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DOE OSTI2022

MODULARITY-AT-SCALE FOR COST COMPETITIVE DEPLOYMENT OF NUCLEAR ENERGY

Modularity options have been limited for traditional nuclear energy deployment due to the conventional light water reactor (LWR) safety requirements, such as high pressure retaining heavy and robust containment structures. However, a relatively new regulatory approach called ‘Functional Containment’ has potential to allow less expensive and more flexible designs for non LWRs. Functional containment provides flexibility in design and deployment based on risk informed and performance-based criteria, so that reactors are not over-designed. Non-nuclear industry has successfully used modular design approaches in automotive, aerospace, chemical processing, building construction, and ship building. These industries have shown that modular construction reduces construction time by around 30% - 50% compared to the conventional stick built approach. The nuclear industry can use similar approaches to reduce construction time and costs, balanced with safety requirements, using the functional containment approach. This paper discussing the background of modularity in nuclear energy, examples of less learned, modularity approaches in non-nuclear industries and the potential of cost and schedule savings through the emerging regulatory design flexibilities potentially enabling combination of modular deployment at different scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

A simplified method of evaluating the stress wave environment of internal equipment

A simplified method called the transfer function technique (TFT) was devised for evaluating the stress wave environment in a structure containing internal equipment. The TFT consists of following the initial in-plane stress wave that propagates through a structure subjected to a dynamic load and characterizing how the wave is altered as it is transmitted through intersections of structural members. As a basis for evaluating the TFT, impact experiments and detailed stress wave analyses were performed for structures with two or three, or more members. Transfer functions that relate the wave transmitted through an intersection to the incident wave were deduced from the predicted wave response. By sequentially applying these transfer functions to a structure with several intersections, it was found that the environment produced by the initial stress wave propagating through the structure can be approximated well. The TFT can be used as a design tool or as an analytical tool to determine whether a more detailed wave analysis is warranted.

Colton, J. D.↗

NASA NTRS1998

Health Monitoring of Composite Material Structures Using a Vibrometry Technique

Non-destructive evaluation (NDE) methods for quantifying and locating damage are essential for inspecting structures to ensure safety and reliability. Transmittance function monitoring is a potentially new NDE technique being tested as a tool to detect, quantify, and locate damage on flexible structures. The technique has a large spatial range that is practical for detecting damage on large composite material structures such as a reusable launch vehicle. The Transmittance Function (TF) theory is based on structural dynamics principles that define how vibration at one point in a structure is related to a force at another point. This relationship is called the Frequency Response Function (FRF). A Transmittance Function (TF) is derived as the ratio of FRFs, and can detect damage because the FRFs change due to damage. If one excitation is used for the testing, the force does not need to be measured to compute the TF. In the damage detection procedure, the structure is subjected to wide-band vibration and TFs are computed between different accelerometers to detect changes in the structure, presumably due to damage. In the first year of the project the TF method was tested on a bolted panel, a curved panel, and beams, all made of fiberglass. It was shown that damage could be detected using low frequency vibration, 250 to 1,250 Hz. The technique is sensitive to damage, but it requires storage of historical or pre-damage TFs for the healthy structure. This would become a large data storage requirement for large structures. Thus one objective for the second year of the project was to eliminate the need to store historical data. The second year report gives details of how storage of historical data was eliminated. Further results of testing panel structures are also given.

Schulz, Mark J.↗

NASA NTRS1986

Solar wind observations near the sun

Observations of interplanetary scintillations with the VLA telescope are reported. The solar wind in the accelerating region from 3 to 12 solar radii was observed by scintillation of the radio source 3C279. The results obtained outside of 7 solar radii showed good agreement with previous work but observations between 3 and 4.5 solar radii were new and unexpected. Turbulence in the solar wind has a spatially anisotropic structure elongated in the radial direction, the flow direction being also in the radial direction. An abrupt change of both the velocity and the spatial anisotropy of turbulence was found at distances from 3 to 4.5 solar radii. There is a large random velocity component inside of 12 solar radii which is comparable to the bulk flow speed, and it has a spatially anisotropic probability distribution. From the measured cross-correlation functions, evidence which may be related to the complex structure of the magnetic field is found.

Armstrong, J. W.↗

DOE OSTI2025

Gaia: An AI-enabled genomic context–aware platform for protein sequence annotation

Protein sequence similarity search is fundamental to biology research, but current methods are typically not able to consider crucial genomic context information indicative of protein function, especially in microbial systems. Here, we present Gaia (Genomic AI Annotator), a sequence annotation platform that enables rapid, context-aware protein sequence search across genomic datasets. Gaia leverages gLM2, a mixed-modality genomic language model trained on both amino acid sequences and their genomic neighborhoods to generate embeddings that integrate sequence-structure-context information. This approach allows for the identification of functionally and/or evolutionarily related genes that are found in conserved genomic contexts, which may be missed by traditional sequence- or structure-based search alone. Gaia enables real-time search of a curated database comprising more than 85 million protein clusters from 131,744 microbial genomes. We compare the homolog retrieval performance of Gaia search against other embedding and alignment-based approaches. We provide Gaia as a web-based, freely available tool.

Jha, Nishant↗

NASA NTRS1985

Simulation studies for surfaces and materials strength

From intermolecular force studies, it is now known that the overall non-additive contribution to the lattice enegy is positive so that analysis based on only pairwise additivity suggests a shallower intermolecular potential than the true value. Two body contributions alone are also known to be categorically unable to even qualitatively describe some configurations of molecular clusters in the gas phase or the general relaxation and reconstruction of fcc crystal surfaces. In addition, the many-body contribution was shown to play a key role in the stability of certain crystal structures. In these recent analyses, a relatively simple potential energy function (PEF), comprising only a two-body Mie-type potential plus a three-body Axilrod-Teller-type potential, was found to be extremely effective. This same parametric PEF is applied to describe the bulk stability and surface energy for the diamond cubic structure. To test the stability condition, the FCC, BCC, diamond cubic, graphite and beta-tin structures were considered.

Halicioglu, T.↗

DOE OSTI2023

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2024

Logic Programming with Extensible Types

Logic programming allows structuring code in terms of predicates or relations, rather than functions. Although logic programming languages present advantages in terms of declarativeness and conciseness, the introduction of static types has not become part of most popular logic programming languages, increasing the difficulty of testing and debugging of logic programming code. This paper demonstrates how to implement logic programming in Haskell, thus empowering logic programs with types, and functional programs with relations or predicates. We do so by combining three ideas. First, we use extensible types to generalize a type by a parameter type function. Second, we use a sum type as an argument to introduce optional variables in extensible types. Third, we implement a unification algorithm capable of working with any data structure, provided that certain operations are implemented for the given type. We demonstrate our proposal via a series of increasingly complex examples inspired by educational texts in logic programming, and leverage the host language's features to make new notation convenient for users, showing that the proposed approach is not just technically possible but also practical.

logic programming↗

DOE OSTI2022

DMC-ICE13 : Ambient and high pressure polymorphs of ice from diffusion Monte Carlo and density functional theory

Ice is one of the most important and interesting molecular crystals, exhibiting a rich and evolving phase diagram. Recent discoveries mean that there are now 20 distinct polymorphs; a structural diversity that arises from a delicate interplay of hydrogen bonding and van der Waals dispersion forces. This wealth of structures provides a stern test of electronic structure theories, with Density Functional Theory (DFT) often not able to accurately characterize the relative energies of the various ice polymorphs. Thanks to recent advances that enable the accurate and efficient treatment of molecular crystals with Diffusion Monte Carlo (DMC), we present here the DMC-ICE13 dataset; a dataset of lattice energies of 13 ice polymorphs. This dataset encompasses the full structural complexity found in the ambient and high-pressure molecular ice polymorphs, and when experimental reference energies are available, our DMC results deliver sub-chemical accuracy. Using this dataset, we then perform an extensive benchmark of a broad range of DFT functionals. Of the functionals considered, revPBE-D3 and RSCAN reproduce reference absolute lattice energies with the smallest error, while optB86b-vdW and SCAN+rVV10 have the best performance on the relative lattice energies. Our results suggest that a single functional achieving reliable performance for all phases is still missing, and that care is needed in the selection of the most appropriate functional for the desired application. The insights obtained here may also be relevant to liquid water and other hydrogen-bonded and dispersion-bonded molecular crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

QuantumScents: Quantum-Mechanical Properties for 3.5k Olfactory Molecules

Quantitative structure–odor relationships are critically important for studies related to the function of olfaction. Current literature data sets contain expert-labeled molecules but lack feature data. This paper introduces QuantumScents, a quantum mechanics augmented derivative of the Leffingwell data set. QuantumScents contains 3.5k structurally and chemically diverse molecules ranging from 2 to 30 heavy atoms (CNOS) and their corresponding 3D coordinates, total PBE0 energy, molecular dipole moment, and per-atom Hirshfeld charges, dipoles, and ratios. The authors demonstrate that Hirshfeld charges and ratios contain sufficient information to perform molecular classification by training a Message Passing Neural Network with chemprop (Heid, E.; et al. ChemRxiv, 2023, DOI: 10.26434/chemrxiv-2023-3zcfl) to predict scent labels. Finally, the QuantumScents data set is freely available on Zenodo along with the authors’ code, example models, and data set generation workflow (https://zenodo.org/doi/10.5281/zenodo.8239853).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

SPARC: Structural properties associated with residue constraints

SPARC facilitates the generation of plausible hypotheses regarding underlying biochemical mechanisms by structurally characterizing protein sequence constraints. Such constraints appear as residues co-conserved in functionally related subgroups, as subtle pairwise correlations (i.e., direct couplings), and as correlations among these sequence features or with structural features. SPARC performs three types of analyses. First, based on pairwise sequence correlations, it estimates the biological relevance of alternative conformations and of homomeric contacts, as illustrated here for death domains. Second, it estimates the statistical significance of the correspondence between directly coupled residue pairs and interactions at heterodimeric interfaces. Third, given molecular dynamics simulated structures, it characterizes interactions among constrained residues or between such residues and ligands that: (a) are stably maintained during the simulation; (b) undergo correlated formation and/or disruption of interactions with other constrained residues; or (c) switch between alternative interactions. We illustrate this for two homohexameric complexes: the bacterial enhancer binding protein (bEBP) NtrC1, which activates transcription by remodeling RNA polymerase (RNAP) containing σ 54 , and for DnaB helicase, which opens DNA at the bacterial replication fork. Based on the NtrC1 analysis, we hypothesize possible mechanisms for inhibiting ATP hydrolysis until ADP is released from an adjacent subunit and for coupling ATP hydrolysis to restructuring of σ 54 binding loops. Based on the DnaB analysis, we hypothesize that DnaB ‘grabs’ ssDNA by flipping every fourth base and inserting it into cavities between subunits and that flipping of a DnaB-specific glutamine residue triggers ATP hydrolysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Tailored Silicone Network Architecture for Ultimate Mechanical Reinforcement

Hydrosilylation cured silicone elastomers are subject to reaction inefficiency, leading to incomplete and non-uniform crosslink networks, restricting the potential of mechanical reinforcement. This work investigates pre-synthesized, functional PDMS architectures as additives to improve ultimate mechanical performance relative to conventional single-step curing. Three custom, functional structures were prepared: a partially crosslinked PDMS scaffold (Structure A), a bottle-brush PDMS (Structure B), and a star-shaped PDMS derived from an MQ resin (Structure C). Rheological characterization was used to identify the ultimate design space and proper stoichiometric ratio for Structure A, and confirm successful formation of all structures for suitable incorporation into a base silicone formulation at 30wt%. Mechanical tests indicated that all three structures increased in ultimate tensile strength relative to their single-step counterparts, with Structure A providing additional improvements to toughness (432 vs. 258 kJ/m3) and ultimate elongation (158 vs. 115%). Furthermore, Structure B remained very soft in the unfilled state, while Structure C provided hardness (23 vs. 18 Shore A) and stiffness (780 vs. 420 kPa Young’s modulus) increases. In silica filled systems, Structure A retained increased strength but reduced elongation, while Structure B indicated strong reinforcement in terms of strength, toughness, and stiffness. Thermal analysis on the cure profiles of these materials suggested that pre-formation of network architectures enable a more complete reaction than a single-step process (15.9 vs. 15.1 J/g). Ultimately, these results indicate that tailoring PDMS architecture before the final cure can improve ultimate mechanical properties via improved network development in silicone elastomers. Furthermore, this work offers a promising strategy for designing higher-performance, more tunable silicone formulations.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Hybrid Quantum–Classical Study of Ion Adsorption at the Copper Electrode

Here, we present a set of computational studies that surveys the molecular structure and thermodynamics of simple ions at the electrode–electrolyte interface. A hybrid quantum–classical approach is used to obtain free energy profiles and solvent structure as a function of the ion’s position relative to the electrochemical liquid/solid interface and system potential. Model systems consist of a copper electrode and single halide or alkali metal ion in contact with an implicit solvent and reveal new insights into the interplay of forces that drive or resist ion absorption at the electrode/ electrolyte interface. We also expand on subtleties of absorption site preference and describe the complex relationship between the energetic barrier to absorption and the ion–electrode binding energy as a function of electrode potential.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Variance reduction in lattice QCD observables via normalizing flows

Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a derivative with respect to action parameters. This work implements the approach for observables involving gluonic operator insertions in the SU(3) Yang-Mills theory and two-flavor QCD in four space-time dimensions. Variance reduction by factors of 10–60 is achieved in glueball correlation functions and in gluonic matrix elements related to hadron structure, with demonstrated computational advantages. The observed variance reduction is found to be approximately independent of the lattice volume, so volume transfer can be utilized to minimize training costs.

Abbott, Ryan [Columbia U.; MIT, Cambridge, CTP; IA↗

DOE OSTI2022

Shear strain alters the structure and migration mechanism of self-interstitial atoms in copper

Here, we use atomistic modeling to show that externally applied shear strain causes the lowest energy self-interstitial atom (SIA) structure in copper (Cu) to change from a <100>-type dumbbell to a <110>-type dumbbell. Concurrently, SIA migration switches from the 3-D random walk characteristic of <100>-type dumbbells to a 1-D mechanism analogous to that of crowdion SIAs. Furthermore, the relative energies of these two dumbbell structures as a function of strain are well predicted using elastic dipole tensors computed at zero strain, indicating that examination of these tensors may be used to assess the likelihood of strain-induced SIA structure transitions in other materials. Changes in lowest energy SIA structures and associated migration mechanisms stand to impact predictions of SIA behavior in irradiated solids.

36 MATERIALS SCIENCE↗

NASA NTRS1985

Intercomparison of global SST fields derived from satellite sensors and ship observations

Near global comparisons were made between binned forms of SST obtained from different instruments, ship meteorological observations, and the output of a meteorological model. Binning hereinafter means gridding by simple summation of data values in a bin, which in this study was a 2 deg. x 2 deg. box or a 10 deg. x 10 box surrounding a grid node. In the binned comparisons, the question is asked: are the binned data from two instruments drawn from the same population? The first two measures of statistical moments of the populations are used to test the hypothesis that they are. Comparisons were also attempted between raw forms of the various SST retrievals, using a structure function analysis. The results of this analysis were relatively uninteresting and are therefore omitted.

Pazan, S. E.↗

NASA NTRS1992

Computer codes developed and under development at Lewis

The objective of this summary is to provide a brief description of: (1) codes developed or under development at LeRC; and (2) the development status of IPACS with some typical early results. The computer codes that have been developed and/or are under development at LeRC are listed in the accompanying charts. This list includes: (1) the code acronym; (2) select physics descriptors; (3) current enhancements; and (4) present (9/91) code status with respect to its availability and documentation. The computer codes list is grouped by related functions such as: (1) composite mechanics; (2) composite structures; (3) integrated and 3-D analysis; (4) structural tailoring; and (5) probabilistic structural analysis. These codes provide a broad computational simulation infrastructure (technology base-readiness) for assessing the structural integrity/durability/reliability of propulsion systems. These codes serve two other very important functions: they provide an effective means of technology transfer; and they constitute a depository of corporate memory.

Chamis, Christos C.↗