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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiplexed profiling of transcriptional regulators in plant cells

Transcriptional regulators play key roles in plant growth, development and environmental responses; however, understanding how their regulatory activity is encoded at the protein level has been hindered by a lack of multiplexed large-scale methods to characterize protein libraries in planta. Here we present enrichment of nuclear trans-elements reporter assay in plants with sequencing (ENTRAP-seq), a high-throughput method that introduces protein-coding libraries into plant cells to drive a nuclear magnetic sorting-based reporter, enabling multiplexed measurement of regulatory activity from thousands of protein variants. Using ENTRAP-seq and machine learning, we screen 1,495 plant viruses and identify hundreds of putative transcriptional regulatory domains found in structural proteins and enzymes not associated with gene regulation. In addition, we combine ENTRAP-seq with machine-guided design to engineer the activity of a plant transcription factor in a semirational fashion. Our findings demonstrate how scalable protein function assays deployed in planta will enable the characterization of natural and synthetic coding diversity in plants.

Alamos, Simon↗
DOE OSTI2022

Interpreting ion-energy distributions using charge exchange emitted from deeply kinetic field-reversed-configuration plasmas

Energy resolving the atomic hydrogen outflux created within plasmas by charge exchange (CX) of hot plasma ions with cooler hydrogen neutrals is used to infer the ion energy distribution within the plasma, IED p . In high- β plasma with field nulls and ion gyro-radii comparable to the plasma size, the measured ion energy distribution (IED m ) of the CX outflux will depend on the viewing angle and position of the detector. Here, we describe the physics for this, results from a synthetic diagnostic code that contrasts the IED m to the IED p within relatively small and hot field-reversed-configuration plasmas, and how these data can show the presence of magnetic nulls and different orbit classes in the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

tonalli : an asexual genetic code to characterize APOGEE-2 stellar spectra. I. Validation with synthetic and solar spectra

ABSTRACT We present tonalli, a spectroscopic analysis python code that efficiently predicts effective temperature, stellar surface gravity, metallicity, $\alpha$-element abundance, and rotational and radial velocities for stars with effective temperatures between 3200 and 6250 K, observed with the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2). tonalli implements an asexual genetic algorithm to optimize the finding of the best comparison between a target spectrum and the continuum-normalized synthetic spectra library from the Model Atmospheres with a Radiative and Convective Scheme (MARCS), which is interpolated in each generation. Using simulated observed spectra and the APOGEE-2 solar spectrum of Vesta, we study the performance, limitations, accuracy, and precision of our tool. Finally, a Monte Carlo realization was implemented to estimate the uncertainties of each derived stellar parameter.

Adame, Lucía (ORCID:0000000263286099)↗
DOE OSTI2024

Adversarial Robustness Limits

This is the official code for the ICML 2024 paper "Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies". This code extends that of Wang et al. (2023) to facilitate state-of-the-art CIFAR-10 adversarial robustness, via training of WideResNet models on various large synthetic datasets. The code also facilitates derivation of the various scaling laws put forth in our ICML paper, which we use to compute efficient training settings.

Bartoldson, BrianR↗
DOE OSTI2020

Development of a tomographic reconstruction method for axisymmetric D α emission profiles in the ITER plasma boundary

A tomographic method for reconstructing the axially symmetric D α emission profile in the ITER scrape-off layer and divertor from D α intensity measurements in the fields of view (FoV) of Vis/IR TV and Divertor Impurity Monitor diagnostics is under development. The method takes into account the strong background signal due to stray light from divertor produced by reflections from the metal wall of the vacuum chamber. The method allows to filter out the reflections in D α signals measured in the main chamber. Here, the accuracy of this method is tested within the framework of a synthetic diagnostic, which uses the Raysect and Cherab numerical codes for ray-tracing simulations. The D α emission profiles, simulated with the SOLPS and OEDGE codes, are used as synthetic experimental data. Uncertainty in light reflection properties of the first wall (FW) is the major factor affecting the accuracy of the D α emission reconstruction. The dependence on the uncertainty in the FW surface roughness and on the ratio of diffusive to specular reflection of the error in recovering useful D α signals (the direct light without reflections) in the FoV of the ITER main chamber H-alpha and Visible Spectroscopy Diagnostic is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

SplitML

SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.

Klein, Natalie↗
DOE OSTI2023

Validating the simulation of beam-ion charge exchange in MAST Upgrade

Abstract Simulation of the impact of charge-exchange (CX) reactions on beam ions in the Mega Amp Spherical Tokamak (MAST) Upgrade was compared to measurements carried out with a fission chamber (neutron fluxes) and a fast ion deuterium-alpha (FIDA) diagnostic. A simple model was developed to reconstruct the outer-midplane neutral density based on measurements of deuterium-alpha emission from edge neutrals, and on Thomson scattering measurements of electron density and temperature. The main computational tools used were the ASCOT orbit-following code and the FIDASIM code for producing synthetic FIDA signals. The neutral density reconstruction agrees qualitatively with SOLPS-ITER modelling and yields a synthetic passive FIDA signal that is consistent with measurement. When CX losses of beam ions are accounted for, predicted neutron emission rates are quantitatively more consistent with measurement. It was necessary to account for CX losses of beam ions in simulations to reproduce the measured passive FIDA signal quantitatively and qualitatively. The results suggest that the neutral density reconstruction is a good approximation, that CX with edge neutrals causes significant beam-ion losses in MAST Upgrade, typically 20% of beam power, and that the ASCOT fast-ion CX model can be used to accurately predict the redistribution and loss of beam ions due to CX.

Physics↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
DOE OSTI2023

Monte Carlo Radiation Transport for Astrophysical Transients Powered by Circumstellar Interaction

In this paper, we introduce SuperLite, an open-source Monte Carlo radiation transport code designed to produce synthetic spectra for astrophysical transient phenomena affected by circumstellar interaction. SuperLite utilizes Monte Carlo methods for semi-implicit, semirelativistic radiation transport in high-velocity shocked outflows, employing multigroup structured opacity calculations. The code enables rapid post-processing of hydrodynamic profiles to generate high-quality spectra that can be compared with observations of transient events, including superluminous supernovae, pulsational pair-instability supernovae, and other peculiar transients. We present the methods employed in SuperLite and compare the code's performance to that of other radiative transport codes, such as SuperNu and CMFGEN. We show that SuperLite has successfully passed standard Monte Carlo radiation transport tests and can reproduce spectra of typical supernovae of Type Ia, Type IIP, and Type IIn.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Details of the neutral energy distribution and ionization source using spectrally resolved Balmer-alpha measurements on DIII-D

Spectrally resolved passive Balmer- α (D- α, H- α) measurements from the DIII-D 16 channel edge main-ion charge exchange recombination system confirm the presence of higher energy neutrals (“thermal” neutrals) in addition to the cold neutrals that recycle off the walls in the edge region of DIII-D plasmas. Charge exchange between thermal ions and edge neutrals transfers energy and momentum between the populations giving rise to thermal neutrals with energies approximating the ions in the pedestal region. Multiple charge exchange events in succession allow an electron to effectively take a random walk, transferring from ion to ion, providing a pathway of increasing energy and velocity, permitting a neutral to get deeper into the plasma before a final ionization event that contributes to the ion and electron particle fueling. Spectrally resolved measurements provide information about the density and velocity distribution of these neutrals, which has been historically valuable for validating Monte Carlo neutral models, which include the multi stage charge exchange dynamics. Here, in this study, a multi-channel set of such measurements is used to specifically isolate the details of the thermal neutrals that are responsible for fueling inside the pedestal top. Being able to separate the thermal from the cold emission overcomes several challenges associated with optical filter-based neutral density measurements. The neutral dynamics, deeper fueling by the thermal neutrals, and spectral measurement are modeled with the FIDASIM Monte Carlo collisional radiative code, which also produces synthetic spectra with a shape that is in close agreement with the measurements. By scaling the number of neutrals in the simulation to match the intensity of the thermal emission, we show it is possible to obtain local neutral densities and ionization source rates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

RGM: Random Geological Model Generation Package

This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. This Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM – Random Geological Model generation package.

Gao, Kai↗
DOE OSTI2022

Simulating energetic particle losses in JET plasmas with a reverse integration biasing scheme

We report that an integrated energetic particle transport model has been constructed in JET plasmas constrained by experimental fast ion loss measurements. The model incorporates a synthetic fast ion loss detector identical to JET’s thin-foil Faraday cup fast ion loss detector array. The loss model combines analyses from the TRANSP and ORBIT-kick codes with enhanced features for producing the synthetic diagnostic. Extensions to the ORBIT code framework allow a full-orbit representation within the vacuum region that can map particles directly to an installed detector geometry. Since synthetic fast ion loss detectors are plagued by weak loss statistics, a novel reverse integration biasing scheme has been implemented to boost computational efficiency. The model is validated against experimental loss measurements induced by long-lived kink modes and is found to be in good agreement. This confirms the development of a fully integrated transport/loss model which can be quantitatively verified against experiment allowing for future validation and predictive studies. The model is particularly useful for more complicated plasma scenarios that involve multiple fast ion species such as JET’s 2021 DT-campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Code for BALDR Study 07.05 v.1.0.0

SAND2024-01293O The Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning "A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra." The code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Morrow, Tyler↗
DOE OSTI2022

Production of CO2-Negative Building Composites Development

This project will investigate and utilize the basicity and enhanced reactivity of CO2 chemically captured in PNNL’s CO2BOLs carbon capture solvents to perform the first direct carboxylation of the aromatic rings (substituted phenols) in lignin and lignite. This project aims to develop a deep decarbonization approach that can sequester millions of tonnes of CO2 annually by reacting with two large-volume products, lignin, and lignite, to enable their use as composite fillers. The goal is to demonstrate that CO2-containing composites have comparable properties to conventional synthetic materials, meeting international building codes (IBC) while being able to sequester millions of tonnes of CO2 per year.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Development of a scintillator based fast-ion loss detector for the Wendelstein 7-X stellarator

A new scintillator based fast-ion loss detector (FILD) system has been designed for the Wendelstein 7-X (W7-X) stellarator. The mechanical design of the system is presented here along with engineering analyses of the system. This includes an assessment of the structural loads which also considers electromagnetic forces calculated for possible disruption scenarios as well as a mode frequency analysis of the system. Furthermore, an analysis of the thermal characteristics of the actively cooled probe head under prescribed steady state and transient heat loads is presented. Finally, the optical relay system is described and its properties used to forward model synthetic camera signals using the FILDSIM code and based on theoretical fast-ion losses incident on the probe head calculated using the ASCOT5 code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗