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At least 253 records · Page 14

Unit cell geometry of multiaxial preforms for structural composites

The objective of this study is to investigate the yarn geometry of multiaxial preforms. The importance of multiaxial preforms for structural composites is well recognized by the industry but, to exploit their full potential, engineering design rules must be established. This study is a step in that direction. In this work the preform geometry for knitted and braided preforms was studied by making a range of well designed samples and studying them by photo microscopy. The structural geometry of the preforms is related to the processing parameters. Based on solid modeling and B-spline methodology a software package is developed. This computer code enables real time structural representations of complex fiber architecture based on the rule of preform manufacturing. The code has the capability of zooming and section plotting. These capabilities provide a powerful means to study the effect of processing variables on the preform geometry. the code also can be extended to an auto mesh generator for downstream structural analysis using finite element method. This report is organized into six sections. In the first section the scope and background of this work is elaborated. In section two the unit cell geometries of braided and multi-axial warp knitted preforms is discussed. The theoretical frame work of yarn path modeling and solid modeling is presented in section three. The thin section microscopy carried out to observe the structural geometry of the preforms is the subject in section four. The structural geometry is related to the processing parameters in section five. Section six documents the implementation of the modeling techniques into the computer code MP-CAD. A user manual for the software is also presented here. The source codes and published papers are listed in the Appendices.

Ko, Frank↗

Tool-workpiece stick-slip conditions and their effects on torque and heat generation rate in the friction stir welding

Friction stir welding (FSW) has found increased applications in automotive and aerospace industries due to its advantages of solid-state bonding, no fusion and melting, and versatility in various working conditions and material combinations. However, the relationship among processing parameters, material properties, and bonding extent and fidelity remains largely empirical, primarily because of the lack of the mechanistic understanding of the tool-workpiece frictional behavior that affects our subsequent understanding of microstructural evolution and interface bonding formation. While the tool-workpiece stick-slip condition is believed to dictate the resulting torque and heat generation rate during the welding process, it remains rare and elusive to conduct a quantitative experimental measurement of such interfacial field. On the other hand, numerical simulations based on Computational Fluid Dynamics (CFD) rely on ad hoc assumptions of interfacial pressure and shear-stress conditions, but predictions can only be validated via the medium- and far-range temperature field which is known to be insensitive to the interfacial frictional behavior. This work first presents a comparison among two CFD-based simulation methodologies and the Coupled Eulerian Lagrangian (CEL) model in finite element method, the last of which uses the Coulomb friction so that the stick-slip is naturally developed. Based on the Hill-Bower similarity relationship in the contact analysis, an analytical model is developed here to prove why a constant stick-slip fraction will be developed in the steady state, to correlate the stick-slip fraction to processing parameters such as the tool spin rate, and further to derive dimensionless functions for torque and heat-generation-rate predictions. Pros and cons of various numerical approaches in predicting stick-slip are discussed, and our analytical model has been found to agree well with our numerical simulation and literature experimental results. These analyses provide the critical strain-rate and temperature fields that are needed for the bonding analysis in our future work.

36 MATERIALS SCIENCE↗

High-speed X-ray imaging of droplet-powder interaction in binder jet additive manufacturing

Binder jetting (BJ) is an additive manufacturing process that uses a powder feedstock in a layer wise process to print parts by selectively depositing a liquid binder into the powder bed using inkjet technology. This study presents findings from high-speed synchrotron imaging of binder droplet-interaction during the BJ printing process. A custom laboratory-scale BJ test platform was used for testing which enabled control of relevant process parameters including powder material, print geometry, spacing between droplets, powder bed density, and powder moisture content. Powder ejection was observed above the powder bed surface and powder relocation due to droplet impact was observed below the powder bed surface. Powder relocation was observed to be sensitive to powder material, powder bed density, powder bed moisture, droplet spacing, and print geometry. Increasing powder bed density was found to increase particle ejection velocity but reduce the total number of particles ejected. Process parameters that increase binder / moisture content in the powder bed were found to reduce powder ejection. The number of ejected powder particles was reduced for lower droplet spacings. Both powder ejection and powder relocation below the powder bed were reduced by treating the surface of the powder bed with a water/triethylene glycol (TEG) mixture before printing. In conclusion, results from this study help to build understanding of the physical mechanisms in the BJ printing process that may contribute to formation of defects observed in final parts.

36 MATERIALS SCIENCE↗

Microstructural Characterization of Laser Powder Bed Fusion (L-PBF) Additively Manufactured Inconel 718 for Aerospace Application

Alloy 718 (Inconel 718) is used for aerospace applications because of its excellent corrosion resistance and mechanical properties. This alloy is particularly applicable in manufacturing components subjected to high temperatures in rocket engines, aero-engines, and gas turbines. Properties for this alloy when processing on systems from similar and different Laser Powder Bed Fusion (L-PBF) machines provide subtle differences due to process parameters, feedstock, and machine configurations. A series of sixteen L-PBF AM Inconel 718 geometric feature build plates have been evaluated for microstructure using optical microscopy. This study presents the details of the microstructure analysis concerning geometry and different machine platforms. Microstructural investigations of these samples included average grain width measurement for all the X-Y and Y-Z build layers and are accompanied by process parameters and powder characterization. The present work concludes with a discussion on the importance of captured differences among builds to understand the practical limitations among AM platforms.

Additive Manufacturing↗

Non-solvents as physical blowing agents in printable silicone foams

Silicone foams were produced by dispersing an incompatible liquid phase (i.e. a non-solvent) into an uncured, liquid silicone. The formulation and processing parameters were varied to see the effect on porosity and pore morphology. Specifically, two fluorosilanes were added to stabilize the inclusion of fluorinated solvents as blowing agents. As the floruosilane content increased, the void content increased up to about 44 vol. % when the fluorosilane comprised 18 wt. % of the initial formulation. Fumed silica that was treated with a fluorinated silane was also used to try to stabilize the dispersed liquid. While the fumed silica content did not have a strong effect on the total void content, the morphology changed when silica content changed. Various fluorinated solvents with distinct chemical structures were used as the non-solvent and then removed after curing of the silicone. The interaction of the internal non-solvent phase and the silicone phase was expected to influence the porosity. These insights highlight how the manipulation of formulation and processing parameters, focusing on the inclusion of fluorosilanes and fluorinated solvents, contributes to the understanding of how incompatible liquid phases interact with silicone matrices to control porosity and pore morphology. Additionally, these interactions also influenced processability, leading to formulations that could be printed. Higher content of non-solvent inclusions could increase the yield stress and storage modulus of an uncured formulation, leading to the ability to tune intrastrand porosity while a 3D printed architecture could be modified to introduce porosity between the strands. Furthermore, in addition to fluorinated solvents, we also considered non-fluorinated solvents since these may be more industrially relevant in the future. Overall, this approach provides an alternative route to producing porous foams that can be 3D printed, which could be useful for applications like cushioning and protective gear.

physical blowing agent↗

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗

Process Recipes for Additively Printed Copper Ink Flexible Circuits using Direct Write Methods

In this paper, the process-recipes and process-performance relationships for additive-printing of copper circuits using direct-write methods have been studied. The process has been implemented on the direct write platform. Interest in the use of additive printing methods for the manufacture of micro-circuits has grown immensely in recent times. Direct write methods have been shown to have the ability to create circuits in a limited manner. However, the process recipes and the effect of process parameters on the manufactured properties are not well understood. Copper ink is a good and cost-effective alternative to silver ink but its use has lagged owing to an increased propensity for oxidation. In this paper, photonic curing has been used to sinter copper ink to make the traces conductive. The method flashes high energy light that sinter metal particles instantaneously and the temperature of the substrate remains low. The effect of the different photonic sintering profiles on the mechanical and electrical properties of the printed traces has been studied in this paper.The print process parameters also play an important role in the line width and height that has been studied to print with the desired line profile for the end application. An LC filter circuit is been printed with SMD components been attached using an electrically conductive adhesive (ECA). The manufactured flexible LC filter is been tested for its frequency sweep to compare with the commercially available LC filer with the help of the Bode plot.

Process control↗

Porous architecture and thermal properties of thermal barrier coatings deposited by suspension plasma spray

Besides the intrinsic low heat transfer capability of material, the thermal insulation property of thermal barrier coatings (TBCs) also relies on their microstructures. For better understanding the relationship between process parameters, porous architecture, and thermal properties of coatings, YSZ coatings were firstly manufactured by suspension plasma spray (SPS). Afterwards their total porosities were characterized by using the technique of X-ray transmission, the nano/submicro pores in those coatings were detected with Ultra-Small Angle X-ray Scattering (USAXS), and the thermal properties of coatings were measured using the laser flash method. The results indicated that: i) the porous architecture of SPS coatings can be tailored by adapting process parameters. ii) increasing total porosity is an effective means for reducing the heat transfer capability of SPS coatings. iii) nano/submicro pores have higher influence sensitivity on thermal properties than that of larger pores. Increasing the content of nano-submicro pores is therefore more effective for improving the thermal insulation property of SPS coatings. The potential of SPS technique for fabricating TBCs was discussed as well.

36 MATERIALS SCIENCE↗

TopTemp: Parsing Precipitate Structure from Temper Topology

Technological advances are in part enabled by the development of novel manufacturing processes that give rise to new materials or material property improvements. Development and evaluation of new manufacturing methodologies is labor-, time-, and resource-intensive expensive due to complex, poorly defined relationships between advanced manufacturing process parameters and the resulting microstructures. In this work, we present a topological representation of temper (heat-treatment) dependent material micro-structure, as captured by scanning electron microscopy, called TopTemp. We show that this topological representation is able to support temper classification of microstructures in a data limited setting, generalizes well to previously unseen samples, is robust to image perturbations, and captures domain interpretable features. The presented work outperforms conventional deep learning baselines and is a first step towards improving understanding of process parameters and resulting material properties.

Kassab, Lara↗

Friction Stir Welding

Friction stir welding (FSW) is a solid state welding process invented in 1991 at The Welding Institute in the United Kingdom. A weld is made in the FSW process by translating a rotating pin along a weld seam so as to stir the sides of the seam together. FSW avoids deleterious effects inherent in melting and promises to be an important welding process for any industries where welds of optimal quality are demanded. This article provides an introduction to the FSW process. The chief concern is the physical effect of the tool on the weld metal: how weld seam bonding takes place, what kind of weld structure is generated, potential problems, possible defects for example, and implications for process parameters and tool design. Weld properties are determined by structure, and the structure of friction stir welds is determined by the weld metal flow field in the vicinity of the weld tool. Metal flow in the vicinity of the weld tool is explained through a simple kinematic flow model that decomposes the flow field into three basic component flows: a uniform translation, a rotating solid cylinder, and a ring vortex encircling the tool. The flow components, superposed to construct the flow model, can be related to particular aspects of weld process parameters and tool design; they provide a bridge to an understanding of a complex-at-first-glance weld structure. Torques and forces are also discussed. Some simple mathematical models of structural aspects, torques, and forces are included.

Nunes, Arthur C., Jr.↗

Directed energy deposition of functionally graded V-4Cr-4Ti to Fe-9Cr transition for fusion power systems

This study proposes a graded structure via additive manufacturing for divertor and first wall blanket applications in fusion reactors. Materials were selected based on thermodynamic calculations to operate from 1100 °C at the plasma-facing level to 550 °C at the structural steel level. Conventional joining methods often lead to failures due to discrete reaction layers with significant mechanical property differences. Using laser beam-directed energy deposition (LB-DED), this study demonstrates the fabrication of a VCrTi-Gr91 steel functionally graded component through a novel process parameter optimization framework. A systematic approach included powder characterization, single-track depositions, and construction of printability maps. Near full-density specimens of each interlayer were additively manufactured, and a transition from V-based alloys to reduced activation ferritic martensitic steels was achieved. Computational material selection of interlayer alloys and thermodynamic/diffusion kinetics simulations prevented most interface incompatibilities. A brittle intermetallic formed at one interface, causing cracking, which was not predicted by current thermodynamic models. Transition alloy design approach was updated with a more recent database and a mitigation strategy has been proposed to eliminate the formation of deleterious intermetallic phases. Ultimately, LB-DED has proven effective for producing multi-material graded systems for fusion applications, with the demonstrated process parameter optimization framework applicable to various materials.

Additive manufacturing↗

Copper carbon composite wire with a uniform carbon dispersion made by friction extrusion

Copper-carbon composites are a group of materials with excellent mechanical, electrical, thermal, and tribological properties. However, bulk size copper-carbon composites made by the traditional manufacturing processes, like rolling or extrusion, fall short of reaching some of these properties predicted by theory or demonstrated only by samples at centimeter scale or smaller. The two main challenges to the successful scaling-up are: 1) to uniformly disperse carbon in the metal matrix; 2) to avoid degradation due to oxidation or reaction from overheating. In this work, we first demonstrate friction extrusion as a new method to make bulk-size void-free copper-carbon composite wires with homogenized carbon dispersion. Three different carbon varieties, graphite powder, graphene nanopowder, and carbon nanotubes, were added to the copper matrix with the concentration ranging from 0.5 wt% to 15 wt%. Special tooling, processing parameters, and procedures were developed, especially for high carbon content samples. Ten-fold reductions of both copper grain size and carbon particle size were achieved and attributed to the high shear deformation. Energy dispersive X-ray spectrometry indicates the carbon powder was refined to a sub-micron level and uniformly dispersed in the copper matrix. Compared with that of pure copper, the thermal capacity of the composite wire increases by 30 % while density reduces by 29 %.

Friction extrusion, Metal matrix composite, Graphe↗

Thermoplastic matrix composite processing model

The effects the processing parameters pressure, temperature, and time have on the quality of continuous graphite fiber reinforced thermoplastic matrix composites were quantitatively accessed by defining the extent to which intimate contact and bond formation has occurred at successive ply interfaces. Two models are presented predicting the extents to which the ply interfaces have achieved intimate contact and cohesive strength. The models are based on experimental observation of compression molded laminates and neat resin conditions, respectively. Identified as the mechanism explaining the phenomenon by which the plies bond to themselves is the theory of autohesion (or self diffusion). Theoretical predictions from the Reptation Theory between autohesive strength and contact time are used to explain the effects of the processing parameters on the observed experimental strengths. The application of a time-temperature relationship for autohesive strength predictions is evaluated. A viscoelastic compression molding model of a tow was developed to explain the phenomenon by which the prepreg ply interfaces develop intimate contact.

Dara, P. H.↗

Irreversible Multielement Diffusion and the Resulting Compositional and Processing Flexibility in the Synthesis and Densification of Lithium Aluminum Lanthanum Zirconium Oxide

Despite the broad interest in Al-doped lithium lanthanum zirconium oxide (LLZO), the wide range of reported ionic conductivities suggests that the effect of processing parameters on the resulting phase purity and bulk conductivity is not well-understood. Here, in this work, we synthesized six separate series of LLZO with variations in Al concentration, Li excess, Li addition order, Li source, densification method, and mother powder to determine the effect on the composition, phase purity, density, and bulk conductivity. We found that a wider range of compositions (6.08–7.61 mol of Li and 0.06–0.23 mol of Al) than previously reported can result in cubic phase stability and that nearly all elements (Li, Al, Zr, and La) are lost to the MgO crucible during calcination and sintering. The manner in which different elements are lost is affected by the processing parameters. We observed that Al-doped LLZO shows great compositional flexibility in stabilizing the cubic phase, offering an explanation for the range of electrochemical performance metrics reported in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction

Metal additive manufacturing (AM) offers flexibility and cost-effectiveness for printing complex parts but is limited to few alloys. Qualifying new alloys requires process parameter optimisation to produce consistent, high-quality components. High-resolution X-ray computed tomography (XCT) has not been effective for this task due to artifacts, slow scan speed, and costs. We propose a deep learning-based approach for rapid XCT acquisition and reconstruction of metal AM parts, leveraging computer-aided design models and physics-based simulations of nonlinear interactions between X-ray radiation and metals. This significantly reduces beam hardening and common XCT artifacts. We demonstrate high-throughput characterisation of over a hundred AlCe alloy components, quantifying improvements in characterisation time and quality compared to high-resolution microscopy and pycnometry. Our approach facilitates investigating the impact of process parameters and their geometry dependence in metal AM.

36 MATERIALS SCIENCE↗

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗

Mechanical Property Analysis in the Retracted Pin-Tool (RPT) Region of Friction Stir Welded (FSW) Aluminum Lithium 2195

The "Auto-Adjustable Pin Tool for Friction Stir Welding", was developed at The Marshall Space Flight Center to address process deficiencies unique to the FSW process. The auto-adjustable pin tool, also called the retractable pin-tool (R.PT) automatically withdraws the welding probe of the pin-tool into the pin-tool's shoulder. The primary function of the auto-adjustable pin-tool is to allow for keyhole closeout, necessary for circumferential welding and localized weld repair, and, automated pin-length adjustment for the welding of tapered material thickness. An overview of the RPT hardware is presented. The paper follows with studies conducted using the RPT. The RPT was used to simulate two capabilities; welding tapered material thickness and closing out the keyhole in a circumferential weld. The retracted pin-tool regions in aluminum- lithium 2195 friction stir weldments were studied through mechanical property testing and metallurgical sectioning. Correlation's can be =de between retractable pin-tool programmed parameters, process parameters, microstructure, and resulting weld quality.

Ding, R. Jeffrey↗