As an emerging additive manufacturing method, cold spray additive manufacturing (CSAM) has attracted more and more researchers’ attention due to its unique advantages. However, only a few researchers have studied the fabrication of complex structural components. Therefore, it is important to develop a general CSAM framework that is suitable for the fabrication of different shapes of workpieces. In particular, the choice for the optimal kinematic spraying parameters, the prediction of deposit evolution and the planning of spraying trajectory are the most basic and crucial. Different sub-modules are integrated in the proposed framework to solve these problems. In detail, the modeling methodology is used to obtain the optimal kinematic spraying parameters and to predict the deposit evolution in the simulation. Based on the feasible parameters, the trajectory planification methodology is used to generate the spraying trajectory for the workpiece being manufactured, especially the workpiece with complex structure. Finally, the simulation and experimental results of a fabrication for a workpiece with complex structure provide the developed system is reliable and effective. The framework developed in this paper can considered as a general tool for additive manufacturing of with complex structural workpieces in the CSAM.

The porous architecture of coatings has a significant influence on the coating performances and thus should be properly designed for the intended applications. For simulating the coating properties, it is necessary to determine the numerical representation of the coating microstructure. In this study, YSZ coatings were manufactured by suspension plasma spray (SPS). Afterwards, the porous architecture of as-prepared coatings was investigated by the combination of three techniques, imaging analysis, Ultra Small Angle X-ray Scattering (USAXS), and X-ray transmission. A microstructural model for reconstructing the porous architecture of the SPS coating was subsequently computed according to the collected experimental results. Finally, the coating thermal properties were simulated based on the model and were compared with the experimental results.

(MnCu)3O4 spinel coatings are good candidates for Cr-positioning protection on stainless steel interconnect. The spinel coatings can be formed by sputtering MnCu followed by a hot oxidation treatment. To understand how the elements diffuse in the MnCu-steel system, a homogenization diffusion-couple model was built with consideration for Mn oxidation at the coating surface. According to the simulation, the diffusion of Fe from the steel substrate to the MnCu coating occurred while Cr was almost trapped under the MnCu coating. Cu-rich metallic phase formed under the Mn-oxide layer early in the process. The solid solubility of Cr in such Cu phase was very low which can function as a Cr blocker so that Cr external oxidation can be inhibited. The inward diffusion of Mn from the coating to the substrate was caused by the formation of a Mn concentration peak at the interface which, based on thermodynamic simulations, was probably due to the dissolution of Mn with Fe and Cr.

The aim of this work is to better understand the build-up of thermal barrier coatings (TBC) on microtextured substrates, particularly the influence of geometry on the behavior of plasma jets in substrate boundary layers. Coatings produced by suspension plasma spraying served as an experimental reference for numerical analysis, which involved advanced turbulent flow and volumetric heat source modeling along with the use of commercial fluid flow software. Geometric and numerical models were used to simulate the generation of plasma inside the torch and the resulting plasma flow with its highly nonlinear thermophysical characteristics. This work opens the possibility of predicting feedstock particle movement and deposition, which is essential in understanding coating build-up mechanisms in general and the flow of fine particles on substrate surfaces in particular.

The growth kinetics of thermally grown oxide (TGO) silica in Yb-disilicate (YbDS) environmental barrier coatings (EBCs) significantly affects the durability of EBCs. The oxygen permeability can control the TGO growth kinetics and thus could play an essential role in determining EBCs life. Therefore, the oxygen permeability constant of YbDS and TGO is systematically evaluated and quantified in terms of thermodynamics using defect reactions and the parabolic rate constant (kp), respectively. Dry oxygen and wet oxygen conditions as well as different temperatures, partial pressures and top coat modifiers are investigated. The results offer evidence that the oxygen permeability constant for the YbDS top coat is an order of magnitude higher than for the TGO. As such, the TGO hinders the oxidant diffusion stronger, proving to be the diffusion rate controlling layer. Moreover, water vapor strongly increases the oxygen permeability with defect reactions playing a key role. It is suggested that the mass transfer through the top coat is primarily by outward ytterbium ion diffusion and inward oxygen ion movement, with the latter being dominant, particularly in wet environments. The effect of top coat modifiers on oxidant permeation is composition sensitive and seems to be related to their interaction with oxygen ions and their mobility.

In an atmospheric plasma spray (APS) process, in-flight powder particle characteristics, such as the particle velocity and temperature, have significant influence on the coating formation. The nonlinear relationship between the input process parameters and in-flight particle characteristics is thus of paramount importance for coating properties design and quality control. It is also known that the ageing of torch electrodes affects this relationship. In recent years, machine learning algorithms have proven to be able to take into account such complex nonlinear interactions. This work illustrates the application of ensemble methods based on decision tree algorithms to evaluate and to predict in-flight particle temperature and velocity during an APS process considering torch electrodes ageing. Experiments were performed to record simultaneously the input process parameters, the in-flight powder particle characteristics and the electrodes usage time. Various spray durations were considered to emulate industrial coating spray production settings. Random forest and gradient boosting algorithms were used to rank and select the features for the APS process data recorded as the electrodes aged and the corresponding predictive models were compared. The time series aspect of the data will be examined.

In this paper, a diffusion kinetic model was applied to simulate the microstructure development in a MCrAlY-superalloy system at high temperatures. Both simulation and experimental results showed that γ+γ’ microstructure was obtained in the coatings due to Al depletion after oxidation. With the help of the modelling, the mechanism of the formation of the diffusion zones in the single crystal (SC) superalloy can be also analyzed. The results revealed that the inward diffusion of Al from coating affected the depth of secondary reaction zone (SRZ) with the precipitation of TCP phases while the depth of inter-diffusion zone (IDZ) was decided by the inward diffusion of Cr.

Severe plastic deformation (SPD) is the main feature of the Cold Spray (CS) process, which might result in producing metal grain refinement under extensive hydrostatic pressure and high strain rate loading conditions. In this study, an anisotropic strain gradient plasticity model (SGP) is presented to predict materials behavior in CS process. The enhanced dislocation densities produced throughout particle deformation affect coating material properties and modify their thermodynamic characteristics and kinetics of resistance to plastic deformations. This study also demonstrates that the SGP model can describe the experimentally observed trends and account for homogenization of the accumulated strains under dynamic recrystallization conditions. The evolution of statistically stored dislocation density through the characteristic material length scale parameter is in good agreement with experimental results and data reported by other research groups. The proposed SGP modeling is suggested as an express method to evaluate the advanced coating and additively manufactured materials, and powder feedstock used in thermal spray and 3D manufacturing applications.

Up to now, the role of particle sizes on deformation features of ceramic particles in aerosol deposition (AD), is not fully understood. For distinguishing general features, two-dimensional molecular dynamics (MD) simulations are applied to study associated phenomena. The nanoparticles are assumed to have original sizes of 10-300 nm and to impact the substrate at velocities of 100-800 m/s. The applied Lennard-Jones potential for the modelled nanoparticles were adjusted to mimic the mechanical properties of TiO2-anatase. For small particles, the simulations reveal three different impact behaviors of (i) rebounding, (ii) bonding and (iii) fragmentation based on initial size and impact velocity, whereas, the larger ones do not show the bonding behavior. The upper limit of the bonding regime shrinks with increasing particle sizes, the field then diminishing for the largest ones. The different impact phenomena were analyzed by evolution of the stress, strain and temperature fields. Stress and strain field results showed that “localized inelastic deformation” occurred at particle sites spreading from the interface to the substrate to the particle core. Calculated temperature fields show a local rise of around 1200 Kelvin due to the inelastic deformation, which is probably sufficient for thermal activation of further deformation features.

Anode erosion is a common concern in dc plasma spray torches. It depends largely on the heat flux brought by the arc and the dimensions, residence time, and mode of the arc attachment to a given location on the anode wall. This paper compares anode arc attachment modes predicted by LTE (local thermodynamic equilibrium) and 2-T (two-temperature) arc models that include the electrodes in the computational domain. The analysis is based on a commercial cascaded-anode plasma torch operated at high current (500 A) and low gas flow rate (60 NLPM of argon). It shows that the LTE model predicted a constricted anode arc attachment that moves on the anode ring while the 2-T model predicted a diffuse and steady arc attachment. The comparison between the predicted and measured arc voltage indicated that the 2-T prediction is closer to the actual voltage. A post-mortem observation of a new anode ring on a plasma torch operated under the same conditions confirmed the diffuse arc attachment predicted by the 2-T arc model.

Recently, cold spray (CS) technology has attracted extensive interest as an alternative to thermal spray methods to build a coating, which uses high kinetic energy solid particles to impact and adhere to the substrate. To date, numerous numerical studies have been carried out to investigate the deposition processes and associated mechanisms during multiple particle impact in CS. However, in the commonly used numerical techniques, the individual powder particles are often treated separately from one another, thus fail to properly consider the adhesion mechanisms during deposition. In this study, we propose a new numerical approach on base of peridynamics (PD), which incorporates interfacial interactions as a part of constitutive model to capture deformation, bonding and rebound of impacting particles in one unified framework. Two models are proposed to characterize the adhesive contacts: a) a long-range Lenard-Johns type potential that reproduce the mode I fracture energy by suitable calibrations, and b) a force - stretch relation of interface directly derived from the bulk materials mode I fracture simulations. The particle deformation behavior modeled by the peridynamic method compares well with the benchmark finite element method results, which indicates the applicability of the peridynamic model for CS simulation. Furthermore, it is shown that the adhesive contact models can accurately describe interfacial bonding between the powder particles and substrate.

This paper presents a novel approach for predicting cold spray coating thickness. The coating thickness distribution is a collection of single coating profiles associated with different spray angles and spraying distances. 3D geometric models of these profiles are developed and coupled with robotic trajectories and spraying parameters to simulate coating deposition. Based on the results of the simulation, the robot trajectory, operating parameters, and spray strategy can be adjusted by a feedback loop until the desired coating thickness distribution is achieved. Experimental verification shows that the method has good prediction accuracy and wide application potential.

This paper discusses the challenges of constructing mathematical models of physicochemical and heat-mass transfer processes associated with reactive heterogeneous materials used in laser additive manufacturing. The results of calculations of thermocapillary convection induced by laser heating in an aluminum melt with an admixture of nickel particles are presented. Models of interphase and chemical interactions with the formation of intermediate phases and intermetallic compounds on nickel particles added to the melt during laser alloying or cladding are proposed, which make it possible to calculate the composition of intermetallic phases in the trace of the beam after crystallization and cooling.

This study assesses the effect of injector geometry on particle injection in plasma spraying. Numerical simulations show that high particle velocities can be realized with an injector that is significantly longer than the norm. In order to verify the prediction, injectors with different diameters and lengths were used to spray Al 2 O 3 powders while measuring particle velocity at the injector outlet. Based on velocity, coating thickness, and XRD measurements, it is shown that small changes in injector geometry can have a significant influence on particle behavior without affecting phase composition. The unaltered state of the phase composition indicates that the particles did not possess enough momentum to penetrate the comparatively fast plasma jet.

This paper is the second part of a study on how Al and Ta diffusion affects the oxidation of NiCoCrAlYTa coatings. Thermodynamic and diffusion simulations of the coatings with different additions of Al and Ta predicted the development of a typical γ, γ’, ß-phase microstructure and suggested that the ß-NiAl phase was depleted as Al diffused into the substrate. The simulations also indicated that Ta could diffuse back to γ’-Ni 3 (Al,Ta) phase in the substrate with a γ’ depletion due to inward diffusion of Co and Cr from the HVOF-sprayed deposit. How this process impacts microstructure development is discussed in detail.

In suspension high-velocity oxyfuel (SHVOF) thermal spraying, the suspension is usually injected axially into the combustion chamber. Deposition of oxygen sensitive materials such as graphene can be difficult using this approach as the particles degrade with extended exposure to oxygen at high temperatures. Radial injection outside of the nozzle, however, reduces in-flight particle time thereby accommodating oxygen sensitive nanomaterials. The aim of this study is to investigate how radial injection parameters affect in-flight particle conditions during SHVOF spraying. The models used in this work are shown to accurately predict flame temperature in the combustion chamber for an Al 3 O 2 suspension. Experimental observations of the liquid jet obtained using high-speed imaging are compared to numerically predicted values. The results indicate that in-flight particle characteristics can be improved by more than 30% in SHVOF spraying by optimizing the suspension flow rate and radial injection angle.

In this work, numerical models are developed and used to simulate magneto-hydrodynamic fields inside a dc plasma torch during suspension plasma spraying and their influence on arc attachment. A Reynolds stress model is used to simulate turbulent plasma flow and a discrete phase model simulates the effects of arc fluctuation on suspension droplets in the plasma jet. Submicron yttria-stabilized zirconia particles, suspended in ethanol, are modeled as multicomponent droplets and the KHRT model is used to simulate their breakup. The results show that particles are significantly affected by plasma arc fluctuations and that fine particles near the centerline of the torch are hotter and experience better penetration into the plasma jet.

This study employs a three-dimensional simulation to investigate the cold gas dynamic manufacturing process. During the buildup of the desired object, sharp edges, stagnation points, and corners are likely to form that can influence the trajectories of the particles. This leads to dispersion and lack of particle deposition in these areas, which can eventually reduce the precision and efficiency of the build process. A cylindrical and frustum-shaped object are numerically simulated on a substrate to represent typical additively manufactured parts. Particle trajectories and impact conditions with and without these objects are compared. The results provide useful information for understanding the limitations and challenges associated with cold gas dynamic manufacturing, which can help improve the quality and precision of the process.

In this work, a fine copper layer was deposited on an aluminum nitride substrate via cold spraying. Parametric modeling was used to develop a parameter selection map that helped guide preliminary experiments to validate the model for different substrate surfaces, nozzle geometries, gas dynamics, standoff distances, and deposition angles. Further modifications were then made to include failure prediction based on particle impact, leading to the deposition of well-adhered cold-sprayed copper on a ceramic surface.

This study assesses the feasibility of cold spraying metal onto wood for commercial applications. It was found that particle adhesion and coating build-up differ significantly from the standard case of spraying metal on metal. Phenomena such as fiber rupture and buckling, pore filling, and particle anchoring required a new approach for process development and verification. First, a microscale analysis of the unique features of wood was necessary to define the deposition surface. Next, a wide range of cold spray tests were conducted to obtain metal coatings on four species of wood. To better understand the dependency of deposition efficiency on particle state conditions, a CFD models and FEA simulations were used to investigate single and multi-particle impacts on local wood structures as observed in SEM and microtomography images. A conventional pull-off test was used to collect adhesion strength data and a numerical counterpart of the test has been developed, making it possible to compare macroscopic adhesion behavior of real and virtual interfaces.