properties, are increasingly adopted in the high-performance automotive sector. Besides the acknowledged composite components’ performance, enabled lightweighting is becoming even more crucial for energy efficiency, and therefore emissions along vehicle use phase from a decarbonization perspective. However, their use entails energy-intensive and polluting processes involved in raw material production, in manufacturing processes, and, in particular, in end-of-life disposal. Carbon footprint is the established indicator to assess the environmental impact of climate-changing factors on products or services. Research on different carbon footprint sources reduction is increasing, and even the European Composites Industry Association is demanding the development of specific Design for Sustainability approaches.

Airframe section of rockets, missiles and launch vehicles are typically cylindrical in shape. The cylindrical shell is subjected to high axial load and an external pressure during its operation. The design of cylinders subjected to such loads is generally found to be critical in buckling. To minimize the weight of cylinders, it is typically stiffened with rings and stringers on the inner diameter to increase the buckling load factor. Conventionally the buckling load estimated by analytical or numerical means is multiplied by an empirical factor generally called Knockdown factor (kdf) to get the critical buckling load. This factor is considered to account for the variation between theory and experiment and is specified by handbooks or codes. In aerospace industry, NASA SP 8007 is commonly followed and it specifies the kdf as a lower bound fit curve for experimental data .

The study of aerodynamic forces in hypersonic environments is important to ensure the safety and proper functioning of aerospace vehicles. These forces vary with the angle of attack (AOA) and there exists an optimum angle of attack where the ratio of the lift to drag force is maximum. In this paper, computational analysis has been performed on a blunt cone model to study the aerodynamic characteristics when hypersonic flow is allowed to pass through the model. The flow has a Mach number of 8.44 and the angle of attack is varied from 0º to 20º. The commercial CFD solver ANSYS FLUENT is used for the computational analysis and the mesh is generated using the ICEM CFD module of ANSYS. Air is selected as the working fluid. The simulation is carried out for a time duration of 1.2 ms where it reaches a steady state and the lift and drag forces and coefficients are estimated. The pressure, temperature, and velocity contours at different angles of attack are also observed.

Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.

Electric aircraft have emerged as a promising solution for sustainable aviation, aiming to reduce greenhouse gas emissions and noise pollution. Efficiently estimating and optimizing energy consumption in these aircraft is crucial for enhancing their design, operation, and overall performance. This paper presents a novel framework for analyzing and modeling energy consumption patterns in lightweight electric aircraft. A mathematical model is developed, encompassing key factors such as aircraft weight, velocity, wing area, air density, coefficient of drag, and battery efficiency. This model estimates the total energy consumption during steady-level flight, considering the power requirements for propulsion, electrical systems, and auxiliary loads. The model serves as the foundation for analyzing energy consumption patterns and optimizing the performance of lightweight electric aircraft.

Abstract: The present study discusses about the effect of installation torque on the surface and subsurface deformations for thin walled 7075 aluminum alloy used in Aerospace applications. A FE model was constructed to predict the effect of torque induced stresses on thin walled geometry followed with an experimentation. A detailed surface analysis was performed on 7075 aluminum in terms of superficial discontinuities, residual stresses, and grain deformations. The localized strain hardening resulting from increased dislocation density and its effect on surface microhardness was further studied using EBSD and micro indentation. The predicted surface level plastic strain of .25% was further validated with grain deformations measured using optical and scanning electron microscopy.

Abstract: Hydraulic systems in aircrafts largely comprise of metallic components with high strength to weight ratios which comprise of 2024 Aluminum and Titanium Ti-6AL-4V. The selection of material is based on low and high pressure applications respectively. For aircraft fluid conveyance products, hydraulic conduits are fabricated by axisymmetric turning to support flow conditions. The hydraulic conduits further carries groves within for placement of elastomeric sealing components. This article presents a systematic study carried out on common loads experienced by fluid carrying conduits and the failure modes induced. The critical failure locations on fluid carrying conduits of 2024-T351 Aluminum was identified, and the Scanning Electron Microscope (SEM) analysis was carried out to identify the characteristic footprints of failure surfaces and crack initiation. Through this analysis, a load to failure mode correlation is established.

Aerospace structural components grapple with the pressing issue of high-cycle fatigue-induced micro-crack initiation, especially in high-performance alloys like Titanium and super alloys. These materials find critical use in aero-engine components, facing a challenging combination of thermo-mechanical loads and vibrations that lead to gradual dislocations and plastic strain accumulation around stress-concentrated areas. The consequential vibration or overload instances can trigger minor cracks from these plastic zones, often expanding unpredictably before detection during subsequent inspections, posing substantial risks. Effectively addressing this challenge demands the capability to anticipate the consequences of operational life and aging on these components. It necessitates assessing the likelihood of crack initiation due to observed in-flight vibration or overload events.

The descent phase of GAGANYAAN (Indian Manned Space Mission) culminates with a crew module impacting at a predetermined site in Indian waters. During water impact, huge amount of loads are experienced by the astronauts. This demands an impact attenuation system which can attenuate the impact loads and reduce the acceleration experienced by astronauts to safe levels. Current state of the art impact attenuation systems use honeycomb core, which is passive, expendable, can only be used once (at touchdown impact) during the entire mission and does not account off-nominal impact loads. Active and reusable attenuation systems for crew module is still an unexplored territory. Three configurations of impact attenuators were selected for this study for the current GAGANYAAN crew module configuration, namely, hydraulic damper, hydro-pneumatic damper and airbag systems.

Electromechanical actuators (EMAs) play a crucial role in aircraft electrification, offering advantages in terms of aircraft-level weight, rigging and reliability compared to hydraulic actuators. To prevent backdriving, skewed roller braking devices called "no-backs" are employed to provide braking torque. These technology components are continuing to be improved with analysis driven design innovations eg. U.S. Pat. No. 8,393,568. The no-back mechanism has the rollers skewed around their own transverse axis that allow for a combination of rolling and sliding against the stator surfaces. This friction provides the necessary braking torque that prevents the backdriving. By controlling the friction radius and analyzing the Hertzian contact stresses, the brake can be sized for the desired duty cycle. No-backs can be configured to provide braking torque for both tensile and compressive backdriving loads.

Landing of spacecraft on Lunar or Martian surfaces is the last and critical step in inter planetary space missions. The atmosphere on earth is thick enough to slow down the craft but Moon or Mars does not provide a similar atmosphere. Moreover, other factors such as lunar dust, availability of precise onboard navigational aids etc would impact decision making. Soft landing meaning controlling the velocity of the craft from over 6000km/h to zero. If the craft’s velocity is not controlled, it might crash. Various onboard sensors and onboard computing power play a critical role in estimating and hence controlling the velocity, in the absence of GPS-like navigational aids. In this paper, an attempt is made using visual onboard sensor to estimate the velocity of the object. The precise estimation of an object's velocity is a vital component in the trajectory planning of space vehicles, particularly those designed for descent onto lunar or Martian terrains, such as orbiters or landers.

A GE Aviation Systems report documents that the National Oceanic and Atmospheric Administration (NOAA) provided weather forecast data has a bias of 15 knots and a standard deviation of 13.3 knots for the 40 flights considered for the research. It also had a 0.47 bias in the temperature with a standard deviation of 0.27. The temperature errors are not as significant as the wind. There is a potential opportunity to reduce the operational cost by improving the weather forecast. The flight management system (FMS) currently uses the weather forecast, available before takeoff, to identify an optimized flight path with minimum operational costs depending on the selected speed mode. Such a flight plan could be optimum for a shorter flight because these flight path planning algorithms are very less susceptible to the accuracy of the weather forecast.