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DOE OSTI2024

Overview of RFID Applications Utilizing Neural Networks

As Radio Frequency Identification (RFID) methods continue to evolve to higher levels of complexity, one form of machine learning is making its appearance. The use of Neural Networks (NN) in the RFID field is steadily increasing, and in the fields of localization and activity recognition, promising results are being shown from a variety of research. RFID applications fall primarily under two types of problems including regression and classification. We analyze RIFD localization techniques which fall under regression, and activity recognition which falls under classification. Many works don’t classify themselves as activity recognition methods, but because they fall under the classification category, we still consider them as activity recognition techniques. This research overviews the Neural Network models in the localization field based on whether they can perform independently of the environment in which they were tested. For activity recognition and accessory fields, the major methods involve tag-based and tag-free approaches. In conclusion, after the models are surveyed, a comparison study is given to examine what may be the cause for increased accuracy between different Neural Network models.

42 ENGINEERING↗

DOE OSTI2013

Review of Data from Shock Physics Experiments SPE-1, SPE-2 and SPE-3: Data Corrections and Phenomenology Analysis

The NNSA is conducting a series of high explosive (HE) tests – the Source Physics Experiments – at the National Nuclear Security Site (NNSS). These experiments are intended to investigate the generation of geophysical signals from controlled sources. These signals will aid in the development of physics-based models to aid in the discrimination of signals emitted from these and other possible sources, such as earthquakes and clandestine nuclear events. The SPE events include an array of accelerometers near to the source intended to provide measurements of the strong ground motion, or “near field,” regime. LANL performed an extensive review of the near field measurements from the first two events (SPE-1 and SPE-2) in this series. This review revealed that the near field gauges likely rotated during installation, causing measurement uncertainty. 2 This conclusion led to the installation of new gauges for the third experiment, SPE-3, utilizing new physical design and improved installation practices to achieve better quality control on their orientation. A subsequent analysis of SPE-3 data confirmed that rotations occurred and provided the basis for corrections to those data where the amount of rotation could be credibly determined. The corrected data supports a more confident analysis of the entire near field data set. This report summarizes the data errors and provides results of the analysis of the corrected dataset.

42 ENGINEERING↗

DOE OSTI2020

Ibis Networks/WattIQ (IN2 Final Report)

Ibis Networks is a full-stack cleantech company that provides plug-level energy monitoring and control to solve energy and asset management problems for the enterprise. During DATES – DATES, an NREL research team worked with the Ibis team to validate their product, the InteliSocket. The Ibis InteliSocket is a pass-through plug-load energy monitor and controller that is designed to reduce energy wasted by common 120 V plug-in devices in commercial office buildings, such as computer peripherals, conference room AV equipment, and break-room appliances. The system can shut off supply power to these end uses via remote control, manual switches, pre-set schedules, or automated control algorithms. The scope of this IN2 project was the development and refinement of “smart” learning behavior algorithms (LBAs), which could help installation processes and dramatically expand the sockets’ capabilities and energy-saving potential by suggesting suitable control schedules that are based on monitored use patterns. While Ibis has the analytical and software expertise for algorithm development, the lack of test data, both in a controlled laboratory setting and in real-life deployment scenarios, represented a key barrier toward commercialization of the product. Assistance through the IN2 program provided an opportunity to conduct the needed “trial and error” algorithm development. The project included baseline field-data collection, laboratory testing, and field validation components, all of which were conducted at the NREL campus between April 2017 and July 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Evidence for Universality in the Initial Planetesimal Mass Function

Planetesimals may form from the gravitational collapse of dense particle clumps initiated by the streaming instability. We use simulations of aerodynamically coupled gas–particle mixtures to investigate whether the properties of planetesimals formed in this way depend upon the sizes of the particles that participate in the instability. Based on three high-resolution simulations that span a range of dimensionless stopping times 6×10{sup −3}⩽τ⩽2, no statistically significant differences in the initial planetesimal mass function are found. The mass functions are fit by a power law, dN/dM{sub p}∝M{sub p}{sup −p}, with p = 1.5–1.7 and errors of Δp≈0.1. Comparing the particle density fields prior to collapse, we find that the high-wavenumber power spectra are similarly indistinguishable, though the large-scale geometry of structures induced via the streaming instability is significantly different between all three cases. We interpret the results as evidence for a near-universal slope to the mass function, arising from the small-scale structure of streaming-induced turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans

Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher-frequency radars as well as range–height indicator (RHI) scans. The calibration of weather radars represents one of the most dominant sources of error for their use in a variety of fields including quantitative precipitation estimation and model comparisons. While most weather radars are routinely calibrated, the frequency of calibration is often less than required, resulting in miscalibrated time periods. While full absolute calibration techniques often require the radar to be taken offline for a period of time, there have been online calibration techniques discussed in the literature. The relative calibration adjustment (RCA) technique uses the statistics of the ground clutter surrounding the radar as a monitoring source for the stability of calibration but has only been demonstrated to work at S- and C-band for plan-position indicator (PPI) scans at a constant elevation. In this work the RCA technique is modified to work with higher-frequency radars, including Ka-band cloud radars. At higher frequencies the properties of clutter can be much more variable. This work introduces an extended clutter selection procedure that incorporates the temporal stability of clutter and helps to improve the operational stability of RCA for relatively higher-frequency radars. The technique is also extended to utilize range–height scans from radars where the elevation is varied rather than the azimuth. These types of scans are often utilized with research radars to examine the vertical structure of clouds. The newly extended technique (eRCA) is applied to four Department of Energy Atmospheric Radiation Measurement (DOE ARM) weather radars ranging in frequency from C- to Ka-band. Cross comparisons of three co-located radars with frequencies C, X, and Ka at the ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) site show that the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic (ENA) site, we show how the technique can be modified to be more resilient to clutter fields that show increased variability, in this case due to sea clutter. The results show that this technique is promising for a posteriori data calibration and monitoring.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Robustness of Gauge Digitization to Quantum Noise

Quantum noise limits the use of quantum memory in high energy physics simulations. In particular, it breaks the gauge symmetry of stored quantum states. We examine this effect for abelian and nonabelian theories and demonstrate that optimizing the digitization of gauge theories to quantum memory to account for noise channels can extend the lifetime before complete loss of gauge symmetry by $2-10\times$ over some other digitizations. These constructions also allow for quantum error correction to integrate the symmetries of quantum fields and prioritize the largest gauge violations.

Gustafson, Erik J.↗

DOE OSTI2016

Protected gates for topological quantum field theories

We study restrictions on locality-preserving unitary logical gates for topological quantum codes in two spatial dimensions. A locality-preserving operation is one which maps local operators to local operators — for example, a constant-depth quantum circuit of geometrically local gates, or evolution for a constant time governed by a geometrically local bounded-strength Hamiltonian. Locality-preserving logical gates of topological codes are intrinsically fault tolerant because spatially localized errors remain localized, and hence sufficiently dilute errors remain correctable. By invoking general properties of two-dimensional topological field theories, we find that the locality-preserving logical gates are severely limited for codes which admit non-abelian anyons, in particular, there are no locality-preserving logical gates on the torus or the sphere with M punctures if the braiding of anyons is computationally universal. Furthermore, for Ising anyons on the M-punctured sphere, locality-preserving gates must be elements of the logical Pauli group. We derive these results by relating logical gates of a topological code to automorphisms of the Verlinde algebra of the corresponding anyon model, and by requiring the logical gates to be compatible with basis changes in the logical Hilbert space arising from local F-moves and the mapping class group.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Understanding Atom Probe Tomography of Oxide-Supported Metal Nanoparticles by Correlation with Atomic Resolution Electron Microscopy and Field Evaporation Simulation

Metal-dielectric composite materials, specifically metal nanoparticles supported on or embedded in metal oxides, are widely used in catalysis. The accurate optimization of such nanostructures warrants the need for detailed three-dimensional characterization. Atom probe tomography is uniquely capable of generating sub-nanometer structural and compositional data with part-per-million mass sensitivity, but there are reconstruction artifacts for composites containing materials with strongly differing fields of evaporation, as for oxide-supported metal nanoparticles. By correlating atom probe tomography with scanning transmission electron microscopy for Au nanoparticles embedded in an MgO support, deviations from an ideal topography during evaporation are demonstrated directly, and correlated with compositional errors in the reconstructed data. Finite element simulations of the field evaporation process confirm that protruding Au nanoparticles will evolve on the tip surface, and that evaporation field variations lead to an inaccurate assessment of the local composition, effectively lowering the spatial resolution of the final reconstructed dataset. Cross-correlating the experimental data with simulations results in a more detailed understanding of local evaporation aberrations during APT analysis of metal-oxide composites, paving the way towards a more accurate three-dimensional characterization of this technologically important class of materials.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2025

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that it produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification in atomistic force fields and is a promising method that should be further explored in other domains of machine learning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

SU-E-T-630: Commissioning for SRS Planning Systems

Purpose: This study will try to find optimal procedures to collect small fields beam data for commissioning in treatment planning systems (TPS), and to provide a protocol to collect output factors for very small field sizes: 0.5 cm × 0.5 cm to 4.0 cm × 4.0 cm.This will help in determining the correct beam configuration methods in TPS planning intensity modulated radiation therapy (IMRT), and stereotactic radiosurgery SRS using mini multileaf collimation (mMLC). Methods: Data has been collected for a mMLC linear accelerator (linac) Novalis from 0.5 cm × 0.5 cm to 10 cm × 10 cm (its maximum field size). The TPS chosen is BrainLab, Eclipse and Cyberknife. The beam data collected was modeled and imported in the TPS. Verification plans were generated in solid water to confirm the goodness of the data. 3D and IMRT plans on regular CT scans were generated and verified using Mapcheck. All 3D plans with field sizes above 4 cm × 4 cm verified excellent using a distance to agreement of 2 mm and a 2% tolerance. IMRT plans gave an error of -8%. New scans with new detectors have been taken, new field sizes were introduced, and focus has been applied on determining the dosimetric leaf gap. Results: Although this is still a work in progress, this study brings several issues to light: the importance of the correct technique in beam data collection from the correct watertank to the correct detectors. Readings for rectangular fields have to be taken especially for fields which one side is under 4 cm. Conclusion: The use of equivalent square fields will not provide correct readings for the fields with large differences between the length and the width.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Effective field theory approach to heavy quark fragmentation

Using an approach based on Soft Collinear Effective Theory (SCET) and Heavy Quark Effective Theory (HQET) we determine the b-quark fragmentation function from electron-positron annihilation data at the Z-boson peak at next-to-next-to leading order with next-to-next-to leading log resummation of DGLAP logarithms, and next-to-next-to-next-to leading log resummation of endpoint logarithms. This analysis improves, by one order, the previous extraction of the b-quark fragmentation function. We find that while the addition of the next order in the calculation does not much shift the extracted form of the fragmentation function, it does reduce theoretical errors indicating that the expansion is converging. Using an approach based on effective field theory allows us to systematically control theoretical errors. Furthermore, while the fits of theory to data are generally good, the fits seem to be hinting that higher order correction from HQET may be needed to explain the b-quark fragmentation function at smaller values of momentum fraction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗

DOE OSTI2023

An Interactive Spectral Analysis Tool for Chemical Identification and Quantification of Gas-Phase Species in Complex Spectra

A spectral analysis tool has been developed to interactively identify and quantify individual gas-phase species from complex infrared absorbance spectra obtained from laboratory or field data. The SpecQuant program has an intuitive graphical interface that accommodates both reference and experimental data with varying resolution and instrumental lineshape, as well as algorithms to readily align the wavenumber axis of a sample spectrum with the raster of a reference spectrum. Using a classical least squares model in conjunction with reference spectra such as those from the Pacific Northwest National Laboratory (PNNL) gas-phase infrared database or simulated spectra derived from the HITRAN line-by-line database, the mixing ratio of each identified species is determined along with its associated estimation error. After correcting the wavelength and intensity of the field data, SpecQuant displays the calculated mixing ratio versus the experimental data for each analyte along with the residual spectrum with any or all analyte fits subtracted for visual inspection of the fit and residuals. The software performance for multianalyte quantification was demonstrated using moderate resolution (0.5 cm –1 ) infrared spectra that were collected during the time-resolved infrared photolysis of methyl iodide.

Thompson, Christopher J.↗

DOE OSTI2021

Transport coefficients for magnetic-field evolution in inviscid magnetohydrodynamics

The magnetized resistivity and electrothermal tensors when substituted into the induction equation lead to electrothermal magnetic field generation, resistive magnetic diffusion, and magnetic field advection due to resistivity gradients, temperature gradients and currents. Here, the advection terms driven by temperature gradient and current have cross-field components (perpendicular to both the magnetic field and the driving term) that depend on significantly modified versions of Braginskii’s transport coefficients. The improved fits to Braginskii’s coefficients given by Epperlein and Haines and Ji and Held give physically incorrect results for cross-field advection at small Hall parameters (product of cyclotron frequency and collision time). The errors in Epperlein and Haines’ fits are particularly severe, giving increasing advection velocities below a Hall parameter of one when they should decrease linearly to zero. Epperlein and Haines’ fits can also give erroneous advection terms due to variations in effective atomic number. The only serious error in Braginskii’s fits is an overestimate in advection due to perpendicular resistivity. New fits for the cross-field advection terms are obtained from a direct numerical solution of the Fokker-Planck equation and Ji and Held’s higher order expansion approach that are continuous functions of the effective atomic number.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

SU-F-BRF-04: Evaluation of Five Commercially-Available Algorithms for Deformable Image Registration

Purpose: Deformable image registration (DIR) is increasingly being used in various clinical applications. Although there are several DIR packages all making successful attempts at modeling complex anatomical changes using even more complex mathematical approximations, they are all subject to various uncertainties. Many studies have attempted to quantify the spatial uncertainty with DIR. This is the first study to compare the uncertainty for interfraction DIR for 5 different commercially-available algorithms. The aim of this study was to benchmark the performance of the most commonlyused DIR algorithms offered through these 5 software packages: Eclipse, MIM, Pinnacle, RaySearch, and Velocity. Methods: A set of 10 virtual H'N phantoms [Pukala et al. MedPhys. 40(11) 2013] with known deformations were used to determine the spatial errors that might be seen when performing DIR. The “ground-truth” deformation vector field (DVF) was compared to the DVF output of the 5 commercially-available algorithms in order to evaluate spatial errors for six regions of interest (ROIs): brainstem, cord, mandible, left parotid, right parotid, and the external body contour. Results: We found that each software package had varying uncertainties with the various ROIs, but were generally all comparable to one another – with mean spatial errors for each algorithm below 3.5 mm for each ROI (averaged across all phantoms). We also found that no single algorithm was the clear winner over the other 4 algorithms. However, at times, we found huge maximum errors in our results (e.g. phantom #9 maximum errors: right parotid = 22.9 mm, external contour = 30.5mm) with the varying DIR algorithms. Conclusion: Although our evaluation was limited to H'N patients, we show that our methods are a single-assessment analysis tool that could be used by any physicist, within any type of facility, to compare their DIR software before initiating widespread use within their daily radiotherapy practice.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-73: A Robust Proton Beam Therapy Technique for High-Risk Prostate Cancer Whole Pelvis Irradiation: Bilateral Opposed Single Field Uniform Dose (SFUD) Plan with Lateral Penumbra Gradient Matching

Purpose: To develop a clinical feasible and robust proton therapy technique to spare bowel, bladder and rectum for high-risk prostate cancer patients Methods: The study includes 3 high-risk prostate cancer cases treated with bilateral opposed SFUD with lateral penumbra gradient matching technique prescribed to 5400cGyE in 30 fx in our institution. To treat whole pelvic lymph node chain, the complicated ‘H’ shape, using SFUD technique, we divided the target into two sub-targets (LLAT beam treating ‘90 degree T-shape’ and RLAT beam treating ‘: shape’) in Plan A and use lateral penumbra gradient matching at patient’s left side. Vice verse in Plan B. Each plan deliver half of the prescription dose. Beam-specific PTVs were created to take range uncertainty and setup error into account. For daily treatment, patient received four fields from both plan A and B per day. Robustness evaluation were performed in the worst case scenario with 3.5% range uncertainty and 1, 2, 3mm overlap or gap between LLAT and RLAT field matching in Raystation 4.0. All of cases also have a Tomotherapy backup plan approved by physician as a dosimetric comparison. Results: The total treatment time take 15–20mins including IGRT and four fields delivery on ProteusONE, a compact size PBS proton system, compared to 25–30min in traditional Tomotherapy. Robustness analysis shows that this plan technique is insensitive to the range uncertainties. With the lateral gradient matching, 1, 2, 3mm overlap renders only 2.5%, 5.5% and 8% hot or cool spot in the junction areas. Dosimetric comparisons with Tomotherapy show a significant dose reduction in bladder D50%(14.7±9.3Gy), D35%(7.3±5.8Gy); small bowel and rectum average dose(19.6±7.5Gy and 14.5±6.3Gy respectively). Conclusion: The bilateral opposed(SFUD) plan with lateral penumbra gradient matching has been approved to be a safe, robust and efficient treatment option for whole pelvis high-risk prostate cancer patient which significantly spares the OARs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A Fast Algebraic Multigrid Solver and Accurate Discretization for Highly Anisotropic Heat Flux I: Open Field Lines

We present a novel solver technique for the anisotropic heat flux equation, aimed at the high level of anisotropy seen in magnetic confinement fusion plasmas. Such problems pose two major challenges: (i) discretization accuracy and (ii) efficient implicit linear solvers. We simultaneously address each of these challenges by constructing a new finite element discretization with excellent accuracy properties, tailored to a novel solver approach based on algebraic multigrid (AMG) methods designed for advective operators. We pose the problem in a mixed formulation, introducing the directional temperature gradient as an auxiliary variable. The temperature and auxiliary fields are discretized in a scalar discontinuous Galerkin space with upwinding principles used for discretizations of advection. We demonstrate the proposed discretization’s superior accuracy over other discretizations of anisotropic heat flux, achieving error 1000x smaller for anisotropy ratio of 10 9 , for closed field lines. The block matrix system is reordered and solved in an approach where the two advection operators are inverted using AMG solvers based on approximate ideal restriction, which is particularly efficient for upwind discontinuous Galerkin discretizations of advection. To ensure that the advection operators are nonsingular, in this paper we restrict ourselves to considering open (acyclic) magnetic field lines for the linear solvers. We demonstrate fast convergence of the proposed iterative solver in highly anisotropic regimes where other diffusion-based AMG methods fail.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Mean Field Games for Stochastic Growth with Relative Utility

This paper considers continuous time stochastic growth-consumption optimization in a mean field game setting. The individual capital stock evolution is determined by a Cobb–Douglas production function, consumption and stochastic depreciation. The individual utility functional combines an own utility and a relative utility with respect to the population. The use of the relative utility reflects human psychology, leading to a natural pattern of mean field interaction. The fixed point equation of the mean field game is derived with the aid of some ordinary differential equations. Due to the relative utility interaction, our performance analysis depends on some ratio based approximation error estimate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗