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.
Thermo-mechanical fatigue and natural aging due to environmental conditions are difficult to simulate in an actual test with the advanced fiber-reinforced composites, where their fatigue and aging behavior is little understood. Predictive modeling of these processes is challenging. Thermal cyclic tests take a prohibitively long time, although the strain rate effect can be scaled well for accelerating the mechanical stress cycles. Glass fabric composites have important applications in aircraft and spacecraft structures including microwave transparent structures, impact-resistant parts of wing, fuselage deck and many other load bearing structures. Often additional additively manufactured features and coating on glass fabric composites are employed for thermal and anti-corrosion insulations. In this paper we employ a thermo-mechanical fatigue model based accelerated fatigue test and life prediction under hot to cold cycles.
Industries have been increasingly adopting AI based computer vision models for automated asset defect inspection. A challenging aspect within this domain is the inspection of composite assets consisting of multiple components, each of which is an object of interest for inspection, with its own structural variations, defect types and signatures. Training vision models for such an inspection process involves numerous challenges around data acquisition such as insufficient volume, inconsistent positioning, poor quality and imbalance owing to inadequate image samples of infrequently occurring defects. Approaches to augmenting the dataset through Standard Data Augmentation (SDA) methods (image transformations such as flipping, rotation, contrast adjustment, etc.) have had limited success. When dealing with images of such composite assets, it is challenging to correct the data imbalance at the component level using image transformations as they apply to all the components within an image.
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Abstract This research looks into how abrasive water jet machining (AWJM) can be used on carbon fiber-reinforced polymer (CFRP) materials, specifically how the kerf characteristics change with respect to change in process parameters. We carefully looked into four important process parameters: stand-off distance (SOD), water pressure (WP), traverse rate (TR), and abrasive mass flow rate (AMFR). The results showed that as SOD goes up, the kerf taper angle goes up because of jet dispersion, but as WP goes up, the angle goes down because jet kinetic energy goes up. The TR was directly related to the kerf taper angle, but it made the process less stable. The kerf drop angle was not greatly changed by AMFR. When it came to kerf top width, SOD made it wider, WP made it narrower, TR made it narrower, and AMFR made it a little wider. When the settings (SOD: 1 mm, WP: 210 MPa, TR: 150 mm/min, AMFR: 200 g/min) were optimized, the kerf taper angle and kerf top width were lowered.
This specification covers an aluminum alloy in the form of alclad coiled sheet from 0.010 to 0.128 inch (0.25 to 3.25 mm), inclusive, in thickness supplied in the -T4 temper (see 8.5).
Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.
This standard specifies the characteristics of the MJ profile metric series of screw threads, altered from ISO 68 M Profile, to include a mandatory controlled radius of 0.18042P to 0.15011P at the root of the external thread and with the minor diameter of both external and internal threads increased to provide a basic thread height of 0.5625H in order to accommodate the external thread maximum root radius.
This specification covers a corrosion- and heat-resistant steel in the form of bars, wire, forgings, mechanical tubing, flash-welded rings, and stock for forging or flash-welded rings.
This specification covers a corrosion- and heat-resistant steel in the form of work-strengthened bars and wire, 1-1/4 inches (31.8 mm) and under in nominal diameter or least distance between parallel sides.