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Hanford Direct Feed Low Activity Waste Program Throughput Optimization Through Modeling - 18587

The Direct Feed Low Activity Waste (DFLAW) program at Hanford allows for the early treatment of tank wastes years earlier than previously planned. Operational Research (OR) modeling is being used to provide invaluable insight into how complex and integrated processes will operate. The DFLAW OR models are used to help optimize the design and operation of the integrated system. The DFLAW OR models include the processes and real-life complexities involved in the day-to-day operation of the systems and equipment, and can predict key performance characteristics including throughput, mission timescale, equipment and labor utilization, lag storage and capacity requirements. The DFLAW OR models also have the in-built capability to simulate random events such as equipment failures. Adding random variability to models introduces a real-life element to model results. For example, OR modeling breakdown analysis of equipment failure and restoration times may inform specific improvements to a design and plant operation, including areas where the provision of spare (duty/standby) equipment would prove beneficial; the optimum number and capacity of lag storage tanks (for waste intermediate storage, reagents, etc.); operational issues, including scheduling constraints, labor resource constraints, effect of shift schedules (e.g. days only, extended shifts, 24/7),, maintenance strategies, including planned maintenance, equipment upgrades, on-hand spare part stockholding, etc. At Hanford, standalone OR models to date, have been used to help identify key operational issues and improve the design and operation of individual systems within the Tank Farms, Low Activity Waste Pretreatment System (LAWPS), Low Activity Waste (LAW) Vitrification and Effluent Management Facility (EMF) and Integrated Disposal Facility (IDF), logistics and infrastructure, 222-S laboratory [References 1 and 2] including: - Identification of critical spares including transfer pumps; - Underpin size and number of lag storage tanks to maintain continuous LAW feed to the LAW melters; - Underpin sample turnaround times at the 222-S Laboratory (e.g. feed prequalification and evaporator campaign samples) and determine how targets can be achieved without impacting waste feed delivery to LAWPS and the LAW Vitrification Facility; - Determine operational strategy required at IDF including shift schedules and sizes and the number of ILAW transporters that can support DFLAW throughput; - Identification of lag storage management strategies for glass formers, reagents, other consumables due to delivery distance and delays due to bad weather; and - Truck delivery badging needs to support 24/7 operation and management of shift in/out times required to reduce congestion. An Integrated DFLAW OR model has been developed and combines the standalone OR models such that integrated throughput and availability can be assessed from a program perspective. The Integrated OR model will provide a more detailed understanding of the interactions between Tank Farms, LAWPS, LAW VIT and IDF such that key bottleneck areas can be identified and ensure improvements are focused. Examples of future improvements that may be considered include identification of critical spare parts, required on-site maintenance capabilities, shift scheduling, and craft and labor availability. The methods, results and insights derived by DFLAW OR modeling efforts are expected to provide useful applications to other projects that involve combinations of mechanical handling, chemical processing, waste treatment/packaging or environmental remediation operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

3-D Unsteady Model for Be-Steam Reaction in Water-Cooled Ceramic Breeder Blanket

Here, the design of the water-cooled ceramic breeder (WCCB) blanket includes beryllium multiplier layers. At elevated temperature, beryllium reacts with steam in an exothermic reaction producing beryllium oxide and hydrogen. Such situation may occur in WCCB in the case of the rupture of one of the cooling pipes in the blanket module. This process occurs locally in a complex 3-D geometry of the blanket containing several different granular levels and a network of cooling pipes and structural supports. The process is also inherently unsteady since reaction rate depends on concentration of steam and pure beryllium which changes in time. In order to perform the detailed analysis of the process, the model of the reacting flowthrough porous media was developed and introduced into 3-D computational fluid dynamics code. In this model, granular beds are introduced as porous solids simplifying the model geometry and reducing typical mesh size to manageable amount of tens of millions of elements. A reaction rate between solid beryllium and steam is obtained from experimental results, and depends on temperature and concentration of the reactants. The differential equation for beryllium oxide fraction is introduced, allowing obtaining distributions of beryllium oxide in space and time. Multicomponent flow consisting of a homogenous mixture of steam and hydrogen is considered flowing through the porous solid with variable properties. Sink and source terms for steam and hydrogen fractions are determined by local beryllium oxide mass fraction source according to the molar ratios of beryllium steam reaction. The conjugated heat transfer approach is applied to calculate heat transfer in support structures as well as coolant flow, simultaneously with the porous medium steam flow in a blanket's granular beds. The model is validated using experimental data on beryllium steam reaction for granular bed samples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of Multi-Step CADIS Parameter Sensitivity to Neutron Flux Spectrum in Shutdown Dose Rate Calculations

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final dose rate. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. For example, SDDR assessments are required throughout the biological shield (bio-shield) of the ITER experimental facility to evaluate the required waiting period after the shutdown of ITER and to identify the locations where human accessibility should be prohibited. The bio-shield is a large cylindrical concrete structure (30 m tall and 34 m in diameter) surrounding the very complex tokamak machine. Determining the effects on SDDR of important factors, such as the cross talk (interactions) between the different ports of ITER, is possible only through full-scale simulations that involve all the complex inner details of the ITER tokamak machine. These simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate the distribution of radioisotopes causing the SDDR. Determining a good importance function that can be used in biasing a neutron MC calculation for SDDR is complicated because it is difficult to explicitly express the SDDR response function, which depends on subsequent computational steps. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid MC/deterministic method was developed to speed up the SDDR MC neutron transport calculation using an importance function that represents the neutron importance to the final SDDR. The MS-CADIS method uses the CADIS method, which has been Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). successfully used for more than a decade in radiation shielding applications to generate consistent source biasing and weight window (WW) variance reduction parameters to accelerate continuous-energy MC simulations. However, because MS-CADIS focuses on multi-step shielding calculations such as SDDR calculations, it develops an importance function for the initial radiation transport calculation (e.g., the neutron calculations in SDDR simulations) that represents the importance of particles to the final response of the overall simulation. To develop this importance function, the MS-CADIS method uses an adjoint calculation with a specific neutron adjoint source that represents the neutron's contribution to the final SDDR. Brute force calculation of the MS-CADIS neutron adjoint source requires a deterministic neutron transport calculation coupled with activation calculations in each element of the deterministic mesh. These calculations are needed to determine the MS-CADIS parameter for the neutron interactions that produce radioisotopes contributing to the SDDR. The MS-CADIS parameter is the microscopic cross section of the radioisotope-producing interaction, multiplied by the mass of this radioisotope existing at the end of the irradiation and decay scenario, and divided by the steady-state rate of the interaction. Because the activation calculations are performed for each radionuclide in each mesh element, implementation of the MS-CADIS method can be computationally expensive. However, these neutron transport and activation calculations are not needed if we assume that the radioisotopes are created due to single neutron interactions and their concentrations do not change as a result of burnup by neutron irradiation. The use of this approximation, which renders the MS-CADIS parameter independent of the neutron flux, seems reasonable in calculating the MS-CADIS importance function because this function is needed only to speed up the MC calculation, not to calculate the final SDDR. In this work, we investigate the validity of this approximation by investigating the behavior of the MS-CADIS parameter as a function of the neutron flux spectra in the Fusion Evaluated Nuclear Data Library (FENDL) Neutronics and Shielding Benchmark problem that contains representative isotopes and flux environments of fusion energy systems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Precious metals and rare earth elements in municipal solid waste – Sources and fate in a Swiss incineration plant

Highlights: ► We carefully addressed all the very valuable comments and suggestions of the reviewers. ► We also have shortened the size of the paper and tried simplify it substantially, as requested by the reviewers (introduction 25% reduced!). ► We have decided to take the chance and have replaced the data for the “additional” elements (Cu, Cd, Zn, Pb, Sn, Cr, Ni, Fe, Al) of the earlier MFA (Morf, 2011) with data that belong to the samples of this study. ► We are convinced that with the revision the paper has significantly improved in quality and attractiveness. - Abstract: In Switzerland many kinds of waste, e.g. paper, metals, electrical and electronic equipment are separately collected and recycled to a large extent. The residual amount of municipal solid waste (MSW) has to be thermally treated before final disposal. Efforts to recover valuable metals from incineration residues have recently increased. However, the resource potential of critical elements in the waste input (sources) and their partitioning into recyclable fractions and residues (fate) is unknown. Therefore, a substance flow analysis (SFA) for 31 elements including precious metals (Au, Ag), platinum metal group elements (Pt, Rh) and rare earth elements (La, Ce, etc.) has been conducted in a solid waste incinerator (SWI) with a state-of-the-art bottom ash treatment according to the Thermo-Re® concept. The SFA allowed the determination of the element partitioning in the SWI, as well as the elemental composition of the MSW by indirect analysis. The results show that the waste-input contains substantial quantities of precious metals, such as 0.4 ± 0.2 mg/kg Au and 5.3 ± 0.7 mg/kg Ag. Many of the valuable substances, such as Au and Ag are enriched in specific outputs (e.g. non-ferrous metal fractions) and are therefore recoverable. As the precious metal content in MSW is expected to rise due to its increasing application in complex consumer products, the results of this study are essential for the improvement of resource recovery in the Thermo-Re® process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

{sup 13}C-METHYL FORMATE: OBSERVATIONS OF A SAMPLE OF HIGH-MASS STAR-FORMING REGIONS INCLUDING ORION-KL AND SPECTROSCOPIC CHARACTERIZATION

We have surveyed a sample of massive star-forming regions located over a range of distances from the Galactic center for methyl formate, HCOOCH{sub 3}, and its isotopologues H{sup 13}COOCH{sub 3} and HCOO{sup 13}CH{sub 3}. The observations were carried out with the APEX telescope in the frequency range 283.4-287.4 GHz. Based on the APEX observations, we report tentative detections of the {sup 13}C-methyl formate isotopologue HCOO{sup 13}CH{sub 3} toward the following four massive star-forming regions: Sgr B2(N-LMH), NGC 6334 IRS 1, W51 e2, and G19.61-0.23. In addition, we have used the 1 mm ALMA science verification observations of Orion-KL and confirm the detection of the {sup 13}C-methyl formate species in Orion-KL and image its spatial distribution. Our analysis shows that the {sup 12}C/{sup 13}C isotope ratio in methyl formate toward the Orion-KL Compact Ridge and Hot Core-SW components (68.4 ± 10.1 and 71.4 ± 7.8, respectively) are, for both the {sup 13}C-methyl formate isotopologues, commensurate with the average {sup 12}C/{sup 13}C ratio of CO derived toward Orion-KL. Likewise, regarding the other sources, our results are consistent with the {sup 12}C/{sup 13}C in CO. We also report the spectroscopic characterization, which includes a complete partition function, of the complex H{sup 13}COOCH{sub 3} and HCOO{sup 13}CH{sub 3} species. New spectroscopic data for both isotopomers H{sup 13}COOCH{sub 3} and HCOO{sup 13}CH{sub 3}, presented in this study, have made it possible to measure this fundamentally important isotope ratio in a large organic molecule for the first time.

79 ASTRONOMY AND ASTROPHYSICS↗

Linear spectropolarimetry of 35 Type Ia supernovae with VLT/FORS: an analysis of the Si$\small {II}$ line polarization

Spectropolarimetry enables us to measure the geometry and chemical structure of the ejecta in supernova explosions, which is fundamental for the understanding of their explosion mechanism(s) and progenitor systems. We collected archival data of 35 Type Ia supernovae (SNe Ia), observed with Focal Reducer and Low-Dispersion Spectrograph (FORS) on the Very Large Telescope at 127 epochs in total. We examined the polarization of the Si ιι λ6355 Å line ($p_{\rm Si\, \small {II}}$) as a function of time, which is seen to peak at a range of various polarization degrees and epochs relative to maximum brightness. We reproduced the $\Delta m_{15}\!-\!p_{\rm Si\, \small {II}}$ relationship identified in a previous study, and show that subluminous and transitional objects display polarization values below the $\Delta m_{15}\!-\!p_{\rm Si\, \small {II}}$ relationship for normal SNe Ia. We found a statistically significant linear relationship between the polarization of the Si ii λ6355 Å line before maximum brightness and the Si ιι line velocity and suggest that this, along with the $\Delta m_{15}\!-\!p_{\rm Si\, \small {II}}$ relationship, may be explained in the context of a delayed-detonation model. In contrast, we compared our observations to numerical predictions in the $\Delta m_{15}\!-\!v_{\rm Si\, \small {II}}$ plane and found a dichotomy in the polarization properties between Chandrasekhar and sub-Chandrasekhar mass explosions, which supports the possibility of two distinct explosion mechanisms. A subsample of SNe displays evolution of loops in the q–u plane that suggests a more complex Si structure with depth. This insight, which could not be gleaned from total flux spectra, presents a new constraint on explosion models. To conclude, we compared our statistical sample of the Si ιι polarization to quantitative predictions of the polarization levels for the double-detonation, delayed-detonation, and violent-merger models.

79 ASTRONOMY AND ASTROPHYSICS↗

Synthesis of Hf 6 Ta 2 O 17 superstructure via spark plasma sintering for improved oxidation resistance of multi-component ultra-high temperature ceramics

Ultra-high temperature ceramics (UHTCs) have shown aspiration to overcome challenges in the thermal protection system (TPS) by designing new materials referred to as multi-component UHTCs (MC-UHTCs) in the compositional space. MC-UHTCs have shown remarkable improvement in oxidation resistance due to the formation of the Hf6Ta2O17 superstructure during plasma exposure. Herein, the Hf 6 Ta 2 O 17 superstructure is synthesized via a solid-state reaction between HfO 2 and Ta 2 O 5 powder mixtures during spark plasma sintering (SPS). The compositions chosen are 50 vol% of HfO 2 -50 vol% of Ta 2 O 5 (50HO-50TO) and 70 vol% of HfO 2 -30 vol% of Ta 2 O 5 (70HO-30TO). The phase quantification via Rietveld analysis showed Hf 6 Ta 2 O 17 as a principal phase with some residual Ta 2 O 5 phase in both the samples. The high-temperature thermal stability of the samples was evaluated using high-velocity plasma jet exposure for up to 3 min. 50HO-50TO was able to withstand the intense plasma condition, which is attributed to the higher content of the Hf 6 Ta 2 O 17 phase (~84%) and lower strain in the Ta 2 O 5 phase. The augmentation in the Hf 6 Ta 2 O 17 phase to 94.7% (in 50HO-50TO) post plasma exposure has been attributed to the invariant transformation from a liquid state to Hf 6 Ta 2 O 17 at temperatures >2500 °C during testing. The mechanical integrity is elucidated from the insignificant change in the hardness ~13.3 GPa before and 11.2 GPa after plasma exposure of the 50HO-50TO sample. As a result, the Hf 6 Ta 2 O 17 superstructure's thermo-mechanical stability suggests developing novel oxidation-resistant MC-UHTCs in compositional space for reusable space vehicle applications.

36 MATERIALS SCIENCE↗

Effect of extended strain fields on point defect phonon scattering in thermoelectric materials

The design of thermoelectric materials often involves the integration of point defects (alloying) as a route to reduce the lattice thermal conductivity. Classically, the point defect scattering strength follows from simple considerations such as mass contrast and the presence of induced strain fields (e.g. radius contrast, coordination changes). While the mass contrast can be easily calculated, the associated strain fields induced by defect chemistry are not readily predicted and are poorly understood. In this work, we use classical and first principles calculations to provide insight into the strain field component of phonon scattering from isoelectronic point defects. Our results also integrate experimental measurements on bulk samples of SnSe and associated alloys with S, Te, Ge, Sr and Ba. These efforts highlight that the strength and extent of the resulting strain field depends strongly on defect chemistry. Strain fields can have a profound impact on the local structure. For example, in alloys containing Ba, the strain fields have significant spatial extent (1 nm in diameter) and produce large shifts in the atomic equilibrium positions (up to 0.5 A). Such chemical complexity suggests that computational assessment of point defects for thermal conductivity depression should be hindered. However, in this work, we present and verify several computational descriptors that correlate well with the experimentally measured strain fields. Furthermore, these descriptors are conceptually transparent and computationally inexpensive, allowing computation to provide a pivotal role in the screening of effective alloys. The further development of point defect engineering could complement or replace nanostructuring when optimizing the thermal conductivity, offering the benefits of thermodynamic stability, and providing more clearly defined defect chemistry.

30 DIRECT ENERGY CONVERSION↗

Blazar variability power spectra from radio up to TeV photon energies: Mrk 421 and PKS 2155−304

ABSTRACT We present the results of the power spectral density (PSD) analysis for the blazars Mrk 421 and PKS 2155−304, using good-quality, densely sampled light curves at multiple frequencies, covering 17 decades of the electromagnetic spectrum, and variability time-scales from weeks up to a decade. The data were collected from publicly available archives of observatories at radio from Owens Valley Radio Observatory, optical and infrared (B, V, R, I, J, H, and Kbands), X-rays from the Swift and the Rossi X-ray Timing Explorer, high and very high energy (VHE) γ-rays from the Fermi and Very Energetic Radiation Imaging Telescope Array System as well as the High Energy Stereoscopic System. Our results are: (1) the power-law form of the variability power spectra at radio, infrared, and optical frequencies have slopes ∼1.8, indicative of random-walk-type noise processes; (2) the power-law form of the variability power spectra at higher frequencies, from X-rays to VHE γ-rays, however, have slopes ∼1.2, suggesting a flicker noise-type process; and (3) there is significantly more variability power at X-rays, high and VHE γ-rays on time-scales ≲ 100 d, as compared to lower energies. Our results do not easily fit into a simple model, in which a single compact emission zone is dominating the radiative output of the blazars across all the time-scales probed in our analysis. Instead, we argue that the frequency-dependent shape of the variability power spectra points out a more complex picture, with highly inhomogeneous outflow producing non-thermal emission over an extended, stratified volume.

Goyal, Arti↗

Multi-contrast 3D X-ray imaging of porous and composite materials

Grating-based X-ray computed tomography allows for simultaneous and nondestructive determination of the full X-ray complex index of refraction and the scattering coefficient distribution inside an object in three dimensions. Its multi-contrast capabilities combined with a high resolution of a few micrometers make it a suitable tool for assessing multiple phases inside porous and composite materials such as concrete. Here, we present quantitative results of a proof-of-principle experiment performed on a concrete sample. Thanks to the complementarity of the contrast channels, more concrete phases could be distinguished than in conventional attenuation-based imaging. The phase-contrast reconstruction shows high contrast between the hardened cement paste and the aggregates and thus allows easy 3D segmentation. Thanks to the dark-field image, micro-cracks inside the coarse aggregates are visible. We believe that these results are extremely interesting in the field of porous and composite materials studies because of unique information provided by grating interferometry in a non-destructive way.

36 MATERIALS SCIENCE↗

Embedded symmetric positive semi-definite machine-learned elements for reduced-order modeling in finite-element simulations with application to threaded fasteners

Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.

97 MATHEMATICS AND COMPUTING↗

Endophyte-Promoted Phosphorus Solubilization in Populus

Phosphorus is an important plant nutrient, but in soils the majority of phosphorus, present in the form of a phosphate, forms metal complexes in soil making it relatively unavailable to plants. Therefore, inorganic phosphate solubilization is an important process of plant growth promotion by plant associated bacteria and fungi. Non nodulating plant species have been shown to thrive in low-nutrient environments, in some instances by relying on plant associated microorganisms called endophytes. These microorganisms live within the plant and help supply nutrients for the plant. Despite their potential enormous environmental importance, there are a limited number of studies looking at the direct molecular impact of phosphate solubilizing endophytic bacteria on the host plant. In this work, we studied the impact of two endophyte strains of wild poplar (Populus trichocarpa) that solubilize phosphate. Using a combination of x-ray imaging, spectroscopy methods, and proteomics we report direct evidence of endophyte-promoted phosphorus uptake in poplar. We found that the solubilized phosphate inside the plant may react and become insoluble again suggesting that the phosphate could be re-released within the plant by endophytes. Using synchrotron x-ray fluorescence spectromicroscopy combined with x-ray absorption near-edge structure, we visualized the nutrient phosphorus inside poplar roots inoculated by the selected endophytes and found the phosphorus in both forms of organic and inorganic phosphates inside the root. Tomography-based root imaging revealed a markedly different root biomass and root architecture for poplar samples inoculated with the phosphate solubilizing bacteria strains. Proteomics characterization on poplar roots coupled with protein network analysis revealed novel proteins and metabolic pathways with possible involvement in endophyte enriched phosphorus uptake. These findings suggest an important role of endophytes for phosphorus acquisition and provide a deeper understanding of the critical symbiotic associations between poplar and the endophytic bacteria.

36 MATERIALS SCIENCE↗

Dynamic Analysis Methods for Detecting Anomalies in Asynchronously Interacting Systems

Detecting modifications to digital system designs, whether malicious or benign, is problematic due to the complexity of the systems being analyzed. Moreover, static analysis techniques and tools can only be used during the initial design and implementation phases to verify safety and liveness properties. It is computationally intractable to guarantee that any previously verified properties still hold after a system, or even a single component, has been produced by a third-party manufacturer. In this paper we explore new approaches for creating a robust system design by investigating highly-structured computational models that simplify verification and analysis. Our approach avoids the need to fully reconstruct the implemented system by incorporating a small verification component that dynamically detects for deviations from the design specification at run-time. The first approach encodes information extracted from the original system design algebraically into a verification component. During run-time this component randomly queries the implementation for trace information and verifies that no design-level properties have been violated. If any deviation is detected then a pre-specified fail-safe or notification behavior is triggered. Our second approach utilizes a partitioning methodology to view liveness and safety properties as a distributed decision task and the implementation as a proposed protocol that solves this task. Thus the problem of verifying safety and liveness properties is translated to that of verifying that the implementation solves the associated decision task. We develop upon results from distributed systems and algebraic topology to construct a learning mechanism for verifying safety and liveness properties from samples of run-time executions.

97 MATHEMATICS AND COMPUTING↗

Synthesis, structural and electrical properties of a new cobalt arsenate NaCo{sub 2}As{sub 3}O{sub 10}

The title compound sodium dicobalt triarsenate NaCo{sub 2}As{sub 3}O{sub 10} has been synthesized by solid state reaction. Crystal structure and electrical properties were studied by X-ray diffraction and complex impedance spectroscopy, respectively. The obtained structural model is supported by charge-distribution (CHARDI) analysis and bond-valence-sum (BVS) validations tools. The structure (triclinic, P−1, a=6.800 (8) Å, b=7.816 (9) Å, c=8.718 (3) Å, α=108.03 (2)°, β=108.48 (3)°, γ=100.11 (2)°) can be described as a three-dimensional framework resulted from corner-connection between cobalt metallic chains running along [−110] and As{sub 3}O{sub 10} groups; the negative charge is balanced by Na{sup +} ions which house the two tunnels parallel to a and b axes. Ball milling was used as mechanical means to reduce the particles sizes of the synthesized powder. At the optimal sintering temperature of 650 °C, 85% of the relative density was obtained. The conductivity measurements show that NaCo{sub 2}As{sub 3}O{sub 10} is a cationic conductor with an activation energy of 0.48 eV and a conductivity of σ=1.2×10{sup −5} S cm{sup −1} at 310 °C. The BVS model is extended to simulate the ionic migration pathways of alkali cations in the anionic framework. - Graphical abstract: 1D pathways link Na atoms along the a-axis with bond valence mismatch |ΔV(Na)|=0.64 v.u. - Highlights: • A new single crystal NaCo{sub 2}As{sub 3}O{sub 10} was grown by solid state reaction and its structure determined by single-crystal X-ray diffraction. • The purity of the powder sample was verified by Rietveld refinement. • The CIS measurements were optimized and the obtained spectra were fitted by electrical equivalent circuits. • The conduction pathways for Na{sup +} cations are simulated by means of the bond valence sum model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the feasibility of crack detection in plate weldments through an interposed layer of viscoelastic material.

Development of new approaches in the nondestructive evaluation of welded steel plates for large naval structures continues to be an area of interest for the DoD and the military complex. In this report we will evaluate an elastic-microwave based detection and imaging method using both numerical finite element (3D FEM) and experimental methods. The evaluation was performed on two test articles that were designed to represent critical structural components with flaws of interest. Details of the materials and the mechanical drawings were provided with the test articles. Flaws, cracks and weld defects have been included in the test articles to determine detection sensitivity and accuracy of the proposed method. Our approach uses a microwave interferometer (MI) to record the scattered response of flaws in the steel plated as it is driven by an incident elastic field. The MI can “see” (penetrate) through the viscoelastic coating to the upper surface of the plate. Out-of-plane displacement amplitudes of 10nm in the frequency range (1kHz to 25kHz) are readily observable, with the key feature being, that the surface bond between the coating and the steel plate are undisturbed. The non-contact aspect of the interferometer allows for large surface regions to be accurately and efficiently scanned in space and time. Spatiotemporal data sets of this kind and specialized wavefield processing provide powerful detection and imaging modalities. From these wavefield data sets, a plate thickness mapping capability has been demonstrated that can detect thickness changes on the order of 0.79 mm (1/32”) with spatial resolution on the order of the spatial sampling rate, 15mm (~5/8”). We have also shown that a topological energy analysis of the wavefield data can detect and locate small flaws, on the order of 5-10 mm (0.025-0.40”) in the welded joint of a 1.5” thick T-plate. As before, these results are obtained through a 2” thick viscoelastic coating without altering the integrity of coating or the coating bond. These results show that we are detecting and locating damage (flaws) in the plate that are much smaller than the wavelength of the propagating guided modes. Classical scattering theory places a (λ/2) resolution limit on the detectability of flaws in terms of the incident field [22], however, since the spatial resolution of the scanned region is much smaller, (Δx=Δy=15mm) and the inherent natural focusing of the time reversal operation, we are able to detect smaller flaws on the order of (λ/10). It is important to realize that we are not imaging the flaw but detecting and localizing a difference between a reference (pristine) sample and the measured (damaged) sample, relative to a spatial grid on the surface. The current scan resolution is 15mm x 15mm. At present we cannot expect to resolve individual flaws within a grid space only their cumulative effect. Even with the current limitations, this imaging approach appears to be a promising alternative to current methods where the coating layer is removed.

36 MATERIALS SCIENCE↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

Effective detection of CO 2 leakage: a comparison of groundwater sampling and pressure monitoring

Shallow aquifer monitoring is likely to be a required aspect to any geologic CO 2 sequestration operation. Collecting groundwater samples and analyzing for geochemical parameters such as pH, alkalinity, total dissolved carbon, and trace metals has been suggested by a number of authors as a possible strategy to detect CO 2 leakage. The effectiveness of this approach, however, will depend on the hydrodynamics of the leak-induced CO 2 plume and the spatial distribution of the monitoring wells relative to the origin of the leak. To our knowledge, the expected effectiveness of groundwater sampling to detect CO 2 leakage has not yet been quantitatively assessed. In this study we query hundreds of simulations developed for the National Risk Assessment Project (US DOE) to estimate risks to drinking water resources associated with CO 2 leaks. The ensemble of simulations represent transient, 3-D multi-phase reactive transport of CO 2 and brine leaked from a sequestration reservoir, via a leaky wellbore, into an unconfined aquifer. Key characteristics of the aquifer, including thickness, mean permeability, background hydraulic gradient, and geostatistical measures of aquifer heterogeneity, were all considered uncertain parameters. Complex temporally-varying CO 2 and brine leak rate scenarios were simulated using a heuristic scheme with ten uncertain parameters. The simulations collectively predict the spatial and temporal evolution of CO 2 and brine plumes over 200 years in a shallow aquifer under a wide range of leakage scenarios and aquifer characteristics. Using spatial data from an existing network of shallow drinking water wells in the Edwards Aquifer, TX, as one illustrative example, we calculated the likelihood of leakage detection by groundwater sampling. In this monitoring example, there are 128 wells available for sampling, with a density of about 2.6 wells per square kilometer. If the location of the leak is unknown a priori, a reasonable assumption in many cases, we found that the leak would be detected in at least one of the monitoring wells in less than 10% of the scenarios considered. This is because plume sizes are relatively small, and so the probability of detection decreases rapidly with distance from the leakage point. For example, 400m away from the leakage point there is less than 20% chance of detection. We then compared the effectiveness of groundwater quality sampling to shallow aquifer and/or reservoir pressure monitoring. For the Edwards Aquifer example, pressure monitoring in the same monitoring well network was found to be even less effective that groundwater quality monitoring. This is presumably due to the unconfined conditions and relatively high permeability, so pressure perturbations quickly dissipate. Although specific results may differ from site to site, this type of analysis should be useful to site operators and regulators when selecting leak detection strategies. Given the spatial characteristics of a proposed monitoring well network, probabilities of leakage detection can be rapidly calculated using this methodology. Although conditions such as these may not be favorable for leakage detection in shallow aquifers, leakage detection could be much more successful in the injection reservoir. We demonstrate proof-of-concept for this hypothesis, presenting a simulation where there is measurable pressure change at the injection well due to overpressurization, fault rupture, and consequent leakage up the fault into intermediate and shallow aquifers. The size of the detectible pressure change footprint is much larger in the reservoir than in either of the overlying aquifers. Further exploration of the range of conditions for which this technique would be successful is the topic of current study.

54 ENVIRONMENTAL SCIENCES↗

Bayesian analysis of the dynamic cosmic web in the SDSS galaxy survey

Recent application of the Bayesian algorithm \textsc(borg) to the Sloan Digital Sky Survey (SDSS) main sample galaxies resulted in the physical inference of the formation history of the observed large-scale structure from its origin to the present epoch. In this work, we use these inferences as inputs for a detailed probabilistic cosmic web-type analysis. To do so, we generate a large set of data-constrained realizations of the large-scale structure using a fast, fully non-linear gravitational model. We then perform a dynamic classification of the cosmic web into four distinct components (voids, sheets, filaments, and clusters) on the basis of the tidal field. Our inference framework automatically and self-consistently propagates typical observational uncertainties to web-type classification. As a result, this study produces accurate cosmographic classification of large-scale structure elements in the SDSS volume. By also providing the history of these structure maps, the approach allows an analysis of the origin and growth of the early traces of the cosmic web present in the initial density field and of the evolution of global quantities such as the volume and mass filling fractions of different structures. For the problem of web-type classification, the results described in this work constitute the first connection between theory and observations at non-linear scales including a physical model of structure formation and the demonstrated capability of uncertainty quantification. A connection between cosmology and information theory using real data also naturally emerges from our probabilistic approach. Our results constitute quantitative chrono-cosmography of the complex web-like patterns underlying the observed galaxy distribution.

79 ASTRONOMY AND ASTROPHYSICS↗