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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 919 records · Page 51

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

97 MATHEMATICS AND COMPUTING↗

Design Optimization for a Maglev System Employing Flux Eliminating Coils

Flux eliminating coils have received no little attention over the past thirty years as an alternative for realizing lift in a MAGLEV system. When the magnets on board the vehicle are displaced from the equilibrium or null flux point of these coils, they induce current in those coils which act to restore the coil to its null flux or centerline position. The question being addressed in this paper is that of how to choose the best coil for a given system. What appears at first glance to be an innocent question is in fact one that is actually quite involved, encompassing both the global economics and physics of the system. The real key in analyzing that question is to derive an optimization index or functional which represents the cost of the system subject to constraints, the primary constraint being that the vehicle lift itself at a certain threshold speed. Outlined in this paper is one scenario for realizing a total system design which uses sequential quadratic programming techniques.

Davey, Kent R.↗

Coordinated Optimization and Control of Residential Solid State Power Substations in Electrical Distribution Network

This paper proposes a computationally efficient mixed integer linear programming (MILP) model for the coordinated optimization of solid-state power substations (SSPSs) in a feeder considering the full unbalanced three-phase structure of the distribution grid and its characteristics. The proposed model determines the optimal real and reactive power of each SSPS at the point of common coupling (PCC) that minimizes the operating cost and maximizes the system performance, e.g., voltage regulation and phase balancing. To improve the computational efficiency, an inscribed octagon is introduced to approximate the quadratic capacity constraints of components. Numerical simulation results show the effectiveness of the proposed model and significant improvements in voltage profiles and power imbalance between phases.

Liu, Guodong↗

SU-G-TeP3-13: The Role of Nanoscale Energy Deposition in the Development of Gold Nanoparticle-Enhanced Radiotherapy

Purpose: Gold nanoparticles (GNPs) can enhance radiotherapy effects. The high photoelectric cross section of gold relative to tissue, particularly at lower energies, leads to localized dose enhancement. However in a clinical context, photon energies must also be sufficient to reach a target volume at a given depth. These properties must be balanced to optimize such a therapy. Given that nanoscale energy deposition patterns around GNPs play a role in determining biological outcomes, in this work we seek to establish their role in this optimization process. Methods: The PENELOPE Monte Carlo code was used to generate spherical dose deposition kernels in 1000 nm diameter spheres around 50 nm diameter GNPs in response to monoenergetic photons incident on the GNP. Induced “lesions” were estimated by either a local effect model (LEM) or a mean dose model (MDM). The ratio of these estimates was examined for a range of photon energies (10 keV to 2 MeV), for three sets of linear-quadratic parameters. Results: The models produce distinct differences in expected lesion values, the lower the alpha-beta ratio, the greater the difference. The ratio of expected lesion values remained constant within 5% for energies of 40 keV and above across all parameter sets and rose to a difference of 35% for lower energies only for the lowest alpha-beta ratio. Conclusion: Consistent with other work, these calculations suggest nanoscale energy deposition patterns matter in predicting biological response to GNP-enhanced radiotherapy. However the ratio of expected lesions between the different models is largely independent of energy, indicating that GNP-enhanced radiotherapy scenarios can be optimized in photon energy without consideration of the nanoscale patterns. Special attention may be warranted for energies of 20 keV or below and low alpha-beta ratios.

60 APPLIED LIFE SCIENCES↗

LOGAN: High-Performance X-Drop Pairwise Alignment on GPU (LOGAN) v1.0

Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the run time for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational expense of analyzing these long read lengths (1Kb-1Mb). Given the quadratic overhead of exact pairwise algorithms such as Smith-Waterman, for long alignments, the community primarily relies on approximate algorithms that search only for high-quality alignments and stop early when one is not found. In this work, we present the first GPU optimization of the popular X-drop alignment algorithm, named LOGAN. Results show that our high-performance multi-GPU LOGAN implementation achieves up to 181.6 GCUPS and speed-ups up to 6.6x and 30.7x using 1 and 6 NVIDIA Tesla V100, respectively, over the state-of-the-art software running on two IBM Power9 processors using 168 threads, with equivalent accuracy. We also demonstrate a 2.3x LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for sequence alignment implemented in minimap2. To highlight the impact of our work on a real-world application, we couple the LOGAN aligner with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10.6x. Finally, we adapt the Roofline model for our optimized kernel and demonstrate that our implementation is near-optimal on the NVIDIA Tesla V100s.

Guidi, Giulia↗

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimal control of spin-stabilized spacecraft with telescoping appendages

The control of a spin-stabilized spacecraft consisting of a rigid central hub and one or two movable offset telescoping booms (with end masses) is considered. The equations of rotational motion are linearized about either of two desired final states. A control law for the boom end mass position is sought such that a quadratic cost functional involving the weighted components of angular velocity plus the control is minimized when the final time is unspecified and involves the solution of the matrix Riccati algebraic equation. For three axis control more than one offset boom (orthogonal to each other) is required. For two-axis control with a single boom offset from a symmetrical hub, an analytic solution is obtained; when this system is used for nutation decay the time constant is one order of magnitude smaller than previously achieved using nonoptimal control logic. For the general case results are obtained numerically.

Bainum, P. M.↗

Vibration control of large linear quadratic symmetric systems

Some unique properties on a class of the second order lambda matrices were found and applied to determine a damping matrix of the decoupled subsystem in such a way that the damped system would have preassigned eigenvalues without disturbing the stiffness matrix. The resulting system was realized as a time invariant velocity only feedback control system with desired poles. Another approach using optimal control theory was also applied to the decoupled system in such a way that the mode spillover problem could be eliminated. The procedures were tested successfully by numerical examples.

Jeon, G. J.↗

Experimental and statistical study on the effect of process parameters on the quality of continuous fiber composites made via additive manufacturing

Ongoing research in additive manufacturing towards structural and industrial application has led to the use of commingled roving as a manufacturing feedstock for printing high fiber volume fraction composites. The prospects of using this technology for high performance applications necessitates the need for a comprehensive experimental investigation into the effects of processing parameters on the quality of an additively manufactured composite printed from commingled roving feedstock. Here, in this work, transverse flexure and void fraction matrix pyrolysis testing are both performed to evaluate composite quality. The transverse flexure test is a testing approach that evaluates the quality of the interfacial fiber-matrix bond while the void fraction test estimates the void content in the printed composite. A full observational study consisting of 27 different test combinations is done to investigate the effects of three different process parameters namely, temperature, pressure, and print speed across three different levels. Composite samples were made from commingled roving of E-glass and amorphous PET using an in-house built continuous fiber composite digital manufacturing system. Least squares regression analysis is performed to study the main, interaction and quadratic effects of process parameters. A statistical regression model having an R2 adjusted value of 80.1% is generated from the transverse flexure study, which is used to explain main and interaction effects and also predict performance. Response surface plots are also generated and are used to optimize process parameters which can subsequently be of help in scaling up composite manufacturing. Results show that all three process parameters are highly statistically significant at the 0.01 level of significance. Pressure * Temperature and Pressure * Printspeed are significant interaction terms. Pressure plays a weightier role when print speed is increased or temperature is decreased as it closes more voids that would ordinarily have been introduced because of drop in polymer melt viscosity. Micrographic analysis is also performed.

36 MATERIALS SCIENCE↗

Singular Vectors for Moisture-Measuring Norms

In dynamic meteorology, singular vectors (SVs) are the structures that maximize a given norm of a forecast perturbation given a tangent linear model and a quadratic constraint on the initial perturbation. That constraint is a prescription of the value of either the same or a different norm applied to the initial perturbations. In the sense that SVs maximize the forecast perturbations according to a specified measure, they may be considered as optimal perturbations. SVs are used to characterize predictability, to identify and correct possible initial errors given forecast errors, to create a set of significant perturbations for ensemble forecasting, or to determine locations for observation targeting. They are a specific application of generally defined singular vectors in mathematics.

Errico, Ronald M.↗

Slushy weightings for the optimal pilot model

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Dillow, J. D.↗

Kernel Manifolds: Nonlinear‐Augmentation Dimensionality Reduction Using Reproducing Kernel Hilbert Spaces

This paper generalizes recent advances on quadratic manifold (QM) dimensionality reduction by developing kernel methods-based nonlinear-augmentation dimensionality reduction. QMs, and more generally feature map-based nonlinear corrections, augment linear dimensionality reduction with a nonlinear correction term in the reconstruction map to overcome approximation accuracy limitations of purely linear approaches. While feature map-based approaches typically learn a least squares optimal polynomial correction term, we generalize this approach by learning an optimal nonlinear correction from a user-defined reproducing kernel Hilbert space. Our approach allows one to impose arbitrary nonlinear structure on the correction term, including polynomial structure, and includes feature map and radial basis function-based corrections as special cases. Furthermore, our method has relatively low training cost and has monotonically decreasing error as the latent space dimension increases. In conclusion, we compare our approach to proper orthogonal decomposition and several recent QM approaches on data from several example problems.

kernel methods↗

3-D Deep Penetration Neutron Imaging of Thick Absorgin and Diffusive Objects Using Transport Theory

A current area of research interest in national security is to effectively and efficiently determine the contents of the many shipping containers that enter ports in the United States. This interest comes as a result of the 9/11 Commission Act passed by Congress in 2007 that requires 100% of inbound cargo to be scanned by 2012. It appears that this requirement will be achieved by 2012, but as of February of 2009 eighty percent of the 11.5 million inbound cargo containers were being scanned. The systems used today in all major U.S. ports to determine the presence of radioactive material within cargo containers are Radiation Portal Monitors (RPM). These devices generally exist in the form of a gate or series of gates that the containers can be driven through and scanned. The monitors are effective for determining the presence of radiation, but offer little more information about the particular source. This simple pass-fail system leads to many false alarms as many everyday items emit radiation including smoke detectors due to the Americium-241 source contained inside, bananas, milk, cocoa powder and lean beef due to the trace amounts of Potassium-40, and fire brick and kitty litter due to their high clay content which often contains traces of uranium and thorium. In addition, if an illuminating source is imposed on the boundary of the container, the contents of the container may become activated. These materials include steel, aluminum and many agricultural products. Current portal monitors also have not proven to be that effective at identifying natural or highly enriched uranium (HEU). In fact, the best available Advanced Spectroscopic Portal Monitors (ASP) are only capable of identifying bare HEU 70-88% of the time and masked HEU and depleted uranium (DU) only 53 percent of the time. Therefore, a better algorithm that uses more information collected from better detectors about the specific material distribution within the container is desired. The work reported here explores the inverse problem of optical tomography applied to heterogeneous domains. The neutral particle transport equation was used as the forward model for how neutral particles stream through and interact within these heterogeneous domains. A constrained optimization technique that uses Newtons method served as the basis of the inverse problem. Optical tomography aims at reconstructing the material properties using (a) illuminating sources and (b) detector readings. However, accurate simulations for radiation transport require that the particle (gamma and/or neutron) energy be appropriate discretize in the multigroup approximation. This, in turns, yields optical tomography problems where the number of unknowns grows (1) about quadratically with respect to the number of energy groups, G, (notably to reconstruct the scattering matrix) and (2) linearly with respect to the number of unknown material regions. As pointed out, a promising approach could rely on algorithms to appropriately select a material type per material zone rather than G2 values. This approach, though promising, still requires further investigation: (a) when switching from cross-section values unknowns to material type indices (discrete integer unknowns), integer programming techniques are needed since derivative information is no longer available; and (b) the issue of selecting the initial material zoning remains. The work reported here proposes an approach to solve the latter item, whereby a material zoning is proposed using one-group or few-groups transport approximations. The capabilities and limitations of the presented method were explored; they are briefly summarized next and later described in fuller details in the Appendices. The major factors that influenced the ability of the optimization method to reconstruct the cross sections of these domains included the locations of the sources used to illuminate the domains, the number of separate experiments used in the reconstruction, the locations where measurements were collected, the optical thickness of the domain, the amount of signal noise and signal bias applied to the measurements and the initial guess for the cross section distribution. All of these factors were explored for problems with and without scattering. Increasing the number of source and measurement locations and experiments generally was more successful at reconstructing optically thicker domains while producing less error in the image. The maximum optical thickness that could be reconstructed with this method was ten mean free paths for pure absorber and two mean free paths for scattering problems. Applying signal noise and signal bias to the measured fluxes produced more error in the produced image. Generally, Newtons method was more successful at reconstructing domains from an initial guess for the cross sections that was greater in magnitude than their true values than from an initial guess that was lower in magnitude.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Minimum-variance fixed-form compensation of linear systems

The problem of determining the linear time-invariant compensator of a specified dimension which minimizes the asymptotic expected value of a quadratic form in the state variables of a linear stochastic system of arbitrary order, is considered. It is shown that under appropriate assumptions, the solution of this problem can be interpreted as a minimum-order observer-based or dual observer-based compensator for an optimally aggregated model of the plant.

Johnson, T. L.↗

Disjunctive linear separation conditions and mixed-integer formulations for aircraft conflict resolution

In this paper, we address the aircraft conflict resolution problem in air traffic control. We introduce new mixed-integer programming formulations for aircraft conflict resolution with speed, heading and altitude control which are based on disjunctive linear separation conditions. We first examine the two-dimensional aircraft conflict resolution problem with speed and heading control represented as continuous decision variables. We show that the proposed disjunctive linear separation conditions are equivalent to the classical nonlinear conditions for aircraft separation. Further, we characterise conflict-free trajectories based on aircraft velocity bounds and propose a simple pre-processing algorithm to identify aircraft pairs which are either always conflict-free, or which cannot be separated using speed and heading control only. We then incorporate altitude control and propose a lexicographic optimisation formulation that aims to minimise the number of flight level changes before resolving outstanding conflicts via two-dimensional velocity control. The proposed mixed-integer programming formulations are nonconvex, and we propose convex relaxations, decomposition methods and constraint generation algorithms to solve the two-dimensional and lexicographic optimisation formulations to guaranteed optimality. Numerical experiments on four types of conflict resolution benchmarking instances are conducted to test the performance of the proposed mixed-integer formulations. Further, the proposed method is compared against two benchmarks based on state-of-the-art approaches for the aircraft conflict resolution problem. Our numerical results show that the proposed method largely outperforms both benchmarks in terms of runtime and is able to solve significantly more instances to global optimality.

97 MATHEMATICS AND COMPUTING↗

Preparation and characterization of Pb(Lu1/2Nb1/2)O3-Pb(Ni1/3Nb2/3)O3-PbTiO3 ternary ferroelectric ceramics with high piezoelectric constant

Highlights: • PLN-PNN-PT ternary ferroelectric systems were prepared by two-step method. • PLN-PNN-PT ceramics exhibit typical relaxor behavior. • 0.17PLN-0.47PNN-0.36PT ceramic has optimal properties (T{sub C} ∼ 142 °C, d{sub 33} ∼ 378 pC/N). - Abstract: Pb(Lu{sub 1/2}Nb{sub 1/2})O{sub 3}-Pb(Ni{sub 1/3}Nb{sub 2/3})O{sub 3}-PbTiO{sub 3} ferroelectric ceramics were successfully prepared by a modified two-step columbite precursor method. The structural, dielectric, ferroelectric and piezoelectric properties were characterized by X-ray diffraction, ferroelectric and dielectric measurements. All the obtained samples have pure perovskite structure. The composition of 0.17PLN-0.47PNN-0.36PT within morphotropic phase boundary exhibits optimal properties with piezoelectric coefficient d{sub 33} = 378 pC/N, Curie temperature Tc = 142 °C, dielectric constant ε΄ = 4700, dielectric loss tangent tanδ = 0.05, remnant polarization Pr = 27.1 μC/cm{sup 2} and coercive field Ec = 8.89 KV/cm. According to Curie-Weiss Law and Lorentz-type quadratic relationship, the dielectric behavior was studied and the relaxor factor γ is between 1.55–1.87, indicating the character of diffuse phase transition of the Pb(Lu{sub 1/2}Nb{sub 1/2})O{sub 3}-Pb(Ni{sub 1/3}Nb{sub 2/3})O{sub 3}-PbTiO{sub 3} ceramics. The excellent piezoelectric properties and high Curie temperature make this system a promising material for high-power transducer applications in a broad temperature range.

36 MATERIALS SCIENCE↗

Evaluating the impact of peat soils and snow schemes on simulated active layer thickness at pan-Arctic permafrost sites

Abstract Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO 2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model’s sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.

54 ENVIRONMENTAL SCIENCES↗

Digital program for solving the linear stochastic optimal control and estimation problem

A computer program is described which solves the linear stochastic optimal control and estimation (LSOCE) problem by using a time-domain formulation. The LSOCE problem is defined as that of designing controls for a linear time-invariant system which is disturbed by white noise in such a way as to minimize a performance index which is quadratic in state and control variables. The LSOCE problem and solution are outlined; brief descriptions are given of the solution algorithms, and complete descriptions of each subroutine, including usage information and digital listings, are provided. A test case is included, as well as information on the IBM 7090-7094 DCS time and storage requirements.

Geyser, L. C.↗