Engineering topics

Plotkowski, Alex

Publications and source records attributed to Plotkowski, Alex.

71 records · Page 4

DOE OSTI2021

Microstructure and properties of additively manufactured Al–Ce–Mg alloys

Additive manufacturing of aluminum alloys is largely dominated by a near-eutectic Al-Si compositions, which are highly weldable, but have mechanical properties that are not competitive with conventional wrought Al alloys. In addition, there is a need for new Al alloys with improved high temperature properties and thermal stability for applications in the automotive and aerospace fields. In this work, we considered laser powder bed fusion additive manufacturing of two alloys in the Al–Ce–Mg system, designed as near-eutectic (Al–11Ce–7Mg) and hyper-eutectic (Al–15Ce–9Mg) compositions with respect to the binary L → Al + Al 11 Ce eutectic reaction. The addition of magnesium is used to promote solid solution strengthening. A custom laser scan pattern was used to reduce the formation of keyhole porosity, which was caused by excessive vaporization due to the high vapor pressure of magnesium. The microstructure and tensile mechanical properties of the alloys were characterized in the as-fabricated condition and following hot isostatic pressing. The two alloys exhibit significant variations in solidification structure morphology. These variations in non-equilibrium solidification structure were rationalized using a combination of thermodynamic and thermal modeling. Both alloys showed higher yield strength than AM Al-10Si-Mg for temperatures up to 350 °C and better strength retention at elevated temperatures than additively manufactured Scalmaloy.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Solidification dynamics in metal additive manufacturing: analysis of model assumptions

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. In this study, we investigate various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Microstructure and properties of a high temperature Al–Ce–Mn alloy produced by additive manufacturing

An Al–10Ce-8Mn (wt%) alloy was designed and fabricated by laser powder bed fusion additive manufacturing (AM). The rapid cooling rates of the AM process produced a refined microstructure with a large fraction of reinforcing intermetallic phases. The tensile properties of the alloy were characterized in the as-fabricated state and following thermal exposure. The properties of the as-fabricated microstructure showed exceptional high-temperature performance and strength retention at elevated temperatures up to 400 °C relative to benchmark wrought Al and AM Al alloy properties. Characterization of the microstructure and thermodynamic modeling of the ternary Al–Ce–Mn system rationalized the solidification and solid-state phase transformations. Finally, analysis of the relevant strengthening mechanisms for both the as-fabricated and thermally exposed conditions was performed.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Primary solidification of ternary compounds in Al-rich Al–Ce–Mn alloys

Primary solidification of ternary compounds Al 20 Mn 2 Ce and Al 10 Mn 2 Ce were analyzed through the coupling of the thermodynamic modeling and classic nucleation theory. Thermodynamic models of Al 20 Mn 2 Ce and Al 10 Mn 2 Ce were developed using the CALPHAD approach based on first-principles calculated enthalpy of formation and experimental data obtained from this work and the literature. The analysis suggested that despite the larger thermodynamic driving force for nucleation of Al 10 Mn 2 Ce, nucleation is preferred for the Al 20 Mn 2 Ce phase in the highly undercooled liquid due to its smaller interfacial energy. Therefore, manufacturing methods with rapid cooling rates will favor primary solidification of Al 20 Mn 2 Ce for Al-rich Al–Ce–Mn alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Spatiotemporal parallelization of an analytical heat conduction model for additive manufacturing via a hybrid OpenMP + MPI approach

The ability to do thermal simulations for entire additive manufacturing builds is a key computational problem facing the additive manufacturing community; however, complex numerical models considering multiple physical phenomena currently do not have the capacity for simulations at this scale. To this end, conduction only analytic models offer a viable approach due to the massive drop in computational expense. In this work, we extend an existing implementation which uses a governing equation which can be evaluated at any point in space and time. This implementation already utilizes OpenMP with a spatial decompositions scheme stemming from a melt pool tracking algorithm. Furthermore, we then combine this with a parallel in time (PinT) approach to make the problem highly parallelizable. The new scheme, which uses MPI for internode communication and OpenMP for intranode communication, is shown to scale very well across multiple computational nodes. This approach results in the ability to simulate the 3D solidification conditions for entire layers of additively manufactured parts in minutes making part scale thermal simulations more practical.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Sparse thermal data for cellular automata modeling of grain structure in additive manufacturing

Grain growth in the wake of the melt pool formed during alloy-based additive manufacturing (AM) is complex and multifaceted, depending on parameters governing heat transport, fluid flow, and solidification itself. Cellular automata (CA) models have proven effective in providing computationally efficient and physically sound predictions of grain structure for several AM problems, but their efficiency is tied to the performance of heat transport models. CA models use only a small portion of the problem's temperature data (near the moving melt pool boundary), and much of the CA calculations do not affect the final result due to re-melting of material. Coupling of and communication between heat transport and solidification models, and eliminating operations irrelevant towards final grain structure prediction, will be necessary for using these methods for efficient simulation of large parts. In this work, we introduce a procedure of decoupling the CA from temperature field simulation, using files of relevant temperature data written by the heat transport model. This approach is validated against the standard coupling approach using data obtained through the computational fluid dynamics software OpenFOAM. Negligible differences are seen in grain size, volume, and texture distributions for multilayer simulation of test problems, while the quantity of temperature data for these test problems was reduced by four orders of magnitude (from 100s of GB to 10s of MB) and the code performance sped up by a factor of around 50. Furthermore, variability in microstructure as a function of cell size, substrate, time step, and nucleation parameters is studied, and it is found that cell sizes less than or equal to 1.67 μm and sufficiently small time steps yield Αstatistically equivalent microstructures. Finally, a potential use case for this CA approach—the layer-wise convergence in grain structure starting from extremes in initial grain size—is examined. This approach's ability to simulate expected trends in nucleation and epitaxial grain growth for large regions of microstructure, simulated independently of heat transport models themselves, should prove useful for investigation of various microstructure uncertainties and prediction of part-scale experimental results.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Geometry-independent microstructure optimization for electron beam powder bed fusion additive manufacturing

The ability to manipulate the formation of microstructure is one of the potential advantages of additive manufacturing. Yet, the additive manufacturing process is riddled with complex interactions between processing parameters, geometry, and spot melting sequence which makes the task of controlling microstructure challenging. This paper proposes a method to solve the microstructure texture optimization problem by leveraging established optimization techniques and increasingly fast and accurate analytical heat transfer models. Respectively, we apply two different optimization algorithms, genetic algorithm and concurrent greedy line search, in order to induce arbitrarily shaped microstructure regions and we use a heat transfer model to evaluate the fitness of solutions in an iterative approach that is far more efficient than pure trial and error. The objective of the optimization algorithm is to control local thermal conditions – hence microstructure formation – during the melting process by manipulating the order and the dwell time of all the points of the infill pattern sequence. We then analyze the optimized sequence to determine important path characteristics that affect the microstructure formation. Through examples, we show that relative order and frequency, as measured by weighted average and variance of spot order, are important factors that influence the final characteristics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

An additively manufactured AlCuMnZr alloy microstructure and tensile mechanical properties

In this study, selective laser melting (SLM) was used to fabricate an AlCuMnZr alloy. The microstructural features that resulted from additive manufacturing (AM) were significantly refined compared to the corresponding cast alloy features. A combination of fine equiaxed and columnar grains along with in-situ formation of θ' precipitates during AM leads to enhanced yield strength (up to 300°C) in the as-fabricated AM alloy. The refinement of brittle intermetallics and a bimodal grain size distribution leads to improved tensile elongation in the AM alloy. The results illustrate the microstructural advantages that can result from additive processing over conventionally processed microstructures.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Feedstock Modification for Enhanced Additive Alloys

This project investigated the use of Y 2 O 3 nanoparticles to enhance IN625 feedstock for metal additive manufacturing. The oxide nanoparticles are adhered to the outer surface of the pre-alloyed IN625 powder feedstock, and serve to form an oxide dispersion strengthened (ODS) material in situ during processing. The conventional and enhanced feedstocks were processed using a laser powder bed fusion additive manufacturing (AM) system. The properties of the AM materials were characterized at elevated temperatures and compared to conventional wrought material. The addition of the Y 2 O 3 nanoparticles improved the yield strength, stress rupture, and corrosion properties of the AM material, and compared more favorably with conventional wrought IN625. This research will enable future adoption of additively manufactured ODS-IN625 components with superior properties to current printed IN625 material.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Predicting Geometric Influences in Metal Additive Manufacturing

Metal additive manufacturing (AM) has evolved from scientific curiosity to a potential paradigm shift in materials manufacturing owing to its ability to control microstructure and fabricate complex geometries. However, geometry, often ignored as a variable, can have a significant impact on microstructure evolution, thereby indirectly limiting the design flexibility offered by AM. Currently, the process of retaining microstructure with changing geometry relies on trial and error-based processing followed by microstructural evaluation that places significant demands on time and costs associated with experimentation and characterization. We demonstrate herein that lightweight thermal models can be effectively used to predict microstructural changes with geometry. These models can in turn be used as precursors to developing geometry independent scan strategies and achieve microstructure control in various alloy systems. Even if the thermal signatures predicted by the model are not accurate, scan strategies can be developed to mimic the thermal conditions during initial process development. We present a case study on one of the most studied AM alloys: Ti-6Al-4V.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Geometry-Dependent Solidification Regimes in Metal Additive Manufacturing

Recent modeling and experimental work in additive manufacturing has suggested that cross-sectional geometry may play a significant role in the local development of the solidification structure through its influence on the heat source path. This effect has been rationalized as the transition from a quasi-static point heat source regime, to a regime dominated by the quasi-static motion of an equivalent line source. This work provides a simple analytical framework for determining the conditions under which a system transitions between these regimes. Here, a transient semi-analytical heat transfer model is used to examine a wide range of process conditions and material properties. A simple analytical expression is derived and shown to accurately predict the transition between solidification regimes over these conditions. The functional form of this expression is then used to help understand the importance of various material properties, process parameters, and geometric factors on the characteristics of the solidification conditions. This approach may be used as a simple guideline for optimizing process conditions in response to variations in cross-sectional geometry to produce more consistent microstructural distributions in additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Revisiting solidification microstructure selection maps in the frame of additive manufacturing

Understanding microstructural development in additive manufacturing under highly non-equilibrium cooling conditions and the consequent effects on mechanical properties of the final component is critical for accelerating industrial adoption of these manufacturing techniques. In this study, simple but effective theoretical solidification models are recalled to evaluate their ability to predict of microstructural features in additive manufacturing applications. As a case study, the resulting solidification microstructure selection maps are created to predict the stable growth modality and the columnar to equiaxed transition (CET) of an Al-10Si-0.5Mg alloy processed via Selective Laser Melting. The potential of this method in microstructural predictions for additively manufactured products, as well as outstanding challenges and limitations, are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Multi-solution nature of topology optimization and its application in design for additive manufacturing

The purpose of this paper is to introduce the multi-solution nature of topology optimization (TO) as a design tool for additive manufacturing (AM). The sensitivity of topologically optimized parts and manufacturing constraints to the initial starting point of the optimization process leading to structures with equivalent performance is explored. A modified bi-directional evolutionary structural optimization (BESO) code was used as the numerical approach to optimize a cantilever beam problem and reduce the mass by 50 per cent. Several optimized structures with relatively equivalent mechanical performance were generated by changing the initial starting point of the TO algorithm. These optimized structures were manufactured using fused deposition modeling (FDM). The equivalence of strain distribution in FDM parts was tested with the digital image correlation (DIC) technique and compared with that from the modified BESO code.The results confirm that TO could lead to a wide variety of non-unique solutions based on loading and manufacturability constraints. The modified BESO code was able to reduce the support structure needed to build the simple two-dimensional cantilever beam by 15 per cent while keeping the mechanical performance at the same level. Finally, the originality of this paper lies in introduction and application of the multi-solution nature of TO for AM as a design tool for optimizing structures with minimized features in the overhang condition and the need for support structures.

36 MATERIALS SCIENCE↗

DOE OSTI2019

A Forward Time Stepping Heat Conduction Model for Spot Melt Additive Manufacturing

Solidification dynamics are crucial for determining microstructure development in additively manufactured parts. Multiphysics models based on finite element or finite volume methods may help gain insight for complicated phenomena such as fluid flow, keyholing, and porosity but are too computationally expensive to use for simulating actual builds. Recent analytic and semi-analytic solutions for moving heat sources in a semi-infinite three-dimensional space provide a way to accurately estimate the solidification conditions for entire builds. The downside to these methods is that, unlike finite element or finite volume methods, they cannot use the temperature distribution of the previous timesteps to march the solution forward in time. This paper provides the mathematical formulation and implementation of a forward time stepping (FTS) approach to an existing semi-analytic solution. The speed and accuracy of the two methods are then compared for various scan patterns. The result is that, for spot melts, the forward time-stepping model provides improvements in both speed and accuracy. This is especially true for longer simulations, where the simulation can be orders of magnitude faster. Finally, the longest simulation analyzed in this paper was roughly 30× faster when using the forward time-stepping model versus the straightforward implementation of the semi-analytic solution.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Influence of scan pattern and geometry on the microstructure and soft-magnetic performance of additively manufactured Fe-Si

The influence of geometry and scan pattern on the microstructure evolution and magnetic performance of additively manufactured Fe-3Si components was investigated. To reduce eddy current losses, novel geometries were designed and built and the microstructure and properties of these samples were characterized. The laser scan pattern was shown to strongly influence both the as-built grain structure and strength of the crystallographic texture, resulting in measurable changes in the as-built magnetic performance. In thin wall samples, heat treatment resulted in an increase in the maximum relative magnetic permeability and decrease in power losses in most samples, consistent with grain growth. However, decreases in the spacing between thin walls to increase the stacking factor of the cross-section was shown to result in unwanted electrical shorting between walls and an increase in eddy current losses. Compared to simple parallel plate construction and a mesh structure, a novel cross-section design based on the Hilbert space filling curve was found to produce the lowest power losses. The mechanisms behind these results were explored using a combination of heat conduction and electromagnetic simulations, providing a route for future component and process optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Experiments and simulations on solidification microstructure for Inconel 718 in powder bed fusion electron beam additive manufacturing

Previous research on the powder bed fusion electron beam additive manufacturing of Inconel 718 has established a definite correlation between the processing conditions and the solidification microstructure of components. However, the direct role of physical phenomena such as fluid flow and vaporization on determining the solidification morphology have not been investigated quantitatively. In this work, we investigate the transient and spatial evolution of the fusion zone geometry, temperature gradients, and solidification growth rates during pulsed electron beam melting of the powder bed with a focus on the role of key physical phenomena. The effect of spot density during pulsing, which relates to the amount of heating of the build area during processing, on the columnar-to-equiaxed transition of the solidification structure was studied both experimentally and theoretically. Predictions and the evaluation of the role of heat transfer and fluid flow were established using existing solidification theories combined with transient, three-dimensional numerical heat transfer and fluid flow modeling. Metallurgical characteristics of the alloy’s solidification are extracted from the transient temperature fields, and microstructure is predicted and validated using optical images and electron backscattered diffraction data from the experimental results. Simulations show that the pure liquid region solidified quickly, creating a large two-phase, mushy region that exists during the majority of solidification. While conductive heat transfer dominates in the mushy region, both the pool geometry and the solidification parameters are affected by convective heat transfer. Lastly, increased spot density during processing is shown to increase the time of solidification, lowering temperature gradients and increasing the probability of equiaxed grain formation.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Fabrication and Modeling of Laser Additive Manufactured Materials with Multi-Beam Adaptive Beam Shaping

The objective of this research was to fabricate laser additive manufactured samples using the multi-beam fiber laser array system developed by Optonicus, and to test the ability of existing simulation tools to help understand the influence of various beam configurations on the heat transfer and solidification conditions that control microstructure development during processing. Optonicus produced Inconel 718 samples with two different beam configurations that exhibited dramatically different microstructure characteristics. A simplified analytical model was used in conjunction with microstructure selection theory to relate the differences in beam configuration and process conditions to the changes in microstructure. The analytical model was verified against standard quasi-static solutions and a numerical Computational Fluid Dynamics CFD model and the influence of fluid mechanics on the melt pool geometry was evaluated.

36 MATERIALS SCIENCE↗