Numerical simulation of materials-oriented ultra-precision diamond cutting:review and outlook

Ultra-precision diamond cutting is a promising machining technique for realizing ultra-smooth surface of different kinds of materials.While fundamental understanding of the impact of workpiece material properties on cutting mechanisms is crucial for promoting the capability of the machining technique,numerical simulation methods at different length and time scales act as important supplements to experimental investigations.In this work,we present a compact review on recent advancements in the numerical simulations of material-oriented diamond cutting,in which representative machining phenomena are systematically summarized and discussed by multiscale simulations such as molecular dynamics simulation and finite element simulation:the anisotropy cutting behavior of polycrystalline material,the thermo-mechanical coupling tool-chip friction states,the synergetic cutting responses of individual phase in composite materials,and the impact of various external energetic fields on cutting processes.In particular,the novel physics-based numerical models,which involve the high precision constitutive law associated with heterogeneous deformation behavior,the thermo-mechanical coupling algorithm associated with tool-chip friction,the configurations of individual phases in line with real microstructural characteristics of composite materials,and the integration of external energetic fields into cutting models,are highlighted.Finally,insights into the future development of advanced numerical simulation techniques for diamond cutting of advanced structured materials are also provided.The aspects reported in this review present guidelines for the numerical simulations of ultra-precision mechanical machining responses for a variety of materials.

Microstructure analyses and phase-field simulation of partially divorced eutectic solidification in hypoeutectic Mg-Al Alloys

In this study the partially divorced eutectic microstructure ofα-Mg andβ-Mg17Al12was investigated by electron backscatter diffraction,transmission electron microscopy,and phase-field modeling in hypoeutectic Mg-Al alloys.The orientation relationships between the individual eutecticαgrains,eutecticβphase,and primaryαgrains were investigated.While the amount of eutectic morphology is primarily determined by the Al content,the in-depth microstructure analyses and the phase-field simulation suggest non-interactive nucleation and growth of eutecticαphase in theβphase grown on the interdendritic primaryαdendrites.Also,phase-field simulations showed a preferred nucleation sequence where theβphase nucleates first and subsequently triggers the nucleation of eutecticαphase at the movingβphase solidification front,which supports the microstructural analysis results.

Plastic deformation modelling of tempered martensite steel block structure by a nonlocal crystal plasticity model

The plastic deformations of tempered martensite steel representative volume elements with different martensite block structures have been investi- gated by using a nonlocal crystal plasticity model which considers isotropic and kinematic hardening produced by plastic strain gradients. It was found that pro- nounced strain gradients occur in the grain boundary region even under homo- geneous loading. The isotropic hardening of strain gradients strongly influences the global stress-strain diagram while the kinematic hardening of strain gradi- ents influences the local deformation behaviour. It is found that the additional strain gradient hardening is not only dependent on the block width but also on the misorientations or the deformation incompatibilities in adjacent blocks.

Efficient finite strain elasticity solver for phase-field simulations

We present an effective mechanical equilibrium solution algorithm suitable for finite strain consideration within the phase-field method.The proposed algorithm utilizes a Fourier space solution in its core.The performance of the proposed algorithm is demonstrated using the St.Venant–Kirchhoff hyperelastic model,but the algorithm is also applicable to other hyperelastic models.The use of the fast Fourier transformation routines and fast convergence within several iterations for most common simulation scenarios makes the proposed algorithm suitable for phase-field simulations of rapidly evolving microstructures.Additionally,the proposed algorithm allows using different strain measures depending on the requirements of the underlying problem.The algorithm is implemented in the OpenPhase phase-field simulation library.A set of example simulations ranging from simple geometries to complex microstructures is presented.The effect of different externally applied mechanical boundary conditions and internal forces is also demonstrated.The proposed algorithm can be considered a straightforward update to already existing small strain solvers based on Fourier space solutions.

Non-collinear magnetic atomic cluster expansion for iron

The Atomic Cluster Expansion(ACE)provides a formally complete basis for the local atomic environment.ACE is not limited to representing energies as a function of atomic positions and chemical species,but can be generalized to vectorial or tensorial properties and to incorporate further degrees of freedom(DOF).This is crucial for magnetic materials with potential energy surfaces that depend on atomic positions and atomic magnetic moments simultaneously.In this work,we employ the ACE formalism to develop a non-collinear magnetic ACE parametrization for the prototypical magnetic element Fe.The model is trained on a broad range of collinear and non-collinear magnetic structures calculated using spin density functional theory.We demonstrate that the non-collinear magnetic ACE is able to reproduce not only ground state properties of various magnetic phases of Fe but also the magnetic and lattice excitations that are essential for a correct description of finite temperature behavior and properties of crystal defects.

The interaction between grain boundary and tool geometry in nanocutting of a bi-crystal copper

Anisotropy is one central influencing factor on achievable ultimate machined surface integrity of metallic materials.Specifically,grain boundary has a strong impact on the deformation behaviour of polycrystalline materials and correlated material removal at the microscale.In the present work,we perform molecular dynamics simulations and experiments to elucidate the underlying grain boundaryassociated mechanisms and their correlations with machining results of a bi-crystal Cu under nanocutting using a Berkovich tool.Specifically,crystallographic orientations of simulated bi-crystal Cu with a misorientation angle of 44.1°are derived from electron backscatter diffraction characterization of utilized polycrystalline copper specimen.Simulation results reveal that blocking of dislocation motion at grain boundaries,absorption of dislocations by grain boundaries and dislocation nucleation from grain boundaries are operating deformation modes in nanocutting of the bi-crystal Cu.Furthermore,heterogeneous grain boundary-associated mechanisms in neighbouring grains lead to strong anisotropic machining behaviour in the vicinity of the grain boundary.Simulated machined surface morphology and machining force evolution in the vicinity of grain boundary qualitatively agree well with experimental results.It is also found that the geometry of Berkovich tool has a strong impact on grain boundary-associated mechanisms and resultant ploughing-induced surface pile-up phenomenon.

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics.Active learning methods have been recently developed to train force fields efficiently and automatically.Among them,Bayesian active learning utilizes principled uncertainty quantification to make data acquisition decisions.In this work,we present a general Bayesian active learning workflow,where the force field is constructed from a sparse Gaussian process regression model based on atomic cluster expansion descriptors.To circumvent the high computational cost of the sparse Gaussian process uncertainty calculation,we formulate a high-performance approximate mapping of the uncertainty and demonstrate a speedup of several orders of magnitude.We demonstrate the autonomous active learning workflow by training a Bayesian force field model for silicon carbide(SiC)polymorphs in only a few days of computer time and show that pressure-induced phase transformations are accurately captured.The resulting model exhibits close agreement with both ab initio calculations and experimental measurements,and outperforms existing empirical models on vibrational and thermal properties.The active learning workflow readily generalizes to a wide range of material systems and accelerates their computational understanding.

Accelerating ab initio melting property calculations with machine learning:application to the high entropy alloy TaVCrW

Melting properties are critical for designing novel materials,especially for discovering highperformance,high-melting refractory materials.Experimental measurements of these properties are extremely challenging due to their high melting temperatures.Complementary theoretical predictions are,therefore,indispensable.One of the most accurate approaches for this purpose is the ab initio free-energy approach based on density functional theory(DFT).However,it generally involves expensive thermodynamic integration using ab initio molecular dynamic simulations.The high computational cost makes high-throughput calculations infeasible.Here,we propose a highly efficient DFT-based method aided by a specially designed machine learning potential.As the machine learning potential can closely reproduce the ab initio phase-space distribution,even for multi-component alloys,the costly thermodynamic integration can be fully substituted with more efficient free energy perturbation calculations.The method achieves overall savings of computational resources by 80%compared to current alternatives.We apply the method to the high-entropy alloy TaVCrW and calculate its melting properties,including the melting temperature,entropy and enthalpy of fusion,and volume change at the melting point.Additionally,the heat capacities of solid and liquid TaVCrW are calculated.The results agree reasonably with the CALPHAD extrapolated values.

Chemical ordering and magnetism in facecentered cubic CrCoNi alloy

The impact ofmagnetism on chemical ordering in face-centered cubic CrCoNi medium entropy alloy is studied by a combination of ab initio simulations,machine learning potentials,and Monte Carlo simulations.Large magnetic energies are revealed for some mixed L1_(2)/L1_(0) type ordered configurations,which are rooted in strong nearest-neighbor magnetic exchange interactions and chemical bonding among the constituent elements.

Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds

The primary challenge in the field of high-temperature superconductivity in hydrides is to achieve a superconducting state at ambient pressure rather than the extreme pressures that have been required in experiments so far.Here,we propose a family of compounds,of composition Mg_(2)XH_(6)with X=Rh,Ir,Pd,or Pt,that achieves this goal.These materials were identified by scrutinizing more than a million compounds using a machine-learning accelerated high-throughput workflow.We predict that their superconducting transition temperatures are in the range of 45–80 K,or even above 100 K with appropriate electron doping of the Pt compound.These results indicate that,although very rare,high-temperature superconductivity in hydrides is achievable at room pressure.

Numerical study of convective heat transfer in static arrangements of particles with arbitrary shapes:A monolithic hybrid lattice Boltzmann-finite difference-phase field solver

A compressible lattice Boltzmann-finite difference method is extended by the phase-field approach into a monolithic scheme to study fluid flow and heat transfer through regular arrangements of solid bodies of circular,elliptical and irregular shapes.The advantage of using the phase-field method is demon-strated both in its simplicity of accounting for flow and thermal boundary conditions at solid surfaces with irregular shapes and in the capability of generating such complex-shaped objects.For an array of discs,numerical results for the overall solid-to-gas heat transfer rate are validated via experiments on flow through arrays of hot cylinders.The thus validated compressible LB-FD-PF hybrid scheme is used to study the dependence of heat transfer on flow and thermal boundary conditions(Reynolds number,temperature difference between the hot solid bodies and the inlet gas),porosity as well as on the shape of solid objects.Results are rationalized in terms of the residence time of the gas close to the solid body and downstream variations of gas velocity and temperature.Perspective for further applications of the proposed methodology are also discussed.

Spatially resolved investigation of flame particle interaction in a two dimensional model packed bed

This study investigates the interaction between a premixed methane-air flame and particles inside a model packed bed.The opacity of the spherical packed beds to visible light poses a major barrier to the implementation of highly resolved optical diagnostics,so that no detailed experimental data were so far available for the validation of numerical simulation.Here,a two-dimensional cylindrical packed bed design is set up,which enables direct line-of-sight optical measurements without loss of spatial reso-lution over the fluid region between the particles.In this study,the case of cold metallic cylindrical particles(T=377 K)relevant to start-up of a reactor is investigated using internal particle cooling,which also allows cylinder specific heat transfer rate measurements by differential temperature measurements on the coolant streams.The two dimensional assumption is first verified by measuring the inflow ve-locity and cylinder temperature profile along the cylinders.Chemiluminescence imaging is then per-formed using a telecentric lens to observe the position and geometry of the two-dimensional flame front with respect to the surrounding cylinders without loss of resolution.Simultaneously,the cylinder-specific flame to cylinder heat transfer rates and cylinder surface temperature are measured.As the flame is closely surrounded by the three cooled cylinders,intense heat transfer is observed in this region corresponding to 25±2.5%of the flame thermal power.Flames were stabilised at different positions depending on inflow velocity and equivalence ratio,and a direct correlation between flame to cylinder stand-off distance and the heat transfer rate normalised to the flame thermal power was found for both top and side cylinders.Also,sidewall quenching distances to the curved cylinder surfaces were evaluated,and seem to be influenced by the presence of a warm recirculation zone behind the cylinders.This investigation provides fully resolved flame front position and heat transfer rates for a known geometry and cylinder thermal boundary conditions,and provides validation data for numerical simulations of this high flame particle coupling case.

Cutting path-dependent machinability of SiCp/Al composite under multi-step ultra-precision diamond cutting

Particle-tool interactions,which govern the synergetic deformation of SiC particle reinforced Al matrix composites under mechanical machining,strongly depend on the geometry of particle position residing on cutting path.In the present work,we investigate the influence of cutting path on the machinability of a SiCp/Al composite in multi-step ultra-precision diamond cutting by combining finite element simulations with experimental observations and characterization.Be consistent with experimentally characterized microstructures,the simulated SiCp/Al composite is considered to be composed of randomly distributed polygonally-shaped SiC particles with a volume fraction of 25 vol%.A multi-step cutting strategy with depths of cut ranging from 2 to 10 lm is adopted to achieve an ultimate depth of cut of 10 lm.Intrinsic material parameters and extrinsic cutting conditions utilized in finite element simulations of SiCp/Al cutting are consistent with those used in corresponding experiments.Simulation results reveal different particle-tool interactions and failure modes of SiC particles,as well as their correlations with machining force evolution,residual stress distribution and machined surface topography.A detailed comparison between numerical simulation results and experimental data of multi-step diamond cutting of SiCp/Al composite reveals a substantial impact of the number of cutting steps on particle-tool interactions and machined surface quality.These findings provide guidelines for achieving high surface finish of SiCp/Al composites by ultra-precision diamond cutting.

Atomic mobilities and diffusivities in Al alloys

Knowledge of diffusivity is a prerequisite for understanding many scientific and technological disciplines. In this paper, firstly major experimental methods, which are employed to provide various diffusivity data, are briefly described. Secondly, the fun-damentals of various computational methods, including first-principles method, embedded atomic method/molecular dynamic simulation, semi-empirical approaches, and phenomenological DICTRA technique, are demonstrated. Diffusion models re- cently developed for order/disorder transitions and stoichiometric compounds are also briefly depicted. Thirdly, a newly estab- lished diffusivity database for liquid, fcc_A1, Lie, bcc_A2, bcc_B2, and interrnetallic phases in the multicomponent A1 alloys is presented via a few case studies in binary, ternary and quaternary systems. And the integration of various computational techniques and experimental methods is highlighted. The reliability of this diffusivity database is validated by comparing the calculated and measured concentration profiles, diffusion paths, and Kirkendall shifts in various binary, ternary and quaternary diffusion couples. Next, the established diffusivity databases along with thermodynamic and other thermo-physical properties are utilized to simulate the microstructural evolution for Al alloys during solidification, interdiffusion and precipitation. A spe- cial discussion is presented on the phase-field simulation of interdiffusion microstructures in a series of Ni-Al diffusion couples composed of γ, γ＇, and β phases under the effects of both coherent strain and external compressive force. Future orientations in the establishment of next generation of diffusivity database are finally addressed.

Detwinning-induced reduction in ductility of twinned copper nanowires

Detwinning is a unique deformation mechanism of nanotwinned metals with twin lamellae thickness down to a few nanometers.In this work we investigate the impact of detwinning mechanism on the tensile ductility of twinned Cu nanowires containing high density of parallel twin boundaries by means of molecular dynamics simulations.Simulation results show that the fracture strain of twinned Cu nanowires has a strong dependence on twin boundary spacing,resulting from the competition between individual deformation modes.Particularly for the twinned Cu nanowires containing the thinnest twin lamellaes,the dominant detwinning mechanism leads to a significant reduction in the tensile ductility.It is found that detwinning originates from twin boundary migration,which is a result of the glide of lattice partial dislocations on the twin planes.This work advances our fundamental understanding of the twin boundary-related mechanical properties of twinned metallic nanowires.

Thermodynamic description of the Mn-Si-Zn system

The experimental phase equilibria of the Mn-Si-Zn system available in the literature were critically evaluated.Thermodynamic assessment of the Mn-Si-Zn system was then performed in the framework of CALPHAD(CALculation of PHAse Diagram) method on the basis of the experimental data in the literature.The optimal thermodynamic parameters of the ternary system were then obtained,yielding a good agreement with most of the experimental data.The complete liquidus projection and reaction scheme was also presented for the Mn-Si-Zn system.It is noteworthy that a stable closed liquid miscibility gap appears in the computed ternary phase diagrams,even though it is metastable in three boundary binaries.The occurrence of such a closed miscibility gap can be predicted by a criterion considering the general thermodynamic rules and the features of the three constituent binary systems.

Anisotropy-Related Machining Characteristics in Ultra-Precision Diamond Cutting of Crystalline Copper

Deformation behavior at grain levels greatly affects the machining characteristics of crystalline materials.In the present work,we investigate the influence of material anisotropy on ultra-precision diamond cutting of single crystalline and polycrystalline copper by experiments and crystal plasticity finite element simulations.Specifically,diamond turning and in situ SEM orthogonal cutting experiments are carried out to provide direct experimental evidence of the material anisotropy-dependent cutting results in terms of machined surface morphology and chip profile.Corresponding numerical simulations with the analysis of built stress further validate experimental results and reveal the mechanisms governing the material anisotropy influence.The above findings provide insight into the fabrication of ultra-smooth surfaces of polycrystalline metals by ultraprecision diamond turning.