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DOE OSTI2018

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↗

DOE OSTI2022

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

S. elongatus PCC 7942 Carbon Metabolism Proteomics (MC-DP2)

The purpose of this experiment was to examine the redox proteome of S. elongatus PCC 7942 CscB/SPS under different light conditions (light and dark) and culture conditions (dense and dilute optical density). Samples were processed using a resin-assisted capture (RAC) workflow with TMT labeling to enrich and quantify protein cysteines which were differentially oxidized under four conditions. The datasets were generated by a Q Exactive Plus Orbitrap Mass Spectrometer coupled with a Waters nanoAcquity UPLC, then searched by MSGF+ for downstream redox PTM analysis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Estimating Species Distributions Across Space Through Time and with Features of the Environment

Complete guidance for mastering the tools and techniques of the digital revolution With the digital revolution opening up tremendous opportunities in many fields, there is a growing need for skilled professionals who can develop data-intensive systems and extract information and knowledge from them. This book frames for the first time a new systematic approach for tackling the challenges of data-intensive computing, providing decision makers and technical experts alike with practical tools for dealing with our exploding data collections. Emphasizing data-intensive thinking and interdisciplinary collaboration, The Data Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business examines the essential components of knowledge discovery, surveys many of the current research efforts worldwide, and points to new areas for innovation. Complete with a wealth of examples and DISPEL-based methods demonstrating how to gain more from data in real-world systems, the book: Outlines the concepts and rationale for implementing data-intensive computing in organizations Covers from the ground up problem-solving strategies for data analysis in a data-rich world Introduces techniques for data-intensive engineering using the Data-Intensive Systems Process Engineering Language DISPEL Features in-depth case studies in customer relations, environmental hazards, seismology, and more Showcases successful applications in areas ranging from astronomy and the humanities to transport engineering Includes sample program snippets throughout the text as well as additional materials on a companion website The Data Bonanza is a must-have guide for information strategists, data analysts, and engineers in business, research, and government, and for anyone wishing to be on the cutting edge of data mining, machine learning, databases, distributed systems, or large-scale computing.

Kelling, S.↗

DOE OSTI2017

Spectroscopic Characterization of Tc(I) Tricarbonyl Species Relevant to the Hanford Tank Waste - 17379

Technetium-99 (Tc) generated from the fission of {sup 235}U and {sup 239}Pu in high yields is one of the most difficult contaminants to be addressed at the U.S. Department of Energy (DOE) Hanford Site. Among radioactive contaminants, Tc presents a unique challenge in that it has a long half-life (T{sub 1/2} = 2.11x10{sup 5} y), exhibits diverse chemical properties and typically highly mobile in the environment leading to several uncertainties regarding treatment and disposition options. The complex behavior of Tc under storage, treatment, and immobilization conditions significantly affects its management options. The overall objective of the Technetium Management program at Pacific Northwest National Laboratory is to provide the DOE Office of Environmental Management with practical solutions to Tc needs encountered in the processing of Hanford tank waste and vadose zone remediation; and technical activities are being performed in the areas of Tc characterization, treatment, and disposition. One specific task is focused on elucidation of the identity and properties of non-pertechnetate species in the liquid Hanford tank waste. Previous analysis of the tank waste samples provided strong evidence that non-pertechnetate species can be comprised of Tc(CO)3+ complexes containing Tc in oxidation state +1. This paper describes our current results on the development of spectroscopic library of Tc(I) tricarbonyl species for their characterization and identification in the Hanford tank wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

ESTIMATING BLACK HOLE MASSES IN HUNDREDS OF QUASARS

We explore the practical feasibility of active galactic nucleus (AGN) broadband reverberation mapping and present first results. We lay out and apply a rigorous approach for the stochastic reverberation mapping of unevenly sampled multi-broadband flux measurements, assuming that the broad-line region (BLR) line flux is contributing up to 15% in some bands, and is directly constrained by one spectroscopical epoch. The approach describes variations of the observed flux as the continuum, modeled as a stochastic Gaussian process, and emission line contribution, modeled as a scaled, smoothed, and delayed version of the continuum. This approach can be used not only to interpolate in time between measurements, but also to determine confidence limits on continuum—line emission delays. This approach is applied to Sloan Digital Sky Survey observations in Stripe 82 (S82), providing flux measurements that are precise to 2% at ∼60 epochs over ∼10 yr. The strong annual variations in the epoch sampling prove a serious limitation in practice. In addition, suitable redshift ranges must be identified where strong, broad emission lines contribute to one filter, but not to another. By generating and evaluating problem-specific mock data, we verify that S82-like data can constrain τ{sub delay} for a simple transfer function model. In application to real data, we estimate τ{sub delay} for 323 AGNs with 0.225 < z < 0.846, combining information for different objects through the ensemble-scaling relationships for BLR size and black hole mass. Our analysis tentatively indicates a 1.7 times larger BLR size of Hα and Mg II compared to Kaspi et al. and Vestergaard, but the seasonal data sampling casts doubt on the robustness of the inference.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Editorial: Biomass Modification, Characterization, and Process Monitoring Analytics to Support Biofuel and Biomaterial Production

This Frontiers Research Topic journeys through various challenges facing researchers seeking to develop fuels and products derived from lignocellulosic biomass. These challenges include: the rapid quantification of plant cell wall chemistry, enabling yields of potential monomeric sugars to be assessed, identification of plants possessing ideal trait that can be brought to the forefront of research efforts; once the native plant chemistry is known, how can yields be improved by chemically or genetically altering plant cell walls to reduce recalcitrance; does genetic modification of plants to increase accessibility to saccharification enzymes hinder the plant’s growth and/or function; are the innovative methods identified by researchers cost-effective and scalable to a commercial level? These topics are a sampling of the obstacles researchers combat when nominating a specific plant for downstream applications or implementing new deconstruction, genetic, or measurement strategies. How well can different plants can be broken down into useful, downstream precursor molecules? Efforts to develop a lucid picture of the chemical composition of abundant, diverse plants being explored as potential starting feedstocks has resulted in the evolution of high-throughput techniques that permit many more samples to be screened in much shorter periods of time. Advances in thermochemical and spectroscopic techniques have enabled the screening of thousands of plants for different phenotypes, such as cell-wall composition and monomeric sugar release. Some instrumental methods have been coupled with multivariate analysis, providing elegant chemometric predictive models enabling the accelerated identification of potential feedstocks. Rapid instrumental techniques have been developed for real-time monitoring of diverse processes, such as the efficacy of specific pretreatment strategies, or downstream products, such as biofuels and biomaterials. Real-time process monitoring techniques are needed for all stages of the feedstocks-to-biofuels conversion process to maximize efficiency and lower costs by monitoring and optimizing performance. These approaches allow researchers to adjust experimental conditions during, rather than at the conclusion, of processes, thereby decreasing overhead expenses.

09 BIOMASS FUELS↗

DOE OSTI2020

Comparison between mirror Langmuir probe and gas-puff imaging measurements of intermittent fluctuations in the Alcator C-Mod scrape-off layer

Statistical properties of the scrape-off layer plasma fluctuations are studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first time, plasma fluctuations as well as parameters that describe the fluctuations are compared across measurements from a mirror Langmuir probe (MLP) and from gas-puff imaging (GPI) that sample the same plasma discharge. This comparison is complemented by an analysis of line emission time-series data, synthesized from the MLP electron density and temperature measurements. The fluctuations observed by the MLP and GPI typically display relative fluctuation amplitudes of order unity together with positively skewed and flattened probability density functions. Such data time series are well described by an established stochastic framework that models the data as a superposition of uncorrelated, two-sided exponential pulses. The most important parameter of the process is the intermittency parameter, $γ=τ_d/τ_w$, where τd denotes the duration time of a single pulse and $τ_w$ gives the average waiting time between consecutive pulses. In this study we show, using a new deconvolution method, that these parameters can be consistently estimated from different statistics of the data. We also show that the statistical properties of the data sampled by the MLP and GPI diagnostic are very similar. Finally, a synthetic GPI signal using only plasma parameters sampled by the MLP shows qualitatively different fluctuation statistics from the measured GPI signal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Chemical analysis of simulated high level waste glasses to support stage III sulfate solubility modeling

The U.S. Department of Energy (DOE), Office of Environmental Management (EM) is sponsoring an international, collaborative project to develop a fundamental model for sulfate solubility in nuclear waste glass. The solubility of sulfate has a significant impact on the achievable waste loading for nuclear waste forms within the DOE complex. These wastes can contain relatively high concentrations of sulfate, which has low solubility in borosilicate glass. This is a significant issue for low-activity waste (LAW) glass and is projected to have a major impact on the Hanford Tank Waste Treatment and Immobilization Plant (WTP). Sulfate solubility has also been a limiting factor for recent high level waste (HLW) sludge processed at the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF). The low solubility of sulfate in glass, along with melter and off-gas corrosion constraints, dictate that the waste be blended with lower sulfate concentration waste sources or washed to remove sulfate prior to vitrification. The development of enhanced borosilicate glass compositions with improved sulfate solubility will allow for higher waste loadings and accelerate mission completion.The objective of the current scope being pursued by SHU is to mature the sulfate solubility model to the point where it can be used to guide glass composition development for DWPF and WTP, allowing for enhanced waste loadings and waste throughput at these facilities. A series of targeted glass compositions was selected to resolve data gaps in the model and is identified as Stage III. SHU fabricated these glasses and sent samples to SRNL for chemical composition analysis. SHU will use the resulting data to enhance the sulfate solubility model and resolve any deficiencies. In this report, SRNL provides chemical analyses for the Stage III, simulated HLW glasses fabricated by SHU in support of the sulfate solubility model development.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Nanostructure and burning mode of light-duty diesel particulate with conventional diesel, biodiesel, and intermediate blends

The nanostructure of diesel particulates has been shown to impact its oxidation rate and burnout trajectory. Additionally, this nanostructure can evolve during the oxidation process, furthering its influence on the burnout process. For this study, exhaust particulates were generated on a light-duty diesel engine with conventional diesel fuel, biodiesel, and intermediate blends of the two at a single load-speed point. Despite the singular engine platform and operating point, the different fuels created particulates with varied nanostructure, thereby greatly expanding the window for observing nanostructure evolution and oxidation. The physical and chemical properties of the particulates in the nascent state and at partial oxidation states were measured in a laboratory reactor and by high-resolution transmission electron microscopy as a function of the degree of oxidation in O 2 . X-ray photoacoustic spectroscopy analysis, thermal desorption, and solvent extraction of the nascent particulate samples reveal a significant organic content in the biodiesel-derived particulates, likely accounting for differences in the nanostructure. This study reports the nanoscale structural changes in the particulate with biofuel blend level and during O 2 oxidation as observed by high-resolution transmission electron microscopy and quantitated by fringe analysis and Brunnauer–Emmet–Teller total surface area measurements. It was observed that initial fuel-related differences in the lamella lengths, spacing, and curvature disappear when the particulate reaches approximately 50% burnout. Specifically, the initial ordered, fullerenic, and amorphous nanostructures converge during the oxidation process and the surface areas of these particulates appear to grow through these complex changes in internal particle structure. The specific surface area, measured at several points along the burnout trajectory, did not match the shrinking core projection and in contrast suggested that internal porosity was increasing. Thus, the appropriate burnout model for these particulates is significantly different from the standard shrinking core assumption, which does not account for any internal structure. An alternative burnout model is supported by high-resolution transmission electron microscopy image analysis.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Energy dissipation efficiency in the CP43 assembly intermediate complex of photosystem II

Photosystem II in oxygenic organisms is a large membrane bound rapidly turning over pigment protein complex. During its biogenesis, multiple assembly intermediates are formed, including the CP43-preassembly complex (pCP43). Here, to understand the energy transfer dynamics in pCP43, we first engineered a His-tagged version of the CP43 in a CP47-less strain of the cyanobacterium Synechocystis 6803. Isolated pCP43 from this engineered strain was subjected to advanced spectroscopic analysis to evaluate its excitation energy dissipation characteristics. These included measurements of steady-state absorption and fluorescence emission spectra for which correlation was tested with Stepanov relation. Comparison of fluorescence excitation and absorptance spectra determined that efficiency of energy transfer from β-carotene to chlorophyll a is 39 %. Time-resolved fluorescence images of pCP43-bound Chl a were recorded on streak camera, and fluorescence decay dynamics were evaluated with global fitting. These demonstrated that the decay kinetics strongly depends on temperature and buffer used to disperse the protein sample and fluorescence decay lifetime was estimated in 3.2–5.7 ns time range, depending on conditions. The pCP43 complex was also investigated with femtosecond and nanosecond time-resolved absorption spectroscopy upon excitation of Chl a and β-carotene to reveal pathways of singlet excitation relaxation/decay, Chl a triplet dynamics and Chl a → β-carotene triplet state sensitization process. The latter demonstrated that Chl a triplet in the pCP43 complex is not efficiently quenched by carotenoids. Finally, detailed kinetic analysis of the rise of the population of β-carotene triplets determined that the time constant of the carotenoid triplet sensitization is 40 ns.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Dynamic shear localization of a titanium alloy under high-rate tension characterized by x-ray digital image correlation

Highlights: • First systematic error analyses for XDIC • First XDIC study of Ti-6Al-4V under dynamic tension • Deformation mode transition induces dynamic ductility decrease. • Dynamic shear localization due to rate-dependent microvoid coalescence process. - Abstract: Dynamic and quasi-static tension experiments are conducted on Ti-6Al-4V alloys, with in situ, synchrotron-based, high-speed, x-ray phase contrast imaging implemented to characterize the dynamic deformation and fracture process of Ti alloys at the Advanced Photon Source. X-ray digital imaging correlation (XDIC) is applied for strain field mapping. The size distribution of x-ray speckles are quantified via a morphological analysis, with a mean of ∼20 μm. Systematic error analyses of displacement and strain field measurements are firstly conducted for XDIC, and demonstrate that the displacement and strain errors can be controlled below 0.01 pixel and 0.1%, respectively. Mesoscale strain characteristics measured via XDIC are consistent with and reveal mechanisms for the bulk-scale stress–strain responses. Under dynamic tension, a sharp transition to strain softening occurs when the bulk strain exceeds about 0.04, which leads to a lower dynamic fracture strain (0.08) than the quasi-static one (0.1). The corresponding strain filed mapping demonstrates that shear deformation localizations grow and coalesce rapidly into a narrow shear deformation band under dynamic loading, while tensile deformation and necking progresses gradually under quasi-static loading. Scanning electron microscopy shows that void nucleation occurs mainly at the interface of α and β phases for both quasi-static and dynamic tension. However, microvoids coalesce preferentially along colony boundaries or the boundary α phase under quasi-static tension, but along the maximum shear stress direction (across colonies) under dynamic tension. Fractography of recovered samples also shows consistent features.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Assessing the recharge process and importance of montane water to adjacent tectonic valley-plain groundwater using a ternary end-member mixing analysis based on isotopic and chemical tracers

A study in eastern Taiwan evaluated the importance of montane water contribution (MC) to adjacent valley-plain groundwater (VPG) in a tectonic suture zone. The evaluation used a ternary natural-tracer-based end-member mixing analysis (EMMA). With this purpose, VPG and three end-member water samples of plain precipitation (PP), mountain-front recharge (MFR), and mountain-block recharge (MBR) were collected and analyzed for stable isotopic compositions (δ{sup 2}H and δ{sup 18}O) and chemical concentrations (electrical conductivity (EC) and Cl{sup −}). After evaluation, Cl{sup −} is deemed unsuitable for EMMA in this study, and the contribution fractions of respective end members derived by the δ{sup 18}O–EC pair are similar to those derived by the δ{sup 2}H–EC pair. EMMA results indicate that the MC, including MFR and MBR, contributes at least 70% (679 × 10{sup 6} m{sup 3} water volume) of the VPG, significantly greater than the approximately 30% of PP contribution, and greater than the 20–50% in equivalent humid regions worldwide. The large MC is attributable to highly fractured strata and the steep topography of studied catchments caused by active tectonism. Furthermore, the contribution fractions derived by EMMA reflect the unique hydrogeological conditions in the respective study sub-regions. A region with a large MBR fraction is indicative of active lateral groundwater flow as a result of highly fractured strata in montane catchments. On the other hand, a region characterized by a large MFR fraction may possess high-permeability stream beds or high stream gradients. Those hydrogeological implications are helpful for water resource management and protection authorities of the studied regions.

58 GEOSCIENCES↗

DOE OSTI2022

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Radiation Transport in Random Media With Large Fluctuations

Strongly heterogeneous media arise in several applications that include radiation shields, nuclear fuel, BWR moderators, clouds, planetary and stellar atmospheres, turbulent gases and plasmas. Neutral and charged particle transport computations in such media have relied heavily on formulating transport equations with spatially random coefficients (physical data) and developing solution methods to deal with the additional stochastic dimensions. Attempts at developing approximate closures that yield only low order statistical information (e.g., mean and variance of the flux) have proved to be highly restrictive under real physics conditions or rely on techniques that require fluctuation amplitudes to be small for robustness. Recently, stochastic spectral methods such as polynomial chaos and stochastic collocation have been developed for aleatoric uncertainty quantification and sensitivity analysis, and successfully applied in radiation transport work. Advances in UQ techniques have tended to focus on efficiently handling large numbers of uncertain variables but the rigorous stochastic basis of the approach also promotes its use in situations where stochasticity is due to spatial heterogeneity and the associated uncertainty is large. Here we apply these techniques to radiation transport in media with spatially randomly varying cross sections without restriction on fluctuation amplitudes. Specifically, we represent the cross sections as a lognormal spatial random process with specified mean, variance and covariance function and use a Karhunen-Loeve (KL) decomposition to generate cross section realizations that are strictly positive. Woodcock Monte Carlo (WMC) is then used to simulate transport using random sampling of cross sections and deterministic sampling based on a stochastic collocation technique. Numerical results for the mean and variance in the scalar flux and leakage currents are obtained for weak and strong random variations. We focus in this work on demonstrating the approach and defer application to specific problems to a future investigation. We have demonstrated that a combination of stochastic spectral representation and Woodcock Monte Carlo simulation allows efficient computation of radiation transport in strongly random media. The use of a lognormal distribution to represent the fluctuations in medium properties facilitates enforcement of strict positivity of cross section realizations, a condition that has challenged standard approaches that assume Gaussian fluctuations. The fact that the lognormal random process is a memoryless nonlinear transformation of a Gaussian process further enables efficient and accurate reconstruction of the random cross section realizations using a Karhunen-Loeve representation of the cross section. Finally, the robustness of this model enables fluctuations of arbitrarily large amplitude to be studied, using both random sampling Monte Carlo and more efficient stochastic collocation techniques. The present work is being extended to allow reconstruction of probability density functions of output variables using polynomial chaos representation, and to accommodate general cross section covariance functions. Also, techniques are being explored to more judiciously select ceiling cross sections to enhance the efficiency of Woodcock Monte Carlo for transport in random media. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Measurements of the thermal conductivity of reference liquids using a modified transient hot-wire needle probe

Many power generation processes feature some type of working fluid that plays a critical role in the transfer of heat throughout the system. To optimize thermal efficiencies, an accurate characterization of the temperature-dependent thermal conductivity of the fluid is needed. Herein, this study develops a time-domain Modified Transient Hot-wire Needle Probe to overcome phenomena that have impaired traditional measurement techniques when the fluid is both corrosive and at an elevated temperature. First, the physical design of the instrument is presented to demonstrate features that limit interference from corrosion, electrical conduction, and convective and radiative heat transfer. Next, a governing equation for 1D (radial) heat conduction is fully developed using the thermal quadrupoles technique. A finite-element study is performed for validation. A sensitivity analysis is done to assess the time-dependent influence of critical parameters in the governing equation for several samples. Finally, thermal conductivity measurements are presented for seven different liquid substances by fitting the thermal model to experimental data across a range of temperatures. Reference correlations are included for comparison. The sample thermal conductivity and ambient temperature of the experimental conditions range from 0.125–16.5$\frac{W}{m·K}$ and 10–400°C, respectively. The total uncertainty, comprised of both the experimental design and fitting process, of all measurements is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Quantifying the cooperative evolution of microphase segregation and nanostructural order in annealed polyurethanes of MDI-BDO-PTHF

Here, we quantify the relationship between microphase segregation and local structure development in thermoplastic polyurethanes. Samples were prepared with varying ratios of 4,40 -methylene diphenyl diisocyanate (MDI) and 1,4-butanediol (BDO) to polytetrahydrofuran (PTHF) and annealed at temperatures T a between RT–140 °C for 20 h each. Distinct populations of smaller and larger ordered domains are distinguished by pair distribution func tion analysis. The intermediate-range order of nanoscale hard domains in the paracrystalline state (form I) is directly extracted and characterized. The results suggest that form I of the MDI-BDO:PTHF system presents a conformational and packing order similar to the form III structure, typically obtained from stretching/annealing, but with limited spatial coherence of 3–7 nm. Heating above T g of the hard segments is necessary to achieve a substantial structural response from the annealing treatment. Increasing T a promotes purification of the soft phase via microphase segregation, coalescence of the hard blocks, and growth of paracrystalline phase, while a minority fraction of longer-range ordered domains left over from production remains relatively constant. We observe a composition-dependent decrease in the average nearest-neighbor dis tance that can be correlated with the greater number of C C, C N, and C O bonds with increased hard segment content. A non-linear deviation in the trend is observed to correlate with sample densification. The mechanical and thermal behavior of the samples is intimately tied to the segregation state.

processing-structure-properties↗

DOE OSTI2024

From optimal observables to machine learning: an effective-field-theory analysis of e + e − → W + W − at future lepton colliders

We apply machine-learning techniques to the effective-field-theory analysis of the e + e − → W + W − processes at future lepton colliders, and demonstrate their advantages in comparison with conventional methods, such as optimal observables. In particular, we show that machine-learning methods are more robust to detector effects and backgrounds, and could in principle produce unbiased results with sufficient Monte Carlo simulation samples that accurately describe experiments. This is crucial for the analyses at future lepton colliders given the outstanding precision of the e + e − → W + W − measurement (~ 10−4 in terms of anomalous triple gauge couplings or even better) that can be reached. Our framework can be generalized to other effective-field-theory analyses, such as the one of e + e − → t t ¯ or similar processes at muon colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗