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Results for “structured model reduction”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Redistribution of Electron Equivalents between Magnetite and Aqueous Fe 2+ Induced by a Model Quinone Compound AQDS

The complex interactions between magnetite and aqueous Fe 2+ (Fe 2+ (aq) ) pertain to many biogeochemical redox processes in anoxic subsurface environments. The effect of natural organic matter, abundant in these same environments, on Fe 2+ (aq) -magnetite interactions is an additional complex that remains poorly understood. We investigated the influence of a model quinone molecule anthraquinone-2,6-disulfonate (AQDS) on Fe 2+ (aq) -magnetite interactions by systematically studying equilibrium Fe 2+ (aq) concentrations, rates and extents of AQDS reduction, and structural versus surface-localized Fe(II)/Fe(III) ratios in magnetite under different controlled experimental conditions. The equilibrium concentration of Fe 2+ (aq) in Fe 2+ -amended magnetite suspensions with AQDS proportionally changes with solution pH or initial AQDS concentration, but independent of magnetite loadings through the solid concentrations that were studied here. The rates and extents of AQDS reduction by Fe 2+ -amended magnetite proportionally increased with solution pH, magnetite loading, and initial Fe 2+ (aq) concentration, which correlates with the corresponding change of reduction potentials for the Fe 2+ -magnetite system. AQDS reduction by surface-associated Fe(II) in the Fe2+-magnetite suspensions induces solid-state migration of electron equivalents from particle interiors to the near-surface region and the production of nonmagnetic Fe(II)-containing species, which inhibits Fe 2+ (aq) incorporation or electron injection into the magnetite structure. Finally, this study demonstrates the significant influence of quinones on reductive activity of the Fe 2+ -magnetite system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models

Abstract. We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16 % and EP by 7–18 %. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positive biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. Community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Design Principles in Engineering of Multigrain Nanocatalysts via Multiscale Electronic Structure Characterization

Engineering grain boundary (GB) strain provides a promising pathway to tune the catalytic properties of nanocrystals. However, structural heterogeneity from random grain orientation and geometry has limited clear structure–property correlations. Here, we utilize a multigrain Co3O4/Mn3O4 core/shell nanocrystal platform as a model system to systematically investigate how geometric misfit strain at GBs serves as catalytically active sites for the oxygen reduction reaction. Through precise subnanometer-level control over grain morphology and by integrating multiscale electronic structure characterization, we identify the electronic structural signature of GB defects and establish a direct correlation between localized strain fields and modified electronic states. Strain modulation at GBs alters the eg orbital energy levels, with elongation along the z-axis combined with shear strain stabilizing the eg states, in contrast to the destabilization observed under pure shear strain. This stabilization mechanism enhances the electrocatalytic activity and selectivity of strained GBs compared with strain-relaxed grain surfaces. Furthermore, we reveal that GBs exhibit a radial strain gradient, producing a spatial energy shift that further modulates local electronic structures, as resolved through the classification of electron energy loss spectroscopy data. Together, these findings demonstrate that geometric misfit strain enables precise tuning of grain geometry and the resulting electronic structures, offering a robust strategy for engineering next-generation nanocatalysts.

Cho, Min Gee↗
DOE OSTI2026

Revealing EDL-driven reduction mechanisms in binary, ternary, and quaternary fluorinated electrolytes via an integrated MD–DFT–ML framework

Accurately predicting solid electrolyte interphase (SEI) formation requires explicitly resolving the electric double layer (EDL) structure, which deviates significantly from that of the bulk electrolyte. Although an established molecular dynamics (MD) and Density Functional Theory (DFT) framework can model SEI formation by evaluating reduction reactions of local clusters in the EDL, it suffers from a combinatorial computational bottleneck. To overcome this limitation, we introduce a machine-learning-accelerated simulation workflow (MD–DFT–ML), integrating a gradient-boosted regression model trained on EDL composition data to efficiently predict reduction potentials. We apply this framework to seven fluorinated electrolytes comprising fluorinated anions, a fluorinated ester solvent, two types of diluent (ion-solvating ester vs. non-solvating ether), and an FEC additive. The analysis shows that the EDL selectively accumulates cation-binding species; consequently, the non–cation-binding ether diluent rarely enters the EDL and makes minimal contributions to SEI formation. DFT calculations on statistically representative EDL clusters provide reduction potentials and fluorine-release pathways, while the ML model, which substantially reduces the DFT workload, predicts cluster reduction energies with a mean absolute error of 0.1 eV. The combined MD–DFT–ML approach also quantifies contributions from different sources to LiF formation in the SEI. This methodology establishes a generalizable route for multiscale modeling electrolyte and interphase design for next-generation electrochemical energy-storage systems.

DFT-MD-ML workflow↗
DOE OSTI2022

Regularizing Invertible Neural Networks for Airfoil Design Through Dimension Reduction

This work examines how dimension reduction can improve the performance of invertible neural networks (INN) for airfoil design. Design workflows are typically expensive, relying on many evaluations of high fidelity computational fluid dynamics (CFD) models. Furthermore, the inverse design problem is typically ill-posed. That is, multiple valid solutions exist that satisfy the design criteria. Regularization can reduce this inverse design space and simplify the problem. We study the use of subspace-based input dimension reduction to act as a regularizer for the INN model and improve the recovery of new airfoil shapes with desired performance characteristics. We find that the dimension reduction identifies two dominant modes, relating to airfoil thickness and camber, that optimally determine the airfoil's aerodynamics. We demonstrate the capability of the proposed INN model to generate 100 airfoils that satisfy the specific aerodynamic and structural characteristics.

airfoil design↗
DOE OSTI2020

Enhanced Menshutkin S N 2 Reactivity in Mesoporous Silica: The Influence of Surface Catalysis and Confinement

A significant enhancement in the Menshutkin S N 2 reaction between 1-methylimidazole (MeIm) and methyl thiocyanate (MeSCN) is observed when the reaction is confined in the nanoscale silica pores of MCM41 and SBA15. The experiments in the silica pores are conducted without surrounding bulk reaction mixture. The influences of temperature, pore radius, and surface chemistry on the kinetics of the confined reaction are analyzed with time-dependent infrared spectroscopy, molecular dynamics simulations, and ab initio calculations. The rate constant of the pseudo-first order reaction increases with decreasing pore size, and the activation energy is found to decrease by 5.6 kJ/mol in the smallest pore studied (2.8 nm) relative to the bulk reaction. The rate constant dependence on pore size is accurately described by a two-state model in which molecules within the 4.6 Å interfacial layer experience a 2.4-fold rate constant increase relative to those reacting at the bulk rate further away from the interface. The removal of polar silanol groups from the silica surface via passivation with trimethylsilyl chloride results in bulk-like kinetics despite a reduction in the pore diameter, demonstrating the role of silanols as catalytic sites. Here, electronic structure calculations of the energy profile on a model silica surface confirm that silanol groups, particularly those of the vicinal type, can reduce the activation energy and reaction endothermicity through the donation of hydrogen bonds to the reactant, transition state, and product complexes.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Modeling Pore Closure in the Hot Isostatic Pressing of Additively Manufactured Inconel 718 Samples

Additive manufacturing provides opportunity for a new world of possibilities for metallic component design and fabrication; however, as-built part quality is notoriously variable, anisotropic, and degraded by porous defects. To improve quality, parts are commonly post processed using a variety of techniques including hot isostatic pressing (HIP). During HIP, high temperature and pressure is employed to improve microstructure and reduce pore volume by inducing visco-plastic deformation in the metallic substrate. Validated computational capabilities can provide predictions to guide the selection of processing condition, expected pore reduction, and the effects of varying entrapped gas in the pores. This discussion describes a micro-scale finite element structural model developed to predict pore closure due to HIP in as-built additively manufactured Inconel 718 samples produced by the laser powder bed fusion process. The model accounts for plastic deformation, creep, and internal pressure for a single pore. Pores are characterized in physical samples before and after HIP, and model predictions are compared to this measured data.

defect model prediction↗
DOE OSTI2019

Anisotropic structural dynamics of monolayer crystals revealed by femtosecond surface X-ray scattering

Ultrafast X-ray scattering is one of the primary tools to track intrinsic crystallographic evolution with atomic accuracy in real time. However, its application to study nonequilibrium structural properties at the two-dimensional limit remains a long-standing challenge due to a significant reduction of diffraction volume and complexity of data analysis. Here, we report femtosecond surface X-ray diffraction in combination with crystallographic model-refinement calculations to quantify the ultrafast structural dynamics of monolayer WSe 2 crystals supported on a substrate. We found the absorbed optical photon energy is preferably coupled to the in-plane lattice vibrations within one picosecond whereas the out-of-plane lattice vibration amplitude remains unchanged during the first ten picoseconds. The model-assisted fitting suggests an asymmetric intralayer spacing change upon excitation. The observed nonequilibrium anisotropic structural dynamics agrees with first-principles modelling in both real and momentum space, marking the distinct structural dynamics of monolayer crystals from their bulk counterparts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Characterizing Structural Controls of EGS-Candidate and Conventional Geothermal Reservoirs in the Great Basin: Developing Successful Exploration Strategies in Extended Terranes

We conducted a comprehensive analysis of the structural controls of geothermal systems within the Great Basin and adjacent regions. Our main objectives were to: 1) Produce a catalogue of favorable structural environments and models for geothermal systems. 2) Improve site-specific targeting of geothermal resources through detailed studies of representative sites, which included innovative techniques of slip tendency analysis of faults and 3D modeling. 3) Compare and contrast the structural controls and models in different tectonic settings. 4) Synthesize data and develop methodologies for enhancement of exploration strategies for conventional and EGS systems, reduction in the risk of drilling non-productive wells, and selecting the best EGS sites.

15 GEOTHERMAL ENERGY↗
NASA NTRS1993

Transverse cracking and stiffness reduction in composite laminates

A study of transverse cracking mechanism in composite laminates is presented using a singular hybrid finite element model. The model provides the global structural response as well as the precise local crack-tip stress fields. An elasticity basis for the problem is established by employing Lekhnitskii's complex variable potentials and method of eigenfunction expansion. Stress singularities associated with the transverse crack are obtained by decomposing the deformation into the symmetric and antisymmetric modes and proper boundary conditions. A singular hybrid element is thereby formulated based on the variational principle of a modified hybrid functional to incorporate local crack singularities. Axial stiffness reduction due to transverse cracking is studied. The results are shown to be in very good agreement with the existing experimental data. Comparison with simple shear lag analysis is also given. The effects of stress intensity factors and strain energy density on the increase of crack density are analyzed. The results reveal that the parameters approach definite limits when crack densities are saturated, an evidence of the existence of characteristic damage state.

Yuan, F. G.↗
DOE OSTI2015

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.

Stander, Nielen↗
NASA NTRS1992

Dynamic test/analysis correlation using reduced analytical models

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Mcgowan, Paul E.↗
DOE OSTI2019

Reduction Mechanism of Iron Oxide Briquettes by Carbonaceous Materials Extracted from Blast Furnace Dust

The reducibility of carbonaceous powder extracted from blast furnace dust was investigated. In this study, pickling treatment was used for BF bag dust and BF gravitational dust to extract the carbonaceous material. The structural characteristics of carbonaceous material were studied by X-ray diffraction, scanning electron microscope, and energy-dispersive spectrometer. The reduction of ferric oxide and carbon gasification experiments were researched by thermogravimetry. The results show that the pickled raw coal gives the highest reducibility, which is followed by BF bag dust and BF gravitational dust. The reason for this is that the higher disordered crystalline structure leads to stronger gasification reactivity, and further results in stronger reduction reactivity. Based on the randomized nucleation model, the kinetic analysis shows that the activation energies for the reduction reaction of BF gravitational dust, BF bag dust, and raw coal after pickling are 300.14, 180.43, and 124.62 kJ mol{sup −1}, respectively.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Recent advances in reduction methods for nonlinear problems

Status and some recent developments in the application of reduction methods to nonlinear structural mechanics problems are summarized. The aspects of reduction methods discussed herein include: (1) selection of basis vectors in nonlinear static and dynamic problems, (2) application of reduction methods in nonlinear static analysis of structures subjected to prescribed edge displacements, and (3) use of reduction methods in conjunction with mixed finite element models. Numerical examples are presented to demonstrate the effectiveness of reduction methods in nonlinear problems. Also, a number of research areas which have high potential for application of reduction methods are identified.

Noor, A. K.↗
NASA NTRS2010

NICMOS Spectroscopy of HD 189733b

Spectral features corresponding to methane and water opacity were reported based on transmission spectroscopy of HD 189733b with Hubble/NICMOS. Recently, these data, and a similar data set for XO-1b, have been reexamined in Gibson et al. 2010, who claim they cannot reliably reproduce prior results. We examine the methods used by the Gibson team and identify two specific issues that could act to increase the formal uncertainties and to create instability in the minimization process. This would also be consistent with the GPA10 finding that they could not identify a way to select among the several instrument models they constructed. In the case of XO-1b, the Gibson team significantly changed the way in which the instrument model is defined (both with respect to the three approaches they used for HD 189733b, and the approach used by previous authors); this change, which omits the effect of the spectrum position on the detector, makes direct intercomparison of results difficult. In the experience of our group, the position of the spectrum on the detector is an important element of the instrument model because of the significant residual structure in the NICMOS spectral flat field. The approach of changing instrument models significantly complicates understanding the data reduction process and interpreting the results. Our team favors establishing a consistent method of handling NICMOS instrument systematic errors and applying it uniformly to data sets.

infrared↗
DOE OSTI2020

Generic, Sparse Tensor Core for Neural Networks

Sparse neural network attracts more attention for model compression, fast execution, and power reduction. The state-of-the-art designed sparse tensor core for structured and static sparsity, which did not support well for generic or dynamic sparsity. We design a sparse tensor core to support generic sparsity pruning with a novel hybrid and blocked sparse matrix storage format, HB-ELL, which saves computation and storage while keeping the most significant elements, as well as supporting dynamic sparsity for data flow in neural networks. We achieve better performance with preliminary results than the state-of- the-art on an NVIDIA GPU simulator.

Wu, Xiaolong↗
DOE OSTI2014

Concentration Effects of Polymer Electrolyte Membrane Degradation Products on Oxygen Reduction Activity for Three Platinum Catalysts

A rotating disk electrode (RDE) along with cyclic voltammetry (CV) and linear sweep voltammetry (LSV), were used to investigate the impact of two model compounds representing degradation products of Nafion and 3M perfluorinated sulfonic acid membranes on the electrochemical surface area (ECA) and oxygen reduction reaction (ORR) activity of polycrystalline Pt, nano-structured thin film (NSTF) Pt (3M), and Pt/Vulcan carbon (Pt/Vu) (TKK) electrodes. ORR kinetic currents (measured at 0.9 V and transport corrected) were found to decrease linearly with the log of concentration for both model compounds on all Pt surfaces studied. Ultimately, model compound adsorption effects on ECA were more abstruse due to competitive organic anion adsorption on Pt surfaces superimposing with the hydrogen underpotential deposition (HUPD) region.

30 DIRECT ENERGY CONVERSION↗