Vincent Paquit Section Head, Secure & Digital Manufacturing Contact 865.241.1789 | PAQUITVC@ORNL.GOV All Publications A Co-Registered In-Situ and Ex-Situ Dataset from Wire Arc Additive Manufacturing process FY23 Multi-Dimensional Data Correlation Platform: Unified Software Architecture for AMMT Data Management and Processing Review of In Situ Sensing for Directed Energy Deposition for Industrial Part Quality Assessment Peregrine Software Development: Report on the Code Conversion From Python to C++ FY 2024 Multidimensional Data Correlation Platform Data Management Infrastructure Progress: Materials Laboratory FY 2024 Multidimensional Data Correlation Platform: Unified Software Architecture For Advanced Materials And Manufacturing Technologies Data Management And Processing Denoising diffusion probabilistic models for generative alloy design Deep-learning based artificial intelligence tool for melt pools and defect segmentation Recent Advances on the Use of In Situ Monitoring as an Nondestructive Evaluation Tool for Additive Manufacturing Processes Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in L-PBF... A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts Deep Learning Based Workflow for Accelerated Industrial X-Ray Computed Tomography Neural network-based single material beam-hardening correction for X-ray CT in Additive Manufacturing IN-SITU MONITORING ASSISTED LARGE-SCALE ADDITIVE MANUFACTURING OF MILD STEEL AND 316L ALLOYS FOR NUCLEAR APPLICATION Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning Methods for rapid identification of anomalous layers in laser powder bed fusion... Process Optimization... Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction Towards generic memory forensic framework for programmable logic controllers Observation of spatter-induced stochastic lack-of-fusion in laser powder bed fusion using in situ process monitoring Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction Advancement of Certification Methods and Applications for Industrial Deployments of Components Derived from Advanced Manufacturing Technologies High Throughput Deep Learning-Based X-ray CT Characterization for Process Optimization in Metal Additive Manufacturing A scalable digital platform for the use of digital twins in additive manufacturing Data Mining and Visualization of High-Dimensional ICME Data for Additive Manufacturing Pagination Current page 1 Page 2 Page 3 Next page ›â¶Äº Last page Last » Key Links Curriculum Vitae Organizations Energy Science and Technology Directorate Manufacturing Science Division Secure and Digital Manufacturing Section
