Manchester Grand Hyatt San Diego
|Member - Early (until 17 December)
|Member - Standard
|| $400 |
|| $450 |
The use of 3D printing, also known as Additive Manufacturing (AM), has moved well beyond prototyping, rapid tooling and toys; it is considered a production tool. As these advanced manufacturing techniques enable complex and revolutionizing structures and material with intricate details that were not
possible before, topology optimization is considered the ideal design method to produce such innovative and unintuitive designs for AM.
This course will provide a practical understanding of topology optimization and additive manufacturing. It will uncover the numerical machineries of a range of topology optimization methods and reveal how to formulate design problems and select numerical parameters to yield successful designs. It will also discuss
the state-of-the-art topology optimization capabilities in the context of material and structural designs under multiphysics. The course will also offer an overview of rapidly developing additive manufacturing technologies, including those commercially available as well as the state-of-the-art methods for the
future. It will discuss the material types and capabilities for each method and the associated considerations for design, both at material and structural scales. The course will also include a practical hands-on element using an open source topology optimization code.
- To gain a practical understanding of topology optimization methods (both SIMP and level set topology optimization) and the numerical parameters.
- To use topology optimization for design of structures and/or architected material.
- To evaluate additive manufacturing methods suitable for a given design problem.
- To design an architected material or structure for a chosen additive manufacturing technique.
- To discuss the state-of-the-art additive manufacturing and design optimization techniques hence steer and shape future development strategies.
Who Should Attend
The target audience includes managers who wish to gain an understanding of topology optimization and additive manufacturing capabilities for the future, practitioners of architected material design, design for additive manufacturing and topology optimization as well as researchers interested in employing topology optimization
and additive manufacturing in their research (e.g. graduate students, postdocs and academics). The fundamental concepts in digitally linking manufacturing to design via optimization and design for uncertainty material properties arising from manufacturing and integrating multiple scale in design of
structural-material systems would also interest systems engineers, ICME (integrated computational material engineering,) and digital engineering practitioners.
H Alicia Kim, Ph.D. is Jacobs Scholars Chair Professor at the University of California San Diego and Director of Multiscale and Multiphysics Design Optimization (M2DO) Lab. Professor Kim has over 20 years of research experience in the fields of topology optimization, multiscale and multiphysics
design optimization, composite and smart materials, which have been published in over 200 publications. Her pioneering research has been recognized by awards from AIAA and ISSMO (International Society of Structural and Multidisciplinary Optimization) and a prestigious fellowship from the UK Engineering and Physical
Sciences Research Council. She received her Ph.D. in topology optimization from the University of Sydney, Australia and began her academic appointment at the University of Bath, UK for 15 years before moving to the current position in the US in 2015.
M. Spadaccini, Ph.D., is currently the Director of the Additive Manufacturing Initiative at the Lawrence Livermore National Laboratory (LLNL) as well as the leader of the Center for Engineered Materials and Manufacturing. He has been working in advanced additive manufacturing process development and architected materials
for the last decade and has over 40 journal publications, three book chapters, and several dozen patents awarded and pending. Dr. Spadaccini founded several new fabrication laboratories at LLNL for process development focused on micro and nanoscale features and mixed material printing. He received his B.S., M.S.,
and Ph.D. degrees from the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology (MIT) in 1997, 1999, and 2004 respectively and has been a member of the LLNL technical staff for over 14 years. He has also been a lecturer in the Chemical, Materials, and Biomedical
Engineering Department at the San Jose State University where he taught graduate courses in heat, mass, and momentum transfer.
- 1. Introduction to topology optimization
- 1.1 Mathematical programming
- 1.2 SIMP method
- 1.3 Level set method
- 2. Overview of additive manufacturing
- 2.1 Classes of additive manufacturing methods available today
- 2.2 State of the art additive manufacturing methods
- 3. Application of additive manufacturing - material and structural scale
- 3.1 Case studies of applications
- 3.2 Pre-processing for additive manufacturing
- 3.3 Design considerations for additive manufacturing
- 4. Application of topology optimization
- 4.1 Structural mechanics design
- 4.2 Design for multiphysics multidisciplinary design
- 4.3 Multiscale optimization for structural-material systems
- 4.4 Challenges and limitations of applying topology optimization
- 5. Hands-on demonstration with an open source topology optimization software
Course notes will be made available about one week prior to the course event. You will receive an email with detailed instructions on how to access your course notes. Since these notes will not be distributed on site, AIAA and your course instructor highly recommend that you bring your
computer with the course notes already downloaded.
An open source topology optimization code is available
- Registration will open in September 2018.
Jason Cole if you have any questions about courses and workshops at AIAA forums.