This study investigates the impact of hydrogen soaking on the medium-cycle fatigue behavior of various metallic materials commonly used in gas transmission pipelines. The tested materials include ex-service gray cast iron, ex-service X52 carbon steel, brass, and welded X52 carbon steel. A comprehensive fatigue testing program was conducted on both as-received and hydrogen-soaked specimens. Rigorous statistical analysis of the results revealed minimal impact of hydrogen on fatigue life for the materials and hydrogen charging conditions studied. The experimental data for hydrogen-soaked specimens aligned closely with baseline scatter bands from as-received specimens. This work suggests that, for the specific hydrogen-charging procedure and fatigue testing conditions employed, additional considerations for hydrogen effects in fatigue design may not be necessary for the materials examined.
In order to mitigate the challenges associated with exploration and inspection within confined environments, a cost‐effective (<£150) hand‐wearable system (i.e., EyeGlove) is proposed to help operators track their hand movements when performing camera‐based inspection in confined environments by leveraging the inherent dexterity of the human hands as manipulators. The EyeGlove system integrates two low‐cost cameras and two sets of contact pads (working with magnets), thereby creating a stereo camera system characterized by disjointed camera configurations. When wearing the EyeGlove system, operators harness the manipulation capabilities of their hands to pose the cameras, enabling real‐time in situ visual inspection within confined spaces. While the construction of the measurement function has been reported, we are now enhancing the facility by enabling hand tracking for in situ maintenance and service. This provides a comprehensive solution encompassing inspection, measurement, and tracking capabilities, setting the EyeGlove system apart from other systems. Building upon the unique design of the EyeGlove system, which features disjointed camera configurations, this paper proposes a novel hand tracking method tailored to the low‐cost EyeGlove camera, based on sparse optical flow techniques, i.e., the Lucas–Kanade method. The proposed tracking method utilizes optical flow‐based keypoint/feature match techniques in both stereo match and frame match to achieve robust hand movement tracking, which is specifically customized for the low‐cost cameras of the EyeGlove system. Finally, validation experiments have been conducted to demonstrate the tracking performance of the EyeGlove system in confined environments with various lighting conditions.
The introduction of advanced automation and human-artificial intelligence (AI) teaming is expected to permit more efficient use of airspace in the face of increasing air transport demand. Additionally, the development of next-generation aircraft to support net-zero has introduced more complexity into the future flight deck and informational requirements. This study evaluates a design for an 'intelligent assistant' system that could share tasks with the pilot during engine failure and pilot incapacitation events, promoting greater reliance on system interaction as workload increases. Four professional pilots were split into two groups to perform six and eight scenarios, respectively. The aim was to identify the task-related information for the designed system to promote transparency to the pilots. Three modalities varied across each scenario (visual, auditory and physical) to evaluate the combination of modality to increase pilot monitoring and interaction with the system. Analysis of participant feedback indicated key limitations to existing human-machine-interaction design, with current operational procedures creating disparity between the system and pilots' authority to handle the scenario. Additionally, the use of audio narration was negatively received by participants, primarily due to the potential overlap between other audio stimuli, masking the perception of task-critical audio prompts and delaying critical flight tasks from being performed. Design considerations were generated for future 'intelligent assistant' systems, with further research required to understand the effect of each modality on pilot reliance on these 'intelligent assistant' systems.
Conventional strategies to strengthen alloys are usually accompanied by drastic sacrifice in ductility, which is known as the strength-ductility trade-off. New metallurgical processing approaches are required to defeat this longstanding dilemma. Here we report a novel solid-state powder manufacturing route to overcome this challenge enabling the architecting of a complex multiphase constituent composite using readily available metal powder as a feedstock. The materials design philosophy is successfully verified in a system mixing conventional austenitic stainless steel and ferritic steel powder and consolidating it by hot isostatic pressing. Significant strengthening and work hardenability are achieved at no expense of ductility compared to the ferrite and austenite on their own. Such extraordinary strength-ductility synergy is attributed to the well-architected compositional gradients across different phases resulting in soft and hard regions at the scale of the original powder without sharp interfaces. Accordingly, plasticity progresses from soft to hard regions during mechanical loading, which is the key to mitigating the deformation incompatibility and enabling remarkable ductility. Our study provides a new concept for materials design with synergistic properties that used to be trade-offs in conventional materials, which is applicable to a broad range of material systems with unprecedented multifunctionality. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
Interconnected intelligent systems in multi-stage smart machining environments are an advancing area of research, demonstrating many real-life opportunities that can benefit from the development and integration of cyber-physical systems into machining habitats, while different automation levels in industrial manufacturing sites call for flexibility of core strategies towards smart machining ecosystems. This article introduces a versatile and smart multi-stage machining environment for the controlled clamping and machining of low-rigidity structures in an interconnected cyber-physical factory. This is exemplified by a deformation-prone thin-wall workpiece, which undergoes controlled clamping, enabled by interchangeable robotic automation and automation via human-cyber-physical systems, as well as digital-twin-assisted corrective machining enabled by the swift estimation of workpiece deformations and multi-stage communication between machining habitats. The underlying digital twin presents a fast, lightweight simulation approach, based on a mass-spring-lattice model, allowing information flow from and to systems, which is utilized by the CNC machine as well as the interchangeable robot- and human-in-the-loop clamping enablers. By employing this controlled clamping approach workpiece deformations are aimed to be minimized. At the same time, a desired total clamping force is achieved in order to perform subsequent digital-twin-assisted machining corrections to reduce deformation-caused flatness errors. Ultimately, this article presents an intelligent multi-stage machining scenario where digital-twin enabled information moves along with thin-wall structures and branches out for knowledge-based control and corrections to robots, humans and CNC machines respectively, showcasing a real-life example for versatile, information-driven smart machining ecosystems.
