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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Benchmarking structural evolution methods for training of machine learned interatomic potentials

When creating training data for machine-learned interatomic potentials (MLIPs), it is common to create initial structures and evolve them using molecular dynamics (MD) to sample a larger configuration space. Here, we benchmark two other modalities of evolving structures, contour exploration (CE) and dimer-method (DM) searches against MD for their ability to produce diverse and robust density functional theory training data sets for MLIPs. We also discuss the generation of initial structures which are either from known structures or from random structures in detail to further formalize the structure-sourcing processes in the future. The polymorph-rich zirconium-oxygen composition space is used as a rigorous benchmark system for comparing the performance of MLIPs trained on structures generated from these structural evolution methods. Using Behler–Parrinello neural networks as our MLIP models, we find that CE and the DM searches are generally superior to MD in terms of spatial descriptor diversity and statistical accuracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A gated graph transformer for protein complex structure quality assessment and its performance in CASP15

Abstract Motivation Proteins interact to form complexes to carry out essential biological functions. Computational methods such as AlphaFold-multimer have been developed to predict the quaternary structures of protein complexes. An important yet largely unsolved challenge in protein complex structure prediction is to accurately estimate the quality of predicted protein complex structures without any knowledge of the corresponding native structures. Such estimations can then be used to select high-quality predicted complex structures to facilitate biomedical research such as protein function analysis and drug discovery. Results In this work, we introduce a new gated neighborhood-modulating graph transformer to predict the quality of 3D protein complex structures. It incorporates node and edge gates within a graph transformer framework to control information flow during graph message passing. We trained, evaluated and tested the method (called DProQA) on newly-curated protein complex datasets before the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) and then blindly tested it in the 2022 CASP15 experiment. The method was ranked 3rd among the single-model quality assessment methods in CASP15 in terms of the ranking loss of TM-score on 36 complex targets. The rigorous internal and external experiments demonstrate that DProQA is effective in ranking protein complex structures. Availability and implementation The source code, data, and pre-trained models are available at https://github.com/jianlin-cheng/DProQA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

SCOPe: improvements to the structural classification of proteins – extended database to facilitate variant interpretation and machine learning

Abstract The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structural and functional insights into the interaction between the bacteriophage T4 DNA processing proteins gp32 and Dda

Abstract Bacteriophage T4 is a classic model system for studying the mechanisms of DNA processing. A key protein in T4 DNA processing is the gp32 single-stranded DNA-binding protein. gp32 has two key functions: it binds cooperatively to single-stranded DNA (ssDNA) to protect it from nucleases and remove regions of secondary structure, and it recruits proteins to initiate DNA processes including replication and repair. Dda is a T4 helicase recruited by gp32, and we purified and crystallized a gp32–Dda–ssDNA complex. The low-resolution structure revealed how the C-terminus of gp32 engages Dda. Analytical ultracentrifugation analyses were consistent with the crystal structure. An optimal Dda binding peptide from the gp32 C-terminus was identified using surface plasmon resonance. The crystal structure of the Dda–peptide complex was consistent with the corresponding interaction in the gp32–Dda–ssDNA structure. A Dda-dependent DNA unwinding assay supported the structural conclusions and confirmed that the bound gp32 sequesters the ssDNA generated by Dda. The structure of the gp32–Dda–ssDNA complex, together with the known structure of the gp32 body, reveals the entire ssDNA binding surface of gp32. gp32–Dda–ssDNA complexes in the crystal are connected by the N-terminal region of one gp32 binding to an adjacent gp32, and this provides key insights into this interaction.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Metastable piezoelectric group-IV monochalcogenide monolayers with a buckled honeycomb structure

Multiple two-dimensional materials are being naïvely termed stable on the grounds of displaying phonon dispersions with no negative frequencies and of not collapsing on molecular dynamics calculations at fixed volume. But, if these phases do not possess the smallest possible structural energy, how does one understand and establish their actual meta stability? To answer this question, twelve two-dimensional group-IV monochalcogenide monolayers (SiS, SiSe, SiTe, GeS, GeSe, GeTe, SnS, SnSe, SnTe, PbS, PbSe, and PbTe) with a buckled honeycomb atomistic structure—belonging to symmetry group P3m1—displaying an out-of-plane intrinsic electric polarization are shown to be metastable by three independent methods. First, we uncover a coordination-preserving structural transformation from the low-buckled honeycomb structure onto the lower-energy Pnm2 1 (or Pmmn for PbS, PbSe, and PbTe) phase to estimate energy barriers E B that must be overcome during such structural transformation. Using the curvature of the local minima and E B as inputs to Kramers escape formula, large escape times are found, implying the structural metastability of the buckled honeycomb phase (with the exception of PbS and PbSe, these phases display escape times ranging from 700 years to multiple times the age of the universe and can be considered “stable” for practical purposes in that relative sense). The second demonstration is provided by phonon dispersion relations that include the effect of long-range Coulomb forces and display no negative vibrational modes. The third and final demonstration of structural metastability is furnished by room-temperature ab initio molecular dynamics for selected compounds. Here, the magnitude of the electronic band gap evolves with chemical composition. Different from other binary two-dimensional compounds such as transition metal dichalcogenide monolayers and hexagonal boron nitride monolayers which only develop an in-plane piezoelectric response, the twelve group-IV monochalcogenide monolayers with a buckled honeycomb structure also display out-of-plane piezoelectric properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Assessment of thermally driven local structural phase changes in 1⁢𝑇′−MoTe 2

The role of layer disorder is important in establishing the topological phases of MoTe 2 . A rich tapestry of atomic ordering influences the structural phase transitions (SPTs), but there is little understanding of the mechanistic details of the phase transition. An atomistic level study was conducted to investigate the local structure of the 1⁢𝑇′ and 𝑇 𝑑 phases of MoTe 2 by using the pair distribution function (PDF) technique. While the average structure exhibits an SPT and coexistence of phases as a function of temperature, the local structure showed the suppression of SPT. The sample retained its monoclinic structure at all temperatures in short-range order. A sharp PDF peak observed at short distances indicated a strong atom-atom correlation between the Mo and Te atoms within the Mo octahedra. In addition, a large-box modeling of the PDF data indicated a preferential motion of Te atoms towards 𝑐 axis at all temperatures. Structural defects, such as stacking faults, likely result in the coexistence of phases in the average structure and suppress the local SPT of MoTe 2 . These results are stepping stones to understand the long-debated origins of structural, vibrational, and electronic properties of MoTe 2 and similar transition metal dichalcogenides.

2-dimensional systems↗
DOE OSTI2023

Decoding structure-spectrum relationships with physically organized latent spaces

Here, a semisupervised machine learning method for the discovery of structure-spectrum relationships is developed and then demonstrated using the specific example of interpreting x-ray absorption near-edge structure (XANES) spectra. This method constructs a one-to-one mapping between individual structure descriptors and spectral trends. Specifically, an adversarial autoencoder is augmented with a rank constraint (RankAAE). The RankAAE methodology produces a continuous and interpretable latent space, where each dimension can track an individual structure descriptor. As a part of this process, the model provides a robust and quantitative measure of the structure-spectrum relationship by decoupling intertwined spectral contributions from multiple structural characteristics. This makes it ideal for spectral interpretation and the discovery of descriptors. The capability of this procedure is showcased by considering five local structure descriptors and a database of >50 000 simulated XANES spectra across eight first-row transition metal oxide families. The resulting structure-spectrum relationships not only reproduce known trends in the literature but also reveal unintuitive ones that are visually indiscernible in large datasets. The results suggest that the RankAAE methodology has great potential to assist researchers in interpreting complex scientific data, testing physical hypotheses, and revealing patterns that extend scientific insight.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multilevel atomic structural model for interstratified opal materials

The structure of opal has long fascinated scientists. It occurs in a number of structural states, ranging from amorphous to exhibiting features of stacking disorder. Opal-CT, where C and T signify cristobalite- and tridymite-like interstratification, represents an important link in the length scales between amorphous and crystalline states. However, details about local atomic (dis)order and arrangements extending to long-range stacking faults in opal polymorphs remain incompletely understood. Here, a multilevel modeling approach is reported that considers stacking states in correlation with the abundance of C and T segments as a high-level structural parameter (i.e. not each atom). Optimization accounting for inter-tetrahedral bond lengths and angles and the regularity of the silicate tetrahedra is included as lower levels of structural parameters. Together, a set of parameters with both coarse-grained and atomistic features for different levels of structural details is refined. Structural disorder at the ~10–100 Å distance scale is evaluated using experimental pair distribution function and diffraction datasets, comparing peak intensities, widths and asymmetry. Here this work presents a complete multilevel structural description of natural opal-CT and explains many of the unusual features observed in X-ray powder diffraction patterns. This modeling approach can be adopted generally for analyzing layered materials and their assembly into 3D structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Complementarity of neutron, XFEL and synchrotron crystallography for defining the structures of metalloenzymes at room temperature

Room-temperature macromolecular crystallography allows protein structures to be determined under close-to-physiological conditions, permits dynamic freedom in protein motions and enables time-resolved studies. In the case of metalloenzymes that are highly sensitive to radiation damage, such room-temperature experiments can present challenges, including increased rates of X-ray reduction of metal centres and site-specific radiation-damage artefacts, as well as in devising appropriate sample-delivery and data-collection methods. It can also be problematic to compare structures measured using different crystal sizes and light sources. In this study, structures of a multifunctional globin, dehaloperoxidase B (DHP-B), obtained using several methods of room-temperature crystallographic structure determination are described and compared. Here, data were measured from large single crystals and multiple microcrystals using neutrons, X-ray free-electron laser pulses, monochromatic synchrotron radiation and polychromatic (Laue) radiation light sources. These approaches span a range of 18 orders of magnitude in measurement time per diffraction pattern and four orders of magnitude in crystal volume. The first room-temperature neutron structures of DHP-B are also presented, allowing the explicit identification of the hydrogen positions. The neutron data proved to be complementary to the serial femtosecond crystallography data, with both methods providing structures free of the effects of X-ray radiation damage when compared with standard cryo-crystallography. Comparison of these room-temperature methods demonstrated the large differences in sample requirements, data-collection time and the potential for radiation damage between them. With regard to the structure and function of DHP-B, despite the results being partly limited by differences in the underlying structures, new information was gained on the protonation states of active-site residues which may guide future studies of DHP-B.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer

Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.

Gao, Mu↗
DOE OSTI2020

Network structure of vertebrate scavenger assemblages at the global scale: drivers and ecosystem functioning implications

The organization of ecological assemblages has important implications for ecosystem functioning, but little is known about how scavenger communities organize at the global scale. Here, we test four hypotheses on the factors affecting the network structure of terrestrial vertebrate scavenger assemblages and its implications on ecosystem functioning. We expect scavenger assemblages to be more nested (i.e. structured): 1) in species-rich and productive regions, as nestedness has been linked to high competition for carrion resources, and 2) regions with low human impact, because the most efficient carrion consumers that promote nestedness are large vertebrate scavengers, which are especially sensitive to human persecution. 3) We also expect climatic conditions to affect assemblage structure, because some scavenger assemblages have been shown to be more nested in colder months. Finally, 4) we expect more organized assemblages to be more efficient in the consumption of the resource. We first analyzed the relationship between the nestedness of the scavenger assemblages and climatic variables (i.e. temperature, precipitation, temperature variability and precipitation variability), ecosystem productivity and biomass (i.e. NDVI) and degree of human impact (i.e. human footprint) using 53 study sites in 22 countries across five continents. Then, we related structure (i.e. nestedness) with its function (i.e. carrion consumption rate). We found a more nested structure for scavenger assemblages in regions with higher NDVI values and lower human footprint. Moreover, more organized assemblages were more efficient in the consumption of carrion. However, our results did not support the prediction that the structure of the scavenger assemblages is directly related to climate. Our findings suggest that the nested structure of vertebrate scavenger assemblages affects its functionality and is driven by anthropogenic disturbance and ecosystem productivity worldwide. Disarray of scavenger assemblage structure by anthropogenic disturbance may lead to decreases in functionality of the terrestrial ecosystems via loss of key species and trophic facilitation processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Signal sequences target enzymes and structural proteins to bacterial microcompartments and are critical for microcompartment formation

ABSTRACT Spatial organization of pathway enzymes has emerged as a promising tool to address several challenges in metabolic engineering, such as flux imbalances and off-target product formation. Bacterial microcompartments (MCPs) are a spatial organization strategy used natively by many bacteria to encapsulate metabolic pathways that produce toxic, volatile intermediates. Several recent studies have focused on engineering MCPs to encapsulate heterologous pathways of interest, but how this engineering affects MCP assembly and function is poorly understood. In this study, we investigated the role of signal sequences, short domains that target proteins to the MCP core, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterized two novel Pdu signal sequences on the structural proteins PduM and PduB, which constitute the first report of metabolosome signal sequences on structural proteins rather than enzymes. We then explored the role of enzymatic and structural Pdu signal sequences on MCP assembly by deleting their encoding sequences from the genome alone and in combination. Deleting enzymatic signal sequences decreased the MCP formation, but this defect could be recovered in some cases by overexpressing genes encoding the knocked-out signal sequence fused to a heterologous protein. By contrast, deleting structural signal sequences caused similar defects to knocking out the genes encoding the full-length PduM and PduB proteins. Our results contribute to a growing understanding of how MCPs form and function in bacteria and provide strategies to mitigate assembly disruption when encapsulating heterologous pathways in MCPs. IMPORTANCE Spatially organizing biosynthetic pathway enzymes is a promising strategy to increase pathway throughput and yield. Bacterial microcompartments (MCPs) are proteinaceous organelles that many bacteria natively use as a spatial organization strategy to encapsulate niche metabolic pathways, providing significant metabolic benefits. Encapsulating heterologous pathways of interest in MCPs could confer these benefits to industrially relevant pathways. Here, we investigate the role of signal sequences, short domains that target proteins for encapsulation in MCPs, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterize two novel signal sequences on structural proteins, constituting the first Pdu signal sequences found on structural proteins rather than enzymes, and perform knockout studies to compare the impacts of enzymatic and structural signal sequences on MCP assembly. Our results demonstrate that enzymatic and structural signal sequences play critical but distinct roles in Pdu MCP assembly and provide design rules for engineering MCPs while minimizing disruption to MCP assembly.

Johnson, Elizabeth R. (ORCID:0000000179236881)↗
DOE OSTI2025

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗
DOE OSTI2021

From Gargamelle to MINERvA: exploring the structure of the nucleon with neutrinos

Neutrino scattering experiments have been exploring the structure of the nucleon with Deep-Inelastic Scattering for over 50 years. Although hints of nucleon structure were available using CERN’s first neutrino beam in the 1960s, the study actually started quantitatively in the early 1970s with the Gargamelle heavy liquid bubble chamber that produced first neutrino confirmation of scaling. This study of nucleon structure continued with both bubble chambers and more massive electronic detectors that, with higher energy neutrino beams and $Q^2$ reach, examined the breaking of this scaling while testing Quantum Chromodynamics. Here, a significant factor when including neutrino explorations of nucleon structure in the overall picture is that to gather significant statistics, neutrino experiments have had to use heavier nuclear targets. It has been experimentally demonstrated that the structure of the nucleon in the nuclear environment is indeed different than the free nucleon structure. Understanding this modified structure has played an important part in the experimental and theoretical exploration of nucleon structure by neutrinos and is one of the important goals of the on-going MINERvA experiment at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Confocal Raman Microscopy for Measuring In Situ Temperature-Dependent Structural Changes in Poly(Ethylene Oxide) Thin Films

Crystallization from the melt is a critical process governing the properties of semi-crystalline polymeric materials. While structural analyses of melting and crystallization transitions in bulk polymers have been widely reported, in contrast, those in thin polymer films on solid supports have been underexplored. Herein, in situ Raman microscopy and self-modeling curve resolution (SMCR) analysis are applied to investigate the temperature-dependent structural changes in poly(ethylene oxide) (PEO) films during melting and crystallization phase transitions. By resolving complex overlapping sets of spectra, SMCR analysis reveals that the thermal transitions of 50 µm thick PEO films comprise two structural phases: an ordered crystalline phase and a disordered amorphous phase. The ordered structure of the crystalline PEO film entirely disappears as the polymer is heated; conversely, the disordered structure of the amorphous PEO film reverts to the ordered structure as the polymer is cooled. Broadening of the Raman bands was observed in PEO films above the melting temperature (67 °C), while sharpening of bands was observed below the crystallization temperature (45 °C). The temperatures at which these spectral changes occurred were in good agreement with differential scanning calorimetry (DSC) measurements, especially during the melting transition. The results illustrate that in situ Raman microscopy coupled with SMCR analysis is a powerful approach for unraveling complex structural changes in thin polymer films during melting and crystallization processes. Furthermore, we show that confocal Raman microscopy opens opportunities to apply the methodology to interrogate the structural features of PEO or other surface-supported polymer films as thin as 2 µm, a thickness regime beyond the reach of conventional thermal analysis techniques.

Koh, Miharu [Department of Chemistry, University o↗
DOE OSTI2020

The crystal structure of a Polerovirus exoribonuclease-resistant RNA shows how diverse sequences are integrated into a conserved fold

Exoribonuclease-resistant RNAs (xrRNAs) are discrete elements that block the progression of 5' to 3' exoribonucleases using specifically folded RNA structures. A recently discovered class of xrRNA is widespread in several genera of plant-infecting viruses, within both noncoding and protein-coding subgenomic RNAs. The structure of one such xrRNA from a dianthovirus revealed three-dimensional details of the resistant fold but did not answer all questions regarding the conservation and diversity of this xrRNA class. Here, we present the crystal structure of a representative polerovirus xrRNA that contains sequence elements that diverge from the previously solved structure. This new structure rationalizes previously unexplained sequence conservation patterns and shows interactions not present in the first structure. Together, the structures of these xrRNAs from dianthovirus and polerovirus genera support the idea that these plant virus xrRNAs fold through a defined pathway that includes a programmed intermediate conformation. This work deepens our knowledge of the structure-function relationship of xrRNAs and shows how evolution can craft similar RNA folds from divergent sequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structure of the dengue virus RNA promoter

Dengue virus, a single-stranded positive sense RNA virus, is the most prevalent mosquito-borne pathogen in the world. Like all RNA viruses, it uses conserved structural elements within its genome to control essential replicative steps. A 70 nt stem–loop RNA structure (called SLA), found at the 5'-end of the genome of all flaviviruses, functions as the promoter for viral replication. This highly conserved structure interacts with the viral polymerase NS5 to initiate RNA synthesis. Here, we report the NMR structure of a monomeric SLA from dengue virus serotype 1, assembled to high-resolution from independently folded structural elements. The DENV1 SLA has an L-shaped structure, where the top and side helices are coaxially stacked, and the bottom helix is roughly perpendicular to them. Because the sequence is highly conserved among different flavivirus genomes, it is very likely that the three-dimensional fold and local structure of SLA are also conserved among flaviviruses and required for efficient replication. This work provides structural insight into the dengue promoter and provides the foundation for the discovery of new antiviral drugs that target this essential replicative step.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Assessment of Grizzly Capabilities for Reactor Pressure Vessels and Reinforced Concrete Structures

Over the last several years, capabilities to simulate the progression and effects of degradation in critical structures in light water reactor (LWR) nuclear power plants have been under development in the Grizzly code. Age-related material degradation is important for a number of systems in LWRs, but the main focus for Grizzly development has been on reactor pressure vessels (RPVs) and concrete structures because of their central role and the difficulty of replacement of these structures if they are found to be degraded to an unacceptable degree. The capabilities for analyzing both RPVs and concrete structures in Grizzly have reached a point where the feature sets are sufficiently complete to perform credible analyses of those types of structures. Because of this, the emphasis has shifted from foundational development to assessing the accuracy of these modeling capabilities on representative problems of interest and on improving the physical basis of those models to improve their ability to predict the actual response of those structural systems. This report documents a first set of test cases that have been developed to assess the Grizzly code on real-world problems for these two types of structures. For RPVs, these test cases consist of a set of benchmark problems where Grizzly is compared to another code. For concrete structures, a set of models of experimental specimens designed to characterize the multidimensional swelling response of reinforced concrete members due to alkali-silica reaction (ASR) has been developed and compared with experimental results. Both the RPV and concrete test cases developed here are much more computationally intensive than the small regression tests that are used in the testing that Grizzly undergoes every time a proposed set of changes is made to ensure that those changes do not adversely affect previously established behavior. A system for regularly running these large problems to monitor the behavior of the code as it is developed has been instituted. While these test cases generally indicate good comparison with the benchmark results, they also indicate areas where further development is warranted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗