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At least 631 records · Page 35

Pressurizing Hagan and SAVY containers to 30-psig (air) to measure the release of analytical cerium oxide test powder

In response to an ESS surrounding the storage of sealed sources at TA-55, personnel from RP-SVS (Radiation Protection Services) and ORI-2 (Operational Readiness & Execution) were approached by ES-55 (Facility System Engineering) to provide technical testing of known nuclear material storage containers. Testing criteria were determined by SB-PF (Safety Basis for Plutonium Facilities). Tests were conducted in conjunction with multiple related projects at the Aerosol Sciences Laboratory (TA-03-0130-0103). An experimental system was quickly developed to deliver a pressure pulse (30-psig) that mimics a sealed source burst scenario. A series of twelve tests was conducted. Six tests were done with two different 5QT SAVY-4000 containers, where each SAVY filter-lid combination was subjected to three successive test insults. Three tests were done with a (0.375" diameter filter) 8Q.T Hagan container, and three tests with a (0.625" diameter filter) 8QT Hagan container. An unused, fresh container filter was used for each tested Hagan container, each receiving only one test insult per filter. Cerium oxide (CeO 2 ) powder was loaded (100 grams per test) into a nozzle in the tested Hagan and SAVY containers, and the nozzle was hard-plumbed to a ball valve and a pressure source. This system was installed into the Los Alamos RRFMC (Respirable Release Measurement Chamber), which is an integrated multipurpose aerosol wind tunnel that satisfies NQA-1 subpart 2.4 for R&D work. The ball valve was fitted with a mechanical linkage for operation from outside the wind tunnel. An aerodynamic particle sizer counted the particle concentrations and size distributions of released aerosol. Respirable aerosol released during the tests was measured and a correction factor for wind tunnel flowrate and internal duct deposition was applied.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Storage Enabled Flexibility of Conventional Generation Assets (StorFlex)

The power systems have faced progressively more demanding operational requirements over the last two decades. Several factors contribute to these challenging operating conditions, including load growth, aging infrastructure, increasing penetrations of distributed energy resources (DERs), electrification of the economy, and policy initiatives such as decarbonization. The power system and its components must provide high operational flexibility to mitigate these challenges. For example, the proliferation of intermittent DERs such as wind and solar has increased the need for conventional generation assets like hydropower plants to respond to sudden load-generation imbalances. The higher flexibility requirements for hydropower plants cause more wear and tear, potentially shortening the useful lifespan of hydropower turbines. To reduce the need for hydropower plants to follow sudden changes in the dispatch signal, we investigate their combined operation with the energy storage systems (ESSs; “ESS-based hybridization”). Our analyses focuses on improving the lifespan of hydropower plants through ESS-based hybridization. Wear and tear on hydropower turbines (particularly Francis turbines) is modeled using a loss-of-life concept that is based on damage experienced by the turbine due to various cycles of operation. Then, we show that using ESSs to offset some of the high variation increases the remaining life of the hydropower plants. To demonstrate this, a few modeling tools were developed for this work: (1) a dynamic model for various components of the turbine and its governor; (2) a control strategy that assigns a slow-varying dispatch signal to a hydropower unit versus a fastmoving signal to ESS, such that the overall power request remains the same; and (3) models for the financial analysis to quantify the economic merits of such a framework. We used the models we developed to analyze the dispatch pattern of an actual hydropower plant with a power output of 50 MW and a head height of 152 m. This work showed that ESS-based hybridization could extend the life of the hydropower plant by 5% on average. This extension in life was then used to estimate the economic benefit in terms of cost deferrals associated with hydropower plant maintenance and replacement: on average, $3.6 million. Sensitivity analysis with respect to the size of ESS and cost of turbines was performed to show the variation in benefits over the range of turbine costs and ESS sizes. Crucially, stacking damage reduction and lifetime extension with other ESS value streams such as providing ancillary services could substantially increase the financial benefits of ESS-based hybridization. The higher costs associated with ESS of appropriate size would make more financial sense when multiple value streams are stacked and co-optimized to extract the maximum benefit. This dimension will be explored in future work.

13 HYDRO ENERGY↗

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗

ASASSN-14ko is a Periodic Nuclear Transient in ESO 253-G003

We present the discovery that ASASSN-14ko is a periodically flaring active galactic nucleus at the center of the galaxy ESO 253-G003. At the time of its discovery by the All-Sky Automated Survey for Supernovae (ASAS-SN), it was classified as a supernova close to the nucleus. The subsequent 6 yr of V - and g -band ASAS-SN observations revealed that ASASSN-14ko has nuclear flares occurring at regular intervals. The 17 observed outbursts show evidence of a decreasing period over time, with a mean period of P 0 = 114.2 ± 0.4 days and a period derivative of . The most recent outburst in 2020 May, which took place as predicted, exhibited spectroscopic changes during the rise and had a UV bright, blackbody spectral energy distribution similar to tidal disruption events (TDEs). The X-ray flux decreased by a factor of 4 at the beginning of the outburst and then returned to its quiescent flux after ~8 days. The Transiting Exoplanet Survey Satellite observed an outburst during Sectors 4–6, revealing a rise time of 5.60 ± 0.05 days in the optical and a decline that is best fit with an exponential model. We discuss several possible scenarios to explain ASASSN-14ko’s periodic outbursts, but currently favor a repeated partial TDE. The next outbursts should peak in the optical on UT 2020 September 7.4±1.1 and UT 2020 December 26.5±1.4.

Astronomy & Astrophysics↗

Characterization of organic aerosol across the global remote troposphere: a comparison of ATom measurements and global chemistry models

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 µg sm -3 ). Lower concentrations (~0.1–0.3 µg sm -3 ) are observed in the northern middle and high latitudes and very low concentrations (<0.1 µg sm -3 ) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the secondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA/OC) ratios of ~2.2–2.8, and is 30 %–60 % more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model–measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗

Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Current Status of Problem 2 in the HTGR T/H Benchmark

Problem 2 of the HTGR T/H Benchmark is for modeling the depressurized conduction cooldown (DCC) transient. This presentation shares the status of code-to-code and code-to-date comparisons (Exercises 1 and 2) of Problem 2 with results from several participants. A key factor in the discrepancy between results and data in Exercise 2 is the assumed power distribution that is used to model PG-29. This talk highlights both the similarities and differences in solutions and discusses areas where further investigation is merited.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Calculating the angle between jet axes

We study the angle between i) the standard jet axis, ii) the axis of a jet which has been groomed using soft drop, with reduced sensitivity to soft radiation, iii) the jet axis obtained with the winner-take-all recombination scheme, which is insensitive to soft radiation at leading power. We calculate the distributions for these angles at next- to-leading logarithmic accuracy, including non-global logarithms. The angle between the standard and groomed jet axis directly probes soft wide-angle radiation, leading to a novel factorization formula. This angle is also very sensitive to nonperturbative physics, which is directly connected to nonperturbative contribution to the rapidity anomalous dimension for transverse momentum distributions. Comparing our predictions to Pythia we find good agreement, and we foresee applications to jet substructure in proton-proton and heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Picturing QCD jets in anisotropic matter: from jet shapes to energy energy correlators

Abstract Recent theoretical developments in the description of jet evolution in the quark gluon plasma have allowed to account for the effects of hydrodynamic gradients in the medium modified jet spectra. These constitute a crucial step towards using jets as tomographic probes of the nuclear matter they traverse. In this work, we complement these studies by providing leading order calculations of widely studied jet observables, taking into account matter anisotropies. We show that the energy distribution inside a jet is pushed towards the direction of the largest matter anisotropy, while the away region is depleted. As a consequence, the jet mass and girth gain a non-trivial azimuthal dependence, with the average value of the distribution increasing along the direction of largest gradients. However, we find that, for these jet shapes, matter anisotropic effects can be potentially suppressed by vacuum Sudakov factors. We argue that the recently proposed measurements of energy correlations within jets do not suffer from such effects, with the azimuthal dependence being visible in a large angular window, regardless of the shape of the distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A two-level GPU-accelerated incomplete LU preconditioner for general sparse linear systems

This paper presents a parallel preconditioning approach based on incomplete LU (ILU) factorizations in the framework of Domain Decomposition (DD) for general sparse linear systems. We focus on distributed memory parallel architectures, specifically, those that are equipped with graphic processing units (GPUs). In addition to block-Jacobi, we present general purpose two-level ILU Schur complement-based approaches, where different strategies are presented to solve the coarse-level reduced system. These strategies are combined with modified ILU methods in the construction of the coarse-level operator, in order to effectively remove smooth errors by targeting an algebraically smooth vector. We leverage available GPU-based sparse matrix kernels to accelerate the setup and the solve phases of the proposed ILU preconditioner. We evaluate the efficiency of the proposed methods as a smoother for algebraic multigrid (AMG) and as a preconditioner for Krylov subspace methods on challenging anisotropic diffusion problems and a collection of general sparse matrices.

97 MATHEMATICS AND COMPUTING↗

Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH

Isobaric labeling via tandem mass tag (TMT) reagents enables sample multiplexing prior to LC–MS/MS, facilitating high-throughput large-scale quantitative proteomics. Consistent and efficient labeling reactions are essential to achieve robust quantification; therefore, embedded in our clinical proteomic protocol is a quality control (QC) sample that contains a small aliquot from each sample within a TMT set, referred to as “Mixing QC.” This Mixing QC enables the detection of TMT labeling issues by LC–MS/MS before combining the full samples to allow for salvaging of poor TMT labeling reactions. While TMT labeling is a valuable tool, factors leading to poor reactions are not fully studied. We observed that relabeling does not necessarily rescue TMT reactions and that peptide samples sometimes remained acidic after resuspending in 50 mM HEPES buffer (pH 8.5), which coincided with low labeling efficiency (LE) and relatively low median reporter ion intensities (MRIIs). To obtain a more resilient TMT labeling procedure, we investigated LE, reporter ion missingness, the ratio of mean TMT set MRII to individual channel MRII, and the distribution of log 2 reporter ion ratios of Mixing QC samples. We discovered that sample pH is a critical factor in LE, and increasing the buffer concentration in poorly labeled samples before relabeling resulted in the successful rescue of TMT labeling reactions. Moreover, resuspending peptides in 500 mM HEPES buffer for TMT labeling resulted in consistently higher LE and lower missing data. By better controlling the sample pH for labeling and implementing multiple methods for assessing labeling quality before combining samples, we demonstrate that robust TMT labeling for large-scale quantitative studies is achievable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Opposing Effects of Impurity Ion Sr 2+ on the Heterogeneous Nucleation and Growth of Barite (BaSO 4 )

Nucleation of barite (BaSO 4 ) has broad implications in geological, environmental, and materials sciences. While impurity metals are common, our understanding of how they impact nucleation remains dim. In this work, we used classical optical microscopy compared to fast X-ray nanotomography (XnT) to investigate heterogeneous nucleation of barite on silica in situ with Sr 2+ as an impurity ion. The observed barite nucleation rates were consistent with classical nucleation theory (CNT), where barite crystals displayed a nonuniform size distribution, exhibiting distinct morphologies and incubation periods in Sr-free solutions. While undetectable with optical microscopy, nanotomography revealed that addition of Sr2+ enhances nucleation rates driven by the pre-factor in CNT, likely because both adsorbed Ba 2+ and Sr 2+ act as precursor sites on which nucleation occurs. Sr 2+ simultaneously inhibits growth, however, leading to a homogeneous distribution of smaller crystals. This finding will enable an improved predictive understanding of nucleation in natural and synthetic environments.

36 MATERIALS SCIENCE↗

QCD Theory and Transverse Momentum Dependent Physics

A major challenge for QCD theorists is to understand how to different categories of QCD physics contribute to a single observable. This is the goal of QCD factorization theory. Today, QCD physicists are tasked with describing increasingly detailed properties of transverse momentum dependent particle distributions, including their shapes and normalizations, their variation with energy and other kinematical variables, the identity of particles involved, correlations with spin, and the relationship between transverse momentum distributions in different processes. Embedded within that broad effort are specific fundamental questions at the heart of QCD theory. Namely, how does one give precise, quantitative meaning to quark and gluon concepts in hard scattering events, and what are the limits of those concepts? In the past two decades, there has been a renaissance in TMD QCD, with a broad spectrum of motivations driving the study of TMD observables. TMD QCD studies are in a transformative stage; subfields that traditionally progressed nearly independently of one other, such as hadronic structure studies and the study of perturbative QCD gluon radiation in high-energy collisions, are becoming intertwined. It is thus becoming increasingly clear that unified approaches -- those that incorporate all the relevant phenomena into a single formalism rooted in QCD fundamentals -- will be critical to the mission to expand the current understanding of QCD nuclear/hadronic dynamics. TMD QCD factorization theorems and their generalizations will be central to these efforts. The factorization theorems, in addition, provide the practical prescription for applying specific calculations to phenomenology. The goal of this project was to unify and push the boundaries of traditional TMD research and prepare it for use in future phenomenological applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Numerical investigation of micro-galvanic corrosion in Mg alloys: Role of the cathodic intermetallic phase size and spatial distributions

Magnesium alloys are of increasing interest in structural applications due to their low-density, moderate specific strength and stiffness, recyclability, and high damping among other properties. However, the wide-scale applicability of magnesium alloys in structural applications has been limited due to many factors including its poor corrosion resistance. In this work, a numerical investigation to simulate the micro-galvanic corrosion behavior was performed to examine the influence of size and distribution of cathodic intermetallic phase (ß-Mg17Al12) in a Mg matrix. The ratio of cathodic to anodic surface area was kept constant in each simulation condition to understand the effect of size and spacing distributions. In general, fragmentation of a larger intermetallic particle into smaller ones was found to enhance the localized current density. However, the uniform distribution of this small intermetallic phase throughout the matrix was found to reduce the overall dissolution current density and hence, pitting corrosion severity.

Beura, Vikrant↗

Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions

Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

54 ENVIRONMENTAL SCIENCES↗

Modeling and Analysing the Impact of Heat Pump Water Heaters on Distribution Systems Using GridLAB-D

With the constant increase in energy demand, finding ways to reduce peak load and the energy-costs factors has become more imperative. Domestic water heating showcases a significant opportunity for such applications. Water heating is the second-highest energy consumer in the residential sector across the United States. Electric Water Heaters (EWHs), in particular, constitute nearly 43% of American household water heating energy consumption. Heat Pump Water Heater (HPWH), on the other hand, are an advanced water heating technology that has recently emerged in the United States residential market. The objectives of this work are to develop a HPWH model and build a case study that evaluates various penetration levels of HPWH in providing reduced peak load and cost-effective energy savings for both utilities and customers. The HPWH model was developed and integrated within the GridLAB-D simulation environment. The model behavior was then validated against a real HPWH unit at Portland State University (PSU). The case studies incorporated five HPWH penetration levels, ranging from 20% to 100%. In each case, EWHs were replaced with HPWHs. The results showed that a high penetration level of HPWHs can reduce the energy consumption on a distribution system to 38%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗

Exploring Transport Behavior in Hybrid Perovskites Solar Cells via Machine Learning Analysis of Environmental-Dependent Impedance Spectroscopy

Hybrid organic–inorganic perovskites are one of the promising candidates for the next-generation semiconductors due to their superlative optoelectronic properties. However, one of the limiting factors for potential applications is their chemical and structural instability in different environments. Herein, the stability of (FAPbI3)0.85(MAPbBr3)0.15 perovskite solar cell is explored in different atmospheres using impedance spectroscopy. An equivalent circuit model and distribution of relaxation times (DRTs) are used to effectively analyze impedance spectra. DRT is further analyzed via machine learning workflow based on the non-negative matrix factorization of reconstructed relaxation time spectra. This exploration provides the interplay of charge transport dynamics and recombination processes under environment stimuli and illumination. The results reveal that in the dark, oxygen atmosphere induces an increased hole concentration with less ionic character while ionic motion is dominant under ambient air. Under 1 Sun illumination, the environment-dependent impedance responses show a more striking effect compared with dark conditions. In this case, the increased transport resistance observed under oxygen atmosphere in equivalent circuit analysis arises due to interruption of photogenerated hole carriers. The results not only shed light on elucidating transport mechanisms of perovskite solar cells in different environments but also offer an effective interpretation of impedance responses.

36 MATERIALS SCIENCE↗