Integrating Materials and Manufacturing Innovation

In this paper, phenomenological relationships are presented that permit the prediction of the plastic regime of stress–strain curves using a limited number of parameters. These relationships were obtained from both conventional (wrought + β annealed) and additively manufactured (i.e., “3D printed”) Ti-6Al-4V. Three different methods of additive manufacturing have been exploited to produce the materials, including large-volume electron beam additive manufacturing, large-volume laser hot wire additive manufacturing, and small-volume selective laser melting. The general fundamental expressions are independent not only of the additive manufacturing process, but also of a wide variety of post-deposition heat treatments, however the coefficients are specific to material states. Thus, this work demonstrates that it is possible to predict not only the ultimate tensile strength, but also the full true stress, true strain curves, if certain parameters of the material are known. In general, the prediction of ultimate tensile strength are within 5% of the experimentally measured values across all additive manufacturing variants and subsequent heat treatments. The absolute values of ultimate tensile strength range from ~ 910 MPa to ~ 1170 MPa for the single alloy Ti-6Al-4V. Data representing 113 explicit samples are included in this work.

Integrated Computational Materials Engineering (ICME)-based tools and techniques have been identified as the best path forward for distortion mitigation in thin-plate steel construction at shipyards. ICME tools require temperature-dependent material properties—including specific heat, thermal conductivity, coefficient of thermal expansion, elastic modulus, yield strength, flow stress, and microstructural evolution—to achieve accurate computational results for distortion and residual stress. However, the required temperature-dependent material property databases of the U.S. Navy-relevant steels are not available in the literature. Therefore, a comprehensive testing plan for some of the most common marine steels used in the construction of the U.S. Naval vessels was completed. This testing plan included DH36, HSLA-65, HSLA-80, HSLA-100, HY-80, and HY-100 steel with a nominal thickness of 4.76 mm (3/16-in.). This report is the fifth part of a seven-part series detailing the pedigreed steel data. The first six reports will report the material properties for each of the individual steel grades, whereas the final report will compare and contrast the measured steel properties across all six steels. This report will focus specifically on the data associated with HY-80 steel.

An integrated computational materials engineering (ICME)-based workflow was adopted for the study of microstructure and property evolution at the heat-affected zone (HAZ) of gas metal arc-welded DP980 steel. The macroscale simulation of the welding process was performed with finite element method (FEM) implemented in Simufact Welding® software and was experimentally validated. The time–temperature profile at HAZ obtained from FEM simulation was physically simulated using Gleeble 3800® thermo-mechanical simulator with a dilatometer attachment. The resulting phase transformations and microstructure were studied experimentally. The austenite-to-ferrite and austenite-to-bainite transformations during cooling at HAZ were simulated using the Johnson–Mehl–Avrami–Kolmogorov (JMAK) equation implemented in JMatPro® software and with phase-field modeling implemented in Micress® software. The phase fractions and the phase transformation kinetics simulated by phase-field method agreed well with experiments. A single scaling factor introduced in JMatPro® software minimized the deviation between calculations and experiments. Asymptotic homogenization implemented in Homat® software was used to calculate the effective macroscale thermo-elastic properties from the phase-field simulated microstructure. FEM-based virtual uniaxial tensile test with Abaqus® software was used to calculate the effective macroscale flow curves from the phase-field simulated microstructure. The flow curve from virtual test simulation showed good agreement with the flow curve obtained with tensile test in Gleeble®. An ICME-based vertical integration workflow in two stages is proposed. With this ICME workflow, effective properties at the macroscale could be obtained by taking microstructure morphology and orientation into consideration.

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing-internal structure-property-performance envelope, along with the capturing and storing of the associated material and model information across its life cycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, materials information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to identify best practices associated with these user demands and key principles for the development of a robust materials information management system will be discussed. The goals are to enable the connections at various length scales to be made between experimental data and corresponding multiscale modeling toolsets and, ultimately, to enable ICME to become a reality. In particular, the NASA Glenn Research Center efforts towards establishing such a database (for combining material and model pedigree) associated with both monolithic and composite materials as well as a multiscale, micromechanics-based analysis toolset for such materials will be discussed.

Large and highly textured regions, referred to as macrozones or microtextured regions, with sizes up to several orders of magnitude larger than those of the individual grains, are found in dual-phase titanium alloys as a consequence of the manufacturing process route. These macrozones have been shown to play a critical role in the failure of titanium alloys, specifically being linked to crack initiation and propagation during cyclic loading. Modeling microstructures containing macrozones using continuum-level formulations to describe the elastic–plastic deformation at the grain scale, i.e., crystal plasticity, poses computational challenges due to the large size of the macrozones, which in turn prevents the use of modeling approaches to understand their deformation behavior. In this work, a crystal plasticity-based modeling approach is implemented to model macrozones in Ti–6Al–4V. Further, to overcome the large computational expense associated with modeling microstructures containing macrozones, a modeling strategy is introduced based on a crystal plasticity description for the macrozone with a reduced-order model for the surrounding aggregate combining anisotropic elasticity and J2 plasticity, based on crystal plasticity-based training data. This modeling approach provides a grain-level description of deformation within macrozones using elastic–plastic continuum simulations, which has often been overlooked. Finally, the reduced-order model is used to investigate the strain localization within the microstructure and the effect of varying the misorientation tolerance on the localization of plastic strain within the macrozones.

The strength of a Ni-base superalloy depends strongly on its microstructure consisting of cuboidal $${\gamma }^{^{\prime}}$$ precipitates surrounded by narrow channels of $$\gamma $$ matrix. According to the theory of Orowan, a moving dislocation has to crimp through the minimal inter-precipitate spacing to admit the plastic deformation. We present a novel approach to evaluate the matrix channel width distribution of a matrix/ $${\gamma }^{^{\prime}}$$ microstructure in binary representation. Our method relies on precise determination of the matrix/precipitate interfaces and requires no additional user input. For each matrix channel between two neighboring precipitates, we identify the minimal interface to interface distance vector with its length being the channel width. The performance of this method is demonstrated on the example of the commercial alloy CSMX-4. We show that, in contrast to conventional line sectioning approaches, the approach consistently handles experimental 2D micrographs and 3D phase-field simulation data. The identified distance vectors correlate to the underlying crystal symmetry independent of the image orientation. The obtained channel width distributions compare well between the 2D and 3D data. This is in terms of similar median and $$\sigma $$ of a log-normal distribution. The presented method overcomes limitations of the conventional line slicing approaches and provides a versatile tool for automated microstructure characterization.

The rapid development of robust, reliable, and reduced-order process-structure evolution linkages that take into account hierarchical structure are essential to expedite the development and manufacturing of new materials. Towards this end, this paper lays a theoretical framework that injects the established time series analysis into the recently developed materials knowledge systems (MKS) framework. This new framework is first presented and then demonstrated on an ensemble dataset obtained using small-angle X-ray scattering on semi-crystalline linear low density polyethylene films from a synchrotron X-ray scattering experiment.

In Liquid Composite Molding (LCM) processes, dry fabric preforms are impregnated with a thermoset resin in a closed mold to fabricate a composite. The resin impregnation process is usually accompanied by other phenomena. In this work, we concentrate on transport phenomena such as convection of heat, cure and volatiles that impact the filling process and/or the quality of the manufactured part. Conventional approach to modeling such a flow is to integrate all the involved physics into the numerical solver. The complexity of integrated computational models will increase the computational time and complicate modification of transport and retention models once implemented. The latter particularly complicates the exploratory modeling attempts to uncover additional physics that require fast and easy code modification. We propose and provide an implementation methodology to separately couple transport and flow models. With this approach, one can couple flow simulation using highly specialized simulation tools with associated transport phenomena that use separate implementation. The emphasis is on transport of volatiles, both discrete bubbles and dissolved solvents, but it is equally applicable to other problems, such as particle transport and filtration or cure propagation. The challenge of this approach is to (1) formulate proper models and implement them and (2) solve the communication between models efficiently. In our case, the distinct models can be coupled through data exchange, via standardized message passing interface (MPI). A well-tested and optimized flow simulation tool LIMS (Liquid Injection Molding Simulation) is used to implement the coupled simulation processes and transfer the simulation state in an efficient manner to model other transport phenomena. Coupled models to track distinct particles and/or bubbles of volatiles and implement convected/diffused dissolved volatiles. The results are presented highlighting the feasibility and utility of this methodology.