Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A critical verification of beam and shell models of wind turbine blades

Ever-increasing wind turbine size has challenged predictive capabilities on several fronts. Here, to address part of the blade structural modeling uncertainty, a systematic model fidelity comparison study was conducted on commonly used finite elements. pyNuMAD was utilized to create beam, shell, and solid models of a 100 m long blade undergoing large static deflections. The solid model avoided the use of layered-solid elements by resolving core and facesheet layers. An unprecedented model with 73.7 million elements revealed insights that have never been possible from prior experimental and numerical studies. As compared to the solid element model, the tip deflection from the shell and beam model was found to be about 2% and 4.3% too low, respectively. The twist from the beam model was found to be about 5.6% too high, while the twist from shell model was 24% too low, though improvement was demonstrated with mesh refinement. The beam model adhesive stresses were more accurate than the shell model. Out-of-plane stresses were of great significance near geometric and material discontinuities, and neither the shell nor beam model captured these effects well. Failure predictions from beam, shell, or layered-solid models are unlikely to be reliable at trailing edges, adhesives, ply-drops, spar-cap boundaries.

17 WIND ENERGY↗
DOE OSTI2020

Measurement of the central exclusive production of charged particle pairs in proton-proton collisions at $\sqrt{s}$ = 200 GeV with the STAR detector at RHIC

We report on the measurement of the Central Exclusive Production of charged particle pairs h+h- (h = π, K, p) with the STAR detector at RHIC in proton-proton collisions at $\sqrt{s}$ = 200 GeV. The charged particle pairs produced in the reaction pp → p' + h + h - + p' are reconstructed from the tracks in the central detector and identified using the specific energy loss and the time of flight method, while the forward-scattered protons are measured in the Roman Pot system. Exclusivity of the event is guaranteed by requiring the transverse momentum balance of all four final-state particles. Differential cross sections are measured as functions of observables related to the central hadronic final state and to the forward-scattered protons. They are measured in a fiducial region corresponding to the acceptance of the STAR detector and determined by the central particles’ transverse momenta and pseudorapidities as well as by the forward-scattered protons’ momenta. This fiducial region roughly corresponds to the square of the four-momentum transfers at the proton vertices in the range 0.04 GeV 2 < -t 1 , -t 2 < 0.2 GeV 2 , invariant masses of the charged particle pairs up to a few GeV and pseudorapidities of the centrally-produced hadrons in the range |η| < 0.7. The measured cross sections are compared to phenomenological predictions based on the Double Pomeron Exchange (DPE) model. Structures observed in the mass spectra of π + π - and K + K - pairs are consistent with the DPE model, while angular distributions of pions suggest a dominant spin-0 contribution to π + π - production. For π + π - production, the fiducial cross section is extrapolated to the Lorentz-invariant region, which allows decomposition of the invariant mass spectrum into continuum and resonant contributions. The extrapolated cross section is well described by the continuum production and at least three resonances, the f 0 (980), f 2 (1270) and f 0 (1500), with a possible small contribution from the f 0 (1370). Fits to the extrapolated differential cross section as a function of t 1 and t 2 enable extraction of the exponential slope parameters in several bins of the invariant mass of π + π - pairs. These parameters are sensitive to the size of the interaction region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗
DOE OSTI2025

Microstructurally Strained Pyrochlore–Perovskite Biphasic Electrocatalysts for the Oxygen Evolution Reaction

Efficiency of water splitting for hydrogen production is often limited by the sluggish kinetics of multiple electronic transfers required in the heterogeneous oxygen evolution reaction (OER). Catalyst design for reducing the high OER overpotential remains a major scientific challenge. Lattice-strain engineering, a method for tuning the electronic structure and surface geometric configuration of active sites, may greatly affect the interaction between adsorbates and catalytic surfaces for high activity and stability. Here, in this study, we present the synthesis of biphasic oxides of YPrSrRuMnO x , which consists of distinct phases of Y 2 Ru 2 O 7 pyrochlore and (Pr 0.7 Sr 0.3 )MnO 3 perovskite, and the development of a suitable analytical approach to study the strain–catalytic property relationship. Linear sweep voltammetry results reveal that the biphasic oxide exhibits approximately 3.1 times greater mass activity and 2.4 times larger turnover frequency (TOF) than single-phase Y 2 Ru 2 O 7 in the 0.1 M HClO 4 electrolyte. The biphasic catalyst is also about 3 times more stable than the single-phase oxide under acidic conditions. X-ray photoelectron spectroscopy, nitrogen isotherm, and electrochemical surface area analyses indicate that the oxidation state, specific surface area, and electrochemical surface area do not cause enough difference in the observed enhancement of OER performance. We examined the effects of microstrain on electrocatalysis, originating from lattice mismatch between different phases, using three different structural models. Specifically, we compared the Williamson–Hall method, standard stress–strain analysis, and Rietveld refinement in analyzing the structure–property relationship. Strain mapping using geometric phase analysis (GPA) further revealed significant microstrain and lattice dislocations localized near phase boundaries in the biphasic oxide, in contrast to the uniform strain in single-phase materials. The results reveal that the increased microstrain correlates well with the improved OER performance, as the biphasic oxide catalyst exhibits 2–3 times greater microstrain than Y 2 Ru 2 O 7 pyrochlore.

electrocatalysts↗
DOE OSTI2013

Calculation of metamorphic two-dimensional quantum energy system: Application to wetting layer states in InAs/InGaAs metamorphic quantum dot nanostructures

In this work, we calculate the two-dimensional quantum energy system of the In(Ga)As wetting layer that arises in InAs/InGaAs/GaAs metamorphic quantum dot structures. Model calculations were carried on the basis of realistic material parameters taking in consideration their dependence on the strain relaxation of the metamorphic buffer; results of the calculations were validated against available literature data. Model results confirmed previous hypothesis on the extrinsic nature of the disappearance of wetting layer emission in metamorphic structures with high In composition. We also show how, by adjusting InGaAs metamorphic buffer parameters, it could be possible: (i) to spatially separate carriers confined in quantum dots from wetting layer carriers, (ii) to create an hybrid 0D-2D system, by tuning quantum dot and wetting layer levels. These results are interesting not only for the engineering of quantum dot structures but also for other applications of metamorphic structures, as the two design parameters of the metamorphic InGaAs buffer (thickness and composition) provide additional degrees of freedom to control properties of interest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations

We present that borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Qn distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3B and 4B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. Lastly, the results shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impacts of climate change on subannual hydropower generation: a multi-model assessment of the United States federal hydropower plant

Abstract Hydropower is a low-carbon emission renewable energy source that provides competitive and flexible electricity generation and is essential to the evolving power grid in the context of decarbonization. Assessing hydropower availability in a changing climate is technically challenging because there is a lack of consensus in the modeling representation of key dynamics across scales and processes. Focusing on 132 US federal hydropower plants, in this study we evaluate the compounded impact of climate and reservoir-hydropower models’ structural uncertainties on monthly hydropower projections. In particular, instead of relying on one single regression-based hydropower model, we introduce another conceptual reservoir operations-hydropower model in the assessment framework. This multi-model assessment approach allows us to partition uncertainties associated with both climate and hydropower models for better clarity. Results suggest that while at least 70% of the uncertainties at the annual scale and 50% at the seasonal scale can be attributed to the choice of climate models, up to 50% of seasonal variability can be attributed to the choice of hydropower models, particularly in regions over the western US where the reservoir storage is substantial. The analysis identifies regions where multi-model assessments are needed and presents a novel approach to partition uncertainties in hydropower projections. Another outcome includes an updated evaluation of Coupled Model Intercomparison Project Phase 5 (CMIP5)-based federal hydropower projection, at the monthly scale and with a larger ensemble, which can provide a baseline for understanding future assessments based on CMIP6 and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Closing the loop: model-predictive control for a closed-circuit reverse osmosis system

This article presents a model-predictive controller (MPC) for the maximization of the energy efficiency of a closed-circuit desalination reverse osmosis (CCRO) system. CCRO is a process for producing drinking water that is based on a cyclic operation with the following two phases: (a) filtration and (b) drain. In this article, we test model predictive control for optimal control of this process. The most important features of our approach are as follows: (a) the selection of a model structure that enables reliable forecasts of the filtration phase (up to 3 h), (b) an on-line model calibration strategy that ensures model forecast reliability, and (c) the satisfaction of equipment safety and operational constraints on the selected setpoints. We challenge this through deliberate introduction of changes in the unmeasured feed concentration and the applied constraints. Our results indicate that frequent model parameter updates are critical to maintain model reliability for MPC purposes. In addition, we illustrate that parameter identifiability is not guaranteed and that deliberate variation in flow rates is necessary even though the process never operates in steady state. Finally, MPC can compute flow rate setpoints that maximize the energy efficiency of the CCRO process while satisfying the applicable equipment and safety constraints.

closed-circuit reverse osmosis↗
DOE OSTI2023

HLA-Clus: HLA class I clustering based on 3D structure

In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository (https://github.com/yshen25/HLA-Clus).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

China's Building Energy Demand: Long-Term Implications from a Detailed Assessment

We present here a detailed, service-based model of China’s building energy use, nested in the GCAM (Global Change Assessment Model) integrated assessment framework. Using the model, we explore long-term pathways of China’s building energy use and identify opportunities of reducing greenhouse gas emissions. The inclusion of a structural model of building energy demands within an integrated assessment framework represents a major methodological advance. It allows for a structural understanding of the drivers of building energy consumption while simultaneously considering the other human and natural system interactions that influence changes in the global energy system and climate. We also explore a range of different scenarios to gain insights into how China’s building sector might evolve and what the implications might be for improved building energy technology and carbon policies. The analysis suggests that China’s building energy growth will not wane anytime soon, although technology improvement will put downward pressure on this growth. Also, regardless of the scenarios represented, the growth will involve the continued, rapid electrification of the buildings sector throughout the century, and this transition will be accelerated by the implementation of carbon policy.

Building energy modeling↗
DOE OSTI2024

Synthesis and symmetry of perovskite oxynitride CaW(O,N) 3

Perovskite oxynitrides, in addition to being promising electrocatalysts and photoabsorbers, present an interesting case study in crystal symmetry. Full or partial ordering of the O and N anions affects global symmetry and influences material performance and functionality; however, anion ordering is challenging to detect experimentally. In this work, we synthesize a novel perovskite oxynitride CaW(O,N) 3 and characterize its crystal structure using both X-ray and neutron diffraction. Through co-refinement of the diffraction patterns with a range of literature and theory-derived model structures, we demonstrate that CaW(O,N) 3 adopts an orthorhombic Pnma average structure and exhibits octahedral distortion with evidence for preferred anion site occupancy. However, through comparison with a large, low-symmetry unit cell, we identify the presence of disorder that is not fully accounted for by the high-symmetry model. We compare CaW(O,N) 3 with SrW(O,N) 3 to demonstrate the broader presence of such disorder and identify contrasting features in the electronic structures. This work signifies an updated perspective on the inherent crystal symmetry present in perovskite oxynitrides.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Experimental evaluation and numerical modelling of timber-framed walls

Timber-framed wall buildings are seen all over Europe, especially in seismic regions, given its adequacy to resist earthquakes. The pombaline buildings, developed after the big 1755 earthquake that destroyed Lisbon, constitute one of the best examples of ancient seismic-resistant structures based on timber-framed masonry walls. But in addition to suffering natural degradation and frequent inadequate interventions, these buildings were not prepared to resist the severe seismic actions envisaged by today’s structural codes. In this context, they increasingly have to undergo rehabilitation and reinforcing works. The success of these projects strongly depends on the accuracy of the structural modelling, which in turn depends on knowledge of the behaviour of the existing structure. Aiming at providing reliable data to be used in structural design, a series of tests was carried out on the base element that constitutes the timber-framed masonry walls: the Saint Andrew’s cross. The experimental tests were numerically simulated in order to determine the parameters that lead to the most accurate results when using linear-elastic models.

42 ENGINEERING↗
DOE OSTI2013

Zinc ion coordination as a modulating factor of the ZnuA histidine-rich loop flexibility: A molecular modeling and fluorescence spectroscopy study

Highlights: Black-Right-Pointing-Pointer Fluorescence data indicate that the His-loop of ZnuA interacts with Zn{sup +2} ions. Black-Right-Pointing-Pointer The ZnuA structural model proposed validates these spectroscopic findings. Black-Right-Pointing-Pointer It is proposed that a zinc loaded His-loop may facilitate the ZnuA-ZnuB recognition. -- Abstract: ZnuA is the soluble component of the high-affinity ZnuABC zinc transporter belonging to the ATP-binding cassette-type periplasmic Zn-binding proteins. The zinc transporter ZnuABC is composed by three proteins: ZnuB, the membrane permease, ZnuC, the ATPase component and ZnuA, the soluble periplasmic metal-binding protein which captures Zn and delivers it to ZnuB. The ZnuA protein contains a charged flexible loop, rich in histidines and acidic residues, showing significant species-specific differences. Various studies have established that this loop contributes to the formation of a secondary zinc binding site, which has been proposed to be important in the acquisition of periplasmic Zn for its delivery to ZnuB or for regulation of zinc uptake. Due to its high mobility the structure of the histidine-rich loop has never been solved by X-ray diffraction studies. In this paper, through a combined use of molecular modeling, mutagenesis and fluorescence spectroscopy, we confirm the presence of two zinc binding sites characterized by different affinities for the metal ion and show that the flexibility of the loop is modulated by the binding of the zinc ions to the protein. The data obtained by fluorescence spectroscopy have then be used to validate a 3D model including the unsolved histidine-rich loop.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Random vs realistic amorphous carbon models for high resolution microscopy and electron diffraction

Amorphous carbon and amorphous materials in general are of particular importance for high resolution electron microscopy, either for bulk materials, generally covered with an amorphous layer when prepared by ion milling techniques, or for nanoscale objects deposited on amorphous substrates. In order to quantify the information of the high resolution images at the atomic scale, a structural modeling of the sample is necessary prior to the calculation of the electron wave function propagation. It is thus essential to be able to reproduce the carbon structure as close as possible to the real one. The approach we propose here is to simulate a realistic carbon from an energetic model based on the tight-binding approximation in order to reproduce the important structural properties of amorphous carbon. At first, we compare this carbon with the carbon obtained by randomly generating the carbon atom positions. In both cases, we discuss the limit thickness of the phase object approximation. In a second step, we show the influence of both carbons models on (i) the contrast of Cu, Ag, and Au single atoms deposited on carbon and (ii) the determination of the long-range order parameter in CoPt bimetallic nanoalloys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Predicting RNA structure and dynamics with deep learning and solution scattering

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA’s conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg 2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg 2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structural considerations of folded protein import through the chloroplast TOC/ TIC translocons

Protein import into chloroplasts is carried out by the protein translocons at the outer and inner envelope membranes (TOC and TIC). Detailed structures for these translocons are lacking, with only a low-resolution TOC complex structure available. Recently, we showed that the TOC/TIC translocons can import folded proteins, a rather unique feat for a coupled double membrane system. In this work we also determined the maximum functional TOC/TIC pore size to be 30–35 Å. Here, we discuss how such large pores could form and compare the structural dynamics of the pore-forming Toc75 subunit to its bacterial/mitochondrial Omp85 family homologs. We put forward structural models that can be empirically tested and also briefly review the pore dynamics of other protein translocons with known structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The energy budget and figure of Earth during recovery from the Moon-forming giant impact

Quantifying the energy budget of Earth in the first few million years following the Moon-forming giant impact is vital to understanding Earth's initial thermal state and the dynamics of lunar tidal evolution. After the impact, the body was substantially vaporized and rotating rapidly, very different from the planet we know today. The subsequent evolution of Earth's energy budget, as the body cooled and angular momentum was transferred during lunar tidal recession, has not been accurately calculated with all relevant energy components included. In this work, we use giant impact simulations and planetary structure models to calculate the energy budget at stages in Earth's evolution. We show that the figure and internal structure of Earth changed substantially during its post-impact evolution and that changes in kinetic, potential, and internal energy were all significant. These changes have important implications for the dynamics of tidal recession and the thermal structure of early Earth.

58 GEOSCIENCES↗