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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Particle physics with the LHC data

In this talk, I give reasons why we regard GUT as a part of the Standard Model of Elementary Particle Physics that explain all phenomena observed at high energy experiments and in the universe, with a few notable exceptions. It is based on my introduction-to-elementary-particle-physics lectures for the first year graduate students at Sokendai, Graduate University for Advanced Studies. No new observation is made, but I think that it is important for us to examine the LHC data from the GUT viewpoint together with our fresh students.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Identification and Resolution of Gaps in Mechanistic Source Term and Consequence Analysis Modeling for Molten Salt Reactors Salt Spill Scenarios

This report represents an assessment of the gaps in Mechanistic Source Term (MST) and consequence assessment modeling for Molten Salt Reactors (MSRs). The current capabilities for MELCOR and the MELCOR Accident Code System (MACCS) are discussed, along with updates needed in order to address specific needs for MSRs. A test plan developed by Argonne National Laboratories is discussed as addressing some of these gaps, while some will require additional attention. Further recommendations are made on addressing these gaps. This report satisfies the DOE NE Milestone M2RD-21SN0601061 to leverage MELCOR and MACCS to identify parameters of importance for source term assessments for salt spill experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1988

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗
NASA NTRS1989

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurataely model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗
DOE OSTI2022

A review of active probing-based system identification techniques with applications in power systems

System identification is becoming a relevant research area for numerous applications in power grids due to the increasing complexity of the system. A paradigm shift in power system infrastructure driven by renewable energy resources, controllable loads, and new power electronics technologies have given rise to new challenges in power systems operation and control. This increased complexity of power systems and unavailability of physics-based models of most inverter-based resources requires that traditional modeling of power systems approaches be complemented by system identification-based black or grey box modeling techniques. In light of the importance of system identification and little attention paid to the applications of these techniques in transforming power systems, this paper provides a comprehensive review of active probing-based system identification methods in the context of power system applications. It reviews applications of both linear and nonlinear system identification with discussion on their potential and key takeaways. To motivate a further practical use in power systems, the paper provides an example of system identification, to develop a state space model of an unknown plant with step-by-step details. The paper highlights the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Fuselage-Induced Velocity Model for LRTA, RTA, and HART Fuselages

In order to make the aerodynamic fuselage-rotor interference effects available to comprehensive rotor codes, a simple analytical model of the fuselage-induced velocities within the volume of rotor blade operation above the fuselage is developed here for the following bodies used in wind tunnel experiments: the Large Rotor Test Apparatus (LRTA), the Rotor Test Apparatus (RTA), and the Higher Harmonic Control Aeroacoustic Rotor Test (HART).While the first two are used in the National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames, California, the third one is used by DLR in the large low-speed facility of the German-Dutch wind tunnel in the Netherlands. The fuselage-induced velocity model is based on parameter identification of isolated fuselage-induced velocity data (computed by means of computational fluid dynamics, CFD) and is intended to be generic enough to be used for real helicopter fuselages as well. The accuracies obtained in reproducing the CFD data show a remaining average error of less or equal 5 of the peak-to-peak induced velocity range, which is considered sufficient for comprehensive code analysis.

HART↗
NASA NTRS1996

Flight test maneuvers for closed loop lateral-directional modeling of the F-18 High Alpha Research Vehicle (HARV) using forebody strakes

Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for closed loop parameter identification purposes, specifically for lateral linear model parameter estimation at 30, 45, and 60 degrees angle of attack, using the Actuated Nose Strakes for Enhanced Rolling (ANSER) control law in Strake (S) model and Strake/Thrust Vectoring (STV) mode. Each maneuver is to be realized by applying square wave inputs to specific pilot station controls using the On-Board Excitation System (OBES). Maneuver descriptions and complete specification of the time/amplitude points defining each input are included, along with plots of the input time histories.

Morelli, E. A.↗
DOE OSTI2019

Singlet Fission Rate: Optimized Packing of a Molecular Pair. Ethylene as a Model

Here, a procedure is described for unbiased identification of all π-electron chromophore pair geometry choices that locally maximize the rate of conversion of a singlet exciton into a singlet biexciton (triplet pair), using a simplified version of the diabatic frontier orbital model of singlet fission (SF).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

An Empirical Bayes Approach to Spatial Analysis

Multi-channel LANDSAT data are collected in several passes over agricultural areas during the growing season. How empirical Bayes modeling can be used to develop crop identification and discrimination techniques that account for spatial correlation in such data is considered. The approach models the unobservable parameters and the data separately, hoping to take advantage of the fact that the bulk of spatial correlation lies in the parameter process. The problem is then framed in terms of estimating posterior probabilities of crop types for each spatial area. Some empirical Bayes spatial estimation methods are used to estimate the logits of these probabilities.

Morris, C. N.↗
NASA NTRS1986

COFS 3: Multibody dynamics and control technology

COFS 3 is the third project within the Control of Flexible Structures (COFS) program. It deals with developing multibody dynamics and control technology for large space structures. It differs from COFS 1 and 2 in two respects. First, it addresses a more complex class of structure, and second it is basically a scale model ground test and analysis program while COFS 1 and 2 feature Shuttle flight experiments. The specific technology thrusts within COFS 3 are model sensitivities, test methods, analysis validation, systems identification, and vibration suppression. The COFS 3 project will develop the methods for using dynamically scaled models and analysis to predict the structural dynamics of large space structures. The project uses the space station as a focus because it is typical of the structures of interest and provides the first opportunity to obtain full-scale on-orbit dynamics data.

Letchworth, Robert↗
DOE OSTI2016

From genomes to metabolomes: Understanding mechanisms of symbiosis and cell-cell signaling using the archaeal system Ignicoccus-Nanoarchaeum

The main objective of this project was to use symbiotic Nanoarchaeaota, a group of thermophilic Archaea that are obligate symbionts/parasites on other Archaea, to develop an integrated multi-omic approach to study inter-species interactions as well as to understand fundamental mechanism that enable such relationships. As part of this grant we have achieved a number of important milestone on both technical and scientific levels. On the technical side, we developed immunofluorescence labeling and tracking methods to follow Nanoarchaeota in cultures and in environmental samples, we applied such methods in conjunction with flow cytometry to quantify and isolate uncultured representatives from the environment and characterized them by single cell genomics. On the proteomics side, we developed a more efficient and sensitive method to recover and semi-quantitatively measure membrane proteins, while achieving high total cellular proteome coverage (70-80% of the predicted proteome). Metabolomic analyses used complementary NMR and LC/GC mass spectrometry and led to the identification of novel lipids in these organisms as well as quantification of some of the major metabolites. Importantly, using several informatics approaches we were also able to integrate the transcriptomic, proteomic and metabolomic datasets, revealing aspects of the interspecies interaction that were not evident in the single omic analyses (manuscript in review). On the science side we determined that N. equitans and I. hospitalis are metabolically coupled and that N. equitans is strictly dependent on its host both for metabolic precursors and energetic needs. The actual mechanism by which small molecules move across the cell membrane remains unknown. The Ignicoccus host responds to the metabolic and energetic burned by upregulating of key primary metabolism steps and ATP synthesis. The two species have co-evolved, aspect that we determined by comparative genomics with other species of Ignicoccus (manuscript in preparation) and by characterizing other similar Nanoarchaeota systems. Using a single cell genomics approach we characterized the first terrestrial geothermal Nanoarchaeota system, from Yellowstone National Park. That nanoarchaeon uses a different host, a species of Sulfolobales, and comparative genomics with N. equitans-Ignicoccus allowed us to come up with an evolutionary model for the evolution of this group of organisms across marine and terrestrial ecosystems. Based on metabolic inferences we were also able to isolate in culture the first such terrestrial nanoarchaeal system, also from Yellowstone, which involves a species of Acidilobus. The novel nanoarchaeal system was characterized using proteomics and it helped us better understand the metabolic capabilities of these organisms as well as how co-evolution shapes the genomes of interacting species. It was also one of the very few cases in which prior genomic data was used to successfully design an approach to culture an organism, which remains the gold standard in microbiology research. As a better understanding of interspecies interaction requires multiple model systems, we have pursued identification and genomic characterization or isolation of additional nanoarchaeal systems from geographically and geochemically distinct environments. Two additional nanoarchaeal systems are presently being characterized from hot springs in Yellowstone and Iceland and will be the subject to future publications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Optimized System Identification

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

Juang, Jer-Nan↗
DOE OSTI2024

Convergence of Weak-SINDy Surrogate Models

In this paper, we give an in-depth error analysis for surrogate models generated by a variant of the Sparse Identification of Nonlinear Dynamics (SINDy) method. We start with an overview of a variety of nonlinear system identification techniques, namely SINDy, weak-SINDy, and the occupation kernel method. Under the assumption that the dynamics are a finite linear combination of a set of basis functions, these methods establish a linear system to recover coefficients. We illuminate the structural similarities between these techniques and establish a projection property for the weak-SINDy technique. Following the overview, we analyze the error of surrogate models generated by a simplified version of weak-SINDy. In particular, under the assumption of boundedness of a composition operator given by the solution, we show that (i) the surrogate dynamics converges towards the true dynamics and (ii) the solution of the surrogate model is reasonably close to the true solution. Finally, as an application, we discuss the use of a combination of weak-SINDy surrogate modeling and proper orthogonal decomposition (POD) to build a surrogate model for partial differential equations (PDEs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

On Optimal Input Design and Model Selection for Communication Channels

In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

fast identification↗
NASA NTRS1986

Validation of large space structures by ground tests

The paper presents concepts designed to validate, through the use of ground tests, mathematical models of continuous type structures and structures comprised of interconnecting subsystems. For continuous-type structures, a multiple boundary condition test approach is considered in which the basic idea is to perform a large number of tests using artificial boundary conditions from which good ground test data can be obtained. The test ensures an arbitrarily large number of test data for use in the validation and updating of the mathematical model. Another approach, applicable to structures comprised of subsystems, involves the identification of significant structural elements for the system dynamic model which are not validated by standard modal tests of the subsystems.

Wada, B. K.↗