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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining an array of bins, each bin identified by a unique number and including histogram data for a range of y values; for each consecutive pair of data points including a current data point and a next data point, determining a corresponding one of a plurality of linear equations, each linear equation defining a line between the current data point and the next data point; for each line, determining an amount of time that the y value of the line is within the range of values for each bin from the current data point to the next data point; and adding the time to the histogram data for each bin.

Tohlen, Michael Aaron↗
DOE OSTI2024

Understanding atom probe’s analytical performance for iron oxides using correlation histograms and ab initio calculations

Abstract Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influence of the intense electrostatic field (10 10 Vm −1 ), makes them prone to dissociation with or without an exchange of energy amongst them. These processes can affect the analytical performance of atom probe tomography (APT). For instance, neutral molecules formed through dissociation may not be detected at all or with a time of flight no longer related to their mass, causing their loss from the analysis. Here, we evaluated the changes in the measured composition of FeO, Fe 2 O 3 and Fe 3 O 4 across a wide range of analysis conditions. Possible dissociation reactions are predicted by density-functional theory calculations considering the spin states of the molecules. The energetically favoured reactions are traced on to the multi-hit ion correlation histograms, to confirm their existence within experiments, using an automated Python-based routine. The detected reactions are carefully analyzed to reflect upon the influence of these neutrals from dissociation reactions on the performance of APT for analysing iron oxides.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Dose–volume histogram evaluation scheme for beam orientations in intensity-modulated radiation therapy

Beam orientations in intensity-modulated radiation therapy (IMRT) is an important, but difficult NP-hard optimization problem. A considerable part of this difficulty is due to the essential prerequisite of defining, appropriately, counter-intuitive criteria for a mathematical plan evaluation that coincides with the clinical judgment of the considered plan. Moreover, the quality of beam directions depends heavily on their intensities. Usually a stochastic selector is utilized for optimizing beam orientations, and the intensities are thus calculated many thousands of times, each time for a different selection of beam directions, resulting in excessive time complexity. Therefore, selecting an appropriate set of beam directions in IMRT is still a time-consuming manual trial-and-error search procedure that depends on intuition and empirical knowledge. To overcome these difficulties, this work utilizes the concept of dose–volume histogram (DVH), which is one of the main recognized quantitative measurement tools used for plan judgment, and presents a DVH evaluation scheme that parallelizes plan evaluation with clinical plan judgment. This scheme is then utilized to optimize the intensities of each individual beam, enabling it to be represented by its DVHs, produced for the different irradiated volumes. Finally, an evolutionary algorithm is employed to search for the best combination of those DVHs reflecting the clinical optimal. The presented methods have been applied to three real clinical examples. In comparison to the standard equally spaced beam plans, improvements were reported in all three cases. In comparison with the greedy algorithm, improvements were reported in those examples requiring more than five beam directions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Histogram-free multicanonical Monte Carlo sampling to calculate the density of states

Here, we report a new multicanonical Monte Carlo algorithm to obtain the density of states for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain a closed-form expression for the density of states expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical sampling and Wang–Landau sampling. This is enabled by storing the visited states directly and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Magnetic Resonance, Vendor-independent, Intensity Histogram Analysis Predicting Pathologic Complete Response After Radiochemotherapy of Rectal Cancer

The objective of this study is finding an intensity based histogram (IBH) signature to predict pathologic complete response (pCR) probability using only pre-treatment magnetic resonance (MR) and validate it externally in order to create a workflow for the external validation of an MR IBH signature and to apply the model out of the environment where it has been tuned. The impact of pCR and the final predictors on the survival outcome were also evaluated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Daily Rectal Dose-volume Histogram Variation in Prostate Intensity-modulated Radiation Therapy: Is It Clinically Significant in the Era of Image Guidance?

Because of the steep dose gradient associated with dose-escalated intensity-modulated radiation therapy, interfraction motion and variation in rectal volume may result in the rectum receiving a larger dose than predicted at treatment planning. This study aims to quantify the variation in daily rectal dose-volume histograms (DVHs) from the treatment plan and to discuss the potential clinical significance of this variation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorption properties of nanoporous materials and are critical for the in silico identification of promising materials for a variety of gas storage and chemical separation applications. In this work we demonstrate that a well-known biasing technique, known as “flat-histogram” sampling, can be combined with temperature extrapolation of the free energy landscape to efficiently provide significantly more useful thermodynamic information than standard open ensemble MC simulations. Namely, we can accurately compute the isosteric heat of adsorption and number of particles adsorbed for various adsorbates over an extremely wide range of temperatures and pressures from a set of simulations at just one temperature. We extend this derivation of the temperature extrapolation to adsorbates with intramolecular degrees of freedom when Rosenbluth sampling is employed. Consequently, the working capacity and isosteric heat can be computed for any given combined temperature/pressure swing adsorption process for a large range of operating conditions with both rigid and deformable adsorbates. Finally, continuous thermodynamic properties can be computed with this technique at very moderate computational cost, thereby providing a strong case for its application to the in silico identification of promising nanoporous adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Dynamic color mapping with a multi-scale histogram: A design study with physical scientists

Many research and development activities for scientific data analysis have focused on scalability challenges and data-driven features. Conversely, data visualization that focus on models requiring human interaction rarely involve practical and largescale scientific data analysis. Therefore, a gap exists between interactive data visualization and scientific data analysis applications. In this paper, we present a design study of interactive data visualization to support scientists who visually analyze data from neutron scattering experiments. This study was conducted in multiple phases: 1) problem characterization; 2) initial design and formative evaluation; and 3) iterative design. We characterize the problems and the design requirements for the analysis of the specific physical science data. We discuss the design, development, evaluation of our visual analytics tool and as well as our iterative developments with physical scientists. We show how to bridge the gap between the two disciplines uncovering new potential to solve their challenges in this design study. We focus on a specific challenge, finding an optimal color mapping, which plays a critical role in neutron scattering science and is broadly applicable to other scientific domains. To address the challenge, we propose two interactive visualization techniques: a dynamic color scale bar (DCSB) and a multi-scale histogram (MSH).

Chae, Junghoon↗
NASA NTRS1979

Multidimensional histograms

Program computes four dimensional histogram of Landsat multispectral image data. System enhances image handling and significantly reduces reprocessing costs.

Jayroe, R. R., Jr.↗
NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗
NASA NTRS2018

Utilizing Brightness Temperature Histograms for Microwave Radiometer High Frequency (150-183 Ghz) Calibration

Spaceborne microwave radiometers with high frequency channels (150-183 GHz) are important for retrieving many geophysical parameters such as snowfall, ice water path, and atmospheric water vapor profiles. In order to obtain accurate retrievals from the brightness temperature measurements, the radiometers must be properly calibrated. Several methods have been developed to analyze the on-orbit calibration, including comparisons with radiative transfer models, comparisons with radiosonde profiles, and cross-calibration with similar radiometers. This paper introduces a new method to calibrate high frequency channels that utilizes TB histograms. This new method gives an independent approach that can be used by itself to analyze radiometer calibration or in conjunction with other methods to corroborate results.

microwave radiometry↗
DOE OSTI2017

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

Li, Ying Wai↗
DOE OSTI2022

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining a plurality of bins; defining an array of elements; dividing the sampled data points into a plurality of sections; assigning a plurality of polynomial equations, one polynomial equation to each section, each polynomial equation having a waveform that fits the data points of the associated section; determining a plurality of section bin times, one section bin time for each bin in each section, each section bin time determined using the polynomial equation and indicating an amount of time that the waveform has values in the range of one of the bins; and adding the section bin time for each bin in each section to the histogram data in the array element pointed to by the number of the bin.

Tohlen, Michael Aaron↗