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At least 469 records · Page 26

Shrinkage-induced deformations and creep of structural concrete: 1-year measurements and numerical prediction

Highlights: • Extensive experimental study on drying shrinkage, creep and microcracking of concrete • All specimens prepared from a single batch of ordinary-strength structural concrete • 1st year of measurements of (not only) non-uniformly drying beams with span up to 3-m • The database is downloadable from free-to-use research data repository • Modified MPS model for concrete creep used in blind prediction of all experiments The material models for creep and shrinkage operating on the material point level in FEM are usually intended for challenging complex applications and structures, where the average cross-sectional approach does not suffice. The identification of the growing number of material parameters induced by increasing model capabilities relies on very specific and narrow-oriented yet interconnected experiments which are scarce. The presented comprehensive experiments aim to provide a clearer image of the complicated interaction among the basic phenomena: drying, shrinkage, creep, and microcracking. The cornerstone of this ongoing research is a unique set of 30 partially-sealed unreinforced concrete beams with span 1.75–3.0 m subjected to drying. To minimize material variation, all specimens in this study were cast from a single batch of ordinary strength structural concrete with slag-blended binder. The resulting experimental database will be suitable both for validation and development of the constitutive models.

36 MATERIALS SCIENCE↗

Amino acids as performance-controlling additives in carbonation-activated cementitious materials

This article presents an investigation on the application of amino acids to control the CaCO{sub 3} crystallization in carbonation cured wollastonite composites. It was observed that wollastonite carbonated without any amino acid formed calcite as the primary polymorph of CaCO{sub 3}. In contrast, the use of amino acids as admixtures resulted in the formation of stable amorphous calcium carbonate (ACC), vaterite, and aragonite during the carbonation of wollastonite. The carbonated composites produced with amino acids were observed to have a lower critical pore size, but a higher total porosity, compared to the control batch. Additionally, the utilization of amino acids was observed to increase the flexural strength and compressive strength of the composites up to 106% and 48%, respectively, compared to the control batch. Such performance enhancement of the carbonated composites in the presence of amino acids was attributed to the reduced critical pore size and the formation of organic-inorganic hybrid phases in the matrix.

36 MATERIALS SCIENCE↗

An acidic polysaccharide (AGC3) isolated from North American ginseng ( Panax quinquefolius ) suspension culture as a potential immunomodulatory nutraceutical

Polysaccharides isolated from Panax quinquefolius roots are widely used as nutraceuticals due to their immunomodulatory properties. Despite their popularity, several challenges exist in isolating ginseng root polysaccharides such as batch-to-batch structural inconsistencies and bacterial endotoxin contamination. A plant tissue culture-based platform offers a potential solution to isolate natural polysaccharide fractions with consistent chemical characteristics and reduced endotoxin content. In this study, an acidic polysaccharide fraction (AGC3) with immunomodulatory properties was isolated from Panax quinquefolius suspension cultures. The heterogeneous fraction (molecular weight: 4.81 and 32.14 kDa), purified by anion exchange chromatography, was predominantly composed of galactose (>60%) along with the presence of rhamnose, arabinose, glucose, glucuronic acid and galacturonic acid. The major glycosidic linkages were found to be t-Galp (47.7%), 4-Galp (15.6%), 2,4-Rhap (8.1%), 6-Galp (8.1%) and 4-GalAp (6.8%). Structural analyses indicated the presence of a pectic rhamnogalacturonan I polysaccharide in AGC3. AGC3 significantly (p < 0.05) stimulated RAW 264.7 murine macrophage cells and primary murine splenocytes by enhancing the production of several immunomodulatory mediators such as IL-6, TNF-α, GM-CSF and MCP-1. The results also indicated the putative roles of NF-κB (p65/RelA) and MAPK (p38) signaling pathways in the immunostimulatory response. Additionally, AGC3 induced murine splenocyte proliferation, another major indicator of immunostimulation. Overall, AGC3 has the potential to be used as an immunostimulatory nutraceutical.

59 BASIC BIOLOGICAL SCIENCES↗

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

54 ENVIRONMENTAL SCIENCES↗

Direct internal recycling fractions approaching unity

Direct internal recycling (DIR) refers to the process of recovering pure hydrogen isotopes (D/T) from helium and other impurities in the fusion plasma exhaust and directing them back to the fuel injection system. Increasing the exhaust fraction purified through DIR significantly reduces the size and cost of the tritium plant and provides additional benefits including reduced requirements for both the tritium startup inventory and tritium breeding ratio. Metal foil pumps (MFPs) are the dominant technology for this separation, relying on the concept of superpermeation. We recently demonstrated that PdCu foils operated at low temperature provide both exceptional flux and resilience to helium absorption as the DIR fraction is increased. Herein we design and demonstrate continuous and semi-batch DIR processes using PdCu MFPs. Under continuous processing, stable performance was observed for DIR fractions up to 92 %. In addition, we demonstrate a semi-batch process capable of extending the DIR fraction to unity (> 99.8 %). Under the experimental conditions described within a PdCu MFP area of ~22 m 2 would be sufficient to process the fusion exhaust with 92 % DIR fraction at expected flowrates of 100 Pa·m 3 ·s -1 for a future fusion power plant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗

A combined experimental and modelling study of granite hydrothermal alteration

Geochemical reactions can induce significant changes of rock reservoir porosity and permeability via mineral dissolution and precipitation processes, affecting the long-term fluid behaviour within various geological systems. Here, the understanding and quantification of these reactions rely on field and experimental studies and on the predictions of reactive transport models. The present study was aimed at assessing the extent to which current geochemical models integrating available mineral dissolution/precipitation rate equations can reproduce the experimental data obtained from 4 to 17-day long hydrothermal alteration experiments of a muscovite-biotite granite and, thus, help provide an accurate description of the evolution of geothermal systems within granitic reservoirs. The experiments were conducted at a constant temperature of 180 °C and over an aqueous fluid pH range of 2 to 8.5, using both mixed-flow and static batch reactors. Modelled major element (K, Al, Si, Ca, and Mg) concentrations were generally in satisfactory agreement with the corresponding measured elemental fluxes – the differences between modelled and experimental values were generally within a factor of 5 – and the predicted identity and mass of formed secondary phases were consistent with the microscopic observations of the reacted solids. However, larger differences between measured and modelled element concentrations were observed when significant amounts of secondary phases formed, notably at pH 2 to 3, and for longer-term batch experiments. Much of this concentration difference stems from the underestimation of the amounts of Al-phases formed at acid to near-neutral pH. Although an idealized rock composition was considered, the observed mismatch between model calculations and experimental data can be attributed to inadequate mineral precipitation reaction rates and a poor description of reactive surface areas in existing geochemical modelling codes. More accurate quantification of precipitation kinetics, including nucleation and growth, and improved descriptions of the temporal change of mineral surface area would enhance the predictive capabilities of reactive transport models and benefit, particularly, the efforts aimed at increasing the sustainability of EGS reservoirs.

58 GEOSCIENCES↗

Consequences of product inhibition in the quantification of kinetic parameters

While the potential for product inhibition in catalytic reactions is well known, the impact of neglected inhibition on measured kinetic parameters is often overlooked. The presence of product inhibition, most often caused by the competitive adsorption of products with reactants on catalytic active sites, is difficult to determine a priori for an arbitrary catalytic system. The significance of product inhibition relies on the concentration of the products, their adsorption thermodynamics on catalytically relevant sites, and process parameters such as temperature and pressure. When inhibition is significant, however, apparent activation energies and reaction orders vary from the differential-reactor apparent activation energy by a factor of 1/(1 - δ), where δ is the total inhibition order (e.g., the factor (1 - δ) = 1.6 for a system with product inhibition of -0.6 order). This is illustrated here with the kinetics of NO oxidation over Cu ion clusters (Cu x O y ) in Cu-SSZ-13, for which the product NO 2 inhibits the forward reaction. Furthermore, in the presence of inhibition, when only reactants are fed to a flow reactor or placed in a batch reactor, there is often no practical conversion that is low enough to guarantee differential behavior. Inclusion of products in the feed solves this problem, allowing accurate determination of kinetic parameters such as apparent reaction orders and activation energies. We also demonstrate that evaluation of the necessity of co-feeding products to assure measurement of differential-reactor data in a given catalytic system is straightforward from a plot of the log of the rate (or conversion) versus the log of the space time in a flow reactor or elapsed time in a batch reactor. We encourage inclusion of this test in all kinetic analyses that are reasonably approximated by power law rate expressions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Part II: Predicting performance of $\mathrm{DOWEX 21K}$ resin for remediation of comingled contaminants in groundwater

The selectivity of ion exchange (IX) resins for aqueous contaminant removal can be impacted by changing concentrations of competing natural groundwater ions. In a two-part investigation, the Hanford Site 200 West Area pump-and-treat (P&T) facility in Washington State, USA is used as a case study to evaluate the performance of two IX resins for groundwater treatment: Purolite® A532E for pertechnetate (TcO 4 - ) removal, explored in Part I, and DOWEX 21K (DOWEX) for uranium (U) removal. In Part II, DOWEX selectivity for U, as uranyl carbonate species, and uptake kinetics is quantified in a series of laboratory-scale aqueous batch experiments containing Hanford-relevant concentrations of competing anions nitrate (NO 3 - ), sulfate (SO 4 2- ), chloride (Cl - ), and carbonate (CO 3 2- ), as well as co-mingled contaminant TcO 4 - . Here the results demonstrate that DOWEX trimethylammonium functional groups are highly selective for U carbonate species (85–100 % uptake) under all conditions investigated. Only NO 3 - concentrations of 100 mM were shown to decrease U removal, with the extent (85–99 %) depending on competing anion concentrations present in solution. However, at the highest NO 3 - concentrations reported for groundwaters treated at the P&T facility (25 mM), the effect on U uptake is minimal. The batch sorption results are modeled to obtain chloride normalized equilibrium exchange coefficients (K) for predicting DOWEX performance: K SO4--/Cl- = 2.0, K NO3-/Cl- = 5.0, K HCO3-/Cl- = 1.5, K TcO4-/Cl- = 2,000, and K U/Cl- = 50,000. These K values predict little effect of current and future influent chemistries on U removal by DOWEX, where both uranyl carbonate species and TcO 4 - are removed such that effluent concentrations meet groundwater treatment requirements.

54 ENVIRONMENTAL SCIENCES↗

Simultaneous immobilization of aqueous co-contaminants using a bismuth layered material

The remediation of co-located contaminants in the vadose zone can be challenging due to accessibility and different responses of different contaminants to remedial actions. At the Hanford Site (WA, USA), multiple contaminants are present in the vadose zone and groundwater, including I, Tc, U, Cr, and NO3. We used a bismuth layered oxide in a series of batch experiments to test aqueous removal of multiple contaminants, including Tc, Cr, and U, as well as potentially competing anions, including NO3 and I. The results demonstrated successful removal of all four contaminants (>98% removal from the aqueous phase after 30 days) when tested individually. When contaminants were combined, a slight decrease in Tc removal occurred (-6%). The addition of sediment decreased the removal for Tc and I, but U and Cr removal was unaffected. Competition with anions released from the sediment likely caused the decreased removal of Tc and I and indicated that bismuth is less selective for these two contaminants. The results of these batch tests demonstrated that the bismuth based oxy-hydroxide material is a promising material for sequestering multiple contaminants in situ.

Lawter, Amanda R.↗

Effects of flow on uranium speciation in soils impacted by acidic waste fluids

Radioactive acidic liquid waste is a common byproduct of uranium (U) and plutonium (Pu) enrichment and recycling processes whose accidental and planned release has led to a significant input of U into soils and sediments across the world, including at the U.S. DOE's Hanford site (WA, USA). Because of the particularly hazardous nature of U, it is important to predict its speciation when introduced into soils and sediments by acidic waste fluids. Of fundamental importance are the coupled effects of acid-driven mineral transformation and reactive transport on U speciation. To evaluate the effect of waste-fluid residence time and co-associated dissolved phosphate concentrations on U speciation in impacted soils and sediments, uncontaminated surface materials (from the Hanford Site) were reacted with U-containing synthetic acidic waste fluids (pH 2) amended with dissolved phosphate concentrations in both batch (no flow) and flow-through column systems for 7–365 days. By comparing dissolved U behavior and solid phase speciation as a function of flow regimen, we found that the availability of proton-promoted dissolution products (such as Si) to sequester U into uranyl silicates was dependent on waste fluid-sediment contact time as uranyl silicates were not detected in short contact time flow-through systems but were detected in no-flow, long contact time, reactors. Moreover, the dominance of uranyl phosphate as neoprecipitate U scavenger (principally in the form of meta-ankoleite) in phosphate amended systems confirmed the importance of phosphate amendments for an efficient sequestration of U in the soils and sediments. Overall, our experiments suggest that the formation of uranyl silicates in soils impacted by acidic waste fluids is likely to be limited unless reaction products are allowed to accumulate in soil pores, highlighting the importance of investigating soil U speciation in flow-through, transport-driven systems as opposed to no-flow, batch systems. Finally, this study provides insights into uranium speciation and its potential changes under acidic conditions for better prediction of risks and subsequent development of efficient remediation strategies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Efficient screening of rare large pit anomalies on polished surfaces using a minimalist sampling scheme

Lawrence Livermore National Laboratory (LLNL) has made significant strides in generating clean energy through its inertial confinement fusion (ICF) experiments. These experiments rely on high-density carbon (HDC) coated shells to encapsulate the fusion fuel. The success of these experiments is heavily dependent on the surface quality of these shells, as even minor imperfections, such as deep pits, can negatively impact fusion yield. Ensuring the required smoothness involves an extensive surface-finishing process that spans approximately 20 stages, making it both time-intensive and resource-demanding. A critical challenge in this process is the need for high-resolution scans to detect rare deep pits, which can be costly and impractical if performed on every shell. This highlights the necessity of developing more efficient scanning methods to optimize time and cost without compromising accuracy. To address these challenges, we introduce a novel approach that employs the multivariate Dvoretzky–Kiefer–Wolfowitz (DKW) inequality to provide a probabilistic upper bound on the error in estimating pit distribution characteristics via a Kernel Density Estimator (KDE). This error bound enables efficient and reliable estimation of pit distribution characteristics at a specified statistical confidence level using a minimal number of surface scans. The integrated DKW-KDE approach was validated through surface-finishing experiments across two batches of HDC-coated shells, demonstrating consistent and robust performance across multiple stages of the surface-finishing experiments. The validation studies suggest that the integrated DKW-KDE approach achieves comparable accuracy in estimating the risk of deleterious large pits with six scans, thus conserving time and resources. Further evaluations show that performance remains consistent across batches and over multiple polishing stages. In conclusion, based on these findings, one can leverage the minimal-scan insights to strategically improve the bottleneck inspection process, thus enhancing the productivity and quality of shell polishing and similar challenging manufacturing processes.

Inertial confinement fusion↗

No ball milling needed: Alternative ODS steel manufacturing with gas atomization reaction synthesis (GARS) and friction-based processing

Oxide dispersion strengthened (ODS) steels are promising structural materials for future fusion reactors. The high-density (~10 23 /m 3 ) of highly stable Y-(Ti)-O nano-oxides provide high sink strength for radiation resistance and high-temperature (> 650 °C) creep strength. Concomitantly, helium management is enabled by trapping high density (~10 23 /m 3 ) of small (< 3 nm) helium bubbles in the vicinity of nano-oxides. However, conventional route of making ODS steels involves prolonged ball milling, canning, degassing, and laborious thermo-mechanical processing (TMP). Such route, especially the batch-by-batch ball milling step, faces persistent challenge with scalability and high costs. Gas atomization reaction synthesis (GARS) method has demonstrated the potential of making precursor ODS steel powders without ball milling, but the nano-oxide density was around 10 21 /m 3 in the final consolidated form by conventional TMP. Taking advantage of GARS precursor powder, we use friction-based processing, including friction consolidation and extrusion, to manufacture ODS steel with further improved nano-oxide characteristics. Here, preliminary results showed that Y/Ti/O species were intimately mixed and rapidly reacted to form nano-oxides with a number density of ~10 22 /m 3 .

36 MATERIALS SCIENCE↗

Effect of charge and anisotropic diffusivity on ion exchange kinetics in nuclear waste form materials

Motifs of radionuclide absorption particles (absorbers or fillers) for the nuclear waste treatment usually have crystal structures with nano-sized tunnels for fast ion diffusion. On the other hand, the accumulation of ions generates an electric field which affects the ion diffusion. Therefore, the strong anisotropic kinetic properties and the electric field affect ion exchange kinetics, especially in an assembly of these particles which may block the fast diffusion tunnels for each other. In this work, we developed a mesoscale model to describe the effect of anisotropic kinetic properties and electric field on ion exchange kinetics. With the model we simulated the effect of anisotropic diffusivity, electrochemical potential, particle morphology, size and aggregation on ion exchange kinetics during batch experiments. Here, tt is found that 1) ion exchange results in charge accumulation inside the particle because different ions have different diffusivities and different diffusion driving forces. The electric neutrality is not preserved; 2) the electric field speeds up the slower diffusion ions (either uptake or release) and slows down the faster diffusion ions to reduce charge accumulation and maintains charge neutrality; 3) the ion exchange becomes very slow at the later stages because a) diffusion driving force (electrochemical gradient, Cs + concentration in the solution and Na + inside the particle) continuously decreases, as observed in batch experiments; and b) the diffusivity decreases due to the Cs + concentration dependence of ion diffusivity. This can explain the observed experimental phenomena that the radionuclide capacity usually cannot be reached; 4) for needle-like particle and their clusters, both surface area and diffusion distance along the direction with the fastest diffusivities have significant impact on the ion exchange kinetics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Humidity sensitivity of large area silicon sensors: Study and implications

The production of large area sensors is one of the main challenges that the ATLAS collaboration faces for the new Inner-Tracker full-silicon detector. During the prototype fabrication phase for the High Luminosity Large Hadron Collider upgrade, several ATLAS institutes observed indications of humidity sensitivity of large area sensors, even at relative humidities well below the dew point. Specifically, prototype Barrel and End-Cap silicon strip sensors fabricated in 6-inch wafers manifest a prompt decrease of the breakdown voltage when operating under high relative humidity, adversely affecting the performance of the sensors. In addition to the investigation of these prototype sensors, a specific fabrication batch with special passivation is also studied, allowing for a deeper understanding of the responsible mechanisms. Here we present an extensive study of this behaviour on large area sensors. The locations of the hotspots at the breakdown voltage at high humidity are revealed using different infrared thermography techniques. Several palliative treatments are attempted, proving the influence of sensor cleaning methods, as well as baking, on the device performance, but no improvement on the humidity sensitivity was achieved. Furthermore, a study of the incidence of the sensitivity in different batches is also presented, introducing a hypothesis of the origins of the humidity sensitivity associated to the sensor edge design, together with passivation thickness and conformity. Several actions to be taken during sensor production and assembly are extracted from this study, in order to minimize the impact of humidity sensitivity on the performance of large area silicon sensors for High Energy Physics experiments.

47 OTHER INSTRUMENTATION↗

Second gadolinium loading to Super-Kamiokande

The first loading of gadolinium (Gd) into Super-Kamiokande in 2020 was successful, and the neutron capture efficiency on Gd reached 50%. To further increase the Gd neutron capture efficiency to 75%, 26.1 tons of Gd 2 (SO 4 ) 3 ∙ 8H 2 O was additionally loaded into Super-Kamiokande (SK) from May 31 to July 4, 2022. As the amount of loaded Gd 2 (SO 4 ) 3 ∙ 8H 2 O was doubled compared to the first loading, the capacity of the powder dissolving system was doubled. We also developed new batches of gadolinium sulfate with even further reduced radioactive impurities. In addition, a more efficient screening method was devised and implemented to evaluate these new batches of Gd 2 (SO 4 ) 3 ∙ 8H 2 O. Following the second loading, the Gd concentration in SK was measured to be 333.5 ± 2.5 ppm via an Atomic Absorption Spectrometer (AAS). From the mean neutron capture time constant of neutrons from an Am/Be calibration source, the Gd concentration was independently measured to be 332.7 ± 6.8(sys.) ± 1.1(stat.) ppm, consistent with the AAS result. Furthermore, during the loading the Gd concentration was monitored continually using the capture time constant of each spallation neutron produced by cosmic-ray muons, and the final neutron capture efficiency was shown to become 1.5 times higher than that of the first loaded phase, as expected.

Gadolinium↗

Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations

For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗