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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units

Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.

Wang, Hong↗
DOE OSTI2023

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials

Noncanonical Amino Acids (NCAAs) provide numerous avenues for introduction of novel functionality to peptides and proteins. NCAAs can be incorporated through solid phase synthesis or genetic code expansion in conjugation with heterologous expression of the encoded protein modification. Due to the difficulty of synthesis, wide chemical space and lack of empirically resolved structures modeling the effects of NCAA mutation is critical for rational protein design. To evaluate the structural and functional perturbations NCAAs introduce we utilize molecular potentials that describe the forces in protein structure. Most potentials such as CHARMM are designed to model canonical residues but can be parameterized in include novel NCAAs. Here, in this work, we introduce NCAP a software package to generate CHARMM compatible parameters from quantum chemical calculation. Unlike currently available tools NCAP is designed to recognize NCAA structure and automatically bridge the gap between DFT calculations and potential parameters. For our software we discuss workflow, validation against canonical parameter sets and comparison to published NCAA-protein structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The exo-β- N -acetylmuramidase NamZ from Bacillus subtilis is the founding member of a family of exo-lytic peptidoglycan hexosaminidases

Endo-β-N-acetylmuramidases, commonly known as lysozymes, are well-characterized antimicrobial enzymes that catalyze an endo-lytic cleavage of peptidoglycan; i.e., they hydrolyze the β-1,4-glycosidic bonds connecting N-acetylmuramic acid (MurNAc) and N-acetylglucosamine (GlcNAc). In contrast, little is known about exo-β-N-acetylmuramidases, which catalyze an exo-lytic cleavage of β-1,4-MurNAc entities from the non-reducing ends of peptidoglycan chains. Such an enzyme was identified earlier in the bacterium Bacillus subtilis, but the corresponding gene has remained unknown so far. We now report that ybbC of B. subtilis, renamed namZ, encodes the reported exo-β-N-acetylmuramidase. A ΔnamZ mutant accumulated specific cell wall fragments and showed growth defects under starvation conditions, indicating a role of NamZ in cell wall turnover and recycling. Recombinant NamZ protein specifically hydrolyzed the artificial substrate para-nitrophenyl β-MurNAc and the peptidoglycan-derived disaccharide MurNAc-β-1,4-GlcNAc. Together with the exo-β-N-acetylglucosaminidase NagZ and the exo-muramoyl-L-alanine amidase AmiE, NamZ degraded intact peptidoglycan by sequential hydrolysis from the non-reducing ends. A structure model of NamZ, built on the basis of two crystal structures of putative orthologs from Bacteroides fragilis, revealed a two-domain structure including a Rossmann-fold-like domain that constitutes a unique glycosidase fold. Thus, NamZ, a member of the DUF1343 protein family of unknown function, is now classified as the founding member of a new family of glycosidases (CAZy GH171). NamZ-like peptidoglycan hexosaminidases are mainly present in the phylum Bacteroidetes and less frequently found in individual genomes within Firmicutes (Bacilli, Clostridia), Actinobacteria, and γ-proteobacteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Expression of divergent methyl/alkyl coenzyme M reductases from uncultured archaea

Abstract Methanogens and anaerobic methane-oxidizing archaea (ANME) are important players in the global carbon cycle. Methyl-coenzyme M reductase (MCR) is a key enzyme in methane metabolism, catalyzing the last step in methanogenesis and the first step in anaerobic methane oxidation. Divergent mcr and mcr -like genes have recently been identified in uncultured archaeal lineages. However, the assembly and biochemistry of MCRs from uncultured archaea remain largely unknown. Here we present an approach to study MCRs from uncultured archaea by heterologous expression in a methanogen, Methanococcus maripaludis . Promoter, operon structure, and temperature were important determinants for MCR production. Both recombinant methanococcal and ANME-2 MCR assembled with the host MCR forming hybrid complexes, whereas tested ANME-1 MCR and ethyl-coenzyme M reductase only formed homogenous complexes. Together with structural modeling, this suggests that ANME-2 and methanogen MCRs are structurally similar and their reaction directions are likely regulated by thermodynamics rather than intrinsic structural differences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural origin of recovered ferroelectricity in BaTi O 3 nanoparticles

Nanoscale BaTiO 3 particles (≈10 nm) prepared by ball-milling a mixture of oleic acid and heptane have been reported to have an electric polarization several times larger than that for bulk BaTiO 3 . In this work, detailed local, intermediate, and long-range structural studies are combined with spectroscopic measurements to develop a model structure of these materials. The X-ray spectroscopic measurements reveal large Ti off-centering as the key factor producing the large spontaneous polarization in the nanoparticles. Temperature-dependent lattice parameter changes reveal the sharpening of the structural phase transitions in these BaTiO 3 nanoparticles compared to the pure nanoparticle systems. In conclusion, sharp crystalline-type peaks in the barium oleate Raman spectra suggest that this component in the composite core-shell matrix, a product of mechanochemical synthesis, stabilizes an enhanced polar structural phase of the BaTiO 3 core nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accurate prediction of protein structures and interactions using a three-track neural network

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo–electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. Here, we make the method available to the scientific community to speed biological research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2021

Low global warming potential (GWP) refrigerant supermarket refrigeration system modeling and its application

As an environmentally friendly low global warming potential (GWP) refrigerant, Carbon dioxide (CO 2 ) has continuously gained popularity and research attention as alternative refrigerant for supermarket refrigeration system. In this paper, to fulfill the increasing need of accurate Low-GWP supermarket refrigeration models for development of supervisory level control and optimization strategies, a high fidelity model is developed for CO 2 transcritical supermarket refrigeration system which includes compressor rack of low temperature (LT) compressors and medium temperature (MT) compressors, air-cooled gas cooler, evaporator, expansion valves and other auxiliary equipment. A resistance-capacity model structure is proposed to simulate the display cases. Semi-thermodynamic models are proposed to estimate reciprocating compressors volumetric efficiency and power consumption. Furthermore the zone modeling approach is used for evaporator simulation, and air-cooled gas cooler is modeled with distributed modeling method. The expansion valve simulation is based on orifice flow model. To calibrate these models, both manufacture performance data and experimental data are used. The experiments are conducted with a full instrumental CO 2 supermarket refrigeration system installed in Oak Ridge National Lab Flexible Research Platform (FRP). The simulation model can predict the system performance, including power consumption, cooling capacity, mass flow rate, temperature, and pressure, with high accuracy (within ±4%) compared to experimental data. In addition, this developed model has been used to create the system optimum high side pressure for high side expansion valve control, and to generate wide operating range simulation data for developing the batter-equivalent commercial refrigeration system model which can be used in grid interactive control development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Atomic-Level Structure of Mesoporous Hexagonal Boron Nitride Determined by High-Resolution Solid-State Multinuclear Magnetic Resonance Spectroscopy and Density Functional Theory Calculations

Mesoporous hexagonal boron nitride (p-BN) has received significant attention over the last decade as a promising candidate for water cleaning/pollutant removal and hydrogen storage applications. In this work, high-resolution solid-state NMR spectroscopy and plane-wave density-functional theory (DFT) calculations are used to obtain an atomic-level description of p-BN. 1 H– 15 N or 1 H– 14 N heteronuclear (HETCOR) correlation experiments recorded with either conventional NMR at room temperature or dynamic nuclear polarization surface-enhanced spectroscopy (DNP-SENS) at ca. 100 K reveal NB 2 H, NBH 2 , NBH 3 + species residing on the edges of BN sheets. Ultra-high field 35.2 T 11 B NMR spectroscopy was used to resolve 11 B NMR signals from BN 3 , BN 2 O x (OH) 1–x (x = 0–1), BNO x (OH) 2–x (x = 0–2), BO x (OH) 3–x (x = 0–3), and BO x (OH) 4–x – (x = 0–4). Importantly, 2D 11 B dipolar double-quantum–single-quantum homonuclear correlation spectra reveal that many pore/defect sites are composed of boron oxide/hydroxide clusters connected to the BN framework through BN 2 O units. 1D and 2D 11 B{ 15 N} HETCOR NMR experiments, in addition to plane-wave DFT calculations of nine different structural models, further confirm the assignment of all NMR signals. The detailed structure determination of the pore and edge/defect sites within p-BN should further enable the rational design and development of next-generation p-BN-based materials. In addition, the techniques outlined here should be applicable to determine structure within other porous and/or boron-based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

BaCu 4/3 Si 2/3 P 2 and BaCu 2–( x + y ) Zn x Si y P 2 : Expanding the Semiconducting Landscape in the ThCr 2 Si 2 -Type Family

ThCr 2 Si 2 -type layered materials are a large family of compounds with applications ranging from thermoelectricity to magnetism, with the vast majority of the members exhibiting metallic behavior. Here, in this study, we synthesized a new group of materials with Cu-Si and Cu-Zn-Si square nets with the general formula BaCu 1.33 Si 0.67 P 2 and BaCu 2–(x+y) Zn x Si y P 2 (0 ≤ x ≤ 0.9; 0.3 ≤ y ≤ 0.7). Several synthesized compounds are charge-balanced semiconductors, which are rare in the ThCr 2 Si 2 family. All the reported compounds crystallize in the ThCr 2 Si 2 -type tetragonal I4/mmm space group, with Cu/Zn/Si jointly occupying the same 4d crystallographic site. In the Zn-free composition, BaCu 1.33 Si 0.67 P 2 , Ba, and P each occupy a single crystallographic site. The introduction of Zn results in the expansion of the unit cell and splitting the Ba atomic sites along the [001] direction. Such structural displacement of the Ba atoms was confirmed by the heat capacity measurements. Band structure and density-of-states calculations on ordered hypothetical structural models reveal either a small bandgap (∼0.2 eV) or semimetallic band structures. The compounds reported here exhibit high Seebeck coefficients and ultralow thermal conductivity, making them promising candidates for the development of thermoelectric materials.

crystal structure↗
DOE OSTI2022

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Massively Parallel Capability in Sierra/SD for Simulation Vibration with Piezoelectrics

Sierra/SD is an engineering structural dynamics code that provides Sandia and other customers a tool to model structural and acoustic physics on large complex physical systems using massively parallel processing. This report provides a detailed overview on Sierra/SD’s most recent physics package: coupled electro-mechanical physics. This capability uses the finite element method to model coupled electro-mechanical physics exhibited by piezoelectric materials. This report provides an applications overview, theory overview, and verification examples demonstrating the electro-mechanical physics modeling capabilities of Sierra/SD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Fundamental problems in astroparticle physics and cosmology (Final Technical Report)

In the standard cosmological model, structure forms when gas cools and condenses to the center of dark matter halos. The onset of structure is governed by rapid star formation and subsequent evolution of the first massive stars. One of the endpoints of stellar evolution is the formation of a black hole. We showed that all black hole merger events must occur after the universe is about 85 million years old. This prediction is important because it means that if a future experiment makes a detection of a black hole merger event at an earlier time then our understanding of cosmology and the onset of structure formation is not fully developed. In addition, we explored dark matter models that have either self-interactions or experience decays. In the first case, self-interactions may lead to the formation of a thick disk that can be co-planar to the Galactic disc due to correlations in angular momentum between dark matter and baryons that are predicted by tidal torque theory. We showed that for heavy dark matter particles, either the self interaction may not be strong enough to solve the small scale structure motivation or a dark disc cannot be present in the Milky Way. In the second-case, we showed that if dark matter experiences decays into two particles, one of which behaves like radiation, then it is possible to relieve the tension that exists between measurements of the local expansion rate. Finally, we developed methods on how to distinguish gamma-ray excesses from promising dark matter targets as compared to conventional astrophysical sources. This is an important toolset that is applicable to any suspected dark matter source.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

X-ray Spectroscopy Fingerprints of Pristine and Functionalized Graphene

In this work, we demonstrate how to identify and characterize the atomic structure of pristine and functionalized graphene materials from a combination of computational simulation of X-ray spectra, on the one hand, and computer-aided interpretation of experimental spectra, on the other. Despite the enormous scientific and industrial interest, the precise structure of these 2D materials remains under debate. As we show in this study, a wide range of model structures from pristine to heavily oxidized graphene can be studied and understood with the same approach. We move systematically from pristine to highly oxidized and defective computational models, and we compare the simulation results with experimental data. Comparison with experiments is valuable also the other way around; this method allows us to verify that the simulated models are close to the real samples, which in turn makes simulated structures amenable to several computational experiments. Our results provide ab initio semiquantitative information and a new platform for extended insight into the structure and chemical composition of graphene-based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗
DOE OSTI2020

Call for Participation: Collaborative Benchmarking of Functional-Structural Root Architecture Models. The Case of Root Water Uptake

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models, such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore, defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute toward improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development.

Plant Sciences↗
DOE OSTI2020

Cryo-based Structural Characterization and Growth Model of Salt Film on Metal

Metal salt films play a critical role in high rate dissolution processes such as within an active pit. However, structural and compositional characterization of salt films is challenging owing to the dynamic nature of the dissolving interface. Here, the salt film formed on SS304 one-dimensional artificial pit surface was directly characterized using flash freezing and cryo-based focused ion beam/scanning electron microscopy. The salt film exhibits a porous structure. Ni is co-located with Fe in the salt film, indicating the formation of co-precipitated salt containing Fe2+ and Ni2+. Additionally, a salt film growth model is presented based on ion transport.

Salt film, Pitting corrosion, Cryogenic, Cryo-FIB/↗