Additive Manufacturing: Materials Design and Alloy Development II: Alloy Design-Accelerated Development and Modeling
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS: Additive Manufacturing Committee, TMS: Integrated Computational Materials Engineering Committee
Program Organizers: Behrang Poorganji, Morf3d; James Saal, Citrine Informatics; Orlando Rios, University of Tennessee; Hunter Martin, HRL Laboratories LLC; Atieh Moridi, Cornell University
Thursday 8:30 AM
February 27, 2020
Room: 6F
Location: San Diego Convention Ctr
Session Chair: Hunter Martin, HRL Laboratories LLC
8:30 AM Keynote
Alloy Prototyping Techniques for Powder-based Additive Manufacturing: Eric Jaegle1; Dierk Raabe1; 1Max-Planck-Institut Fuer Eisenforschung
When designing new alloys specifically for AM, the availability of powder with tailored composition is an obstacle with regard to both time and cost. This talk presents an overview of several approaches to overcome this obstacle. First, we bypass powder atomization completely, instead judging processability by laser re-melting. This approach is used for an initial screening step and allows the identification of compositions prone to e.g. hot cracking. Next, we produce alloys by mixing pure element powders in-situ. Using several powder feeders in the DED process, we produce graded specimens that allow screening of various alloy compositions in one specimen. We also process powder mixtures in the L-PBF process, and show how the process needs to be controlled in order to achieve chemical homogeneity and where the limitations of the powder mixing approach lie. Finally, we report on our attempts to produce powders in a self-designed EIGA-type lab-scale atomizer.
9:00 AM
A Rapid Screening Benchmark Test Methodology for Accelerated AM Alloy Design: Ralph Napolitano1; Timothy Prost2; Shubhra Jain1; Emma White2; Iver Anderson2; 1Iowa State University; 2Ames Laboratory
A critical issue limiting widespread AM implementation of high-performance alloys is the phenomenon of cracking during localized repetitive melting and freezing. In-build cracking in AM processes may be attributed to solidification hot-cracking, liquation cracking, transformation-induced cracking, or simply to thermal stress induced cracking. The associated poor “buildability” restricts the use of established engineering alloys and presents a challenge in the development of new alloys. Accelerated alloy/process design practices require efficient test methods for reproducible benchmarking of hot cracking susceptibility, correlation with predictive cracking criteria, and efficient comparison of new alloys. Here, we examine the utility of a spot-melting cantilever bend test method for rapid screening and assessment of hot-cracking susceptibility in localized melting AM processes. Test results are compared with established solidification-path-based hot cracking predictors computed for several Al-, Ni-, and Fe-based alloys. (Supported by Iowa State internal grant, with collaborative support from Ames Laboratory DE-AC02-07CH11358.765, U.S. DOE-EERE-Advanced Manufacturing.)
9:20 AM
Accelerated Development of Alloys via Direct Laser Metal Deposition: Husam Alrehaili1; Praveen Sreeramagiri1; Ajay Bhagavatam1; Guru Dinda1; 1Wayne State University
The rapid growth in the additive manufacturing (AM) field raised the need of novel alloys that are tailored for the AM. The current alloy development research focuses on the processability improvement of the current conventional alloys or the design of new alloys for AM. In most cases, the testing of the mechanical properties of the newly developed alloys comes at later stages during the alloy development practice. This paper reports a fabrication strategy of hundreds of miniature tensile test specimens with different composition in few hours by direct laser metal deposition process. In addition, this paper also presents an accelerated path that allows quick testing of the mechanical properties at the early stages of the alloy development. Each of these samples represents a novel alloy. Therefore, based on the results of the mechanical properties, one can decide whether or not a specific alloy can be a good candidate for AM.
9:40 AM
Efficient Material and Processing Parameter Optimization in Laser Powder Bed Fusion Through Novel Amalgamation of Computational Modeling, Non-destructive Evaluation, and Material Characterization: Christopher Peitsch1; Steven Storck1; Ian McCue1; Joseph Sopcisak1; Morgan Trexler1; 1JHU/APL
Current standards and best practices for material qualification in additive manufacturing (AM) often constitute an expensive process that can inhibit rapid development of new materials and structures. Intelligent experimental design, derived from computational modeling, can be used to bound the selection of candidate material alloys and processing parameters. By developing custom sample geometries, traditionally costly characterization techniques, such as x-ray computed tomography, can be tailored to improve efficiency. This technique is also complemented with other fast and inexpensive characterization methods such as Vickers hardness or compression testing. The combination of these data, with modeling and non-destructive analysis can be used to evaluate defects in the resulting structures, and enable rapid deconvolution of the material-process-performance relationships. The results of this technique have been shown to improve the overall development of special alloys for AM, including metal matrix composites and shape memory alloys, reducing the time invested from weeks to days.
10:00 AM
Modeling Hot Cracking in Metal Additive Manufacturing: Eric Clough1; Brennan Yahata1; Mark O'Masta1; Hunter Martin1; Matthew Begley2; 1HRL Laboratories; 2University of California, Santa Barbara
Hot cracking in metals occurs when liquid films, present at grain boundaries in the final stages of solidification, cavitate to accommodate thermal and solidification shrinkage. The initiation and growth of these hot cracks is a complex phenomenon dictated by the interaction between geometric, thermal, mechanical, and alloy solidification factors. Despite significant advancements in the understanding of hot cracking over the past >80 years, the phenomenon has yet to yield to a quantitative and predictive theory.In this seminar we will present a computational multi-physics model of hot cracking that rigorously accounts for phase transformations, microstructural effects, thermal and mass diffusion, fluid flow, solid mechanics, and fluid-solid interactions. We compare our modeling results to classical hot cracking experiments of binary and ternary alloys, and discuss the implications of our findings on alloy design and processing parameter optimization in the context of additive manufacturing.
10:20 AM Break
10:35 AM Invited
Assessing the Printability of Metal Alloys for Additive Manufacturing: Raymundo Arroyave1; Luke Johnson1; Raiyan Seede1; Mohamad Mahmoudi1; Bing Zhang1; Alaa Elwany1; Ibrahim Karaman1; 1Texas A&M University
We propose a methodology for predicting the printability of an alloy, subject to laser powder bed fusion additive manufacturing. Regions in the process space associated with keyhole formation, balling, and lack of fusion are assumed to be strong functions of the geometry of the melt pool, which in turn is calculated for various combinations of laser power and scan speed via a Finite Element thermal model that incorporates a novel vaporization-based transition from surface to volumetric heating upon keyhole formation. Process maps established from the Finite Element simulations agree with experiments for a Ni-5wt.\%Nb alloy and an equiatomic CoCrFeMnNi High Entropy Alloy and suggest a strong effect of chemistry on alloy printability. Uncertainties in the printability maps were quantified via Monte Carlo sampling. The printability maps generated with the proposed method can be used in the selection---and potentially the design---of alloys best suited for Additive Manufacturing.
11:00 AM
Composition Control in Laser Powder Bed Fusion Additive Manufacturing Through Differential Evaporation: Meelad Ranaiefar1; Ibrahim Karaman1; Alaa Elwany1; Raymundo Arroyave1; 1Texas A&M University
Differential evaporation during part fabrication using laser powder bed fusion additive manufacturing can contribute to variation in composition. This uncontrolled evaporation is a prevalent issue throughout the additive manufacturing process and is associated with uncontrolled changes in structure and properties, along with reduced performance of a part. However, we can utilize the underlying mechanisms of differential evaporation to direct processing parameters, control composition, tailor location specific properties, and achieve desired performance. In this work, a model for predicting differential evaporation and the associated change in composition during laser powder bed additive manufacturing is presented. This is used to investigate the effects of alloying elements and processing parameters on evaporation and composition.
11:20 AM
Computational Design of Compositionally Graded Alloys for Monotonic Property Gradients: Tanner Kirk1; Olga Eliseeva1; Richard Malak1; Raymundo Arroyave1; Ibrahim Karaman1; 1Texas A&M University
Additive manufacturing has accelerated the development of Functionally Graded Materials (FGMs) by enabling the layer-by-layer control of composition. Previous work has applied path planning algorithms and CALPHAD phase predictions to design FGMs that avoid deleterious phases. This work is extended to design FGMs with monotonic property gradients by minimizing a Lack of Monotonicity (LOM) cost function. By controlling material deposition rate, compositional paths with monotonic property gradients can be used to create functionally graded parts with properties that vary linearly, monotonically or even nonmonotonically along the dimensions of the part. Case studies are presented that showcase the design of compositionally graded alloys that have monotonic gradients in Coefficient of Thermal Expansion (CTE). These monotonic CTE gradients can be used to create functionally graded parts that minimize CTE mismatch and consequently reduce stresses induced during manufacturing. Other case studies demonstrate the design of FGMs for part-scale objectives like stiffness and density.
11:40 AM
Microsegregation Analysis, Modeling, and Correlation to Cracking Behaviors in AM: Timothy Prost1; Emma White1; Shubhra Jain2; Ralph Napolitano2; Iver Anderson2; 1Ames Laboratory; 2Ames Laboratory/Iowa State University
The extension of additive manufacturing (AM) into new industrial sectors promises enhanced design flexibility and speed but calls for developments in processing and alloy design. While powder-based e-beam processes show great potential, many conventionally cast or wrought alloys exhibit severe cracking during AM processing. The ability to rapidly screen alloy compositions could help accelerate the further adoption of AM to other sectors. The work presented here will encompass a rapid, objective sampling technique that indicates segregation within an arbitrary section of a material and the comparison of this information to calculation and simulation of microsegregation. This comparison is used to correlate what can be seen in real microsegregation patterns with various cracking phenomena, which tend to plague the AM community, and to prescribe alloy development directions for avoiding these issues. This research was performed at Ames Laboratory through contract no. DE-AC02-07CH11358.765 with support from U.S. DOE-EERE-Advanced Manufacturing Office.
12:00 PM
Rapid Process Parameter Discovery for Functionally Graded Heterogeneous Materials Using Machine Learning and High Throughput Experiments: Behzad Rankouhi1; Salman Jahani1; Ankur Agrawal1; Gabriel Meric de Bellefon1; Dan Thoma1; Frank Pfefferkorn1; 1University of Wisconsin-Madison
In this work, we propose a fast and efficient method to discover the suitable process parameters for manufacturing heterogeneous functionally graded materials (FGMs) using selective laser melting (SLM) process. Specifically, a regression model based on a multi-variant Gaussian process is developed to correlate laser power, scan velocity, and hatch spacing with material properties. The training data for the algorithm is collected using a high-throughput experimentation method that allows for rapid measurement of material density, macro-hardness and surface roughness. Laser beam diameter, powder particle size, and layer thickness are kept constant at 80 µm, ≤60 µm, and 20 µm, respectively. Furthermore, a Pareto optimality solution is used to determine the optimal set of process parameters. Finally, a scan strategy is derived to manufacture SS316L-HastelloyX and SS316L-Cu heterogeneous FGMs. Results indicate that heterogeneous FGMs can be manufactured via SLM with relative densities above 95% using the proposed predictive framework.