National Center for Additive Manufacturing Excellence (NCAME)

The National Center for Additive Manufacturing Excellence (NCAME) invites applications for fully funded PhD student positions. Successful candidates will join NCAME at Auburn University, contributing to cutting-edge research in additive manufacturing. Application link: https://lnkd.in/exY8cWuW Shuai Shao,  Nima Shamsaei Auburn University Auburn University Mechanical Engineering Auburn University, Samuel Ginn College of Engineering #Hiring #PhDposition #AdditiveManufacturing #3DPrinting #AuburnUniversity #NCAME #AdvancedManufacturing

We recently conducted non-linear resonance testing on a metal heat exchanger to evaluate material integrity and detect potential microstructural defects. This technique is powerful because it can identify subtle damage or internal anomalies across a range of parts without destructive testing. It provides another layer of confidence when evaluating components produced through advanced manufacturing processes.   The heat exchanger used in this test was provided by REM Surface Engineering, and the testing was performed using equipment from Theta Technologies Limited (NDT). Both organizations are doing impressive work in post-processing and inspection, enabling better characterization and quality assurance for complex metal components.   Amanda Vogel, Scot Carpenter, P.E., Justin Michaud, Agustin Diaz, Steve Butler, Shuai Shao, Nima Shamsaei   Auburn University Auburn University Mechanical Engineering Auburn University, Samuel Ginn College of Engineering National Center for Additive Manufacturing Excellence (NCAME)   #AdditiveManufacturing #AdvancedManufacturing #3DPrinting #NDE

𝐈𝐧 𝐟𝐚𝐭𝐢𝐠𝐮𝐞, 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐩𝐫𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧 𝐫𝐞𝐚𝐥𝐥𝐲 𝐦𝐚𝐭𝐭𝐞𝐫𝐬.   Before mechanical testing, we use a longitudinal polisher to create a consistent surface finish along the loading direction. This helps minimize surface-induced stress concentrations and improves the repeatability and reliability of our fatigue results.   Small preparation steps like this often make a big difference in data quality. Jiwon Jung, Scot Carpenter, P.E., Shuai Shao, Nima Shamsaei   Auburn University Auburn University Mechanical Engineering National Center for Additive Manufacturing Excellence (NCAME) #NCAME #AdditiveManufacturing #AdvancedManufacturing #3DPrinting

CuNi30 is widely used in aggressive environments such as pipe fittings in marine and offshore oil and gas systems by virtue of its excellent corrosion resistance, fouling resistance, and ductility. Although components used in such applications undergo cyclic loads, the fatigue behavior of CuNi30 remains largely unexplored. In this ongoing study, we designed net-shape tubular specimens that mimic piping geometries commonly used in marine and energy systems, aiming to provide the first insights into the mechanical performance of tubular net-shape laser powder bed fused (L-PBF) CuNi30 parts. This study systemically investigates the fatigue behavior of L-PBF CuNi30 as influenced by geometry and post-processing, which provides meaningful data for the reliable design of L-PBF CuNi30 components in corrosive service environments. Shahab Musavi, Erfan Maleki, Shuai Shao, Nima Shamsaei Auburn University Auburn University Mechanical Engineering National Center for Additive Manufacturing Excellence (NCAME) #AdvancedManufacturing #AdditiveManufacturing #3DPrinting

Don't miss out on the latest research from #NCAME. Join us for insightful talk and engage with our team at #TMS2026. Shuai Shao, Nima Shamsaei Auburn University Auburn University Mechanical Engineering National Center for Additive Manufacturing Excellence (NCAME)   #AdditiveManufacturing #3DPrining #AdvancedManufacturing 

NCAME is at #TMS2026! Come learn about our latest advancements in additive manufacturing. Shuai Shao, Nima Shamsaei   Auburn University Auburn University Mechanical Engineering National Center for Additive Manufacturing Excellence (NCAME) #AdditiveManufacturing #3DPrining #AdvancedManufacturing 

Most laboratory fatigue tests rely on constant amplitude loading, but in-service parts, like those in aerospace or defense, face variable amplitude loading. For additively manufactured (AM) components, understanding how these fluctuating loading impact the structural integrity is the missing link between the laboratory specimen data and the performance of mission-critical parts. In addition, part geometry alters the cooling rates locally, creating a complex micro-/defect-structure of varying grain sizes and location-specific defects that may interact with these variable service loads. The National Center for Additive Manufacturing Excellence (NCAME) is currently addressing this challenge. As part of the Defense Advanced Research Projects Agency (DARPA) project, the NCAME team ­­­­— together with researchers from the University of Michigan-Dearborn, Texas A&M University, and the University of California, San Diego, along with industry partners including Addiguru, AlphaSTAR, and ASTM International — is investigating variable amplitude loading effects to enable the accurate estimation of life spans for real-world AM components. This work is essential for ensuring that AM parts can handle the more complex, real-world load spectrum of mission-critical environments with improved reliability. By bridging the gap between the lab and the runway, #NCAME is helping to set the standard for the next generation of resilient engineering. Salman Yasin, Patricio Carrion, Sajith Soman, Stefano Beretta, Shuai Shao, Nima Shamsaei Auburn University Auburn University Mechanical Engineering #NCAME #AdditiveManufacturing #FatigueLife #3DPrinting #AdvancedManufacturing

#NCAME is actively investigating the transferability of anomaly characteristics and their effect on fatigue properties from AlSi10Mg standard specimens to application-relevant components, with a focus on additively manufactured wishbone geometries produced using the RenAM 500Q Flex system. While the fatigue properties of AM alloys are commonly characterized using standardized specimens, real components experience different geometries, stressed volumes, and defect populations, making direct transfer of specimen-based fatigue data non-trivial. This study aims to investigate how defect populations in specimens can be used to predict fatigue behavior in components. The final goal is to incorporate these results into a probabilistic fatigue framework to enable prediction-based qualification of additively manufactured aluminum components for safety-critical applications. Behnam Salehnasab, Daniel Perghem, Stefano Beretta, Shuai Shao, Nima Shamsaei Auburn University National Center for Additive Manufacturing Excellence (NCAME) Politecnico di Milano #AdditiveManufacturing #Fatigue #Probabilistic #AlSi10Mg #3DPrinting #AdvancedManufacturing