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At least 1,045 records · Page 58

A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model

Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth's Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (R sfc > 0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (τ) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓ sfc and SW↑ TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10 W m -2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and r e retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

54 ENVIRONMENTAL SCIENCES↗

Linking Hydrology and Dissolved Organic Matter Characteristics in a Subtropical Wetland: A Long-Term Study of the Florida Everglades

Dissolved organic matter (DOM) acts as an important biogeochemical component of aquatic ecosystems that controls nutrient cycling, influences water quality, and links terrestrial and oceanic carbon pools, yet long-term studies of how changing environmental drivers alter its abundance and composition are rare. Using a ten-year, spatially explicit dataset from Everglades National Park (ENP), a globally significant wetland, we investigated the relationships between DOM quality/quantity and hydrologic/climatic drivers along two contrasting marsh-estuarine transects based on generalized linear modeling and a cumulative sums analysis. Analyses revealed distinct spatial, seasonal, and interannual patterns in variability of DOC and optical properties. Landscape-scale seasonal patterns showed an enrichment in microbial-like and protein-like DOM during the dry season relative to the wet season. We found that, while some compositional constituents varied with the solar calendar, responsive to temperature and photoperiod, others varied with the hydrologic calendar. Independent water level and discharge effects indicated strong hydrologic control on DOM quality that differed between the two transects, evidencing differences in their connectivity to areas of high agricultural activity. Across all sites, a significant long-term increasing trend in the fluorescence index was observed, associated with a positive correlation with precipitation and also potential changes in agricultural inputs, with other features associated with drought and hurricanes. Lastly, the cumulative sums analysis revealed differences between the two transects in the sensitivity of DOM composition to decreased water levels associated with 30-year climate scenarios, with the less hydrologically dynamic transect exhibiting greater potential sensitivity.

54 ENVIRONMENTAL SCIENCES↗

Loss resilience for two-qubit state transmission using distributed phase sensitive amplification

We transmit phase-encoded non-orthogonal quantum states through a 5-km long fibre-based distributed optical phase-sensitive amplifier (OPSA) using telecom-wavelength photonic qubit pairs. The gain is set to equal the transmission loss to probabilistically preserve input states during transmission. While neither state is optimally aligned to the OPSA, each input state is equally amplified with no measurable degradation in state quality. These results promise a new approach to reduce the effects of loss by encoding quantum information in a two-qubit Hilbert space which is designed to benefit from transmission through an OPSA.

97 MATHEMATICS AND COMPUTING↗

New Physics Agnostic Selections For New Physics Searches

We discuss a model-independent strategy for boosting new physics searches with the help of an unsupervised anomaly detection algorithm. Prior to a search, each input event is preprocessed by the algorithm - a variational autoencoder (VAE). Based on the loss assigned to each event, input data can be split into a background control sample and a signal enriched sample. Following this strategy, one can enhance the sensitivity to new physics with no assumption on the underlying new physics signature. Our results show that a typical BSM search on the signal enriched group is more sensitive than an equivalent search on the original dataset.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Formation enthalpies for transition metal alloys using machine learning

The enthalpy of formation is an important thermodynamic property. Developing fast and accurate methods for its prediction is of practical interest in a variety of applications. Material informatics techniques based on machine learning have recently been introduced in the literature as an inexpensive means of exploiting materials data, and can be used to examine a variety of thermodynamics properties. Here we investigate the use of such machine learning tools for predicting the formation enthalpies of binary intermetallic compounds that contain at least one transition metal. We consider certain easily available properties of the constituting elements complemented by some basic properties of the compounds, to predict the formation enthalpies. We show how choosing these properties (input features) based on a literature study (using prior physics knowledge) seems to outperform machine learning based feature selection methods such as sensitivity analysis and LASSO (least absolute shrinkage and selection operator) based methods. A nonlinear kernel based support vector regression method is employed to perform the predictions. The predictive ability of our model is illustrated via several experiments on a dataset containing 648 binary alloys. We train and validate the model using the formation enthalpies calculated using a model by Miedema, which is a popular semiempirical model used for the prediction of formation enthalpies of metal alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Topness, Version 1

The code would be used in analyses of data from the LHC, to improve the sensitivity of their experiments to new exotic particles. The software minimizes a certain function, as defined in the above reference, for some input provided by the user. The output to the user is the global minimum of that function. The code finds the global minimum using the Nelder-Mead algorithm. All the codes for the minimization including the Nelder-Mead algorithm, is written by the author. The software is written in c++.

Graesser, MichaelL.↗

Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest

Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗

Refining a Novel Process Monitoring Method to Safeguard Continuously Cycling Designs Using Isotopic Ratios

In advanced reactor (AR) designs, a common feature is continuous chemical processing and circulation of the nuclear material. This work bridges a significant measurement gap in safeguarding reactors with circulating fuel or continuous refueling by leveraging and building on the isotope ratio method first developed by our team under an FY21 Advanced Reactors International Safeguards Engagement (ARISE) project (Uribe et al. 2021). In circulating fuel designs, the radioisotope inventory changes from traditional effects (e.g., radioactive decay, fission) but also includes material transport due to pressure and temperature gradients. Such designs may also require regular or continuous additions or removals during operation, which significantly increases the rate of inventory change compared to traditional pressurized water reactor (PWR)s. Thus, directly tracking the nuclear inventory is ineffective since the isotopes are continuously added and removed. The isotope ratio method instead focuses on detecting changes to the input and output flows of radioisotopes. Previous work showed that for well-chosen pairs of isotopes, the isotopic ratio provides a sensitive and lasting indicator of deviation from normal conditions (e.g., startup, shutdown, diversion). The isotope ratio method is a process monitoring method with potential for application in for forward-looking approaches to International Atomic Energy Agency (IAEA) safeguards. The original process monitoring method was developed for a specific case—the decay tank of a thorium-fueled molten salt breeder reactor. In this expanded work, we explored other types of reactors and processes with nonstationary (e.g., flowing) nuclear material, which are difficult to safeguard with traditional methods because of the transient nature of the systems. The goal of the present work is to generalize the isotope ratio method for use in processes with continuously flowing nuclear material. All continuous processes have an average time for isotopes to be replaced in the system. The isotope ratio method works by choosing radioisotopes with half-lives both above and below the processing time. The present work seeks to explore which isotopes are suitable for the method by simulating the nuclear inventory, radioisotope emissions, and detector responses for several classes of advanced reactors. While the method can in principle be applied to other processes (e.g., enrichment or reprocessing facilities), the present work limits scope to ARs with continuously flowing fuel. Section 2 details the mathematics supporting the isotope ratio method, and Section 3 introduces the representative ARs selected for this work. Section 4 discusses how each reactor was analyzed, and Section 5 showcases the results for each representative reactor. Finally, Section 6 provides concluding remarks and suggests pathways for further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

An advanced technique for the prediction of decelerator system dynamics.

An advanced two-body six-degree-of-freedom computer model employing an indeterminate structures approach has been developed for the parachute deployment process. The program determines both vehicular and decelerator responses to aerodynamic and physical property inputs. A better insight into the dynamic processes that occur during parachute deployment has been developed. The model is of value in sensitivity studies to isolate important parameters that affect the vehicular response.

Talay, T. A.↗

Development of optical diaphragm deflection sensors

The objective of this project was to develop high-temperature pressure sensors using non-metallic components and optical sensing methods. The sensors are to operate over a temperature range from room temperature approx. 20C to 540C, to respond to internal pressure up to 690 kPa, to respond to external pressure up to 690 kPa, and to withstand external overpressure of 2070 kPa. Project tasks include evaluating sensing techniques and sensor systems. These efforts include materials and sensing method selection, sensor design, sensor fabrication, and sensor testing. Sensors are tested as a function of temperature, pressure, overpressure, and vibration. The project results show that high-temperature pressure sensors based on glass components and optical sensing methods are feasible. The microbend optical diaphragm deflection sensor exhibits the required sensitivity and stability for use as a pressure sensor with temperature compensation. for the microbend sensor, the 95% confidence level deviation of input pressure from the pressure calculated from the overall temperature-compensated calibration equation is 3.7% of full scale. The limitations of the sensors evaluated are primarily due to the restricted temperature range of suitable commercially available optical fibers and the problems associated with glass-to-metal pressure sealing over the entire testing temperature range.

Ghering, W. L.↗

Cellular and Network Mechanisms Underlying Information Processing in a Simple Sensory System

Realistic, biophysically-based compartmental models were constructed of several primary sensory interneurons in the cricket cercal sensory system. A dynamic atlas of the afferent input to these cells was used to set spatio-temporal parameters for the simulated stimulus-dependent synaptic inputs. We examined the roles of dendritic morphology, passive membrane properties, and active conductances on the frequency tuning of the neurons. The sensitivity of narrow-band low pass interneurons could be explained entirely by the electronic structure of the dendritic arbors and the dynamic sensitivity of the SIZ. The dynamic characteristics of interneurons with higher frequency sensitivity required models with voltage-dependent dendritic conductances.

Jacobs, Gwen↗

The Primordial Inflation Explorer (PIXIE) Mission

The Primordial Inflation Explorer (PIXIE) is an Explorer-class mission to map the absolute intensity and linear polarization of the cosmic microwave background and diffuse astrophysical foregrounds over the full sky from frequencies 30 GHz to 6 THz (I cm to 50 I-tm wavelength). PIXIE uses a polarizing Michelson interferometer with 2.7 K optics to measure the difference spectrum between two orthogonal linear polarizations from two co-aligned beams. Either input can view either the sky or a temperature-controlled absolute reference blackbody calibrator. The multimoded optics and high etendu provide sensitivity comparable to kilo-pixel focal plane arrays, but with greatly expanded frequency coverage while using only 4 detectors total. PIXIE builds on the highly successful COBEIFIRAS design by adding large-area polarization-sensitive detectors whose fully symmetric optics are maintained in thermal equilibrium with the CMB. The highly symmetric nulled design provides redundant rejection of major sources of systematic uncertainty. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r much less than 10(exp -3). PIXIE will also return a rich data set constraining physical processes ranging from Big Bang cosmology, reionization, and large-scale structure to the local interstellar medium. Keywords: cosmic microwave background, polarization, FTS, bolometer

Kogut, Alan J.↗

The Arctic Sea Ice Cover of 2016: A Year of Record-Low Highs and High-Than-Expected Lows

The Arctic sea ice cover of 2016 was highly noteworthy, as it featured record low monthly sea ice extents at the start of the year but a summer (September) extent that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea ice state in terms of its monthly sea ice cover, placing this in the context of the sea ice conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea ice extent and area estimates, in terms of their magnitude and annual rankings, to the ice concentration input data (using two widely used datasets) and to the averaging methodology used to convert concentration to extent (daily or monthly extent calculations). We use estimates of sea ice area over sea ice extent to analyse the relative “compactness†of the Arctic sea ice cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher-than-expected September ice extent. Two cyclones that entered the Arctic Ocean during August appear to have driven this low-concentration/compactness ice cover but were not sufficient to cause more widespread melt-out and a new record-low September ice extent. We use concentration budgets to explore the regions and processes (thermodynamics/ dynamics) contributing to the monthly 2016 extent/area estimates highlighting, amongst other things, rapid ice intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record-early melt onset in the North Atlantic sector of the Arctic. Our results also show record-late 2016 freeze-up in the central Arctic, North Atlantic and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer ice compactness for seasonal forecasting, suggesting that sea ice area could be a more reliable metric to forecast in this more seasonal, "New Arctic", sea ice regime.

sea ice↗

u-Spec Spectrometers for the EXCLAIM Instrument

The EXperiment for Cryogenic Large-aperture Intensity Mapping (EXCLAIM) is a cryogenic balloon-borne instrument that will map carbon monoxide and singly-ionized carbon emission lines across redshifts from 0to 3.5, using an intensity mapping approach. EXCLAIM will broaden our understanding of these elemental and molecular gases, and the role they play in star formation processes across cosmic time scales. The focal plane of EXCLAIM’s cryogenic telescope features sixμ-Spec spectrometers.μ-Spec is a compact, integrated grating-analog spectrometer, which uses meandered superconducting niobium microstrip transmission lines on a single-crystal silicon dielectric to synthesize the grating. It features superconducting aluminum microwave kinetic inductance detectors (MKIDs), also in a microstrip architecture. The spectrometers for EXCLAIM couple to the telescope optics via a hybrid planar antenna coupled to a silicon lenslet. The spectrometers operate from420−540 GHz with a resolving power R=λ/∆λ= 512, and employ an array of 355 MKIDs on each spectrometer. The spectrometer design targets a noise equivalent power (NEP) of 2×10−18W/√Hz (defined at the input to the main lobe of the spectrometer lenslet beam, within a 9◦half width), enabled by the cryogenic telescope environment, the sensitive MKID detectors, and the low dielectric loss of single-crystal silicon. We report on these spectrometers under development for EXCLAIM, providing an overview of the spectrometer and component designs, the spectrometer fabrication process, fabrication developments since previous prototype demonstrations, and the current status of their development for the EXCLAIM mission.

EXCLAIM Instrument↗

Sensitivity Analysis of a Wireless Power Transfer (WPT) System for Electric Vehicle Application

This paper presents a detailed parametric sensitivity analysis for a wireless power transfer (WPT) system in electric vehicle application. Specifically, several key parameters for sensitivity analysis of a series-parallel (SP) WPT system are derived first based on analytical modeling approach, which includes the equivalent input impedance, active / reactive power, and DC voltage gain. Based on the derivation, the impact of primary side compensation capacitance, coupling coefficient, transformer leakage inductance, and different load conditions on the DC voltage gain curve and power curve are studied and analyzed. It is shown that the desired power can be achieved by just changing frequency or voltage depending on the design value of coupling coefficient. However, in some cases both have to be modified in order to achieve the required power transfer.

electric vehicle↗

Topness, Version 1

The code would be used in analyses of data from the LHC, to improve the sensitivity of their experiments to new exotic particles. The software minimizes a certain function, as defined in the above reference, for some input provided by the user. The output to the user is the global minimum of that function. The code finds the global minimum using the Nelder-Mead algorithm. All the codes for the minimization including the Nelder-Mead algorithm, is written by the author. The software is written in c++.

Graesser, Michael L.↗

FECM/NETL Unconventional Shale Well Economic Model (UShWEM)

FECM/NETL Unconventional Shale Well Economic Model (UShWEM) is an Excel-based model that evaluates the economics of an unconventional shale well on a per-well and per-pad basis. The model calculates the net cash flow, internal rate of return (IRR), net present value (NPV), earnings before interest, taxes, depreciation, and amortization (EBITDA), payout month and year, and breakeven price (for either oil- or gas-wells). The model can be used to estimate the economics of a well or pad over its lifetime (development through site reclamation) based on (1) the capital and operating costs associated with well/pad development and operations, (2) the revenue associated with oil, gas, and condensate production streams, and (3) accounting for relevant tax policies and asset depreciation applicable for oil and gas operations. The main input for the model is the completion design and production data. Key financial considerations in the model include oil, gas, and condensate market prices, tax-related settings, royalty rates, the discount rate, minimum economic hurdle (IRR) [if performing break-even analysis], and project contingency. The financial consideration can be adjusted to reflect the level of granularity the user requires as input when calculating the economics for a well or pad development. In addition, the model affords users the option to provide their user inputs for all cost categories considered. As a result, the model can be used to generate a multitude of scenario cases for sensitivity analysis of the various financial considerations, as well as production and cost profiles. To make this seamless, the model has the capability for key economic outputs to be exported in large batches through macros-enabled functions on its “Model Output Summary” and “Multi-Well Cost Analysis. The spreadsheet model includes macros and user-defined functions, so the user must enable Excel’s macro capability for the model to function correctly.

Sheriff, Alana↗

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications (Executive Summary)

The overall goal of this work was to advance the integrated workflow capabilities to provide the weapon system analysts the tools to construct, communicate and robustly execute end-to-end computational simulation models and analysis. Specifically, this includes developing and running automated, CompSim workflows that map model inputs to responses from large-scale studies executed on a distributed, heterogenous computing environment (e.g., CAD applications on Windows laptop to Sierra FEM codes on Trinity within a single workflow). The workflows developed enable ensemble calculations in support of ND program decisions, including sensitivity analysis, optimization and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗