Search NASA⌕ Search

SEARCH · Search NASA

Results for “fast function extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Numerical Method for Determining the Elements of Circumbinary Orbits and Its Application to Circumbinary Planets and the Satellites of Pluto-Charon

Planets and satellites orbiting a binary system exist in the solar system and extrasolar planetary systems. Their orbits can be significantly different from Keplerian orbits, if they are close to the binary and the secondary-to-primary mass ratio is high. A proper description of a circumbinary orbit is in terms of the free eccentricity e {sub free} at the epicyclic frequency κ {sub 0}, forced eccentricity e {sub forced} at the mean motion n {sub 0}, and oscillations at higher frequencies forced by the non-axisymmetric components of the binary’s potential. We show that accurate numerical values for the amplitudes and frequencies of these terms can be extracted from numerical orbit integrations by applying fast Fourier transformation (FFT) to the cylindrical distance between the circumbinary object and the center of mass of the binary as a function of time. We apply this method to three Kepler circumbinary planets and the satellites of Pluto-Charon. For the satellite Styx of Pluto-Charon, the FFT results for κ {sub 0} and e {sub free} differ significantly from the first-order analytic value and the value reported by Showalter & Hamilton, respectively. We show that the deviation in κ {sub 0} is likely due to the effect of the 3:1 mean-motion resonance and discuss the implications of the lower value for e {sub free}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Review of Current Software for Analyzing Total X-ray Scattering Data from Liquids

The popularity of the pair distribution function (PDF) analysis of X-ray total scattering data has steadily grown as access to ex situ synchrotron data has expanded. Due to the broadening of the PDF user community, there is a growing demand for software that can be used to extract PDFs and is accessible to non-expert users. While user-friendly options have been developed over the past decade for fast, streamlined data analysis, care must be taken in both processing the data and understanding any limitations, especially in the case of liquids. In this review, the same scattering data are analyzed using different total X-ray scattering software, in order to compare the accuracy of the extracted structure factors and associated pair distribution functions. The goal is to assess the best practices for extracting the most accurate liquid data for each software package. The importance of absolute normalization and the application of the most appropriate corrections are emphasized via quantitative comparisons between liquid sulfur and water. Additionally, an awareness of the competing conventions used to define the PDF in crystallography and liquids/glasses is crucial for both the downstream analyses of the data and a comparison with the previous results in the literature.

Gallington, Leighanne C. (ORCID:0000000203837522)↗
DOE OSTI2018

Functionalized Porous Organic Polymers as Uranium Nano-Traps for Efficient Recovery of Uranium from Seawater

The long-term use of nuclear power for energy applications relies on the secure and economical supply of nuclear fuel. Among various natural sources of uranium for use in nuclear reactors, seawater is highly appealing given that the oceans contain about 4.5 billion tons of dissolved uranium, almost 1000 times that estimated for mineral reserves. Nonetheless, the concentration of uranium in seawater is extremely low (3-3.3 mg L -1 or 3-3.3 ppb); this, coupled with the presence of a relatively high concentration of other metal ions, makes uranium recovery from seawater a challenge that requires the development of efficient and effective separation processes. Various adsorbent technologies based upon synthetic organic polymers, biopolymers, inorganic materials, mesoporous silica materials, porous carbon-based adsorbents, and ionic liquids have been widely developed for the extraction of uranium from seawater. However, these benchmark sorbent materials suffer from a number of drawbacks such as low adsorption capacity (typically 0.1~3.2 mg-U g -1 adsorbent), poor selectivity, and slow kinetics. Given the extreme complexity and vast volume of seawater, as well as the very low concentration of uranium present, to attain this ambitious task demands the design of adsorbents with high affinity and fast kinetics. The main objective of this project is to develop functional porous organic polymers (POPs) as a new type of adsorbent for mining uranium from seawater. This class of porous materials has quickly moved to the forefront of materials research due to their high internal surface areas, exceptional water/chemical stability, facile chemical tunability, and extraordinary capability to selectively adsorb large quantities of guest species The potential to deploy POPs in uranium extraction is related to the ease with which their internal surfaces can be decorated with high densities of strong binding sites. Beyond introducing postsynthetic modification, the specific functionalities also can be used as building units to be incorporated into porous frameworks. Our approach to fulfill this task involves the custom-design of POP-based uranium “nano-traps” via a “crystal engineering” guided design followed by stepwise post-synthetic modification. Furthermore, to increase the density of chelating groups and to enhance their affinity towards uranyl ions, judiciously designed chelating systems were constructed into porous organic polymers. Moreover, to improve the accessibility of the chelating groups and thereby the utilization efficiency, we assembled the chelating groups into highly crystalline materials where they are aligned in periodic arrays on the open channels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Deep Data Analytics in Structural and Functional Imaging of Nanoscale Materials

Recent advances in scanning probe microscopy and scanning transmission electron microscopy have opened unprecedented opportunities in probing the materials structural parameters and electronic properties in real space on a picometre-scale. At the same time, the ability of modern day microscopes to quickly produce large, high-resolution datasets has created a challenge for rapid physics-guided analysis of data that typically contain several hundreds to several thousand atomic or molecular units per image. Here it is demonstrated how the advanced statistical analysis and machine learning techniques can be used for extracting relevant physical and chemical information from microscope data on multiple functional materials. Specifically, the following three case studies are discussed (i) application of a combination of convolutional neural network and Markov model for analyzing positional and orientational order in molecular self-assembly; (ii) a combination of sliding window fast Fourier transform, Pearson correlation matrix and canonical correlation analysis methods to study the relationships between lattice distortions and electron scattering patterns in graphene; (iii) application of a non-negative matrix factorization with physics-based constraints and Moran’s analysis of spatial associations to extracting electronic responses linked to different types of structural domains from multi-modal imaging datasets on iron-based superconductors. The approaches demonstrated here are universal in nature and can be applied to a variety of microscopic measurements on different materials.

Ziatdinov, Maxim↗
DOE OSTI2026

Fermilab PIP II machine protection system digitized data noise elimination scheme and its FPGA implementation

In Fermilab's PIP-II machine protection system, beam loss signals from various detectors are digitized at 125 MS/s. Noise from both high-frequency sources and low-frequency 60 Hz AC power equipment can contaminate the data. To suppress noise across these ranges especially 60 Hz and its harmonics, which overlap with beam loss signal frequencies advanced digital processing beyond standard filtering is required. Several real-time functional blocks were simulated and tested on an FPGA: (1) a dual time-constant discharging integrator filter, (2) a de-ripple baseline extraction and storage block, and (3) a fast-recovery discharging integrator. The nonlinear IIR integrator filter removes high-frequency noise and feeds into the baseline extractor. Upon detecting abrupt beam loss, it switches to a longer time constant to prevent baseline distortion. The de-ripple block calculates a valid baseline by averaging over multiple 60 Hz periods, storing results in a 4096-word FPGA RAM. This baseline is subtracted from raw data before integration by the fast-recovery block, which resets quickly after use. All blocks achieved expected performance.

Wu, J. [Fermilab] (ORCID:0000000344329521)↗
DOE OSTI2019

A fast reconstruction method of the dense point-cloud model for cultural heritage artifacts based on compressed sensing and sparse auto-encoder

Since the point cloud data of cultural heritage artifacts obtained by the laser scanner is enormous and dense, these lead to a large quantity of network resource for storing, processing, and transmission. This paper provided a fast reconstruction method of the dense point cloud model for cultural relics based on sparse auto-encoder and compressed sensing. Firstly, the octree method based on the hash function was utilized to extract local features and remove redundant points. Secondly, the point cloud, which can be seen as the 3D geometric signal, is projected to the discrete Laplacian sparse basis via the point cloud adjacency matrix. Then, aiming at the bottleneck of slow recovery caused by tremendous scale of inverse problem based on compressed sensing theory, the sparse auto-encoder was applied to reduce the dimension and speed up the recovery. Finally, the OMP algorithm was applied to reconstruct 3D point cloud model based on the stochastic Gauss matrix. In order to test the performance of our methods, the 3D point cloud model of terracotta warriors and horses head were used. And the experimental results demonstrated that our approach can obviously accelerate the process of reconstruction of the dense point cloud model for the cultural heritage artifacts and ensure the recovery accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Improvements to Passive Heat Removal Systems in SAS4A/SASSYS-1

Safe operation of a sodium cooled fast reactor (SFR) can be significantly aided by heat removal systems that do not rely on active power, but function using passive means. Passive heat removal from such reactors can employ systems that extract heat directly from sodium coolant by utilizing heat exchangers submerged in the coolant and natural circulation of a metal fluid sodium (or sodium potassium eutectic) to heat exchangers (generally air cooled) externally located. These types of systems are generally called Direct Reactor Auxiliary Cooling Systems (DRACS). Another type of passive heat removal system particularly suitable for pool-type SFRs relies on indirect extraction of heat by utilizing air flow in an annular region surrounding the reactor guard vessel which discharges the heat via the chimney effects to the atmosphere. These systems are generally called Reactor Vessel Auxiliary Cooling Systems (RVACS).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A robust BAO extractor

We define a procedure to extract the oscillating part of a given nonlinear Power Spectrum, and derive an equation describing its evolution including the leading effects at all scales. The intermediate scales are taken into account by standard perturbation theory, the long range (IR) displacements are included by using consistency relations, and the effect of small (UV) scales is included via effective coefficients computed in simulations. We show that the UV effects are irrelevant in the evolution of the oscillating part, while they play a crucial role in reproducing the smooth component. Our 'extractor' operator can be applied to simulations and real data in order to extract the Baryonic Acoustic Oscillations (BAO) without any fitting function and nuisance parameter. We conclude that the nonlinear evolution of BAO can be accurately reproduced at all scales down to 0 z = by our fast analytical method, without any need of extra parameters fitted from simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Fermilab PIP II Machine Protection System Digitized Data Noise Elimination Scheme and Its FPGA Implementation

In Fermilab's PIP-II machine protection system, beam loss signals from various detectors are digitized at 125 MS/s. Noise from both high-frequency sources and low-frequency 60 Hz AC power equipment can con-taminate the data. To suppress noise across these ranges especially 60 Hz and its harmonics, which overlap with beam loss signal frequencies advanced digital processing beyond standard filtering is re-quired. Several real-time functional blocks were simu-lated and tested on an FPGA: (1) a dual time-constant discharging integrator filter, (2) a de-ripple baseline extraction and storage block, and (3) a fast-recovery discharging integrator. The nonlinear IIR integrator filter removes high-frequency noise and feeds into the baseline extractor. Upon detecting abrupt beam loss, it switches to a longer time constant to prevent baseline distortion. The de-ripple block calculates a valid base-line by averaging over multiple 60 Hz periods, storing results in a 4096-word FPGA RAM. This baseline is subtracted from raw data before integration by the fast-recovery block, which resets quickly after use. All blocks achieved expected performance.

Wu, Jinyuan [Fermilab] (ORCID:0000000344329521)↗
NASA NTRS1972

Computer generation of symbolic network functions - A new theory and implementation.

A new method is presented for obtaining network functions in which some, none, or all of the network elements are represented by symbolic parameters (i.e., symbolic network functions). Unlike the topological tree enumeration or signal flow graph methods generally used to derive symbolic network functions, the proposed procedure employs fast, efficient, numerical-type algorithms to determine the contribution of those network branches that are not represented by symbolic parameters. A computer program called NAPPE (for Network Analysis Program using Parameter Extractions) and incorporating all of the concepts discussed has been written. Several examples illustrating the usefulness and efficiency of NAPPE are presented.

Alderson, G. E.↗
NASA NTRS1992

Real-time diagnostics for a reusable rocket engine

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Guo, T. H.↗
DOE OSTI2017

Laser photodetachment of radioactive 128 I -

The first experimental investigation of the electron affinity (EA) of a radioactive isotope has been conducted at the CERN-ISOLDE radioactive ion beam facility. The EA of the radioactive iodine isotope 128 I ($t$ 1/2 = 25 min) was determined to be 3.059 052(38) eV. The experiment was conducted using the newly developed Gothenburg ANion Detector for Affinity measurements by Laser PHotodetachment (GANDALPH) apparatus, connected to a CERN-ISOLDE experimental beamline. 128 I was produced in fission induced by 1.4 GeV protons striking a thorium/tantalum foil target and then extracted as singly charged negative ions at a beam energy of 20 keV. Laser photodetachment of the fast ion beam was performed in a collinear geometry inside the GANDALPH chamber. Neutral atoms produced in the photodetachment process were detected by allowing them to impinge on a glass surface, creating secondary electrons which were then detected using a channel electron multiplier. The photon energy of the laser was tuned across the threshold of the photodetachment process and the detachment threshold data were fitted to a Wigner law function in order to extract the EA. In conclusion, this first successful demonstration of photodetachment at an isotope separator on line facility opens up the opportunity for future studies of the fundamental properties of negatively charged radioactive isotopes such as the EA of astatine and polonium.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Efficient Capture and Release of the Rare-Earth Element Neodymium in Aqueous Solution by Recyclable Covalent Organic Frameworks

Rare-earth elements (REEs) are present in a broad range of critical materials. The development of solid adsorbents for REE capture could enable the cost-effective recycling of REE-containing magnets and electronics. In this context, covalent organic frameworks (COFs) are promising candidates for REE adsorption due to their exceptionally high surface area. Despite having attractive physical properties, COFs are heavily underutilized for REE capture applications due to their limited lifecycle in aqueous acidic environments, as well as synthetic challenges associated with the incorporation of ligands suitable for REE capture. Here, in this work, we show how the Ugi multicomponent reaction can be leveraged to postsynthetically modify imine-based COFs for the introduction of a diglycolic acid (DGA) moiety, an efficient scaffold for REE capture. The adsorption capacity of the DGA-functionalized COF was found to be more than 40 times higher than that of the pristine imine COF precursor and more than four times higher than that of the next-best reported DGA-functionalized solid support. This rationally designed COF has appealing characteristics of high adsorption capacity, fast and efficient capture and release of the REE ions, and reliable recyclability, making it one of the most promising adsorbents for solid–liquid REE ion extractions reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques

Abstract. Improving predictive understanding of Earth system variability and change requires data–model integration. Efficient data–model integration for complex models requires surrogate modeling to reduce model evaluation time. However, building a surrogate of a large-scale Earth system model (ESM) with many output variables is computationally intensive because it involves a large number of expensive ESM simulations. In this effort, we propose an efficient surrogate method capable of using a few ESM runs to build an accurate and fast-to-evaluate surrogate system of model outputs over large spatial and temporal domains. We first use singular value decomposition to reduce the output dimensions and then use Bayesian optimization techniques to generate an accurate neural network surrogate model based on limited ESM simulation samples. Our machine-learning-based surrogate methods can build and evaluate a large surrogate system of many variables quickly. Thus, whenever the quantities of interest change, such as a different objective function, a new site, and a longer simulation time, we can simply extract the information of interest from the surrogate system without rebuilding new surrogates, which significantly reduces computational efforts. We apply the proposed method to a regional ecosystem model to approximate the relationship between eight model parameters and 42 660 carbon flux outputs. Results indicate that using only 20 model simulations, we can build an accurate surrogate system of the 42 660 variables, wherein the consistency between the surrogate prediction and actual model simulation is 0.93 and the mean squared error is 0.02. This highly accurate and fast-to-evaluate surrogate system will greatly enhance the computational efficiency of data–model integration to improve predictions and advance our understanding of the Earth system.

58 GEOSCIENCES↗
DOE OSTI2017

Detection of Ketones by a Novel Technology: Dipolar Proton Transfer Reaction Mass Spectrometry (DP-PTR-MS)

Proton transfer reaction mass spectrometry (PTR-MS) has played an important role in the field of real-time monitoring of trace volatile organic compounds (VOCs) due to its advantages such as low limit of detection (LOD) and fast time response. Recently, a new technology of proton extraction reaction mass spectrometry (PER-MS) with negative ions OH{sup –} as the reagent ions has also been presented, which can be applied to the detection of VOCs and even inorganic compounds. In this work, we combined the functions of PTR-MS and PER-MS in one instrument, thereby developing a novel technology called dipolar proton transfer reaction mass spectrometry (DP-PTR-MS). The selection of PTR-MS mode and PER-MS mode was achieved in DP-PTR-MS using only water vapor in the ion source and switching the polarity. In this experiment, ketones (denoted by M) were selected as analytes. The ketone (molecular weight denoted by m) was ionized as protonated ketone [M + H]{sup +} [mass-to-charge ratio (m/z) m + 1] in PTR-MS mode and deprotonated ketone [M – H]{sup –} (m/z m – 1) in PER-MS mode. By comparing the m/z value of the product ions in the two modes, the molecular weight of the ketone can be positively identified as m. Results showed that whether it is a single ketone sample or a mixed sample of eight kinds of ketones, the molecular weights can be detected with DP-PTR-MS. The newly developed DP-PTR-MS not only maintains the original advantages of PTR-MS and PER-MS in sensitive and rapid detection of ketones, but also can estimate molecular weight of ketones. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Digital Time-Resolved Spot Diagnostic

The digital time-resolved spot diagnostic (D-TRSD) is a fast-response, time-dependent beam diagnostic for measuring the emitted spot size and beam target interactions from radiographic x-ray sources. Legacy streaked TRSD analysis requires image processing and data extraction, which give noisy results. Processed data are used to extract edge spread and corresponding line spread functions. Digital TRSD simplifies this process, eliminating the complexity of streak camera–based systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Measuring Plant Metabolite Abundance in Spearmint ( Mentha spicata L.) with Raman Spectra to Determine Optimal Harvest Time

A fast field-deployable method utilizing Raman spectroscopy to determine the optimal harvest time of plants to extract the highest abundance of target metabolites is presented. Rosmarinic acid is a metabolite extracted from spearmint (Mentha spicata L.). Leaves from commercial “Native” and proprietary clonal line “KI110” spearmint were measured as a function of cell type and age to determine rosmarinic acid abundance. A linear regression model with leave-one-out cross-validation (R 2 CV = 0.61, RMSECV = 11.1 mg/g) was developed between selected Raman peak areas and rosmarinic acid concentrations determined by high-performance liquid chromatography (HPLC). A principal component analysis (PCA) model was also developed to determine rosmarinic acid abundance. The method may be suited to the analysis of many agriculturally relevant plant species and metabolites with distinct Raman peaks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors

This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗