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At least 1,639 records · Page 91

Tank 11H Low Temperature Aluminum Dissolution and Inhalation Dose Potential Analyses at Savannah River Site – 26018

Currently, there is approximately 34 million gallons of high-level radioactive tank waste in the Tank Farm at the Savannah River Site (SRS). The ultimate goal of operations at the Tank Farm is to remove the high level waste (HLW) from the tanks followed by stabilization of the waste through vitrification of the HLW into glass or grouting the decontaminated waste into saltstone. After bulk removal of the HLW consisting of sludge, saltcake, and supernatant, further efforts are made to reduce the residual waste present in the tank in order to declare preliminary cease waste removal (PCWR) signifying completion of HLW removal. These reduction efforts can include tank washing to remove soluble salts and radioisotopes and dissolution of solids including aluminum. Aluminum in the form of gibbsite and boehmite is relatively insoluble in water. Through addition of aqueous sodium hydroxide, the aluminum can be dissolved at mild temperatures. In order for the waste tank to meet closure mode requirements of the Concentration, Storage, and Transfer Facilities (CSTF), which includes the Tank Farm, Documented Safety Analysis (DSA), a component of the safety basis, the inhalation dose potential (IDP) and the radiolytic hydrogen generation rate of the stored waste must be demonstrated to be lower than their respective designated limits. These parameters are calculated from measured radiochemical analyses of isotopes that emit a high amount of radioactivity including Cs-137, Sr-90, Pu-238, Pu-239, Pu-240, Pu-241, Am-241, and Cm-244. Following the low temperature aluminum dissolution (LTAD) process, Tank 11H slurry samples were pulled from the tank and sent to Savannah River National Laboratory (SRNL) to measure the extent of aluminum dissolution, hydroxide concentration, densities of slurry and supernatant, weight percent solids analyses, and radionuclide activities. The analyses of the composite sample found that approximately 90% of the total aluminum in the slurry was dissolved, indicating successful reduction of the insoluble aluminum in the waste tank. Additionally, the weight percent insoluble solids (slurry basis) measurement of the composite sample was found to be approximately 1%, demonstrating that minimal solids still remain in the tank. Finally, the radiochemical analyses of the composite sample determined that the waste contents of the tank met the IDP and radiolytic hydrogen generation rate requirements of the CSTF DSA. These measurements have shown that the LTAD process in Tank 11H was successful in waste reduction efforts and a positive step towards declaring PCWR and tank closure at SRS.

Dekarske, John [Savannah River National Laboratory↗

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

54 ENVIRONMENTAL SCIENCES↗

Stellar Populations in type Ia supernova host galaxies at intermediate-high redshift: Star formation and metallicity enrichment histories

ABSTRACT We present a summary of our project that studies galaxies hosting type Ia supernova (SN Ia) at different redshifts. We present Gran Telescopio de Canarias (GTC) optical spectroscopy of six SN Ia host galaxies at redshift z ∼ 0.4–0.5. They are joined to a set of SN Ia host galaxies at intermediate-high redshift, which include galaxies from surveys SDSS and COSMOS. The final sample, after a selection of galaxy spectra in terms of signal-to-noise and other characteristics, consists of 680 galaxies with redshift in the range 0.04 < z < 1. We perform an inverse stellar population synthesis with the code fado to estimate the star formation and enrichment histories of this set of galaxies, simultaneously obtaining their mean stellar age and metallicity and stellar mass. After analysing the correlations among these characteristics, we look for possible dependencies of the Hubble diagram residuals and supernova features (luminosity, colour and strength parameter) on these stellar parameters. We find that the Hubble residuals show a clear dependence on the stellar metallicity weighted by mass with a slope of −0.061 mag dex−1, when represented in logarithmic scale, log 〈ZM/Z⊙〉. This result supports our previous findings obtained from gas oxygen abundances for local and SDSS-survey galaxies. Comparing with other works from the literature that also use the stellar metallicity, we find a similar value, but with more precision and a better significance (2.08 versus ∼ 1.1), due to the higher number of objects and wider range of redshift of our sample.

Millán-Irigoyen, I. (ORCID:0000000341155140)↗

Suppression of ferromagnetism governed by a critical lattice parameter in CeTiGe 3 with hydrostatic pressure or V substitution

We combine structural and magnetic measurements to compare the different magnetic phase diagrams between the pressure and substitution studies in CeTiGe 3 . We report on the structural, magnetic, and electrical transport properties of single crystals of CeTi 1–x V x Ge 3 (x = 0, 0.1, 0.2, 0.3, 0.4, 0.9, and 1), and of polycrystalline samples (x = 0.5, 0.6, 0.7, 0.8), as well as structural properties of CeTiGe 3 under pressure up to 9 GPa. The ferromagnetic ordering in CeTiGe 3 is suppressed with V doping in CeTi 1–x V x Ge 3 , and suggests a possible ferromagnetic quantum critical point near x = 0.45. We perform a detailed crystalline electric field (CEF) analysis, and the magnetic susceptibility data in pure CeTiGe 3 and CeVGe 3 can be well explained by the CEF model. The proposed CEF energy levels suggest that there is a gradual change of the ground state from |±5/2 in CeTiGe 3 to |±1/2 in CeVGe 3 , and a suppression of CEF splitting energies near the quantum critical region. When hydrostatic pressure is used instead of chemical substitution, the quantum critical point is avoided by the appearance of magnetic phases above around 4.1 GPa. In the substitution study, the ferromagnetic and antiferromagnetic regions are well separated, whereas they touch in the pressure study. We observe a different trend in the temperature dependence of the resistivity maximum in both studies, suggesting that the CEF splitting energy is suppressed by V substitution but enhanced by pressure. Here, we also observe different responses in lattice constants between the two studies, highlighting the fact that substitution effects cannot be reduced to chemical pressure effects only. Nevertheless, when the magnetic phase diagrams of both hydrostatic pressure and substitution are compared, we find a common critical lattice constant c = 5.78 Å where the ferromagnetic ordering is suppressed in both studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

Elucidating the effect of preheating temperature on melt pool morphology variation in Inconel 718 laser powder bed fusion via simulation and experiment

In laser powder bed fusion (L-PBF) additive manufacturing, the mechanical performance, microstructure and defects of fabricated parts are closely associated with the melt pool morphology, e.g., its dimension and shape through the building process. Past studies have largely focused on how the process parameters such as laser power and scan speed affect melt pool characteristics. In this study, the melt pool morphology variation as a function of preheating temperature in the conduction, transition, and keyhole regimes and the underlying mechanisms in each regime are investigated through ex-situ sample characterization and computation thermal fluid dynamics (CtFD) simulation. Single tracks with different combinations of laser power and scan speed are deposited on an Inconel 718 bare plate preheated to a temperature range of 100–500 °C in the experiment. Significant changes are observed in melt pool morphology as a function of preheating temperature from optical measurements of melt track cross sections. The depth of melt pool in the three regimes increases monotonically with preheating temperature, e.g., at 500 °C, the experimental melt pool depth is increased by 49% in conduction regime, 34% in transition regime and 33% in keyhole regime, respectively, while the variation of melt pool width in each regime does not all follow an increasing trend but depends on the melt pool regimes. Melt pool width variation in the conduction and transition regimes is found to depend on the enhanced heat conduction directly related to temperature dependent thermal properties. Through validated CtFD simulations, it is found that in the keyhole regime the evaporation mass, recoil pressure, and laser drilling effect is enhanced with higher preheating temperature, which gives rise to a deeper melt pool. The simulations also reveal that preheating temperature significantly elongates the melt track length due to the increased flow rate and strong recoil pressure that accelerates the backward flow.

36 MATERIALS SCIENCE↗

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗

Effect of lattice orientation on compressive properties of selective laser sintered nylon lattice coupons

As AM lattices become more popular in medical devices, it is important to consider how lattice design parameters affect the mechanical integrity and performance of a device. This research investigated the effect of lattice orientation on the compressive mechanical response of five common lattice geometries: Hexagonal Honeycomb (Hex), Diamond, Voronoi Tessellation Method (VTM), sheet-based Gyroid, and Face-Centered-Cubic (FCC). Samples were tested at two relative densities and eight orientations, printed in Nylon 12 (PA2200) on an EOS P396. The mechanical response was compared to simulated finite element analysis (FEA) response for Hex and FCC lattices. Hex lattices displayed significant orientation dependance. Diamond lattices demonstrated some orientation dependance when at a lower relative density. Gyroid, FCC, and VTM all displayed minimal orientation dependance. Increasing lattice relative density appeared to reduce anisotropy among tested orientations of all lattice geometries except Hex. FEA simulations were able to produce a trend response that matched the mechanical response trends based on the investigated orientations. Furthermore, these results support the need for multi axial lattice mechanical test considerations. It also bolsters the need for lattice FEA models to have a sufficient comparator when identifying “worst-case” lattice test scenarios.

36 MATERIALS SCIENCE↗

Multimodal Nanoscale Mapping of Local Structure and CO 2 Adsorption in Metal–Organic Frameworks

Diamine functionalization of the metal−organic framework Mg 2 (dobpdc) (dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) significantly enhances its selectivity for CO 2 capture from flue gases and air. The structure and CO 2 capacity of such materials are typically assessed using bulk techniques that rely on averaging signal over large ensembles of unit cells, obscuring local heterogeneities, such as variations in CO 2 occupancy across individual nanocrystals. To resolve this limitation, we demonstrate a multimodal, nanoscale characterization of Mg 2 (dobpdc) appended with 1,3-diaminopropane. By employing recently developed characterization techniques at progressively smaller length scales, we uncover insights from correspondingly smaller populations of unit cells. First, we use parallel-beam 3D electron diffraction (3D ED) to identify a prominent expansion in lattice parameters upon desorption of CO 2 , as observed at the level of single nanocrystals. Second, we use convergent-probe 4D scanning transmission electron microscopy (4D-STEM) to quantify associated differences in lattice strain as a function of gas loading and diamine appending. These measurements sample small subvolumes within individual nanocrystals. Finally, we apply infrared scattering scanning near-field optical microscopy (IR s- SNOM) to confirm variable CO 2 chemisorption across adsorption sites at the surface of single nanocrystals. This multimodal, multiscale approach allows us to map heterogeneity within individual nanocrystals. Collectively, these findings emphasize the importance of local, nanoscale characterization of metal−organic frameworks in revealing previously unresolvable features that impact their performance.

Karstens, Sarah L. [University of California, Berk↗

Dimensionality crossover to a two-dimensional vestigial nematic state from a three-dimensional antiferromagnet in a honeycomb van der Waals magnet

The effects of fluctuations and disorder, which are substantially enhanced in reduced dimensional-ities, can play a crucial role in producing nontrivial phases of matter such as vestigial orders char-acterized by a composite order parameter. However, fluctuation-driven magnetic phases in low dimensions have remained relatively unexplored. Here we demonstrate a phase transition from the zigzag antiferromagnetic order in the three-dimensional bulk to a Z 3 vestigial Potts-nematicity in two-dimensional few-layer samples of van der Waals magnet NiPS 3 . Our spin relaxometry and op-tical spectroscopy measurements reveal that the spin fluctuations are enhanced over the gigahertz to terahertz range as the layer number of NiPS 3 reduces. Monte Carlo simulations corroborate the experimental finding of 3-fold rotational symmetry breaking, but show that translational symmetry is restored in thin layers of NiPS 3 . Furthermore, our results show that strong quantum fluctuations can stabilize an unconventional magnetic phase after destroying a more conventional one.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-pressure high-temperature synthesis and characterization of B 10 C

The boron-rich boron carbide materials have been traditionally synthesized by adding boron powder to B 4 C material and subjecting it to hot pressing sintering for materials composition containing 8.8–20 at. % carbon in boron (composition range of B 10.4 C to B 4 C). Our study explores a synthesis route for B 10 C starting from high-purity boron and carbon and direct conversion under high pressure and high temperature (HPHT) conditions of 2000 °C and 6–8 GPa. Synthesis was verified via x-ray diffraction analysis, showing the conversion of the high-purity boron and carbon powder mixture into a hexagonal B 10 C structure (R-3m space group) with lattice parameters of a = b = 5.6115 Å and c = 12.197 Å. The concentration of boron was measured through x-ray photoelectron spectroscopy, confirming the B 10 C ratio. The measured nanoindentation mean hardness of B 10 C was 40 GPa. Raman spectroscopy of the HPHT synthesized sample shows characteristic vibrational breathing modes of boron icosahedron and an additional intense band at a vibrational frequency of 380 cm –1 . This Raman band, which appears notably weaker in earlier studies and B 4 C samples, is assigned to the linear chain of B–B–B and attributed to the maximal incorporation of boron within the hexagonal structure.

36 MATERIALS SCIENCE↗

Wavelet flow for extragalactic foreground simulations

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian statistical distributions is increasingly important for optimal information extraction, particularly given the low-noise observations from current and upcoming experiments. Here, we explore the use of Wavelet Flow (WF) models to tackle the novel task of modeling the field-level probability distributions of multi-component CMB secondaries and foregrounds. Specifically, we jointly train correlated CMB lensing convergence (κ) and cosmic infrared background (CIB) maps with a WF model and obtain a network that statistically recovers the input to high accuracy — the trained network generates samples of κ and CIB fields whose average power spectra are within a few percent of the inputs across all scales, and whose Minkowski functionals are similarly accurate compared to the inputs. Leveraging the multiscale architecture of these models, we fine-tune both the model parameters and the priors at each scale independently, optimizing performance across different resolutions. These results demonstrate that WF models can accurately simulate correlated components of CMB secondaries, supporting improved analysis of cosmological data. Our code and trained models can be found on this GitHub repo.

cosmological simulations↗

Parametric description of intermittent probability distribution functions in solar wind and magnetohydrodynamic turbulence

ABSTRACT In this work, we find empirical evidence that the scale-dependent statistical properties of solar wind and magnetohydrodynamic (MHD) turbulence can be described in terms of a family of parametric probability distribution functions (PDFs) known as Normal Inverse Gaussian (NIG). Understanding these PDFs is one of the most important goals in turbulence theory, as they are inherently connected to the intermittent properties of solar wind turbulence. We investigate the properties of PDFs of Elsasser increments based on a large statistical sample from solar wind observations and high-resolution numerical simulations of MHD turbulence. In order to measure the PDFs and their corresponding properties, three experiments are presented: fast and slow solar wind for experimental data and a simulation of reduced MHD (RMHD) turbulence. Conditional statistics on a 23-yr-long sample of WIND data near 1 au and high-resolution pseudo-spectral simulation of steadily driven RMHD turbulence on a $2048^3$ mesh are used to construct scale-dependent PDFs. The empirical PDFs are fitted to NIG distributions, which depend on four free parameters. Our analysis shows that NIG distributions accurately capture the evolution of the PDFs, with scale-dependent parameters, from large scales characterized by a Gaussian distribution, turning to exponential tails within the inertial range and stretched exponentials at dissipative scales. We also show that empirically-measured NIG parameters exhibit well-defined scaling properties that are similar across the three empirical data sets, which may be indicative of universal behaviour.

Astronomy & Astrophysics↗

A strong blend in the morning: studying the circumgalactic medium before cosmic noon with strong, blended Ly α forest systems

ABSTRACT We study of the properties of a new class of circumgalactic medium absorbers identified in the Ly α forest: ‘Strong, Blended Lyman-α’ (or SBLA) absorption systems. We study SBLAs at 2.4 < z < 3.1 in SDSS-IV/eBOSS spectra by their strong extended Ly α absorption complexes covering 138 $\, \, {\rm km}\, {\rm s}^{-1}$ with an integrated $\log (N_{\rm H\, {\small I}}/\mathrm{cm}^{-2}) =16.04$$\substack{+0.05 \\ -0.06}$ and Doppler parameter b = 18.1$\substack{+0.7 \\ -0.4}$$\, \, {\rm km}\, {\rm s}^{-1}$. Clustering with the Ly α forest provides a large-scale structure bias of b = 2.34 ± 0.06 and halo mass estimate of $M_h \approx 10^{12}\, h^{-1}\, {\rm M_{\odot }}$ for our SBLA sample. We measure the ensemble mean column densities of 22 metal features in the SBLA composite spectrum and find that no single-population multiphase model for them is viable. We therefore explore the underlying SBLA population by forward modelling the SBLA absorption distribution. Based on covariance measurements and favoured populations we find that ≈25 per cent of our SBLAs have stronger metals. Using silicon only we find that our strong metal SBLAs trace gas with a log (nH/cm−3) > −2.40 for T = 103.5 K and show gas clumping on <210 parsec scales. We fit multiphase models to this strong subpopulation and find a low ionization phase with nH = 1 cm−3, T = 103.5 K, and [X/H] = 0.8, an intermediate ionization phase with log (nH/cm−3) = −3.05, T = 103.5 K and [X/H] = −0.8, and a poorly constrained higher ionization phase. We find that the low ionization phase favours cold, dense super-solar metallicity gas with a clumping scale of just 0.009 parsecs.

Morrison, Sean (ORCID:0000000267702627)↗

Predicting microstructurally sensitive fatigue‐crack path in WE43 magnesium using high‐fidelity numerical modeling and three‐dimensional experimental characterization

Abstract Microstructurally small fatigue‐crack growth in polycrystalline materials is highly three‐dimensional due to sensitivity to local microstructural features (e.g., grains). One requirement for modeling microstructurally sensitive crack propagation is establishing the criteria that govern crack evolution, including crack deflection. Here, a high‐fidelity finite‐element modeling framework is used to assess the performance and validity of various crack‐growth criteria, including slip‐based metrics (e.g., fatigue‐indicator parameters), as potential criteria for predicting three‐dimensional crack paths in polycrystalline materials. The modeling framework represents cracks as geometrically explicit discontinuities and involves voxel‐based remeshing, mesh‐gradation control, and a crystal‐plasticity constitutive model. The predictions are compared to experimental measurements of WE43 magnesium samples subject to fatigue loading, for which three‐dimensional grain structures and fatigue‐crack surfaces were measured post‐mortem using near‐field high‐energy x‐ray diffraction microscopy and x‐ray computed tomography. Findings from this work are expected to improve the predictive capabilities of simulations involving microstructurally small fatigue‐crack growth in polycrystalline materials.

Engineering↗

Spatiotemporal characterization of the field-induced insulator-to-metal transition

Watching a metal filament grow Resistive switching is a process in which the electrical resistance of a sample changes abruptly in response to a voltage pulse, often by orders of magnitude. This process is at the heart of many neuromorphic computing approaches but visualizing it in both space and time is tricky. del Valle et al . monitored the resistive switching in three different vanadium oxide compounds by measuring time- and space-resolved optical reflectivity (see the Perspective by Hilgenkamp and Gao). A characteristic conducting filament was quickly nucleated on the inhomogeneities in the sample and then propagated due to Joule heating. —JS

Science & Technology - Other Topics↗

Uncertainty analysis for VERA problem 2 using the cell-code Condor v2.8.05

Condor is a cell-level neutronic calculation code that applies multi-group collision probabilities with heterogeneous response coupling method within generic geometry configurations. Under the Condor's code continuous development, the incorporation of up-to-date methodologies and state-of-the-art practices in reactor analysis represents a driving force. In this work, the capabilities of Condor v2.8.05 to develop an uncertainty analysis for realistic PWR-kind fuel assemblies are studied. The Total Monte Carlo approach is applied to quantify the impact of fabrication tolerances in the code's results for reactivity and power distributions, by means of randomly sampled input values using the VERA problem 2 as basis. The VERA problem 2 proposes a series of Westinghouse 2D 17 x 17-type fuel lattices, to be calculated reflected at beginning-of-life without Xe. The configurations correspond to a modern PWR. Selected neutronic parameters from Condor runs are thus analyzed in terms of the observed spread as well as the obtained distributions for the randomly perturbed cases, showing the capability of the code to handle the required input data, as well as its ability to provide valuable insights regarding uncertainty quantification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗