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Proceedings Volume NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE II, PC1295201 https://doi.org/10.1117/12.3019015
Due to recent advancements in electric propulsion, battery technology, and aerodynamics, eVTOL (electric Vertical Take-off and Landing) aircraft are heralded as the next frontier in the aviation industry. However, unlike their conventional counterparts, eVTOLs are much smaller in size and lighter in weight, creating challenges in navigating through turbulent atmospheric conditions at lower altitudes. Consequently, these aircraft must demonstrate exceptional agility to effectively maneuver through challenging weather conditions. Complicating matters further, eVTOLs rely on battery power, whose reliability and health status remain unpredictable and difficult to gauge precisely, thereby introducing additional complexities to their operation and maintenance. Therefore, innovative techniques are needed to ensure flight safety and battery health.
In this presentation, we will introduce novel fly-by-feel and battery health monitoring techniques based on integrated piezoelectric sensor/actuator networks. These techniques are aimed at making eVTOL operations safer and more efficient by providing real-time high-fidelity insights into flight mechanics and battery performance, thereby empowering operators to make informed decisions and mitigate potential risks effectively.
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Proceedings Volume NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE II, PC1295202 https://doi.org/10.1117/12.3015097
Computed Radiography for Nondestructive Imaging Applications of Aircraft Structures
The aerospace industry has stringent product quality requirements to ensure structural integrity of critical components, safety and airworthiness of aircraft. Non-destructive inspections (NDI) are routinely performed to ensure product quality and identify defect before it reaches critical size. Several NDI methods, including industrial radiography, play a key role in the inspection process and is the most widely used method for detection of volumetric defects. Digital computed radiography (CR) eliminates the needs for films and processing chemicals. However, the digital radiography systems require a regular and careful performance evaluation. Presentation highlights the CR performance metrics including traditional radiography factors as well as new digital imaging related factors such as spatial resolution, signal-to-noise ratio (SNR), contrast to noise ratio (CNR), equivalent penetrameter sensitivity (EPS) and how those parameters affect the final output image, defect detection capability and overall performance of CR.
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Proceedings Volume NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE II, PC1295204 https://doi.org/10.1117/12.3012617
In this talk, we highlight the need for advanced inspection methods in EV cell manufacturing at gigafactory scales that deliver comprehensive information for 100% of cells produced to assess the true cell quality distribution and prevent quality escapes. We share how cell and pack manufacturers can achieve and maintain higher quality faster and at lower overall cost by utilizing Liminal’s in-line high-throughput primary inspection to screen 100% of cells produced and high-resolution secondary inspection to diagnose anomalous cells. We discuss the use of ultrasound inspection and physics-assisted machine learning methods to assess cell quality, better than state-of-the-art electrochemical methods.
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Proceedings Volume NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE II, PC1295205 https://doi.org/10.1117/12.3015507
Low mechanical capability currently limits the applicability of lithium-ion batteries for use in the structural components of electric vehicles and aircraft. This paper introduces a new Multifunctional Energy Storage Composites (MESC) concept to achieve a good balance between high energy density and mechanical strength with minimal compromise. The proposed MESC involves reinforcing lithium-ion battery cells using embedded rivets and integrates the cells into a CFRP composite structure. This research employs a combination of experimental and computational tools to conduct a comprehensive parametric study aimed at maximizing the mechanical and electrical performance of MESC. Multiple MESC samples underwent three-point bending tests and a multi-physics simulation model was developed using Abaqus to validate their manufacturing limits. The results demonstrate that the MESC significantly enhances the load transfer capabilities of CFRP composite sandwich structures with a battery core. This advancement holds promise for the development of electric vehicle body structures with improved performance.
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