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At least 1,783 records · Page 99

Upgrading Limiting Peak-Power Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor

Here, this work demonstrates the acceptability of the 2D deterministic transport code, HELIOS, to replace the legacy diffusion code, PDQ, for computing the peak-power performance parameters of the Advanced Test Reactor (ATR). The 95% Confidence Rule, commonly used in the commercial reactor sector, is explored to develop the so-called “reliability factors” which provide statistical confidence that the peak-power limits within the hottest location along a fuel plate, referred to as the hot-stripe, will not be exceeded. Additionally, an alternative “legacy” methodology was explored that attempts to mimic the exact PDQ analysis process used for defining the peak-power limits. The legacy methodology, involves interpolating power between regions at azimuthal boundaries subtending the regions of interest. In order to apply the 95% Confidence Rule, a statistically significant calculation-to-measurement bias must first be established. Unlike the commercial world where thousands of power observations can be collected every cycle using on-line flux mapping instrumentation, the ATR power distribution must be measured during “depressurized” zero-power measurements using fission wires in polyethylene wands. In 2012, fission wire activation data was collected during a flux run in the Advanced Test Reactor – Critical facility. Also to improve statistical validity, archival data from ATR zero power flux runs from 1977, 1986, and 1994 were digitized from scanned reports and used to create new benchmark models. Borrowing from least-squares adjustment methods commonly used for neutron activation spectroscopy, adjusted fission wire powers were calculated for all four datasets. The mean and standard deviation of the bias between a priori calculated and adjusted wire-powers was then taken as the bias and uncertainty used in the 95% Confidence Rule.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

TU-A-9A-11: Gold Nanoparticles Enhanced Diffuse Optical Tomography: A Proof of Concept Study

Purpose: To investigate the feasibility and potential of gold nanoparticles (GNP) enhanced diffuse optical tomography (DOT) as a novel imaging strategy for tumor detection. Methods: Simulation was performed on a digital homogeneous cylindrical phantom of 30mm×30mm. Gold nanorods (GNR) with aspect ratio 3.9 and effective radius 21.86nm were used as contrast agent. The peak light absorption for these GNR occurs at 842nm within the near-infrared region, with the absorption cross-section of 1.97×10{sup -14}m{sup -2} and scatter cross-section of 1.07×10{sup -14}m{sup -2}. A 6mmdiameter sphere of GNR solution was positioned inside the tissue-simulating phantom. Simulations were performed at the GNR concentration level of 1nM, 100pM and 10pM, respectively. The points representing laser sources and light detectors were around the phantom with 30o apart tangentially and 1mm apart axially for 9 rows. As one point being source, all the other points within the current row and nearby four rows become detectors. Hence there are 108 source points in total and 55 detector points corresponding to each source. Forward light transport at 842nm wavelength was run on a three-dimensional mesh of 33186 nodes (∼0.5mm resolution) to acquire the light emission data. Reconstruction was performed on a coarse mesh of 19408 nodes (∼1mm resolution) with ∼20minutes on a 2.4GHz CPU and 8GB RAM computer. Results: The position of the GNR solution at 1nM, 100pM and 10pM concentration was reconstructed, respectively, with <1mm error. The GNR concentration was interpreted from the reconstructed absorption coefficient within the enhanced volume. The reconstructed maximum concentrations were 0.3nM, 120.0pM, and 5.3pM, respectively. Conclusion: To the best of our knowledge, this is the first time to apply GNP to enhance DOT. The simulation results showed the high sensitivity of GNP enhanced DOT, which is in pM concentration level, compared to the μM level for MRI agents and nM level for PET agents.

60 APPLIED LIFE SCIENCES↗

Deployment of Digital Twins and Advanced Instrumentation to Identify Looseness Between Rotor Spider Arms and Rim Attachment in Hydro Turbines

The project aimed to develop a Virtual Sensor Digital Twin (VS-DT) to monitor rotor rim float displacement (RRFD) in legacy hydropower turbines. RRFD, if undetected, can cause rotor and stator damage, leading to costly repairs and safety concerns. The purpose of the VS-DT was to predict RRFD signals using existing conventional sensors instead of installing dedicated, costly physical sensors, thereby reducing operational costs and enhancing safety.

13 HYDRO ENERGY↗

Quantum simulations of hadron dynamics in the Schwinger model using 112 qubits

Hadron wave packets are prepared and time evolved in the Schwinger model using 112 qubits of IBM’s 133-qubit Heron quantum computer ibm_torino. The initialization of the hadron wave packet is performed in two steps. First, the vacuum is prepared across the whole lattice using the recently developed SC-ADAPT-VQE algorithm and workflow. SC-ADAPT-VQE is then extended to the preparation of localized states, and used to establish a hadron wave packet on top of the vacuum. This is done by adaptively constructing low-depth circuits that maximize the overlap with an adiabatically prepared hadron wave packet. Due to the localized nature of the wavepacket, these circuits can be determined on a sequence of small lattices using classical computers, and then robustly scaled to prepare wave packets on large lattices for simulations using quantum computers. Time evolution is implemented with a second-order Trotterization. To reduce both the required qubit connectivity and circuit depth, an approximate quasilocal interaction is introduced. This approximation is made possible by the emergence of confinement at long distances, and converges exponentially with increasing distance of the interactions. Using multiple error-mitigation strategies, up to 14 Trotter steps of time evolution are performed, employing 13,858 two-qubit gates (with a CNOT depth of 370). The propagation of hadrons is clearly identified, with results that compare favorably with Matrix Product State simulations. Finally, prospects for a near-term quantum advantage in simulations of hadron scattering are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

PCAST: Report to the President on Strategy for Cyber-Physical Resilience: Fortifying Our Critical Infrastructure for a Digital World

The President’s Council of Advisors on Science and Technology (PCAST) is the sole body of advisors from outside the federal government charged with making science, technology, and innovation policy recommendations to the President and the White House. Established by Executive Order, it is an independent Federal Advisory Committee comprised of distinguished individuals from industry, academia, and non-profit organizations with a range of perspectives and expertise. On February 27, 2024, PCAST sent a report to the President with recommendations to bolster the resilience and adaptability of the nation’s cyber-physical infrastructure resources.

42 ENGINEERING↗

Remote sensing and geophysical characterization of a floodplain-hillslope system in the East River watershed, Colorado

This package is part of the Watershed Function SFA Data Collection and contains remote sensing data and geophysical measurements acquired at the Pumphouse hillslope-floodplain site, in the East River, Colorado. The remote sensing dataset includes: a) a WorldView-2 (WV-2) pan-sharpened multi-spectral remote sensing image, and b) LiDAR derived products. The WV-2 image was acquired on September 24th, 2015, and it is composed of eight spectral bands (coastal, blue, green, yellow, red, red edge, NIR1, and NIR2) with a spatial resolution of 0.5 m, covering an area of 750x750 m. The LiDAR products are a digital surface model (DSM), representing the top-of-canopy elevation, and a digital terrain model (DTM), representing the bare-ground elevation, at the spatial resolution of 0.5 m. Such data are extracted from the LiDAR point-cloud dataset acquired over the entire watershed on August 2015 (http://dx.doi.org/10.21952/WTR/1412542). The geophysical dataset is composed of the electrical resistivity tomography (ERT) data acquired along a 158.75 m long transect, spanning the hillslope topographical gradient with 1.25 m electrode spacing. The dataset also includes soil water content measured with a TDR system. The package provides also polygons of different vegetation communities, which were used as reference data for mapping plant community distributions. The spatial polygons are based on plant locations acquired during the field campaign of June-July 2017 using an RTK DGPS system. The reference dataset is composed by 11 vegetation classes, namely, deciduous forest, evergreen forest, riparian shrubland, sagebrush, shrubland, potentilla, frasera, lupine meadow, veratrum, bunchgrass meadow, and forb, as well as four non-vegetation classes, such as water-river, water-lake, man-made, bare area, and shadow. The vegetation classes are determined based on distinct spectral and/or structural signatures of dominant species. The package includes products derived by these datasets, such as: a) a plant height map, computed by subtracting the DTM from the DSM, and b) a plant community distribution map, obtained by using a data-fusion machine-learning-based framework that exploit the WV-2 image and plant height information.

54 ENVIRONMENTAL SCIENCES↗

SU-C-201-01: Investigation of the Effects of Scintillator Surface Treatment On Light Output Measurements with SiPM Detectors

Purpose: To examine the effect of different scintillator surface treatments (BGO crystals) on the fraction of scintillation photons that exit the crystal and reach the photodetector (SiPM). Methods: Positron Emission Tomography is based on the detection of light that exits scintillator crystals, after annihilation photons deposit energy inside these crystals. A considerable fraction of the scintillation light gets trapped or absorbed after going through multiple internal reflections on the interfaces surrounding the crystals. BGO scintillator crystals generate considerably less scintillation light than crystals made of LSO and its variants. Therefore, it is crucial that the small amount of light produced by BGO exits towards the light detector. The surface treatment of scintillator crystals is among the factors affecting the ability of scintillation light to reach the detectors. In this study, we analyze the effect of different crystal surface treatments on the fraction of scintillation light that is detected by the solid state photodetector (SiPM), once energy is deposited inside a BGO crystal. Simulations were performed by a Monte Carlo based software named GATE, and validated by measurements from individual BGO crystals coupled to Philips digital-SiPM sensor (DPC-3200). Results: The results showed an increment in light collection of about 4 percent when only the exit face of the BGO crystal, is unpolished; compared to when all the faces are polished. However, leaving several faces unpolished caused a reduction of at least 10 percent of light output when the interaction occurs as far from the exit face of the crystal as possible compared to when it occurs very close to the exit face. Conclusion: This work demonstrates the advantages on light collection from leaving unpolished the exit face of BGO crystals. The configuration with best light output will be used to obtain flood images from BGO crystal arrays coupled to SiPM sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

In situ tumor model for longitudinal in silico imaging trials

Abstract Objective.In this article, we introduce a computational model for simulating the growth of breast cancer lesions accounting for the stiffness of surrounding anatomical structures.Approach.In our model, ligaments are classified as the most rigid structures while the softer parts of the breast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidly proliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumvent stiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines of the breast’s soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elastic constants of the tissues surrounding the tumor, this model thus creates the potential for realizing a database of unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure. We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed by Graffet alwith a resolution of 50μm generated with the open-source and readily available Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) imaging pipeline. To visualize and validate the realism of the lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the siemens mammomat inspiration mammography system in a digital format. This system was instrumental in generating digital mammogram (DM) images for each breast model containing the simulated lesions.Results.By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of the lesions as they integrated with the anatomical backgrounds. Our research also involved a reader study that compared 25 simulated DM regions of interest (ROIs) with inserted lesions from our models with DM ROIs from the DDSM dataset containing real manifestations of breast cancer. In general the simulation time for the lesions was approximately 2.5 hours, but it varied depending on the lesion’s local environment.Significance.The lesion growth model will facilitate and enhance longitudinal in silico trials investigating the progression of breast cancer.

Engineering↗

A Generalized Stress Inversion Approach With Application to Residual Stress Estimation

In this work develop a generalized stress inversion technique (or the generalized inversion method) capable of recovering stresses in linear elastic bodies subjected to arbitrary cuts. Specifically, given a set of displacement measurements found experimentally from digital image correlation (DIC), we formulate a stress estimation inverse problem as a partial differential equation-constrained optimization problem. We use gradient-based optimization methods, and we accordingly derive the necessary gradient and Hessian information in a matrix-free form to allow for parallel, large-scale operations. By using a combination of finite elements, DIC, and a matrix-free optimization framework, the generalized inversion method can be used on any arbitrary geometry, provided that the DIC camera can view a sufficient part of the surface. We present numerical simulations and experiments, and we demonstrate that the generalized inversion method can be applied to estimate residual stress.

42 ENGINEERING↗

Polar Format Algorithm: Survey of Assumptions and Approximations

Since the Polar Format Algorithm (PFA) was first introduced by Jack Walker 30 years ago, digital processing and Moore’s law have provided the means by which to process an increasing amount of data, at finer resolutions, over a larger area, and in real-time. Inherent in the polar format algorithm are assumptions that limit the focused scene size. This report presents a development of PFA for a linear frequency modulated chirp pulsed radar utilizing stretch processing to illustrate how PFA approximations are used to form an image. Also techniques to mitigate the errors resulting from the approximations are presented from a survey of literature sources. There are many techniques that are successful at increasing the focused scene size, these include image corrections made after image formation, subaperture processing, and careful selection of processing coordinates. This report only considers methods that use the polar format algorithm.

97 MATHEMATICS AND COMPUTING↗

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business units have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.

36 MATERIALS SCIENCE↗

A Cybersecurity Event Simulation Tool and Platform

Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and application of FPGA-based logic controller - 357

The control systems of nuclear power plants contain many components which are becoming obsolete at an increasing rate. Nowadays maintenance for analog-based protection systems may be difficult as analog parts become obsolete or hard to obtain. Various studies have been conducted to address this control system hardware obsolescence issue. Those control systems of nuclear power plants have been replaced with modern digital control systems such as the programmable logic controller (PLC) and the distributed control system (DCS). The central processing unit (CPU)- based platforms such as the PLC and the DCS require an operating system (OS) and application software, and thus they might result in a common-cause failure when a problem occurs in the operating system or application software. The field programmable gate array (FPGA) is highlighted as an alternative to the conventional protection or control systems. This paper presents the development of an FPGA-based logic controller (FLC) and a diverse protection system (DPS) with the FLC platform. Protection functions for the DPS were implemented in FPGAs without any CPU or OS. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Solutions for Digital Video Transmission Technology Final Report CRADA No. TC02068.0

This Project aimed at development of software for seismic data processing based on the Geotool code developed by the American company Multimax., Inc. The Geotool code was written in early 90-es for the UNIX platform. Under Project# 2821, functions of the old Geotool code were transferred into a commercial version for the Microsoft XP and Vista platform with addition of new capabilities on visualization and data processing. The developed new version of the Geotool+ was implemented using the up-to-date tool Microsoft Visual Studio 2005 and uses capabilities of the .NET platform. C++ was selected as the main programming language for the Geotool+. The two-year Project was extended by six months and funding levels increased from 600,000 to $670,000. All tasks were successfully completed and all deliverables were met for the project even though both the industrial partner and LLNL principal investigator left the project before its final report.

58 GEOSCIENCES↗

Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures

Increased data acquisition by uncalibrated, heterogeneous digital sensor systems such as smartphones present new challenges. Binary metrics are proposed for the quantification of cyber-physical signal characteristics and features, and a standardized constant-Q variation of the Gabor atom is developed for use with wavelet transforms. Two different continuous wavelet transform (CWT) reconstruction formulas are presented and tested under different signal to noise ratio (SNR) conditions. A sparse superposition of Nth order Gabor atoms worked well against a synthetic blast transient using the wavelet entropy and an entropy-like parametrization of the SNR as the CWT coefficient-weighting functions. The proposed methods should be well suited for sparse feature extraction and dictionary-based machine learning across multiple sensor modalities.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

AUTOMATED UNSUPERVISED CLASSIFICATION OF THE SLOAN DIGITAL SKY SURVEY STELLAR SPECTRA USING k-MEANS CLUSTERING

Large spectroscopic surveys require automated methods of analysis. This paper explores the use of k-means clustering as a tool for automated unsupervised classification of massive stellar spectral catalogs. The classification criteria are defined by the data and the algorithm, with no prior physical framework. We work with a representative set of stellar spectra associated with the Sloan Digital Sky Survey (SDSS) SEGUE and SEGUE-2 programs, which consists of 173,390 spectra from 3800 to 9200 A sampled on 3849 wavelengths. We classify the original spectra as well as the spectra with the continuum removed. The second set only contains spectral lines, and it is less dependent on uncertainties of the flux calibration. The classification of the spectra with continuum renders 16 major classes. Roughly speaking, stars are split according to their colors, with enough finesse to distinguish dwarfs from giants of the same effective temperature, but with difficulties to separate stars with different metallicities. There are classes corresponding to particular MK types, intrinsically blue stars, dust-reddened, stellar systems, and also classes collecting faulty spectra. Overall, there is no one-to-one correspondence between the classes we derive and the MK types. The classification of spectra without continuum renders 13 classes, the color separation is not so sharp, but it distinguishes stars of the same effective temperature and different metallicities. Some classes thus obtained present a fairly small range of physical parameters (200 K in effective temperature, 0.25 dex in surface gravity, and 0.35 dex in metallicity), so that the classification can be used to estimate the main physical parameters of some stars at a minimum computational cost. We also analyze the outliers of the classification. Most of them turn out to be failures of the reduction pipeline, but there are also high redshift QSOs, multiple stellar systems, dust-reddened stars, galaxies, and, finally, odd spectra whose nature we have not deciphered. The template spectra representative of the classes are publicly available in the online journal.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of x-ray imaging technique for liquid screening at airport

X-ray imaging technology is a viable option to recognize flammable liquids for the purposes of aviation security. In this study, an X-ray imaging technology was developed whereby, the image viewing system was built with the use of a digital camera coupled with a gadolinium oxysulfide (GOS) fluorescent screen. The camera was equipped with a software for remote control setting of the camera via a USB cable which allows the images to be captured. The image was analysed to determine the average grey level using a software designed by Microsoft Visual Basic 6.0. The data was obtained for various densities of liquid thickness of 4.5 cm, 6.0 cm and 7.5 cm respectively for X-ray energies ranging from 70 to 200 kVp. In order to verify the reliability of the constructed calibration data, the system was tested with a few types of unknown liquids. The developed system could be conveniently employed for security screening in order to discriminate between a threat and an innocuous liquid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Harnessing ionic complexity: A modeling approach for hierarchical ionic circuit design

Since the 1950s, soft ionic devices have evolved from individual components to an expanding library of sensors, actuators, signal transmitters, and processors. However, integrating these components into complex, multifunctional systems remains challenging due to the nonintuitive and nonlinear interactions between ionic elements. In this work, we address these fundamental challenges by developing a lumped element model that enables interrogation of the physics that governs ionic circuits, as well as rapid design and optimization. Our model captures features specific to ionic charge carriers, while preserving the hierarchical design flexibility and computational efficiency of traditional circuit modeling. We demonstrate that our model can not only fit individual device behavior but also accurately predict the behavior of larger circuits formed by combining those devices. Additionally, we show how our tool utilizes the intrinsic nonlinearities of ionic systems to enable extended functionality, revealing how factors such as ion enrichment, ion leakage, and polymer charge density influence performance. Lastly, we present a fully ionic power supply, sensor, control system, and actuator for a soft robot that adapts its motion in response to environmental salt, illustrating the tool’s potential to accelerate advancements in chemical sensing, biointerfacing, biomimetic systems, and adaptive materials.

42 ENGINEERING↗