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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 15, 22, and 26 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS) to ensure acceptance of their vitrified high-level waste (HLW) into the Civilian Radioactive Waste Management System. Production Records must document the constituents of the MST/SS material in the PRFT from each salt batch (StB) processed at SWPF. Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 15, 22, and 26, which corresponds to material from the processing of StB4, StB5, and StB7, respectively, are reported herein. The unwashed dried solids of the PRFT batches were found to be 86-87% MST. Additionally, the total sulfur values are well below the assumed 982 mg of sulfate/kg of PRFT slurry used in Material Tracking Program calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Evaluating the Influence of Plants on Hydrologic Cycling: Quantifying and Validating the Role of Plant Processes and Stomatal Conductance (Final Report)

Plants can exert strong controls on water cycling, both locally and across the globe. The impacts are driven by how plants control the exchange of water and energy between the land and the atmosphere, which in turn are influenced by how plants photosynthesize and grow (e.g. biogeochemical cycling). Our team has shown previously that plant responses to increasing CO 2 in the atmosphere can influence the water cycle through changes in rainfall and the amount of water on land with implications for drought. Plant responses can also alter both average and extreme flow of water in rivers, with implications for freshwater availability and flood frequency. Although the impact of plant responses on water cycling has been demonstrated to exist, significant uncertainty remains in our understanding of the magnitude and form of the plant responses themselves, as well as their ultimate impact on water availability for people and ecosystems. In this project we worked to quantify the role of plant processes in regulating water cycling (e.g., precipitation, evapotranspiration, runoff, droughts, etc.). We addressed the following objectives: quantify the control of physiological vs. radiative effects on water cycling across many coupled models in idealized and realistic scenarios, as well as to quantify how our assumptions about leaf-level processes (e.g. coupling between stomatal conductance and photosynthesis), and organism-level processes (e.g. leaf area response to high CO 2 ) contributed to uncertainties and biases in water cycling. We focused on the impact of these processes on water cycling to assess the sensitivities of precipitation, evapotranspiration, and runoff to model assumptions about plant processes at the leaf, organism, and community level. As part of this project we used measurements of stable carbon isotopes to generate observationally based estimates of plant functioning during the historical period. This work is directly relevant to DOE’s primary scientific research questions in the RGMA topic area (b) on Biogeochemical processes, feedbacks, and interactions in the Earth system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development of advanced materials and components fabricated via additive manufacturing, and is using laser powder bed fusion (LPBF) of 316H stainless steel as an initial case study. In the previous fiscal year, miniature high-throughput specimens were printed on multiple LPBF systems to provide initial processing windows to minimize porosity and limit epitaxial grain growth during prints. This fiscal year, scaled builds were completed on three different LPBF systems at ORNL: a GE Concept Laser M2, a Renishaw AM400, and an EOS M290. Builds on the Concept Laser were conducted on multiple powder lots and processing parameter ranges to provide microstructure effects on time-independent and time-dependent mechanical properties. Builds on the Renishaw were produced using Oak Ridge National Laboratory (ORNL)-optimized printing parameters and Argonne National Laboratory (ANL)-optimized printing parameters to compare outcomes of parallel process optimization efforts at different national laboratories on the same LPBF system. Similarly, the build completed on the EOS M290 replicated the processing parameters of builds completed at Los Alamos National Laboratory (LANL). Optical microscopy and electron backscatter diffraction characterization was completed on all builds. In addition to the general round robin characterization, this work-package generated time-independent data, including tensile and fracture toughness test data on scaled Concept Laser builds as a function of processing parameters and post-build heat treatment. This analysis is complimentary to work in parallel work packages aiming to establish heat treatment and processing effects on time-dependent properties. It was found that although the stress-relief heat treatment provides the highest strength at lower-temperatures, tensile strength begins to converge at higher temperatures regardless of heat treatment condition. In addition, the more rigorous solution annealing and hot-isostatic pressing post-build heat treatments result in higher fracture toughness than the stress-relieved condition. The root-causes of the lower fracture toughness of the stress-relieved LPBF 316H material was informed via a stress-relief optimization study on a scaled concept laser print, where it was found that although dislocation recovery was largely complete after only a couple hours at 650°C, the extended hold of the current 24h heat treatment employed on scaled builds likely caused increased carbide volume fractions along the LPBF 316H grain boundaries, thereby deteriorating crack propagation resistance. This trend was seen to become more deleterious with additional increases of stress-relief temperature to 750°C or 850°C. These results have helped inform a new optimal stress-relief annealing condition for LPBF 316H for future campaign testing (650°C for 2h).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development of advanced materials and components fabricated via additive manufacturing, and is using laser powder bed fusion (LPBF) of 316H stainless steel as an initial case study. In the previous fiscal year, miniature high-throughput specimens were printed on multiple LPBF systems to provide initial processing windows to minimize porosity and limit epitaxial grain growth during prints. This fiscal year, scaled builds were completed on three different LPBF systems at ORNL: a GE Concept Laser M2, a Renishaw AM400, and an EOS M290. Builds on the Concept Laser were conducted on multiple powder lots and processing parameter ranges to provide microstructure effects on time-independent and time-dependent mechanical properties. Builds on the Renishaw were produced using Oak Ridge National Laboratory (ORNL)-optimized printing parameters and Argonne National Laboratory (ANL)-optimized printing parameters to compare outcomes of parallel process optimization efforts at different national laboratories on the same LPBF system. Similarly, the build completed on the EOS M290 replicated the processing parameters of builds completed at Los Alamos National Laboratory (LANL). Optical microscopy and electron backscatter diffraction characterization was completed on all builds. In addition to the general round robin characterization, this work-package generated time-independent data, including tensile and fracture toughness test data on scaled Concept Laser builds as a function of processing parameters and post-build heat treatment. This analysis is complimentary to work in parallel work packages aiming to establish heat treatment and processing effects on time-dependent properties. It was found that although the stress-relief heat treatment provides the highest strength at lower-temperatures, tensile strength begins to converge at higher temperatures regardless of heat treatment condition. In addition, the more rigorous solution annealing and hot-isostatic pressing post-build heat treatments result in higher fracture toughness than the stress-relieved condition. The root-causes of the lower fracture toughness of the stress-relieved LPBF 316H material was informed via a stress-relief optimization study on a scaled concept laser print, where it was found that although dislocation recovery was largely complete after only a couple hours at 650°C, the extended hold of the current 24h heat treatment employed on scaled builds likely caused increased carbide volume fractions along the LPBF 316H grain boundaries, thereby deteriorating crack propagation resistance. This trend was seen to become more deleterious with additional increases of stress-relief temperature to 750°C or 850°C. These results have helped inform a new optimal stress-relief annealing condition for LPBF 316H for future campaign testing (650°C for 2h).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This project (1) developed and demonstrated data-driven process controls at full-scale facilities for five promising WRRF process technologies that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) created a Machine Learning (ML) Toolkit and an implementation guide of new process control approaches that walks users through each step of the ML workflow and illustrates the steps through case study examples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Optimization of enhanced law correlation glasses for processing

Primary objectives of this work are given below. Review past test data to identify potential causes for poor processing characteristics of some glass compositions generated by the Enhanced LAW Glass Correlation and conduct tests to investigate these effects. Evaluate strategies to ameliorate processing characteristics of poorly performing Enhanced LAW Glass Correlation compositions through manipulation of glass compositions and GFC additives. Characterize new glass compositions to be processed on the DM100 with respect to properties affecting processability and product quality for melt viscosity, melt electrical conductivity, VHT, PCT, crystallization, refractory corrosion, and sulfate incorporation. Conduct Inconel 690 corrosion tests for various compositions designed by the Enhanced LAW Glass Correlation. Characterize melter feeds to be processed on the DM100 to verify that they have physical and rheological properties that are acceptable for melter feed processing at the WTP. Further refine the Enhanced LAW Glass Correlation based on the results from the rheology, feed VGF, Inconel 690 corrosion, crucible and melter tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 44 and 49 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS). Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 44 and 49, which correspond to material from the processing of Salt Batches (StB) 12 and 11, respectively, are reported herein. The unwashed dried solids of the PRFT Batches 44 and 49 are predominately MST, ~63-59% MST. The two batches have a much higher amount of Fe, Mn, and Ni compared to all previous batches. For Batch 44 this appears to be due to the use of a sludge simulant filter aid during processing of StB 12 and for Batch 49, it is possibly due to the larger amount of insoluble solids for StB 11 in comparison to all previous salt batches. Like previous PRFT batches, a significant amount of the unwashed dried solids are alkaline earth metals. The total sulfate, in mg/kg of slurry, for PRFT Batches 44 and 49 is 119 and 139, respectively, which is well below the current sulfate concentration used in Material Tracking Program calculations and is in agreement with DWPF laboratory sulfate measurements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

ON PROCESS STABILITY IN WAAM-CMT OF ALUMINUM ALLOYS

Wire-arc additive manufacturing (WAAM) has become a cost-efficient metal additive manufacturing process. However, depositing aluminum with WAAM is challenging due to its sensitivity to heat input (linear energy density), which can cause undesirable surface topology waviness if not controlled. Thus, a process window is needed that can produce stable geometry and deposition conditions while minimizing production times. In this study, 5183 aluminum alloy wire is used to deposit 10-layer walls with varying wire feed speeds (WFS) and traverse speeds (TS) (at a constant WFS/TS ratio) and varying interpass temperature (IPT). In-situ process data consisting of optical contact-tip-workpiece-distance (CTWD) and current/voltage measurements are collected to determine process condition stability throughout the build. Part geometry is measured using a 3D scanner and build porosity is characterized via digital X-ray. A process window is identified that produces stable surface topology and process conditions at a minimal production time.

aluminum alloy↗
DOE OSTI2021

Differential Gene Expression in Host Ubiquitination Processes in Childhood Malarial Anemia

Background: Malaria remains one of the leading global causes of childhood morbidity and mortality. In holoendemic Plasmodium falciparum transmission regions, such as western Kenya, severe malarial anemia [SMA, hemoglobin (Hb) < 6.0 g/dl] is the primary form of severe disease. Ubiquitination is essential for regulating intracellular processes involved in innate and adaptive immunity. Although dysregulation in ubiquitin molecular processes is central to the pathogenesis of multiple human diseases, the expression patterns of ubiquitination genes in SMA remain unexplored. Methods: To examine the role of the ubiquitination processes in pathogenesis of SMA, differential gene expression profiles were determined in Kenyan children ( n = 44, aged <48 mos) with either mild malarial anemia (M l MA; Hb ≥9.0 g/dl; n = 23) or SMA (Hb <6.0 g/dl; n = 21) using the Qiagen Human Ubiquitination Pathway RT 2 Profiler PCR Array containing a set of 84 human ubiquitination genes. Results: In children with SMA, 10 genes were down-regulated ( BRCC3 , FBXO3 , MARCH5 , RFWD2 , SMURF2 , UBA6 , UBE2A , UBE2D1 , UBE2L3 , UBR1 ), and five genes were up-regulated ( MDM2 , PARK2 , STUB1 , UBE2E3 , UBE2M ). Enrichment analyses revealed Ubiquitin-Proteasomal Proteolysis as the top disrupted process, along with altered sub-networks involved in proteasomal, protein, and ubiquitin-dependent catabolic processes. Conclusion: Collectively, these novel results show that protein coding genes of the ubiquitination processes are involved in the pathogenesis of SMA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data

Over the past decade, a variety of innovative methodologies have been developed to better characterize the relationships between processing conditions and the physical, morphological, and chemical features of special nuclear material (SNM). Different processing conditions generate SNM products with different features, which are known as “signatures” because they are indicative of the processing conditions used to produce the material. These signatures can potentially allow a forensic analyst to determine which processes were used to produce the SNM and make inferences about where the material originated. This article investigates a statistical technique for relating processing conditions to the morphological features of PuO 2 particles. We develop a Bayesian implementation of seemingly unrelated regression (SUR) to inverse-predict unknown PuO 2 processing conditions from known PuO 2 features. Model results from simulated data demonstrate the usefulness of the technique. Applied to empirical data from a bench-scale experiment specifically designed with inverse prediction in mind, our model successfully predicts nitric acid concentration, while results for Pu concentration and precipitation temperature were equivalent to a simple mean model. Our technique compliments other recent methodologies developed for forensic analysis of nuclear material and can be generalized across the field of chemometrics for application to other materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

The Origin of r-process Elements in the Milky Way

Some of the heavy elements, such as gold and europium (Eu), are almost exclusively formed by the rapid neutron capture process (r-process). However, it is still unclear which astrophysical site between core-collapse supernovae and neutron star–neutron star (NS–NS) mergers produced most of the r-process elements in the universe. Galactic chemical evolution (GCE) models can test these scenarios by quantifying the frequency and yields required to reproduce the amount of europium (Eu) observed in galaxies. Although NS–NS mergers have become popular candidates, their required frequency (or rate) needs to be consistent with that obtained from gravitational wave measurements. We address the first NS–NS merger detected by LIGO/Virgo (GW170817) and its associated gamma-ray burst and analyze their implication for the origin of r-process elements. The range of NS–NS merger rate densities of 320–4740 Gpc -3 yr -1 provided by LIGO/Virgo is remarkably consistent with the range required by GCE to explain the Eu abundances in the Milky Way with NS–NS mergers, assuming the solar r-process abundance pattern for the ejecta. Under the same assumption, this event has produced about 1–5 Earth masses of Eu, and 3–13 Earth masses of gold. When using theoretical calculations to derive Eu yields, constraining the role of NS–NS mergers becomes more challenging because of nuclear astrophysics uncertainties. This is the first study that directly combines nuclear physics uncertainties with GCE calculations. Finally, if GW170817 is a representative event, NS–NS mergers can produce Eu in sufficient amounts and are likely to be the main r-process site.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

R-process-rich Stellar Streams in the Milky Way*

We present high-resolution Magellan/MIKE spectra of 22 bright (9 < V < 13.5) metal-poor stars (-3.18 < [Fe/H] < -1.37) in three different stellar streams, the Helmi debris stream, the Helmi trail stream, and the ω Centauri progenitor stream. We augment our Helmi debris sample with results for 10 stars by Roederer et al. for a total of 32 stars. Detailed chemical abundances of light elements as well as heavy neutron-capture elements have been determined for our 22 stars. All three streams contain carbon-enhanced stars. For 13 stars, neutron-capture element lines were detectable, and they all show signatures in agreement with the scaled solar r -process pattern, albeit with a large spread of -0.5 < [Eu/Fe] < +1.3. Eight of these stars show an additional small s -process contribution superposed onto their r -process pattern. This could be discerned because of the relatively high signal-to-noise ratio of the spectra given that the stars are close by in the halo. Our results suggest that the progenitors of these streams experienced one or more r -process events early on, such as a neutron star merger or another prolific r -process source. This widely enriched these host systems before their accretion by the Milky Way. The small s -process contribution suggests the presence of asymptotic giant branch stars and associated local (inhomogeneous) enrichment as part of the ongoing chemical evolution by low-mass stars. Stars in stellar streams may thus be a promising avenue for studying the detailed history of large dwarf galaxies and their role in halo assembly with easily accessible targets for high-quality spectra of many stars.

Astronomy & Astrophysics↗
DOE OSTI2022

Impact of Hypernova νp-process Nucleosynthesis on the Galactic Chemical Evolution of Mo and Ru

We calculate the Galactic Chemical Evolution of Mo and Ru by taking into account the contribution from νp-process nucleosynthesis. We estimate yields of p-nuclei such as 92,94 Mo and 96,98 Ru through the νp-process in various supernova progenitors based upon recent models. In particular, the νp-process in energetic hypernovae produces a large amount of p-nuclei compared to the yield in ordinary core-collapse SNe. Because of this, the abundances of 92,94 Mo and 96,98 Ru in the Galaxy are significantly enhanced at [Fe/H] = 0 by the νp-process. We find that the νp-process in hypernovae is the main contributor to the elemental abundance of 92 Mo at low metallicity [Fe/H] < −2. Our theoretical prediction of the elemental abundances in metal-poor stars becomes more consistent with observational data when the νp-process in hypernovae is taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

What controls the vertical distribution of aerosol? Relationships between process sensitivity in HadGEM3–UKCA and inter-model variation from AeroCom Phase II

The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3–UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3–UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN > 3 nm), while the profiles of larger particles (e.g. CN > 100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. Here, we also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0

Atmospheric aerosol microphysical processes are a significant source of uncertainty in predicting climate change. Specifically, aerosol nucleation, emissions, and growth rates, which are simulated in chemical transport models to predict the particle size distribution, are not understood well. However, long-term size distribution measurements made at several ground-based sites across Europe implicitly contain information about the processes that created those size distributions. This work aims to extract that information by developing and applying an inverse technique to constrain aerosol emissions as well as nucleation and growth rates based on hourly size distribution measurements. We developed an inverse method based upon process control theory into an online estimation technique to scale aerosol nucleation, emissions, and growth so that the model–measurement bias in three measured aerosol properties exponentially decays. The properties, which are calculated from the measured and predicted size distributions, used to constrain aerosol nucleation, emission, and growth rates are the number of particles with a diameter between 3 and 6 nm, the number with a diameter greater than 10 nm, and the total dry volume of aerosol ( N 3–6 , N 10 , V dry ), respectively. In this paper, we focus on developing and applying the estimation methodology in a zero-dimensional “box” model as a proof of concept before applying it to a three-dimensional simulation in subsequent work. The methodology is first tested on a dataset of synthetic and perfect measurements that span diverse environments in which the true particle emissions, growth, and nucleation rates are known. The inverse technique accurately estimates the aerosol microphysical process rates with an average and maximum error of 2 % and 13 %, respectively. Next, we investigate the effect that measurement noise has on the estimated rates. The method is robust to typical instrument noise in the aerosol properties as there is a negligible increase in the bias of the estimated process rates. Finally, the methodology is applied to long-term datasets of in situ size distribution measurements in western Europe from May 2006 through June 2007. At Melpitz, Germany, and Hyytiälä, Finland, the average diurnal profiles of estimated 3 nm particle formation rates are reasonable, having peaks near noon local time with average peak values of 1 and 0.15 cm –3 s –1 , respectively. The normalized absolute error in estimated N 3–6 , N 10 , and V dry at three European measurement sites is less than 15 %, showing that the estimation framework developed here has potential to decrease model–measurement bias while constraining uncertain aerosol microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Thermographic In-Situ Process Monitoring of the Electron Beam Melting Technology used in Additive Manufacturing

Oak Ridge National Laboratory (ORNL) has been utilizing the ARCAM electron beam melting technology to additively manufacture complex geometric structures directly from powder. Although the technology has demonstrated the ability to decrease costs, decrease manufacturing lead-time and fabricate complex structures that are impossible to fabricate through conventional processing techniques, certification of the component quality can be challenging. Because the process involves the continuous deposition of successive layers of material, each layer can be examined without destructively testing the component. However, in-situ process monitoring is difficult due to metallization on inside surfaces caused by evaporation and condensation of metal from the melt pool. This work describes a solution to one of the challenges to continuously imaging inside of the chamber during the EBM process. Here, the utilization of a continuously moving Mylar film canister is described. Results will be presented related to in-situ process monitoring and how this technique results in improved mechanical properties and reliability of the process.

Additive manufacturing↗
DOE OSTI2017

Metal Big Area Additive Manufacturing: Process Modeling and Validation

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology for printing large-scale 3D objects. mBAAM is based on the gas metal arc welding process and uses a continuous feed of welding wire to manufacture an object. An electric arc forms between the wire and the substrate, which melts the wire and deposits a bead of molten metal along the predetermined path. In general, the welding process parameters and local conditions determine the shape of the deposited bead. The sequence of the bead deposition and the corresponding thermal history of the manufactured object determine the long range effects, such as thermal-induced distortions and residual stresses. Therefore, the resulting performance or final properties of the manufactured object are dependent on its geometry and the deposition path, in addition to depending on the basic welding process parameters. Physical testing is critical for gaining the necessary knowledge for quality prints, but traversing the process parameter space in order to develop an optimized build strategy for each new design is impractical by pure experimental means. Computational modeling and optimization may accelerate development of a build process strategy and saves time and resources. Because computational modeling provides these opportunities, we have developed a physics-based Finite Element Method (FEM) simulation framework and numerical models to support the mBAAM process s development and design. In this paper, we performed a sequentially coupled heat transfer and stress analysis for predicting the final deformation of a small rectangular structure printed using the mild steel welding wire. Using the new simulation technologies, material was progressively added into the FEM simulation as the arc weld traversed the build path. In the sequentially coupled heat transfer and stress analysis, the heat transfer was performed to calculate the temperature evolution, which was used in a stress analysis to evaluate the residual stresses and distortions. In this formulation, we assume that physics is directionally coupled, i.e. the effect of stress of the component on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Additive Manufacturing↗
DOE OSTI2017

Visual Sensing and Image Processing for Error Detection in Laser Metal Wire Deposition

Laser metal deposition with wire (LMD-w) involves feeding metal wire through a nozzle and melting the wire with a high-power laser. With efficient process control, comprising sensing, processing and feedback correction of errors, the technology has a potential of changing the course of manufacturing. However, the limitation most often encountered in LMD is the difficulty in controlling the process. Monitoring and control of metal additive manufacturing processes has been mostly researched on powder-based systems, and has not yet been investigated to much extent on the side of metal wire feed arrangements. This work proposes a method for detecting cavities in a deposited layer in the LMD-w process via optical inspection and processing of images obtained from a high-resolution camera. The aim is to develop an effective sensing module which automatically detects discontinuities in each layer before proceeding to subsequent layers, to reduce part porosity and improve inter-layer bond integrity.

Adediran, Adeola↗