Function Of Process Parameters Research Articles

A physics-based modeling framework to assess the cost scaling of additive manufacturing, with application to laser powder bed fusion

Purpose This study presents a framework to estimate throughput and cost of additive manufacturing (AM) as related to process parameters, material thermodynamic properties and machine specifications. Taking a 3D model of the part design as input, the model uses a parametrization of the rate-limiting physics of the AM build process – herein focusing on laser powder bed fusion (LPBF) and scaling of LPBF melt pool geometry – to estimate part- and material-specific build time. From this estimate, per-part cost is calculated using a quantity-dependent activity-based production model. Design/methodology/approach Analysis tools that assess how design variables and process parameters influence production cost increase our understanding of the economics of AM, thereby supporting its practical adoption. To this aim, our framework produces a representative scaling among process parameters, build rate and production cost. Findings For exemplary alloys and LPBF system specifications, predictions reveal the underlying tradeoff between production cost and machine capability, and look beyond the capability of currently commercially available equipment. As a proxy for build quality, the number of times each point in the build is re-melted is derived analytically as a function of process parameters, showcasing the tradeoff between print quality due to increased melting cycles, and throughput. Originality/value Typical cost models for AM only assess single operating points and are not coupled to models of the representative rate-limiting process physics. The present analysis of LPBF elucidates this important coupling, revealing tradeoffs between equipment capability and production cost, and looking beyond the limits of current commercially available equipment.

Predicting particle orientation: Is an accurate flow field more important than the actual orientation model?

Analytical orientation prediction models (OPMs) are widely applied to efficiently predict the orientation of particles in suspensions or pastes. One application of these prediction models are extrusion processes where the model is used to identify combination of process and paste parameters that yield anisotropic orientation within the extruded filament. The accuracy of these predictions mainly depends on two elements that are the correct choice of the orientation model itself and the rheology model. The rheology of a paste is commonly modeled with the help of the Herschel Bulkley (HB) rheology model. The optimal OPM is still topic of today’s research. Which of the two elements, however, has a stronger influence on the orientation has not been addressed, yet. We make use of a wide range of HB parameters reported in literature with a particular focus on data that is reported for varying paste compositions. Based on this data, we use the HB model to predict the velocity and shear rate profile within a pipe and perform orientation predictions with the help of the models by Jeffery and Folgar and Tucker (FT). These predictions are used to estimate the sensitivity of the final orientation on the HB parameters and on the OPM. For our study, we assume that the paste can be described by the standard Herschel Bulkley rheology model. We assume no-slip boundary conditions and no influence of the particle orientation on the rheology. Second, we assume that the initial particle orientation before entering the pipe is random. Our results suggest that capturing the rheology model correctly is generally more important than capturing the OPM correctly. This applies in particular when densely filled states are approached. We also provide universal relations for predicting the degree of particle alignment and the mean flow velocity as functions of process parameters and material properties. • A suitable rheology model is found to be more important than the actual orientation prediction model in terms of particle orientation. • Normalized diagrams enable quick estimations of the evolution of particle orientation based on process parameters and paste properties. • The derived methodology is applied to a large set of published rheology data.

Deformation based additive manufacturing of a metastable high entropy alloy via Additive friction stir deposition

Additive friction stir deposition (AFSD) is a novel solid-state additive manufacturing process which offers unique capability of producing 3-D parts with no solidification related defects and having homogeneous, equiaxed microstructure. However, to fulfill the full potential of the process for structural applications, AFSD needs intense process optimization for a wide range of alloys with excellent mechanical properties. The present study explored AFSD of a novel metastable high entropy alloy (HEA), CS-HEA (Fe 40 Mn 20 Co 20 Cr 15 Si 5 (at.%)), enabled with transformation and twinning induced plasticity during deformation. Intense shear deformation at elevated temperature and strain rate during AFSD led to the operation of restoration mechanisms such as recovery, recrystallization, and grain growth which resulted in refined grains with excellent strength and work hardenability. The average grain size for as-deposited CS-HEA is 3.0 ± 0.5 µm, and the average tensile yield strength of as-deposited CS-HEA is 450 ± 20 MPa. The microstructural variation and mechanical response of the alloy as a function of process parameters were correlated to the AFSD process variables, phase transformation, and recrystallization kinetics. Further, the interaction between recrystallization kinetics and transformation kinetics on microstructural evolution of the material was explored. Additionally, the microstructure and stacking fault energy of the alloy were used to predict the mechanical response of the deposited material using a five parameter work hardening model. • A Metastable high entropy alloy, CS-HEA is additively manufactured using a deformation based additive manufacturing process – additive friction stir deposition. • Operation of discontinuous dynamic recrystallization during AFSD deposition of CS-HEA led to formation of refined equiaxed grain structure in as deposited state. • Variation in AFSD processing parameters affected the microstructure of the alloy, higher heat input resulted in larger grain size with higher fraction of high temperature γ phase. • γ→ε transformation and twinning in ε phase provided excellent strength-ductility combination in as deposited state.

Electrical Discharge Coating a Potential Surface Engineering Technique: A State of the Art

Electrical discharge coating (EDC) process is used to deposit material on workpiece surface from sacrificial or green compact tool electrode in an electrical discharge machine. The paper presents the mechanism of EDC using green compact electrode and powder mixed dielectric methods. The tool electrode material, electrode size, process parameters, and type of dielectrics can directly affect the surface integrity of workpiece. Here, a process map of EDC as a function of process parameters, its classification, advantages, and applications for a wide range of engineering materials offers a proper template for the evaluation of coating phenomena. This study shows that EDC is an economic process as compared to other costlier techniques. Additionally, the effect of various EDM and EDC parameters on surface integrity and tribological behavior of deposited coatings is studied with their pros and cons. Finally, the current research trends of EDC and its challenges are elaborated.

An experimental investigation and neuro-fuzzy modeling to ascertain metal deposition parameters for the wire arc additive manufacturing of Incoloy 825

Additive manufacturing is critical to repair, rebuild, and rapidly manufacture major components in today's manufacturing environment. Wire arc additive manufacturing technique using metal inert gas welding, which is a better way to produce large-scale parts at a subsidized cost was experimented on Incoloy 825 due to its many industrial applications in the construction of large structures. As bead deposition is vital for wire arc additive manufacturing, single bead depositions were performed. Metrological features of all deposited beads are evaluated using the CNC Video Measuring System by capturing the macrostructures. The effects of input parameters on bead geometry are statistically analyzed, and regression models are derived to forecast bead geometry. An adaptive Neural Fuzzy Inference System was implemented to predict geometrical characteristics, and the results were compared with experimental results. Subtractive clustering fuzzy inference model obtained the lowest percentage error difference in predicting deposited bead geometry as a function of process parameters. Further, the multi-objective optimization technique determined optimal input parameters for the best bead geometry. Finally, using identified optimum parameters, wire arc additive manufacturing of a single-pass multi-layer wall of Incoloy 825 was successfully constructed for validation, which revealed that the microstructure of the built structure was of appreciable quality without cracks and porosity.

Effects of processing conditions on the solidification and heat-affected zone of 309L stainless steel claddings on carbon steel using wire-directed energy deposition

Directed energy deposition and laser cladding technologies are suitable advanced manufacturing techniques for applying corrosion-resistant claddings to large carbon steel components. In this work, we clad 309L stainless steel wire onto carbon steel substrates and examine the effects of processing parameters (laser power and travel speed) on metallurgical bonding and microstructures. Wire dripping defects correlate to excessive heat input, while cracking, stubbing and delamination defects are linked with insufficient heat input. Spectroscopic scans of the weld microstructure show the amount of base metal mixing in the weld is a function of processing parameters and the number of cladding layers. In the first cladding layer, the weld metal is diluted with base metal ranging from 1.7 to 45.6 %; this amount dramatically decreases in the second layer (0–8.6 %), promoting primary ferrite solidification, which decreases solidification cracking susceptibility. Martensite forms in the heat-affected zone from the high cooling rates associated with laser processing. Subsequent laser passes temper the martensite and carbon diffuses from the substrate into the first cladding layer. Cladding two or more layers is beneficial for mitigating defects, lowering dilution, and producing a highly alloyed surface suitable for corrosion protection.

Mathematical modelling for prediction of surface roughness in Pneumatically Configurable Polishing process

Pneumatically configurable polishing is a superfinishing process which can generate nano-meter level surface finish on workpiece surfaces. It utilizes pneumatic pressure for controlled inflation of a cup shaped elastomeric membrane which has a stretchable polishing film fixed to its bottom surface. A slurry containing abrasive particles, thoroughly mixed in a carrier medium is applied on the workpiece surface. When the inflated membrane is brought in contact with a rigid surface, it adheres to the profile of the workpiece being polished, which ensures the entrapment of abrasive particles between the membrane and the surface to be polished. The abrasive slurry is replenished at a fixed interval during the process. This flexibility of the membranous tool enables it to finish complex 3D surface profiles. The final surface characteristics generated are a function of process parameters as well as material properties. This study proposes a mathematical model for the prediction of surface roughness as a function of workpiece properties such as hardness, tool characteristics, and significant process parameters such as working gap, applied pneumatic pressure, spindle speed, concentration of abrasive slurry, abrasive mesh size and dwell time. The model uses Hertz contact theory of elastic surfaces for modelling of contact pressure between the inflated membranous tool and the workpiece surface. A single abrasive particle is modelled for its influence on the workpiece surface as a function of its radial distance from the tool centre. This model is used to estimate the combined effect of all the active abrasive particles, participating in the finishing process. The final penetration depth obtained at different radial coordinates is used to estimate the theoretical surface roughness on the workpiece surface. The normal, shear and friction forces acting on a single abrasive grain have been modelled to determine the process capability during material removal. The model is finally validated by performing experiments under different conditions of process parameters. The experimental findings and theoretical results are found to be within an error range of −16.5%–11.8%. • Control of polishing forces using pneumatic pressure. • Modelling microscopic material removal by abrasive at each sampling point in contact zone. • Spot size prediction using the theory of large deflection of a thin plate. • Friction and shear force on a tetrahedral diamond abrasive particle.

Material characterisation of additive manufacturing titanium alloy (Titanium 6Al-4V) for quality control and properties evaluations

ABSTRACT Current additive manufacturing (AM) technologies use various raw materials such as plastics and metals to fabricate parts. Moreover, the increasing use of metallic parts makes AM applicable to commercial use such as aeronautical, and medical field. For this reason, manufacturing process quality evaluation becomes essential to achieve higher quality products. Quality control and material property assessment for AM parts is a major challenge due to the complexity of the materials and geometry of the parts. Non-Destructive Testing (NDT) is being proposed as a cost-effective way to evaluate the quality of the product. For this reason, the nanoindentation, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) techniques are being used as useful forms of NDT techniques to assess the quality and material characteristics in metal AM samples. The material properties of additively manufactured Titanium 6Al-4 V alloy are studied to verify the in-situ process monitoring published results at different manufacturing process conditions. The comparison of material properties of three different process conditions made by direct energy deposition (DED) metal additive manufacturing is discussed to understand the variation. The results show that the characteristics of materials are a function of process parameters and have a strong correlation to the expected in-situ monitoring indicators.

First, do not degrade – Dual Beam Laser Sintering of polymers

In this paper, the method of Dual Beam Laser Sintering of polymers (DBLS) is presented for the first time. In this method, rather than heating the entire volume of the polymer throughout the entire process, a second, additional laser is used to heat the material selectively in terms of volume and time. The principle of operation and the design of the prototype are presented. Using the developed system, an experiment has been carried out in which samples of technical polylactide (PLA) powder were sintered for selected process parameters. This experiment confirms that the proposed method is fully functional and proves that sintering can be controlled in a wide range. A preliminary comparison of the changes in the physicochemical properties of the obtained samples compared to those sintered by standard polymer Laser Sintering (pLS) was carried out using Gel Permeation Chromatography, Fourier Transform Infrared Reflectance and Differential Scanning Calorimetry. Our experiment shows that the method has a potential to limit the thermal degradation of sensitive polymer materials. • The design and principle of operation of the Dual Beam LS station were presented. • The change in PLA properties as a function of process parameters was examined. • The potential of the method to limit the thermal degradation of polymers was shown. • Lower degradation of the post-process powder by the DBLS method was demonstrated.

Molecular Dynamics Modeling of Interfacial Interactions between Flattened Carbon Nanotubes and Amorphous Carbon: Implications for Ultra-Lightweight Composites.

Flattened carbon nanotubes (flCNTs) naturally form in many carbon nanotube-based materials and can exhibit mechanical properties similar to round carbon nanotubes but with tighter packing and alignment. To facilitate the design, fabrication, and testing of flCNT-based composites for aerospace structures, computational modeling can be used to efficiently and accurately predict their performance as a function of processing parameters, such as reinforcement/matrix cross-linking. In this study, molecular dynamics modeling is used to predict the load transfer characteristics of the interface region between the flat region of flCNTs (i.e., bi-layer graphene) and amorphous carbon (AC) with various levels and locations of covalent bond cross-linking and AC mass density. The results of this study show that increasing the mass density of AC at the interface improves the load transfer capability of the interface. However, a much larger improvement is observed when cross-linking is added both to the flCNT–AC interface and between the flCNT sheets. With both types of cross-linking, substantial improvements in interfacial shear strength, transverse tension strength, and transverse tension toughness are predicted. The results of this study are important for optimizing the processing of flCNT/AC composites for demanding engineering applications.

Microstructure and mechanical properties of Ti6Al4V alloys fabricated by additive friction stir deposition

The additive friction stir deposition (AFSD) of Ti6Al4V alloy was successfully performed over a wide processing window. The microstructures were examined based on the high atemperature β grain size, grain boundary α formation and the propensity of variant selection as a function of process parameters. The analysis revealed that a reduction in deposition temperature could be achieved by the change in AFSD parameters, resulting in major reduction of prior β grain size and refinement of as-deposited α phase structure. This resulted in significant improvements of ductility and strength in the as-deposited state with ductility values up to ∼20% and maximum yield and ultimate tensile strengths values of 1010 MPa and 1233 MPa, respectively.

A simple polyacrylamide gel route for the synthesis of MgAl2O4 nanoparticles with different metal sources as an efficient adsorbent: Neural network algorithm simulation, equilibrium, kinetics and thermodynamic studies

• A polyacrylamide gel method have been used to synthesize the MgAl 2 O 4 nanoparticles. • An artificial neural network model of phase purity of MgAl 2 O 4 was constructed. • The microstructure and adsorption performance of MgAl 2 O 4 nanoparticles were compared. • An adsorption mechanism of MgAl 2 O 4 nanoparticles was proposed. The MgAl 2 O 4 nanoparticles with different particle sizes prepared by a polyacrylamide gel method with different metal salts as raw materials which was used to study its efficiency as an adsorbent for removal of Congo red, acid orange 7 and acid fuchsin from wastewater. It was difficult to obtain pure MgAl 2 O 4 nanoparticles with basic magnesium carbonate or aluminum acetate coupled with other metal salts. Based on the molecular weight, coordination number, ion radius and the number of water of crystallization for the metal salt and the phase purity of the target product, a neural network prediction model was established to predict the effect of synthesis parameters on the phase purity of MgAl 2 O 4 . The microstructure characterization confirmed that the minimum particle size of MgAl 2 O 4 nanoparticles prepared with aluminum nitrate and magnesium sulfate as metal salts was about 22 nm, and the maximum particle size of MgAl 2 O 4 nanoparticles prepared with aluminum nitrate and magnesium chloride as metal salts was about 50 nm. Adsorption experiments of MgAl 2 O 4 nanoparticles were performed as a function of process parameters: various dyes including Congo red, acid orange 7 and acid fuchsin, adsorption time, particles size, initial dye concentration, initial adsorbent concentration, pH value and reaction temperature. The thermodynamic studies showed that the adsorption of MgAl 2 O 4 nanoparticles for removal of Congo red from wastewater is an exothermic and spontaneous process. The maximum adsorption capacity of 89.043 mg/g for the MgAl 2 O 4 nanoparticles was found at 1 g/L of initial adsorbent concentration, 100 mg/L of initial dye concentration, 6.9 of pH, and 299.8 K of temperature for removal of Congo red from wastewater. The adsorption of Congo red, acid orange 7 and acid fuchsin can be assigned to the synergistic effect of electrostatic interaction, pore filling and ion exchange. This present work provides a technical reference for the synthesis of other metal oxide nanoparticles using metal salts with different acid groups.

Towards the additive manufacturing of Ni-Mn-Ga complex devices with magnetic field induced strain

Laser powder bed fusion ( L -PBF) is used to produce foam-like Ni-Mn-Ga with tailored microscale and mesoscale features. Ni50-Mn28.2-Ga21.8 (at%) powder was gas atomised and processed in an L -PBF system with a range of energy density from 26.24 and 44.90 J/mm 3 . We characterised microscale and mesoscale properties, such as the chemical composition, crystal structure, magnetisation measurements, density, and porosity measurements as a function of process parameters, in a systematic design of experiment. Preliminary research on macroscale properties included tensile testing and magnetic field induced strain (MFIS) measurements. Results show how controlling process parameters allows tailoring the Ni-Mn-Ga polycrystalline microstructure. Hence, obtaining twinned martensitic structures with a predominant orientation going across the visible grain boundaries. All the processed samples showed a 56 Am 2 /kg magnetisation level, close to Ni-Mn-Ga 10 M single crystals. Mesoscale results show a distinctive porosity pattern that is tailored by the process parameters and the laser scanning strategy. In contrast, macroscale mechanical tensile test results show a brittle fracture of Ni-Mn-Ga due to the high porosity with yield stress 2–3 times higher than shown in single crystals. In sum, we built geometrically complex demonstrators with (i) microscale twinned martensitic structures with a predominant orientation going across the visible grain boundaries and (ii) mesoscale tailored periodic porosity patterns created by modifying power, scanning speed, and scanning strategy systematically. L -PBF demonstrates great potential to produce foam-like polycrystalline Ni-Mn-Ga, reducing grain boundary constraints and thus the magnetic force needed for MFIS.

Monitoring Shearing-Plowing Transitions in Micro-Milling Using Fluctuations in Cutting Forces

Abstract In micromilling, understanding transitions between the desired shearing-dominant to the undesired plowing-dominant cutting mechanism could help obtain high quality microfeatures. This work investigates the transitions in cutting mechanisms in micromilling using fluctuations in cutting force signals, characterized by using a fluctuation parameter. A new analytical model correlating fluctuation in force signals to the transitions in cutting mechanism has been developed. Two types of slot milling experiments were performed to understand the transitions in cutting mechanisms, as a function of processing parameters, and over the entire life of micro-endmills. The proposed model was found to agree with experimental values of forces within 15% error. The limiting value of the fluctuation parameter has been estimated as 0.01, which corresponds to a limiting feed of 1 μm/tooth. Feed per tooth and cutting edge radius are the important parameters that affect transitions in cutting mechanisms. The cutting mechanism changes from shearing to plowing and vice-versa over the entire life of the tool. Shearing-dominant mechanism prevailed in the first region due to the sharper cutting edges with radius less than 9 μm. Though plowing-dominant cutting mechanism prevails in the remaining two regions, the mechanism comes closer to shearing-dominant near the end of tool life. This is primarily because of the generation of localized sharpness on tool cutting edges due to chipping. Furthermore, it was evident that cutting mechanism changes from shearing to plowing due to wear, when surface roughness increases above 400 nm Ra.

Surface characteristics and in-vitro studies of TiO2 coatings by plasma electrolytic oxidation in potassium-phosphate electrolyte

Plasma electrolytic oxidation (PEO) was used to produce titanium oxide (TiO2) coatings on Ti surface in potassium - phosphate electrolyte. The morphology, wettability, phase, and chemical compositions were studied as a function of processing parameters. The bioactivity of the coating was assessed by the ability to form biomimetic apatite in-vitro using cell culture medium. In-vitro studies using human mesenchymal stem cells were also conducted to evaluate cells' proliferation and viability of the treated Ti. The results revealed that the produced TiO2 coatings comprised pore features with the pore size increasing with applied current density and treatment duration due to high energy discharge channels at higher potential. The PEO treated Ti exhibited superhydrophilic characteristics with a contact angle <1°. The findings indicated that the large actual surface area produced by the PEO treatment and the presence of negatively charge are the key factors for the superhydrophilic behavior. The in-vitro studies revealed that the PEO treated groups had higher amount of biomimetic apatite formation compared to the as-polished Ti. The PEO treatment significantly enhanced the cells' adhesion and growth after 24 and 72 hrs compared to the untreated Ti. A significant difference in the bioactivity was not observed between anatase and rutile.

Influence of geometry on columnar to equiaxed transition during electron beam powder bed fusion of IN718

Correlation between spot-melt scan parameters (linear spot-density aka areal energy density), build geometry, and solidification microstructure evolution (columnar vs equiaxed) in a powder bed fusion technology is investigated. It is shown that to maintain the equiaxed solidification microstructure evolution in electron beam powder bed additive manufacturing (AM), the areal energy density per layer needs to be scaled with respect to the 2D cross-sectional area of the layer being melted. Samples with two different cross-sectional areas (40 × 40 mm and 20 × 20 mm) have been fabricated with varying areal energy densities. For a given square cross-section (20 × 20 mm), increasing the areal energy density (4.8 MJ/sq.m to 14.7 MJ/sq.m) transitioned the solidification microstructure from columnar to equiaxed. The observed microstructure data (Electron Back Scattered Diffraction - EBSD) is quantified by calculating the principal component (PC) score using a spatial statistics methodology. The sample with equiaxed grains is found to have a low PC score while the sample with columnar grain had a high PC score. A semi-analytical model is used to simulate the heat transfer and the local solidification conditions as a function of processing parameters (linear spot-density). The result from the heat transfer model is correlated with previously quantified microstructure data. Space-Time analysis of the melt pattern is done and correlated with the observed microstructure. In addition, from the findings, appropriate parameters have been used to additively manufacture a turbine blade with site-specific or hybrid solidification microstructure (traditional fabrication possible via a patented method of localized cold working and heat treatment).

Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach

Abstract Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often the case that a suite of hierarchically linked (or coupled) simulation models is needed to achieve the above tasks, as the entirety of the complex physical phenomena relevant to the understanding of process-structure-property-performance relationships in the context of AM precludes the use of a single simulation framework. In this study using a Bayesian network approach, we address the important problem of conducting uncertainty quantification (UQ) analysis for multiple hierarchical models to establish process-microstructure relationships in laser powder bed fusion (LPBF) AM. More significantly, we present the framework to calibrate and analyze simulation models that have experimentally unmeasurable variables, which are quantities of interest predicted by an upstream model and deemed necessary for the downstream model in the chain. We validate the framework using a case study on predicting the microstructure of a binary nickel-niobium alloy processed using LPBF as a function of processing parameters. Our framework is shown to be able to predict segregation of niobium with up to 94.3% prediction accuracy on test data.

Cold spray deformation and deposition of blended feedstock powders not necessarily obey the rule of mixture

Cold spray additive manufacturing has the potential to be used in repair and manufacturing of a wide variety of parts and coatings including composite coatings . Understanding materials' fundamental behaviour during deposition is essential for the process development which was not addressed enough for mixed powders. One objective of this study is to explore the process-structure relation of mixed Ni-Ti powders in cold spray to provide a methodology to achieve a coating with the composition of interest. Single/multi-particle impact experiments and FEM modelling were employed to investigate the particle deformation and microstructure evolution using SEM, EBSD and EDS. The sprays of mixed powders were performed using a wide process parameter window and the deposition characteristics and composition variation as a function of process parameters were explored. The experiments and modelling showed that splats in dissimilar multi-particle impacts experience more deformation than those of similar materials, which in microstructural scale translates to variation of deformation mechanism from single-component coatings. This results in higher degree of grain refinement, specifically for Ti in the composite coating with an average grain size of 500 nm. Experiments showed that the DE of mixed powder deviates from the rule of mixture, which means the critical velocity of Ni-Ti powder is different from the single-component Ni and Ti coatings due to material interactions. Findings showed there is a process parameter criteria for which relative DEs of components, and thereby composition of composite coatings, remain at almost constant ratios. η (impact velocity/critical velocity ratio) is used as a measure to predict qualitative composition variation as a function of spraying parameters and powder characteristics. • Process-structure relation of cold sprayed mixed powders is explored experimentally & numerically. • Process criteria are proposed to predict composition variation using V and V cr . • A methodology is proposed to achieve a composite with the composition of interest. • Materials interaction & intrinsic materials properties result in change of V cr & DE deviation from mixing rule.

A comprehensive analytical-computational model of laser directed energy deposition to predict deposition geometry and integrity for sustainable repair

• An integrated framework developed to model the key physical aspects of DED: laser-powder interaction; melt pool formation; powder catchment and deposition geometry; dilution and residual stresses. • A novel analytical formulation for gravity-dependent powder flux exiting a co-axial nozzle. • Developed a comprehensive analytical-computational model to predict deposition geometry, contact angle, dilution, and residual stress. • Identified physics-based metrics for favorable depositions and developed data-driven process maps of favorable parameter space. Laser directed energy deposition (DED) is an innovative additive manufacturing technology with tremendous potential for remanufacturing and repairing critical components. For sustainable repair, it is necessary to control the deposition geometry and integrity in terms of residual stresses and dilution. Obtuse contact angles and inadequate dilution can lead to inter-track porosity and cracks at the edge of the deposition-substrate interface. In addition, the fatigue life of the restored part is compromised if tensile residual stresses are induced in the deposited layer. A comprehensive modeling approach presented in this paper integrates analytical formulations for the laser-powder interaction and the powder entrapment in the melt pool, with the finite element models for determining the melt pool characteristics and the residual stresses. This model captures the physics of the key phenomena in DED, namely, power attenuation due to laser-particle interaction, melt-pool formation, powder catchment in the melt pool, and the residual stress evolution due to differential thermal contraction and metallurgical transformations. The model predictions have been experimentally validated for residual stresses, dilutions, catchment efficiencies, powder flux, and deposition geometries for crucible particle metallurgy (CPM 9V) steel powder on H13 tool steel. CPM 9V is a preferred material for repairing H-13 molds. Extensive simulations have been carried out using the comprehensive analytical-computational model to develop data-driven expressions for deposition geometry, normalized dilution, and residual stress as a function of process parameters (laser power, scan speed, and powder feed rate). For identifying the preferred deposition regime, these relations are employed to bifurcate the entire operating space into obtuse and acute contact angle, insufficient and sufficient dilution, tensile and compressive residual stress. Higher P v / m ˙ values yield depositions with the desired acute contact angles and higher specific energies ( P / v d ) induce favorable compressive longitudinal residual stress in the depositions.

An Efficient Thermal Cure Profile for Thick Parts Made by Reactive Processing of Acrylic Thermoplastic Composites

The process of curing of large thick composite parts needs attention regarding the formation of residual stresses. Similarly, novel reactive thermoplastics need investigating to produce an efficient thermal cure profile that decreases the risk of warpage and residual stress. In this work, the polymerization kinetics of the Elium resin system is investigated by differential scanning calorimetry (DSC) tests, the analysis of thermo-grams, and the parameters of Kamal and Sourour’s semi-empirical model. A numerical model based on finite elements was set up to reproduce the temperature fields during part consolidation. Several processing conditions were investigated (dwell temperature, environment, heat exchange) in order to predict the thermal gradient within the part. The optimal cure profile was identified as a function of process parameters with the aim of minimizing the thermal gradient within the composite element. The analysis revealed that, for the reactive thermoplastic Elium, the consolidation in facilities with high thermal exchange may increase the risk of residual stresses within the parts, erasing the advantage of short cure cycles.