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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Segmentation of RDX and TNT in X‐Ray Computed Tomography Reconstructions of Melt‐Cast Explosives

ABSTRACT Three‐dimensional mesoscale characterization of heterogeneous melt‐cast high explosives is challenging because of the difficulty differentiating binder from explosive crystals: two functionally different materials which are typically similar in density by design. Here, we report an algorithm which can differentiate hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine (RDX) from 2,4,6‐trinitrotoluene (TNT) in x‐ray computed tomography (CT) volumes with tens of microns resolution. This method allows us to quantify RDX/TNT content, porosity, and RDX domain size. We calibrated the segmentation algorithm using simulated x‐ray CT volumes containing object models of RDX crystals within a TNT matrix. We then segmented and analyzed CT data for Composition B (Comp B), a 60/40 RDX/TNT mixture, and Cyclotol, a 75/25 RDX/TNT mixture. We examined melt‐cast samples fabricated with 100% theoretical maximum density (TMD) and 85% TMD. For the 100% TMD Comp B and Cyclotol samples, the RDX content values calculated by segmentation were 3% and 9% lower, respectively, than the values measured by high‐performance liquid chromatography on material from the same synthesis lots. This result is consistent with the expected underreporting of RDX content resulting from x‐ray CT resolution limits on RDX particles with diameters smaller than 25 µm. The 85% TMD samples were less accurately segmented with our algorithm due to the confounding presence of voids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2012

An Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation of the ICESat-2 Mission

The Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission has been selected by NASA as a Decadal Survey mission, to be launched in 2016. Mission objectives are to measure land ice elevation, sea ice freeboard/ thickness and changes in these variables and to collect measurements over vegetation that will facilitate determination of canopy height, with an accuracy that will allow prediction of future environmental changes and estimation of sea-level rise. The importance of the ICESat-2 project in estimation of biomass and carbon levels has increased substantially, following the recent cancellation of all other planned NASA missions with vegetation-surveying lidars. Two innovative components will characterize the ICESat-2 lidar: (1) Collection of elevation data by a multi-beam system and (2) application of micropulse lidar (photon counting) technology. A micropulse photon-counting altimeter yields clouds of discrete points, which result from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of returned points to reflectors of interest including canopy and ground in forested areas. The objective of this paper is to derive and validate an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2-type data. Data are based on airborne observations with a Sigma Space micropulse lidar and vary with respect to signal strength, noise levels, photon sampling options and other properties. A mathematical algorithm is developed, using spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors and geostatistical classification parameters and hyperparameters. Validation shows that the algorithm works very well and that ground and canopy elevation, and hence canopy height, can be expected to be observable with a high accuracy during the ICESat-2 mission. A result relevant for instrument design is that even the two weaker beam classes considered can be expected to yield useful results for vegetation measurements (93.01-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp9) and 72.85% - 98.68% for 0.48 msp (msp4)). Resampling options affect results more than noise levels. The algorithm derived here is generally applicable for analysis of micropulse lidar altimeter data collected over forested areas as well as other surfaces, including land ice, sea ice and land surfaces.

Herzfeld, Ute C.↗

DOE OSTI2024

Evaluating cosmological biases using photometric redshifts for Type Ia Supernova cosmology with the Dark Energy Survey Supernova Program

Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance–redshift relation. While obtaining a host-galaxy spectroscopic redshift for most SNe is feasible for small-area transient surveys, it will be too resource intensive for upcoming large-area surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time, which will observe on the order of millions of SNe. Here, we use data from the Dark Energy Survey (DES) to address this problem with photometric redshifts (photo-z) inferred directly from the SN light curve in combination with Gaussian and full p(z) priors from host-galaxy photo-z estimates. Using the DES 5-yr photometrically classified SN sample, we consider several photo-z algorithms as host-galaxy photo-z priors, including the Self-Organizing Map redshifts (SOMPZ), Bayesian Photometric Redshifts (BPZ), and Directional-Neighbourhood Fitting (DNF) redshift estimates employed in the DES 3 × 2 point analyses. With detailed catalogue-level simulations of the DES 5-yr sample, we find that the simulated w can be recovered within ±0.02 when using SN+SOMPZ or DNF prior photo-z, smaller than the average statistical uncertainty for these samples of 0.03. With data, we obtain biases in w consistent with simulations within ~1σ for three of the five photo-z variants. We further evaluate how photo-z systematics interplay with photometric classification and find classification introduces a subdominant systematic component. This work lays the foundation for next-generation fully photometric SNe Ia cosmological analyses.

(cosmology:) dark energy↗

NASA NTRS2020

An Efficient Area-Based Algorithm for SAR Radiometric Terrain Correction and Map Projection

This article presents a projection algorithm based on the representation of radar samples as area elements, rather than point elements as traditionally done in previous works. Each area element in the geographic grid (geogrid) is associated with a set of samples in the radar grid that intersect completely or partially the area element according to the topography and the radar geometry. Accurate geocoding with adaptive multi-looking is achieved by successively assigning the weighted average of the radar samples to the corresponding geogrid elements. Analogously, the slant-range projection of geocoded data is improved by projecting the geogrid pixels onto the radar grid according to their projected area. When our slant-range projection approach is used within previously-published radiometric terrain correction (RTC) algorithms, the processing time is significantly reduced, performing 3.6 to 5.2 times faster over multi-looked data and up to 8.9 over single-look data. We demonstrate the strength of the area projection algorithm for RTC and geocoding using UAVSAR and Sentinel-1 data, and evaluate the results in the context of the upcoming NISAR mission.

Shiroma, Gustavo H↗

DOE OSTI2025

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗

NASA NTRS2010

Utilization of Airborne and in Situ Data Obtained in SGP99, SMEX02, CLASIC and SMAPVEX08 Field Campaigns for SMAP Soil Moisture Algorithm Development and Validation

Field experiment data sets that include coincident remote sensing measurements and in situ sampling will be valuable in the development and validation of the soil moisture algorithms of the NASA's future SMAP (Soil Moisture Active and Passive) mission. This paper presents an overview of the field experiment data collected from SGP99, SMEX02, CLASIC and SMAPVEX08 campaigns. Common in these campaigns were observations of the airborne PALS (Passive and Active L- and S-band) instrument, which was developed to acquire radar and radiometer measurements at low frequencies. The combined set of the PALS measurements and ground truth obtained from all these campaigns was under study. The investigation shows that the data set contains a range of soil moisture values collected under a limited number of conditions. The quality of both PALS and ground truth data meets the needs of the SMAP algorithm development and validation. The data set has already made significant impact on the science behind SMAP mission. The areas where complementing of the data would be most beneficial are also discussed.

Soil moisture↗

NASA NTRS1978

A direct element resequencing procedure

Element by element frontal solution algorithms are utilized in many of the existing finite element codes. The overall computational efficiency of this type of procedure is directly related to the element data input sequence. Thus, it is important to have a pre-processor which will resequence these data so as to reduce the element wavefronts to be encountered in the solution algorithm. A direct element resequencing algorithm is detailed for reducing element wavefronts. It also generates computational by products that can be utilized in pre-front calculations and in various post-processors. Sample problems are presented and compared with other algorithms.

Akin, J. E.↗

NASA NTRS2021

Multi-Pass Sequential Mini-Batch Stochastic Gradient Descent Algorithms for Noise Covariance Estimation in Adaptive Kalman Filtering

Estimation of unknown noise covariances in a Kalman filter is a problem of significant practical interest in a wide array of applications. Although this problem has a long history, reliable algorithms for their estimation were scant, and necessary and sufficient conditions for identifiability of the covariances were in dispute until recently. Necessary and sufficient conditions for covariance estimation and a batch estimation algorithm were presented in our previous study. This paper presents stochastic gradient descent algorithms for noise covariance estimation in adaptive Kalman filters that are an order of magnitude faster than the batch method for similar or better root mean square error. More significantly, these algorithms are applicable to non-stationary systems where the noise covariances can occasionally jump up or down by an unknown magnitude. The computational efficiency of the new algorithms stems from adaptive thresholds for convergence, recursive fading memory estimation of the sample cross-correlations of the innovations, and accelerated stochastic gradient descent algorithms. The comparative evaluation of the proposed methods on a number of test cases demonstrates their computational efficiency and accuracy.

Adaptive Kalman filtering↗

NASA NTRS2004

Hardware-In-The-Loop Testing of Continuous Control Algorithms for a Precision Formation Flying Demonstration Mission

A sample mission sequence is defined for a low earth orbit demonstration of Precision Formation Flying (PFF). Various guidance navigation and control strategies are discussed for use in the PFF experiment phases. A sample PFF experiment is implemented and tested in a realistic Hardware-in-the-Loop (HWIL) simulation using the Formation Flying Test Bed (FFTB) at NASA's Goddard Space Flight Center.

Naasz, Bo J.↗

NASA NTRS2017

Kepler Planet Detection Metrics: Automatic Detection of Background Objects Using the Centroid Robovetter

We present an automated method of identifying background eclipsing binaries masquerading as planet candidates in the Kepler planet candidate catalogs. We codify the manual vetting process for Kepler Objects of Interest (KOIs) described in Bryson et al. (2013) with a series of measurements and tests that can be performed algorithmically. We compare our automated results with a sample of manually vetted KOIs from the catalog of Burke et al. (2014) and find excellent agreement. We test the performance on a set of simulated transits and find our algorithm correctly identifies simulated false positives approximately 50 of the time, and correctly identifies 99 of simulated planet candidates.

Centroid↗

NASA NTRSDate not supplied

Ten Year Ozone Profile Record From Suomi NPP OMPS Limb Profiler

In this study, we evaluate a decadal ozone profile record derived from Suomi NPP Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP). The data from OMPS LP were re-processed with the new retrieval algorithm from 2012 to present. The new reprocessing includes adjustments in both Level 1 and Level 2 algorithms. The sensor’s altitude registration, updates in radiometric calibrations, under-sampling and stray light corrections were addressed in Level 1 processing. The new retrieval algorithm (version 2.7) combines measurements from UV and VIS parts of the spectra to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km, unlike to previous version 2.5 where ozone profiles were retrieved independently from UV and VIS. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, we implemented a new aerosol correction that assumes a gamma-function particle size distribution. In addition, ozone and nitrogen dioxide cross sections and climatologies were updated. We discuss sensitivity of the ozone retrievals to implemented changes in Level 1 and Level 2 algorithms. We focus our analysis on evaluation of the stability of the 10-year record from OMPS LP. We show results from the internal methods for characterizing the stability of the LP altitude registration and compare the LP reflectivity and ozone with the similar quantities measured by OMPS nadir sensors. Finally, we will show results from comparisons with independent satellite (MLS and SAGE III) and ozone sonde measurements.

Ozone↗

NASA NTRS1994

Massively Parallel Algorithms for Real-Time Wavefront Control of a Dense Adaptive Optics System

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. We have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. We develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, our algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures.

massively↗

NASA NTRS2018

Performance Metrics for the Assessment of Satellite Data Products: An Ocean Color Case Study

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multimetric and user-dependent approach that can be applied within science, modeling, and resource management communities.

remote sensing↗

DOE OSTI2025

RICH (Robotic Interface Control & Handling) System for VULCAN

High flux neutron beam and high efficiency detectors warrant quick turn arounds of neutron diffraction measurements at the engineering materials diffractometer VULCAN. Efficient change and alignment of samples and automatic measurements at VULCAN are desired for better use of neutron beam time by users. In this work, we aim to develop a proof-of-concept Robotic Interactive Control & Handling System (RICH) for sample handling at VULCAN that could assist high throughput experiments and reduce the overhead time significantly. This was realized by a six-axis desktop robot with trained AI models. The trained AI models can recognize and locate samples in various types of positions in a live video stream. In addition, we developed smart algorithms which used our models on multiple cameras to recognize where samples are with respect to multiple point of views, and then using user-inputted parameters, align them to perform complex measurements.

42 ENGINEERING↗

NASA NTRS1999

A Goal Seeking Strategy for Constructing Systems from Alternative Components

This paper describes a methodology to efficiently construct feasible systems then modify feasible systems to meet successive goals by selecting from alternative components, a problem recognized to be n-p complete. The methodology provides a means to catalog and model alternative components. A presented system modeling Structure is robust enough to model a wide variety of systems and provides a means to compare and evaluate alternative systems. These models act as input to a methodology for selecting alternative components to construct feasible systems and modify feasible systems to meet design goals and objectives. The presented algorithm's ability to find a restricted solution, as defined by a unique set of requirements, is demonstrated against an exhaustive search of a sample of proposed shuttle modifications. The utility of the algorithm is demonstrated by comparing results from the algorithm with results from three NASA shuttle evolution studies using their value systems and assumptions.

Valentine, Mark E.↗

DOE OSTI2025

Randomized Algorithms for Low-Rank Matrix and Tensor Decompositions

This paper surveys randomized algorithms in numerical linear algebra for low-rank decompositions of matrices and tensors. The survey begins with a review of classical matrix algorithms that can be accelerated by randomized dimensionality reduction, such as the singular value decomposition (SVD) or interpolative (ID) and CUR decompositions. Recent advances in randomized dimensionality reduction are discussed, including new methods of fast matrix sketching and sampling techniques, which are incorporated into classical matrix algorithms for fast low-rank matrix approximations. The extension of randomized matrix algorithms to tensors is then explored for several low-rank tensor decompositions in the CP and Tucker formats, including the higher-order SVD, ID, and CUR decomposition.

Pearce, Katherine J. [The University of Texas at A↗

NASA NTRS1999

A Comparative Study of Interferometric Regridding Algorithms

THe paper discusses regridding options: (1) The problem of interpolating data that is not sampled on a uniform grid, that is noisy, and contains gaps is a difficult problem. (2) Several interpolation algorithms have been implemented: (a) Nearest neighbor - Fast and easy but shows some artifacts in shaded relief images. (b) Simplical interpolator - uses plane going through three points containing point where interpolation is required. Reasonably fast and accurate. (c) Convolutional - uses a windowed Gaussian approximating the optimal prolate spheroidal weighting function for a specified bandwidth. (d) First or second order surface fitting - Uses the height data centered in a box about a given point and does a weighted least squares surface fit.

Hensley, Scott↗