Modeling and Experimental Validation of the Electron Beam Selective Melting Process

Electron beam selective melting （EBSM） is a promising additive manufacturing （AM） technology. The EBSM process consists of three major procedures：（1） spreading a powder layer, （2） preheating to slightly sinter the powder, and （3） selectively melting the powder bed. The highly transient multi-physics phenomena involved in these procedures pose a significant challenge for in situ experimental observation and measurement. To advance the understanding of the physical mechanisms in each procedure, we leverage high- fidelity modeling and post-process experiments. The models resemble the actual fabrication procedures, including （1） a powder-spreading model using the discrete element method （DEM）, （2） a phase field （PF） model of powder sintering （solid-state sintering）, and （3） a powder-melting （liquid-state sintering） model using the finite volume method （FVM）. Comprehensive insights into all the major procedures are provided, which have rarely been reported. Preliminary simulation results （including powder particle packing within the powder bed, sintering neck formation between particles, and single-track defects） agree qualitatively with experiments, demonstrating the ability to understand the mechanisms and to guide the design and optimization of the experimental setup and manufacturing process.

Data Mining for Mesoscopic Simulation of Electron Beam Selective Melting

In the electron beam selective melting(EBSM)process,the quality of each deposited melt track has an effect on the properties of the manufactured component.However,the formation of the melt track is governed by various physical phenomena and influenced by various process parameters,and the correlation of these parameters is complicated and difficult to establish experimentally.The mesoscopic modeling technique was recently introduced as a means of simulating the electron beam(EB)melting process and revealing the formation mechanisms of specific melt track morphologies.However,the correlation between the process parameters and the melt track features has not yet been quantitatively understood.This paper investigates the morphological features of the melt track from the results of mesoscopic simulation,while introducing key descriptive indexes such as melt track width and height in order to numerically assess the deposition quality.The effects of various processing parameters are also quantitatively investigated,and the correlation between the processing conditions and the melt track features is thereby derived.Finally,a simulation-driven optimization framework consisting of mesoscopic modeling and data mining is proposed,and its potential and limitations are discussed.

Patient-specific bicuspid aortic valve hemodynamics study based on computer simulation and in vitro experiment

Bicuspid aortic valve(BAV)is a common congenital malformation of the aortic valve with various structural characteristics.Different types of BAV can cause secondary aortic diseases,including calcific aortic valve stenosis and aortic dilation,although their pathogenesis remains unclear.In this study,we first established patient-specific BAV simulation models and silicone models(Type 0 A-P,Type 1 R-N,and Type 1 L-R)based on clinical computed tomography angiography(CTA)and pressure data.Next,we applied a research method combining fluid-structure interaction(FSI)simulation and digital particle image velocimetry(DPIV)experiment to quantitatively analyze the hemodynamic,structural mechanical,and flow field characteristics of patients with different BAV types.Simulation-based hemodynamic parameters and experimental results were consistent with clinical data,affirming the accuracy of the model.The location of the maximum principal strain in the patientspecific model was associated with the calcification site,which characterized the mechanism of secondary aortic valve stenosis.The maximum wall shear stress(WSS)of the patient-specific model(>67.1 Pa)exceeded 37.9 Pa and could cause endothelial surface injury as well as remodeling under long-term exposure,thus increasing the risk of aortic dilation.The distribution of WSS was mainly caused by BAV type,resulting in different degrees of dilation in different parts guided by the type.The patient-specific model revealed a maximum viscous shear stress(VSS)value of 5.23 Pa,which was smaller than the threshold for shear-induced hemolysis of red blood cells(150 Pa)and platelet activation(10 Pa),but close to the threshold for platelet sensitization(6 Pa).The results of flow field characteristics revealed a low risk of hemolysis but a relative high risk of thrombus formation in the patient-specific model.This study not only provides a basis for future comprehensive research on BAV diseases,but also generates relevant insights for theoretical guidance for calcific aortic valve stenosis and aortic dilation caused by different types of BAV,as well as biomechanical evidence for the potential risk of hemolysis and thrombus formation in BAV,which is of great value for clinical diagnosis and treatment of BAV.

Phase-field modeling of grain evolutions in additive manufacturing from nucleation,growth,to coarsening

A three-dimensional phase-field model is developed to simulate grain evolutions during powder-bed-fusion(PBF)additive manufacturing,while the physically-informed temperature profile is implemented from a thermal-fluid flow model.The phase-field model incorporates a nucleation model based on classical nucleation theory,as well as the initial grain structures of powder particles and substrate.The grain evolutions during the three-layer three-track PBF process are comprehensively reproduced,including grain nucleation and growth in molten pools,epitaxial growth from powder particles,substrate and previous tracks,grain re-melting and re-growth in overlapping zones,and grain coarsening in heat-affected zones.A validation experiment has been carried out,showing that the simulation results are consistent with the experimental results in the molten pool and grain morphologies.Furthermore,the grain refinement by adding nanoparticles is preliminarily reproduced and compared against the experimental result in literature.

Mechanism of keyhole pore formation in metal additive manufacturing

During metal additive manufacturing,the porosity of the as-built part deteriorates the mechanical property and even hinders the further application of metal additive manufacturing.Particularly,the mechanisms of keyhole pores associated with the keyhole fluctuation are not fully understood.To reveal the mechanisms of the keyhole pores formation,we adopt a multiphysics thermal-fluid flow model incorporating heat transfer,liquid flow,metal evaporation,Marangoni effect,and Darcy’s law to simulate the keyhole pore formation process,and the results are validated with the in situ X-ray images.The simulation results present the instant bubble formation due to the keyhole instability and motion of the instant bubble pinning on the solidification front.Furthermore,comparing the keyhole pore formation under different laser scanning speeds shows that the keyhole pore is sensitive to the manufacturing parameters.Additionally,the simulation under a low ambient pressure shows the feasibility of improving the keyhole stability to reduce and even avoid the formation of keyhole pores.

Selective laser melting of dense and crack-free AlCoCrFeNi_(2.1) eutectic high entropy alloy: Synergizing strength and ductility

Additively manufactured high-entropy alloys generally suffer from low strength and/or poor ductility.In this work,by leveraging the good castability of eutectic high entropy alloys and high cooling rate of selective laser melting(SLM),we report a nearly fully dense and crack-free as-SLM AlCoCrFeNi_(2.1) eutectic high entropy alloy with an exceptional strength-ductility synergy,showing an ultrahigh yield strength of 982.1±35.2 MPa and an ultimate tensile strength of 1322.8±54.9 MPa together with an elongation to fracture of 12.3±0.5%.Such strength-ductility enhancement is owing to the heterogeneous eutectic microstructure consisting of the columnar,equiaxed,and“L-shape”cells with much refined sizes down to nanoscales.The morphology of cells in the transition zone is related to the misorientation between the growth direction of adjacent layers.This heterogeneous eutectic microstructure is the result of the graingrowth behavior dominated by the mechanisms of the epitaxial growth and growth of heterogeneous nuclei in SLM.Our current results provide a new methodology for the future design of ultrahigh-strength and ductile SLM-fabricated metallic materials including HEAs,and other printable alloys for various structural applications.

Multistage strain-hardening behavior of ultrastrong and ductile lightweight refractory complex-concentrated alloys

Lightweight high-entropy alloys or complex-concentrated alloys have demonstrated great potential for engineering applications due to their high strength and lightweight.However,a weak strain-hardening ability and a limited tensile ductility remain their major hindrance.Here,a multistage strain-hardening effect is developed to ensure a high strength and still a sufficient ductility in a rolled and annealed(Ti_(44)V_(28)Zr_(14)Nb_(14))_(98.5)Mo_(1.5)(at.%)lightweight refractory complex-concentrated alloy(M1.5A-LRCCA).This multistage strain-hardening behavior is related to the microstructure and the corresponding initial aver-age dislocation density and distribution by comparison with rolled and annealed Ti_(44)V_(28)Zr_(14)Nb_(14)(M0-LRCCA)and as-cast(Ti_(44)V_(28)Zr_(14)Nb_(14))_(98.5)Mo_(1.5)(M1.5C-LRCCA).The microstructure,with homogeneously distributed submicron precipitations,a moderate initial average dislocation density,and uniform disloca-tion distribution(e.g.,M1.5A-LRCCA),is susceptible to producing various deformation substructures,such as dislocation substructures(slip bands,Taylor lattices,microbands,DDWs),shear bands,and deformation twins,which results in the multistage strain-hardening behavior.This method of achieving multistage strain hardening behavior through a microstructure modulation is significant for engineering applications of lightweight high-entropy alloys or complex-concentrated alloys,and it might be extended to other lightweight and high-strength alloys.

Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing

A bottleneck in Laser Powder Bed Fusion(L-PBF)metal additive manufacturing(AM)is the quality inconsistency of its products.To address this issue without costly experimentation,computational multi-physics modeling has been used,but the effectiveness is limited by parameter uncertainties and their interactions.We propose a full factorial design and variable selection approach for the analytics of main and interaction effects arising from material parameter uncertainties in multi-physics models.Data is collected from high-fidelity thermal-fluid simulations based on a 2-level full factorial design for 5 selected material parameters.Crucial physical phenomena of the L-PBF process are analyzed to extract physics-based domain knowledge,which are used to establish a validation checkpoint for our study.Initial data visualization with half-normal probability plots,interaction plots and standard deviation plots,is used to assess if the checkpoint is being met.We then apply the combination of best subset selection and the LASSO method on multiple linear regression models for comprehensive variable selection.Analytics yield statistically and phyiscally validated findings with practical implications,emphasizing the importance of parameter interactions under uncertainty,and their relation to the underlying physics of L-PBF.

A Review on Discrete Element Method Simulation in Laser Powder Bed Fusion Additive Manufacturing

Laser powder bed fusion(LPBF)is a popular metal additive manufacturing technique.Generally,the materials employed for LPBF are discrete and particulate metal matters.Thus,the discontinuous behaviors exhibited by the powder materials cannot be simulated solely using conventional continuum-based computational approaches,such as finite-element or finite-difference methods.The discrete element method(DEM)is a proven numerical method to model discrete matter,such as powder particles,by tracking the motion and temperature of individual particles.Recently,DEM simulation has gained popularity in LPBF studies.However,it has not been widely applied.This study reviews the existing applications of DEM in LPBF processing,such as powder spreading and fusion.A review of the existing literature indicates that DEM is a promising approach in the study of the kinetic and thermal fluid behaviors of powder particles in LPBF additive manufacturing.

Modeling process-structure-property relationships for additive manufacturing

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing （AM） materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the process- structure relationship, the multi-scale multi-physics pro- cess modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a high- efficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.