Additive Manufacturing for Energy Applications V: Properties, Performance Testing and Modeling II
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS Structural Materials Division, TMS: Additive Manufacturing Committee, TMS: Nuclear Materials Committee
Program Organizers: Isabella Van Rooyen, Pacific Northwest National Laboratory; Subhashish Meher, Pacific Northwest National Laboratory; Xiaoyuan Lou, Purdue University; Kumar Sridharan, University of Wisconsin-Madison; Michael Kirka, Oak Ridge National Laboratory; Yi Xie, Purdue University
Tuesday 2:30 PM
March 21, 2023
Room: 23A
Location: SDCC
Session Chair: Michael Kirka, Oak Ridge National Laboratory
2:30 PM Introductory Comments
2:35 PM Invited
Failure Phenomena of Additively Manufactured Ni-base Superalloys at Various Temperatures under Static and Cyclic Loadings: Shuai Shao1; Nima Shamsaei1; 1Auburn University
This work investigated the failure phenomena and mechanical responses of several additively manufactured (AM) Ni-superalloys under both static and cyclic loading conditions over a wide temperature range – from cryogenic to elevated temperatures. The alloys include Hastelloy X, Haynes 282, Inconel 718, and Inconel 625 produced via two processes, namely laser powder bed fusion and laser powder direct energy deposition. Thorough analysis on micro-/defect- structure, mechanical characterization under static and cyclic axial loads, as well as postmortem fractography were performed. This study aimed to provide new understanding of process - structure - property relationships for these AM alloys in two regards; (1) the micro- / defect- structural evolution as the result of thermal cycles has been studied based on scanning electron microscopy and x-ray computed tomography, and (2) both fatigue and tensile properties as well as failure mechanisms were attempted to be correlated with micro-/defect- structure.
3:10 PM
Elevated Temperature Fretting Wear Analysis of Additively Manufactured Inconel 625: Manisha Tripathy1; LLoyd Hackel2; Keivan Davami3; Ali Beheshti1; 1George Mason University; 2Curtiss Wright Surface Technologies; 3The University of Alabama
Inconel 625 is a nickel-based superalloy with excellent mechanical properties and corrosion resistance at high temperatures used in harsh environments as joints, seals, valves, etc; which are subjected to fretting loads. This study evaluates the fretting wear properties of AM Inconel 625 with its wrought (WR) counterpart at high temperatures up to 700οC. The samples were manufactured by metal powder bed fusion technology using different process parameters. AM samples showed better friction and wear properties at high temperatures than WR samples whereas WR samples fared slightly better at room temperature. In addition, samples are treated using shot peening (SP), and laser peening (LP). SP and LP samples show improved tribological properties at room temperature whereas, at higher temperatures, no improvement was observed. Surface oxide composition and microstructure characterization was done to understand changes in deformation mechanisms affecting friction and wear for AM and WR samples with SP and LP processes.
3:30 PM
The Effects of Process Parameters and Scan Strategy on the Corrosion Properties of Laser Powder Bed Fusion Additively Manufactured Haynes 282: Junwon Seo1; Nicholas Lamprinakos1; Youyang Zhao2; Anthony Rollett1; 1Carnegie Mellon University; 2National Renewable Energy Laboratory
Laser powder bed fusion additive manufacturing of nickel-based superalloys allows the fabrication of sophisticated geometries, which has opened up the design space for manufacturing products such as heat exchangers or nuclear reactors that require mechanical and chemical reliability at a wide range of temperatures. However, this novel fabrication method inevitably leaves the printed parts with defects such as porosity and rough surfaces, which may deteriorate such reliability. In order to address this problem, the room-temperature corrosion properties of additively manufactured Haynes 282 were characterized as a function of process parameters and scan strategy. Cubic samples were printed by intentionally varying these printing conditions to control the surface roughness and the porosity distribution. We show that these defects in the printed samples, which are quantified by three-dimensional laser scanning and serial sectioning, affect the corrosion rate. Finally, the process is optimized for more sophisticated geometries to increase their corrosion resistance.
3:50 PM Break
4:05 PM Invited
Role of Predictive Modeling and Uncertainty Quantification in Qualification of Additively Manufactured Alloys: David Andersson1; Mariyappan Kumar1; Laurent Capolungo1; 1Los Alamos National Laboratory
Additively manufactured (AM) alloys have unique micro-structure features compared to conventionally manufactured materials of the same composition. Interestingly, the micro-structure varies spatially in an AM component. Grain size and shape as well as porosity represent some of the key features that are known to be sensitive to the AM process parameters. The impact on mechanical properties of the micro-structure and its spatial distribution in a component manufactured by, e.g., laser powder bed fusion governs its performance in applications. Understanding and being able to model this relation for properties such as creep and creep-fatigue, including uncertainty quantification, is consequently important for both materials design and qualification. In this talk, the role of predictive modeling, uncertainty quantitation and scale-bridging in designing and qualifying materials and components for nuclear applications will be discussed, both in a general context and with specific applications to conventional and AM materials.
4:40 PM
Quantification of Uncertainties in Metal Additive Manufacturing Processes in Support of Qualification: Daniel Moser1; Helen Cleaves1; Michael Heiden1; Scott Jensen1; Kyle Johnson1; Mario Martinez1; Theron Rodgers1; David Saiz1; Michael Stender1; 1Sandia National Laboratories
Qualification of metal additive processes is difficult partly because variabilities in process outcomes are observed even when process inputs are tightly controlled. These repeatability challenges can make qualification ill-defined, particularly for failure-critical applications. This work attempts to address this using computational modeling and uncertainty quantification (UQ) techniques to predict the effect of machine variabilities on part properties for laser powder bed fusion (LPBF). An uncertainty inventory of an LBPF machine is compiled. Probability distributions for the uncertainties are measured or estimated and UQ techniques used to propagate these distributions through physical models to predict distributions for output quantities of interest including melt pool shapes, as-built part geometries, residual stresses, and microstructural features. Large volumes of test artifacts are then produced to experimentally quantify variability and compare to computationally predicted distributions.This work was supported by the LDRD program at SNL, managed and operated by NTESS under DOE NNSA contract DE-NA0003525
5:00 PM
Surface Roughness of Heat Exchanger Flow Channels Manufactured with Directed Energy Deposition: Luis Nuņez1; Minseop Song1; Sunming Qin1; Piyush Sabharwall1; Isabella van Rooyen2; 1Idaho National Laboratory; 2Pacific Northwest National Laboratory
Additive manufacturing (AM) presents techniques which can benefit the design of compact heat exchangers (HXs) by further enhancing thermal performance and reducing economic costs. Powder-based AM methods such as directed energy deposition (DED) suffer from high as-built surface roughness. Rough surfaces in flow channels can benefit thermal performance but conventionally increase the frictional and pressure losses. Rough surfaces also can exhibit hydrophobic properties due to solid-liquid fraction of wetting contact and can decrease the frictional losses and fouling. This study focuses on the feasibility of fabricating 316L stainless steel HX flow channels with DED and measurements of arithmetic mean average surface roughness with laser-optical microscopy. A HX numerical and analytical model is developed and compared with experimental data. Hydrophobic potential for Cassie-Baxter and Wenzel models are also analyzed and presented.