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DOE OSTI2020

Multi-resolution, Multi-scale Modeling for Scalable Macroalgae Production

Macroalgae harvested along coastlines and in the open ocean has traditionally been used as food for human consumption, animal feed, and fertilizer. The U.S. ARPA-E MARINER Program estimates that the nation has suitable conditions and geography to produce at least 500 million dry metric tons of macroalgae per year, yielding approximately 2.7 quadrillion BTUs of energy in the form of liquid fuel, which is roughly 10% of the nation’s annual transportation energy demand. Adverse environmental effects of nutrient overload and ocean acidification may also be reduced by large-scale macroalgae cultivation in many coastal ocean regions. However, the successful deployment of large-scale marine macroalgae farms for fuel production depends on ambient hydrodynamic conditions and nutrient availability, as well as their interactions with macroalgae farm structures. Pacific Northwest National Laboratory led an ARPA-E MARINER project to develop a set of numerical modeling tools capable of simulating ocean hydrodynamic and biogeochemical processes, macroalgae trajectories for free-floating systems, macroalgae growth and biomass yields, and hydrodynamic load on macroalgae canopies and farm structures using a multi-resolution and multi-scale approach. This set of modeling tools provides a suite of information essential for system design, optimal project siting, risk analysis, and management of macroalgae production systems in the ocean. Better clarity can also help macroalgae system developers reduce deployment costs, operational risk, and potential impacts on the local marine environment.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2014

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

General circulation models↗

DOE OSTI2018

Sesame-style decomposition of KS-DFT molecular dynamics for direct interrogation of nuclear models

A common paradigm used in the construction of equations of state is to decompose the thermodynamics into a superposition of three terms: a static-lattice cold curve, a contribution from the thermal motion of the nuclei, and a contribution from the thermal excitation of the electrons. While statistical mechanical models for crystals provide tractable framework for the nuclear contribution in the solid phase, much less is understood about the nuclear contribution above the % melt temperature $(C^{(nuc)}_ν≈3R)$ and how it should transition to the high-temperature limit $(C^{(nuc)}_ν\sim\frac{3}{2}R)$. Here, we describe an algorithm for extracting both the thermal nuclear and thermal electronic contributions from quantum molecular dynamics (QMD) simulations. We then use the VASP QMD package to probe thermal nuclear behavior of liquid aluminum at normal density to compare the results to semi-empirical models – the Johnson generic model, the Chisolm high-temperature liquid model, and the CRIS model. The thermal electronic energy is also calculated from the VASP results and compared to the Kohn-Sham calculations from QE-DFT simulations, Green’s function average atom calculations, and the Thomas-Fermi atomic model.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

Application of Machine Learning to Predict the Response of the Liquid Mercury Target at the Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is currently the most powerful accelerator-driven neutron source in the world. The intense proton pulses strike on SNS’s mercury target to provide bright neutron beams, which also leads to severe fluid-structure interactions inside the target. Prediction of resultant loading on the target is difficult particularly when helium gas is intentionally injected into mercury to reduce the loading and mitigate the pitting damage on the target’s internal walls. Leveraging the power of machine learning and the measured target strain, we have developed machine learning surrogates for modeling the discrepancy between simulations and experimental strain data. We then employ these surrogates to guide the refinement of the high-fidelity mercury/helium mixture model to predict a better match of target strain response.

Lin, Lianshan↗

DOE OSTI2022

Molecular simulation of glycerol-derived triether podands for lithium ion solvation

Solvate ionic liquids (ILs) are promising candidates for several applications due to their stability, high coulombic efficiency, and low volatility. In this work, we investigate the solvation of lithium-bistriflimide by different glycerol-derived triether solvents, using molecular dynamics simulations. Very strong interactions between Li + and the solvent oxygen sites are found, leading to significant conformational changes in the solvent. Here, by comparing the conformation of the neat solvents with their IL mixtures at different concentrations and temperatures, we find that the presence of Li + induces a distinct crown-like structure in the solvent molecules. The Li + cations and the surrounding solvent form a podand complex, which is stable even at elevated temperatures. These glycerol-derived solvents exhibit distinct interactions with Li + cations which may be exploited in electrolytic applications or lithium recovery processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1985

Cirrus clouds. I - A cirrus cloud model. II - Numerical experiments on the formation and maintenance of cirrus

A simplified cirrus cloud model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus cloud. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on cloud-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus cloud are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of cloud-scale processes in determining the cloud properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the cloud. It is shown that cirrus clouds operate in an entirely different manner than liquid phase stratiform clouds.

Starr, D. OC.↗

DOE OSTI2022

Use of Novel Diglycolamide Extractants in Liquid-liquid Separations of Light Rare Earths

Creation of a novel extractant that can improve rare earth separations both economically and environmentally will be pivotal for industry progression. Diglycolamide (DGA) extractants provide chemistries that support this goal by serving as an extractant with high affinity for lanthanides and improved separation factors for light rare earths as compared to current extractants like PC88A. Initial organic phase loading capacity and phase dispersion tests performed with various modified DGAs generated results that were unfavorable for industrial processing, but further modification of the DGA alkyl chain substituents have resulted in new structures with promising results. Dispersion time measurements taken in small scale batch contacts of the extractant with a simulated leach liquor containing La, Ce, Nd, and Pr support implementation in both mixer-settlers and centrifugal contactors for larger scale separations. Furthermore, this confirmation allowed for preliminary flowsheet design using extraction equilibria at various organic to aqueous flow ratios (O/A) for extraction, scrubbing, and stripping stages. These values along with expected product/effluent compositions for each section aid in the testing for specific distribution ratios and final flowsheet design. Implementation of the DGA extractant into solvent extraction equipment will provide essential information for the next steps of this project and how this extractant may be optimized for future applications.

42 ENGINEERING↗

DOE OSTI2022

Flexible cryogenic air separation unit—An application for low-carbon fossil-fuel plants

In this study, the rapid integration of intermittent renewable sources into the electricity grid is driving the need for a flexible cryogenic air separation unit (ASU) coupled with a low-carbon fossil-fuel plant. However, the state-of-the-art ASU process is highly integrated and nonlinear, which can significantly restrict its ramping rate. In this work, we study the fundamental dynamics of a state-of-the-art double-column ASU, focusing on the dynamic characteristics of the highly integrated and nonlinear heat and mass transfers, and we propose basic control methods for achieving high process ramping rates. We found that the vapor–liquid countercurrent flows in the low-pressure column are critical to the cryogenic rectification of air, which governs the ramp rate of the ASU. This countercurrent flow structure is created through a complex heat integration process in the ASU. Here, this process is simplified as a countercurrent heat transfer to reduce the complexity of studying the ASU dynamics. To preserve this flow structure, the heat integration is maintained so that its heat duty follows the ASU load, using several basic controllers on the critical stream flowrates. A flow-driven dynamic ASU model is built in Aspen Plus Dynamics to capture the basic ramping dynamics. This model revealed a fundamental mismatch in the dynamics in the ASU column that causes a significant loss of O 2 product purity when ramping down the ASU and slightly increases the purity when ramping up. Based on these findings, we propose a basic control method for rapidly ramping down/up the ASU while maintaining O 2 product purity. Simulation results show the ASU basic dynamic process successfully ramps at a rate up to 10 %/min (40–100 % load) while maintaining the O 2 product purity at 95.2–95.6 mol%.

42 ENGINEERING↗

DOE OSTI2017

Stern Layer Structure and Energetics at Mica-Water Interfaces

The screening of surface charge by dissolved ions at solid liquid interfaces in the region of interfacial fluid known as the electrical double layer (EDL)-plays a recurrent role in surface science, from ion adsorption to colloidal mechanics to the transport properties of nanoporous media. A persistent unknown in theories of EDL-related phenomena is the structure of the Stern layer, the near-surface portion of the EDL where water molecules and adsorbed ions form specific short-range interactions with surface atoms. Here, we describe a set of synchrotron X-ray reflectivity (XRR) experiments and molecular dynamics (MD) simulations carried out under identical conditions for a range of 0.1 M alkali chloride (Li-, Na-, K-, Rb-, or CsCl) solutions on the basal surface of muscovite mica, a mineral isostructural to phyllosilicate clay minerals and one of the most widely studied reference surfaces in interfacial science. Our XRR and MD simulation results provide a remarkably consistent view of the structure and energetics of the Stern layer, with some discrepancy on the fraction of the minor outer-sphere component of Rb and on the adsorption energetics of Li. The results of both techniques, along with surface complexation model calculations, provide insight into the sensitivity of water structure and ion adsorption to surface topography and the type of adsorbed counterion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Hydrophobic Solvation of Gases (CO 2 , CH 4 , H 2 , Noble Gases) in Clay Interlayer Nanopores

In the past few years, experimental studies have shown that CO 2 is roughly 5 times more soluble in water-saturated clay interlayer water than in bulk liquid water. The fundamental basis of this selectivity remains unknown, as does its relevance to other gases. Here, we use molecular dynamics (MD) simulations and gravimetric adsorption experiments to determine the solubilities of CO 2 , CH 4 , H 2 , and noble gases in clay interlayer water. Our results confirm that clay minerals, despite their well-known hygroscopic nature, have a significant hydrophobic character at the atomistic scale. The affinity of dissolved gases for the clay surface shows significant variations related to the size and shape of the adsorbing molecules and the structuring of interfacial water by clay surfaces. Our results indicate that dissolved gases likely do not behave as inert tracers in fine-grained sedimentary rocks such as shale and mudstone, as routinely assumed in groundwater hydrology studies. Lastly, our results have implications for the fundamental science of hydrophobic adsorption, for the use of dissolved gases as tracers of fluid migration in the subsurface, and for low-carbon energy technologies that rely on fine-grained sedimentary rocks, such as carbon capture and storage, nuclear energy, and the transition from coal to natural gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Theory of activated glassy dynamics in randomly pinned fluids

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Disentangling cation effects on ion mobility and structure in ionic liquid electrolytes

Ionic liquids (ILs) are low-temperature molten salts, where ion transport is primarily governed by ion–ion interactions. Yet, the impact of organic IL cations on critical electrolyte properties such as ion dissociation and overall transport behavior in lithium-salt-doped ILs remains poorly understood. Moreover, despite their critical role in designing IL-based electrolytes for energy storage applications, ion–ion interactions and ion-specific transport under an applied electrical potential are seldom quantified, largely due to the unique experimental and computational challenges involved. Herein, we compare transport properties obtained using 1 H, 7 Li, and 19 F pulsed-field gradient nuclear magnetic resonance (NMR) and electrophoretic NMR (eNMR) with those measured by electrochemical impedance spectroscopy. Non-equilibrium molecular dynamics (MD) simulations and eNMR confirm the presence of negatively charged [Li(TFSI) n ] (1−n) aggregates that migrate towards the positive electrode, resulting in negative lithium transference numbers. Equilibrium MD simulations reveal a vehicular Li ion transport mechanism facilitated by long-lived aggregates with Li + cations strongly bound to multiple TFSI − anions. Finally, we observe an inverse relationship between the apparent charge of the TFSI − anion in the neat IL, which is dictated by the IL cation, and Li + transport in the salt-doped systems. This highlights the opportunity to tune electrolyte performance by tailoring cation chemistry.

Li-ion batteries↗

DOE OSTI2023

Theory of glide symmetry protected helical edge states in a WTe 2 monolayer

Helical edge states in quantum spin Hall (QSH) materials are central building blocks of topological matter design and engineering. Despite their principal topological protection against elastic backscattering, the level of operational stability depends on manifold parameters such as the band gap of the given semiconductor system in the “inverted” regime, temperature, disorder, and crystal orientation. Here, we theoretically investigate electronic and transport properties of QSH edge states in large gap 1-T' WTe 2 monolayers. We explore the impact of edge termination, disorder, temperature, and interactions on experimentally addressable edge state observables, such as local density of states and conductance. We show that conductance quantization can remain surprisingly robust even for heavily disordered samples because of an anomalously small edge state decay length and additional protection related to the large direct gap allowed by glide symmetry. From the simulation of temperature-dependent resistance, we find that moderate disorder enhances the stability of conductance by localizing bulk states. We evaluate the edge state velocity and Luttinger liquid parameter as functions of the chemical potential, finding prospects for physics beyond linear helical Luttinger liquids in samples with ultraclean and well-defined edges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Critical Factors in Computational Characterization of Hydrogen Storage in Metal–Organic Frameworks

Inconsistencies in high-pressure H2 adsorption data and a lack of comparative experiment–theory studies have made the evaluation of both new and existing metal–organic frameworks (MOFs) challenging in the context of hydrogen storage applications. In this work, we performed grand canonical Monte Carlo (GCMC) simulations in nearly 500 experimentally refined MOF structures to examine the variance in simulation results because of the equation of state, H 2 potential, and the effect of density functional theory structural optimization. We find that hydrogen capacity at 77 K and 100 bar, as well as hydrogen 100-to-5 bar deliverable capacity, is correlated more strongly with the MOF pore volume than with the MOF surface area (the latter correlation is known as the Chahine’s rule). The tested methodologies provide consistent rankings of materials. In addition, four prototypical MOFs (MOF-74, CuBTC, ZIF-8, and MOF-5) with a range of surface areas, pore structures, and surface chemistries, representative of promising adsorbents for hydrogen storage, are evaluated in detail with both GCMC simulations and experimental measurements. Simulations with a three-site classical potential for H 2 agree best with our experimental data except in the case of MOF-5, in which H 2 adsorption is best replicated with a five-site potential. However, for the purpose of ranking materials, these two choices for H 2 potential make little difference. Here more significantly, 100 bar loading estimates based on more accurate equations of state for the vapor–liquid equilibrium yield the best comparisons with the experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗

DOE OSTI2016

Vibrational spectroscopic, structural and nonlinear optical activity studies on 6-aminonicotinamide: A DFT approach

The conformational analysis was carried out for 6-aminonicotinamide (ANA) using potential energy surface scan method and the most stable optimized conformer was predicted. The theoretical vibrational frequencies were calculated for the optimized geometry using DFT/B3LYP cc-pVQZ basis set by Gaussian 09 Program. The vibrational frequencies were assigned on the basis of potential energy distribution calculation using VEDA 4.0 program. The Mulliken atomic charge values were calculated. In the Frontier molecular orbitals analysis, the molecular reactivity, kinetic stability, intermolecular charge transfer studies and the related molecular properties were calculated. The ultraviolet-visible spectrum was simulated for both in the gas phase and liquid phase (ethanol) and the π to π* electronic transition was predicted. The nonlinear optical (NLO) activity was studied by means of the first order hyperpolarizability value, which was 8.61 times greater than the urea and the natural bond orbital analysis was also performed to confirm the NLO activity of the molecule. Hence, the ANA molecule is a promising candidate for the NLO materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Review of Tools for Modeling Core Radial Expansion in Liquid Metal-Cooled Fast Reactors

Core radial expansion in liquid-metal cooled fast reactor systems is a well-known phenomenon that produces strong reactivity feedback effects. It is crucial from a safety standpoint to design a reactor with the proper core restraint system to guide expansion of the fuel assemblies into a formation that produces negative reactivity feedback in accident conditions. However, the modeling of core radial expansion and its associated reactivity feedback is extremely challenging. Liquid metal-cooled fast reactor designers (both industry and commercial) have pointed to improved modeling of core radial expansion as a key modeling challenge for these types of reactors. The Department of Energy Nuclear Energy Advanced Modeling and Simulation (DOE-NEAMS) program has an important role to play in helping to develop a robust, predictive tool for this phenomenon. A literature review has been performed to identify current simulation capabilities applicable to the prediction of core radial expansion in liquid metal-cooled fast reactors and the resultant reactivity feedback effects. An overview as well as a detailed description of the multi-physics phenomena underlying core radial expansion is given in the first two chapters. The objective of this report is to identify existing software that has been or could be applied to the core radial expansion problem, and then to identify possible paths to develop a robust, coupled Multiphysics tool for advanced analysis, in which all three physics (radiation transport, structural mechanics, thermal fluids) are taken into account considering feedback effects from each physics to the other. Several computer codes and workflows have been developed in the United States and abroad to perform individual aspects of radial expansion calculations or to perform loosely coupled analysis. No code system currently exists which tightly and robustly couples the neutronics, thermal hydraulics, and thermal mechanical physics with enough detail to fully resolve the complex core radial expansion reactivity feedback effects. The future availability of such a code system is of vital importance to fully understanding the reactivity feedback effects that occur due to radial expansion, and consequently to optimizing the design of the core restraint system. A potential code development path forward using MOOSE-based tools is suggested in order to leverage the natural tight coupling and robustness of MOOSE-based applications. Additionally, potential gaps for modeling and common assumptions are listed which require further investigation to ensure accuracy for prediction of deformations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗