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At least 199 records · Page 11

Early-time measure in eternal inflation

In a situation like eternal inflation, where our data is replicated at infinitely-many other space-time events, it is necessary to make a prior assumption about our location to extract predictions. The principle of mediocrity entails that we live at asymptotic late times, when the occupational probabilities of vacua has settled to a near-equilibrium distribution. In this paper we further develop the idea that we instead exist during the approach to equilibrium, much earlier than the exponentially-long mixing time. In this case we are most likely to reside in vacua that are easily accessed dynamically. Using first-passage statistics, we prove that vacua that maximize their space-time volume at early times have: 1. maximal ever-hitting probability; 2. minimal mean first-passage time; and 3. minimal decay rate. These requirements are succinctly captured by an early-time measure. The idea that we live at early times is a predictive guiding principle, with many phenomenological implications. First, our vacuum should lie deep in a funneled region, akin to folding energy landscapes of proteins. Second, optimal landscape regions are characterized by relatively short-lived vacua, with lifetime of order the de Sitter Page time. For our vacuum, this lifetime is ~ 10 130 years, which is consistent with the Standard Model estimate due to Higgs metastability. Third, the measure favors vacua with small, positive vacuum energy. This can address the cosmological constant problem, provided there are sufficiently many vacua in the entire ensemble of funnels. As a concrete example, we study the Bousso-Polchinski lattice of flux vacua, and find that the early-time measure favors lattices with the fewest number of flux dimensions. This favors compactifications with a large hierarchy between the lightest modulus and all other Kähler and complex structure moduli.

79 ASTRONOMY AND ASTROPHYSICS↗

Impurity transport in ion- and electron-root confinement scenarios at Wendelstein 7-X

This paper reports on the observation of enhanced Ar impurity confinement in high density, turbulence reduced ion-root confinement (IRC) scenarios in Wendelstein 7-X (W7-X). Compared to the central electron-root confinement (CERC), Ar densities are substantially increased up to one order of magnitude and Ar flux profiles switch from slightly positive to pronounced negative fluxes all along the plasma radius in IRC. Estimations of the diffusive D and convective V transport parameter profiles using the STRAHL impurity transport code suggest a fundamentally different behavior in CERC and IRC with, compared to neoclassical values, high diffusive D and typical V profiles in CERC versus strongly reduced D and pronounced negative V profiles in IRC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Single-Spin Readout and Quantum Sensing Using Optomechanically Induced Transparency

Solid-state spin defects are promising quantum sensors for a large variety of sensing targets. Some of these defects couple appreciably to strain in the host material. We propose to use this strain coupling for mechanically mediated dispersive single-shot spin readout by an optomechanically induced transparency measurement. Surprisingly, the estimated measurement times for negatively charged silicon-vacancy defects in diamond are an order of magnitude shorter than those for single-shot optical fluorescence readout. Here, our scheme can also be used for general parameter-estimation metrology and offers a higher sensitivity than conventional schemes using continuous position detection.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Combining lattice QCD and phenomenological inputs on generalised parton distributions at moderate skewness

Abstract We present a systematic study demonstrating the impact of lattice QCD data on the extraction of generalised parton distributions (GPDs). For this purpose, we use a previously developed modelling of GPDs based on machine learning techniques fulfilling the theoretical requirements of polynomiality, a form of positivity constraint and known reduction limits. A special care is given to estimate the uncertainty stemming from the ill-posed character of the connection between GPDs and the experimental processes usually considered to constrain them, like deeply virtual Compton scattering (DVCS). Moke lattice QCD data inputs are included in a Bayesian framework to a prior model based on an Artificial Neural Network. This prior model is fitted to reproduce the most experimentally accessible information of a phenomenological extraction by Goloskokov and Kroll. We highlight the impact of the precision, correlation and kinematic coverage of lattice data on GPD extraction at moderate $$\xi $$ ξ which has only been brushed in the literature so far, paving the way for a joint extraction of GPDs.

Physics↗

First Principles Determination of the Potential-of-Zero-Charge in an Alumina-Coated Aluminum/Water Interface Model for Corrosion Applications

The surfaces of most metals immersed in aqueous electrolytes have a several-nanometer-thick oxide/hydroxide surface layer. This gives rise to the existence of both metal|oxide and oxide|liquid electrotlyte interfaces, and makes it challenging to correlate atomic length-scale structures with electrochemical properties such the potential-of-zero-charge (PZC). The PZC has been shown to be correlated the onset potential for pitting corrosion. Here, we conduct large-scale Density Functional Theory and ab initio molecular dynamics to calculate the PZC of a Al(111)| γ -Al 2 O 3 (110)| water double-interface model within the context of aluminum corrosion. By partitioning the multiple interfaces involved into binary components with additive contributions to the overall work function and voltage, we predict the PZC to be -1.53 V vs SHE for this model. Furthermore, we calculate the orbital energy levels of defects like oxygen vacancies in the oxide, which are critical parameters in theories associated with pitting corrosion. We predict that the Fermi level at the PZC lies above the impurity defect levels of the oxygen vacancies, which are therefore uncharged at the PZC. From the PZC estimate, we predict the voltage needed to create oxygen vacancies with net positive charges within a flatband approximation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BOILER Experiment Material Characterization and HFIR Irradiation Status

Pre-oxidized alumina-forming austenitic (AFA) steels have been previously identified as candidate alloys for structural components in lead-cooled fast reactors (LFRs). They offer compatibility with liquid Pb, high-temperature strength, formability, and cost advantages. However, variations in Ni content can affect the formation and stability of the Al 2 O 3 layer, influencing compatibility with liquid Pb. The effect of fast neutron irradiation on Al 2 O 3 stability in liquid Pb also requires evaluation. Therefore, understanding how Ni concentrations impacts pre-oxidized AFAs under combined extremes of irradiation and liquid metal corrosion is essential before safe deployment. The Behavior Of In-situ Lead Environments & Radiation (BOILER) experiment was developed under the Nuclear Science User Facilities (NSUF) program to integrate alloy development, irradiation experiment design, and irradiated materials characterization. In this effort, two pre-oxidized AFA steels with 20 wt% and 25 wt% Ni, hereinafter referred to as GA05-20Ni and GA05-25Ni, were produced. An irradiation experiment was then planned for the High Flux Isotope Reactor (HFIR), designed for passive heating of irradiation rabbit capsules from gamma heating in the HFIR flux trap (1 × 10 15 n/cm 2 ·s, >0.1 MeV). This heating melts Pb and exposes the pre-oxidized AFA steel specimens to nominal temperatures of 400 and 650°C. Detailed neutronics and thermal analyses were performed, though based on nominal design rather than as-built, as-irradiated conditions. This report documents further characterization of the pre-oxidized AFAs in the unirradiated condition. It also includes as-built thermal analysis using measured component dimensions, updated fill gas concentrations, and actual HFIR irradiation positions. Finally, the report summarizes capsule fabrication, current irradiation status, projected completion, estimated damage accumulation, and initial plans for post-irradiation examination plans.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Challenging a Global Land Surface Model in a Local Socio-Environmental System

Land surface models (LSMs) predict how terrestrial fluxes of carbon, water, and energy change with abiotic drivers to inform the other components of Earth system models. Here, we focus on a single human-dominated watershed in southwestern Michigan, USA. We compare multiple processes in a commonly used LSM, the Community Land Model (CLM), to observational data at the single grid cell scale. For model inputs, we show correlations (Pearson’s R) ranging from 0.46 to 0.81 for annual temperature and precipitation, but a substantial mismatch between land cover distributions and their changes over time, with CLM correctly representing total agricultural area, but assuming large areas of natural grasslands where forests grow in reality. For CLM processes (outputs), seasonal changes in leaf area index (LAI; phenology) do not track satellite estimates well, and peak LAI in CLM is nearly double the satellite record (5.1 versus 2.8). Estimates of greenness and productivity, however, are more similar between CLM and observations. Summer soil moisture tracks in timing but not magnitude. Land surface reflectance (albedo) shows significant positive correlations in the winter, but not in the summer. Looking forward, key areas for model improvement include land cover distribution estimates, phenology algorithms, summertime radiative transfer modelling, and plant stress responses.

54 ENVIRONMENTAL SCIENCES↗

Identification of Possible Stellar Companions via Speckle Interferometry in a Sample of Be Stars

We present speckle interferometric measurements of Be stars made with the 1.60 m Perkin-Elmer telescope at the Pico dos Dias Observatory of the Laboratório Nacional de Astrofísica in Brazil. Using three different filters (V, R, and I), we obtained astrometric measurements for 23 stars, during three observing runs allocated in 2017 March, 2018 April, and 2019 July. We identified pairs with angular separation ranging from 0.″10 to 6.″69, including six systems with separations smaller than 1.″0. We estimated a mean error in separation of 15 mas, 1.°2 in position angle, and 0.29 mag for the magnitude difference. We discovered three new possible double systems that are not identified in the literature: HD 174886, HD 159032, and HD 168135 with an average angular separation of 0.″20, 3.″23, and 5.″41, respectively. In addition, we identified four new pairs in multiple systems previously known in the Washington Double Star Catalog. However, for 16 stars of our sample, we did not find evidence of binarity, based on the diffraction-limited resolution, the field of view, and/or the sensitivity of our observations. From the cross-match with data from Gaia Data Release 2, we verified the possibility of some of these systems be gravitationally bound or not.

79 ASTRONOMY AND ASTROPHYSICS↗

Towards a Robust Sampling Approach: A Computational Review and Design

As pointed out in several other works, the estimation of the reliability of the electrical grid can not be conducted without the estimation of the stochastic phenomena of electicity demand and electricity production by variable renewable sources. Therefore, sampling procedures have become integral in the design of engineering structures and analysis. Commonly referred to as Monte Carlo uncertainty analysis or integration, the general objective of these procedures is to establish specifics about the uncertainty of an output characteristic of such an engineering system, given uncertainty about its input characteristics. These sampling procedures are applied in a context in which establishing such specifics cannot be performed through other means. Variance-reduction techniques are designed to lessen the variability among estimators to estimate statistics of those output uncertainties. Importance-sampling techniques, on the other hand, are designed to reduce the number of samples needed to estimate a particular statistic—e.g., a tail probability. The combination of these approaches can reduce the computational burden considerably for a particular estimator and statistic. Importance sampling—geared and designed as it is toward improving a particular estimator—suffers, unfortunately, from the unintended consequence of reducing the performance of other estimators in terms of their variance. The objective of this paper is to offer an alternative sampling procedure where this variance does not grow unacceptably large for a suite of estimators. Moreover, it is anticipated that, with additional knowledge of how an engineering output characteristic responds to its input characteristics, tuning parameters of the input’s sampling procedure can be set to improve the output characteristic’s estimation. This work proves the effectiveness of the suggested alternative approach. Such positive outcome will lead to a decrease of the computational burden of performing stochastic optimization of integrated energy systems (e.g., components dispatch, and portfolio composition). In particular, capturing the contribution to the overall system cost of rare and unlikely events and patterns of the electricity demand and production will become less computationally expensive. This is due to the fact that the approach demonstrated here will allow the sampling of those rare occurrences more frequently without misrepresenting their probabilistic impacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A VOI Web Application for Distinct Geothermal Domains: Statistical Evaluation of Different Data Types within the Great Basin

The Great Basin region contains different domains that have different structural and hydrothermal flow patterns. Depending on the characteristics of these patterns, certain data types may be more successful at detecting hidden geothermal resources. In this paper, we quantitatively evaluate if certain data types are more successful in certain domains. Given different aquifer, strain and structural conditions, we explore which data types statistically reveal positively labeled geothermal sites. We utilize value of information (VOI) metrics to help quantify the reliability of data types to discriminate against "positive" and "negative" labeled geothermal sites. We also evaluate how kernel density estimation can help generalize the statistics that inform VOI, which is necessary given the limited data in geothermal exploration. Except for the Carbonate Aquifer, the highest ranking of the Vimperfect is the Local Structural Setting. Next, the slip and dilation tendency is first for Carbonate Aquifer and second for Central Nevada Seismic Belt and Western Great Basin. For the Carbonate Aquifer, heat flow is has the lowest Vimperfect value compared to the other three domains, which is consistent with the understanding of how heat flow measurements are masked by regional groundwater flow.

Bayesian analysis↗

Single reader between-cases AUC estimator with nested data

The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.

Health Care Sciences & Services↗

A Test Bed for Evaluating Frequency Estimation Algorithms in Synthetic Inertia Control: User Manual

As penetration of converter interfaced generators (CIGs) increases, the need for CIG frequency control participation increases. Traditionally, research in this area has been performed using positive sequence simulation software, which provides voltage magnitude and phase measurements, but not point-on-wave (POW) measurements. This means that the effect of frequency estimation algorithms cannot be accurately modeled, especially when the voltage waveform is distorted by faults or load connection events. This report serves as a user manual for an electromagnetic transient simulation testbed, which allows for accurate modeling of frequency estimation and control techniques.

42 ENGINEERING↗

Data-Driven Adaptive Damping Controller for Wind Power Plants with Doubly-Fed Induction Generators

This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.

damping controller↗

Data-Driven Adaptive Damping Controller for Wind Power Plants with Doubly-Fed Induction Generators: Preprint

This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.

61 RADIATION PROTECTION AND DOSIMETRY↗

Estimated capital costs of fish exclusion technologies for hydropower facilities

Hydropower is a reliable source of renewable energy, and its future expansion is likely to be in the form of either smaller new stream development (NSD) projects or powering existing non-powered dams. Thresholds for entrainment risk to fish and the requirements for fish exclusion at hydropower facilities often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders, but little quantitative information is present within the literature regarding the specific costs of fish exclusion measures. Cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening were identified using keyword searches of an existing environmental mitigation cost data set and manual extraction from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 p.m.&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens and represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with NSD projects. Results indicate highly variable costs are associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1–2 in.). These data provide an initial baseline for estimating exclusion costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects.

13 HYDRO ENERGY↗

Sensor Drift Estimation for Reactor Systems by Fusing Multiple Sensor Measurements

A nuclear power plant is instrumented with a variety of sensors that monitor its variables to estimate the state and initiate safety actions, if needed. We address the problem of estimating drifts or errors in sensor measurements due to factors such as calibration changes. We propose an information fusion method that uses measurements from other sensors to generate an estimate of a sensor measurement, and its difference from an actual measurement provides an error estimate. We present two fusers based on the ensemble of trees and support vector machine that are trained using sensor measurements collected at an emulated test loop of a pressurized water reactor under no-drift conditions. We present error estimates for a differential pressure sensor of the heat exchanger of the primary coolant system, under twenty controlled scenarios using the test loop. Both positive and negative errors are captured by both methods in scenarios involving calibration drifts, blocking, air gap and electromagnetic interference. The root mean square errors of estimated drifts are typically within 2% percent of the maximum.

Rao, Nageswara↗

Investigation of Plasmodium falciparum pfhrp2 and pfhrp3 gene deletions and performance of a rapid diagnostic test for identifying asymptomatic malaria infection in northern Ethiopia, 2015

Background: Rapid diagnostic tests (RDTs) are widely used for malaria diagnosis of both symptomatic and asymptomatic infections. Although RDTs are a reliable and practical diagnostic tool, the sensitivity of histidine-rich protein 2 (HRP2)-based RDTs can be reduced if pfhrp2 or pfhrp3 (pfhrp2/3) gene deletions exist in the Plasmodium falciparum parasite population. This study evaluated dried blood spot (DBS) samples collected from a national household survey to investigate the presence of pfhrp2/3 deletions and the performance of the RDT used in the cross-sectional survey in a low transmission setting. Methods: The 2015 Ethiopia Malaria Indicator Survey tested household members by RDT and collected DBS samples. DBS (n = 2648) from three regions in northern Ethiopia were tested by multiplex bead-based antigen detection assay after completion of the survey. The multiplex assay detected pan-Plasmodium lactate dehydrogenase (LDH), pAldolase, and HRP2 antigens in samples. Samples suspected for pfhrp2/3 gene deletions (pLDH and/or pAldolase positive but low or absent HRP2) were further investigated by molecular assays for gene deletions. Antigen results were also compared to each individual’s RDT results. Dose–response logistic regression models were fit to estimate RDT level of detection (LOD) antigen concentrations at which 50, 75, 90, and 95% of the RDTs returned a positive result during this survey. Results: Out of 2,648 samples assayed, 29 were positive for pLDH or pAldolase antigens but low or absent for HRP2 signal, and 15 of these samples (51.7%) were successfully genotyped for pfhrp2/3. Of these 15 P. falciparum infections, eight showed single deletions in pfhrp3, one showed a single pfhrp2 deletion, and six were pfhrp2/3 double-deletions. Six pfhrp2 deletions were observed in Tigray and one in Amhara. Twenty-five were positive for HRP2 by the survey RDT while the more sensitive bead assay detected 30 HRP2-positive samples. A lower concentration of HRP2 antigen generated a positive test result by RDT compared to pLDH (95% LOD: 16.9 ng/mL vs. 319.2 ng/mL, respectively). Conclusions: There is evidence of dual pfhrp2/3 gene deletions in the Tigray and Amhara regions of Ethiopia in 2015. As the prevalence of malaria was very low (< 2%), it is difficult to make strong conclusions on RDT performance, but these results challenge the utility of biomarkers in household surveys in very low transmission settings.

60 APPLIED LIFE SCIENCES↗

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗