/library/oar/handle/123456789/1024 Thu, 25 Dec 2025 21:32:08 GMT 2025-12-25T21:32:08Z /library/oar/handle/123456789/142211 Title: Enhancing fatigue resistance in WAAM AZ80 magnesium and wrought Al6082 through shot peening : a comparative study Authors: Grima, Daniel; Layeb, Nejmeddine; Li, Runsheng; Zammit, Brian; Attard, Bonnie; Zammit, Ann; Cassar, Glenn Abstract: Shot peening is a well-established surface treatment that enhances mechanical performance by inducing plastic deformation, grain refinement and compressive residual stresses. This study evaluates the effects of shot peening on wire arc additively manufactured (WAAM) AZ80 magnesium alloy, benchmarked against wrought Al6082 aluminium—a widely used aerospace material. WAAM AZ80 was assessed in two states: a baseline variant (P1) with significant retained process-induced defects, and an improved version (P2) produced via refined processing parameters. Microstructure, hardness, surface roughness, residual stress and fatigue behaviour were systematically analysed. Shot peening induced notable grain refinement in both materials without causing phase transformations. Surface hardness increased by 18% in Al6082, and by 37% and 45% in WAAM AZ80 (P1 and P2, respectively), mainly due to work hardening and grain boundary strengthening. Increased surface roughness was observed across all conditions. Al6082 exhibited peak compressive residual stresses of ~280 MPa at depths >100 µm, whilst WAAM AZ80 reached ~ 110 MPa at ~ 75 µm. Fatigue life improved by 44% in Al6082, and by 100–350% depending on the orientation of residual defects caused by the AM process in the WAAM AZ80 (P1) specimens. Shot peening proved effective in mitigating the influence of surface and near-surface defects. Densified WAAM AZ80 (P2) samples also exhibited significantly improved fatigue performance after shot peening, reaching the test run-out of 106 cycles without failure. The improvements in WAAM AZ80 are largely attributed to reduced surface-connected porosity and delayed crack initiation. Whilst Al6082 retains superior fatigue properties, shot-peened WAAM AZ80 shows strong potential as a lightweight alternative for weight-sensitive aerospace applications involving cyclic loading. Wed, 01 Jan 2025 00:00:00 GMT /library/oar/handle/123456789/142211 2025-01-01T00:00:00Z /library/oar/handle/123456789/139022 Title: Increasing predictability in the response of an AI-assisted stall recovery system in complex stall conditions by expanding the knowledge-base of AI Authors: Koopman, C.; Zammit-Mangion, David Abstract: The environment in the cockpit of commercial aircraft is becoming increasingly complex due to the introduction of automation systems. This complexity is especially evident when malfunctions take place, making it difficult for pilots to comprehend the interconnectedness of the systems and potentially leading to loss of control. This paper investigates a novel method for creating an Artificial Intelligence-based stall recovery assistant using Reinforcement Learning by training the agent to generate a stall and subsequently recover from it. This enables training in a large training space with a simple reward function, where the agent has the ability to develop a deep understanding of the environment. Tests show that the agent is able to recover from stall at a variety of altitudes while experiencing unreliable airspeed information originating from a blocked Pitot tube system and with a better response than all baseline agents. The results indicate that restricting AI is not always necessary and, further, that too many restrictions can lead to a system that learns only shallow features, causing it to be unreliable in unforeseen circumstances. Mon, 01 Jan 2024 00:00:00 GMT /library/oar/handle/123456789/139022 2024-01-01T00:00:00Z /library/oar/handle/123456789/137445 Title: JARUS whitepaper on considerations for automation of the airspace environment Authors: Bloch-Hansen, Craig; Llucia, Santiago; Kopardekar, Parimal; Gandara Ossel, Roberto; Ryan, Wes; Martin Gomez, David; Gaspar, Alberto; Robles Quilca, Angelica Cristina; Kunchalia, Akaki; Donovan, Todd; Ducci, Marco; Diotalevi, Eugenio; Parkinson, Alan (Stan); Jost, Daniel; Chircop, Kenneth; Velotto, Sergio; Borgna, Ennio; Zaglul González, Diego Ernesto; Raju, Praveen; Martin, Jose; Blum, Scott; Ghazavi, Noureddin; Toews, Tyson; Perca, Andreaa; Sabatini, Roberto Abstract: This document in its draft version is internal to JARUS. It is intended to provide an outline for considering the impact of automation across all aspects of aviation safety, while providing considerations for further developing the future of automation roll-out across the airspace. The scope is limited to safety aspects and does not specifically address broader issues related to liability, cost, or legal authority as these must be interpreted through local customs including the legal system, history, cultural practices, and public acceptance of risk and liability. Mon, 01 Jan 2024 00:00:00 GMT /library/oar/handle/123456789/137445 2024-01-01T00:00:00Z /library/oar/handle/123456789/137440 Title: JARUS methodology for evaluation of automation for UAS operations Authors: Bloch-Hansen, Craig; Llucia, Santiago; Gardi, Alex; Senatore, Costantino; Kazik, Tim; Sayyed, Ruby; Gandara Ossel, Roberto; Ryan, Wes; Martin Gomez, David; Shedden, Michael; Kopardekar, Parimal; Eisele, Christopher; Berry, Andrew; Gaspar, Alberto; Carlos Cirilo, Martin; Zou, Xiang; Robles Quilca, Angelica Cristina; Kunchalia, Akaki; Maitre, Tristan; Mahelo, Keith; Donovan, Todd; Ducci, Marco; Lyu, Renli; Diotalevi, Eugenio; Parkinson, Alan (Stan); Baumgartner, Marc; Jost, Daniel; Swider, Chris; Koh, Bensen; Chircop, Kenneth; Johnson, Marcus; Thurling, Andrew; Velotto, Sergio; Borgna, Ennio; Wain, Gabrielle; Zaglul González, Diego Ernesto; Raju, Praveen; Martin, Jose; Blum, Scott; Ghazavi, Noureddin; Toews, Tyson; Perca, Andreaa; Sabatini, Roberto Abstract: This document is intended to provide a standard view on how to assess functional automation for the JARUS community. The JARUS Automation WG has been tasked with defining a framework for assessing the impact of automation on an concept of operations and developing a framework for evaluating automation in proposed UAS operations. The framework includes definitions, assumptions, levels of automation, and the safety impact assessment methodology. The roles of the manufacturer, operator, pilot, service providers, and regulators are also assessed for each level of automation. Sun, 01 Jan 2023 00:00:00 GMT /library/oar/handle/123456789/137440 2023-01-01T00:00:00Z