Residual stress measurements using neutron diffraction and the contour method were performed on a valve housing made from 316 L stainless steel powder with intricate three-dimensional internal features using laser powder-bed fusion additive manufacturing. The measurements captured the evolution of the residual stress fields from a state where the valve housing was attached to the base plate to a state where the housing was cut free from the base plate. Making use of this cut, thus making it a non-destructive measurement in this application, the contour method mapped the residual stress component normal to the cut plane (this stress field is completely relieved by cutting) over the whole cut plane, as well as the change in all stresses in the entire housing due to the cut. The non-destructive nature of the neutron diffraction measurements enabled measurements of residual stress at various points in the build prior to cutting and again after cutting. Good agreement was observed between the two measurement techniques, which showed large, tensile build-direction residual stresses in the outer regions of the housing. The contour results showed large changes in multiple stress components upon removal of the build from the base plate in two distinct regions: near the plane where the build was cut free from the base plate and near the internal features that act as stress concentrators. These observations should be useful in understanding the driving mechanisms for builds cracking near the base plate and to identify regions of concern for structural integrity. Neutron diffraction measurements were also used to show the shear stresses near the base plate were significantly lower than normal stresses, an important assumption for the contour method because of the asymmetric cut.

Time horizons for nuclear materials development and qualification must be shortened to realize future nuclear energy concepts. Inspired by the Materials Genome Initiative, we present an integrated approach to materials discovery and qualification to insert new materials into service.

Direct ink write (DIW) is an emerging additive manufacturing technique that allows for the fabrication of arbitrary complex geometries required in many technologies. DIW of metallic or ceramic materials involves a sintering step, which greatly influences many of the microstructural features of the printed object. Herein, we explore solid-state sintering in DIW through a mesoscopic modeling framework that is capable of capturing bulk and interface thermodynamics and accounting for various mass transport mechanisms. Simulation results of idealized geometries identify regimes in materials parameter space, where densification rates are enhanced. With the aid of several statistical and topological descriptors, the role of particle size distribution (PSD) on the microstructural evolution is explored and quantified. More specifically, it is found that a bi-dispersed PSD enhances pore shrinkage kinetics. However, bi-dispersity yields microstructures with pores that are highly eccentric, an effect that could be detrimental to the mechanical properties of the printed material. On the whole, our modeling approach provides a capability to explore the phase space of DIW process parameters and determine ones that lead to optimal microstructures.

Sintering is a processing technique used to produce bulk materials from powder compacts. Recently, sintering has been the subject of active research for its relevance to a wide range of applications, such as additive manufacturing and fabrication of bulk nanocrystalline materials. Of particular interest is the role of grain boundaries (GBs) on sintering mechanisms, cooperative mass transport, and pore shrinkage rates. Herein, atomistic simulations are leveraged to investigate sintering kinetics and densification rates of nanoscale particles as a function of GB misorientation. The two-particle geometry is used to examine particle neck growth rates and crystallographic re-orientation events, and report relative GB diffusion rates as a function of GB misorientation. For the three-particle configuration, simulation results reveal a plethora of pore shrinkage profiles ranging from complete shrinkage to stagnant response depending on the GBs present in the system. This is the first atomistic study that systematically examines the role of GB misorientation on pore shrinkage rates. Our results highlight the need to revisit continuum sintering treatments in order to account for the anisotropy in GB properties.

Additive Manufacturing (AM) can create novel and complex engineered material structures. Features such as controlled porosity, micro-fibers and/or nano-particles, transitions in materials and integral robust coatings can be important in developing solutions for fusion subcomponents. A realistic understanding of this capability would be particularly valuable in identifying development paths. Major concerns for using AM processes with lasers or electron beams that melt powder to make refractory parts are the power required and residual stresses arising in fabrication. A related issue is the required combination of lasers or e-beams to continue heating of deposited material (to reduce stresses) and to deposit new material at a reasonable built rate while providing adequate surface finish and resolution for meso-scale features. Some Direct Write processes that can make suitable preforms and be cured to an acceptable density may offer another approach for PFCs.

Additive Manufacturing (AM) offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this paper. Introduction Additive Manufacturing (AM) is a flexible, agile production pathway ideal for low volume, high value, high consequence, complex parts that are common in high-risk industries such as defense, energy, aerospace, and medical [1,2]. To achieve a paradigm shift in qualification using the promise of AM there are multiple technical challenges that must be addressed. Today, AM processes suffer from challenges with variability in part quality due to build-to-build inconsistencies, inadequate dimensional tolerances, surface roughness, grain size, and defects [3, 4]. These challenges result in costly and time consuming post-build processes (e.g. Hot Isostatic Pressing, machining) to inspect/remediate internal defects (porosity, cracks), alter material properties (strength, ductility), or introduce surface modifications (finish, tolerance). Minimizing these added post-build processes is strongly desirable for financial and qualification needs. Having the ability to predict properties, structure, and performance of AM builds allows for the use of optimization for part performance and the ability to eliminate -or at least reduce -postbuild processing to specific locations known before the build. Inherent to the paradigm shift needed to change qualification is the integration of computational and physical models that comprise of a range of material options and incorporate multiple length and time scales. Utilizing these integrated models to produce a validated, predictive capability integrated with real-time and ex-situ diagnostics is the foundation of this approach. The technical challenges to achieve this new paradigm can be divided into five key areas. 1. Novel real-time AM diagnostic tools to quantify and monitor critical AM process variables for materials control and optimization. 3 Solid Freeform Fabrication 2018: Proceedings of the 29th Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference Reviewed Paper

A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. Progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. This paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.

The potential for bias to affect the results of knowledge elicitation studies is well recognized. Researchers and knowledge engineers attempt to control for bias through careful selection of elicitation and analysis methods. Recently, the development of a wide range of physiological sensors, coupled with fast, portable and inexpensive computing platforms, has added an additional dimension of objective measurement that can reduce bias effects. In the case of an abductive reasoning task, bias can be introduced through design of the stimuli, cues from researchers, or omissions by the experts. We describe a knowledge elicitation methodology robust to various sources of bias, incorporating objective and cross-referenced measurements. The methodology was applied in a study of engineers who use multivariate time series data to diagnose the performance of devices throughout the production lifecycle. For visual reasoning tasks, eye tracking is particularly effective at controlling for biases of omission by providing a record of the subject's attention allocation.

The assurance of the integrity of adhesive bonding at substrate interfaces is paramount to the longevity and sustainability of encapsulated components. Unfortunately, it is often difficult to non-destructively evaluate these materials to determine the adequacy of bonding after manufacturing and then later in service. A particularly difficult problem in this regard is the reliable detection/monitoring of regions of weak bonding that may result from poor adhesion or poor cohesive strength, or degradation in service. One promising and perhaps less explored avenue we have recently begun to investigate for this purpose centers on the use of (chirped) fiber Bragg grating sensing technology. In this scenario, a grating is patterned into a fiber optic such that a (broadband) spectral reflectance is observed. The sensor is highly sensitive to local and uniform changes across the length of the grating. Initial efforts to evaluate this approach for measuring adhesive bonding defects at substrate interfaces are discussed.Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Internal residual stresses and overall mechanical properties of thermoset resins are largely dictated by the curing process. It is well understood that fiber Bragg grating (FBG) sensors can be used to evaluate temperature and cure induced strain while embedded during curing. Herein, is an extension of this work whereby we use FBGs as a probe for minimizing the internal residual stress of an unfilled and filled Epon 828/DEA resin. Variables affecting stress including cure cycle, mold (release), and adhesion promoting additives will be discussed and stress measurements from a strain gauge pop-off test will be used as comparison.Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Nd:YAG laser joining is a high energy density (HED) process that can produce high-speed, low-heat input welds with a high depth-to-width aspect ratio. This is optimized by formation of a “keyhole” in the weld pool resulting from high vapor pressures associated with laser interaction with the metallic substrate. It is generally accepted that pores form in HED welds due to the instability and frequent collapse of the keyhole. In order to maintain an open keyhole, weld pool forces must be balanced such that vapor pressure and weld pool inertia forces are in equilibrium. Travel speed and laser beam power largely control the way these forces are balanced, as well as welding mode (Continuous Wave or Square Wave) and shielding gas type [1]. A study into the phenomenon of weld pool porosity in 304L stainless steel was conducted to better understand and predict how welding parameters impact the weld pool dynamics that lead to pore formation.

A previously developed model for simulation of recoil-pressure induced melt displacement during laser pulse interaction has been upgraded to include the restraining effect of surface tension. The results of numerical simulations of melt displacement/ejection during laser welding and drilling using this enhanced model are presented. In particular, the dependences of the threshold pulse energies for melt displacement and melt ejection as functions of laser pulse duration, beam radius and beam intensity distribution are computed and analysed.

In an ideal world, laser welds would always be made on perfect parts allowing no pre-weld gap, edge rounding or surface level offset. In the real world however, such deviations are not only unavoidable, but are subject to the cost/schedule/performance constraint when piece part dimensional tolerances are decided. In this work we collect recommendations from a variety of sources and try to rationalize how and why they work. We will look at common laser weld geometries: edge, butt, and lap, and discuss how the part deviations from ideality interact with the beam to determine the resulting size and character of the weld. With the aid of simple geometrical and energy arguments and finite element calculations employing level set methodology we will try to understand the physics of the weld variations that were found to result in practice.

Laser spot. welding is a common technique for joining small components that require precise fit-up and small distortion after joining. Finite element models of the laser spot welding process are being developed so that more effective welds can be made. The models being developed use an arbitrary Lagrangian/Eulerian finite element method to predict the formation of the keyhole and the solidification velocities in the laser spot weld. These velocity predictions evolve from the recoil pressure caused by rapid evaporation from the high temperature molten surface and the thermal boundary conditions. The recoil pressure is used as a boundary condition to determine the deformation of the free surface of the molten pool. High-speed, high-magnification video microscopy experiments have been used to measure solidification velocities in actual laser spot welds. The welding modes filmed in this study are limited to welds with no keyhole formation. Solidification velocity data were extracted from video clips using computerized image analysis software. This data were compared to computer model predictions of solidification velocity. This comparison allowed for validation of the fluid and thermal boundary conditions used in the finite element model. Visualization and data extraction techniques will be discussed. Experimental data and predicted solidification velocities will be compared and discussed.

Computer models are being developed to fully understand the laser welding process for critical applications. Validation of these models is an essential part of their development. Sandia National Laboratories’ GOMA code uses an arbitrary Lagrangian / Eulerian finite element method to predict evolution of the fusion zone (including keyhole formation and collapse) in laser spot welds. Recoil pressure caused by evaporation from the high temperature molten surface is a key boundary condition determining deformation of the molten pool surface. Previously, high-speed, video microscopy was used for model validation by measuring solidification velocities in conduction mode laser spot welds. That work is currently being extended to keyhole mode laser spot welds. Additionally, high sensitivity load cell techniques are being developed to simultaneously measure recoil forces associated with keyhole formation. Images of solidifying laser welds and force measurement techniques will be presented and discussed.