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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Red, Straight, no bends: primordial power spectrum reconstruction from CMB and large-scale structure

We present a minimally parametric, model independent reconstruction of the shape of the primordial power spectrum. Our smoothing spline technique is well-suited to search for smooth features such as deviations from scale invariance, and deviations from a power law such as running of the spectral index or small-scale power suppression. We use a comprehensive set of the state-of the art cosmological data: Planck observations of the temperature and polarisation anisotropies of the cosmic microwave background, WiggleZ and Sloan Digital Sky Survey Data Release 7 galaxy power spectra and the Canada-France-Hawaii Lensing Survey correlation function. This reconstruction strongly supports the evidence for a power law primordial power spectrum with a red tilt and disfavours deviations from a power law power spectrum including small-scale power suppression such as that induced by significantly massive neutrinos. This offers a powerful confirmation of the inflationary paradigm, justifying the adoption of the inflationary prior in cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1970

Simple data-smoothing and noise-suppression technique

Algorithm, based on the Borel method of summing divergent sequences, is used for smoothing noisy data where knowledge of frequency content is not required. Technique's effectiveness is demonstrated by a series of graphs.

Duty, R. L.↗
DOE OSTI2015

Smoothed dissipative particle dynamics with angular momentum conservation

Smoothed dissipative particle dynamics (SDPD) combines two popular mesoscopic techniques, the smoothed particle hydrodynamics and dissipative particle dynamics (DPD) methods, and can be considered as an improved dissipative particle dynamics approach. Despite several advantages of the SDPD method over the conventional DPD model, the original formulation of SDPD by Español and Revenga (2003) [9], lacks angular momentum conservation, leading to unphysical results for problems where the conservation of angular momentum is essential. To overcome this limitation, we extend the SDPD method by introducing a particle spin variable such that local and global angular momentum conservation is restored. The new SDPD formulation (SDPD+a) is directly derived from the Navier–Stokes equation for fluids with spin, while thermal fluctuations are incorporated similarly to the DPD method. We test the new SDPD method and demonstrate that it properly reproduces fluid transport coefficients. Also, SDPD with angular momentum conservation is validated using two problems: (i) the Taylor–Couette flow with two immiscible fluids and (ii) a tank-treading vesicle in shear flow with a viscosity contrast between inner and outer fluids. For both problems, the new SDPD method leads to simulation predictions in agreement with the corresponding analytical theories, while the original SDPD method fails to capture properly physical characteristics of the systems due to violation of angular momentum conservation. In conclusion, the extended SDPD method with angular momentum conservation provides a new approach to tackle fluid problems such as multiphase flows and vesicle/cell suspensions, where the conservation of angular momentum is essential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

On the parameter combinations that matter and on those that do not: data-driven studies of parameter (non)identifiability

Abstract We present a data-driven approach to characterizing nonidentifiability of a model’s parameters and illustrate it through dynamic as well as steady kinetic models. By employing Diffusion Maps and their extensions, we discover the minimal combinations of parameters required to characterize the output behavior of a chemical system: a set of effective parameters for the model. Furthermore, we introduce and use a Conformal Autoencoder Neural Network technique, as well as a kernel-based Jointly Smooth Function technique, to disentangle the redundant parameter combinations that do not affect the output behavior from the ones that do. We discuss the interpretability of our data-driven effective parameters, and demonstrate the utility of the approach both for behavior prediction and parameter estimation. In the latter task, it becomes important to describe level sets in parameter space that are consistent with a particular output behavior. We validate our approach on a model of multisite phosphorylation, where a reduced set of effective parameters (nonlinear combinations of the physical ones) has previously been established analytically.

Evangelou, Nikolaos↗
NASA NTRS1983

Computer programs for smoothing and scaling airfoil coordinates

Detailed descriptions are given of the theoretical methods and associated computer codes of a program to smooth and a program to scale arbitrary airfoil coordinates. The smoothing program utilizes both least-squares polynomial and least-squares cubic spline techniques to smooth interatively the second derivatives of the y-axis airfoil coordinates with respect to a transformed x-axis system which unwraps the airfoil and stretches the nose and trailing-edge regions. The corresponding smooth airfoil coordinates are then determined by solving a tridiagonal matrix of simultaneous cubic-spline equations relating the y-axis coordinates and their corresponding second derivatives. A technique for computing the camber and thickness distribution of the smoothed airfoil is also discussed. The scaling program can then be used to scale the thickness distribution generated by the smoothing program to a specific maximum thickness which is then combined with the camber distribution to obtain the final scaled airfoil contour. Computer listings of the smoothing and scaling programs are included.

Morgan, H. L., Jr.↗
DOE OSTI2015

Is there a clinical benefit with a smooth compensator design compared with a plunged compensator design for passive scattered protons?

In proton therapy, passive scattered proton plans use compensators to conform the dose to the distal surface of the planning volume. These devices are custom made from acrylic or wax for each treatment field using either a plunge-drilled or smooth-milled compensator design. The purpose of this study was to investigate if there is a clinical benefit of generating passive scattered proton radiation treatment plans with the smooth compensator design. We generated 4 plans with different techniques using the smooth compensators. We chose 5 sites and 5 patients for each site for the range of dosimetric effects to show adequate sample. The plans were compared and evaluated using multicriteria (MCA) plan quality metrics for plan assessment and comparison using the Quality Reports [EMR] technology by Canis Lupus LLC. The average absolute difference for dosimetric metrics from the plunged-depth plan ranged from −4.7 to +3.0 and the average absolute performance results ranged from −6.6% to +3%. The manually edited smooth compensator plan yielded the best dosimetric metric, +3.0, and performance, + 3.0% compared to the plunged-depth plan. It was also superior to the other smooth compensator plans. Our results indicate that there are multiple approaches to achieve plans with smooth compensators similar to the plunged-depth plans. The smooth compensators with manual compensator edits yielded equal or better target coverage and normal tissue (NT) doses compared with the other smooth compensator techniques. Further studies are under investigation to evaluate the robustness of the smooth compensator design.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1986

Kalman filtering, smoothing and recursive robot arm forward and inverse dynamics

The inverse and forward dynamics problems for multi-link serial manipulators are solved by using recursive techniques from linear filtering and smoothing theory. The pivotal step is to cast the system dynamics and kinematics as a two-point boundary-value problem. Solution of this problem leads to filtering and smoothing techniques identical to the equations of Kalman filtering and Bryson-Frazier fixed time-interval smoothing. The solutions prescribe an inward filtering recursion to compute a sequence of constraint moments and forces followed by an outward recursion to determine a corresponding sequence of angular and linear accelerations. In addition to providing techniques to compute joint accelerations from applied joint moments (and vice versa), the report provides an approach to evaluate recursively the composite multi-link system inertia matrix and its inverse. The report lays the foundation for the potential use of filtering and smoothing techniques in robot inverse and forward dynamics and in robot control design.

Rodriguez, G.↗
NASA NTRS1986

Airfoil Smoothing and Scaling Programs

Two programs smooth and scale arbitrary airfoil coordinates. Airfoil smoothing program (AFSMO) utilizes both least-squares polynomial and leastsquares cubic-spline techniques to smooth iteratively second derivatives of y-axis airfoil coordinates with respect to transformed x-axis system that unwraps airfoil and stretches nose and trailing-edge regions.

Morgan, Harry L., Jr.↗
NASA NTRS1985

A comparison of smooth specimen and analytical simulation techniques for notched members at elevated temperatures

Experimental strain measurements have been made at the highly strained regions on notched plate specimens that were made of Hastelloy X. Tests were performed at temperatures up to 1,600 F. Variable load patterns were chosen so as to produce plastic and creep strains. Were appropriate, notch root stresses were experimentally estimated by subjecting a smooth specimen to the measured notch root strains. The results of three analysis techniques are presented and compared to the experimental data. The most accurate results were obtained from an analysis procedure that used a smooth specimen and the Neuber relation to simulate the notch root stress-strain response. When a generalized constitutive relation was used with the Neuber relation, good results were also obtained, however, these results were not as accurate as those obtained when the smooth specimen was used directly. Finally, a general finite element program, ANYSIS, was used which resulted in acceptable solutions, but, these were the least accurate predictions.

Martin, J. F.↗
DOE OSTI2016

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particle swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.

42 ENGINEERING↗
NASA NTRS1972

Discrete square root smoothing.

The basic techniques applied in the square root least squares and square root filtering solutions are applied to the smoothing problem. Both conventional and square root solutions are obtained by computing the filtered solutions, then modifying the results to include the effect of all measurements. A comparison of computation requirements indicates that the square root information smoother (SRIS) is more efficient than conventional solutions in a large class of fixed interval smoothing problems.

Kaminski, P. G.↗
NASA NTRS1987

Recursive Robot-Arm Dynamics via Filtering and Smoothing

Forward and inverse dynamics solved using Kalman filtering and Bryson-Frazier smoothing. Dynamics of serial-link robot arm solved by using recursive techniques from linear filtering and smoothing theory. Solutions of dynamical equations give forces, moments, and accelerations at joints between links, and multilink inertia matrix and its inverse. Theoretical developments lay foundation for use of filtering and smoothing techniques in design of robot controls.

Rodriguez, Guillermo↗
NASA NTRS1981

Procedures for analysis of spatial relationships among ship survey data and sea surface temperature

The establishment of a limited spatial data base for the U.S. eastern seaboard vicinity is discussed along with the demonstration of computer assisted analysis techniques for investigating spatial patterns and relationships among ship survey data and remotely sensed sea surface temperature. Ship survey variables included concentrations of two zooplankton, two icthyoplankton, and two fish species, in addition to physical data of depth to bottom and surface and bottom water temperatures. Continuous spatial distributions of these data were created by both weighted nearest neighbor and iterative smoothing interpolation techniques. Maps of surface water temperature were created by digitizing GOES satellite images. All mapped data were spatially registered by conversion of latitude and longitude coordinates to rotated Lambert conic conformal rectilinear coordinates and stored in grid format of approximately one hundred square kilometers per cell. The analysis of these data include the generation of statistical summaries and maps describing the joint occurrence among variables.

Berry, J. K.↗
NASA NTRS1983

An experimental study of changes in the structure of a turbulent boundary layer due to surface geometry changes

This investigation attempts to observe changes in the flow structure of a nominally zero pressure gradient turbulent boundary layer by altering the surface of a smooth plate with small triangular riblets oriented in the direction of flow and protruding just above the viscous sublayer. Hot-wire measurements show a reduction in the local skin friction over the riblet valleys by about 40% compared to the smooth surface near the end of the plate. Local skin friction increases by about 10% over the riblet peaks. Results showing the effects of the riblets on the mean, root-mean-square and skewness factor distributions of the streamwise velocity are presented. The mean profile displays characteristics similar to those of drag reducing additives; the streamwise turbulence intensity is reduced by approximately 10-15% near the surface by the riblets; the skewness factor distribution is virtually unchanged. A comparison of results from an application of the VITA 'burst' detection technique to smooth and riblet surface data is also presented although the results are rather inconclusive. Flow visualization of 'bursting' over both surfaces, while dramatically revealing the structure, reveals little difference resulting from the presence of the riblet.

Source record↗
DOE OSTI2014

Spectrally tailored supercontinuum generation from single-mode-fiber amplifiers

Spectral filtering of an all-normal-dispersion Yb-doped fiber laser was demonstrated effective for broadband supercontinuum generation in the picosecond time region. The picosecond pump pulses were tailored in spectrum with 1 nm band-pass filter installed between two single-mode fiber amplifiers. By tuning the spectral filter around 1028 nm, four-wave mixing was initiated in a photonic crystal fiber spliced with single-mode fiber, as manifested by the simultaneous generation of Stokes wave at 1076 nm and anti-Stokes wave at 984 nm. Four-wave mixing took place in cascade with the influence of stimulated Raman scattering and eventually extended the output spectrum more than 900 nm of 10 dB bandwidth. This technique allows smooth octave supercontinuum generation by using simple single-mode fiber amplifiers rather than complicated multistage large-mode-area fiber amplifiers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion

Robust Subspace Recovery (RoSuRe) algorithm was recently introduced as a principled and numerically efficient algorithm that unfolds underlying Unions of Subspaces (UoS) structure, present in the data. The union of Subspaces (UoS) is capable of identifying more complex trends in data sets than simple linear models. In this work, we build on and extend RoSuRe to prospect the structure of different data modalities individually. We propose a novel multi-modal data fusion approach based on group sparsity which we refer to as Robust Group Subspace Recovery (RoGSuRe). Relying on a bi-sparsity pursuit paradigm and non-smooth optimization techniques, the introduced framework learns a new joint representation of the time series from different data modalities, respecting an underlying UoS model. We subsequently integrate the obtained structures to form a unified subspace structure. The proposed approach exploits the structural dependencies between the different modalities data to cluster the associated target objects. The resulting fusion of the unlabeled sensors’ data from experiments on audio and magnetic data has shown that our method is competitive with other state of the art subspace clustering methods. The resulting UoS structure is employed to classify newly observed data points, highlighting the abstraction capacity of the proposed method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

GradeIT (Road Grade Inference Tool)

The National Renewable Energy Laboratory (NREL) has developed the Road Grade Inference Tool, "GradeIT". This tool is a modular Python package the leverages the United States Geological Survey’s (USGS) 1/3 arc-second Digital Elevation Model (DEM), an open and free public dataset. Roadway gradient (slope) has a strong influence on vehicle energy consumption behavior and longitudinal dynamics. Therefore, any tools, models, or analyses that consider vehicle energy consumption or driving profiles is incomplete without accurate elevation and grade information. Despite the acute need for this data, it is rarely collected alongside GPS (latitude and longitude) data, and tools to post-process GPS data to append elevation and grade are difficult to come by. GradeIT satisfies this significant need in the research community. Utilization of the USGS DEM makes the underlying data available to any potential user and ensures continuous data anywhere in the continental United States. The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.

Holden, Jacob↗
DOE OSTI2016

Status of the Flooding Fragility Testing Development

This report provides an update on research addressing nuclear power plant component reliability under flooding conditions. The research includes use of the Component Flooding Evaluation Laboratory (CFEL) where individual components and component subassemblies will be tested to failure under various flooding conditions. The resulting component reliability data can then be incorporated with risk simulation strategies to provide a more thorough representation of overall plant risk. The CFEL development strategy consists of four interleaved phases. Phase 1 addresses design and application of CFEL with water rise and water spray capabilities allowing testing of passive and active components including fully electrified components. Phase 2 addresses research into wave generation techniques followed by the design and addition of the wave generation capability to CFEL. Phase 3 addresses methodology development activities including small scale component testing, development of full scale component testing protocol, and simulation techniques including Smoothed Particle Hydrodynamic (SPH) based computer codes. Phase 4 involves full scale component testing including work on full scale component testing in a surrogate CFEL testing apparatus.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗