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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 127 records · Page 7

Unified Geometric Multigrid Algorithm for Hybridized High-Order Finite Element Methods

In this paper, we consider a standard elliptic partial differential equation and propose a geometric multigrid algorithm based on Dirichlet-to-Neumann (DtN) maps for hybridized high-order finite element methods. The proposed unified approach is applicable to any locally conservative hybridized finite element method including multinumerics with different hybridized methods in different parts of the domain. For these methods, the linear system involves only the unknowns residing on the mesh skeleton, and constructing intergrid transfer operators is therefore not trivial. The key to our geometric multigrid algorithm is the physics-based energy-preserving intergrid transfer operators which depend only on the fine scale DtN maps. Thanks to these operators, we completely avoid upscaling of parameters and no information regarding subgrid physics is explicitly required on coarse meshes. Moreover, our algorithm is agglomeration-based and can straightforwardly handle unstructured meshes. We perform extensive numerical studies with hybridized mixed methods, hybridized discontinuous Galerkin methods, weak Galerkin methods, and hybridized versions of interior penalty discontinuous Galerkin methods on a range of elliptic problems including subsurface flow through highly heterogeneous porous media. We compare the performance of different smoothers and analyze the effect of stabilization parameters on the scalability of the multigrid algorithm.

97 MATHEMATICS AND COMPUTING↗

Preliminary Assessment of Optimal Longitudinal-Mode Control for Drag Reduction through Distributed Aeroelastic Shaping

The emergence of advanced lightweight materials is resulting in a new generation of lighter, flexible, more-efficient airframes that are enabling concepts for active aeroelastic wing-shape control to achieve greater flight efficiency and increased safety margins. These elastically shaped aircraft concepts require non-traditional methods for large-scale multi-objective flight control that simultaneously seek to gain aerodynamic efficiency in terms of drag reduction while performing traditional command-tracking tasks as part of a complete guidance and navigation solution. This paper presents results from a preliminary study of a notional multi-objective control law for an aeroelastic flexible-wing aircraft controlled through distributed continuous leading and trailing edge control surface actuators. This preliminary study develops and analyzes a multi-objective control law derived from optimal linear quadratic methods on a longitudinal vehicle dynamics model with coupled aeroelastic dynamics. The controller tracks commanded attack-angle while minimizing drag and controlling wing twist and bend. This paper presents an overview of the elastic aircraft concept, outlines the coupled vehicle model, presents the preliminary control law formulation and implementation, presents results from simulation, provides analysis, and concludes by identifying possible future areas for research

aeroelastic↗

Calculation of free fall trajectories based on numerical optimization techniques

The development of a means of computing free-fall (nonthrusting) trajectories from one specified point in the solar system to another specified point in the solar system in a given amount of time was studied. The problem is that of solving a two-point boundary value problem for which the initial slope is unknown. Two standard methods of attack exist for solving two-point boundary value problems. The first method is known as the initial value or shooting method. The second method of attack for two-point boundary value problems is to approximate the nonlinear differential equations by an appropriate linearized set. Parts of both boundary value problem solution techniques described above are used. A complete velocity history is guessed such that the corresponding position history satisfies the given boundary conditions at the appropriate times. An iterative procedure is then followed until the last guessed velocity history and the velocity history obtained from integrating the acceleration history agree to some specified tolerance everywhere along the trajectory.

Source record↗

Component specific modeling

Modern jet engine design imposes extremely high loadings and temperatures on hot section components. A series of interdisciplinary modeling and analysis techniques which were specialized to address three specific components (combustor burner linings, hollow air-cooled turbine blades, and air-cooled turbine vanes) were developed and verified. These techniques will incorporate data as well as theoretical methods from many diverse areas, including cycle and performance analysis, heat transfer analysis, linear and nonlinear stress analysis, and mission analysis. Building on the proven techniques already available in these fields, the new methods developed will be integrated to predict temperature, deformation, stress, and strain histories throughout a complete flight mission.

Roberts, M. L.↗

Update on the NASA GRC Stirling Technology Development Project

The Department of Energy, NASA Glenn Research Center (GRC), and Stirling Technology Company (STC) are developing a free-piston Stirling convertor for a Stirling radioisotope power system (SRPS) to provide spacecraft on-board electric power for NASA deep space missions. The SRPS has recently been identified for potential use on the Europa Orbiter and Solar Probe Space Science missions. Stirling is also now being considered for unmanned Mars rovers. NASA GRC is conducting an in-house project to assist in developing the Stirling convertor for readiness for space qualification and mission implementation. As part of this continuing effort, the Stirling convertor will be further characterized under launch environment random vibration testing, methods to reduce convertor electromagnetic interference (EMI) will be developed, and an independent performance verification will be completed. Convertor life assessment and permanent magnet aging characterization tasks are also underway. Substitute organic materials for the linear alternator and piston bearing coatings for use in a high radiation environment have been identified and have now been incorporated in Stirling convertors built by STC for GRC. Electromagnetic and thermal finite element analyses for the alternator are also being conducted. This paper discusses the recent results and status for this NASA GRC in-house project.

Thieme, Lanny G.↗

High performance liquid chromatographic assay for the quantitation of total glutathione in plasma

A simple and widely used homocysteine HPLC procedure was applied for the HPLC identification and quantitation of glutathione in plasma. The method, which utilizes SBDF as a derivatizing agent utilizes only 50 microl of sample volume. Linear quantitative response curve was generated for glutathione over a concentration range of 0.3125-62.50 micromol/l. Linear regression analysis of the standard curve exhibited correlation coefficient of 0.999. Limit of detection (LOD) and limit of quantitation (LOQ) values were 5.0 and 15 pmol, respectively. Glutathione recovery using this method was nearly complete (above 96%). Intra-assay and inter-assay precision studies reflected a high level of reliability and reproducibility of the method. The applicability of the method for the quantitation of glutathione was demonstrated successfully using human and rat plasma samples.

Non-NASA Center↗

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

This annual report summarizes the work completed during the third year of technical effort on the referenced contract. Principal developments continue to focus on the Probabilistic Finite Element Method (PFEM) which has been under development for three years. Essentially all of the linear capabilities within the PFEM code are in place. Major progress in the application or verifications phase was achieved. An EXPERT module architecture was designed and partially implemented. EXPERT is a user interface module which incorporates an expert system shell for the implementation of a rule-based interface utilizing the experience and expertise of the user community. The Fast Probability Integration (FPI) Algorithm continues to demonstrate outstanding performance characteristics for the integration of probability density functions for multiple variables. Additionally, an enhanced Monte Carlo simulation algorithm was developed and demonstrated for a variety of numerical strategies.

Source record↗

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗

Guidance and Control System for a Satellite Constellation

A distributed guidance and control algorithm was developed for a constellation of satellites. The system repositions satellites as required, regulates satellites to desired orbits, and prevents collisions. 1. Optimal methods are used to compute nominal transfers from orbit to orbit. 2. Satellites are regulated to maintain the desired orbits once the transfers are complete. 3. A simulator is used to predict potential collisions or near-misses. 4. Each satellite computes perturbations to its controls so as to increase any unacceptable distances of nearest approach to other objects. a. The avoidance problem is recast in a distributed and locally-linear form to arrive at a tractable solution. b. Plant matrix values are approximated via simulation at each time step. c. The Linear Quadratic Gaussian (LQG) method is used to compute perturbations to the controls that will result in increased miss distances. 5. Once all danger is passed, the satellites return to their original orbits, all the while avoiding each other as above. 6. The delta-Vs are reasonable. The controller begins maneuvers as soon as practical to minimize delta-V. 7. Despite the inclusion of trajectory simulations within the control loop, the algorithm is sufficiently fast for available satellite computer hardware. 8. The required measurement accuracies are within the capabilities of modern inertial measurement devices and modern positioning devices.

Bryson, Jonathan Lamar↗

DUNE-PRISM – A New Method to Measure Neutrino Oscillations

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long baseline neutrino oscillation experiment designed to make precision measurements in a 1.2 2.4 MW neutrino beam, which is directed 1285 km from the Fermi National Accelerator Laboratory (Fermilab) to the Sandford Underground Research Facility (SURF) in South Dakota. Neutrinos are measured at two detector facilities: a near detector located at Fermilab close where the beam is produced and a far detector at SURF. The neutrino beam can be configured to be composed primarily of either muon or anti-muon neutrinos. DUNE measures the disappearance of muon and anti-muon neutrinos and appearance electron and anti-electron neutrinos in the neutrino beam. Measuring these neutrino flavour transitions provides DUNE with sensitivity to the neutrino mass ordering, $\delta_{CP}$, $\theta_{13}$, $\theta_{23}$ and the magnitude of $\Delta m^2_{23}$. The DUNE Precision Reaction Independent Spectrum Measurement (DUNE-PRISM) concept presents a novel way to perform a neutrino oscillation analysis, which has the potential to significantly reduce the impact of large systematic uncertainties in the neutrino interaction model. The PRISM method linearly combines measurements of off-axis neutrino interactions at the DUNE near detector to produce data-driven predictions of the oscillated neutrino event rate spectrum at the far detector. By building an oscillated far detector prediction directly from data, any unknown or poorly modelled neutrino interaction effects will be naturally incorporated into the measurement of the parameters of the neutrino oscillation model. This thesis presents the first complete neutrino oscillation analysis for DUNE using the PRISM method. Details of the methodology are fully explained and the prospects for further improvements to the techniques described are highlighted. The expected impact and relative importance of the neutrino flux, cross section and detector systematic uncertainties are described in detail. Finally, this thesis demonstrates that the PRISM method is capable of performing a measurement of the oscillation parameters that is robust against neutrino interaction modelling errors.

Hasnip, Ciaran↗

PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks

We propose a novel prediction interval (PI) method for uncertainty quantification, which addresses three major issues with the state-of-the-art PI methods. First, existing PI methods require retraining of neural networks (NNs) for every given confidence level and suffer from the crossing issue in calculating multiple PIs. Second, they usually rely on customized loss functions with extra sensitive hyperparameters for which fine tuning is required to achieve a well-calibrated PI. Third, they usually underestimate uncertainties of out-of-distribution (OOD) samples leading to over-confident PIs. Our PI3NN method calculates PIs from linear combinations of three NNs, each of which is independently trained using the standard mean squared error loss. The coefficients of the linear combinations are computed using root-finding algorithms to ensure tight PIs for a given confidence level. We theoretically prove that PI3NN can calculate PIs for a series of confidence levels without retraining NNs and it completely avoids the crossing issue. Additionally, PI3NN does not introduce any unusual hyperparameters resulting in a stable performance. Furthermore, we address OOD identification challenge by introducing an initialization scheme which provides reasonably larger PIs of the OOD samples than those of the in-distribution samples. Benchmark and real-world experiments show that our method outperforms several state-of-the-art approaches with respect to predictive uncertainty quality, robustness, and OOD samples identification.

Liu, Siyan↗

Inducing Fe moment in LaFeSi with p-block element substitution

We studied the LaFeSi phase using density functional theory based full-potential linearized augmented plane wave (FP-LAPW) method. Specifically we examined the effect of p-element substitution on the stability and magnetic properties focusing on pathways to induce Fe magnetic moments. We demonstrate that either partial or complete substitutions at the Si 2 c-site by several p-block elements lead to non-zero Fe moments. Our theoretical study shows that partially substituted LaFeSi 1-y Ga y and LaFeSi 1-y Al y are more thermodynamically stable than the fully substituted LaFeGa and LaFeAl. We also found that the P substitutions, either partial or complete, have the most negative formation energies, however the compounds containing phosphorus are non-magnetic. Our work highlights a pathway toward manipulations of the otherwise quenched Fe-moments in LaFeSi-related compounds and help in advancing the potential magnetic functionalities of LaFeX compounds.

36 MATERIALS SCIENCE↗

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

This work evaluates different optimization algorithms for computational fluid dynamics (CFD) simulations of engine combustion. Due to the computational expense of CFD simulations, emulators built with machine learning algorithms were used as surrogates for the optimizers. Two types of emulators were used: a Gaussian process (GP) and a weighted variety of machine learning methods called SuperLearner (SL). The emulators were trained using a dataset of 2048 CFD simulations that were run concurrently on a supercomputer. The design of experiments (DOE) for the CFD runs was obtained by perturbing nine input parameters using a Monte-Carlo method. The CFD simulations were of a heavy duty engine running with a low octane gasoline-like fuel at a partially premixed compression ignition mode. Ten optimization algorithms were tested, including types typically used in research applications. Each optimizer was allowed 800 function evaluations and was randomly tested 100 times. The optimizers were evaluated for the median, minimum, and maximum merits obtained in the 100 attempts. Some optimizers required more sequential evaluations, thereby resulting in longer wall clock times to reach an optimum. The best performing optimization methods were particle swarm optimization (PSO), differential evolution (DE), GENOUD (an evolutionary algorithm), and micro-genetic algorithm (GA). These methods found a high median optimum as well as a reasonable minimum optimum of the 100 trials. Moreover, all of these methods were able to operate with less than 100 successive iterations, which reduced the wall clock time required in practice. Two methods were found to be effective but required a much larger number of successive iterations: the DIRECT and MALSCHAINS algorithms. A random search method that completed in a single iteration performed poorly in finding optimum designs but was included to illustrate the limitation of highly concurrent search methods. The last three methods, Nelder–Mead, bound optimization by quadratic approximation (BOBYQA), and constrained optimization by linear approximation (COBYLA), did not perform as well.

Probst, Daniel M.↗

A probabilistic Hu-Washizu variational principle

A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.

Liu, W. K.↗

Filtering states with total spin on a quantum computer

Starting from a general wave-function described on a set of spins or qubits, we propose several quantum algorithms to extract the components of this state on eigenstates of total spin S 2 and its z component S z . The method plays the role of total spin projection and gives access to the amplitudes of the initial state on a total spin basis. Here, the different algorithms have various degrees of sophistication depending on the requested tasks. They can either solely project onto the subspace with good total spin or completely uplift the degeneracy in this subspace. In the former case, when the projection on the total spin j is made, we show that the number of operations for the projection can be reduced from a quadratic to a linear dependence in j. After each measurement, the state collapses to one of the spin eigenstates that could be used for postprocessing. For this reason, we call the method total quantum spin filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Comparison of Patient-Reported Outcomes After Breast-Conserving Surgery and Mastectomy with Implant Breast Reconstruction

Background: Many factors influence decisions regarding choice of breast-conserving surgery (BCS) versus mastectomy with reconstruction for early invasive breast cancer. The purpose of this study was to compare patient satisfaction following BCS and mastectomy with implant reconstruction (M-iR) utilizing the BREAST-Q patient-reported outcome measure. Methods: Women with stage I or II breast cancer undergoing BCS or M-iR who completed a BREAST-Q from 2010 to 2016 were identified by retrospective review of a prospective database. Baseline characteristics were compared, and linear mixed models were used to analyze associations with BREAST-Q scores over time. Results: Our study group was composed of 3233 women; 2026 (63%) had BCS, 123 (3.8%) had nipple-sparing mastectomy, and 1084 (34%) had skin-sparing or total mastectomy. Median time from surgery to BREAST-Q was 205 days for BCS and 639 days for M-iR (p < 0.001). Regardless of type of surgery, breast satisfaction scores decreased significantly over time (p < 0.001), whereas psychosocial (p = 0.001) and sexual (p = 0.004) well-being scores increased significantly over time. BCS was associated with significantly higher scores over time compared with M-iR across all subscales (all p < 0.001). Radiation was significantly associated with decreased scores over time across all subscales (all p < 0.05). Conclusions: Breast satisfaction and quality-of-life scores were higher for BCS compared with M-iR in early-stage invasive breast cancer. These findings may help in counseling women who have a choice for surgical treatment. Breast satisfaction scores decreased over time in all women, highlighting the need for further evaluation with longer follow-up.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Magnetic fields in star-forming regions - Observations

We review the observational aspects of magnetic fields in dense, star-forming regions. First we discuss ways to observe the field. These include direct methods, which consist of the measurement of both linear and circular polarization of spectral line and continuum radiation; and indirect methods, consisting of the angular distribution of H2O masers on the sky and the measurement of ambipolar diffusion. Next we discuss selected observational results, focusing on detailed discussions of a small number of points rather than a generalized discussion that covers the waterfront. We discuss the Orion/BN-KL region in detail, both on the small and large scales. Next we discuss the derivation of the complete magnetic vector, including both the systematic and fluctuating component, from a large sample of Zeeman and linear polarization measurements for the L204 dark cloud. We examine the virial theorem as it applies to dark clouds in general and one dark cloud, Barnard 1, in particular. We critically discuss the numerous claims for alignment of cloud structural features with the plane-of-the-sky component of the magnetic field, and find that many of these have not been definitively established.

Heiles, Carl↗