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Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

V-HAMSTeR v1.0.0

V-HAMSTeR is a bioinformatics software tool designed to predict the hosts of viruses directly from genomic sequences. It can be used by researchers to predict animal, prokaryotic, plant, protist or fungal viral hosts including viruses that may be fragmented or discovered in environmental metagenomic datasets. Features & Uses: The software employs a novel dual-stream deep learning architecture that dynamically fuses implicit sequence embeddings from a genomic foundation model with 13 explicit, handcrafted biological features (e.g., coding density and strand switch rates). To ensure maximum reliability, V=HAMSTeR deploys a 5-fold deep ensemble calibrated via Joint Temperature Scaling, providing users with statistically rigorous confidence probabilities. It also features an automated sequence chunking and mean-pooling module to seamlessly process variable-length contigs. Advantages Over Similar Technologies: Existing tools (e.g., IPEV, RNAVirHost) typically rely on either basic k-mers or isolated neural networks. V-HAMSTeR's hybrid architecture captures both broad genomic context and specific biological motifs that standalone foundation models often miss. Furthermore, unlike competitor tools that struggle with incomplete data or exhibit extreme overconfidence, V-HAMSTeR is explicitly benchmarked and mathematically calibrated for fragmented assemblies (1kb–10kb). This makes it uniquely robust, accurate, and trustworthy for the messy reality of real-world environmental viromics.

Grigson, Susie [Lawrence Berkeley National Laborat↗

The North American Monsoon GPS Transect Experiment 2013

Northwestern Mexico experiences large variations in water vapor on seasonal time scales in association with the North American monsoon, as well as during the monsoon associated with upper-tropospheric troughs, mesoscale convective systems, tropical easterly waves, and tropical cyclones. Together these events provide more than half of the annual rainfall to the region. A sufficient density of meteorological observations is required to properly observe, understand, and forecast the important processes contributing to the development of organized convection over northwestern Mexico. The stability of observations over long time periods is also of interest to monitor seasonal and longer-time-scale variability in the water cycle. For more than a decade, the U.S. Global Positioning System (GPS) has been used to obtain tropospheric precipitable water vapor (PWV) for applications in the atmospheric sciences. There is particular interest in establishing these systems where conventional operational meteorological networks are not possible due to the lack of financial or human resources to support the network. We provide an overview of the North American Monsoon GPS Transect Experiment 2013 in northwestern Mexico for the study of mesoscale processes and the impact of PWV observations on high-resolution model forecasts of organized convective events during the 2013 monsoon. Some highlights are presented, as well as a look forward at GPS networks with surface meteorology (GPS-Met) planned for the region that will be capable of capturing a wider range of water vapor variability in both space and time across Mexico and into the southwestern United States.

58 GEOSCIENCES↗

Simulating the role of surface forcing on observed multidecadal upper-ocean salinity changes

The ocean’s surface salinity field has changed over the observed record, driven by an intensification of the water cycle in response to global warming. However, the origin and causes of the coincident subsurface salinity changes are not fully understood. The relationship between imposed surface salinity and temperature changes and their corresponding subsurface changes is investigated using idealized ocean model experiments. The ocean’s surface has warmed by about 0.5°C (50 yr) –1 while the surface salinity pattern has amplified by about 8% per 50 years. The idealized experiments are constructed for a 50-yr period, allowing a qualitative comparison to the observed salinity and temperature changes previously reported. The comparison suggests that changes in both modeled surface salinity and temperature are required to replicate the three-dimensional pattern of observed salinity change. The results also show that the effects of surface changes in temperature and salinity act linearly on the changes in subsurface salinity. In addition, surface salinity pattern amplification appears to be the leading driver of subsurface salinity change on depth surfaces; however, surface warming is also required to replicate the observed patterns of change on density surfaces. This is the result of isopycnal migration modified by the ocean surface warming, which produces significant salinity changes on density surfaces.

54 ENVIRONMENTAL SCIENCES↗

Herbaceous Feedstock 2018 State of Technology Report

The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and elsewhere (such as the High-Tonnage Feedstock Logistics projects (Webb et al. 2013a, Webb et al. 2013b, Webb et al. 2013c, Webb and Sokhansanj 2014, Sokhansanj et al. 2014) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D improvements to individual supply system unit operations, and present the status of feedstock logistics technology development for converting biomass into biofuels. These analyses are supported by experimental data where possible, and help to align the SOT relative to the cost goals defined in the Multi-Year Program Plan. The 2018 Herbaceous SOT aligned feedstock logistic design with current biorefinery’s design capacity utilized by biochemical conversion platform. Currently biochemical conversion platform utilizes a 725,000 dry ton/year biorefiney design for the techno economic analysis. Hence, feedstock delivered cost in the 2018 Herbaceous SOT is calculated based on biorefinery’s 725,000 dry ton design capacity instead of 800, 000 dry ton capacity utilized in the 2017 Herbaceous SOT. Biomass availabilities in this SOT were updated to year 2018 data from the 2016 Billion-Ton Report (BT16) (DOE 2016a), with the exception of switchgrass, for which the 2018 Herbaceous SOT utilized the 2019 switchgrass availability data from BT16. The BT16 report (DOE 2016a) does not project switchgrass availability in 2018; the soonest switchgrass is available in the BT16 report is 2019. Therefore, availability of switchgrass for this analysis was that projected for 2019. The 2018 Herbaceous SOT incorporates same technologies utilized in the 2017 Herbaceous SOT. However, a sensitivity analysis is performed to understand the impact of variation of process parameters on those technologies on feedstock logistic cost. New R&D data that shows the variations of process parameters affecting process performance is incorporated in the 2018 SOT to measure the variations in delivered feedstock cost. The 2018 Herbaceous SOT has also provided projected delivered feedstock of 2022 design case based on near term technical target under BETO funded R&D project. Finally, updated biorefinery size of 725,000 dry ton/year was incorporated within least-cost formulation model to select optimal siting and depot scales during optimization of the least cost blend. This modification to the optimization algorithm allows the trade-off between the cost of increased supply radius and the savings from selecting biomass from higher producing counties to be assessed. Such optimization has also showed the economic benefit of decentralized depots in comparison to centralized preprocessing co-located with the biorefinery by decoupling the biorefinery and feedstock locations. The 2018 Herbaceous SOT report documents the current modeled cost of a herbaceous feedstock supply system (from harvest to the pretreatment reactor throat, including grower payment) for hydrocarbon fuel production via biochemical conversion, based on equipment and processes now available or potentially available in the near term. The modeled cost also considers both the required quality and the availability of the biomass resources. The 2018 Herbaceous SOT predicts a modeled delivered feedstock cost of $83.67/dry ton (2016$); this is a $0.23/dry ton (2016$) decrease from the 2017 Herbaceous SOT. The modification of biorefinery’s designed capacity and increased projected biomass availability in the same supply shed contributed to this modeled cost reduction. The least-cost formulation model to optimally site and scale local distributed preprocessing depots also contributed to the cost reduction by considering county-level grower payment and distance from the biorefinery as variables in the optimization algorithm. Sensitivity analysis on various process parameters that affect delivered feedstock cost in the 2018 Herbaceous SOT shows that the delivered cost could varies from $80.45-$88.83/dry ton. The top factors that causes such variations are: effective baling rate, bale density, hammer mill throughput, interest rate and storage dry matter loss.

09 BIOMASS FUELS↗

Combined Effects of Carbon and Nitrogen Source to Optimize Growth of Proteobacterial Methanotrophs

Methane, a potent greenhouse gas, and methanol, commonly called wood alcohol, are common by-products of modern industrial processes. They can, however, be consumed as a feedstock by bacteria known as methanotrophs, which can serve as useful vectors for biotransformation and bioproduction. Successful implementation in industrial settings relies upon efficient growth and bioconversion, and the optimization of culturing conditions for these bacteria remains an ongoing effort, complicated by the wide variety of characteristics present in the methanotroph culture collection. Here, we demonstrate the variable growth outcomes of five diverse methanotrophic strains - Methylocystis sp. Rockwell, Methylocystis sp. WRRC1, Methylosinus trichosporium OB3b, Methylomicrobium album BG8, and Methylomonas denitrificans FJG1 - grown on either methane or methanol, at three different concentrations, with either ammonium or nitrate provided as nitrogen source. Maximum optical density (OD), growth rate, and biomass yield were assessed for each condition. Further metabolite and fatty acid methyl ester (FAME) analyses were completed for Methylocystis sp. Rockwell and M. album BG8. The results indicate differential response to these growth conditions, with a general preference for ammonium-based growth over nitrate, except for M. denitrificans FJG1. Methane is also preferred by most strains, with methanol resulting in unreliable or inhibited growth in all but M. album BG8. Metabolite analysis points to monitoring of excreted formic acid as a potential indicator of adverse growth conditions, while the magnitude of FAME variation between conditions may point to strains with broader substrate tolerance. These findings suggest that methanotroph strains must be carefully evaluated before use in industry, both to identify optimal conditions and to ensure the strain selected is appropriate for the process of interest. As a result, much work remains in addressing the optimization of growth strategies for these promising microorganisms since disregarding these important steps in process development could ultimately lead to inefficient or failed bioprocesses.

09 BIOMASS FUELS↗

Unexpected series of regular frequency spacing of δ Scuti stars in the non-asymptotic regime. II. Sample-Echelle diagrams and rotation

A sequence search method was developed for searching for regular frequency spacing in δ Scuti stars by visual inspection (VI) and algorithmic search. The sample contains 90 δ Scuti stars observed by CoRoT. An example is given to represent the VI. The algorithm (SSA) is described in detail. The data treatment of the CoRoT light curves, the criteria for frequency filtering, and the spacings derived by two methods (i.e., three approaches: VI, SSA, and FT) are given for each target. Echelle diagrams are presented for 77 targets for which at least one sequence of regular spacing was identified. Comparing the spacing and the shifts between pairs of echelle ridges revealed that at least one pair of echelle ridges is shifted to midway between the spacing for 22 stars. The estimated rotational frequencies compared to the shifts revealed rotationally split doublets, triplets, and multiplets not only for single frequencies, but for the complete echelle ridges in 31 δ Scuti stars. Furthermore, using several possible assumptions for the origin of the spacings, we derived the large separation (${\rm{\Delta }}\nu $) that are distributed along the mean density versus large separations relation derived from stellar models.

79 ASTRONOMY AND ASTROPHYSICS↗

JVLA Observations of Young Brown Dwarfs

We present sensitive 3.0 cm JVLA radio continuum observations of six regions of low-mass star formation that include twelve young brown dwarfs (BDs) and four young BD candidates. We detect a total of 49 compact radio sources in the fields observed, of which 24 have no reported counterparts and are considered new detections. Twelve of the radio sources show variability in timescales of weeks to months, suggesting gyrosynchrotron emission produced in active magnetospheres. Only one of the target BDs, FU Tau A, was detected. However, we detected radio emission associated with two of the BD candidates, WL 20S and CHLT 2. The radio flux densities of the sources associated with these BD candidates are more than an order of magnitude larger than expected for a BD and suggest a revision of their classification. In contrast, FU Tau A falls on the well-known correlation between radio luminosity and bolometric luminosity, suggesting that the emission comes from a thermal jet and that this BD seems to be forming as a scaled-down version of low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗

A White Dwarf with Transiting Circumstellar Material Far outside the Roche Limit

We report the discovery of a white dwarf exhibiting deep, irregularly shaped transits, indicative of circumstellar planetary debris. Using Zwicky Transient Facility DR2 photometry of ZTF J013906.17+524536.89 and follow-up observations from the Las Cumbres Observatory, we identify multiple transit events that recur every ≈107.2 days, much longer than the 4.5–4.9 hr orbital periods observed in WD 1145+017, the only other white dwarf known with transiting planetary debris. The transits vary in both depth and duration, lasting 15–25 days and reaching 20%–45% dips in flux. Optical spectra reveal strong Balmer lines, identifying the white dwarf as a DA with ${T}_{\mathrm{eff}}=10,530\pm 140\,{\rm{K}}$ and $\mathrm{log}(g)=7.86\pm 0.06$. A Ca ii K absorption feature is present in all spectra both in and out of transit. Spectra obtained during one night at roughly 15% transit depth show increased Ca ii K absorption with a model atmospheric fit suggesting [Ca/H] = –4.6 ± 0.3, whereas spectra taken on three nights out of transit have [Ca/H] of –5.5, –5.3, and –4.9 with similar uncertainties. While the Ca ii K line strength varies by only 2σ, we consider a predominantly interstellar origin for Ca absorption unlikely. Here, we suggest a larger column density of circumstellar metallic gas along the line of site or increased accretion of material onto the white dwarf's surface are responsible for the Ca absorption, but further spectroscopic studies are required. In addition, high-speed time series photometry out of transit reveals variability with periods of 900 and 1030 s, consistent with ZZ Ceti pulsations.

79 ASTRONOMY AND ASTROPHYSICS↗

THE FIRST DETECTION OF GeV EMISSION FROM AN ULTRALUMINOUS INFRARED GALAXY: Arp 220 AS SEEN WITH THE FERMI LARGE AREA TELESCOPE

Cosmic rays (CRs) in starburst galaxies produce high-energy gamma-rays by colliding with the dense interstellar medium. Arp 220 is the nearest ultraluminous infrared galaxy that has star formation at extreme levels, so it has long been predicted to emit high-energy gamma-rays. However, no evidence of gamma-ray emission was found despite intense search efforts. Here we report the discovery of high-energy gamma-ray emission above 200 MeV from Arp 220 at a confidence level of ∼6.3σ using 7.5 years of Fermi Large Area Telescope observations. The gamma-ray emission shows no significant variability over the observation period and it is consistent with the quasi-linear scaling relation between the gamma-ray luminosity and total infrared luminosity for star-forming galaxies, suggesting that these gamma-rays arise from CR interactions. As the high-density medium of Arp 220 makes it an ideal CR calorimeter, the gamma-ray luminosity can be used to measure the efficiency of powering CRs by supernova (SN) remnants given a known supernova rate in Arp 220. We find that this efficiency is about 4.2 ± 2.6% for CRs above 1 GeV.

79 ASTRONOMY AND ASTROPHYSICS↗

SIMP J013656.5+093347 is likely a planetary-mass object in the carina-near moving group

We report on the discovery that the nearby (∼6 pc) photometrically variable T2.5 dwarf SIMP J013656.5+093347 is a likely member of the ∼200 Myr old Carina-Near moving group with a probability of >99.9% based on its full kinematics. Our vsin i measurement of 50.9 ± 0.8 km s{sup −1} combined with the known rotation period inferred from variability measurements provide a lower limit of 1.01 ± 0.02 R{sub Jup} on the radius of SIMP 0136+0933, an independent verification that it must be younger than ∼950 Myr, according to evolution models. We estimate a field interloper probability of 0.2% based on the density of field T0–T5 dwarfs. At the age of Carina-Near, SIMP 0136+0933 has an estimated mass of 12.7 ± 1.0 M{sub Jup} and is predicted to have burned roughly half of its original deuterium. SIMP 0136+0933 is the closest known young moving group member to the Sun and is one of only a few known young T dwarfs, making it an important benchmark for understanding the atmospheres of young planetary-mass objects.

79 ASTRONOMY AND ASTROPHYSICS↗

Using Willingness to Pay to Forecast the Adoption of Solar Photovoltaics: A ''Parameterization + Calibration'' Approach

Distributed energy resources, such as rooftop solar photovoltaics (PV), are likely to comprise a substantial fraction of new generation capacity in the United States. However, forecasting technology adoption based on people's willingness to pay (WTP) faces two major challenges: the stated-intention and omitted-variable biases. Previous solar adoption literature has neglected to address these two biases altogether. Here, we adopt a 'parameterization + calibration' approach to address both biases and estimate customers' WTP for PV. After collecting survey data on respondents' WTP for adopting PV, we characterize its empirical cumulative density function using a gamma distribution. We further calibrate the gamma distribution parameters using a national distributed PV adoption simulation model, finding the parameters that produce the best fit between simulated and historic solar adoption. We then show that the calibrated gamma distribution improves the raw WTP data after correcting for the two biases. Finally, we use our optimally-calibrated WTP to forecast market demand for residential PV at the county-level of the United States in 2020. Improving estimates of customer willingness to pay has significant implications for policy directly, e.g. estimating the effect of a proposed policy on technology adoption, and other regulatory processes that use forecasting, e.g. integrated resource planning.

14 SOLAR ENERGY↗

A mathematical and numerical framework for the analysis of compressible thermal convection in gases at very high temperatures

The relevance of non-equilibrium phenomena, nonlinear behavior, gravitational effects and fluid compressibility in a wide range of problems related to high-temperature gas-dynamics, especially in thermal, mechanical and nuclear engineering, calls for a concerted approach using the tools of the kinetic theory of gases, statistical physics, quantum mechanics, thermodynamics and mathematical modeling in synergy with advanced numerical strategies for the solution of the Navier–Stokes equations. The reason behind such a need is that in many instances of relevance in this field one witnesses a departure from canonical models and the resulting inadequacy of standard CFD approaches, especially those traditionally used to deal with thermal (buoyancy) convection problems. Starting from microscopic considerations and typical concepts of molecular dynamics, passing through the Boltzmann equation and its known solutions, we show how it is possible to remove past assumptions and elaborate an algorithm capable of targeting the broadest range of applications. Moving beyond the Boussinesq approximation, the Sutherland law and the principle of energy equipartition, the resulting method allows most of the fluid properties (density, viscosity, thermal conductivity, heat capacity and diffusivity, etc.) to be derived in a rational and natural way while keeping empirical contamination to the minimum. Special attention is deserved as well to the well-known pressure issue. With the application of the socalled multiple pressure variables concept and a projection-like numerical approach, difficulties with such a term in the momentum equation are circumvented by allowing the hydrodynamic pressure to decouple from its thermodynamic counterpart. The final result is a flexible and modular framework that on the one hand is able to account for all the molecule (translational, rotational and vibrational) degrees of freedom and their effective excitation, and on the other hand can guarantee adequate interplay between molecular and macroscopic-level entities and processes. Performances are demonstrated by computing some incompressible and compressible benchmark test cases for thermal (gravitational) convection, which are then extended to the high-temperature regime taking advantage of the newly developed features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaluation of performance indicators applied to a material recovery facility fed by mixed packaging waste

Highlights: • Material Flows assessment of a Material Recovery Facility has been realized. • Performance Indicators for a generic MRF have been proposed. • A Dashboard has been utilized to measure the facility performance. • Experimental values of incoming waste and output products composition are reported. - Abstract: Most of the integrated systems for municipal solid waste management aim to increase the recycling of secondary materials by means of physical processes including sorting, shredding and reprocessing. Several restrictions prevent from reaching a very high material recycling efficiency: the variability of the composition of new-marketed materials used for packaging production and its shape and complexity are critical issues. The packaging goods are in fact made of different materials (aluminium, polymers, paper, etc.), possibly assembled, having different shape (flat, cylindrical, one-dimensional, etc.), density, colours, optical properties and so on. These aspects limit the effectiveness and efficiency of the sorting and reprocessing plants. The scope of this study was to evaluate the performance of a large scale Material Recovery Facility (MRF) by utilizing data collected during a long period of monitoring. The database resulted from the measured data has been organized in four sections: (1) data related to the amount and type of inlet waste; (2) amount and composition of output products and waste; (3) operating data (such as worked hours for shift, planned and unscheduled maintenance time, setting parameters of the equipment, and energy consumption for shift); (4) economic data (value of each product, disposal price for the produced waste, penalty for non-compliance of products and waste, etc.). A part of this database has been utilized to build an executive dashboard composed by a set of performance indicators suitable to measure the effectiveness and the efficiency of the MRF operations. The dashboard revealed itself as a powerful tool to support managers and engineers in their decisions in respect to the market demand or compliance regulation variation as well as in the designing of the lay-out improvements. The results indicated that the 40% of the input waste was recovered as valuable products and that a large part of these (88%) complied with the standards of the recycling companies. The evaluation of the indicators led to the decision to modify the layout to improve the interception of some polymers for which the performance indicators were poor. In particular, two additional optical sorters have to be inserted to increase the yield indicator and to the overall performance of the facility. Definitely, the results of the work allowed to: increase the yield and purity of products’ flows; ensure the compliance of waste flows; increase the workability.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Forward Modeling of 3-D Ion Properties in Jupiter’s Magnetosphere Using Juno/JADE-I Data

The Jovian Auroral Distributions Experiment Ion sensor (JADE-I) on NASA’s Juno mission provides in-situ measurements of ions from 0.1 to 46.2 keV/q inside Jupiter’s magnetosphere. JADE-I is used to study the plasma with two types of datasets from the same measurement: Time-of-flight (TOF) and SPECIES. The TOF dataset provides mass-per-charge measurements with a range of 1–64 amu/q but oversamples particles over 6π steradian viewing per spacecraft spin and has little directional information. On the other hand, the SPECIES dataset can provide a good measurement of the flow direction but does not provide mass-per-charge information due to the telemetry limit. In this study, we developed a 2-step forward modeling method that combines the advantages and avoids the disadvantages of TOF and SPECIES data to derive the 3-D properties of heavy ions. Assuming that the ion velocity distribution can be described with the kappa distribution, we first perform the forward model fit of the TOF data to calculate the relative abundance of heavy ion species. Then we fix the relative abundance and perform the second forward model fit on the SPECIES data. Here, using this method, we obtain the densities of different heavy ions, the shared temperature and kappa value, and the 3-D flow velocity vector. Some data examples of the equatorial plasma disk before Perijove 24 are included to demonstrate the method. Plasma properties can then be mapped to explore spatial and temporal variabilities in Jupiter’s magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Climate-Related Trends of Within-Storm Intensities Using Dimensionless Temporal-Storm Distributions

Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. As such, the goal of this paper is to fill this gap by studying Huff curve patterns in a watershed with demonstrated increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve this goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km 2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939 to 2010 were investigated using dimensionless depth (with the frequency of 50%, $d_{50}$) and the curve variability $(V = d_{80} - d_{20})$ at three dimensionless within-storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ρ and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ρ and p were computed: (1) by averaging the individual ρ and p obtained from 10 gauges (AvgI); and (2) by grouped averaging of all individual gauge values of $d_{50}$ and V and then computing ρ and p (AvgG). The test results of individual gauges showed that 4 cases for $d_{50}$ and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for $d_{50}$ and V and AvgG for $d_{50}$ showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is insufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ρ of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V; however, this analysis may be affected by the nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.

54 ENVIRONMENTAL SCIENCES↗

Random center vortex lines in continuous 3D space-time

We present a model of center vortices, represented by closed random lines in continuous 2+1-dimensional space-time. These random lines are modeled as being piece-wise linear and an ensemble is generated by Monte Carlo methods. The physical space in which the vortex lines are defined is a cuboid with periodic boundary conditions. Besides moving, growing and shrinking of the vortex configuration, also reconnections are allowed. Our ensemble therefore contains not a fixed, but a variable number of closed vortex lines. This is expected to be important for realizing the deconfining phase transition. Using the model, we study both vortex percolation and the potential V(R) between quark and anti-quark as a function of distance R at different vortex densities, vortex segment lengths, reconnection conditions and at different temperatures. We have found three deconfinement phase transitions, as a function of density, as a function of vortex segment length, and as a function of temperature. The model reproduces the qualitative features of confinement physics seen in SU(2) Yang-Mills theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗