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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A survey of nonlinear robust optimization

Robust optimization (RO) has attracted great attention from the optimization community over the past decade. RO is dedicated to solving optimization problems subject to uncertainty: design constraints must be satisfied for all the values of the uncertain parameters within a given uncertainty set. Uncertainty sets may be modeled as deterministic sets (boxes, polyhedra, ellipsoids), in which case the RO problem may be reformulated via worst-case analysis, or as families of distributions. The challenge of RO is to reformulate or approximate robust constraints so that the uncertain optimization problem is transformed into a tractable deterministic optimization problem. Most reformulation methods assume linearity of the robust constraints or uncertainty sets of favorable shape, which represents only a fraction of real-world applications. This survey addresses nonlinear RO and includes problem formulations and applications, solution approaches, and available software with code samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

RMCProfile7 : reverse Monte Carlo for multiphase systems

This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.

Chemistry↗
DOE OSTI2022

Local Atomic Configuration in Pristine and A-Site Doped Silver Niobate Perovskite Antiferroelectrics

Antiferroelectrics have attracted increasing research interests in recent years due to both their great potential in energy storage applications and intriguing structural characteristics. However, the links between the electrical properties and structural characteristics of distorted perovskite antiferroelectrics are yet to be fully deciphered. Here, we adopt local-structure methods to elucidate the nanoscale atomic structure of AgNbO3-based antiferroelectrics and their structural evolution upon La doping. The local structural features including interatomic distance distributions and atomic displacements have been analyzed using neutron small-box pair distribution function (PDF) refinement in conjunction with large-box Reverse Monte Carlo modelling. Our results highlight the correlation of cation displacements in AgNbO 3 and its disruption by the incorporation of La, apparently in corroboration with the observed anomalous dielectric properties. Spatial ordering of cation vacancies is observed in La-doped AgNbO 3 samples, which coordinates with oxygen octahedral tilting to relieve lattice strain. These results provide renewed insights into the atomic structure and antiferroelectric phase instabilities of AgNbO 3 and relevant perovskite materials, further lending versatile opportunities for enhancing their functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Mira-Titan Universe. III. Emulation of the Halo Mass Function

We construct an emulator for the halo mass function over group and cluster mass scales for a range of cosmologies, including the effects of dynamical dark energy and massive neutrinos. The emulator is based on the recently completed Mira-Titan Universe suite of cosmological N-body simulations. The main set of simulations spans 111 cosmological models with 2.1 Gpc boxes. We extract halo catalogs in the redshift range z = [0.0, 2.0] and for masses M-200c >= 10(13)M(circle dot)/h. The emulator covers an eight-dimensional hypercube spanned by {Omega(m)h(2), Omega(b)h(2), Omega(nu)h(2), sigma(8), h, n(s), w(0), w(a)}; spatial flatness is assumed. We obtain smooth halo mass functions by fitting piecewise second-order polynomials to the halo catalogs and employ Gaussian process regression to construct the emulator while keeping track of the statistical noise in the input halo catalogs and uncertainties in the regression process. For redshifts z less than or similar to 1, the typical emulator precision is better than 2% for 10(13)-10(14)M(circle dot)/h and <10<^> M similar or equal to 101(circle dot)(54)/h. For comparison, fitting functions using the traditional universal form for the halo mass function can be biased at up to 30% at M similar or equal to 10(144)M(circle dot)/h for z = 0. Our emulator is publicly available at https://github.com/SebastianBocquet/MiraTitanHMFemulator.

cosmology: theory↗
NASA NTRS1985

Elemental technetium as a cosmic-ray clock

Several radioactive isotopes have been proposed as clocks for the study of the mean cosmic ray confinement time, T sub e. Measurements of Be-10 and Al-26 give a value for T sub e of about 10 Myr when one uses a leaky box cosmic ray propagation model. It is important to obtain additional measurements of T sub e from other radioactive isotopes in order to check whether the confinement is the same throughout the periodic table. The possible use of Tc (Z = 43) as a cosmic clock is investigated. Since all isotopes of Tc are radioactive, one might be able to group these isotopes and use the elemental abundance as a whole. The results of the calculations are somewhat inconclusive for two reasons. First, the beta + decay half lives of two of the Tc isotopes relevant to our calculation are not known. Second, the dependence of the Tc abundance on the mean confinement time is rather weak when one considers the number of events expected in 4 trays of plastic track detectors. However, a future, finite measurement of the Beta + half lives and the possible use of the entire collecting area of the HNC to detect Tc nuclei could make the use of Tc as a cosmic ray clock more attractive.

Drach, J.↗
NASA NTRS1993

Squeezed states of electrons and transitions of the density of states

Electron systems which have low dimensional properties have been constructed by squeezing the motion in zero, one, or two-directions. An isolated quantum dot is modeled by a potential box with delta-profiled, penetrable potential walls embedded in a large outer box with infinitely high potential walls which represent the world function with respect to vacuum. We show the smooth crossover of the density of states from the three-dimensional to the quasi-zero dimensional electron gas.

Lee, Seung Joo↗
NASA NTRS1995

Modeling the decay of energy containing eddies: A source of solar wind heating

To understand the solar wind heating and acceleration mechanisms one needs to understand the decay of energy containing eddies. With this goal in mind, attempts have been made to extend the fluid dynamic phenomenology of large scale quasi-equilibrium to the case of magnetohydrodynamics. Matthaeus et al. have proposed a model for the inhomogeneous transport and decay of five mean variables, namely, two mean square Elsasser variables z(exp 2) (sub +/-) their correlation lengths, and the difference between the kinetic and magnetic energies. We test the validity of this model in the simplified case of homogeneous turbulence simulated in a periodic box. We propose a class of models and show that they may fit the simulation satisfactorily. Analytic solutions of this class of model reveal their inherent properties and demonstrate the difficulties associated with finite cross helicity. It is noted that adjustments are required to make the simplest models, which are based upon isotropic turbulence, scale properly with respect to the strength of the mean magnetic field. This can be interpreted as due to anisotropic turbulence, which can be modelled by simple parameterization in the phenomenology.

Hossain, M.↗
NASA NTRS2001

Impact of Albedo Contrast Between Cirrus and Boundary-Layer Clouds on Climate Sensitivity

In assessing the iris effect suggested by Lindzen et al. (2001), Fu et al. (2001) found that the response of high-level clouds to the sea surface temperature had an effect of reducing the climate sensitivity to external radiative forcing, but the effect was not as strong as LCH found. This weaker reduction in climate sensitivity was due to the smaller contrasts in albedos and effective emitting temperatures between cirrus clouds and the neighboring regions. FBH specified the albedos and the outgoing longwave radiation (OLR) in the LCH 3.5-box radiative-convective model by requiring that the model radiation budgets at the top of the atmosphere be consistent with that inferred from the Earth Radiation Budget Experiment (ERBE). In point of fact, the constraint by radiation budgets alone is not sufficient for deriving the correct contrast in radiation properties between cirrus clouds and the neighboring regions, and the approach of FBH to specifying those properties is, we feel inappropriate for assessing the iris effect.

Chou, Ming-Dah↗
DOE OSTI2025

High-Fidelity Modeling of a Type-5 Wind Turbine Gearbox

Type-5 wind turbines are characterized by their use of a hydraulic torque converter and permanent synchronous generator. This combination promotes steady and grid-ready energy without the use of a power converter. Thus, researchers were prompted to study the potential impact on grid reliability, stability, and resilience using a Real Time Digital Simulator (RTDS) model of the type-5 turbine, including a high-fidelity model of its gear box.

13 - HYDRO ENERGY↗
DOE OSTI2023

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Constructing an Educational Mars Simulation

Working in the Educational Programs Office, my task this summer is to model a 3D habitat that will be part of a future Mars base. With the President's charge to further explore mars by way of robotic-led and human-led missions, there has been a surge in the activity regarding the "red planet". Since all present designs are merely conjecture, I have some creative freedom in deciding what the habitat will look like. To get ideas for what a Mars habitat might be like, I looked at several references including websites and NASA documents. One of these was a NASA Technical Memorandum about Space Transportation Systems that I looked at to get insight on spaceship design. Information about the planet's environment, such as the gravity and the weather, is useful as well when designing the structure. The main software that I am using is Lightwave 3D and Modeler 7.5 that comes along with it. Lightwave is very complex in that it lets you model, surface, and animate so there was a lot to learn. To learn the software I watched a series of instructional videos, looked at online tutorials, and referenced several books. Modeling is like shaping clay with a computer. Every item modeled is made of smaller shapes called polygons. For example, each side of a box would be a different polygon. Modelers must be careful to design with users' systems in mind. Having a model made with too many polygons can slow down a walk-through, but it usually improves the small details on a model. Getting speed and quality proved tricky. An important thing for me to remember when modeling the habitat was to save space. Also, I must consider that technology in the future will be much different than now, so I must be especially creative. My project will be used in an educational walkthough simulation in which users can interact with the environment. I worked closely with intern Stephen Henke who built a Mars Rover, terrain and programmed code for the simulation. This summer's project will help me with future aspirations in computer graphics. Modeling is a valuable skill that I appreciate having the chance to learn and practice.

Henke, Stephen A.↗
DOE OSTI2023

Modelling CN Zeeman effect observations of the envelopes of a low-mass protostellar disc and a massive protostar

We use the POLARIS radiative transfer code to produce simulated circular polarization Zeeman emission maps of the cyanide (CN) J = 1–0 molecular line transition for two types of protostellar envelope magnetohydrodynamic simulations. Our first model is a low-mass disc envelope system (box length L = 200 au), and our second model is the envelope of a massive protostar (L = 104 au) with a protostellar wind and a CN-enhanced outflow shell. We compute the velocity-integrated Stokes I and V, as well as the implied V/I polarization percentage, for each detector pixel location in our simulated emission maps. Our results show that both types of protostellar environments are in principle accessible with current circular polarization instruments, with each containing swaths of envelope area that yield percentage polarizations that exceed the 1.8 percent nominal sensitivity limit for circular polarization experiments with the Atacama Large Millimeter/submillimeter Array. In both systems, high-polarization (≳1.8 percent) pixels tend to lie at an intermediate distance away from the central star and where the line-centre opacity of the CN emission is moderately optically thin (τLC ~ 0.1–1). Furthermore, our computed V/I values scale roughly with the density-weighted mean line-of-sight magnetic field strength, indicating that Zeeman observations can effectively diagnose the strength of envelope-scale magnetic fields. We also find that pixels with large V/I are preferentially co-located where the absolute value of the velocity-integrated V is also large, suggesting that locations with favourable percentage polarization are also favourable in terms of raw signal.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

Frequencies and Flutter Speed Estimation for Damaged Aircraft Wing Using Scaled Equivalent Plate Analysis

Equivalent plate analysis is often used to replace the computationally expensive finite element analysis in initial design stages or in conceptual design of aircraft wing structures. The equivalent plate model can also be used to design a wind tunnel model to match the stiffness characteristics of the wing box of a full-scale aircraft wing model while satisfying strength-based requirements An equivalent plate analysis technique is presented to predict the static and dynamic response of an aircraft wing with or without damage. First, a geometric scale factor and a dynamic pressure scale factor are defined to relate the stiffness, load and deformation of the equivalent plate to the aircraft wing. A procedure using an optimization technique is presented to create scaled equivalent plate models from the full scale aircraft wing using geometric and dynamic pressure scale factors. The scaled models are constructed by matching the stiffness of the scaled equivalent plate with the scaled aircraft wing stiffness. It is demonstrated that the scaled equivalent plate model can be used to predict the deformation of the aircraft wing accurately. Once the full equivalent plate geometry is obtained, any other scaled equivalent plate geometry can be obtained using the geometric scale factor. Next, an average frequency scale factor is defined as the average ratio of the frequencies of the aircraft wing to the frequencies of the full-scaled equivalent plate. The average frequency scale factor combined with the geometric scale factor is used to predict the frequency response of the aircraft wing from the scaled equivalent plate analysis. A procedure is outlined to estimate the frequency response and the flutter speed of an aircraft wing from the equivalent plate analysis using the frequency scale factor and geometric scale factor. The equivalent plate analysis is demonstrated using an aircraft wing without damage and another with damage. Both of the problems show that the scaled equivalent plate analysis can be successfully used to predict the frequencies and flutter speed of a typical aircraft wing.

Krishnamurthy, Thiagarajan↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
NASA NTRS2011

Broken Ergodicity in MHD Turbulence in a Spherical Domain

Broken ergodicity (BE) occurs in Fourier method numerical simulations of ideal, homogeneous, incompressible magnetohydrodynamic (MHD) turbulence. Although naive statistical theory predicts that Fourier coefficients of fluid velocity and magnetic field are zero-mean random variables, numerical simulations clearly show that low-wave-number coefficients have non-zero mean values that can be very large compared to the associated standard deviation. In other words, large-scale coherent structure (i.e., broken ergodicity) in homogeneous MHD turbulence can spontaneously grow out of random initial conditions. Eigenanalysis of the modal covariance matrices in the probability density functions of ideal statistical theory leads to a theoretical explanation of observed BE in homogeneous MHD turbulence. Since dissipation is minimal at the largest scales, BE is also relevant for resistive magnetofluids, as evidenced in numerical simulations. Here, we move beyond model magnetofluids confined by periodic boxes to examine BE in rotating magnetofluids in spherical domains using spherical harmonic expansions along with suitable boundary conditions. We present theoretical results for 3-D and 2-D spherical models and also present computational results from dynamical simulations of 2-D MHD turbulence on a rotating spherical surface. MHD turbulence on a 2-D sphere is affected by Coriolus forces, while MHD turbulence on a 2-D plane is not, so that 2-D spherical models are a useful (and simpler) intermediate stage on the path to understanding the much more complex 3-D spherical case.

Shebalin, John V.↗
NASA NTRS1985

Box truss analysis and technology development. Task 1: Mesh analysis and control

An analytical tool was developed to model, analyze and predict RF performance of box truss antennas with reflective mesh surfaces. The analysis system is unique in that it integrates custom written programs for cord tied mesh surfaces, thereby drastically reducing the cost of analysis. The analysis system is capable of determining the RF performance of antennas under any type of manufacturing or operating environment by integrating together the various disciplines of design, finite element analysis, surface best fit analysis and RF analysis. The Integrated Mesh Analysis System consists of six separate programs: The Mesh Tie System Model Generator, The Loadcase Generator, The Model Optimizer, The Model Solver, The Surface Topography Solver and The RF Performance Solver. Additionally, a study using the mesh analysis system was performed to determine the effect of on orbit calibration, i.e., surface adjustment, on a typical box truss antenna.

Bachtell, E. E.↗
NASA NTRS1982

Application of a systematic finite-element model modification technique to dynamic analysis of structures

A systematic finite-element model modification technique has been applied to two small problems and a model of the main wing box of a research drone aircraft. The procedure determines the sensitivity of the eigenvalues and eigenvector components to specific structural changes, calculates the required changes and modifies the finite-element model. Good results were obtained where large stiffness modifications were required to satisfy large eigenvalue changes. Sensitivity matrix conditioning problems required the development of techniques to insure existence of a solution and accelerate its convergence. A method is proposed to assist the analyst in selecting stiffness parameters for modification.

Robinson, J. C.↗