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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Large-signal Stability Analysis of Grid-forming Inverters with Equivalent-circuit Models

Here, this paper proposes an energy function-based direct method for large-signal stability assessment of grid-forming (GFM) inverters leveraging an equivalent-circuit representation of all involved control- and physical-layer dynamics. Three different primary controls, a standard inner-current outer-voltage cascaded-control architecture, output LCL filter, and reference-current saturation limiting are featured in the modeling and analysis framework. A composite energy function for the GFM inverter is obtained by summing up individual energy contributions gleaned from the circuit representation. The approach can readily be generalized to different primary controls, output-filter arrangements, and current limiters since it is based on a circuit-theoretic foundation. Numerical simulations validate the efficacy of the approach in estimating the critical clearing time following a large-signal disturbance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

The triose model - Glyceraldehyde as a source of energy and monomers for prebiotic condensation reactions

Glyceraldehyde acts as a source of energy and monomers in a new model of the origin of life. The simplest form of the model functions by converting formaldehyde from the environment into glyceraldehyde which spontaneously forms hemiacetal adducts that are oxidized to polyglyceric acid. Polyglyceric acid, in turn, acts as an autocatalyst with a rudimentary replicating ability. A unique property of the model is its ability to unite the origin of metabolism and the origin of polymer synthesis into a single process. Furthermore, the chemical resemblance of the model to glycolysis gives it the potential to develop a biological metabolism in a straightforward manner.

Weber, Arthur L.↗
NASA NTRS1990

Application of the algebraic RNG model for transition simulation

The algebraic form of the RNG model of Yakhot and Orszag (1986) is investigated as a transition model for the Reynolds averaged boundary layer equations. It is found that the cubic equation for the eddy viscosity contains both a jump discontinuity and one spurious root. A yet unpublished transformation to a quartic equation is shown to remove the numerical difficulties associated with the discontinuity, but only at the expense of merging both the physical and spurious root of the cubic. Jumps between the branches of the resulting multiple-valued solution are found to lead to oscillations in flat plate transition calculations. Aside from the oscillations, the transition behavior is qualitatively correct.

Lund, Thomas S.↗
NASA NTRSDate not supplied

Finite Element Modeling of Plastic Deformation During Spin Forming of Aluminum 6061-O

Spin and flow forming are metal deformation techniques in which a disk or tube of material is radially thinned and axially lengthened over a rotating mandrel. A finite-element continuum model (FEM) based on commercial software (DEFORM®) was developed to determine the stress/strain distribution and damage accumulation in a flow-formed, near-net-shape part. Computational validation and experimental verification of the model was leveraged to assess the effectiveness of computer simulations. Quantitative comparisons between experimental and computational results show promise for applying a FEM to the flow forming process. Experimental failure locations correlated well with computed damage gradients, and there was good agreement between the measured and predicted roller forces during forming.

Elizabeth Urig↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS1961

Aerodynamic Loads at Mach Numbers from 0.70 to 2.22 on an Airplane Model Having a Wing and Canard of Triangular Plan Form and Either Single or Twin Vertical Tails: Tabulated Data for the Model with Twin Vertical Tails - Supplement 2

Tabulated results of a wind-tunnel investigation of the aerodynamic loads on a canard airplane model with twin vertical tails are presented for Mach numbers from 0.70 to 2.22. The Reynolds number for the measurements was 2.9 x 10(exp 6) based on the wing mean aerodynamic chord. The results include local static-pressure coefficients measured on the wing, body, and one of the vertical tails for angles of attack from -4 degrees to 16 degree angles of sideslip of 0 degrees and 5.3 degrees, and nominal canard deflections of O degrees and 10 degrees. Also included are section force and moment coefficients obtained from integrations of the local pressures and model-component force and moment coefficients obtained from integrations of the section coefficients. Geometric details of the model are shown and the locations of the pressure orifices are shown. An index to the data contained herein is presented and definitions of nomenclature are given. Detailed descriptions of the model and experiments and a brief discussion of some of the results are given. Tabulated results of measurements of the aerodynamic loads on the same canard model but having a single vertical tail instead of twin vertical tails are presented.

Peterson, Victor L.↗
NASA NTRS1946

Jet-boundary and Plan-form Corrections for Partial-Span Models with Reflection-Plane, End-Plate, or No End-Plate in a Closed Circular Wind Tunnel

A method is presented for determining the jet-boundary and plan-form corrections necessary for application to test data for a partial-span model with a reflection plane, an end plate, or no end plate in a closed circular wind tunnel. Examples are worked out for a partial-span model with each of the three end conditions in the Langley 19-foot pressure tunnel and the corrections are applied to measured values of lift, drag, pitching-moment, rolling-moment, and yawing-moment coefficients.

Sivells, James C↗
NASA NTRS1994

LQG optimal compensator transfer function for the NASA LaRC CSI Evolutionary Model

Following the general form for LQG optimal compensators for flexible structures with collocated rate sensors we develop an explicit compensator transfer function for the NASA LaRC CSI Evolutionary model in the form: psi(i omega) = g i omega B(sub u)(sup *)(-M(sub b)omega(exp 2) + T(i omega) + i gamma omega B(sub u)Bu(sub u)(sup *))(exp -1)B(sub u) where T(i omega) is a 48 x 48 positive definite matrix whose derivation is the main result of this report. The undamped mode frequencies can be expressed in terms of T(i omega) as the zeros of Det (-omega(exp 2)M(sub b) + T(i omega)) while 'clamped-clamped' modes of the structure (with all nodes clamped) are the poles.

Balakrishnan, A. V.↗
DOE OSTI2026

Dispersive and nondispersive 𝐾-matrix formalisms

The modeling of coupled-channel effects has become increasingly important due to the availability of highly precise data for a large variety of hadronic (re)scattering processes. The 𝐾-matrix is a powerful, yet comparatively simple, method to describe scattering amplitudes, including coupled-channel effects, with the aim of interpreting experimental data. Throughout the literature, a range of dispersive and nondispersive 𝐾-matrix methods are employed. Here, we compare the dispersive and nondispersive formulations in the context of the N/D method. It is shown that the methods are equivalent in the physical region under 𝐾-matrix reparametrization. Differences away from the physical region are examined. Applications to synthetic data are used to illustrate the effects of model choices concerning form factors and the application of dispersion relations, with the goal of clarifying best practices. We find no clear preference with regard to dispersive modeling. In contrast, we find that interpretational ambiguity of the bare model parameters—and even of the form of the bare model—is endemic, and recommend a thorough sampling of data and model spaces to assess conclusion robustness.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Approximating a finite element model of a hybrid deployable truss by a discrete mass model

The NASTRAN finite element model of the MSFC/hybrid deployable truss is approximated by a model consisting of four bodies serially connected by a spring hinge suspension. The truss is decomposed into four serially connected modules determining the total mass and rotational inertias for a rigid body with its mass center on the axis of the truss for each module. A five-body cantilever truss model is developed along with an undamped form of this model. Spring coefficient values are generated to match eigenvalues of the latter model with those of the NASTRAN model. Damping coefficients are then determined that provide n percent of critical damping for the model.

Chichester, F. D.↗
NASA NTRSDate not supplied

Three-dimensional in Situ Observations of Polycrystalline Microstructure Evolution During Directional Solidification of Transparent Alloys Aboard the ISS and Quantitative Comparison with Numerical Modeling

Cellular/dendritic microstructures formed during solidification have a crucial influence on the mechanical properties of a wide range of structural alloys. By minimizing the amount of gravity-induced convection in the liquid, directional solidification experiments using transparent organic alloys conducted in the DECLIC-DSI onboard the International Space Station have provided unique 3D in situ observations of the spatiotemporal evolution of the solid-liquid interface during the formation of cellular and dendritic microstructures under purely diffusive growth conditions in polycrystalline samples containing several grains with a small misorientation with respect to the temperature gradient. Those observations have made it possible to perform benchmark quantitative comparisons with the predictions of state-of-the-art phase-field simulations of microstructure formation in 3D on experimentally relevant length and time scales. This talk will report quantitative comparisons between microgravity experiments and phase-field simulations in succinonitrile-camphor alloys of two different compositions that shed new light on the role of subgrain boundaries in the spatiotemporal evolution of the primary cellular spacing and the selection of dendritic array structures.

Kaihua Ji↗
NASA NTRSDate not supplied

Three-Dimensional In Situ Observations of Polycrystalline Microstructure Evolution During Directional Solidification of Transparent Alloys Aboard the ISS and Quantitative Comparison with Numerical Modeling

Cellular/dendritic microstructures formed during solidification have a crucial influence on the mechanical properties of a wide range of structural alloys. By minimizing the amount of gravity-induced convection in the liquid, directional solidification experiments using transparent organic alloys conducted in the DECLIC-DSI onboard the International Space Station have provided unique 3D in situ observations of the spatiotemporal evolution of the solid-liquid interface during the formation of cellular and dendritic microstructures under purely diffusive growth conditions. Those observations have made it possible to perform benchmark quantitative comparisons with the predictions of state-of-the-art phase-field simulations of microstructure formation in 3D on experimentally relevant length and time scales. This talk will report quantitative comparisons between microgravity experiments and phase-field simulations in succinonitrile-camphor alloys of two different compositions, which shed new light on the selection of dendritic array structures, and on roles of macroscopic curvatures and subgrain boundaries between grains with a small misorientation with respect to the temperature gradient in the spatiotemporal evolution of the primary cellular spacing.

Kaihua Ji↗
NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗
DOE OSTI2024

Electromagnetic and two-photon transition form factors of the pseudoscalar mesons: An algebraic model computation

We compute electromagnetic and two-photon transition form factors of ground-state pseudoscalar mesons: π , K , η c , η b . To this end, we employ an algebraic model based upon the coupled formalism of Schwinger-Dyson and Bethe-Salpeter equations. Within this approach, the dressed quark propagator and the relevant Bethe-Salpeter amplitude encode the internal structure of the corresponding meson. Electromagnetic properties of the meson are probed via the quark-photon interaction. The algebraic model employed by us unifies the treatment of all ground-state pseudoscalar mesons. Its parameters are carefully fitted performing a global analysis of existing experimental data including the knowledge of the charge radii of the mesons studied. We then compute and predict electromagnetic and two-photon transition form factors for a wide range of probing photon momentum-squared which is of direct relevance to the experimental observations carried out thus far or planned at different hadron physics facilities such as the Thomas Jefferson National Accelerator Facility (JLab) and the forthcoming Electron-Ion Collider. We also present comparisons with other theoretical models and approaches and lattice quantum chromodynamics. Published by the American Physical Society 2024

Higuera-Angulo, I. M. (ORCID:0000000256008875)↗
NASA NTRS1989

The transient performance of a two-phase fluid reservoir

Thermal control of future large, high power spacecraft will require a two-phase fluid central bus. The two-phase fluid reservoir is a critical component in the two-phase fluid bus. It both controls the saturation temperature and provides a space for volumetric changes. A dynamic reservoir simulation model does not currently exist, but it is needed to expedite efforts and reduce risk. During 1989 an effort was made to develop a simulation model of the transient performance of a two-phase fluid reservoir. As a beginning, a preliminary model was developed. It is based upon component mathematical models in lumped parametric form and build upon five component mathematical models for calculating dynamic responses of two-phase fluid reservoirs, primary feedback elements, controller commands, heater actuators, and reservoir heaters. As much as possible, the model took advantage of the available SINDA'85/FLUINT thermal/fluid integrator. Additional calculation logic and computer subroutines were developed to complete implementation of the model. The model is capable of simulating dynamic response of an equilibrium two-phase fluid reservoir. Modification of the model to include the liquid/vapor nonequilibrium is required for applications of the model to simulate performance of reservoir in which the liquid and vapor phases of the reservoir fluid are not in equilibrium. In addition, the model in its present form, needs to be refined in several respects. More empirical data are needed to guide the model development. The model may then be used to conduct a full parametric study of two-phase fluid reservoirs. More complexities in two-phaes flow regions in laboratory and flight conditions may have to be considered eventually if empirical data cannot be simulated satisfactorily. System with other components arrangement also need to be simulated if optimization is ever to be attained. The present model does, however, preliminarily demonstrates that such analyses are quite possible and offers a far less expensive method to understand the transient of a two-phase fluid reservoir system than a totally headware approach.

Chi, Joseph↗
NASA NTRS2010

Algorithm for Stabilizing a POD-Based Dynamical System

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Kalb, Virginia L.↗
NASA NTRS1992

Finite difference time domain grid generation from AMC helicopter models

A simple technique is presented which forms a cubic grid model of a helicopter from an Aircraft Modeling Code (AMC) input file. The AMC input file defines the helicopter fuselage as a series of polygonal cross sections. The cubic grid model is used as an input to a Finite Difference Time Domain (FDTD) code to obtain predictions of antenna performance on a generic helicopter model. The predictions compare reasonably well with measured data.

Cravey, Robin L.↗