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Meeting MS&T26: Materials Science & Technology
Symposium Additive Manufacturing: Equipment, Instrumentation and In-Situ Process Monitoring
Presentation Title Self-Sensing of 3D-Printed Materials by Measuring the Inductance, Resistance and Capacitance
Author(s) Deborah D.L. Chung
On-Site Speaker (Planned) Deborah D.L. Chung
Abstract Scope Self-sensing refers to sensing using the build as the sensor of its own condition, without sensor incorporation. It is achieved by electrical measurement on the build. Inductance-based and resistance-based self-sensing are effective for conductive materials, such as metals and conductor-filled polymers. Capacitance-based self-sensing is effective for non-conductors, such as unfilled polymers. The defects sensed include artificial subtle interlayer defects. The infill angle is also sensed. The inductance is more sensitive than the resistance, due to greater sensitivity of the inductance to current path tortuosity. Both defects and infill angle enhance the tortuosity. For continuous carbon fiber polymer-matrix composites, the contact resistivity of the interlaminar interface is sensitive to the damage (which tends to start at this interface), stress and temperature. The capacitance is sensitive to defects due to the intersection of the defects with the electric field lines emanating from coplanar electrodes. Sensitivity is also shown for the defect position.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

AMDiffusion: Domain-Adaptive Diffusion Modeling for Causal Data Fusion in Additive Manufacturing
Beyond Deep Learning: A Bayesian-Optimized Computer Vision Framework for Rapid Spatter Detection and Tracking in Laser Powder Bed Fusion
Designing Sensor Systems for Anomaly and Flaw Detection in Laser Powder Bed Fusion Additive Manufacturing
Hybrid Feedforward-Feedback Process Control of Laser Powder Bed Fusion
K2: An Open Architecture Wire-Laser Directed Energy Deposition Testbed for Advanced Control Strategy Development
Large Language Models for In-Situ Interpretation of Defect Signatures in Powder Bed Fusion
Rapid Modeling and Prediction of Thermal Strain in Laser Powder Bed Fusion
Self-Sensing of 3D-Printed Materials by Measuring the Inductance, Resistance and Capacitance
Smoke, Mirrors, and Melt Pools: An Assessment of Commercial PBF-LB In-Situ Process Monitoring Solutions

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