Dynamic Die Supply’s Post

In this research, a data-driven physics-based methodology is proposed to predict the mechanical properties of fused filament fabrication (FFF) parts using Bayesian inference. https://lnkd.in/g5VPB_Rd

I’m thrilled to share that our latest research paper, "𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴-𝗕𝗮𝘀𝗲𝗱 𝗙𝗮𝘁𝗶𝗴𝘂𝗲 𝗔𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝗼𝗳 𝟯𝟭𝟲𝗟 𝗦𝘁𝗮𝗶𝗻𝗹𝗲𝘀𝘀 𝗦𝘁𝗲𝗲𝗹 𝗙𝗮𝗯𝗿𝗶𝗰𝗮𝘁𝗲𝗱 𝗯𝘆 𝗟𝗮𝘀𝗲𝗿-𝗣𝗼𝘄𝗱𝗲𝗿 𝗕𝗲𝗱 𝗙𝘂𝘀𝗶𝗼𝗻", has been published in the 𝘐𝘯𝘵𝘦𝘳𝘯𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘑𝘰𝘶𝘳𝘯𝘢𝘭 𝘰𝘧 𝘍𝘢𝘵𝘪𝘨𝘶𝘦. In this study, we used machine learning models combined with SHapley Additive exPlanation (SHAP) to predict fatigue life and defect location in additively manufactured 316L stainless steel components. The three main findings of the study are: 𝟭. 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆: The machine learning model based on gradient boosted trees (XGBoost) combined with SHAP effectively predicted fatigue life and defect location. SHAP values provided insights into the interactions between factors, improving model interpretability. 𝟮. 𝗦𝘁𝗿𝗲𝘀𝘀-𝗥𝗲𝗹𝗮𝘁𝗲𝗱 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗮𝘀 𝗞𝗲𝘆 𝗗𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗮𝗻𝘁𝘀: Stress amplitude and mean stress were identified as the most critical factors influencing the fatigue life of 316L stainless steel, with post-treatment conditions (as-built, heat-treated, turned and heat-treated) also playing a significant role. 𝟯. 𝗥𝗲𝘀𝗶𝗱𝘂𝗮𝗹 𝗦𝘁𝗿𝗲𝘀𝘀 𝗥𝗲𝗹𝗮𝘅𝗮𝘁𝗶𝗼𝗻 𝗜𝗺𝗽𝗮𝗰𝘁: Residual stresses had a substantial effect on fatigue life. As mean stress increased and exceeded the material's yield strength, residual stress relaxation occurred, which improved fatigue life under high-stress conditions. Read more about it here (open access): https://lnkd.in/gTfZCQxM A big thank you to my co-author Xiru Wang, whose project thesis was the basis for this study! #MachineLearning #FatigueAssessment #AdditiveManufacturing #Research #316L #LaserPowderBedFusion #XGBoost #SHAP

Another #WEBLEARN webinar on an exciting topic related to Al casting damage management. Register and join us for free!

How can you see the invisible damage in aluminium castings? Join me and my colleagues in a free webinar on our recent research!

Over many years, the liquid metal flow in steel continuous casting tundishes and molds, the cooling and solidification of the melt and the formation of segregation, as well as stresses and cracks have been the subject of numerous projects in which the phenomena were analyzed by various measurement techniques, calculations and/or analytical or numerical simulations. The motivation for these efforts was the desire to understand the details of the phenomena influencing the casting process performance and the strand quality, in order to be able to optimize the casting process conditions. Read the full article here>>

Free, One-hour Webinar: Interfacial Stress and Delamination in Layered Structures Delamination at interfaces is a common failure mode encountered by engineers responsible for designing and manufacturing systems that rely on bonding between dissimilar materials. This free, one-hour webinar will introduce the mechanics of interfacial stress and delamination in layered structures, with the goal of helping engineers better predict and prevent delamination failures. We will survey the sources and basic characteristics of mechanical stress at interfaces as well as introduce the practical experimental, analytical, and computational approaches available for analyzing delamination failures. Link to Register: https://lnkd.in/eSJSNPCc

Check out this complimentary webinar from Veryst Engineering, LLC

𝐈𝐟 𝐲𝐨𝐮 𝐝𝐨𝐧’𝐭 𝐬𝐞𝐞 𝐚𝐧𝐲𝐭𝐡𝐢𝐧𝐠, 𝐭𝐡𝐞𝐫𝐞’𝐬 𝐧𝐨𝐭𝐡𝐢𝐧𝐠 𝐭𝐨 𝐬𝐞𝐞, 𝐫𝐢𝐠𝐡𝐭? In the webinar 𝘔𝘢𝘯𝘢𝘨𝘦 𝘵𝘩𝘦 𝘋𝘢𝘮𝘢𝘨𝘦, 𝘙𝘦𝘷𝘦𝘢𝘭𝘪𝘯𝘨 𝘵𝘩𝘦 𝘦𝘧𝘧𝘦𝘤𝘵 𝘰𝘧 𝘩𝘪𝘥𝘥𝘦𝘯 𝘥𝘢𝘮𝘢𝘨𝘦 𝘪𝘯 𝘢𝘭𝘶𝘮𝘪𝘯𝘪𝘶𝘮 𝘤𝘢𝘴𝘵𝘪𝘯𝘨, we will present recent research that reveals how hidden damage affects the quality and performance of cast aluminium when it is subjected to different types of loads. We will have a look at the traditional meaning of casting quality and quality assurance techniques, before we dig into the topic of hidden damage. Learn more in our webinar with Murat Tiryakioglu, Jacksonville University, and Toni Bogdanoff and Jakob Olofsson from the the School of Engineering at Jönköping University where they discuss recent research touching upon topics like: 🔹 Material quality from both a traditional and a modern perspective 🔹 Visible and hidden damage 🔹 State-of-the-art in research on the mechanical performance of cast aluminium 🔹 Novel experimental and numerical techniques to visualize and quantify hidden damage 👉 Check out more and register at https://lnkd.in/e3xPc-wq 🗓️ Tuesday 4th June, 10:00-11:30 (CET) on Zoom

Bearing Dynamics 🌟 Dear Bearing network, if you haven't done so yet, I encourage you to take a look at the article "The Influence of Cage Pocket Lubrication on the Simulation of Deep Groove Ball Bearing Cage Motion." I believe it represents a significant advancement in the understanding of cage pocket lubrication. I was honored to collaborate with Prof. Farshid Sadeghi, Dr Thomas Russell, Dr Kang and the entire Team at Purdue University. I am extremely grateful for the work they carried out and their dedication to this project. 📈 Highlights: The model, supported by extensive test results, demonstrates how incorporating lubrication effects can significantly reduce the median contact force between the balls and cage, enhancing the stability of cage motion. More lubricant inside of the cage pocket does not guarantee a lower contact force Cage design and lubrication is crucial for the bearing performance, potentially leading to bearings with longer service life and higher efficiency. 💡 Implications for the Industry? The friction and dynamics of the cage pocket should not be neglected in the optimized design of your applications, especially for those aiming at high performance. 👉 Read our full paper here: https://lnkd.in/dJVhJUAN I'd love to hear your thoughts. Feel free to reach out! #EngineeringResearch #BallBearings #Tribology #MechanicalEngineering #Innovation

I share with you the kind of vortex we get when we do a 2D contraction test of a viscoelastic fluid. The size of the vortex depends on the elasticity of the fluid and the inlet speed. We find this type of contraction in a wide range of manufacturing processes using viscoelastic fluids. This numerical simulation was carried out using the MEF++ software from Giref in which we implemented a new algorithm for solving the viscoelastic equations. This new algorithm is submitted for publication.