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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Consistent Evaluation of the Prompt-fission Neutron Spectrum and Multiplicity for n+ 235,238 U and n+ 239 Pu

This report was written to satisfy a FY20 NCSP milestone on 235,238 U and 239 Pu. The milestone requires to “finalize a report assessing our methodology to evaluate prompt-fission neutron spectrum (PFNS) and multiplicity consistently”. More specifically, we study whether the code CGMF can reproduce ENDF/B-VIII.0 evaluated PFNS and average prompt-fission neutron multiplicities, $\bar{v}$, for 235,238 U and 239 Pu using one joint parameter set per isotope. If CGMF is shown to be able to reasonably reproduce ENDF/B-VIII.0 within its model-parameter space, this code could be used for future consistent evaluations of PFNS and $\bar{v}$. To answer this question, we explore here the parameter space of CGMF and its impact on calculated values and whether they are close to evaluated and experimental data. We also list experimental data that would enter a future evaluation and statistics method that could be used to obtain evaluated data and covariances. We conclude that values of $\bar{v}$ calculated by CGMF are reasonably close to ENDF/B-VIII.0 data, while more work on modeling the PFNS is needed (parameter optimization and model improvements) to reliably use it for evaluations.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Multiple, Compounding Disturbances in a Forest Ecosystem: Fire Increases Susceptibility of Soil Edaphic Properties, Bacterial Community Structure, and Function to Change with Extreme Precipitation Event

The intensity and frequency of ecosystem disturbances are shifting with climate change, and multiple disturbances in close succession have the potential to compound their independent effects and strongly alter ecosystem structure and function. In this paper, we examine the effects of an extreme precipitation event on a montane forest landscape that was previously decimated by wildfire (37 months prior) relative to an unburned site in the same ecosystem. We assessed responses in soil edaphic properties, bacterial community composition and assembly, and soil enzyme activities involved in carbon (C) and nitrogen (N) acquisition. Our research reveals that previously burned landscapes are susceptible to a subsequent extreme precipitation event via significant increases in soil pH where unburned soils are not. Beta- and Delta-proteobacteria associated with early succession increased and shifts were observed in N- vs. C-acquiring extracellular enzymes within burned soils after the extreme precipitation event. Finally, we connected variation in ecological selective pressures on bacterial communities associated with pH change to these differences in microbial mediated soil enzyme activity. Thus, this research demonstrates how multiple, compounding disturbances drive distinct changes relative to systems experiencing a single disturbance and suggests that changes in bacterial community assembly process with disturbance may underlie this response.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sun's Series via Cyclotomic Multiple Zeta Values

We prove and generalize several recent conjectures of Z.-W. Sun surrounding binomial coefficients and harmonic numbers. We show that Sun's series and their analogs can be represented as cyclotomic multiple zeta values of levels N ϵ {4,8,12,16,24} , namely Goncharov's multiple polylogarithms evaluated at N -th roots of unity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Continued Kinematic and Photometric Investigations of Hierarchical Solar-type Multiple Star Systems

We observed 15 of the solar-type binaries within 67 pc of the Sun previously observed by the Robo-AO system in the visible, with the PHARO near-infrared camera and the PALM-3000 adaptive optics system on the 5 m Hale telescope. The physical status of the binaries is confirmed through common proper motion and detection of orbital motion. In the process, we detected a new candidate companion to HIP 95309. We also resolved the primary of HIP 110626 into a close binary, making that system a triple. These detections increase the completeness of the multiplicity survey of the solar-type stars within 67 pc of the Sun. Combining our observations of HIP 103455 with archival astrometric measurements and RV measurements, we are able to compute the first orbit of HIP 103455, showing that the binary has a 68 year period. We place the components on a color–magnitude diagram and discuss each multiple system individually.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spectroscopic Orbits of Subsystems in Multiple Stars. VII

Spectroscopic orbits of main-sequence stars HIP 3150A, 6873B, 11537A, 22531A, 22534B, 31089B, 49336A, 104833C, and 107731A belonging to eight multiple systems are determined from high-resolution spectra taken with CHIRON. Two of those are twins with mass ratios above 0.95. HIP 11537 is a young three-tier quadruple system with inner periods of 22.3 and 1146 days and the outer period of 3 kyr. HIP 22531 (ι Pic) is the brightest star in a hierarchical system with six components. It is a spectroscopic binary with periods of 1.56 days and 2.75 yr, as well as a γ Dor variable with a period of 0.67 day, possibly in a 7:3 resonance with the inner orbit. HIP 22534, also member of this system, is a double-lined binary with a period of 208 days. For HIP 31089, both the spectro-interferometric 32 yr outer orbit and the 213 day orbit of the subsystem are determined. HIP 107731 is a triple system with an inner period of 470 days and a fast spatial motion, likely metal-poor. New orbits contribute to the statistics of hierarchical multiplicity in the solar neighborhood.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Multiple Scattering Measurements in the MICE Experiment

The international Muon Ionization Cooling Experiment (MICE), under construction at RAL, will test a prototype cooling channel for a future Neutrino Factory or Muon Collider. The cooling channel aims to achieve, using liquid hydrogen absorbers, a 10% reduction in transverse emittance. The change in 4D emittance will be determined with an accuracy of 1% by measuring muons individually. Step IV of MICE will make the first precise emittance-reduction measurements of the experiment. Simulation studies using G4MICE, based on GEANT4, find a significant difference in multiple scattering in low Z materials, compared with the standard expression quoted by the Particle Data Group. Direct measurement of multiple scattering using the scintillating-fibre trackers is found to be possible, but requires the measurement resolution to be unfolded from the data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Leveraging Interaction History for Intelligent Configuration of Multiple Coordinated Views in Visualization Tools

Visualization tools can take advantage of multiple coordinated views to support analysis of large, multidimensional data sets. Effective design of such views and layouts can be challenging, but understanding users analysis strategies can inform design improvements. We outline an approach for intelligent design configuration of visualization tools with multiple coordinated views, and we discuss a proposed software framework to support the approach. The proposed software framework could capture and learn from user interaction data to automate new compositions of views and widgets. Such a framework could reduce the time needed for meta analysis of the visualization use and lead to more effective visualization design.

infovis↗
DOE OSTI2017

Fast-neutron Multiplicity Counter for Passive and Active Measurements of Special Nuclear Material

We developed a fast-neutron multiplicity counter (FNMC) based on organic scintillators (liquid and stilbene). The system is able to detect correlated photon and neutron multiplets emitted by fission reactions. We tested the system both in passive and active operation mode, and present the results of the experiments, both carried out at the Zero Power Physics Reactor of Idaho National Laboratory. The system was operated in coincidence mode (with a gate time of 50 nanoseconds) and two calibration-based approaches were used to estimate the 240Pu effective (240Pueff) and 235U mass of the samples. In passive mode, we assayed two types of plutonium metal plates, i.e. PAHN and PANN, with a 240Pueff mass of 4.7 g and 25.05 g per plate, respectively. The 239Pu mass percentage was 74% for the PAHN and 95% for the PANN series. We measured neutrons emitted in coincidence by several plate assemblies, having an overall 240Pueff mass in the 4.7 g to 500 g range. In active mode, we characterized several uranium samples. We used two AmLi sources (~50000 neutrons emitted per second) to induce fission in the samples. The first six measured samples were certified reference materials (CRM, set 149), having a constant enrichment, i.e. 93.2 wt%, and mass in the range between 0.5 and 4 kg. Additionally, we assayed three CRM-146 samples, with constant total mass of 500 g and an enrichment of 20.1 wt%, 52.8 wt% and 93.2 wt%. In both configurations, the system succeeded in estimating the fissile mass of an unknown sample with a statistical uncertainty lower than 1% (4-minute assay) and 7% (10-minute assay), in passive and active mode, respectively. In passive mode, the statistical uncertainty is lower than the one achieved by standard 3He counters for plutonium metal samples of similar mass. The difference between the estimated and the declared 240Pueff mass, i.e., the bias error, measured by the fast neutron multiplicity counter was consistently lower compared to the bias error of a standard thermal system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Multiple-objective Reinforcement Learning for Inverse Design and Identification

The aim of inverse chemical design is to develop new molecules with given optimized molecular properties or objectives. Recently, generative deep learning (DL) networks are considered as the state-of-the-art in inverse chemical design and have achieved early success in generating molecular structures with desired properties in the pharmaceutical and material chemistry fields. However, satisfying a large number (> 10 objectives) of molecular objectives is a limitation of current generative models. To improve the model’s ability to handle a large number of molecule design objectives, we developed a Reinforcement Learning (RL) based generative framework to optimize chemical molecule generation. Our use of Curriculum Learning (CL) to fine-tune the pre-trained generative network allowed the model to satisfy up to 21 objectives and increase the generative network’s robustness. The experiments show that the proposed multiple-objective RL-based generative model can correctly identify unknown molecules with an 83% to 100% success rate, compared to the baseline approach of 0%. Additionally, this proposed generative model is not limited to just chemistry research challenges; we anticipate that problems that utilize RL with multiple objectives will benefit from this framework.

reinforcement learning, generative model, inverse ↗
DOE OSTI2023

PRINTED, PLANAR MICROWAVE CONNECTOR WITH MULTIPLE SIGNAL LINES

Microwave connectors with a planar geometry have been demonstrated using additive manufacturing techniques. This planar form factor is expected to enable connectors to be integrated directly with other components onto a printed circuit board. The connectors were developed with multiple signal lines that will increase the density of signal connections to PCBs, eliminating the physical constraints of single-signal COTS microwave connectors. This work developed electromagnetic models (using Ansys HFSS) of these planar connectors to predict performance and optimize connector design. Materials and printing processes were developed to fabricate the connectors based on high-temperature PEEK thermoplastics. The multiple signal connectors were designed to operate over the 1-6GHz band and are built upon the single signal printed planar geometry connector introduced in a previous paper [1].

Additive Manufacturing↗
DOE OSTI2017

Using the MCNP6.2 Correlated Fission Multiplicity Models, CGMF and FREYA

The culmination of a multi-year, collaborative effort by researchers at Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL) and the University of Michigan, led to the delivery of two new correlated fission multiplicity models available within the latest release of MCNP{sup R} version 6.2. The needs within the nuclear nonproliferation community, particularly in simulating and predicting the neutron and gamma-ray signatures of special nuclear materials (SNM), provided the motivation for this major collaborative effort. From LANL, the CGMF code has been implemented as an upgrade to the original Cascading Gamma-ray Multiplicity (CGM) code. Additionally, the LLNL Fission Library has been upgraded from the original implementation released in prior versions of MCNP6/X to include the LBNL/LLNL Fission Reaction Event Yield Algorithm (FREYA) code. Both new codes are capable of simulating fission events with correlated neutron and gamma-ray emissions. Due to the release of these new models within MCNP6.2, the purpose of this paper is to describe the differences between these new models and existing capabilities, demonstrate their use in the context of simulation inputs and outputs, and to discuss some of the ongoing work directed toward the next generation of these features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Flattening of fuel importance for heterogeneous system to estimate maximal multiplication factor - 14595

In order to quantify risks of re-criticality incidents associated with loss of coolant accidents (LOCA), the maximum reactivity insertion by relocation of damaged fuel should be quantified. As the first step for the quantification, an automated search scheme is studied for an optimal geometry of damaged fuel in the coolant channel where the neutron multiplication factor k{sub eff} takes a maximal value. The scheme is based on the flattening of the fuel importance. The importance can be recognized as the substitution reactivity from fuel to water in heterogeneous systems. The flattening is achieved by substitution of water and the fuel so as to raise the k{sub eff} referring the local substitution reactivities. To calculate the reactivities efficiently, the first order perturbation scheme is adopted. In the scheme, the adjoint flux is calculated with the PARTISN code. The multi group constants used for the calculation and the perturbed reaction rates are estimated with the continuous energy Monte Carlo code MCNP-5. The proposed methods are tested for a quarter pin cell model that is constructed using Cartesian mesh. From a random distribution of a given amount of fragmented fuel, an optimal geometry is found where the fragmented fuels are aggregated. The multiplication factor in the geometry is greater than that in the original random distribution by 1.4%Δk/k. That indicates the significance of this study. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

Here, we implement a variance-based distance metric (D n ) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased and can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.

58 GEOSCIENCES↗
DOE OSTI2017

Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short–term and long–term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. In conclusion, the issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real–world perspective and needs a suitable institutional environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

By injecting different amounts of SO 2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. This leads to the ability to influence the climate response to geoengineering with stratospheric aerosols, providing the potential for design. In this work, we use simulations from the fully coupled whole-atmosphere chemistry climate model CESM1(WACCM) to demonstrate that by appropriately combining injection at just four different locations, 30°S, 15°S, 15°N, and 30°N, then three spatial degrees of freedom of AOD can be achieved: an approximately spatially uniform AOD distribution, the relative difference in AOD between Northern and Southern Hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yield 1–2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that the response to different combinations of injection at different latitudes can be estimated from single-latitude injection simulations; nonlinearities associated with both aerosol growth and changes to stratospheric circulation will be increasingly important at higher forcing levels. Optimized injection at multiple locations is predicted to improve compensation of CO 2 -forced climate change relative to a case using only equatorial aerosol injection (which overcools the tropics relative to high latitudes). The additional degrees of freedom can be used, for example, to balance the interhemispheric temperature gradient and the equator to pole temperature gradient in addition to the global mean temperature. Further research is needed to better quantify the impacts of these strategies on changes to long-term temperature, precipitation, and other climate parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

First Simulations of Designing Stratospheric Sulfate Aerosol Geoengineering to Meet Multiple Simultaneous Climate Objectives

In this work, we describe the first simulations of stratospheric sulfate aerosol geoengineering using multiple injection locations to meet multiple simultaneous surface temperature objectives. Simulations were performed using CESM1(WACCM), a coupled atmosphere-ocean general circulation model with fully interactive stratospheric chemistry, dynamics (including an internally generated quasi-biennial oscillation), and a sophisticated treatment of sulfate aerosol formation, microphysical growth, and deposition. The objectives are defined as maintaining three temperature features at their 2020 levels against a background of the RCP8.5 scenario over the period 2020-2099. These objectives are met using a feedback mechanism in which the rate of sulfur dioxide injection at each of the four locations is adjusted independently every year of simulation. Even in the presence of uncertainties, nonlinearities, and variability, the objectives are met, predominantly by SO2 injection at 30°N and 30°S. By the last year of simulation, the feedback algorithm calls for a total injection rate of 51 Tg SO2 per year. The injections are not in the tropics, which results in a greater degree of linearity of the surface climate response with injection amount than has been found in many previous studies using injection at the equator. Because the objectives are defined in terms of annual mean temperature, the required geeongineering results in "overcooling" during summer and "undercooling" during winter. The hydrological cycle is also suppressed as compared to the reference values corresponding to the year 2020. The demonstration we describe in this study is an important step toward understanding what geoengineering can do and what it cannot do.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Modulation-Doped Multiple Quantum Wells of Aligned Single-Wall Carbon Nanotubes

Heterojunctions, quantum wells, and superlattices with precise doping profiles are behind today's electronic and photonic devices based on III–V compound semiconductors such as GaAs. Currently, there is considerable interest in constructing similar artificial 3D architectures with tailored electrical and optical properties by using van der Waals junctions of low-dimensional materials. In this study, the authors have fabricated a novel structure consisting of multiple thin (≈20 nm) layers of aligned single-wall carbon nanotubes with dopants inserted between the layers. This “modulation-doped” multiple-quantum-well structure acts as a terahertz polarizer with an ultra-broadband working frequency range (from ≈0.2 to ≈200 THz), a high extinction ratio (20 dB from ≈0.2 to 1 THz), and a low insertion loss (<2.5 dB from ≈0.2 to 200 THz). The individual carbon nanotube films—highly aligned, densely packed, and large (2 in. in diameter)—were produced using vacuum filtration and then stacked together in the presence of dopants. This simple, robust, and cost-effective approach is applicable to the fabrication of a variety of devices relying on macroscopically 1D properties of aligned carbon nanotube assemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Single Bimodular Sensor for Differentiated Detection of Multiple Oxidative Gases

Semiconductive metal-oxide sensors suffer from cross-sensitivities under mixed chemical condition, specifically upon mixture of multiple oxidative or reductive gases. Herein, a single bimodular sensor is demonstrated for smart differentiation of multiple oxidative analytes by relating the resistance-metric mode to impedance-metric mode. The sensor construct based on ZnO nanorods readily outputs three response datasets upon exposure of oxidative-gas mixture including O 2 , SO 2 , and NO 2 , the resistance, real part impedance, and imaginary part impedance. The differentiative and correlated nature between these response signals allows such a single sensor platform to differentiate these oxidative gases accurately and robustly. Linear and non-linear decision boundaries are established over a large gas-concentration range from 2 ppm to 3% through a combination of principal component analysis and artificial neural network training. A facile user interface is demonstrated for recognition and measurement of unknown gas analytes, with the error of the predicted analyte-concentration as low as 2%.

36 MATERIALS SCIENCE↗