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At least 631 records · Page 35

Inadequacy of current approaches for characterizing membrane transport properties at high salinities

Cost optimal design of osmotic membrane processes requires an accurate estimate of membrane transport parameters across their full operational range. However, standard approaches for estimating these parameters rely on empirical methods, the accuracy of which remains unquantified as a function of temperature, salinity, and measurement error. Herein, we present a systematic accuracy analysis of previously developed methods for estimation of membrane transport properties in reverse osmosis, high-pressure reverse osmosis, forward osmosis, pressure retarded reverse osmosis, and osmotically assisted reverse osmosis. We use a Monte Carlo approach to sample the full range of feasible membrane water permeabilities, salt permeabilities, structural parameters, and operating conditions for these processes. These material and process parameters are then incorporated into a physical transport model for each process. Our analysis shows that the statistical uncertainty of current empirical methods for estimating membrane parameters increases by 5 times from low-salinity to high-salinity conditions. Here, the result of this work demonstrates that empirical methods are inadequate for precisely estimating membrane transport properties at high salinity and highlight a critical need for the development of statistically validated higher accuracy methods.

42 ENGINEERING↗

Improved Understanding of Coupled Water and Carbon Cycle Processes through Machine Learning Approaches

Focal Area(s): This white paper addresses how explainable machine learning (ML) algorithms can improve insights gained from complex data (Focal Area 3). We will also address how ML approaches related to sensor compression and low energy AI hardware can be used for efficient data acquisition (Focal Area 1). Science Challenge: We will focus on the coupled water cycle and carbon cycle processes in terrestrial ecosystems and terrestrial-aquatic interfaces. Thus, our approaches will be centered around several data-model integration challenges indicated in EESD strategic plans for two science focus areas: Terrestrial Ecosystem Science and Hydrobiogeochemistry. We can use AI to correct systematic model errors due to biases in either data or model structure/processes. Error patterns in model predictions usually vary by region, model, season etc. But there are systematic patterns in them. e.g., soil moisture tends to be overestimated in the arid western continental United States underestimated in wetter eastern USA; some land surface models tend to underestimate moisture in wet seasons and overestimate in dry seasons. Moreover, the consequences of extreme events (e.g., drought, extreme flooding, storm surges associated with tropical storms, hurricanes) on carbon cycle processes are not well represented in ecosystem and Earth system models. Redox-sensitive processes (e.g., rapid oxidation/reduction of iron and other redox-sensitive elements in soil microsites subjected to fluctuated hydrology) in terrestrial-aquatic interfaces further challenge model predictions of hot-spots (and hot-moments) due to poor understanding of underlying mechanisms. Thus, AI/ML approaches can be used to learn patterns in the data and model errors and use them to build model equations and correct process-based model errors.

54 ENVIRONMENTAL SCIENCES↗

Parameter identification methods for low-order gray box building energy models: A critical review

The body of knowledge on gray box building energy modeling (GBBEM) has been developed over the past few decades and has undergone some important changes recently. Starting with simple methods and simple buildings, the science of GBBEM has grown to encompass complex and more computationally intensive techniques and complex commercial buildings. Numerous works including a recent review have considered model structure and inputs in a nearly systematic way, but no extant work systematically reviews the approaches for GBBEM parameter search initialization and final identification, despite this being arguably the most difficult and impactful part of the modeling process. To this end, we critically review 55 extant works describing advantages, limitations, and domain of applicability of several classes of parameter initialization and optimization techniques specifically for GBBEM. We categorize the classes of methods and analyze the evidence of their applicability for different applications within the field of GBBEM. We find an emerging consensus that initialization of parameter searches for anything other than the simplest building elements is often challenging and sometimes requires a stochastic approach to begin the parameter identification process. After this initial process, faster methods have been used in some cases but often the nature of the problem requires stochastic methods for this portion of the process as well. For less complex systems, more deterministic and efficient methods have been shown to be effective. Finally, we draw conclusions as to the domain of applicability of different classes of initialization and optimization techniques for GBBEEM and offer suggestions for research directions that are likely to prove fruitful.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal conditions for efficient flow-electrode capacitive deionization

One of the current barriers to achieving fast and stable performance for flow-electrode capacitive deionization (FCDI) is determining optimal operating parameters. To date, however, no consensus has been reached for universal conditions for FCDI. Through experimental and modeling approaches in this study, we systematically evaluated the influence of applied potential (V = 1.2–2.4 V) and electrolyte concentration (C0 = 0.05–0.5 M) on the FCDI and electrodialysis (ED) desalination processes. Evaluation indicators include the concentration decrease in the desalinated solution, salt removal rates, pH fluctuations, charge efficiency, and energy consumption. Results demonstrated that the dynamic curves of concentration decrease at 2.0 V nearly overlapped with the response at 1.6 V at certain electrolyte concentrations, while the salt removal rates at 0.2 M salt concentration were the best among all concentrations tested at a range of applied potential. Therefore, it was thus concluded that the optimum conditions for FCDI operation are 1.6 V applied potential and 0.2 M initial salt concentration, under which faradaic reactions are not being triggered, and concentration polarization does not significantly affect ion transfer. Furthermore, a comparative study between FCDI and ED indicated that ED has a different dependence on the electrolyte concentration and applied potential, in which the desalination can be linearly enhanced with increasing potential but greatly limited at high concentrations. Due to the presence of carbon particles in FCDI, the enhanced charge/ion transfer is probably the main reason for the different desalination performance of FCDI and ED. Overall, the optimal operating parameters obtained in this work could be used as basic test conditions for further development of new carbon-based materials for FCDI.

42 ENGINEERING↗

Green Needle Coke Production from Pyrolysis Biocrude toward Bio-based Anode Material Manufacture: Biochar Fines Addition Effect as “Physical Template” on the Crystalline Order

Here, a new method for producing green needle coke (GNC) is developed by replacing the “heavy fraction” of petroleum pitch delayed coking with fast pyrolysis biocrude. A series of alternative biocrude distillation, carbonization, and calcination conditions were investigated to determine the influence of these processing parameters onto the crystalline structure of the resulting graphitized material. For the first time, the addition of biochar fines was found to serve as a “physical template” to increase the graphitic nature of the final product. During the initial biocrude carbonization (350–450 °C), volatile compounds are released, and aromatics in pyrolysis biocrude experience condensation, resulting in GNC solids with carbon contents above 95 wt % and some early lamellar structure. In the second stage of the thermal process (25–1500 °C), there are additional thermal decomposition reactions with an increase in the aromatic nature of the graphitized solid. It was found that systematic addition of biochar fines induces a nucleating effect during the GNC development. Thermogravimetric analysis suggests that biochar fines promote polycondensation reactions by modifying the biopitch structure and molecular weight, while elemental analysis (CHN) shows a reduction in both H/C and O/C ratios which are consistent with the increase in aromaticity and removal of oxygenated compounds as thermal treatment evolves. The effects of different bio-based pitch materials (after distillation) and GNC intermediates were evaluated by pyrolysis-gas chromatography mass spectrometry and Fourier transform infrared, displaying slight changes on product yields and quality. X-ray diffraction patterns taken after graphitization evidence an increase in the graphitic order with the addition of biochar fines. Transmittance electron microscopy depicts an improvement on graphitic morphology as biochar fine content increases. The use of biochar fines showed a significant increase in graphitic ordering at addition levels above 0.01 wt %. These results show that thermally treated biocrude/biochar fine systems can produce graphitic structures (hard carbon-like) that might be suitable for the manufacture of sodium-ion batteries.

09 BIOMASS FUELS↗

The Role of Machine Learning in the Understanding and Design of Materials

Developing algorithmic approaches for the rational design and discovery of materials can enable us to systematically find novel materials, which can have huge technological and social impact. However, such rational design requires a holistic perspective over the full multistage design process, which involves exploring immense materials spaces, their properties, and process design and engineering as well as a techno-economic assessment. The complexity of exploring all of these options using conventional scientific approaches seems intractable. Instead, novel tools from the field of machine learning can potentially solve some of our challenges on the way to rational materials design. Here we review some of the chief advancements of these methods and their applications in rational materials design, followed by a discussion on some of the main challenges and opportunities we currently face together with our perspective on the future of rational materials design and discovery.

36 MATERIALS SCIENCE↗

Scalable synthesis of nanoporous atomically thin graphene membranes for dialysis and molecular separations via facile isopropanol-assisted hot lamination

Scalable graphene synthesis and facile large-area membrane fabrication are imperative to advance nanoporous atomically thin membranes (NATMs) for molecular separations. Although chemical vapor deposition (CVD) allows for roll-to-roll high-quality monolayer graphene synthesis, facile transfer with atomically clean interfaces to porous supports for large-area NATM fabrication remains extremely challenging. Sacrificial polymer scaffolds commonly used for graphene transfer typically leave polymer residues detrimental to membrane performance and transfers without polymer scaffolds suffer from low yield resulting in high non-selective leakage through NATMs. In this study, we systematically study the factors influencing graphene NATM fabrication and report on a novel roll-to-roll manufacturing compatible isopropanol-assisted hot lamination (IHL) process that enables scalable, facile and clean transfer of CVD graphene on to polycarbonate track etched (PCTE) supports with coverage ≥99.2%, while preserving support integrity/porosity. We demonstrate fully functional centimeter-scale graphene NATMs that show record high permeances (~2–3 orders of magnitude higher) and better selectivity than commercially available state-of-the-art polymeric dialysis membranes, specifically in the 0–1000 Da range. Our work highlights a scalable approach to fabricate graphene NATMs for practical applications and is fully compatible with roll-to-roll manufacturing processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Local dynamic responses of magnetic reconnection to three-dimensional perturbations in a laboratory plasma

The dynamic responses of magnetic reconnection to localized three-dimensional (3D) magnetic field perturbations imposed by a pair of figure-8-shaped coils are investigated in the Magnetic Reconnection Experiment (MRX) device. Both the magnetic field geometry and current sheet profiles are altered by external perturbations. For the case when the inductive electric field associated with these perturbations aligns with the preexisting reconnection electric field, O-type magnetic structures appear within an elongated current sheet. When these magnetic structures are ejected downstream at the speed close to the ion outflow velocity, the inductive electric field is enhanced considerably. Despite that the imposed perturbation amplitude is larger than 30% of the original reconnecting magnetic field, the overall reconnection process remains robust without current sheet disruptions. This technique to form O-type magnetic structures can serve as an additional experimental knob for future systematic laboratory investigations of 3D magnetic reconnection and related instabilities without disrupting two-dimensional current sheet.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Asymmetric drift in MaNGA: mass and radially dependent stratification rates in galaxy discs

ABSTRACT We measure the age–velocity relationship from the lag between ionized gas and stellar tangential speeds in ∼500 nearby disc galaxies from MaNGA in Sloan Digital Sky Survey IV (SDSS-IV). Selected galaxies are kinematically axisymmetric. Velocity lags are asymmetric drift, seen in the Milky Way’s (MW) solar neighbourhood and other Local Group galaxies; their amplitude correlates with stellar population age. The trend is qualitatively consistent in rate ($\dot{\sigma }$) with a simple power-law model where σ ∝ tb that explains the dynamical phase-space stratification in the solar neighbourhood. The model is generalized based on disc dynamical times to other radii and other galaxies. We find in-plane radial stratification parameters σ0,r (dispersion of the youngest populations) in the range of 10–40 km s−1 and 0.2 < br < 0.5 for MaNGA galaxies. Overall, brincreases with galaxy mass, decreases with radius for galaxies above 10.4 dex (M⊙) in stellar mass, but is ∼constant with radius at lower mass. The measurement scatter indicates the stratification model is too simple to capture the complexity seen in the data, unsurprising given the many possible astrophysical processes that may lead to stellar population dynamical stratification. None the less, the data show dynamical stratification is broadly present in the galaxy population, with systematic trends in mass and density. The amplitude of the asymmetric drift signal is larger for the MaNGA sample than the MW, and better represented in the mean by what is observed in the discs of M31 and M33. Either typical discs have higher surface-density or, more likely, are dynamically hotter (hence thicker) than the MW.

Bershady, Matthew A. (ORCID:0000000231314374)↗

Turbulence characteristics and flow dynamics impacts on the H-mode transition in favourable magnetic geometry with lower power threshold

We report the L-H transition power threshold (P LH ) in favourable magnetic geometry (ion ∇B drift pointing towards X-point) is much lower than in the unfavourable magnetic geometry (ion ∇B drift pointing away from X-point) on multiple tokamaks. In a systematic experiment on DIII-D, the ion ∇B drift direction was changed continuously from the unfavourable to favourable configuration during plasma discharges. During such process, the input neutral beam power was kept constant at a value that was above P LH for favourable configuration, but lower than P LH for unfavourable configuration. Toroidal field and plasma current were also kept constant and there was little change in the edge electron density ne and electron temperature T e profiles. The density fluctuation amplitude was reduced approaching the transition, while a large increase of turbulence Reynolds stress and flow shear were simultaneously observed. The turbulence decorrelation rate was found to increase as the ion ∇B drift direction was moving towards the favourable configuration, but the flow shear also increased and exceeded the turbulence decorrelation rate. These measurements demonstrate an important correlation between turbulence and turbulence-driven flow and a lowering of PLH, provide insights into the underlying physics behind the hidden parameters and inform a more complete physics-based model of the L-H transition power threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inverse modeling of circular lattices via orbit response measurements in the presence of degeneracy

The number and location of beam position monitors (BPMs) and steerers with respect to the quadrupoles in a circular lattice can lead to degeneracy in the context of fitting linear optics and extracting lattice information from measured closed orbits. Furthermore, the measurement uncertainties due to the imperfection of BPMs and steerers can be propagated by the fitting process in ways that prohibit the successful extraction of discrepancies between lattice elements in the real machine and their description in the corresponding model. We systematically studied the influence of the placement of BPMs and steerers on the reconstruction of linear optics and corresponding lattice information. The derivative of orbit response coefficients with respect to the quadrupole strengths, the Jacobian, is derived as an analytical formula. This analytical version of the Jacobian is used to further derive the theoretical limitations of fitting linear optics from closed orbits in terms of the placement of BPMs and steerers. It is further demonstrated that when evaluating the Jacobian during the fitting procedure, the analytical version can be used in place of the conventional finite-difference computation. This allows for greatly improved efficiency when computing the Jacobian during each iteration of the fitting procedure. The approach is tested with large-scale simulations and the findings are verified by measurement data taken on SIS18 synchrotron at GSI Helmholtz Centre for Heavy Ion Research. The presented methods are of general nature and can be applied to other accelerator lattices as well. The fitting procedure by using the analytical Jacobian is tested in conjunction with various methods for mitigating quasidegeneracy and the results agree with those obtained by using the conventional Jacobian via finite-difference approximation.

47 OTHER INSTRUMENTATION↗

Deployment of the HFIRCON transport and depletion tool for plutonium-238 production studies

Irradiation of {sup 237}Np-bearing targets in Oak Ridge National Laboratory's (ORNL) High Flux Isotope Reactor (HFIR) results in the efficient production of {sup 238}Pu, which, in the form of heat source PuO{sub 2}, is used as a reliable power source for deep-space and planetary NASA missions. A technology demonstration subproject was initiated at ORNL in 2011 to develop and implement the technology required to establish a {sup 238}Pu supply chain. A systematic progression of NpO{sub 2}/Al cermet (20 vol.% NpO{sub 2}) activities to date has successfully demonstrated target fabrication, irradiation, and chemical recovery processes. Recent program tasks have included the development of the HFIRCON transport and depletion tool for efficient reactor physics analyses and the evaluation of increased NpO{sub 2} loadings (i.e., beyond 20 vol.%) and NpN-based targets. This paper documents the deployment of the HFIRCON code to assess various Np concentrations in NpO{sub 2}- and NpN-based targets in HFIR's inner small vertical experiment facilities. Results indicate that {sup 238}Pu production and quality can be enhanced with increased Np loadings; however, target conversion rates are reduced. The results recorded in this paper, thermal and material balance evaluations, and testing requirement planning will be used to determine whether increased NpO{sub 2} loadings or NpN-based targets will be further considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Hadron Polarimetry for the Electron-Ion Collider

The Electron-Ion Collider (EIC) will be the first collider to use both polarized electron beams and polarized proton and light ion beams. It will therefore offer unique opportunities to study the structure of nucleons and to answer fundamental questions in QCD. The uncertainties on the polarization measurement translate directly into the uncertainties of final physics observables. Hence, a precise measurement of the hadron beam polarization and a good control of systematic uncertainties are critical for the success of the spin program at the EIC. Contrary to the case of electron beam polarimetry, which uses physical processes derived from first principles that allow a high precision extraction of the electron beam polarization, for hadron beams no such process is available. The currently best used methods rely on the process of elastic scattering in the Coulomb-Nuclear Interference (CNI) region, for which there are only effective models available. The experience from RHIC, the only existing polarized proton collider, will be detailed and the challenges of the measurements at the EIC will be addressed. In particular, measurements of the present RHIC polarimeters and simulations of the future EIC polarimeters will be presented.

Nunes, Ana Sofia↗

Microgrid Conceptual Design Guidebook | 2022

This guide is meant to assist communities – from residents to energy experts to decision makers – in developing a conceptual microgrid design that meets site-specific energy resilience goals. Using the framework described in this guidebook, stakeholders can come together and start to quantify site-specific vulnerabilities, identify the most significant risks to delivery of electricity, and establish electric outage tolerances across the community. In addition to establishing minimum service needs, this framework encourages communities to consider broader sustainability goals and policy constraints and begin to estimate up-front costs associated with the installation of alternative microgrid solutions. The framework guides a community through data collection and a high-level assessment of its needs, constraints, and priorities, prior to engaging engineers, vendors, and contractors. The first sections of this guidebook provide a high-level primer on electric systems. The latter sections include guidance for step-by-step data gathering and analysis of site conditions. The ultimate product resulting from the stepwise approach is a conceptual microgrid design. A conceptual design is defined as an initial design (10%-20% complete) that considers the specific threats, needs, limitations, and investment options for a given location. Going through this exercise and developing the conceptual microgrid design as a community ensures the same community members who will ultimately live with the solution are the developers of its foundational design. Often, these are also the very same people who understand system tolerances and needs the best and are therefore the ideal candidates for establishing these criteria. Especially when it comes to evaluating critical infrastructure, it is the community that best understands the most critical services. The framework is intended to facilitate a systematic approach to planning for resilience and provide a deeper understanding of how to use a framework to make decisions around microgrid solutions. Like many processes where tradeoffs need to be considered, this is often an iterative process. If this guide serves to help educate and empower communities who are beginning the process of deploying a microgrid, it has met the goal of its authors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Tale of Two Disks: Mapping the Milky Way with the Final Data Release of APOGEE

We present new maps of the Milky Way disk showing the distribution of metallicity ([Fe/H]), α-element abundances ([Mg/Fe]), and stellar age, using a sample of 66,496 red giant stars from the final data release (DR17) of the Apache Point Observatory Galactic Evolution Experiment survey. We measure radial and vertical gradients, quantify the distribution functions for age and metallicity, and explore chemical clock relations across the Milky Way for the low-α disk, high-α disk, and total population independently. The low-α disk exhibits a negative radial metallicity gradient of -0.06 ± 0.001 dex kpc -1 , which flattens with distance from the midplane. The high-α disk shows a flat radial gradient in metallicity and age across nearly all locations of the disk. The age and metallicity distribution functions shift from negatively skewed in the inner Galaxy to positively skewed at large radius. Significant bimodality in the [Mg/Fe]–[Fe/H] plane and in the [Mg/Fe]–age relation persist across the entire disk. The age estimates have typical uncertainties of ~0.15 in log(age) and may be subject to additional systematic errors, which impose limitations on conclusions drawn from this sample. Nevertheless, these results act as critical constraints on galactic evolution models, constraining which physical processes played a dominant role in the formation of the Milky Way disk. We discuss how radial migration predicts many of the observed trends near the solar neighborhood and in the outer disk, but an additional more dramatic evolution history, such as the multi-infall model or a merger event, is needed to explain the chemical and age bimodality elsewhere in the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

First Detection of the GI-type of Intrinsic Alignments of Galaxies Using the Self-calibration Method in a Photometric Galaxy Survey

Weak gravitational lensing is one of the most promising cosmological probes to constrain dark matter, dark energy, and the nature of gravity at cosmic scales. Intrinsic alignments (IAs) of galaxies have been recognized as one of the most serious systematic effects facing gravitational lensing. Such alignments must be isolated and removed to obtain a pure lensing signal. Furthermore, the alignments are related to the processes of galaxy formation, so their extracted signal can help in understanding such formation processes and improving their theoretical modeling. We report in this Letter the first detection of the gravitational shear–intrinsic shape (GI) correlation and the intrinsic shape–galaxy density (Ig) correlation using the self-calibration method in a photometric redshift survey. These direct measurements are made from the KiDS-450 photometric galaxy survey with a significance of 3.65σ in the third bin for the Ig correlation, and 3.51σ for the GI cross-correlation between the third and fourth bins. The self-calibration method uses the information available from photometric surveys without needing to specify an IA model and will play an important role in validating IA models and IA mitigation in future surveys such as the Rubin Observatory Legacy Survey of Space and Time, Euclid, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗

USE OF TWO-PISTON SPLAT QUENCHING TO INVESTIGATE & CHARACTERIZE THE IMPACT OF COMPOSITIONAL VARIATIONS ON RAPID SOLIDIFICATION MICROSTRUCTURES & SUB-MICROSCALE FEATURES IN STAINLESS STEEL ALLOY.

The objective of this dissertation was to use two-piston splat quenching (SQ) to investigate the impact of compositional modifications on the solidification and microstructure of rapidly solidified austenitic stainless steels (SS) and to demonstrate the ability of SQ to quickly and effectively simulate rapid solidification conditions similar to those found in powder bed fusion (PBF) additive techniques. PBF techniques like laser powder bed fusion (LPBF) are being implemented across a breadth of research and industrial applications to create parts with complex geometries and performance capabilities while pushing the current limits of processing conditions and understanding of material systems. In this work, SQ was used to experimentally produce rapid solidification in 20+ unique austenitic SS compositions with systematic variations of the chrome and nickel equivalency ratio (Cr/Nieq) through targeted compositional modifications. From the targeted change of Cr, Ni, and Mo concentrations in rapidly solidified SS alloys, the ferrite solidification mode was found to be the primary solidification mode at significantly lower Cr/Nieq than previously predicted for RS. Also, decreasing concentrations of Fe at a constant Cr/Nieq ratio (i.e., different Fe isopleths), or increased Mo concentrations at a constant Cr/Nieq ratio were found to suppress the ferrite to austenite massive transformation when compared to alloys with lower concentrations at the same Cr/Nieq. Using an established empirical relationship between cell size and cooling rate, the SQ technique was estimated to produce cooling rates between 106 and 108 K/s. Thermal gradients were extracted from 2-D heat transfer simulations of the SQ solidification event and used with these cooling rates to produce solidification rate estimates for SQ which were between 0.4-1.6m/s. The primary solidification mode was observed to be the determining factor in which elements segregated to the cell boundaries during RS, for which Cr and Mo were the main elements to segregate during primary austenite solidification and Ni during primary ferrite solidification. Finally, the solidification rates and conditions produced by SQ experiments resulted in similar microstructures, features, and microsegregation to what was found in LPBF samples of the same feedstock.

Hasenbusch, Zachary↗

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗