Papers by Keyword: Cold Spray

Abstract: This study investigates the applicability of deep learning models for automated quality classification of cold spray coatings, focusing on three deposition categories: good, degraded, and poor deposition. Three state-of-the-art convolutional architectures, ResNet-50, EfficientNet-B0, and ConvNeXt-Tiny, were evaluated across two training phases designed to assess the impact of dataset balancing, data augmentation, and higher input resolution. In the first phase, models were trained on an imbalanced dataset using only class weighting; EfficientNet-B0 achieved the best performance (ACC 80%, F1 77%), while ResNet-50 showed notable instability (ACC 60%, F1 56%). In the refined second phase, oversampling, advanced augmentation, 380×380 resolution, and early stopping led to substantial performance gains for all models. ConvNeXt-Tiny achieved the most robust and balanced results (ACC 93.3%, F1 90.3%), outperforming EfficientNet-B0 and ResNet-50 particularly in sensitivity and specificity for minority classes. Grad-CAM analysis provided qualitative insights into the decision-making process: poor samples elicited strong, spatially extended activations corresponding to defective regions, degraded samples produced more localized responses aligned with mid-scale irregularities, and good samples yielded diffuse, low-intensity activation patterns associated with surface uniformity. These interpretable attention maps validated the physical relevance of the learned features and confirmed the suitability of ConvNeXt-Tiny for reliable and explainable cold spray quality assessment.

Abstract: Aiming to minimize time, energy, and materials-consuming trial and error experimental analyses, a numerical modeling approach of vitrimer flow and cold spray deposition is proposed in this work. The characteristics of vitrimeric matrices were evaluated by elaborating data from previously performed differential scanning calorimetry and dynamic mechanical analysis. The pieces of information related to the transition temperatures and mechanical evolution after curing were exploited to feed the numerical models and to run sensitivity analyses. The flow model is based on prior evaluation of the dry reinforcement permeability at a micro- and meso-scale. The flow model has been implemented using a commercial simulative environment based on the control volumes approach. A single impacting particle was simulated in a finite element environment to analyze, in a focused way, the deposition mechanisms.The objective of this analysis is the integrated implementation of a numerical model for vitrimer flow through carbon fabric reinforcement in infusion processes and single particle deposition on vitrimer matrix composite substrates.

Abstract: Glass containers are manufactured by pressing or blowing a hot glass gob (700-1200°C) onto a metallic mould. Beside forming the glass, moulds are heat exchangers for cooling down the glass final product. To this goal, moulds are made of cast iron or copper-nickel alloy due to their thermal properties. If copper-nickel (nickel aluminium bronze) is the most efficient material, cast iron is mainly used for economic purposes. To enhance the properties of the cast iron mould, cold spray coating of a copper-nickel alloy is investigated. Optimization of the parameters process such as spraying temperature (800-1000°C), pressure (40-50bar) and gun’s travel speed (200-400mm/s) lead to a dense and well-bonded “bronze” coating on cast iron. Microstructural analysis is performed thanks to Optical Microscope, Scanning Electron Microscope, Electron BackScattered Diffraction, X-Rays Diffraction and microhardness tests. Finally, a simple thermal experiment has been designed for demonstrating thermal performances of the coating-substrate couple.

Abstract: The article deals with the influence of process parameters on the properties of the protective coating deposited by Cold Spray technology on X52 pipeline steel. Part of the work is the evaluation of the effect of heat treatment on the resulting properties of the coating. Diamalloy 1003 powder was deposited on X52 steel substrate using four different process parameters, and then the samples were heat treated at 600°C, 800°C and 1000°C. The evaluation of results included analysis of microstructure, porosity and microhardness. The results show that heat treatment has a significant effect on the properties of the coating. The lowest porosity values for all tested parameters were achieved after heat treatment of 1000°C/1 hour.

Abstract: This presentation provides an overview of the recent collaboration between CSIRO and The Boeing Company focused on developing preforms of high-temperature titanium alloys. This collaboration devised a new method for manufacturing preforms, shaped intermediates and mill products directly from titanium powder. These preforms can then undergo thermomechanical processing to produce parts requiring minimal surface finishing with the desired microstructure and mechanical properties.

Abstract: Cold spray technology is a solid-state deposition process where solid particles are accelerated to very high velocities by expanding a compressed gas through a supersonic nozzle. The particles impact a substrate located approximately 25 mm from the exit plane of the nozzle. Predicting the deformation and resultant properties helps in developing process parameters and tailoring coatings to get the desired properties. In this study, aluminum, copper, and nickel coatings were produced using a range of process parameters that produced different particle impact velocities. The Hollomon power law relationship and Johnson-Cook flow stress model were utilized to predict the hardness of cold spray coatings. Results showed there was good agreement between the predicted and measured hardness of the respective coatings. Additionally, a methodology was developed to measure deformation in the form of a flattening ratio of the deposited particles. There was good agreement between the predicted and measured flattening ratio, especially for the Al and Ni feedstock powders.

Abstract: Surface metallization is amongst the recent trends in the polymer and polymer matrix composites (PMCs) research industries to improve the electrical and thermal properties and exploit the subsequent utilization in the aerospace sector. Specifically, polymer matrix composites have been subjected to the limitations in form of high temperature exposure and substrate deterioration. The present study encompasses a new strategy in the manufacturing and metallization process. The first stage in the manufacturing of hybrid thermoplastic-thermoset composite was the hot compaction which comprised of primary preform preparation enabling the partial impregnation of the thermoplastic resin through the fabric reinforcement layer. The subsequent stage entailed the preform vacuum bagging and conducting catalyzed thermoset resin impregnation. The vacuum resin infusion step included a cocuring cycle to generate a fiber reinforced composite comprising of thermoplastic and impregnated thermoset resin with improved adhesion. Resin flow front movement was analyzed during the resin infusion process. Composite metallization was achieved through cold spray (CS). CS process parameters influence on the coating quality and characterization of laminates through microstructural analysis and results have been reported. The hybrid composite with thermoset resin through thickness and in-plane impregnation was achieved with the intact adherent thermoplastic layer after the curing cycle. In the CS metallization, the effective operative window of stand-off distances (SoD) and temperature has been determined.

Abstract: Cold spray additive manufacturing (CSAM) is a promising process for producing metallic layers on different substrates, using powders as a feedstock material. The metallic powders are deposited through pressured gas that reaches supersonic velocities. Due to the low heat input required, as the powders remain in solid-state, this technology is particularly suitable to coat thermo-sensitive materials such as composites. Moreover, the absence of melting allows design freedom, allowing to build complex structures on the substrates, layer by layer. In this scenario, machine learning techniques can be crucial to improve the quality and understanding of this manufacturing process. The aim of this work is to predict the deformation and penetration of a particle upon impact using machine learning techniques in order to assess the properties of the coating. A univariate linear regression method was chosen to verify the feasibility of Theory Guided Machine Learning (TGML) techniques to predict the characteristics of the coating. The training dataset was obtained from both experimental data and computational data. It was confirmed that TGML could be a good route to pursue in order to optimize this process.

Abstract: Cold spray (CS) is a low-temperature process that can be used for the metallization of temperature-sensitive materials, such as polymers or polymer matrix composites, so coupling the lightweight of polymers with the wear resistance, physical properties and hardness of metals. The study of the cold spray of metal particles applied to polymers is still in its early stage and the deposition mechanisms underlying the process are not thoroughly understood yet. Moreover, numerical studies of cold spray of metal-to-polymer are almost completely absent in literature. Therefore, aiming to fulfill this gap of knowledge, the scope of this work is to develop a numerical FE model capable of predicting the impact and the adhesion of a micron size metallic particle onto a polymeric substrate. The results from the model were compared with the experimental outcomes found in literature to establish the effectiveness of the model that was used as a powerful tool to better understand the bonding mechanisms and all the related phenomena ruling the CS process of metal-to-polymer.

Abstract: The article deals with metallographic evaluation of Ni-Cr Cold Spray layers, which were deposited on GOST 22K steel for four layer variants. The sprayed Ni-Cr layer should primarily serve to protect the heterogeneous weld in the nuclear power industry. Metallographic evaluation of the applied layer was focused on the evaluation of spray fillability in the notch.