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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Adsorption of probe molecules in pillared interlayered clays: Experiment and computer simulation

In this paper we investigate the adsorption of various probe molecules in order to characterize the porous structure of a series of pillared interlayered clays (PILC). To that aim, volumetric and microcalorimetric adsorption experiments were performed on various Zr PILC samples using nitrogen, toluene, and mesitylene as probe molecules. For one of the samples, neutron scattering experiments were also performed using toluene as adsorbate. Various structural models are proposed and tested by means of a comprehensive computer simulation study, using both geometric and percolation analysis in combination with Grand Canonical Monte Carlo simulations in order to model the volumetric and microcalorimetric isotherms. On the basis of this analysis, we propose a series of structural models that aim at accounting for the adsorption experimental behavior, and make possible a microscopic interpretation of the role played by the different interactions and steric effects in the adsorption processes in these rather complex disordered microporous systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ab Initio Modeling of Structure and Properties of Single and Mixed Alkali Silicate Glasses

A density functional theory (DFT)-based ab initio molecular dynamics (AIMD) has been applied to simulate models of single and mixed alkali silicate glasses with two different molar concentrations of alkali oxides. The structural environments and spatial distributions of alkali ions in the 10 simulated models with 20% and 30% of Li, Na, K and equal proportions of Li–Na and Na–K are studied in detail for subtle variations among the models. Quantum mechanical calculations of electronic structures, interatomic bonding, and mechanical and optical properties are carried out for each of the models, and the results are compared with available experimental observation and other simulations. The calculated findings are in good agreement with the experimental data. We have used the novel concept of using the total bond order density (TBOD), a quantum mechanical metric, to characterize internal cohesion in these glass models. The mixed alkali effect (MAE) is visible in the bulk mechanical properties but not obvious in other physical properties studied in this paper. We demonstrate that Li doping deviates from expected trend due to the much stronger Li–O bonding than those of Na and K doping. Our method is in contrast with current studies in alkali-doped silicate glasses based only on geometric characterizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Model error estimation for large space systems

In-flight estimation of large structure model errors may have to be carried out in order to detect inevitable deficiencies in large structure controller/estimator models. These error estimates can most efficiently be obtained by the minimization of a quadratic functional of the model errors and on the subsequent analysis of the resulting optimal model error estimates. An integral operator approach to estimation leads to a geometrical interpretation of the model error estimation process. One of the significant insights gained with this interpretation is that the actual but unknown model errors can be decomposed as the sum of two distinct components that are orthogonal in some sense. One of these components is a so-called minimal error vector that retains many of the significant dynamics of the actual errors. The basic ideas in the model error estimation approach are first set forth with a two-dimensional analogy that has most of the essential features of the general estimation problem. The generalized results are then established and their application to a reference large structure model illustrated.

Rodriguez, G.↗
DOE OSTI2014

Distance Restraints from Crosslinking Mass Spectrometry: Mining a Molecular Dynamics Simulation Database to Evaluate Lysine-Lysine Distances

Integrative structural biology models the structures of protein complexes that are intractable by classical structural methods (because of extreme size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such method is chemical cross-linking mass spectrometry (XL-MS), in which cross-linked peptides, derived from a covalently cross-linked protein complex and identified by liquid chromatography-mass spectrometry, pinpoint protein residues close in three-dimensional space. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 Å long when fully extended. However, XL-MS studies on proteins of known structure frequently report cross-links that exceed this distance. Typically, a tolerance of ~3 Å is added to the theoretical maximum to account for this observation, with little justification for the value chosen. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of all protein folds, to investigate the change in lysine-lysine distances resulting from native-state dynamics on the time-scale of tens of nanoseconds. We conclude that observed cross-links are consistent with a protein structure if the distance between cross-linked lysine Nζ atoms is less than the cross-linker length plus 11.3 Å. For DSS or BS3, this corresponds to a Cα to Cα distance of 30.4 Å. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures, and indicates the appropriate values of an XLMS derived distance constraint to use in structural modeling.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Significance We provide a method for population-based structure modeling of whole diploid genomes using Hi-C data. The method considers the stochastic nature of chromosome structures, which allows a detailed analysis of the dynamic landscape of genome organizations. We predict and experimentally validate the presence of chromosome-specific higher-order centromere clusters, which can play a key role in the spatial organization of the human genome, specifically influencing the overall chromosome positioning, as well as the preference of specific chromosome conformations. Our approach generate predictive structural models of diploid genomes from Hi-C data, which can provide insights into the guiding principles of 3D genome organizations.

3D genome organization↗
DOE OSTI2017

Gradient-Based Optimization of Wind Farms with Different Turbine Heights: Preprint

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hub heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.

17 WIND ENERGY↗
DOE OSTI2023

Reducing uncertainty of high-latitude ecosystem models through identification of key parameters

Abstract Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Precision pointing and control of flexible spacecraft

The problem and long term objectives for the precision pointing and control of flexible spacecraft are given. The four basic objectives are stated in terms of two principle tasks. Under Task 1, robust low order controllers, improved structural modeling methods for control applications and identification methods for structural dynamics are being developed. Under Task 2, a lab test experiment for verification of control laws and system identification algorithms is being developed. For Task 1, work has focused on robust low order controller design and some initial considerations for structural modeling in control applications. For Task 2, work has focused on experiment design and fabrication, along with sensor selection and initial digital controller implementation. Conclusions are given.

Bantell, M. H., Jr.↗
DOE OSTI2024

A Novel Method to Train Classification Models for Structure Detection in In Situ Spacecraft Data

We present a method for creating spacecraft-like data which can be used to train Machine Learning (ML) models to detect and classify structures in in situ spacecraft data. First, we use the Grad-Shafranov equation to numerically solve for several magnetohydrostatic equilibria which are variations on a known analytic equilibrium. These equilibria are then used as the initial conditions for Particle-In-Cell simulations in which the structures of interest are observed and labeled. We then take one-dimensional slices through the simulations to replicate what a spacecraft collecting data from the simulation would observe. This sliced data then can be used as training data for the initial training of ML models intended for use on spacecraft data. We demonstrate the method applied to the problem of detecting small-scale plasmoids in the magnetotail, which is important for understanding complex magnetotail reconnection dynamics. The simple 1D classifier we train is able to detect more than 70% of the plasmoid points in the data set but also produces a large number of false positives. Our further work on this example problem is detailed, and further potential uses of the method are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2000

A Shell/3D Modeling Technique for the Analysis of Delaminated Composite Laminates

A shell/3D modeling technique was developed for which a local solid finite element model is used only in the immediate vicinity of the delamination front. The goal was to combine the accuracy of the full three-dimensional solution with the computational efficiency of a shell finite element model. Multi-point constraints provided a kinematically compatible interface between the local 3D model and the global structural model which has been meshed with shell finite elements. Double Cantilever Beam, End Notched Flexure, and Single Leg Bending specimens were analyzed first using full 3D finite element models to obtain reference solutions. Mixed mode strain energy release rate distributions were computed using the virtual crack closure technique. The analyses were repeated using the shell/3D technique to study the feasibility for pure mode I, mode II and mixed mode I/II cases. Specimens with a unidirectional layup and with a multidirectional layup were simulated. For a local 3D model, extending to a minimum of about three specimen thicknesses on either side of the delamination front, the results were in good agreement with mixed mode strain energy release rates obtained from computations where the entire specimen had been modeled with solid elements. For large built-up composite structures the shell/3D modeling technique offers a great potential for reducing the model size, since only a relatively small section in the vicinity of the delamination front needs to be modeled with solid elements.

Krueger, Ronald↗
NASA NTRS1987

A structure-based model of semantic integrity constraints for relational data bases

Data base management systems (DBMSs) are in widespread use because of the ease and flexibility with which users access large volumes of data. Ensuring data accuracy through integrity constraints is a central aspect of DBMS use. However, many DBMSs still lack adequate integrity support. In additon, a comprehensive theoretical basis for such support the role of a constraint classification system - has yet to be developed. This paper presents a formalism that classifies semantic integrity constraints based on the structure of the relational model. Integrity constraints are characterized by the portion of the data base structure they access, whether one or more relations, attributes, or tuples. Thus, the model is completely general, allowing the arbitrary specification of any constraint. Examples of each type of constraint are illustrated using a small engineering data base, and various implementation issues are discussed.

Rasdorf, William J.↗
DOE OSTI2014

Iron on GaN(0001) pseudo-1 × 1 (1+1/(12) ) investigated by scanning tunneling microscopy and first-principles theory

We have investigated sub-monolayer iron deposition on atomically smooth GaN(0001) pseudo-1 × 1 (1+1/(12) ). The iron is deposited at a substrate temperature of 360 °C, upon which reflection high energy electron diffraction shows a transformation to a √(3)×√(3)-R30° pattern. After cooling to room temperature, the pattern transforms to a 6 × 6, and scanning tunneling microscopy reveals 6 × 6 reconstructed regions decorating the GaN step edges. First-principles theoretical calculations have been carried out for a range of possible structural models, one of the best being a Ga dimer model consisting of 2/9 monolayer of Fe incorporated into 7/3 monolayer of Ga in a relaxed but distorted structure.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Active vibration control with model correction on a flexible laboratory grid structure

This paper presents experimental and computational comparisons of three active damping control laws applied to a complex laboratory structure. Two reduced structural models were used with one model being corrected on the basis of measured mode shapes and frequencies. Three control laws were investigated, a time-invariant linear quadratic regulator with state estimation and two direct rate feedback control laws. Experimental results for all designs were obtained with digital implementation. It was found that model correction improved the agreement between analytical and experimental results. The best agreement was obtained with the simplest direct rate feedback control.

Schamel, George C., II↗
NASA NTRS2004

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage (FOD) Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James↗
NASA NTRS2007

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage "FOD" Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/ health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite-element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James A.↗
DOE OSTI2015

Integrative Analysis of Metabolic Models – from Structure to Dynamics

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗