Scott Smith Section Head, Precision Manufacturing and Machining Contact 865.341.0021 | smithss@ornl.gov All Publications Iterative Stress Reconstruction Algorithm to Estimate Three-Dimensional Residual Stress Fields in Manufactured Components LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies... Hybrid metal additive/subtractive machine tools and applications... Residual stress accumulation in large-scale Ti-6Al-4V wire-arc additive manufacturing Process planning for hybrid manufacturing using additive friction stir deposition Cutting force estimation from machine learning and physics-inspired data-driven models utilizing accelerometer measurements A framework for hybrid manufacturing cost minimization and preform design Evaluation of automated stability testing in machining through closed-loop control and Bayesian machine learning Process window estimation in manufacturing through Entropy-Sigma active learning America’s Cutting Edge CNC machining and metrology training America’s Cutting Edge CNC machining and metrology training Bayesian optimization for inverse calibration of expensive computer models: A case study for Johnson-Cook model in machining Joining technique for in-oven/autoclave molds manufactured by large scale polymer additive manufacturing... Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability Improving Milling Performance on New Computer Numerical Control Machining Centers with Machining Dynamics... Logistic classification for tool life modeling in machining... Iterative hybrid manufacture of a titanium alloy component Surface prediction and measurement for modulated tool path (MTP) turning Rethinking production of machine tool bases: Polymer additive manufacturing and concrete Physics-guided logistic classification for tool life modeling and process parameter optimization in machining Mechanical Vibrations: Modeling and Measurement, 2nd Edition... Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency Cutting force and stability for inserted cutters using structured light metrology Milling stability identification using Bayesian machine learning Dynamic stiffness modification by internal features in additive manufacturing... Pagination Current page 1 Page 2 Next page ›› Last page Last » Key Links Curriculum Vitae Google Scholar ORCID LinkedIn Organizations Energy Science and Technology Directorate Manufacturing Science Division Precision Manufacturing and Manufacturing Innovation User Facilities Manufacturing Demonstration Facility
