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At least 1,099 records · Page 61

A data-driven method to estimate the antiproton background in Mu2e

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of neutrinoless conversion of muon to electron in the field of an Al nucleus. The experimental signature is a monochromatic 104.97 MeV conversion electron. One of the expected backgrounds to the conversion electron search is antiprotons produced by the proton beam at the Production Target and annihilating in the Stopping Target (ST). The background expected from antiprotons is low but highly uncertain due to the uncertainty in the antiproton production cross section for the Mu2e beam energy in the relevant angular region. Antiprotons are significantly slower than the other beam particles, so they cannot be efficiently suppressed by the time window cut used to reduce the prompt background. At Mu2e energies, antiproton annihilation at rest in the ST is the only source of events with multiple, simultaneous particle trajectories. We utilized this unique feature and developed a novel way to reconstruct the multi-track events and estimate the antiproton background in situ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Antarctic Circumpolar Current Transport Variability during 2003-05 from GRACE

Gravity Recovery and Climate Experiment (GRACE) gravity data spanning January 2003-November 2005 are used as proxies for ocean bottom pressure (BP) averaged over 1 month, spherical Gaussian caps 500 km in radius, and along paths bracketing the Antarctic Circumpolar Current's various fronts. The GRACE BP signals are compared with those derived from the Estimating the Circulation and Climate of the Ocean (ECCO) ocean modeling-assimilation system, and to a non-Boussinesq version of the Regional Ocean Model System (ROMS). The discrepancy found between GRACE and the models is 1.7 cm H2O (1 cm H2O approx. 1 hPa), slightly lower than the 1.9 cmH2O estimated by the authors independently from propagation of GRACE errors. The northern signals are weak and uncorrelated among basins. The southern signals are strong, with a common seasonality. The seasonal cycle GRACE data observed in the Pacific and Indian Ocean sectors of the ACC are consistent, with annual and semiannual amplitudes of 3.6 and 0.6 cmH2O (1.1 and 0.6 cm H2O with ECCO), the average over the full southern path peaks (stronger ACC) in the southern winter, on days of year 197 and 97 for the annual and semiannual components, respectively; the Atlantic Ocean annual peak is 20 days earlier. An approximate conversion factor of 3.1 Sv (Sv equiv 10(exp 6)cu m/s) of barotropic transport variability per cm H2O of BP change is estimated. Wind stress data time series from the Quick Scatterometer (QuikSCAT), averaged monthly, zonally, and over the latitude band 40(deg)- 65(deg)S, are also constructed and subsampled at the same months as with the GRACE data. The annual and semiannual harmonics of the wind stress peak on days 198 and 82, respectively. A decreasing trend over the 3 yr is observed in the three data types.

Gravity Recovery and Climate Experiment (GRACE)↗

New calorimetric all-particle energy spectrum

Both the maximum size N sub m and the sea level muon size N sub mu have been used separately to find the all-particle energy spectrum in the air shower domain. However the conversion required, whether from N sub m to E or from N sub mu to E, has customarily been carried out by means of calculations based on an assumed cascase model. It is shown here that by combining present data on N sub m and N sub mu spectra with data on: (1); the energy spectrum of air shower muons and (2) the average width of the electron profile, one can obtain empirical values of the N sub m to E and N sub mu to E conversion factors, and an empirical calorimetric all-particle spectrum, in the energy range 2 x 10 to the 6th power E 2 x 10 to the 9th power GeV.

Linsley, J.↗

Supply analysis of preferential market incentive for energy crops

This analysis explores the valuation of feedstock quality attributes of switchgrass and miscanthus – two energy crops poised for future expansion – and compares the relative economic availability of these two crops under two scenarios: (i) uniform price assumptions (i.e., no incentive for quality), and (ii) a scenario of a price premium based on convertibility (i.e., an incentive for quality). Given data on cellulose content, hemicellulose content, and their relative convertibility, miscanthus is expected to be 11% more efficient at conversion to biofuels than switchgrass under the biochemical conversion route. Based on this scenario of improved conversion efficiency and associated profit, we simulate an 11% price premium for miscanthus over other feedstocks in a base-case scenario. By adding this price premium, supplies of miscanthus increase over the base case by about 4 million (44%), 94 million (64%), and 166 million (94%) tons in year 0, 10, and 20 after simulated contracts for production are initiated respectively. These results emphasize that custom simulations are needed to quantify feedstock availability if supplies are intended to reflect grower response to industry demands for feedstock quality specifications. Farmers can grow ‘peas or carrots’, and price signals from biorefineries will influence what energy crops they produce. Recognizing that the energy crop mix is tractable according to quality characteristics is relevant both for near-term and long-term biofuels research and development. Here, we recommend accounting for market preferences for quality attributes when estimating potential future supplies of energy crops.

09 BIOMASS FUELS↗

Unlocking the benefits of transparent and reusable science for climate-risk management

People around the world seek climate-risk information to guide their decisions. For instance, projections about future flood risk inform where households choose to live, how lenders manage credit risks, and which communities receive federal funding. Yet data limitations and fundamental validation challenges raise important concerns about the reliability of such projections. The principles of transparency and reusability help address these concerns by enabling scrutiny of assumptions and methods, development of foundational data and tools, and consistent application of evaluation standards. While there is ongoing debate about how much transparency commercial climate-risk services should provide, many expect non-commercial actors to lead the way on operationalizing transparency and reusability to fulfill their knowledge-building role in the climate-risk ecosystem. However, despite prominent success stories, we find a substantial gap between principles and practice: only four percent of the most-cited peer-reviewed climate-risk studies in recent years fully share their data and code despite this being a widely accepted minimum standard for transparency. We highlight low-cost measures that non-commercial researchers can take now to improve transparency and reusability. We also emphasize that transformative progress requires substantial investment, cross-sector collaboration, and careful consideration of tradeoffs, data rights, and multiple perspectives on equity. We hope this perspective accelerates both immediate actions and longer-term conversations to improve the ability of science to effectively support timely, evidence-based, and sound climate-risk management.

Open Science↗

TEAMER: Results of Investigating Structural Design Concepts and Alternative Materials for a Wave Power System

Included here are materials from a study on the design of a three-body Wave Energy Converter (WEC) utilizing a heave plate, dual Power Take Offs (PTOs), and single point mooring. A material trade study has been conducted to evaluate the effects of introducing various metallic and fiber-reinforced polymer (FRP) elements to the design. The baseline design is C-Power's patented k2 Wave Power System (WPS). This Testing Expertise and Access for Marine Energy Research (TEAMER) Request for Technical Support (RFTS) 9 effort resulted in alternative designs of the WPS center member, the nacelle. The analysis resulting from this study will inform the design of a lightweight structure with lower manufacturing and operating costs that increases energy conversion and power-to-weight ratio of the device. The dataset contains several components: finite element analysis (FEA) data, hand calculations, and CAD models. FEA files includes those used for and generated by finite element simulations. Calculations include hand calculations performed using Microsoft Excel, which assess core laminate properties, buckling, and other structural aspects in accordance with risk management DNV-RP-C201 standards. CAD materials include Solidworks files for parts, assemblies, and drawings of the evaluated models.

16 TIDAL AND WAVE POWER↗

Volume 9: Critical Facility with Add-On Ion Beam

Completion of the originally planned critical facility has been considered as part of the High Flux Isotope Reactor (HFIR) Sustaining and Enhancing Neutron Science Initiative at Oak Ridge National Laboratory (ORNL). A working group of ORNL staff members was formed to develop the idea and to recommend one or more configurations to best support future HFIR operations and scientific capacities. HFIR was designed with a critical pool in the reactor bay that was projected to be outfitted as a critical facility. The primary purpose of the planned critical facility was to measure the subcritical worth of fresh fuel elements to support startup requirements. However, the Y-12 National Security Complex already housed a critical facility that was used for this purpose. This report presents the working group’s efforts, including determination of the proposed critical facility’s high-impact benefits. A generic low-power critical facility would be employed for reactor physics measurements, code and data validation, reactor operator and staff training, and education. This facility would be instrumental in supporting current HFIR operations, conversion of HFIR to low-enriched uranium, existing light water reactor operations, and advanced reactor development and deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Advances in Serial MSK modems

Lumped element as well as distributed element networks are used in the Serial MSK (SMSK) modems, for 20-1000 Mbps data rate range applications, whose design and performance characteristics are described. It is noted that the use of baseband conversion filters for the modulator yields good performance in many applications, with typical matched filter designs (structurally simple to implement) causing less than 0.5 dB bit error rate performance degradation. The SMSK modem technique begins with the use of a biphased shift-keyed modulator, and then employs passive filters to obtain the MSK signal.

Ryan, C. R.↗

A Satellite Borne Cadmium Sulfide Total Corpuscular Energy Detector

The properties of single crystals of cadmium sulfide as radiation detectors are described. It has been found possible to select crystals such that: (a) The ratio of increase of conductivity under irradiation to the rate of absorption of energy in the crystal is substantially independent of particle energy (over the examined ranges of 500 ev to 80 kev for electrons and 5 kev to 180 kev for protons) and of the magnitude of energy flux (over the range from.005 to 10 ergs/cm(sup 2 -sec); and (b) The above ration is substantially the same for protons, electrons, alpha particles, x-rays, and gamma-rays. For a driving voltage of 100 volts, typical crystal yield currents of 10(sup -7) to 10(sup- 6) amperes for each erg/cm(sup 2-sec) of energy absorbed by the crystal. The threshold of such crystal detectors (resulting from dark currents of the order of 10(sup 10 amp) is typically 10(sup -3) ergs/cm(sup 2- sec). For the selected crystals a response-temperature coefficient of -0.25% per degree centigrade is found for the temperature range -50 deg C to + 50 deg C. A description is given of a complete CdS total corpuscular energy detector for the study of geomagnetically trapped radiation by means of a satellite. The detector described has a dynamic range great than 10(sup 4), a solid angle of 10(exp -3) steradian, and a detection threshold of approximately 1 erg/cm(sup 2-sec-sterad). A similar detector employing a small magnet for the selective exclusion of electrons is also described. Noteworthy practical features of these detectors for satellite and space probe experiments are: (a) Use of bare crystals, without covering foils, in order to detect charged particles having energies as low as hundreds of electron volts. (b) Simplicity of electronic auxiliaries. (c) Compactness, lightweight and nechanical ruggedness. (d) Low electrical power requirements; and (e) Conversion of conduction current to the rate of a twostate relaxation oscillator in order to facilitate telemetric transmission of data. A pair of such detectors was flown as part of the s-46 satellite payload on March 23, 1960, but due to vehicular failure an orbit was not achieved and the operation of the CdS detectors was observed for only, six minutes of flight.

Freeman, John W.↗

NASA Cryogenic Propellant Systems Technology Development and Potential Opportunities for Discussion

Members of the eCryo Team are traveling to France to meet with CNES (Centre National d'Etudes Spatiales) on the benchmarking of CFM (Cryogenic Fluids Management) analytical models the week of January 26th, 2015. Mike Meyer is representing the Agency and eCryo Project and will conduct a conversation to explore future work. This slide package (28 charts and 3 movies) requires approval via a 1676. ISS data in this chart set has been copied from public websites.

Cryogenics CPST eCryo Propellent Transfer fluid ma↗

Carbon Cycle Science Data and Services at the Goddard Earth Sciences Data Information and Services Center (GES DISC)

The Goddard Earth Sciences Data Information and Services Center (GES DISC) archives and distributes a number of observational and model carbon cycle science data sets. We also provide services that facilitate data discovery, intercomparison, and visualization of these heterogeneous datasets for both research and applications users, such as subsetting, format conversion, How-To documentation, and the Help Desk.

Hearty, Thomas↗

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗

Global variation of the para hydrogen fraction in Jupiter's atmosphere and implications for dynamics on the outer planets

A detailed analysis of the Voyager infrared spectrometer measurements on Jupiter's atmosphere is presented, and possible implications of para hydrogen disequilibrium for the energetics and dynamics of that atmosphere are examined. The method of data analysis is described, and results for the large scale latitude variation of the para hydrogen fraction are presented. The Jovian results show pronounced latitude variation, and are compared with other parameters including wind fields, thermal structure, and various indicators of atmospheric clouds. The problem of equilibration rate is reexamined, and it is concluded that on Jupiter the equilibration time is longer than the radiative time constant at the level of emission to space, but that this inequality reverses at greater depths. A model for the interaction of fluid motions with the ortho-para conversion process is presented, and a consistent mixing length theory for the reacting ortho-para mixture is developed. Several implications of the Jovian data for atmospheric energetics and stability on the outer planets are presented.

Conrath, B. J.↗

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↗

Stratospheric photochemical studies with Atmospheric Trace Molecule Spectroscopy (ATMOS) measurements

The photochemical partitioning of stratospheric odd chlorine and odd nitrogen is examined utilizing diurnal model calculations and data from the ATMOS experiment. This experiment, conducted during April-May 1985, employed a solar occultation method to obtain vertical profiles of temperature and various other trace constituents at 30 deg N and 48 deg S latitudes. The ATMOS data set confirms the presence of N2O5 in the stratosphere; however, the observed mixing ratios at sunset are more than a factor of 2 less than the calculated values. It is shown that the conversion of N2O5 into HNO3 could take place in the presence of aerosol surfaces quickly enough to affect the N2O5 mixing ratio below 30 km. Inclusion of the heterogeneous reaction brings the calculated N2O5 profile below 30 km into closer agreement with the ATMOS data.

Natarajan, Murali↗