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At least 1,045 records · Page 58

DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid’s post-fault trajectories

This paper proposes a novel data-driven method for the reliable prediction of the power grid’s post-fault trajectories, i.e., the power grid’s dynamic response after a disturbance or fault. Here, the proposed method is based on the recently proposed concept of Deep Operator Networks (DeepONets). Unlike traditional neural networks that learn to approximate functions, DeepONets are designed to approximate nonlinear operators, i.e., mappings between infinite-dimensional spaces. Under this operator framework, we design a novel and efficient DeepONet that (i) takes as inputs the trajectories collected before and during the fault and (ii) outputs the predicted post-fault trajectories. In addition, we endow our method with the much-needed ability to balance efficiency with reliable/trustworthy predictions via uncertainty quantification. To this end, we propose and compare two novel methods that enable quantifying the predictive uncertainty. First, we propose a Bayesian DeepONet (B-DeepONet) that uses stochastic gradient Hamiltonian Monte-Carlo to sample from the posterior distribution of the DeepONet trainable parameters. Then, we design a Probabilistic DeepONet (Prob-DeepONet) that uses a probabilistic training strategy to enable quantifying uncertainty at virtually no extra computational cost. Finally, we validate the proposed methods’ predictive power and uncertainty quantification capability using the New York-New England power grid model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Atomic-scale Imaging of PGM-free Catalyst Active Sites by 30 keV 4D-STEM

Platinum group metal (PGM)-free catalysts have attracted a large amount of attention due to their potential for enabling low-cost, commercially viable hydrogen fuel cells and electrolyzers [1]. Degradation of cell performance remains a significant challenge, however, currently limiting implementation of devices that utilize PGM-free materials [2]. Controlling degradation in these materials requires a better understanding of the atomic structure of active sites, thought to be FeN4 structures within a graphitic carbon lattice, which would enable more accurate prediction of the associated degradation pathways. The exact structural arrangement of active sites in these materials is still debated since a range of structures have been computationally predicted and methods to directly validate these models are still needed [1,3-5].While scanning transmission electron microscopy (STEM) has provided initial glimpses into the nature of the proposed active sites, detailed evaluation of the structure of these sites is challenging since they involve defects, edges, and nitrogen dopants in the graphitic lattice, which are susceptible to beam damage [6,7]. Conventional STEM imaging and spectroscopy methods exacerbate this problem with dose-inefficiency or nonideal contrast characteristics for imaging light and heavy elements simultaneously. A method that minimizes damage while generating dose-efficient, easily-interpretable contrast for both light and heavy elements is therefore needed to facilitate imaging of sensitive active site atomic structure.Here, we demonstrate direct atomic-scale imaging of PGM-free catalyst active sites by low-voltage four-dimensional (4D)-STEM. To accomplish this, we pair a 30 keV aberration-corrected probe, which minimizes knock-on damage, with a fast pixelated detector that has optimal performance at low beam energies [8]. We show how this setup enables relatively simple center-of-mass (CoM) techniques [9,10] to produce images with an increased signal-to-noise ratio (SNR) and light-element contrast over conventional imaging modes, allowing the entire active site structure to be imaged at the atomic scale. Moreover, we show how electron ptychography [11,12] enables images with further improved characteristics to be obtained, for example by minimizing residual aberrations, which provides a more accurate structural representation. The increased understanding that these low-voltage 4D-STEM techniques will provide about the atomic structure of PGM-free active sites and their associated degradation pathways will facilitate rational design of next-generation materials, promoting development of low-cost hydrogen fuel cells, electrolyzers, and other energy conversion devices [13]. References:[1] U Martinez et al., Adv. Mater. 31 (2019), p. 1806545.[2] Y Shao et al., Adv. Mater. 31 (2019), p. 1807615.[3] J Kneebone et al., J. Phys. Chem. C 121, (2017), p.16283.[4] T Mineva et al., ACS Catal. 9 (2019), p. 9359.[5] J Li et al., Nat. Catal. 4 (2021), p. 10.[6] T Susi et al., ACS Nano 6 (2012), p. 8837.[7] P Zelenay and DJ Myers, US Department of Energy Hydrogen and Fuel Cells Program 2017 Annual Merit Review and Peer Evaluation Meeting, Washington, DC (2017).[8] H Ryll et al., J. Inst. 11 (2016), p. P04006.[9] K Müller et al., Nat. Commun. 5 (2014), p. 5653.[10] I Lazic et al., Ultramicroscopy 160 (2016), p. 265.[11] H Yang et al., Nat. Commun. 7 (2016), p. 12532.[12] Y Jiang et al., Nature 559 (2018), p. 343. [13] Research sponsored by the Hydrogen and Fuel Cell Technologies Office, Office of Energy Efficiency and Renewable Energy, US Department of Energy (DOE). Research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.

Zachman, Michael↗

Analytical and Performance-Based Evaluation Alternatives to Full-Scope, High-Fidelity Testbeds

One consequence the design and operational differences of advanced reactors is that integrated system validation (ISV) using full-scope, high-fidelity testbed might not be cost-justified or practical. The absence of traditional ISV may pose an issue for the conduct of safety evaluations since it may leave regulators without the information derived from this performance-based testing. The purpose of this research is to identify analytical and performance-based test and evaluation methods that are alternatives to full-scope, high-fidelity testbeds that have traditionally been used for ISV. We developed a method to test validation based on a multi-stage validation (MSV) framework. MSV is an approach to meeting validation objectives through incremental, successive validation activities beginning in the early stages of the design process and continuing through the later stages. MSV doesn't rely solely on late stage validation, rather it accommodates the use of a broad spectrum of analytical and performance-based information and a diversity of testbeds. In addition, MSV embraces the use of information from other types of evaluations and analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Full stress tensor measurement using fluorescence spectroscopy

Photoluminescent spectral peak positions are known to shift as a function of mechanical stress state. This has been demonstrated at macroscales to determine mean stress and mesoscales to determine mean stress and a quantity related to shear stress. Here, we propose a method to utilize traction-free surface conditions and knowledge of material orientation to solve for two in-plane displacement fields given two measured spectral peak positions measured at a grid of points. It is then possible to calculate the full stress tensor at each measurement point. This is a significant advancement over the previous ability to measure one or two stress quantities. We validate the proposed method using a simple, two-grain geometry and show that it produces the same mean stress and shear stress measure as the existing direct method. Furthermore, we also demonstrate determination of the full stress field in a polycrystalline alumina specimen.

47 OTHER INSTRUMENTATION↗

Simultaneous evaluation of acoustic nonlinearity parameter and attenuation coefficients using the finite amplitude method

A novel method to determine acoustic parameters involved in measuring the nonlinearity parameter of fluids or solids is proposed. The approach is based on the measurement of fundamental and second harmonic pressures with a calibrated receiver, and on a nonlinear least squares data-fitting to multi-Gaussian beam (MGB) equations which explicitly define the attenuation and diffraction effects in the quasilinear regime. Results obtained in water validate the proposed method. The choice of suitable source pressure is discussed with regard to the quasilinear approximation involved. The attenuation coefficients are also acquired in nonlinear regime and their relations are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A peak position comparison method for high-speed quantitative Laue microdiffraction data processing

Indexing Laue patterns of a synchrotron microdiffraction scan can take as much as ten times longer than collecting the data, impeding efficient structural analysis using this technique. Here in this paper, a novel strategy is developed. By comparing the peak positions of adjacent Laue patterns and checking the intensity sequence, grain and phase boundaries are identified, requiring only a limited number of indexing steps for each individual grain. Using this protocol, the Laue patterns can be indexed on the fly as they are taken. The validation of this method is demonstrated by analyzing the microstructure of a laser 3D printed multi-phase/multi-grain Ni-based superalloy.

36 MATERIALS SCIENCE↗

A Deterministic Multivariate Clustering Method for Drive Cycle Generation from In-Use Vehicle Data

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data. This paper explores the development and initial validation of a method of generating representative drive cycles from large collections of real-world vehicle data using a deterministic multivariate clustering approach. Starting with theory and diving into the methodology behind representative cycle generation, the paper aims to also present graphical and tabular results of initial validation via vehicle simulation and chassis dynamometer testing. Additional topics for further research and areas for ongoing development will also be presented.

47 OTHER INSTRUMENTATION↗

Minimizing Fraud in the Carbon Offset Market Using Blockchain Technologies

Fraud in the Environmental Benefit Credit (EBC) markets is pervasive. To make matters worse, the cost of creating EBCs is often higher than the market price. Consequently, a method to create, validate, and verify EBCs and their relevance is needed to mitigate fraud. The EBC market has focused on geologic (fossil fuel) CO 2 sequestration projects that are often over budget and behind schedule and has failed to capture the "lowest hanging fruit" EBCs - terrestrial sequestration via the agricultural industry. This project reviews a methodology to attain possibly the least costly EBCs by tracking the reduction of inputs required to grow crops. The use of bio- stimulant products, such as humate, allows a farmer to use less nitrogen without adversely affecting crop yield. Using less nitrogen qualifies for EBCs by reducing nitrous oxide emissions and nitrate runoff from a farmer's field. A blockchain that tracks the bio-stimulant material from source to application provides a link between a tangible (bio-stimulant commodity) and the associated intangible (EBCs) assets. Covert insertion of taggants in the bio-stimulant products creates a unique barcode that allows a product to be digitally tracked from beginning to end. This process (blockchain technology) is so robust, logical, and transparent that it will enhance the value of the associated EBCs by mitigating fraud. It provides a real time method for monetizing the benefits of the material. Substantial amounts of energy are required to produce, transport, and distribute agricultural inputs including fertilizer and water. Intelligent optimization of the use of agricultural inputs can drive meaningful cost savings. Tagging and verification of product application provides a valuable understanding of the dynamics in the water/food energy nexus, a major food security and sustainability issue. As technology in agriculture evolves so to must methods to verify the Enterprise Resource Planning (ERP) potential of innovative solutions. The technology reviewed provides the ability to combine blockchain and taggants ("taggant blockchains") as the engine by which to (1) mitigate fraudulent carbon credits; (2) improve food chain security, and (3) monitor and manage sustainability. The verification of product quality and application is a requirement to validate benefits. Recent upgrades to humic and fulvic quality protocols known as ISO CD 19822 TC134 offers an analytical procedure. This work has been assisted by the Humic Products Trade Association and International Humic Substance Society. In addition, providing proof of application of these products and verification of the correct application of prescriptive humic and bio-stimulant products is required. Individual sources of humate have unique and verifiable characteristics. Additionally, methods for prescription of site- specific agricultural inputs in agricultural fields are available. (See US Patents 734867B2, US 90658633B2.) Finally, a method to assure application rate is required through the use of taggants. Sensors using organic solid to liquid phase change nanoparticles of various types and melting temperatures added to the naturally occurring materials provide a barcode. Over 100 types of nanoparticles exist ensuring numerous possible barcodes to reduce industry fraud. Taggant materials can be collected from soil samples of plant material to validate a blockchain of humic, fulvic and other soil amendment products. Other non-organic materials are also available as taggants; however, the organic tags are biodegradable and safe in the environment allowing for use during differing application timeliness.

54 ENVIRONMENTAL SCIENCES↗

Taxonomy of USA east coast fishing communities in terms of social vulnerability and resilience

Increased concern with the impacts that changing coastal environments can have on coastal fishing communities led to a recent effort by NOAA Fisheries social scientists to develop a set of indicators of social vulnerability and resilience for the U.S. Southeast and Northeast coastal communities. A goal of the NOAA Fisheries social vulnerability and resilience indicator program is to support time and cost effective use of readily available data in furtherance of both social impact assessments of proposed changes to fishery management regulations and climate change adaptation planning. The use of the indicators to predict the response to change in coastal communities would be enhanced if community level analyses could be grouped effectively. This study examines the usefulness of combining 1130 communities into 35 relevant subgroups by comparing results of a numerical taxonomy with data collected by interview methods, a process herein referred to as “ground-truthing.” The validation of the taxonomic method by the method of ground-truthing indicates that the clusters are adequate to be used to select communities for in-depth research. - Highlights: • We develop a taxonomy of fishing communities based on vulnerability indicators. • We validate the community clusters through the use of surveys (“ground-truthing”). • Clusters differ along important aspects of fishing community vulnerability. • Clustering communities allows for accurate and timely social impact assessments.

54 ENVIRONMENTAL SCIENCES↗

PACT Data Management Plan (V.1.0)

The Perovskite PV Accelerator for Commercial Technology (PACT) is an independent validation center for the evaluation of perovskite PV technologies and their bankability. The center is led by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL) and includes as part of its team Los Alamos National Laboratory (LANL), CFV Labs, Black and Veatch (B&V), and the Electric Power Research Institute (EPRI). The goals of the center are to: Develop and improve indoor and outdoor performance characterization methods, Develop and validate accelerated qualification testing for early failures (5-10 years), Research degradation and failure modes, Validate outdoor performance, and Provide bankability services to US perovskite PV (PSC) industry. The importance of data and data management to the success and outcomes of the PACT center is paramount. This report describes how data will be managed and protected by PACT and identifies important data management principles that will guide our approach.

14 SOLAR ENERGY↗

TU-AB-BRC-09: Fast Dose-Averaged LET and Biological Dose Calculations for Proton Therapy Using Graphics Cards

Purpose: To demonstrate fast and accurate Monte Carlo (MC) calculations of proton dose-averaged linear energy transfer (LETd) and biological dose (BD) on a Graphics Processing Unit (GPU) card. Methods: A previously validated GPU-based MC simulation of proton transport was used to rapidly generate LETd distributions for proton treatment plans. Since this MC handles proton-nuclei interactions on an event-by-event using a Bertini intranuclear cascade-evaporation model, secondary protons were taken into account. The smaller contributions of secondary neutrons and recoil nuclei were ignored. Recent work has shown that LETd values are sensitive to the scoring method. The GPU-based LETd calculations were verified by comparing with a TOPAS custom scorer that uses tabulated stopping powers, following recommendations by other authors. Comparisons were made for prostate and head-and-neck patients. A python script is used to convert the MC-generated LETd distributions to BD using a variety of published linear quadratic models, and to export the BD in DICOM format for subsequent evaluation. Results: Very good agreement is obtained between TOPAS and our GPU MC. Given a complex head-and-neck plan with 1 mm voxel spacing, the physical dose, LETd and BD calculations for 10{sup 8} proton histories can be completed in ∼5 minutes using a NVIDIA Titan X card. The rapid turnover means that MC feedback can be obtained on dosimetric plan accuracy as well as BD hotspot locations, particularly in regards to their proximity to critical structures. In our institution the GPU MC-generated dose, LETd and BD maps are used to assess plan quality for all patients undergoing treatment. Conclusion: Fast and accurate MC-based LETd calculations can be performed on the GPU. The resulting BD maps provide valuable feedback during treatment plan review. Partially funded by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

TU-C-17A-10: Patient Features Based Dosimetric Pareto Front Prediction In Esophagus Cancer Radiotherapy

Purpose: The purpose of this study is to study the feasibility of the dosimetric pareto front (PF) prediction based on patient anatomic and dosimetric parameters for esophagus cancer patients. Methods: Sixty esophagus patients in our institution were enrolled in this study. A total 2920 IMRT plans were created to generated PF for each patient. On average, each patient had 48 plans. The anatomic and dosimetric features were extracted from those plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose and PTV homogeneous index (PTVHI) were recorded for each plan. The principal component analysis (PCA) was used to extract overlap volume histogram (OVH) features between PTV and other critical organs. The full dataset was separated into two parts include the training dataset and the validation dataset. The prediction outcomes were the MHD and MLD for the current study. The spearman rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The PF was fit by the the stepwise multiple regression method. The cross-validation method was used to evaluation the model. Results: The mean prediction error of the MHD was 465 cGy with 100 repetitions. The most correlated factors were the first principal components of the OVH between heart and PTV, and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 195 cGy. The most correlated factors were the first principal components of the OVH between lung and PTV, and the overlap between lung and PTV in Z-axis. Conclusion: It is feasible to use patients anatomic and dosimetric features to generate a predicted PF. Additional samples and further studies were required to get a better prediction model.

60 APPLIED LIFE SCIENCES↗

Three-parameter error analysis method based on rotating coordinates in rotating birefringent polarizer system

We propose error analysis using a rotating coordinate system with three parameters of linearly polarized light—incidence angle, azimuth angle on the front surface, and angle between the incidence and vibration planes—and demonstrate the method on a rotating birefringent prism system. The transmittance and angles are calculated plane-by-plane using a birefringence ellipsoid model and the final transmitted intensity equation is deduced. The effects of oblique incidence, light interference, beam convergence, and misalignment of the rotation and prism axes are discussed. We simulate the entire error model using MATLAB and conduct experiments based on a built polarimeter. The simulation and experimental results are consistent and demonstrate the rationality and validity of this method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

2–stage stochastic Runge–Kutta for stochastic delay differential equations

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Higher-order transverse momentum fluctuations in heavy-ion collisions

In relativistic heavy-ion collisions, the event-by-event mean transverse momentum fluctuations are sensitive to overlap area and energy density fluctuations in the initial state. We present a framework to calculate p T fluctuations up to fourth order using standard and subevent methods, which is validated using the HIJING model. We observe a power-law dependence for cumulants of all orders as a function of charged particle multiplicity N ch , consistent with a simple independent source picture. The fluctuation in pp collisions is observed to be larger than for p+Pb, Pb + Pb, and Xe + Xe collisions at the same N ch due to bias in the number of contributing sources. The short-range correlations are greatly suppressed in the subevent method in comparison to calculations based on the standard method. This paper provides a baseline for transverse momentum fluctuations without the presence of final-state effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sci-Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques - 05: A novel respiratory motion simulation program for VMAT treatment plans: a phantom validation study

Purpose: To develop and validate a computational method to simulate craniocaudal respiratory motion in a VMAT treatment plan. Methods: Three 4DCTs of the QUASAR respiratory motion phantom were acquired with a 2cm water-density spherical tumour embedded in cedar to simulate lung. The phantom was oscillating sinusoidally with an amplitude of 2cm and periods of 3, 4, and 5 seconds. An ITV was contoured and 5mm PTV margin was added. High and a low modulation factor VMAT plans were created for each scan. An in-house program was developed to simulate respiratory motion in the treatment plans by shifting the MLC leaf positions relative to the phantom. Each plan was delivered to the phantom and the dose was measured using Gafchromic film. The measured and calculated plans were compared using an absolute dose gamma analysis (3%/3mm). Results: The average gamma pass rate for the low modulation plan and high modulation plans were 91.1% and 51.4% respectively. The difference between the high and low modulation plans gamma pass rates is likely related to the different sampling frequency of the respiratory curve and the higher MLC leaf speeds in the high modulation plan. A high modulation plan has a slower gantry speed and therefore samples the breathing cycle at a coarser frequency leading to inaccuracies between the measured and planned doses. Conclusion: A simple program, including a novel method for increasing sampling frequency beyond the control point frequency, has been developed to simulate respiratory motion in VMAT plans by shifting the MLC leaf positions.

60 APPLIED LIFE SCIENCES↗

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies

The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

59 BASIC BIOLOGICAL SCIENCES↗

Application of high-order numerical schemes and Newton-Krylov method to two-phase drift-flux model

This study concerns the application and solver robustness of the Newton-Krylov method in solving two-phase flow drift-flux model problems using high-order numerical schemes. In our previous studies, the Newton-Krylov method has been proven as a promising solver for two-phase flow drift-flux model problems. However, these studies were limited to use first-order numerical schemes only. Moreover, the previous approach to treating the drift-flux closure correlations was later revealed to cause deteriorated solver convergence performance, when the mesh was highly refined, and also when higher-order numerical schemes were employed. In this study, a second-order spatial discretization scheme that has been tested with two-fluid two-phase flow model was extended to solve drift-flux model problems. In order to improve solver robustness, and therefore efficiency, a new approach was proposed to treating the mean drift velocity of the gas phase as a primary nonlinear variable to the equation system. With this new approach, significant improvement in solver robustness was achieved. With highly refined mesh, the proposed treatment along with the Newton-Krylov solver were extensively tested with two-phase flow problems that cover a wide range of thermal-hydraulics conditions. Satisfactory convergence performances were observed for all test cases. Numerical verification was then performed in the form of mesh convergence studies, from which expected orders of accuracy were obtained for both the first-order and the second-order spatial discretization schemes. Finally, the drift-flux model, along with numerical methods presented, were validated with three sets of flow boiling experiments that cover different flow channel geometries (round tube, rectangular tube, and rod bundle), and a wide range of test conditions (pressure, mass flux, wall heat flux, inlet subcooling and outlet void fraction).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗