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Results for “one-shot method”

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 OSTI2025

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Solving Stochastic Dynamic Programming Problems: A Mixed Complementarity Approach

We detail a mixed complementarity problem (MCP) formulation of continuous state dynamic programming problems (DP-MCP). We write the solution to projection methods in value function iteration (VFI) as a joint set of optimality conditions that characterize maximization of the Bellman equation; and approximation of the value function. The MCP approach replaces the iterative component of projection based VFI with a one-shot solution to a square system of complementary conditions. We provide three numerical examples to illustrate our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Measurement techniques using the electron beam profile scanner at the Fermilab Main Injector

This work presents techniques for non-invasive transverse profile measurements of high-intensity proton beams using an Electron Beam Profile Scanner (EBPS). The EBPS utilizes low-energy electrons as a probe to analyze the transverse size of proton beams, allowing for potential analysis on a single-bunch basis. Recent upgrades to the Fermilab Main Injector have enhanced beam power on target to 1 MW, with future developments targeting 2 MW. The higher beam power has increased the demand for non-invasive diagnostics, as invasive methods can disrupt operations.The techniques presented include 1) the slow scan technique, which serves as a proof of concept for the probe beam, 2) the one-shot scan technique for measuring horizontal beam profiles, and 3) the raster scan technique for analyzing horizontal beam profiles as a function of the longitudinal distribution of the beam. The profiles obtained will be crucial for studying and understanding instabilities in high-power, high-intensity proton beams. This will contribute to optimizing the operation of high-power proton accelerators by minimizing beam loss, activation, and damage to both the diagnostics and the accelerator components.

Mwaniki, Matilda [IIT, Chicago]↗
DOE OSTI2016

3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images

Purpose: Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. Methods: The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3D exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. Results: The proposed method was applied for tooth segmentation of twenty clinically captured CBCT images. Three metrics, including the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the mean surface deviation (MSD), were used to quantitatively analyze the segmentation of anterior teeth including incisors and canines, premolars, and molars. The segmentation of the anterior teeth achieved a DSC up to 98%, a JSC of 97%, and an MSD of 0.11 mm compared with manual segmentation. For the premolars, the average values of DSC, JSC, and MSD were 98%, 96%, and 0.12 mm, respectively. The proposed method yielded a DSC of 95%, a JSC of 89%, and an MSD of 0.26 mm for molars. Aside from the interactive definition of label priors by the user, automatic tooth segmentation can be achieved in an average of 1.18 min. Conclusions: The proposed technique enables an efficient and reliable tooth segmentation from CBCT images. This study makes it clinically practical to segment teeth from CBCT images, thus facilitating pre- and interoperative uses of dental morphologies in maxillofacial and orthodontic treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Advanced Characterization of Wastewaters with a Focus on the Environment & Economics (Final Technical Progress Report)

This project, funded by the U.S. Department of Energy under award DE-FE0032457 and conducted at the University of Illinois at Urbana-Champaign, focused on advancing the characterization of coal combustion residual (CCR) effluents. The primary objectives were to develop analytical methods for detecting major cations, anions, trace metals, and rare earth elements (REEs) in CCR wastewater, assess environmental impacts, and explore opportunities for resource recovery. The project advanced the development of a "One-Shot" analysis system designed to simultaneously analyze multiple analytes in CCR effluents.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1980

A low-cost forward fairing for the Bell Long Ranger Helicopter

A description is presented of work concerned with determining the effects of long-term flight service on advanced composite helicopter airframe components. The helicopter chosen for the program is the Long Ranger Model 206L. The components to be evaluated include the baggage door, litter door, vertical fin, and forward fairing. Only the vertical fin is classified as primary structure. Loss of any of the other components will not compromise safety of the aircraft. Attention is given to the program objectives, the design of the forward fairing, the fabrication procedures, the exterior surface, the cocure procedure, material tests, and initial cost-tracking. The considered program demonstrates the ability to produce an acceptable fairing by the 'one-shot' cocured process and, based on learning curve experience, production costs will be low. The low-temperature 200 F cure does not affect the structural properties to an unacceptable degree. A method for obtaining a smooth, exterior painted surface for Kevlar/epoxy fabric has been developed.

Zinberg, H.↗
NASA NTRS1993

Classification of multispectral image data by the Binary Diamond neural network and by nonparametric, pixel-by-pixel methods

The classification of multispectral image data obtained from satellites has become an important tool for generating ground cover maps. This study deals with the application of nonparametric pixel-by-pixel classification methods in the classification of pixels, based on their multispectral data. A new neural network, the Binary Diamond, is introduced, and its performance is compared with a nearest neighbor algorithm and a back-propagation network. The Binary Diamond is a multilayer, feed-forward neural network, which learns from examples in unsupervised, 'one-shot' mode. It recruits its neurons according to the actual training set, as it learns. The comparisons of the algorithms were done by using a realistic data base, consisting of approximately 90,000 Landsat 4 Thematic Mapper pixels. The Binary Diamond and the nearest neighbor performances were close, with some advantages to the Binary Diamond. The performance of the back-propagation network lagged behind. An efficient nearest neighbor algorithm, the binned nearest neighbor, is described. Ways for improving the performances, such as merging categories, and analyzing nonboundary pixels, are addressed and evaluated.

Salu, Yehuda↗
NASA NTRS2011

Coding for Parallel Links to Maximize the Expected Value of Decodable Messages

When multiple parallel communication links are available, it is useful to consider link-utilization strategies that provide tradeoffs between reliability and throughput. Interesting cases arise when there are three or more available links. Under the model considered, the links have known probabilities of being in working order, and each link has a known capacity. The sender has a number of messages to send to the receiver. Each message has a size and a value (i.e., a worth or priority). Messages may be divided into pieces arbitrarily, and the value of each piece is proportional to its size. The goal is to choose combinations of messages to send on the links so that the expected value of the messages decodable by the receiver is maximized. There are three parts to the innovation: (1) Applying coding to parallel links under the model; (2) Linear programming formulation for finding the optimal combinations of messages to send on the links; and (3) Algorithms for assisting in finding feasible combinations of messages, as support for the linear programming formulation. There are similarities between this innovation and methods developed in the field of network coding. However, network coding has generally been concerned with either maximizing throughput in a fixed network, or robust communication of a fixed volume of data. In contrast, under this model, the throughput is expected to vary depending on the state of the network. Examples of error-correcting codes that are useful under this model but which are not needed under previous models have been found. This model can represent either a one-shot communication attempt, or a stream of communications. Under the one-shot model, message sizes and link capacities are quantities of information (e.g., measured in bits), while under the communications stream model, message sizes and link capacities are information rates (e.g., measured in bits/second). This work has the potential to increase the value of data returned from spacecraft under certain conditions.

Klimesh, Matthew A.↗
NASA NTRS1992

Derivation of hard deadlines for real-time control systems

The computation-time delay in the feedback controller of a real-time control system may cause failure to update the control input during one or more sampling periods. A dynamic failure is said to occur if this delay exceeds a certain limit called a hard deadline. The authors present a method for calculating the hard deadlines in linear time-invariant control systems. To derive necessary conditions for (asymptotic) system stability, the state difference equation is modified based on an assumed maximum delay and the probability distribution of delays whose magnitudes are less than, or equal to, the assumed maximum delay. Moreover, the allowed state-space-which is derived from given input and state constraints-is used to calculate the hard deadline as a function of time and the system state. The authors consider a one-shot delay model in which a single event causes a dynamic failure.

Shin, Kang G.↗
DOE OSTI2022

An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules

The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.

McKeon, Caroline A. (ORCID:0000000217373503)↗
NASA NTRS1992

Derivation and application of hard deadlines for real-time control systems

The computation-time delay in the feedback controller of a real-time control system may cause failure to update the control input during one or more sampling periods. If this delay exceeds a certain limit called a hard deadline, either the necessary conditions for system stability are violated or the system leaves the allowed state-space. In such a case a dynamic failure is said to occur to the system. A method for calculating the hard deadlines in linear time-invariant control systems by considering system stability and the allowed state-space is presented. To derive necessary conditions for (asymptotic) system stability, the state difference equation is modified based on an assumed maximum delay and the probability distribution of delays whose magnitudes are less than, or equal to, the assumed maximum delay. Moreover, the allowed state-space - which is derived from given input and state constraints - is used to calculate the hard deadline as a function of time and the system state. A one-shot delay model in which a single event causes a dynamic failure is also considered. The knowledge of hard deadline is then applied to the design of error recovery in a triple modular redundant (TMR) controller computer.

Shin, Kang G.↗
DOE OSTI2021

Photoelectron spectra of early 3 d -transition metal dioxide molecular anions from GW calculations

Photoelectron spectra of early 3 d -transition metal dioxide anions, Sc O 2 - , Ti O 2 - , V O 2 - , Cr O 2 - , and Mn O 2 - , are calculated using semilocal and hybrid density functional theory (DFT) and many-body perturbation theory within the GW approximation using one-shot perturbative and eigenvalue self-consistent formalisms. Different levels of theory are compared with each other and with available photoelectron spectra. We show that one-shot GW with a PBE0 starting point ( G 0 W 0 @PBE0) consistently provides very good agreement for all experimentally measured binding energies (within 0.1 eV–0.2 eV or less). We attribute this to the success of PBE0 in mitigating self-interaction error and providing good quasiparticle wave functions, which renders a first-order perturbative GW correction effective. One-shot GW calculations with a Perdew–Burke–Ernzerhof (PBE) starting point do poorly in predicting electron removal energies by underbinding orbitals with typical errors near 1.5 eV. A higher exact exchange amount of 50% in the DFT starting point of one-shot GW does not provide very good agreement with experiment by overbinding orbitals with typical errors near 0.5 eV. While not as accurate as G 0 W 0 @PBE0, the G -only eigenvalue self-consistent GW scheme with W fixed to the PBE level provides a reasonably predictive level of theory (typical errors near 0.3 eV) to describe photoelectron spectra of these 3 d -transition metal dioxide anions. Adding eigenvalue self-consistency also in W , on the other hand, worsens the agreement with experiment overall. Overall, our findings on the performance of various GW methods are discussed in the context of our previous studies on other transition metal oxide molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning and atomic layer deposition: Predicting saturation times from reactor growth profiles using artificial neural networks

In this work, we explore the application of deep neural networks to the optimization of atomic layer deposition (ALD) processes. In particular, we focus on a one-shot optimization problem, where we try to predict the optimal dose time that leads to saturation everywhere in the reactor based on thickness values measured at different points of an ALD reactor after a single trial growth. In order to tackle this problem, we introduce a dataset designed to train neural networks to predict saturation times based on these inputs for a cross-flow ALD reactor. Here, we then explore the predictive ability of artificial neural networks of different depths and sizes using a separate testing dataset to evaluate their accuracies. The results obtained show that networks trained using stochastic gradient descent methods can accurately predict saturation times without requiring any additional information on the surface kinetics. This provides a viable approach to minimize the number of experiments required to optimize new ALD processes in a known reactor, and it highlights the way machine learning can be leveraged for thin film growth and manufacturing. While the datasets and training procedure depend on the reactor geometry, the trained neural networks provide a general surrogate model connecting thickness values and trial dose times with optimal saturation times that can be reused for different ALD processes within the same reactor.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Towards predictive band gaps for halide perovskites: Lessons from one-shot and eigenvalue self-consistent GW

Halide perovskites constitute a chemically diverse class of crystals with great promise as photovoltaic absorber materials, featuring band gaps between about 1 and 3.5 eV depending on composition. Their diversity calls for a general computational approach to predicting their band gaps. However, such an approach is still lacking. Here, we use density functional theory (DFT) and ab initio many-body perturbation theory within the GW approximation to compute the quasiparticle or fundamental band gap of a set of ten representative halide perovskites: CH 3 NH 3 PbI 3 ( MAPbI 3 ), MAPbBr 3 , CsSnBr 3 , ( MA ) 2 BiTlBr 6 , Cs 2 TlAgBr 6 , Cs 2 TlAgCl 6 , Cs 2 BiAgBr 6 , Cs 2 InAgCl 6 , Cs 2 SnBr 6 , and Cs 2 Au 2 I 6 . Comparing with recent measurements, we find that a standard generalized gradient exchange-correlation functional can significantly underestimate the experimental band gaps of these perovskites, particularly in cases with strong spin-orbit coupling (SOC) and highly dispersive band edges, to a degree that varies with composition. We show that these nonsystematic errors are inherited by one-shot G 0 W 0 and eigenvalue self-consistent GW 0 calculations, demonstrating that semilocal DFT starting points are insufficient for MAPbI 3 , MAPbBr 3 , CsSnBr 3 , ( MA ) 2 BiTlBr 6 , Cs 2 TlAgBr 6 , and Cs 2 TlAgCl 6 . On the other hand, we find that DFT with hybrid functionals leads to an improved starting point and G W 0 results in better agreement with experiment for these perovskites. Our results suggest that G W 0 with hybrid functional-based starting points are promising for predicting band gaps of systems with large SOC and dispersive bands in this technologically important class of semiconducting crystals.</

36 MATERIALS SCIENCE↗
DOE OSTI2021

Facile Synthesis of Palladium-Based Nanocrystals with Different Crystal Phases and a Comparison of Their Catalytic Properties

A relatively unexplored aspect of noble-metal nanomaterials is polymorphism, or their ability to crystallize in different crystal phases. Here, in this work, a method is reported for the facile synthesis of Ru@Pd core–shell nanocrystals featuring polymorphism, with the core made of hexagonally close-packed (hcp)-Ru while the Pd shell takes either an hcp or face-centered cubic (fcc) phase. The polymorphism shows a dependence on the shell thickness, with shells thinner than ≈1.4 nm taking the hcp phase whereas the thicker ones revert to fcc. The injection rate provides an experimental knob for controlling the phase, with one-shot and drop-wise injection of the Pd precursor corresponding to fcc-Pd and hcp-Pd shells, respectively. When these nanocrystals are tested as catalysts toward formic acid oxidation, the Ru@Pd hcp nanocrystals outperform Ru@Pd fcc in terms of both specific activity and peak potential. Density functional theory calculations are also performed to elucidate the origin of this performance enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploiting a derivative discontinuity estimate for accurate G0W0 ionization potentials and electron affinities

Abstract The GW approximation has become an important tool for predicting charged excitations of isolated molecules and condensed systems. Its popularity can be attributed to many factors, including a favorable scaling and relatively good accuracy. In practical applications, the GW is often performed as a one-shot perturbation known as G 0 W 0 . Unfortunately, G 0 W 0 suffers from a strong starting point dependence and is often not as accurate as one would need. Self-consistent GW methodologies alleviate these problems but come with a marked increase in computational cost. In this manuscript, we propose the use of an estimate of the exchange-correlation derivative discontinuity to provide a remarkably good starting point for G 0 W 0 calculations, yielding ionization potentials and electron affinities with eigenvalue self-consistent GW quality at no additional cost. We assess the quality of the resulting methodology with the GW 100 benchmark set and compare its advantages over other similar methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-F-T-173: One-Scan Protocol: Verifying the Delivery of Spot-Scanning Proton Beam

Purpose: Radiochromic film for spot-scanning QA provides high spatial resolution and efficiency gains from one-shot irradiation for multiple depths. However, calibration can be a tedious procedure which may limit widespread use. Moreover, since there may be an energy dependence, which manifests as a depth dependence, this may require additional measurements for each patient. We present a one-scan protocol to simplify the procedure. Methods: We performed the calibration using an EBT3 film at depths of 18, 20, 24cm of Plastic Water exposed by a 6-level step-wedge plan on a Proteus Plus proton system (IBA, Belgium). The calibration doses ranged 65–250 cGy(RBE) for proton energies of 170–200MeV. A clinical prostate+nodes plan was used for validation. The planar doses at selected depths were measured with EBT3 films and analyzed using one-scan protocol (one-scan digitization of QA film and at least one film exposed to known dose). The Gamma passing rates, dose-difference maps, and profiles of 2D planar doses measured with EBT3 film, IBA MatriXX PT, versus TPS calculations were analyzed and compared. Results: The EBT3 film measurement results matched well with the TPS calculation data with an average passing rate of ∼95% for 2%/2mm and slightly lower passing rates were obtained from an ion chamber array detector. We were able to demonstrate that the use of a proton step-wedge provided clinically acceptable results and minimized variations between film-scanner orientation, inter-scan, and scanning conditions. Furthermore, it could be derived from no more than two films exposed to known doses (one could be zero) for rescaling the master calibration curve at each depth. Conclusion: The use of a proton step-wedge for calibration of EBT3 film increases efficiency. The sensitivity of the calibration to depth variations has been explored. One-scan protocol results appear to be comparable to that of the ion chamber array detector. One author has a research grant from Ashland Inc., the manufacturer of the GafChromic film.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1986

Reliable One-Shot Separation of Connectors

Concept for separating electrical connectors by remote control simple and reliable. Suitable for one-time, irreversible separations, method uses weak explosion to destroy one member of the connector.

Holmberg, W. R.↗