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At least 109 records · Page 6

Implicit–explicit multirate infinitesimal stage-restart methods

Implicit–Explicit (IMEX) methods are flexible numerical time integration methods which solve an initial-value problem (IVP) that is split into stiff and nonstiff processes with the goal of lower computational costs than a purely implicit or explicit approach. A complementary form of flexible IVP solvers are multirate infinitesimal methods for problems split into fast- and slow-changing dynamics, that solve a multirate IVP by evolving a sequence of “fast” IVPs using any suitably accurate algorithm. This article introduces a new class of high-order implicit–explicit multirate methods that are designed for multirate IVPs in which the slow-changing dynamics are further split in an IMEX fashion. This new class, which we call implicit–explicit multirate infinitesimal stage-restart (IMEX-MRI-SR), both improves upon the previous implicit–explicit multirate infinitesimal generalized-structure additive Runge Kutta (IMEX-MRI-GARK) methods by allowing for far easier creation of new embedded methods, and extends multirate exponential Runge Kutta (MERK) methods by allowing the fast-changing dynamics to be nonlinear and the methods to be implicit. We leverage GARK theory to derive conditions for orders of accuracy up to four, and we provide second- and third-order accurate example methods, which are the first known embedded MRI methods with IMEX structure. We then perform numerical simulations demonstrating convergence rates and computational performance in both fixed-step and adaptive-step settings.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A core–shell structured nanocomposite of NiO with carbon nanotubes as positive electrode material of high capacitance for supercapacitors

Highlights: • A core–shell structured NiO@CNTs nanocomposite is synthesized by a simple hydrothermal method. • The CNTs core effectively improves the capacitance, rate and cycling performance of NiO. • A supercapacitor is assembled when activated carbon is used as the negative electrode. • The supercapacitor presents an energy density up to 52.6 Wh kg{sup −1}. - Abstract: A nanocomposite of carbon nanotubes coated with nickel oxide was prepared by a simple hydrothermal method. The structure, morphology and electrochemical performance of the nanocomposite were investigated by X-ray diffraction, scanning electron microscopy and transmission electron microscopy, electrochemical tests including cyclic voltammogram, galvanostatic charge–discharge and electrochemical impedance spectroscopy, respectively. It presents the highest specific capacitance of 1844 F g{sup −1} at 1 A g{sup −1} and 1145 F g{sup −1} at current density of 10 A g{sup −1} with 88.9% (at 1 A g{sup −1}) capacitance retention after 1000 cycles. The specific capacitance of the nanocomposite is almost double of that of the virginal NiO (972 F g{sup −1} at 1 A g{sup −1}). Its cycling behavior is also very good. When combined with activated carbon as the negative electrode, the energy density can be up to 52.6 Wh kg{sup −1}. Such good electrochemical behavior indicates that the nanocomposite is a promising electrode material for supercapacitors.

36 MATERIALS SCIENCE↗

Batch Active Learning for Multispectral and Hyperspectral Image Segmentation Using Similarity Graphs

Abstract Graph learning, when used as a semi-supervised learning (SSL) method, performs well for classification tasks with a low label rate. We provide a graph-based batch active learning pipeline for pixel/patch neighborhood multi- or hyperspectral image segmentation. Our batch active learning approach selects a collection of unlabeled pixels that satisfy a graph local maximum constraint for the active learning acquisition function that determines the relative importance of each pixel to the classification. This work builds on recent advances in the design of novel active learning acquisition functions (e.g., the Model Change approach in arXiv:2110.07739) while adding important further developments including patch-neighborhood image analysis and batch active learning methods to further increase the accuracy and greatly increase the computational efficiency of these methods. In addition to improvements in the accuracy, our approach can greatly reduce the number of labeled pixels needed to achieve the same level of the accuracy based on randomly selected labeled pixels.

97 MATHEMATICS AND COMPUTING↗

SU-E-T-190: Commissioning An Elekta VersaHD Linear Accelerator

Purpose: The purpose of this study is to report the dosimetric aspects of commissioning performed on an Elekta VersaHD linear accelerator with high dose rate flattening-filter-free (FFF) photon modes and electron modes. Methods: Acceptance and commissioning was performed on an Elekta VersaHD linac with 5 photon energies (6MV, 10MV, 18MV, 6FFF, 10FFF), 4 electron energies (6MeV, 9MeV, 12MeV, 15MeV) and 160 leaf (5mm wide) multi-leaf collimators (MLCs). Mechanical and dosimetric data was measured and evaluated. The measurements include percent depth doses (PDDs), inplane and crossplane profiles, head scatter factor (Sc), relative photon output factors (Scp), universal wedge transmission factor, MLC transmission factors, and electron cone factors. Results: Gantry, collimator, couch isocentricity measurements were within 1mm, 0.7mm and 0.7mm diameter respectively. The PDDs of 6FFF and 10FFF beams show deeper dmax and steeper fall-off with depth than the corresponding flattened beams. While flatness values of 6FFF and 10FFF normalized profiles were higher than the corresponding flattened beams, the symmetry values were almost identical. The crossplane penumbra values were higher than the inplane penumbra values for all the energies. The MLC transmission values were 0.5%, 0.6% and 0.6% for 6MV, 10MV, and 18MV photon beams. The electron PDDs, profiles and cone factors is validated by literature. Conclusion: The outcome of radiation treatment is directly related to the accuracy in the dose modeled in the treatment planning system which is based on the commissioned data. Commissioning data provided us a valuable insight into the dosimetric characteristics of the beam. This set of commissioning data can provide comparison data to others performing VersaHD commissioning thus improving patient safety.

60 APPLIED LIFE SCIENCES↗

Identification and Preservation of Arm Lymphatic System in Axillary Dissection for Breast Cancer to Reduce Arm Lymphedema Events: A Randomized Clinical Trial

Background: Controversy in axillary reverse mapping in axillary lymph node dissection (ALND) possibly results from incomplete recognition of the arm lymphatic system (ALS) and its compromise to oncological safety. The iDEntification and Preservation of ARm lymphaTic system (DEPART) technique facilitates complete identification of ALS; therefore, its use may decrease the occurrence of arm lymphedema. This study aimed to examine the arm lymphedema rate, locoregional recurrence, and feasibility to perform DEPART in ALND. Methods: Patients from February 2013 to October 2017 from two tertiary referral centers were randomly assigned to two groups. In the study group, indocyanine green and methylene blue (MB) were utilized to identify arm sentinel nodes, and 0.1 ml MB was injected into the arm sentinel nodes to reveal the subsequent-echelon nodes and lymphatics. Gross arm lymph nodes were examined by intraoperative partial frozen section and were removed if positive. Arm lymphedema, local recurrence, regional recurrence, and distant metastasis were recorded at different follow-up examinations. Results: Arm sentinel nodes were identified in 573 (83.2%) patients. Subsequent-echelon nodes and lymphatics were visualized in 558 (97.4%) patients. Metastatic arm nodes were identified in 38 (6.8%) patients. The arm lymphedema rate was 3.3% (18/543) in the study group versus 15.3% (99/648) in the control group (p < 0.001) after 37-month median follow-up. Regional recurrence showed no difference between the two groups (1.4% and 1.2%, respectively) (p = 0.392). Conclusions: DEPART can benefit breast cancer patients who undergo ALND, reducing the arm lymphedema rate without adversely affecting the morbidity of regional recurrence.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2014

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2014 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2014. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. Six trends with varying degrees of statistical significance were identified in the data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Growth of titania and tin oxide from Ti 2 SnC via rapid thermal oxidation in air for lithium-ion battery application

Herein, we report the synthesis of TiO 2 –SnO 2 –C/carbide hybrid electrode materials for Li-ion batteries (LIBs) via two different methods of controlled oxidation of layered Ti 2 SnC. The material was partially oxidized in an open-air furnace (OAF) or using a rapid thermal annealing (RTA) approach to obtain the desired TiO 2 –SnO 2 –C/carbide hybrid material; the carbide phase encompassed both residual Ti 2 SnC and TiC as a reaction product. We tested the oxidized materials as an anode in a half cell to investigate their electrochemical performance in LIBs. Analysis of the various oxidation conditions indicated the highest initial lithiation capacity of 838 mAh/g at 100 mA/g for the sample oxidized in the OAF at 700°C for 1 h. Still, the delithiation capacity dropped to 427 mAh/g and faded over cycling. Long-term cycling demonstrated that the RTA sample treated at 800°C for 30 s was the most efficient, as it demonstrated a reversible capacity of around 270 mAh/g after 150 cycles, as well as a specific capacity of about 150 mAh/g under high cycling rate (2000 mA/g). Given the materials’ promising performance, this processing method could likely be applied to many other members of the MAX family, with a wide range of energy storage applications.

25 ENERGY STORAGE↗

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.

59 BASIC BIOLOGICAL SCIENCES↗

Pushing the limits of pulse shape discrimination in a large liquid xenon detector

Abstract The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing tail fraction discriminator is optimized and achieves ER leakage as low as $$15\%$$ 15 % . For specific background processes such as $$^{124}$$ 124 Xe double electron capture, the leakage is reduced further to about $$5\%$$ 5 % . PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ’s WS2024 run and their performance is summarized.

Akerib, D. S. [SLAC National Accelerator Laborator↗

Pushing the Limits of Pulse Shape Discrimination in a Large Liquid Xenon Detector

The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing prompt fraction discriminator is optimized and achieves ER leakage as low as $15\%$. For specific background processes such as $^{124}$Xe double electron capture, the leakage is reduced further to about $5\%$. PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ's WS2024 run and their performance is summarized.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2018

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2018 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2018. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. A statistically significant increasing trend was identified in the frequency of FTLR demands for emergency power system (EPS) and high pressure core spray (HPCS) EDGs and a statistically significant decreasing trend was identified in the frequency of run > 1H hours for EPS and HPCS EDGs.

99 GENERAL AND MISCELLANEOUS↗

Upscaling of Regional Scale Transport Under Transient Conditions: Evaluation of the Multirate Mass Transfer Model

Abstract Regional scale transport models are needed to support the long‐term evaluation of groundwater quality and to develop management strategies aiming to prevent serious groundwater degradation. The purpose of this study is to evaluate the capacity of a previously developed upscaling approach to adequately describe the main solute transport processes, including the capture of late‐time tails under changing boundary conditions. Potential factors that impact the performance of upscaling methods, including temporal variations in mass transfer rates and mass distributions, were investigated. Advective‐dispersive contaminant transport in a 3‐D heterogeneous domain was simulated and used as a reference solution. The equivalent transport under homogeneous flow conditions was then evaluated by applying the multirate mass transfer (MRMT) model. The random walk particle tracking method was used to solve the solute transport for heterogeneous and homogeneous MRMT scenarios under steady state and transient conditions. The results indicate that the MRMT model can capture the tails satisfactorily for plumes transported with ambient steady state flow fields at all studied scales using the same parameters. However, when the boundary conditions change in either local, plume, or regional scale, the mass transfer model calibrated for transport under steady state conditions cannot accurately reproduce the tailings observed for the heterogeneous scenario. The deteriorating impacts of transient boundary conditions on the upscaled model are more significant for regions where the flow fields are dramatically affected, which highlights the poor applicability of the MRMT approach for complex field settings. This finding also has implications for the suitability of other potential upscaling approaches.

Guo, Zhilin↗

Computational modeling of charge hopping dynamics along a disordered one-dimensional wire with energy gradients in quantum environments

This computational study investigates the effects of energy gradients on charge hopping dynamics along a one-dimensional chain of discrete sites coupled to quantum bath, which is modeled at the level of Pauli master equation (PME). This study also assesses the performance of different approximations for the hopping rates. Three different methods for solving the PME, a fourth order Runge–Kutta method, numerical diagonalization of the rate matrix followed by analytic propagation, and kinetic Monte Carlo simulation method, are tested and confirmed to produce virtually identical values of time dependent mean square displacement, diffusion constant, and mobility. Five different rate expressions, exact numerical evaluation of Fermi’s Golden Rule (FGR) rate, stationary phase interpolation (SPI) approximation, semiclassical approximation, classical Marcus rate, and Miller–Abrahams rate, are tested to help understand the effects of approximations in representing quantum environments in the presence of energy gradients. The results based on direct numerical evaluation of FGR rate exhibit transition from diffusive to non-diffusive behavior with the increase in the gradient and show that the charge transport in the quantum bath is more sensitive to the magnitude of the gradient and the disorder than in the classical bath. Among all the four approximations for the hopping rates, the SPI approximation is confirmed to work best overall. A comparison of two different methods to calculate the mobility identifies drift motion of the population distribution as the major source of non-diffusive behavior and provides more reliable information on the contribution of quantum bath.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Astrophysical impact of the updated {sup 9}Be(p,α){sup 6}Li and {sup 10}B(p,α){sup 7}Be reaction rates as deduced by THM

The complete understanding of the stellar abundances of lithium, beryllium, and boron represents one of the most interesting open problems in astrophysics. These elements are largely used to probe stellar structure and mixing phenomena in different astrophysical scenarios, such as pre-main-sequence or main-sequence stars. Their different fragility against (p,α) burning reactions allows one to investigate different depths of the stellar interior. Such fusion mechanisms are triggered at temperatures between T ≈ (2–5) × 10{sup 6} K, thus defining a corresponding Gamow energy between ≈ 3–10 keV, where S(E)-factor measurements need to be performed to get reliable reaction rate evaluations. The Trojan Horse Method is a well defined procedure to measure cross sections at Gamow energies overcoming the uncertainties due to low-energy S(E)-factor extrapolation as well as electron screening effects. Taking advantage of the THM measure of the {sup 9}Be(p,α){sup 6}Li and {sup 10}B(p,α){sup 7}Be cross sections, the corresponding reaction rates have been calculated and compared with the evaluations by the NACRE collaboration, widely used in the literature. The impact on surface abundances of the updated {sup 9}Be and {sup 10}B (p,α) burning rates is discussed for pre-MS stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

XANES and EXAFS of dilute solutions of transition metals at XFELs

This work has demonstrated that X-ray absorption spectroscopy (XAS), both Mn XANES and EXAFS, of solutions with millimolar concentrations of metal is possible using the femtosecond X-ray pulses from XFELs. Mn XAS data were collected using two different sample delivery methods, a Rayleigh jet and a drop-on-demand setup, with varying concentrations of Mn. Here, a new method for normalization of XAS spectra based on solvent scattering that is compatible with data collection from a highly variable pulsed source is described. The measured XANES and EXAFS spectra of such dilute solution samples are in good agreement with data collected at synchrotron sources using traditional scanning protocols. The procedures described here will enable XFEL-based XAS on dilute biological samples, especially metalloproteins, with low sample consumption. Details of the experimental setup and data analysis methods used in this XANES and EXAFS study are presented. This method will also benefit XAS performed at high-repetition-rate XFELs such as the European XFEL, LCLS-II and LCLS-II-HE.

Chatterjee, Ruchira (ORCID:000000020865061X)↗

Estimating Sparse Direct Effects in Multivariate Regression With the Spike-and-Slab LASSO

The multivariate regression interpretation of the Gaussian chain graph model simultaneously parametrizes (i) the direct effects of p predictors on q outcomes and (ii) the residual partial covariances between pairs of outcomes. We introduce a new method for fitting sparse versions of these models with spike-and-slab LASSO (SSL) priors. We develop an Expectation Conditional Maximization algorithm to obtain sparse estimates of the p × q matrix of direct effects and the q × q residual precision matrix. Our algorithm iteratively solves a sequence of penalized maximum likelihood problems with self-adaptive penalties that gradually filter out negligible regression coefficients and partial covariances. Because it adaptively penalizes individual model parameters, our method is seen to outperform fixed-penalty competitors on simulated data. We establish the posterior contraction rate for our model, buttressing our method’s excellent empirical performance with strong theoretical guarantees. Using our method, we estimated the direct effects of diet and residence type on the composition of the gut microbiome of elderly adults.

EM algorithm↗

Comparison of plug flow and multi-node stratified tank modeling approaches regarding computational efficiency and accuracy

Residential water heaters contain water stratified by temperature-driven density differences. This implies that a water tank can reach a state in which the top and bottom sections have different temperatures, unless mixing happens. A high degree of thermal stratification can improve the efficiency of some water heaters, by saving the amount of energy required for the heat-up process. Studies of stratification became popular in the 1970s and it remains an active research topic today. The research has led to the development of different models and techniques to better predict and define a stratified tanks behavior. By comparing these models and techniques used previously to describe thermal stratification, the phenomenon could be better understood, exploited, and used to increase efficiency and thermal energy capacity in modern water tanks. From the existing models, we found the one-dimensional standard plug-flow and a multi node model to be appropriate for analyzing the processes of the heat up and cool-down in a water tank. These two models are based on energy balances. This work involved comparing the accuracy and computational effort needed to implement these models. To assess accuracy, we compared both types of existing models to experimental data (also collected in this work) which included a heat up process using an external heat pump. This external process included a layering process that has an eddy diffusivity at five times the rate of thermal diffusion. For this project, we implemented the models in MATLAB, the multi-paradigm numerical computing environment. We quantified model accuracy using the root mean squared error between modeled data and experimental data for six measured tank temperatures. Comparing the accuracy and the computational time taken to run the simulation provides a method to contrast the performance of each model and a way to rate it. The multi node model was run using from 6 to 96 spatial nodes; the plug flow model was run using 1 to 0.001 º C temperature bin sizes. Additionally, timesteps were varied from 4 to 236 s. The results quantify the tradeoff between accuracy and computational time, providing guidance for simulations to intelligently select the best model type and simulation parameters. This research can be used to validate the pre-existing models and possibly improve the modern water tank.

Bulnes, Fernando Karg↗