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Additive Manufacturing and Welding
United States
Приєднався 22 вер 2021
Additive manufacturing and welding research. We use the emerging tools of mechanistic modeling and machine learning to improve additive manufacturing and welding without expensive and time-consuming trial-and-error testing.
Composition change during additive manufacturing
00:00 Introduction
01:33 Selective vaporization
02:29 Alloy dependence
04:21 Nickel alloys
06:00 Remelting
06:57 Process variables
During additive manufacturing, the chemical composition of a metallic part may be different from that of the feedstock from which the part is made. This is because different alloying elements vaporize at different rates. The selective vaporization of the volatile alloying elements results in changes in the composition of the alloy.
#additivemanufacturing #modeling #3dprinting #composition #powderbedfusion
01:33 Selective vaporization
02:29 Alloy dependence
04:21 Nickel alloys
06:00 Remelting
06:57 Process variables
During additive manufacturing, the chemical composition of a metallic part may be different from that of the feedstock from which the part is made. This is because different alloying elements vaporize at different rates. The selective vaporization of the volatile alloying elements results in changes in the composition of the alloy.
#additivemanufacturing #modeling #3dprinting #composition #powderbedfusion
Переглядів: 430
Відео
Theory and Practice of Additive Manufacturing - Tuhin Mukherjee and Tarasankar DebRoy (Wiley, 2023)
Переглядів 5888 місяців тому
00:00 Introduction 01:00 Special features 05:11 Content highlights 05:56 How to get a copy/QR codes In recent decades, additive manufacturing, also known as 3D printing, has garnered widespread acceptance across industries due to its capacity to economically produce vital components. Our newly published book promotes quantitative scientific understandings of additive manufacturing of metallic m...
Keyhole mode wobble laser welding of a nickel base alloy - modeling, experiments, and process maps
Переглядів 72411 місяців тому
00:00 Introduction 02:31 Keyhole geometry 02:59 Temperature and velocity fields 05:02 Experimental validation 05:40 Process maps 06:09 Main contributions Keyhole mode wobble laser welding of a nickel base superalloy-Modeling, experiments, and process maps, Tuhin Mukherjee, Mingze Gao, Todd A Palmer, Tarasankar DebRoy, Journal of Manufacturing Processes, 24 November 2023, Volume 106, Pages 465-4...
Reliable reverse modeling of additive manufacturing by Tarasankar DebRoy - a keynote at RAAM2023
Переглядів 66211 місяців тому
00:00 Introduction 02:49 Type of modeling 10:29 Reverse modeling 13:26 Improving reliability 17:59 Tailoring fusion zone geometry - a case study 23:01 Main contributions Heat transfer and fluid flow models can provide valuable insights into additive manufacturing processes and materials such as the fusion zone geometry, temperature fields, and cooling rates, that cannot be easily obtained other...
How to control microstructures in additive manufacturing?
Переглядів 1,7 тис.Рік тому
Reusable insights on the control of microstructure in additive manufacturing, not available in individual papers, have just been published in Progress in Materials Science (107 printed pages of unbiassed, alloy-specific solutions). The paper is entitled “Control of grain structure, phases, and defects in additive manufacturing of high-performance metallic components” published in Progress in Ma...
Modeling of common defects in additive manufacturing by Tarasankar DebRoy
Переглядів 1,6 тис.Рік тому
00:00 Introduction 02:15 Common defects 04:47 Selection of models 05:45 Lack of fusion defects 15:28 Solidification cracking 18:16 Residual stress 20:58 Main contributions Properties and serviceability of metallic parts made by additive manufacturing are affected by various defects such as cracking, porosity, and other voids, surface roughness, and waviness, loss of alloying elements, residual ...
Integrated modeling of cracking during deep penetration laser welding of nickel alloys
Переглядів 753Рік тому
00:00 Introduction 02:04 Theory 04:09 Cracking susceptibility 05:50 Mechanisms 07:05 Modeling 10:56 Results 14:21 Summary and conclusions During deep penetration laser welding of nickel alloys, interactions between composition and processing conditions can lead to the formation of defects. Inconel 740H, for example, has demonstrated a susceptibility to horizontal fusion zone cracking at locatio...
Thermal Cutting, Welding and Joining - Animated Overview of the Processes
Переглядів 1,1 тис.Рік тому
00:00 Introduction 00:21 Cutting processes 01:54 Welding processes 12:12 Brazing and soldering The following video is a series of educational animations that illustrate the common welding, joining, and thermal cutting processes including SMAW (MMAW) (stick welding), GTAW (tig welding), GMAW (MIG welding), FCAW (flux cored arc welding), MCAW (metal cored arc welding), SAW (submerged arc welding)...
Vapor pressure versus temperature relations of common elements
Переглядів 274Рік тому
00:00 Introduction 01:16 Why vapor pressure data? 02:02 Problems with current data 03:02 Use of the genetic algorithm 05:16 Recommended data The vapor pressure values of common elements are available in the literature over a limited temperature range and the accuracy and reliability of the reported data are not generally available. We evaluate the reliability and uncertainty of the available va...
Hands-on machine learning in additive manufacturing that everyone can use
Переглядів 2 тис.Рік тому
00:00:00 Introduction 00:01:22 Metal additive manufacturing and its uniqueness and opportunities 00:08:08 Why we need machine learning? 00:10:03 Different types of machine learning in additive manufacturing 00:12:25 Control of grain size using machine learning 00:14:12 Control of residual stresses using machine learning 00:20:39 Control of lack of fusion defects using machine learning 00:27:08 ...
Control of structure, properties, and defects in additive manufacturing
Переглядів 2,2 тис.Рік тому
00:00:00 Introduction 00:01:43 Metal additive manufacturing and its uniqueness and opportunities 00:06:01 Control of structure, properties, and defects 00:08:17 Why we need digital tools? 00:12:41 What is a mechanistic model? 00:23:24 Control of grain structure 00:29:18 Control of properties 00:36:51 Control of lack of fusion voids 00:44:09 Control of residual stresses and distortion 01:01:20 C...
How everyone can model additive manufacturing to print superior parts - A Keynote at RAAM2022
Переглядів 1,4 тис.Рік тому
00:00 Introduction 01:42 Three reasons why 3D printing cannot do without modeling 06:36 Four examples of models that beginner researchers can develop 14:23 Examples of models developed by experienced programmers 17:29 Examples of models developed by experienced researchers 21:30 Main contributions and outlook This talk was presented at the 2nd International Conference on Research Advances in Ad...
Digital Twins in Additive Manufacturing - Concepts, Building Blocks, and Applications @Univ Michigan
Переглядів 2,6 тис.2 роки тому
00:00 Introduction 06:46 Benefits of a digital twin 09:46 Attributes of mechanistic models, machine learning, and digital twins 16:36 Scientific, technological & economic problems solved by digital twins 20:31 Components of a digital twin in additive manufacturing 45:39 Current uses of digital twins of additive manufacturing in the industry 47:06 Outlook This talk was presented in the Departmen...
Laser additive manufacturing of grade 91 steel for affordable nuclear reactor components
Переглядів 4312 роки тому
00:00 Introduction 01:21 Outline 01:56 Background 03:32 Project plan 05:28 Recent results/tempering 07:44 Model development 10:11 Samples/microstructure 12:08 Summary and future work Grade 91 ferritic/martensitic steel is a promising structural or cladding material for various nuclear reactor applications. The main objective of this project is to develop a method and process model that provides...
Spatial variation of hardness during additive manufacturing of a ferritic steel
Переглядів 7372 роки тому
00:00 Introduction 01:59 Why martensite forms? 02:35 Tempering kinetics 05:45 Spatial variation of hardness 07:34 Main contribution Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for this steel, and ...
Lack of fusion voids, balling, surface roughness, and residual stress in additive manufacturing
Переглядів 1,7 тис.2 роки тому
Lack of fusion voids, balling, surface roughness, and residual stress in additive manufacturing
Real-time monitoring of metal transfer and melt pool for gas-metal arc directed energy deposition
Переглядів 9082 роки тому
Real-time monitoring of metal transfer and melt pool for gas-metal arc directed energy deposition
Reducing lack of fusion voids in 3D printing using machine learning
Переглядів 7182 роки тому
Reducing lack of fusion voids in 3D printing using machine learning
Heat transfer and fluid flow in additive manufacturing
Переглядів 1,8 тис.2 роки тому
Heat transfer and fluid flow in additive manufacturing
Reducing surface roughness in additively manufactured parts
Переглядів 1,6 тис.2 роки тому
Reducing surface roughness in additively manufactured parts
A Machine Learning trick that everyone should be using
Переглядів 1,6 тис.2 роки тому
A Machine Learning trick that everyone should be using
Control of microstructure in additive manufacturing by Dr. Alex Plotkowski
Переглядів 5 тис.2 роки тому
Control of microstructure in additive manufacturing by Dr. Alex Plotkowski
Machine Learning in Additive Manufacturing
Переглядів 4,4 тис.2 роки тому
Machine Learning in Additive Manufacturing
Minor alloying element variations and microstructural evolution in additively manufactured materials
Переглядів 1,2 тис.2 роки тому
Minor alloying element variations and microstructural evolution in additively manufactured materials
Cost competitiveness and quality consistency in metal printing
Переглядів 5592 роки тому
Cost competitiveness and quality consistency in metal printing
Rapid calculation of residual stresses in part scale additive manufacturing
Переглядів 3,4 тис.2 роки тому
Rapid calculation of residual stresses in part scale additive manufacturing
Iowa State talk on improved quality consistency through smart metal printing
Переглядів 4652 роки тому
Iowa State talk on improved quality consistency through smart metal printing
Solidification cracking of a nickel alloy during high-power keyhole mode laser welding
Переглядів 6792 роки тому
Solidification cracking of a nickel alloy during high-power keyhole mode laser welding
Smart Metal Printing - a plenary talk at the 4th International Conference on Advances in Mech Eng
Переглядів 5632 роки тому
Smart Metal Printing - a plenary talk at the 4th International Conference on Advances in Mech Eng
Lessons from a great teacher - stories of trouble in tranquility and a vanishing platinum crucible
Переглядів 2732 роки тому
Lessons from a great teacher - stories of trouble in tranquility and a vanishing platinum crucible
Very informative presentation on a novel topic, thank you for your lucid explanation
Please can you tell me what is the software used.
A wonderful video on the modelling of additive manufacturing! 👍👍Many thanks, Proferssor.
Could you please provide the full reference for Wei et al. PMS. 2018? I cannot find it. Thank you very much.
clap clap***
☀☀☀☀☀☀☀☀
Sir, I truly appreciate the detailed explanations of these concepts. I have read several of your papers and find your work inspiring. I hope to meet you in person one day and receive your blessings. Thank you!
Plz provide the dataset
Excellent book!!! This is a must-have for all people who work in additive manufacturing and advanced manufacturing!👍
Many, many thanks, Dr. Du!
Does this model/solution can be done in any FEA software like Ansys or other ? Please let me know .
I just read this paper a few days ago. Great work 👍
Thank you very much. Tarasankar DebRoy
i would like to download this video into my hippocampus
Thanks professor for sharing it. Very informative for additive manufacturing community.
Very helpful presentation - Thank you
Very interesting and insightful presentation. Thank you for sharing!
Very insightful presentation. Looking forward to more of these
Can you suggest me a site where I can get dataset for this?
very interesting subject Prof DebRoy, thanks
Which visualization tool did you use to show the temperature data at 13:50?
We used Tecplot for this and similar plots. Thank you for your interest. Tarasankar DebRoy
These animations are really awesome! It helps a lot to understand these processes.
Great idea! Industry 4.0!
Very informative talk and wonderful work !
Very great discussion
Great job dear
Great talk, really liked the worked examples. Thanks!
Great talk
Thank you for the insightful talk, Dr. Mukherjee.
Attractive area with an exciting presentation. It would be great for me to join your group and do research on this area.
excellent
Is it possible to predict the tensile strength from numerical analysis and not from experimental?
It's a really fantastic and meaningful job. Many thanks for this vedio, Prof.
Thank you very much
Very interesting presentation, Thank you !
Can u please share any paper of this topic ... Please.
Thank you for sharing
✔ 🅿🆁🅾🅼🅾🆂🅼
I would say that this was a very very crucial and interesting topic for the AM enthusiasts like me. Thank you for sharing.
Subho Bijoya!🙏
Very informative and helpful.
Tara Dada, Tara Dada, korchho tumi ki? Ei dekho na ami kemon hashte shikhe chhi! Tara Dada, Tara Dada, tumi research korte jano? O shob kotha chhere dao na, stew thakle ano!:-)
Thanks!
Thank you for this video
So , by reducing powder size surface roughness can be reduced?
Thank you for your question. Yes, a smaller powder size reduces roughness. Please see our 2018 review in PMS.
@@additivemanufacturing_welding sure.
Easy way to learn. I want to be informed about how to make dri from low grade iron ore without pellitizing or sintering. Is that possible?thanks
This is amazing! Love the channel. Is the semi-analytical heat transfer model that you are employing available by any chance? I am using FEA but it can indeed be slow for real geometries. Regards :)
Dear Professor DebRoy, Thank you and your outstanding research group for sharing this valuable video which clearly indicates the importance of physics-informed machine learning. As a researcher, I am very interested in utilizing this trick to fabricate defect-free parts by reducing the needed variables. Sincerely yours, Reza Motallebi
Many thanks!
The video can be summarized with "good feature engineering"
Thank you.
Nice!
Tara Da, khubh bhalo laghlo. Bhalo aachho to?
I am so happy to hear that you liked it. This video is mainly made by Barnali and Tuhin. We are doing well. I also saw the short video that you created using your iPhone while riding a motorcycle. When you have time and energy, please do write to me. All the best, Tarasankar DebRoy
Dear Professor, Thank you for this short but clear video about the importance of reducing the variables for machine learning. It will surely add value to my research work.
The procedure works because the behavior of many complex engineering systems is often accurately described by a group of variables rather than individual variables. An example is the well-studied problem of the flow of fluid in a pipe. In principle, four variables, i.e., the pipe diameter, average fluid velocity, and the density and viscosity of the fluid can predict if the flow is laminar or turbulent. However, it is well accepted that the nature of the flow, laminar or turbulent, can be predicted by only one variable, the Reynolds number. The reduction in the number of variables can make many problems tractable. All the best in your research. T. DebRoy
fantastic video!, eye-opening indeed, many thanks Prof.