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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Optimization of the lithium/thionyl chloride battery

A 1-D math model for the lithium/thionyl chloride primary cell is used in conjunction with a parameter estimation technique in order to estimate the electro-kinetic parameters of this electrochemical system. The electro-kinetic parameters include the anodic transfer coefficient and exchange current density of the lithium oxidation, alpha sub a,1 and i sub o,i,ref, the cathodic transfer coefficient and the effective exchange current density of the thionyl chloride reduction, alpha sub c,2 and a sup o i sub o,2,ref, and a morphology parameter, Xi. The parameter estimation is performed on simulated data first in order to gain confidence in the method. Data, reported in the literature, for a high rate discharge of an experimental lithium/thionyl chloride cell is used for an analysis.

White, Ralph E.↗
DOE OSTI2021

Machine learning methods for probabilistic locked-mode predictors in tokamak plasmas

A rotating tokamak plasma can interact resonantly with the external helical magnetic perturbations, also known as error fields. This can lead to locking and then to disruptions. We leverage machine learning (ML) methods to predict the locking events. We use a coupled third-order nonlinear ordinary differential equation model to represent the interaction of the magnetic perturbation and the plasma rotation with the error field. This model is sufficient to describe qualitatively the locking and unlocking bifurcations. Here, we explore using ML algorithms with the simulation data and experimental data, focusing on the methods that can be used with sparse datasets. These methods lead to the possibility of the avoidance of locking in real-time operations. We describe the operational space in terms of two control parameters: the magnitude of the error field and the rotation frequency associated with the momentum source that maintains the plasma rotation. The outcomes are quan- tified by order parameters that completely characterize the state, whether locked or unlocked. We use unsupervised ML methods to classify locked/unlocked states and note the usefulness of a certain normalization of the order parameters. Three supervised ML classifiers are used in suite to estimate the probability of locking in the region of control parameter space with hysteresis, i.e., the set of control parameters for which both locked and unlocked states can exist. The results show that a neural network gives the best estimate of the locking probability. An analogy of the present locking model with the van der Waals equation of state is also provided.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

Abstract An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. Graphical abstract OFraMP applied to paclitaxel (ATB ID 35922).

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

Equivalent source modeling of the core magnetic field using magsat data

Experiments are carried out on fitting the main field using different numbers of equivalent sources arranged in equal area at fixed radii at and inside the core-mantle boundary. In fixing the radius for a given series of runs, the convergence problems that result from the extreme nonlinearity of the problem when dipole positions are allowed to vary are avoided. Results are presented from a comparison between this approach and the standard spherical harmonic approach for modeling the main field in terms of accuracy and computational efficiency. The modeling of the main field with an equivalent dipole representation is found to be comparable to the standard spherical harmonic approach in accuracy. The 32 deg dipole density (42 dipoles) corresponds approximately to an eleventh degree/order spherical harmonic expansion (143 parameters), whereas the 21 dipole density (92 dipoles) corresponds to approximately a seventeenth degree and order expansion (323 parameters). It is pointed out that fixing the dipole positions results in rapid convergence of the dipole solutions for single-epoch models.

Mayhew, M. A.↗
NASA NTRS2004

Discrete X-Ray Source Populations and Star-Formation History in Nearby Galaxies

This program aims in understanding the connection between the discrete X-ray source populations observed in nearby galaxies and the history of star-formation in these galaxies. The ultimate goal is to use this knowledge in order to constrain X-ray binary evolution channels. For this reason although the program is primarily observational it has a significant modeling component. During the first year of this study we focused on the definition of a pilot sample of galaxies with well know star-formation histories. A small part of this sample has already been observed and we performed initial analysis of the data. However, the majority of the objects in our sample either have not been observed at all, or the detection limit of the existing observations is not low enough to probe the bulk of their young X-ray binary populations. For this reason we successfully proposed for additional Chandra observations of three targets in Cycle-5. These observations are currently being performed. The analysis of the (limited) archival data for this sample indicated that the X-ray luminosity functions (XLF) of the discrete sources in these galaxies may not have the same shape as is widely suggested. However, any solid conclusions are hampered by the small number of detected sources. For this reason during the second year of this study, we will try to extend the sample in order to include more objects in each evolutionary stage. In addition we are completing the analysis of the Chandra monitoring observations of the Antennae galaxies. The results from this work, apart from important clues on the nature of the most luminous sources (Ultra-luminous X-ray sources; ULXs) provide evidence that source spectral and/or temporal variability does not significantly affect the shape of their X-ray luminosity functions. This is particularly important for comparisons between the XLFs of different galaxies and comparisons with predictions from theoretical models. Results from this work have been presented in several conferences. Refereed journal papers presenting these conclusions are currently in preparation. An important part of this study is the Chandra survey of the Small Magellanic Cloud, our second nearest star- forming galaxy. So far we have been awarded 5 Chandra observations of the central youngest part of the galaxy. These observations will help to study the very faint end of the young X-ray binary populations which is not possible to probe in more distant objects. Results from this study have been presented in several conferences and two papers are in preparation. In addition during year-2 we are planning of undertaking the task of identifying optical counterparts to the X-ray sources, which will help us to isolate interlopers (sources not associated with the SMC) and classify the X-ray binaries which are found to be associated with the SMC. In the theoretical front, the Star-Track X-ray binary population synthesis code which will be used for the modeling of the X-ray binary populations (led by co-I V. Kalogera and C. Belczynski), is complete. A first test using the XLF of the star-forming galaxy NGC-1569 showed remarkable agreement between the observed and the modeled XLF. These results are presented in an ApJ. Letters paper (Belczynski et al, 2004, 601, 147). During year-2 of this study we are planning of performing a parameter study in order to investigate which parameters are most important for the shape of the XLF. In addition we will perform comparisons with observations of other galaxies from our sample as they become available.

Zezas, Andreas↗
NASA NTRS1991

A second order iteration procedure for correlation of analysis frequencies with test data

A second derivative frequency modification procedure is developed to iteratively change analysis modeling parameters for the more rapid convergence of analytically determined frequencies to those obtained by structural dynamic testing. A nonlinear system of algebraic equations in the modeling parameters is derived and a rapidly converging iterative method for their solution is presented. Numerical results obtained show that the higher order formulation and nonlinear predictor-corrector solution procedure yields results which are more rapidly convergent than those obtained using only the usual linear first-order parameter modification procedure. The proposed higher order theory also connverges in some cases when the ordinary linear theory does not.

Ojalvo, I. U.↗
NASA NTRS1987

Numerical simulation of cometary nuclei. III - Internal temperatures of cometary nuclei

The thermal diffusion equation for the internal temperature of cometary nuclei is exactly solved by means of a one-dimensional numerical model in order to shed light on the complex behavior of these temperatures with varying orbital and thermal parameters and in order to consider possible cometary nucleus thermal evolution targets for comet rendezvous and/or sample-return missions. The concept of 'new' and 'old' comets, classified in terms of how many passages around the sun have been made, may take on new meaning in view of the present demonstration that differences in eccentricity between two comets having the same period and number of apparitions may yield significantly different internal temperature profiles.

Herman, Gary↗
NASA NTRS1986

The role of modeling and flight testing in rotorcraft parameter identification

The importance of recognizing that each lower-order model used for rotorcraft parameter identification has a limited range of applicability is illustrated in some detail. Examples are given to illustrate the use of conditioning the test input signals and the potential of using multi-axis test inputs to enhance the parameter identifiability. The paper discusses the benefits and limitations of using frequency sweeps as flight-test input signals for identification of frequency response for rotorcraft and for the subsequent fitting of parametric transfer-function models. This paper demonstrates the major role played by analytical modeling and the understanding of the physics involved in the rotorcraft flight dynamics, particularly understanding the limit of lower-order models, in achieving successful rotorcraft parameter identification.

Chen, R. T. N.↗
NASA NTRS1998

Attitude/attitude-rate estimation from GPS differential phase measurements using integrated-rate parameters

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Oshman, Yaakov↗
NASA NTRS1983

Computational methods for estimation of parameters in hyperbolic systems

Approximation techniques for estimating spatially varying coefficients and unknown boundary parameters in second order hyperbolic systems are discussed. Methods for state approximation (cubic splines, tau-Legendre) and approximation of function space parameters (interpolatory splines) are outlined and numerical findings for use of the resulting schemes in model "one dimensional seismic inversion' problems are summarized.

Banks, H. T.↗
NASA NTRS1992

Gravity field improvement using global positioning system data from TOPEX/Poseidon - A covariance analysis

The TOPEX/Poseidon satellite data can be used to improve the knowledge of the earth's gravitational field. The GPS data are especially useful for improving the gravity field over the world's oceans, where the current tracking data are sparse. Using realistic scenario for processing 10 days of GPS data, a covariance analysis is performed to obtain the expected improvement to the GEM-T2 gravity field. The large amount of GPS data and the large number of parameters (1979 parameters for the gravity field, plus carrier-phase biases, etc.) required special filtering techniques for efficient solution. The gravity-bin technique is used to compute the covariance matrix associated with the spherical harmonic gravity field. The covariance analysis shows that the GPS data from one 10-day arc of TOPEX/Poseidon with no a priori constraints can resolve medium degree and order (3-26) parameters with sigmas (standard deviations) that are an order of magnitude smaller than the corresponding sigmas of GEM-T2. When the information from GEM-T2 is combined with the TOPEX/Poseidon GPS measurements, an order-of-magnitude improvement is observed in low- and medium-degree terms with significant improvements spread over a wide range of degree and order.

Bertiger, Willy I.↗
NASA NTRS1989

Uncertainty bounds using sector theory

An approach based on sector-stability theory can furnish a description of the uncertainty associated with the frequency response of a model, given sector-bounds on the individual parameters of the model. The application of the sector-based approach to the formulation of useful uncertainty descriptions for linear, time-invariant multivariable systems is presently explored, and the approach is applied to two generic forms of parameter uncertainty in order to investigate its advantages and limitations. The results obtained show that sector-uncertainty bounds can be used to evaluate the impact of parameter uncertainties on the frequency response of the design model.

Waszak, Martin R.↗
NASA NTRS1992

Calibration of the ARID robot

The author has formulated a new, general model for specifying the kinematic properties of serial manipulators. The new model kinematic parameters do not suffer discontinuities when nominally parallel adjacent axes deviate from exact parallelism. From this new theory the author develops a first-order, lumped-parameter, calibration-model for the ARID manipulator. Next, the author develops a calibration methodology for the ARID based on visual and acoustic sensing. A sensor platform, consisting of a camera and four sonars attached to the ARID end frame, performs calibration measurements. A calibration measurement consists of processing one visual frame of an accurately placed calibration image and recording four acoustic range measurements. A minimum of two measurement protocols determine the kinematics calibration-model of the ARID for a particular region: assuming the joint displacements are accurately measured, the calibration surface is planar, and the kinematic parameters do not vary rapidly in the region. No theoretical or practical limitations appear to contra-indicate the feasibility of the calibration method developed here.

Doty, Keith L↗
NASA NTRS2009

Investigating Response from Turbulent Boundary Layer Excitations on a Real Launch Vehicle using SEA

Statistical Energy Analysis (SEA) response has been fairly well anchored to test observations for Diffuse Acoustic Field (DAF) loading by others. Meanwhile, not many examples can be found in the literature anchoring the SEA vehicle panel response results to Turbulent Boundary Layer (TBL) fluctuating pressure excitations. This deficiency is especially true for supersonic trajectories such as those required by this nation s launch vehicles. Space Shuttle response and excitation data recorded from vehicle flight measurements during the development flights were used in a trial to assess the capability of the SEA tool to predict similar responses. Various known/measured inputs were used. These were supplemented with a range of assumed values in order to cover unknown parameters of the flight. This comparison is presented as "Part A" of the study. A secondary, but perhaps more important, objective is to provide more clarity concerning the accuracy and conservatism that can be expected from response estimates of TBL-excited vehicle models in SEA (Part B). What range of parameters must be included in such an analysis in order to land on the conservative side in response predictions? What is the sensitivity of changes in these input parameters on the results? The TBL fluid structure loading model used for this study is provided by the SEA module of the commercial code VA One.

Harrison, Phillip↗
DOE OSTI2023

Systems and methods for hierarchical multi-objective optimization

A method for optimizing objective functions can include selecting an objective function based at least on a hierarchy, applying parameters to the objective function to generate an output, responsive to the output not satisfying a tolerance condition, assigning a penalty to the set of parameters and evaluating a convergence condition using the set of parameters and the penalty, responsive to the output satisfying the tolerance condition, evaluating an additional objective function using the parameters in an order corresponding to the hierarchy or evaluating the convergence condition responsive to the selected objective function being a final objective function, modifying the set of parameters using a genetic algorithm responsive to the set of parameters not satisfying the convergence condition, and outputting the set of parameters responsive to the set of parameters satisfying the convergence condition.

Chan, Henry↗
DOE OSTI2023

Surface enrichment dictates block copolymer orientation

Orientation of block copolymer (BCP) morphology in thin films is critical to applications as nanostructured coatings. Despite being well-studied, the ability to control BCP orientation across all possible block constituents remains challenging. Here, in this study, we deploy coarse-grained molecular dynamics simulations to study diblock copolymer ordering in thin films, focusing on chain makeup, substrate surface energy, and surface tension disparity between the two constituent blocks. We explore the multi-dimensional parameter space of ordering using a machine-learning approach, where an autonomous loop using a Gaussian process (GP) control algorithm iteratively selects high-value simulations to compute. The GP kernel was engineered to capture known symmetries. The trained GP model serves as both a complete map of system response, and a robust means of extracting material knowledge. We demonstrate that the vertical orientation of BCP phases depends on several counter-balancing energetic contributions, including entropic and enthalpic material enrichment at interfaces, distortion of morphological objects through the film depth, and of course interfacial energies. BCP lamellae are found more resistant to these effects, and thus more robustly form vertical orientations across a broad range of conditions; while BCP cylinders are found to be highly sensitive to surface tension disparity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2003

Program for User-Friendly Management of Input and Output Data Sets

A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alphanumeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that make sense as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations.

Klimeck, Gerhard↗
DOE OSTI2022

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

Post-training model compression can reduce the inference costs of deep neural networks, but uncompressed training still consumes enormous hardware resources and energy. To enable low-energy training on edge devices, it is highly desirable to directly train a compact neural network from scratch with a low memory cost. Low-rank tensor decomposition is an effective approach to reduce the memory and computing costs of large neural networks. However, directly training low-rank tensorized neural networks is a very challenging task because it is hard to determine a proper tensor rank a priori, and the tensor rank controls both model complexity and accuracy. Here, this paper presents a novel end-to-end framework for low-rank tensorized training. We first develop a Bayesian model that supports various low-rank tensor formats (e.g., CANDECOMP/PARAFAC, Tucker, tensor-train, and tensor-train matrix) and reduces neural network parameters with automatic rank determination during training. Then we develop a customized Bayesian solver to train large-scale tensorized neural networks. Our training methods shows orders-of-magnitude parameter reduction and little accuracy loss (or even better accuracy) in the experiments. On a very large deep learning recommendation system with over 4.2 ×10 9 model parameters, our method can reduce the parameter number to 1.6 ×10 5 automatically in the training process (i.e., by 2.6 ×10 4 times) while achieving almost the same accuracy. Code is available at https://github.com/colehawkins/bayesian-tensor-rank-determination.

compact neural networks↗