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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Stochastic and a posteriori optimization to mitigate coil manufacturing errors in stellarator design

Abstract It was recently shown in Wechsung et al (2022 Proc. Natl Acad. Sci. USA 119 e2202084119) that there exist electromagnetic coils that generate magnetic fields, which are excellent approximations to quasi-symmetric fields and have very good particle confinement properties. Using a Gaussian process-based model for coil perturbations, we investigate the impact of manufacturing errors on the performance of these coils. We show that even fairly small errors result in noticeable performance degradation. While stochastic optimization yields minor improvements, it is not possible to mitigate these errors significantly. As an alternative to stochastic optimization, we then formulate a new optimization problem for computing optimal adjustments of the coil positions and currents without changing the shapes of the coil. These a-posteriori adjustments are able to reduce the impact of coil errors by an order of magnitude, providing a new perspective for dealing with manufacturing tolerances in stellarator design.

Physics↗
DOE OSTI2023

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗
DOE OSTI2023

Integrated path planning and control through proximal policy optimization for a marine current turbine

This paper presents an integrated path planning and tracking control framework for a marine current turbine (MCT), where the MCT is treated as an energy-harvesting autonomous underwater vehicle (AUV). Considering the ocean (space of action) is continuous, the proposed framework employs two modules to address path planning and path tracking enabled by the proximal policy optimization (PPO) algorithm, which is a policy gradient deep reinforcement learning (RL) method. Further, to enable fully autonomous operation in a stochastic oceanic environment, the proposed path planning seeks a primary objective of maximizing the harvested energy; then, the path tracking module is designed to minimize the tracking error and avoid collisions with static and dynamic obstacles. Using field-collected acoustic Doppler current profiler (ADCP) data, the performance of the proposed framework is evaluated. Comparative studies with baseline algorithms in three different scenarios of path planning, path tracking without an obstacle, and path tracking with collision avoidance verify the effectiveness of our proposed approach.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗
DOE OSTI2026

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Relating the structure of geminal amido esters to their molecular hyperpolarizability

Advanced organic non-linear optical (NLO) materials have attracted increasing attention due to their multitude of applications in modern telecommunication devices. Arguably the most important advantage of organic NLO materials, relative to traditionally used inorganic NLO materials, is their short optical response time. Geminal amido esters with their donor-x-acceptor (D-π-A) architecture exhibit high levels of electron delocalization and substantial intramolecular charge transfer, which should endow these materials with short optical response times and large molecular (hyper)polarizabilities. In order to test this hypothesis, the linear and second-order non-linear optical properties of five geminal amido esters, ( E )-ethyl 3-(X-phenylamino)-2-(Y-phenylcarbamoyl)acrylate (1: X = 4-H,Y = 4-H; 2: X= 4-CH 3 , Y = 4-CH 3 ; 3: X = 4-NO 2 , Y = 2,5-OCH 3 ; 4: X = 2-Cl, Y = 2-Cl; 5: X = 4-Cl, Y = 4-Cl) were synthesized and characterized, whereby NLO structure-function relationships were established including intramolecular charge transfer characteristics, crystal field effects, and molecular first hyperpolarizabilities β. Given the typically large errors (10-30%) associated with the determination of (β) coefficients, three independent methods were used: i) density functional theory, ii) hyper-Rayleigh scattering, and iii) high-resolution X-ray diffraction data analysis based on multipolar modeling of electron densities at each atom. These three methods delivered consistent values of β, and based on these results, 3 should hold the most promise for NLO applications. In conclusion, the correlation between the molecular structure of these geminal amido esters and their linear and non-linear optical properties thus provide molecular design guidelines for organic NLO materials; this leads to the ultimate goal of generating bespoke organic molecules to suit a given NLO device application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Spectro-thermometry of M dwarfs and their candidate planets: Too hot, too cool, or just right?

We use moderate-resolution spectra of nearby late K and M dwarf stars with parallaxes and interferometrically determined radii to refine their effective temperatures, luminosities, and metallicities. We use these revised values to calibrate spectroscopic techniques to infer the fundamental parameters of more distant late-type dwarf stars. We demonstrate that, after masking out poorly modeled regions, the newest version of the PHOENIX atmosphere models accurately reproduce temperatures derived bolometrically. We apply methods to late-type hosts of transiting planet candidates in the Kepler field, and calculate effective temperature, radius, mass, and luminosity with typical errors of 57 K, 7%, 11%, and 13%, respectively. We find systematic offsets between our values and those from previous analyses of the same stars, which we attribute to differences in atmospheric models utilized for each study. We investigate which of the planets in this sample are likely to orbit in the circumstellar habitable zone. We determine that four candidate planets (KOI 854.01, 1298.02, 1686.01, and 2992.01) are inside of or within 1σ of a conservative definition of the habitable zone, but that several planets identified by previous analyses are not (e.g., KOI 1422.02 and KOI 2626.01). Only one of the four habitable-zone planets is Earth sized, suggesting a downward revision in the occurrence of such planets around M dwarfs. These findings highlight the importance of measuring accurate stellar parameters when deriving parameters of their orbiting planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Improving cosmological analyses of HI clustering by reducing stochastic noise

High-number-density tracers of large-scale structure, such as the HI-rich galaxies measured by 21 cm intensity mapping, have low sampling noise, making them particularly promising as cosmological probes. At large scales, this sampling noise can be subdominant to other scale-independent contributions to the power spectrum; such contributions arise from nonlinear bias, and exceed the sampling noise if at least one of the associated bias coefficients is sufficiently large. This has important consequences for cosmological constraints obtained from such tracers, since it indicates that using the power spectrum does not lead to optimal constraints even in the linear regime. In this paper, we provide a conservative estimate of the possible improvement in constraining power of a 21 cm survey if one were to use an optimal analysis strategy (such as field-level analysis), where only the true sampling noise enters the error budget. We find that improvements in uncertainties on some cosmological parameters can be as large as 50%, depending on redshift, foreground cleaning efficiency, scales used in the analysis, and instrumental noise. One byproduct of our work is measurements of bias parameters and stochasticity for neutral hydrogen in the IllustrisTNG simulation over a wide range of redshifts; we provide simple fitting formulas for these measurements. Furthermore, our results motivate further exploration of new optimal analysis techniques and provide important insights into the constraining power of current and future 21 cm surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Near, far, wherever you are: simulations on the dose efficiency of holographic and ptychographic coherent imaging

Different studies in X-ray microscopy have arrived at conflicting conclusions about the dose efficiency of imaging modes involving the recording of intensity distributions in the near (Fresnel regime) or far (Fraunhofer regime) field downstream of a specimen. A numerical study is presented on the dose efficiency of near-field holography, near-field ptychography and far-field ptychography, where ptychography involves multiple overlapping finite-sized illumination positions. Unlike what has been reported for coherent diffraction imaging, which involves recording a single far-field diffraction pattern, it is found that all three methods offer similar image quality when using the same fluence on the specimen, with far-field ptychography offering slightly better spatial resolution and a lower mean error. These results support the concept that (if the experiment and image reconstruction are done properly) the sample can be near or far; wherever you are, photon fluence on the specimen sets one limit to spatial resolution.

42 ENGINEERING↗
DOE OSTI2013

Response of TLD-100 in mixed fields of photons and electrons

Purpose: Thermoluminescent dosimeters (TLDs) are routinely used for dosimetric measurements of high energy photon and electron fields. However, TLD response in combined fields of photon and electron beam qualities has not been characterized. This work investigates the response of TLD-100 (LiF:Mg,Ti) to sequential irradiation by high-energy photon and electron beam qualities. Methods: TLDs were irradiated to a known dose by a linear accelerator with a 6 MV photon beam, a 6 MeV electron beam, and a NIST-traceable {sup 60}Co beam. TLDs were also irradiated in a mixed field of the 6 MeV electron beam and the 6 MV photon beam. The average TLD response per unit dose of the TLDs for each linac beam quality was normalized to the average response per unit dose of the TLDs irradiated by the {sup 60}Co beam. Irradiations were performed in water and in a Virtual Water Trade-Mark-Sign phantom. The 6 MV photon beam and 6 MeV electron beam were used to create dose calibration curves relating TLD response to absorbed dose to water, which were applied to the TLDs irradiated in the mixed field. Results: TLD relative response per unit dose in the mixed field was less sensitive than the relative response in the photon field and more sensitive than the relative response in the electron field. Application of the photon dose calibration curve to the TLDs irradiated in a mixed field resulted in an underestimation of the delivered dose, while application of the electron dose calibration curve resulted in an overestimation of the dose. Conclusions: The relative response of TLD-100 in mixed fields fell between the relative response in the photon-only and electron-only fields. TLD-100 dosimetry of mixed fields must account for this intermediate response to minimize the estimation errors associated with calibration factors obtained from a single beam quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2018

Direct binary search for improved coherent beam shaping and optical differentiation wavefront sensing

Spatially dithered distributions of binary amplitude pixels are optimized using a full direct binary search taking into account the experimental configuration for amplitude modulation of coherent waves. This design process is shown to yield a significant reduction of the noise induced by binarization and pixelation over the region of interest. In this study, we demonstrate this approach for beam shaping and optical differentiation wavefront sensing, where the region of interest is in an image plane of the pixel distribution and in the far field of the pixel distribution, respectively. Lastly, the observed reduction in error compared to a standard error diffusion algorithm is significant for both applications because it improves performance without the tighter fabrication tolerance and cost associated with smaller pixels.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Reconstructing Richtmyer–Meshkov instabilities from noisy radiographs using low dimensional features and attention-based neural networks

We develop an ML-based approach for density reconstruction based on transformer neural networks. This approach is demonstrated in the setting of ICF-like double shell hydrodynamic simulations wherein the parameters related to material properties and initial conditions are varied. The new method can robustly recover the complex topologies given by the Richtmyer-Meshkoff instability (RMI) from a sequence of hydrodynamic features derived from radiographic images corrupted with blur, scatter, and noise. A noise model is developed to characterize errors in extracting features from synthetic radiographs of the simulated density field. The key component of the network is a transformer encoder that acts on a sequence of features extracted from noisy radiographs. This encoder includes numerous self-attention layers that act to learn temporal dependencies in the input sequences and increase the expressiveness of the model. This approach is shown to exhibit an excellent ability to accurately recover the RMI growth rates, despite the gas-metal interface being greatly obscured by radiographic noise. Our approach can be applied in a broad array of fields involving shock physics and material science.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Numerical Modelling of the Optical Stochastic Cooling Experiment at IOTA

A proof-of-principle optical-stochastic cooling (OSC) experiment is currently in its commissioning phase at the Fermilab’s IOTA ring. In support of this experiment, we recently implemented an OSC element in the ELEGANT tracking program. The model, based on a semi-analytic description of OSC [*], supports the simulation of a large number of macroparticles (10⁴-10⁶) over many turns (10⁶). This paper showcases the simulation capabilities to investigate the beam dynamics in the presence of cooling (or self-interacting radiation field in general) and quantify the impact of various sources of error (e.g. transverse and phase jitter), guide data analysis.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

The Potential NCS issue process - A method to screen emerging issues

The Potential NCS Issue (PNI) Process is a newly developed methodology that allows for the screening of new information potentially adverse to nuclear criticality safety. The PNI Process allows for transparency of possible emerging issues with both contractor management and on-site regulators. Sources of PNI include the -1) discovery of potential errors, inaccuracy, or omission in an effective criticality safety evaluation, -2) field conditions not accounted for in an effective evaluation, and -3) a potential inadequacy in a supporting calculation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Is flat fielding safe for precision CCD astronomy?

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand precision CCD astronomy as their foundation. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding—that a sensor's pixels comprise a uniform grid—invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat-field images, incorporating the superposition of all electrostatic sensor effects—both known and unknown—present in flat-field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat fielding on these observables is negligible in nominal .7'' seeing conditions. Furthermore, these errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-G-JeP3-02: Comparison of Magnitude and Frequency of Patient Positioning Errors in Breast Irradiation Using AlignRT 3D Optical Surface Imaging and Skin Mark Techniques

Purpose: To evaluate clinical usefulness of AlignRT (Vision RT Ltd., London, UK) in reducing patient positioning errors in breast irradiation. Methods: 60 patients undergoing whole breast irradiation were selected for this study. Patients were treated to the left or right breast lying on Qfix Access breast board (Qfix, Avondale, PA) in supine position for 28 fractions using tangential fields. 30 patients were aligned using AlignRT by aligning a breast surface region of interest (ROI) to the same area from a reference surface image extracted from planning CT. When the patient’s surface image deviated from the reference by more than 3mm on one or more translational and rotational directions, a new reference was acquired using AlignRT in-room cameras. The other 30 patients were aligned to the skin marks with room lasers. On-Board MV portal images of medial field were taken daily and matched to the DRRs. The magnitude and frequency of positioning errors were determined from measured translational shifts. Kolmogorov-Smirnov test was used to evaluate statistical differences of positional accuracy and precision between AlignRT and non-AlignRT patients. Results: The percentage of port images with no shift required was 46.5% and 27.0% in vertical, 49.8% and 25.8% in longitudinal, 47.6% and 28.5% in lateral for AlignRT and non-AlignRT patients, respectively. The percentage of port images requiring more than 3mm shifts was 18.1% and 35.1% in vertical, 28.6% and 50.8% in longitudinal, 11.3% and 24.2% in lateral for AlignRT and non-AlignRT patients, respectively. Kolmogorov-Smirnov test showed that there were significant differences between the frequency distributions of AlignRT and non-AlignRT in vertical, longitudinal, and lateral shifts. Conclusion: As confirmed by port images, AlignRT-assisted patient positioning can significantly reduce the frequency and magnitude of patient setup errors in breast irradiation compared to the use of lasers and skin marks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Directional finite difference method for directly solving 3D gyrokinetic field equations with enhanced accuracy

The gyrokinetic (GK) field equation is a three-dimensional (3D) elliptic equation, but it is often simplified to a set of two-dimensional (2D) equations by assuming that the field does not vary along a specific direction. However, this simplification can introduce inevitable 0th-order numerical errors, as nonlinear mode coupling in toroidal geometry can produce undesirable harmonic modes that violate the assumption. In this work, we propose a novel directional finite difference method (FDM) with a local coordinate transformation to better resolve the target field of interest. The directional FDM can accurately solve 3D GK field equations without simplifications, which can overcome the limitations of conventional methods. The accuracy and efficiency of different FDMs are analyzed in great detail for a variety of geometries, from simple 2D Cartesian coordinates to realistic 3D curvilinear coordinates. The 0th-order numerical errors of simplified 2D GK equations were found to be more problematic for low-harmonic modes and low aspect ratio geometries such as spherical tokamaks. On the other hand, the directional 3D FDM can accurately resolve a much wider range of harmonic modes aligned to the direction of interest, including the low-harmonic modes. In conclusion, we demonstrate that the directional 3D FDM is a highly effective algorithm for solving the 3D GK field equations, achieving accuracy improvements of 10 to 100 times or more, particularly for low-harmonic modes in spherical tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗