Bed Fusion Additive Manufacturing Research Articles

An automated computational framework to construct printability maps for additively manufactured metal alloys

In metal additive manufacturing (AM), processing parameters can affect the probability of macroscopic defect formation (lack-of-fusion, keyholing, balling), which can, in turn, jeopardize the final product’s integrity. A printability map classifies regions in the processing space where an alloy can be printed with or without porosity defects. However, the creation of these printability maps is resource-intensive. Previous efforts to generate printability maps have required single-track experiments on pre-alloyed powder, limiting the utilization of these printability maps for the high-throughput design of printable alloys. We address these challenges in the case of Laser Powder Bed Fusion AM (L-PBF-AM) by introducing a fully computational, predictive approach to create printability maps for arbitrary alloys. Our framework uses physics-based thermal models and a variety of defect formation criteria. We benchmark the predictive ability of the proposed framework against literature data for the following commonly printed alloys: 316 Stainless Steel, Inconel 718, Ti-6Al-4V, AF96, and Ni-5Nb. Furthermore, we deploy the framework on NiTi-based Shape Memory Alloys (SMAs) as a case study. We scrutinize the accuracy of various sets of defect criteria and use these accuracy measurements to create an uncertainty-aware probabilistic framework capable of predicting the printability maps of arbitrary alloys. This framework has the potential to guide alloy designers to potentially easy-to-print alloys, enabling the co-design of high-performing printable alloys.

An Overview on Additive Manufacturing of Duplex Stainless Steels: Microstructure, Mechanical Properties, Corrosion Resistance, Postheat Treatment, and Future Perspectives

Additive manufacturing (AM) is a cutting‐edge technique for constructing intricate components with unique microstructural features and strength comparable to wrought alloys. Due to their exceptional corrosion resistance and mechanical properties, duplex stainless steels (DSS) are used in a wide range of critical applications. Over the past several years, a substantial body of research has been conducted on the AM of DSS. In‐depth knowledge is required to understand the complete benefits of the AM process. This review overviews the AM‐processed DSS parts based on process‐specific microstructural changes, mechanical behavior, electrochemical performance, and postheat treatment processes based on the classifications of directed energy deposition and powder bed fusion AM techniques along with future perspectives. Major challenges in AM of DSS are optimizing the austenite–ferrite fractions and controlling the formations of deleterious phases. This review will be extensively useful to researchers and industries working in the AM of DSS.

The Quest for the Holy Grail Of 3D Printing: A Critical Review of Recycling in Polymer Powder Bed Fusion Additive Manufacturing.

The benefits of additive manufacturing (AM) are widely recognised, boosting the AM method's use in industry, while it is predicted AM will dominate the global manufacturing industry. Alas, 3D printing's growth is hindered by its sustainability. AM methods generate vast amounts of residuals considered as waste, which are disposed of. Additionally, the energy consumed, the materials used, and numerous other factors render AM unsustainable. This paper aims to bring forward all documented solutions in the literature. The spotlight is on potential solutions for the Powder Bed Fusion (PBF) AM, focusing on Selective Laser Sintering (SLS), as these are candidates for mass manufacturing by industry. Solutions are evaluated critically, to identify research gaps regarding the recyclability of residual material. Only then can AM dominate the manufacturing industry, which is extremely important since this is a milestone for our transition into sustainable manufacturing. This transition itself is a complex bottleneck on our quest for becoming a sustainable civilisation. Unlike previous reviews that primarily concentrate on specific AM recycling materials, this paper explores the state of the art in AM recycling processes, incorporating the latest market data and projections. By offering a holistic and forward-looking perspective on the evolution and potential of AM, this review serves as a valuable resource for researchers and industry professionals alike.

Sawtooth scanning strategy for additive manufacturing

PurposeThis study aims to improve the acceleration in the additive manufacturing (AM) process. AM tools, such as extrusion heads, jets, electric arcs, lasers and electron beams (EB), experience negligible forces. However, their speeds are limited by the positioning systems. In addition, a thin tool must travel several kilometers in tiny motions with several turns while realizing the AM part. Hence, acceleration is a more significant limiting factor than the velocity or precision for all except EB.Design/methodology/approachThe sawtooth (ST) scanning strategy presented in this paper minimizes the time by combining three motion features: zigzag scan, 45º or 135º rotation for successive layers in G00 to avoid the CNC interpolation, and modifying these movements along 45º or 135º into sawtooth to halve the turns.FindingsSawtooth effectiveness is tested using an in-house developed Sand AM (SaAM) apparatus based on the laser–powder bed fusion AM technique. For a simple rectangle layer, the sawtooth achieved a path length reduction of 0.19%–1.49% and reduced the overall time by 3.508–4.889 times, proving that sawtooth uses increased acceleration more effectively than the other three scans. The complex layer study reduced calculated time by 69.80%–139.96% and manufacturing time by 47.35%–86.85%. Sawtooth samples also exhibited less dimensional variation (0.88%) than zigzag 45° (12.94%) along the build direction.Research limitations/implicationsSawtooth is limited to flying optics AM process.Originality/valueDevelopment of scanning strategy for flying optics AM process to reduce the warpage by improving the acceleration.

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Computationally guided alloy design and microstructure-property relationships for non-equiatomic Ti–Zr–Nb–Ta–V–Cr alloys with tensile ductility made by laser powder bed fusion

Single-phase body-centered cubic refractory complex concentrated alloys (RCCAs), exhibit strength retention at temperatures above the melting points of conventional Ni-based superalloys. However, their lack of room temperature tensile ductility leads to cracks during processing and/or premature failure under mechanical loading when fabricated by laser-based metals additive manufacturing (AM). We present an alloy design framework for tensile ductility in non-equimolar RCCAs amenable to AM processing within the Ti–V–Cr–Nb–Zr–Ta system. First, density functional theory (DFT) and machine learning informed screening of alloy compositions were used to down-select ∼106 alloys with potential for tensile ductility. Next, Scheil solidification modeling was used to eliminate compositions most at risk for micro-segregation and solidification cracking based on the estimated freezing range of each alloy. This led to the design of two new, representative alloys: Ti0.4Zr0.4Nb0.1Ta0.1 and Ti0.486V0.375Ta0.028Cr0.111. These alloys were evaluated for rapid solidification defect formation using in-situ synchrotron melt pool imaging, fabricated via laser powder bed fusion (L-PBF) AM, and then characterized for processing defects, microstructure, and mechanical properties. Overall, both alloys achieved tensile yield strengths >800 MPa and failure strains >5 %. However, the occurrence of un-melted powders of high melting point elements likely resulted in premature failure during tensile straining. Considerations about mitigating this defect source are discussed and the role of local micro-segregation on ductility are elucidated. Overall, these results highlight the success of our framework, and show potential for laser-based AM-RCCAs with tensile ductility.

Spectral Behavior of Fiber Bragg Gratings during Embedding in 3D-Printed Metal Tensile Coupons and Cyclic Loading.

Additive manufacturing (AM) enables the spatially configurable 3D integration of sensors in metal components to realize smart materials and structures. Outstanding sensing capabilities and size compatibility have made fiber optic sensors excellent candidates for integration in AM components. In this study, fiber Bragg grating (FBG) sensors were embedded in Inconel 718 tensile coupons printed using laser powder bed fusion AM. On-axis (fiber runs through the coupon's center of axis) and off-axis (fiber is at 5° and 10° to the coupon's center of axis) sensors were buried in epoxy resin inside narrow channels that run through the coupons. FBGs' spectral evolutions during embedment in the coupons were examined and cyclic loading experiments were conducted to analyze and evaluate the sensor integration process, complex strain loading, process flaws, and sensing performance. This study also demonstrates that the AM process-born deficiencies such as poor surface finish and staircase effects can be detrimental to the embedded sensors and their sensing performance.

On the feasibility and the impact resistance of a 3D cross-based fractal produced by powder bed fusion additive manufacturing

Designers have been fascinated by exploring new geometries made by high-performance structures. In more specific terms, biological systems have always been proven to be characterised by sophisticated structures with adapting properties to nature challenges. Insightful analyses have shown how these natural structures are dominated by characteristics such as high energy absorption and elevated strength-weight proportion. Fractal geometries are examples of bio-inspired mathematical objects whose complex 3D structures can be obtained only by advanced manufacturing systems, such as additive manufacturing (AM). This study investigates the feasibility and energy absorption properties of a novel fractal structure based on a 3D Greek cross (3D-CFS). The structure was designed with different volume fractions and produced by powder bed fusion (PBF) AM processes in polyamide (PA12) and thermoplastic polyurethane (TPU). The 3D-CFS properties are investigated under quasi-static and dynamic compression tests. The analysis revealed that for certain geometrical parameters, the manufacturing of the structures is constrained by the sintered powder entrapped in the structure. However, in the case of powder-free structures, the results showed a high impact resistance and cushioning capability. Overall, in terms of specific energy absorption (SEA), the TPU structures showed values between 2.5 and 3.5 kJ/kg, while PA12 ones are between 7.5 and 17.4 kJ/kg, making the 3D-CFS structure compatible with personal protective equipment (PPE) applications. Compared to the literature data on cellular structures made by AM, 3D-CFS performs considerably better. Also, PA12 3D-CFS is better, with a SEA value up to 170% higher than that of a typical material employed for head PPE (e.g. EPS-60 SEA equal to 2.76 kJ/kg). In contrast, TPU 3D-CFS looks more promising in the case of multiple impact conditions.

Manipulating Stacking Fault Energy to Achieve Crack Inhibition and Superior Strength-Ductility Synergy in an Additively Manufactured High-Entropy Alloy.

Additive manufacturing (AM) is a revolutionary technology that heralds a new era in metal processing, yet the quality of AM-produced parts is inevitably compromised by cracking induced by severe residual stress. In this study, a novel approach is presented to inhibit cracks and enhance the mechanical performances of AM-produced alloys by manipulating stacking fault energy (SFE). A high-entropy alloy (HEA) based on an equimolar FeCoCrNi composition is selected as the prototype material due to the presence of microcracks during laser powder bed fusion (LPBF) AM process. Introducing a small amount (≈2.4 at%) of Al doping can effectively lower SFE and yield the formation of multiscale microstructures that efficiently dissipate thermal stress during LPBF processing. Distinct from the Al-free HEA containing visible microcracks, the Al-doped HEA (Al0.1CoCrFeNi) is crack free and demonstrates ≈55% improvement in elongation without compromising tensile strength. Additionally, the lowered SFE enhances the resistance to crack propagation, thereby improving the durability of AM-printed products. By manipulating SFE, the thermal cycle-induced stress during the printing process can be effectively consumed via stacking faults formation, and the proposed strategy offers novel insights into the development of crack-free alloys with superior strength-ductility synergy for intricate structural applications.

Performance Improvement for the CuCrZr Alloy Produced by Laser Powder Bed Fusion Using the Remelting Process.

Owing to the high optical reflectivity of copper powder, the high-performance fabrication of copper alloys in the laser additive manufacturing (AM) field is problematic. To tackle this issue, this study employs the remelting process during laser powder bed fusion AM to fabricate defect-free and high-performance CuCrZr alloy. Compared to the non-remelting process, the remelting process yields finer grains, smaller precipitates, denser dislocations, and smaller dislocation cells. It realizes not only the dense molding of high laser reflectivity powders but also excellent mechanical properties and electrical conductivity (with an ultimate tensile strength of 329 MPa and conductivity of 96% IACS) without post-heat treatment. Furthermore, this study elucidates the influence of complex thermal gradients and multiple thermal cycles on the manufacturing process under the remelting process, as well as the internal mechanisms of microstructure evolution and performance improvement.

Analytical models for flow time estimation of additive manufacturing machines

The use of Additive Manufacturing (AM) technology has largely increased in the last years. Because of its large differences from conventional technologies, the use of AM in production systems might call for new strategies in production planning and control. To this aim, this paper proposes analytical models to predict aggregate performance measures such as flow time, work in process, and production throughput, for production systems characterised by Laser Powder Bed Fusion AM technology. These indicators could be used both in operations strategy development and in technology comparison. The proposed models differentiate for their detail of the analysis and the number of input parameters that need to be estimated. The results show that the level of detail of the model affects the analysis leading to quite different values of the performance measures, especially in the case of highly saturated systems. Also, a discussion about the applicability of the proposed model to other AM technologies show whether and to what extent the proposed models can be applied for modelling other AM technologies.

Structural and mechanical properties of the additive manufactured CrFeCoNi(Al,Ti) high-entropy alloys produced using powder blends

High-entropy Alloys (HEAs) are considered prospective materials demonstrating the new approach of alloy design creating new compositions for harsh conditions. However, searching for alloy chemical composition providing the best material properties is a costly process. Additive manufacturing (AM) can be an effective technique for adjusting the alloy composition by using several initial materials. The powder bed fusion (PBF) AM process allows the printing of solid parts using powder blends. In the present study, the CrFeCoNi(Al,Ti) HEAs were printed by the PBF technique using the blends of three powders. The structural and phase investigations revealed the chemical inhomogeneity in the materials that led to the new phase formations affecting the mechanical characteristics. The high-temperature annealing at 1200 °C can be considered a post-treatment process for the printed alloys as a homogenization process while the annealing at a lower temperature of 800 °C initiates the decomposition of the initially formed f.c.c. phase.

A Review of Computational Approaches to the Microstructure-Informed Mechanical Modelling of Metals Produced by Powder Bed Fusion Additive Manufacturing.

In the rapidly evolving field of additive manufacturing (AM), the predictability of part properties is still challenging due to the inherent multiphysics complexity of the technology. This results in time-consuming and costly experimental guess-and-check approaches for manufacturing each individual design. Through synthesising advancements in the field, this review argues that numerical modelling is instrumental in mitigating these challenges by working in tandem with experimental studies. Unique hierarchical microstructures induced by extreme AM process conditions- including melt pool patterns, grains, cellular-dendritic substructures, and precipitates-affect the final part properties. Therefore, the development of microstructure-informed mechanical models becomes vital. Our review of numerical studies explores various modelling approaches that consider the microstructural features explicitly and offers insights into multiscale stress-strain analysis across diverse materials fabricated by powder bed fusion AM. The literature indicates a growing consensus on the key role of multiscale integrated process-structure-property-performance (PSPP) modelling in capturing the complexity of AM-produced materials. Current models, though increasingly sophisticated, still tend to relate only two elements of the PSPP chain while often focusing on a single scale. This emphasises the need for integrated PSPP approaches validated by a solid experimental base. The PSPP paradigm for AM, while promising as a concept, is still in its infantry, confronting multifaceted challenges that require in-depth, multidisciplinary expertise. These challenges range from accounting for multiphysics phenomena (e.g., advanced laser-material interaction) and their interplay (thermo-mechanical and microstructural evolution for simulating Type II residual stresses), accurately defined assumptions (e.g., flat molten surface during AM or purely epitaxial solidification), and correctly estimated boundary conditions for each element of the PSPP chain up to the need to balance the model's complexity and detalisation in terms of both multiphysics and discretisation with efficient multitrack and multilayer simulations. Efforts in bridging these gaps would not only improve predictability but also expedite the development and certification of new AM materials.

Prototype Design for Grading Structures in Powder Bed Fusion Processes.

While targeted alignment in certain additive manufacturing (AM) methods such as material extrusion (MEX) and stereolithography (SLA) has been well documented in the research community, a method for targeted alignment of added fillers or fibrous materials in powder bed fusion (PBF) AM devices has yet to be successfully achieved. Similarly, incorporation of multimaterials does not work easily with any of the AM technologies. This study creates a prototype design that could be integrated into a PBF system to allow for multimaterial layer deposition and alignment of powders and powder blends. The rheological properties of polyamide powder and a range of polyamide composite blends (incorporating milled carbon fibre, graphite flakes, polytetrafluoroethylene, and glass microspheres) in different concentrations were studied, and together with the particle size distribution and particle morphology analysis were applied for the design of a prototype hopper for incorporation in the PBF system to create targeted multimaterial deposition. Different concept designs, multichambered and multi-hopper with hopper angles calculated specifically for the composite blend powders selected, were proposed. Initial deposition trials outside a PBF process were tested, and the deposited layers were measured.

Creep Analysis and Microstructural Evaluation of a Novel Additively Manufactured Nickel-Base Superalloy (ABD®-900AM)

Abstract Nickel-base superalloys containing 30 to 50% gamma prime (γ') volume fraction are typically used in hot section components (e.g., guide vanes or blades) for power generating gas turbines, and suitable time-dependent properties are required for long-term elevated temperature operation. Additive manufacturing (AM) has recently been used to develop complex hot-section parts utilizing innovative designs with enhanced cooling features which improve efficiencies by reducing cooling air consumption. To further explore the opportunity to improve time-dependent AM superalloys, this paper focuses on a fundamental creep study and characterization of a novel nickel-base superalloy (ABD-900AM) that was manufactured using a laser-based powder bed fusion (LBPBF) AM process. The material was subjected to a subsolvus solution anneal and multistep aging heat treatment (HT) to produce a bi-modal distribution with ∼35% volume fraction of gamma prime without postprocessing hot isostatic pressing (HIP). Microstructural characterization was carried out for the as-built and fully heat-treated structures, and a creep-rupture test program was conducted to study the resultant creep properties. Activation energies and stress exponents in addition to rupture strength and deformation resistance were compared to traditionally cast IN939 and IN738 materials. After testing, specimens were evaluated using a variety of microscopy tools to determine location and features associated with creep damage. The optimized chemistry for ABD-900AM was printed crack free and fully dense in contrast to studies on similar alloys where significant process development and postbuild heat treatments were required. High-temperature mechanical properties in the heat-treated material showed some decrease in creep strength when compared to traditional casting. This strength and rupture life debit was dependent on build orientation, but a considerable increase in creep ductility was observed due to differences in the microstructure when compared with similar AM alloys. Analysis of creep data showed differences in creep mechanisms compared to traditional cast alloys. The relationship between microstructure and creep mechanisms is discussed, and ongoing work to further improve rupture strength through heat-treatment optimization will be highlighted.

Process qualification of laser powder bed fusion based on processing-defect structure-fatigue properties in Ti-6Al-4V

The aim of this manuscript is to give a compact overview of the results that illustrate the applicability of processing-structure-property relationships in the increasingly important context of 3D printing of metals. A process qualification approach based on the physics-based understanding of defect formation in laser powder bed fusion (L-PBF) additive manufacturing (AM) is investigated for an aerospace-grade titanium alloy (Ti-6Al-4V). A physically interpretable qualification approach is critical for enabling L-PBF part certification for structure-critical applications. This approach relies on systematic experimentation, characterization, testing, and data analysis tasks including design of experiments varying power and velocity to generate varying defect populations, process window development based on defect structure, high throughput fatigue testing, and fractography, 2D porosity characterization, and use of extreme value statistics to develop a porosity metric that, in turn, could have predictive power for the variation in fatigue performance. Results from four-point bend fatigue tests demonstrate that a process window can be defined based on this key mechanical property. This relatively high throughput approach can, in turn, support a reduced set of round bar fatigue tests typically used for qualification. Overall, the proposed ecosystem for process qualification of L-PBF AM shows promise and is expected to apply to other materials and powder bed fusion AM technologies. • A delineated process window for L-PBF printing with Ti-6Al-4V was identified for both porosity and fatigue in power and velocity space with all other variables fixed, which is in good agreement with previous work. • There is a distinct increase in porosity as one moves into the keyhole range (low speed, high power) or towards lack-of-fusion (high speed, low power). • Extreme value analysis (EVA) is found to be beneficial in quantifying pore sizes and frequencies. • The fatigue life measured in 4-point bend fatigue mirrors the variations in porosity, i.e., the fatigue life decreases as porosity increases and is maximal within the process window. • 4-point bend fatigue is found to be practical for screening printed material quality.

Additive manufacturing SiC-reinforced maraging steel: Parameter optimisation, microstructure and properties

The unique deposition manner of additive manufacturing (AM) allows the near-net-shaping of components with multiple materials configurations and complex geometries, which sheds light on the process of high-performance metal matrix composites (MMCs). This work explores laser powder bed fusion (LPBF) AM of SiC-reinforced maraging steel MMCs to consolidate the merits of both ceramics and metal matrix for improving overall properties. The laser processing parameters were systematically optimised based on the density, roughness and hardness of the deposited samples. The effects of SiC content on the microstructures, mechanical properties, tribological performance, and wear resistance are elucidated. SiC particles are refined with uniform distribution in the metal matrix after laser processing. The highest tensile strength reaches 1611 ​MPa together with an elongation of about 10.1% with 3 ​vol% SiC addition. The tribological performance of MMCs is investigated by studying the coefficient of friction (COF), wear rate, and worn morphology. The COF has been slightly reduced with the SiC addition, and the wear rate of MS reduced from 3.25 ​× ​10 −5 to 1.72 ​× ​10 −5 mm 3 /Nm with the 12 ​vol% SiC addition. The underlying wear mechanisms are also investigated. Besides, the corrosion behaviour of MMCs is also investigated; the addition of SiC (≥6 ​vol%) has improved the corrosion properties of the matrix.

A Numerical Investigation of Dimensionless Numbers Characterizing Meltpool Morphology of the Laser Powder Bed Fusion Process.

Microstructure evolution in metal additive manufacturing (AM) is a complex multi-physics and multi-scale problem. Understanding the impact of AM process conditions on the microstructure evolution and the resulting mechanical properties of the printed component remains an active area of research. At the meltpool scale, the thermo-fluidic governing equations have been extensively modeled in the literature to understand the meltpool conditions and the thermal gradients in its vicinity. In many phenomena governed by partial differential equations, dimensional analysis and identification of important dimensionless numbers can provide significant insights into the process dynamics. In this context, we present a novel strategy using dimensional analysis and the linear least-squares regression method to numerically investigate the thermo-fluidic governing equations of the Laser Powder Bed Fusion AM process. First, the governing equations are solved using the Finite Element Method, and the model predictions are validated by comparing with experimentally estimated cooling rates, and with numerical results from the literature. Then, through dimensional analysis, an important dimensionless quantity interpreted as a measure of heat absorbed by the powdered material and the meltpool, is identified. This dimensionless measure of absorbed heat, along with classical dimensionless quantities such as Péclet, Marangoni, and Stefan numbers, are employed to investigate advective transport in the meltpool for different alloys. Further, the framework is used to study variations in the thermal gradients and the solidification cooling rate. Important correlations linking meltpool morphology and microstructure-evolution-related variables with classical dimensionless numbers are the key contribution of this work.

Reactive two-step additive manufacturing of ultra-high temperature carbide ceramics

Ultra-high-temperature ceramics (UHTCs) are candidate structural materials for applications that require resiliency to extreme temperatures (>2000 °C), high mechanical loads, or aggressive oxidizing environments. Processing UHTC transition metal carbides as standalone materials using additive manufacturing (AM) methods has not been fully realized due to their extremely slow atomic diffusivities that impede sintering and large volume changes during indirect AM that can induce defect structures. In this work, a two-step, reactive AM approach was studied for the formation of the ultra-high temperature ceramic TiCx. Readily available equipment including a polymer powder bed fusion AM machine and a traditional tube furnace were used to produce UHTC cubes and lattice structures with sub-millimeter resolution. This processing scheme incorporated, (1) selective laser sintering of a Ti precursor mixed with a phenolic binder for green body shaping, and (2) ex-situ, isothermal gas-solid conversion of the green body in CH4 to form TiCx structures. Reactive post-processing in CH4 resulted in up to 98.2 wt. % TiC0.90 product yield and a reduction in net-shrinkage during consolidation due to the volume expansion associated with the conversion of Ti to TiC. Results indicated that reaction bonding associated with the Gibbs free energy release associated with TiC formation produced interparticle adhesion at low furnace processing temperatures. The ability to bond highly refractory materials through this type of process resulted in structures that were crack-free and resisted fracture during thermal shock testing. Broadly, the additive manufacturing approach presented could be useful for the production of many UHTC carbides that might otherwise be incompatible with prevailing AM techniques that do not include reaction synthesis.

Calibrating uncertain parameters in melt pool simulations of additive manufacturing

Melt pool scale numerical modeling of additive manufacturing (AM) processes can provide predictive capabilities and theoretical insight into the process-property-structure-performance relationships for AM parts. Despite capabilities of numerical models to solve complex multi-physics problems, it is often important to consider a tradeoff between detailed physics and computational cost. Therefore, sources of uncertainty in both experimental conditions and the parameters needed for modeling require models to be validated against empirical evidence. Here, a method is proposed to calibrate uncertain parameters used in continuum-scale melt pool models for powder bed fusion (PBF) AM. Both a simplified heat transfer model and a heat transfer and fluid flow model were investigated. A surrogate model and Markov chain-based optimization algorithm calibrated melt pool geometry for models within experimental variation of the target melt pool width and depth from the NIST AM-Bench 2018-02 dataset. The melt pool temperature distributions, solidification parameters, and simulated multi-layer solidification microstructures were compared between the two models. Similar results from both models indicate that calibrated, lower fidelity numerical models may be used in place of higher fidelity models to generate melt pool solidification data. These calibrated models therefore enable lower computational cost melt pool simulations without a noticeable decrease in simulation accuracy for grain-scale microstructure simulations.