There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Additive manufacturing of metallic components – Process, structure and properties

Additive manufacturing of metals

Additive manufacturing (AM), widely known as 3D printing, is a method of manufacturing that forms parts from powder, wire or sheets in a process that proceeds layer by layer. Many techniques (using many different names) have been developed to accomplish this via melting or solid-state joining. In this review, these techniques for producing metal parts are explored, with a focus on the science of metal AM: processing defects, heat transfer, solidification, solid-state precipitation, mechanical properties and post-processing metallurgy. The various metal AM techniques are compared, with analysis of the strengths and limitations of each. Only a few alloys have been developed for commercial production, but recent efforts are presented as a path for the ongoing development of new materials for AM processes.

The metallurgy and processing science of metal additive manufacturing

Developing Processing Parameters for Nickel-base Superalloys for the Electron Beam Melting Additive Manufacturing Process

In this paper, we present a deep learning algorithm to rapidly obtain high quality CT reconstructions for AM parts. In particular, we propose to use CAD models of the parts that are to be manufactured, introduce typical defects and simulate XCT measurements. These simulated measurements were processed using FBP (computationally simple but result in noisy images) and the MBIR technique. We then train a 2.5D deep convolutional neural network [4], deemed 2.5D Deep Learning MBIR (2.5D DL-MBIR), on these pairs of noisy and high-quality 3D volumes to learn a fast, non-linear mapping function. The 2.5D DL-MBIR reconstructs a 3D volume in a 2.5D scheme where each slice is reconstructed from multiple inputs slices of the FBP input. Given this trained system, we can take a small set of measurements on an actual part, process it using a combination of FBP followed by 2.5D DL-MBIR. Both steps can be rapidly performed using GPUs, resulting in a real-time algorithm that achieves the high-quality of MBIR as fast as standard techniques. Intuitively, since CAD models are typically available for parts to be manufactured, this provides a strong constraint "prior" which can be leveraged to improve the reconstruction.

/pdf/x-ray-ct-reconstruction-of-additively-manufactured-parts-8juz7zs6xm.pdf

X-Ray CT Reconstruction of Additively Manufactured Parts using 2.5D Deep Learning MBIR

Powder-bed fabrication of aerospace alloys may revolutionize production by eliminating the need for extensive machining and expensive tooling. Heated-bed electron-beam melting (EBM) offers advantages over non-heated laser additive manufacturing (AM) methods, including lower residual stress, reduced risk of contamination, slower cooling rates, and faster build times. NASA Glenn Research Center has joint project work with Oak Ridge National Lab and the Air Force Research Laboratory to explore the feasibility of fabricating advanced Ni-based gamma-prime superalloys with EBM AM.

/pdf/nasa-ornl-afrl-project-work-on-ebm-lshr-additive-45sdbf53tl.pdf

NASA/ORNL/AFRL Project Work on EBM LSHR: Additive Manufacturing of High-Temperature Gamma-Prime Strengthened Ni-Based Superalloys

Minor Elements and Solidiﬁcation Cracking During Laser Powder-Bed Fusion of a High c 0 CoNi-Base Superalloy

2 was for XZERES to design tooling for their existing blade geometry and for ORNL to manufacture the tooling and a blade section using advanced manufacturing techniques. Unfortunately, due to personnel turnover at XZERES, Phase 2 was not completed. 

https://info.ornl.gov/sites/publications/Files/Pub148391.pdf

Michael M. Kirka

Papers

Developing Processing Parameters for Nickel-base Superalloys for the Electron Beam Melting Additive Manufacturing Process

X-Ray CT Reconstruction of Additively Manufactured Parts using 2.5D Deep Learning MBIR

NASA/ORNL/AFRL Project Work on EBM LSHR: Additive Manufacturing of High-Temperature Gamma-Prime Strengthened Ni-Based Superalloys

Minor Elements and Solidiﬁcation Cracking During Laser Powder-Bed Fusion of a High c 0 CoNi-Base Superalloy

Full Scale Engine Demonstration of Additively Manufactured High Gamma Prime Turbine Blade