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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Post-main-sequence Evolution of Icy Minor Planets. III. Water Retention in Dwarf Planets and Exomoons and Implications for White Dwarf Pollution

Studies suggest that the pollution of white dwarf (WD) atmospheres arises from the accretion of minor planets, but the exact properties of polluting material, and in particular the evidence for water in some cases are not yet understood. Several previous works studied the possibility of water surviving inside minor planets around evolving stars. However, they all focused on small, comet-sized to moonlet-sized minor planets, when the inferred mass inside the convection zones of He-dominated WDs could actually be compatible with much more massive minor planets. Here we explore for the first time, the water retention inside exoplanetary dwarf planets, or moderate-sized moons, with radii of the order of hundreds of kilometers. This paper concludes a series of papers that has now covered nearly the entire potential mass range of minor planets, in addition to the full mass range of their host stars. We find that water retention is (a) affected by the mass of the WD progenitor, and (b) it is on average at least 5%, irrespective of the assumed initial water composition, if it came from a single accretion event of an icy dwarf planet or moon. The latter prediction strengthens the possibility of habitability in WD planetary systems, and it may also be used in order to distinguish between pollution originating from multiple small accretion events and singular large accretion events. To conclude our work, we provide a code that calculates ice and water retention by interpolation and may be freely used as a service to the community.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Parahydrogen Properties Version 05 Database Release for Nuclear Thermal Propulsion Applications

Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.

Nuclear Thermal Propulsion↗
NASA NTRSDate not supplied

Parahydrogen Properties Version 05 Database Release for NTP Applications

Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.

Nuclear Thermal Propulsion↗
DOE OSTI2013

Implementation of on-the-fly doppler broadening in MCNP

A new method to obtain Doppler broadened cross sections has been implemented into MCNP, removing the need to generate cross sections for isotopes at problem temperatures. When a neutron of energy E enters a material region that is at some temperature T, the cross sections for that material at temperature T are immediately obtained 'on-the-fly' (OTF) by interpolation using a high order functional expansion for the temperature dependence of the Doppler-broadened cross section for that isotope at the neutron energy E. The OTF cross sections agree with the NJOY-based cross sections for all neutron energies and all temperatures in the range specified by the user, e.g., 250 K - 3200 K. The OTF methodology has been successfully implemented into the MCNP Monte Carlo code and has been tested on several test problems by comparing MCNP with conventional ACE cross sections versus MCNP with OTF cross sections. The test problems include the Doppler defect reactivity benchmark suite and two full-core VHTR configurations, including one with multiphysics coupling using RELAP5-3D/ATHENA for the thermal-hydraulic analysis. The comparison has been excellent, verifying that the OTF libraries can be used in place of the conventional ACE libraries generated at problem temperatures. In addition, it has been found that the OTF methodology greatly reduces the complexity of the input for MCNP, resulting in an order of magnitude decrease in the number of input lines for full-core configurations. Finally, for full-core problems with multiphysics feedback, the memory required to store the cross section data is considerably reduced with OTF cross sections and the additional computational effort with OTF is modest, on the order of 10-15%. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

3D Visualisation of Un-georeferenced, Coordinate-poor Spatial Data in Complex D and D and WM Environments - 18294

This paper describes the development of an algorithm-based utility tool using Visual Basic that examines un-georeferenced or GPS-deprived spatial datasets (3D datasets lacking one or more of the key x, y and z components). Taking into account any known geometrical parameters which are input via a user-friendly front-end, the new code automatically evaluates attributes, including any spatial coordinate components, detects invalid survey data points and fills in bad or missing data points utilising data-specific interpolation (e.g. cubic or linear spline) of valid data points, such that local extrema are not created. Previously troublesome 2D data can be easily converted to realistic 3D contour display, integrated with other time-series data to create 4D movies, and incorporated into other existing 3D datasets. More importantly those processed and 'more complete' data can be easily stored in 3D or 4D spatial database management systems for future interrogation by using clear, realistic and intuitive 3D visualisation. Test cases are presented to demonstrate the value and versatility of the newly developed utility tool which include the 3D visualisation of: surveyed wall thicknesses of a helical coil, radiation mapping of a plant and aerial survey mapping of radiation in a region near Fukushima. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Implementation and Comparison of Different Algorithms for on the fly Doppler Broadening in RMC Code

Accurate cross sections are of great importance to Monte Carlo particle transport calculation codes which use pointwise cross sections. It is well known that cross sections have much dependence on temperature on account of Doppler effect which is particularly vital for resonance absorption cross sections. In general, pre-prepared continuous-energy libraries are used in Monte Carlo codes, which is feasible in many applications. However, in multi-physics calculations where neutronics and thermal hydraulics are coupled, cross sections at a fine interval of temperatures are desired, which brings a great challenge to computer memory. Consequently, different methods about on the fly Doppler broadening for cross sections are proposed, which can generate cross sections at the specific temperature points during neutron simulations. These methods can be roughly classified into two categories: one is to calculate the required cross sections by different algorithms, such as interpolation using a high order function expansion, multipole representation, and different integration algorithms based on Doppler broadening equation. The other, for instance, target motion sampling (TMS), does not calculate the Doppler broadening cross sections but takes into account Doppler effect by rejection technique. In this paper, several on the fly Doppler broadening algorithms based on Doppler broadening equation are implemented in the Reactor Monte Carlo code RMC, and then the accuracy and efficiency are discussed and compared. In this paper, several algorithms for on the fly Doppler broadening based on Doppler broadening equation have been implemented in RMC and the focus falls on the comparison of the Gauss Legendre quadrature and Gauss Hermite quadrature. Gauss Legendre quadrature is more accurate than Gauss Hermite quadrature but also more time consuming. Base temperature has a significant impact on Gauss Hermite quadrature while increasing base temperature to room temperature (300 K) can give satisfactory results. In addition, the proportion of overhead of Doppler broadening treatment in total computational time tends to decrease with an increase number of nuclides in fuel. For depletion calculation, both algorithms are in good agreement with reference and the relative errors of K{sub inf} are within 5 times of standard deviation. As for total computational time, the ratio between Gauss Legendre quadrature or Gauss Hermite quadrature and reference decreases and reaches 9.6 or 3.4 at last, respectively. Four important isotopes are chosen to compare the atom density and all relative errors are within 0.25%. After comparisons of different algorithms and different base temperatures, it can be found that Gauss Hermite quadrature broadening from 300 K can perform on the fly cross section Doppler broadening with least total computational time and acceptable precision. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods

Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month. These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Monte Carlo/CFD Coupling for Accurate Modeling of the Delayed Neutron Precursors and Compressibility Effects in Molten Salt Reactors

Multiphysics reactor analysis has become one of the leading activities of most nuclear engineering research groups. Coupled neutronics and thermal/hydraulics (T/H) simulations have traditionally been performed by adopting deterministic transport tools and reactor system T/H codes. The main reason for avoiding higher fidelity numerical methods like continuous-energy Monte Carlo analysis has been the high computational cost of coupled, full-scale simulations. Nowadays, high fidelity multiphysics simulations represent a hot research topic, with several applications involving advanced nuclear systems. Liquid fuel Molten Salt Reactors (MSRs) feature peculiar physical phenomena that are not present in solid fuel reactors. Some of these phenomena are not correctly resolved by legacy reactor physics tools, and require specific treatments. This work focuses in particular on the analysis of the effect of the delayed neutron precursors drift and the impact of liquid fluid thermal expansion and compressibility in postulated criticality excursion transients in fast-spectrum MSRs. A new modeling tool based on a Monte Carlo approach for neutronics (Serpent code) coupled to a Computational Fluid Dynamic (CFD) analysis (OpenFOAM) was developed to obtain accurate modeling and simulation of these phenomena. The development of the Serpent Monte Carlo code [1] at VTT in the past few years has made this code particularly attractive for performing multiphysics studies. The availability of a flexible multiphysics interface, on-the-fly Doppler broadening and density-based collision rejection, and Delta-tracking, proved of paramount importance for the computationally efficient performance of coupled Monte Carlo/CFD calculations [2]. OpenFOAM is a C++ multiphysics toolkit featured by automatic matrix construction and solution capabilities for scalar and vector partial differential equations (PDEs), adopting several possible differencing and interpolation schemes, based on the Finite-Volume method. The ease of implementing the constitutive equations of different physical phenomena makes OpenFOAM particularly suitable for the modeling of complex coupled phenomena. In the past, several research activities proposed the adoption of both Serpent and OpenFOAM for the modeling and simulation of MSRs and the associated fuel cycles. In this work, these tools have been internally coupled for the steady-state and transient analysis of fast-spectrum systems, accounting for the effect of delayed neutron precursors transport and the salt thermal expansion and compressibility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Hadron production cross-sections at relativistic energies with large phase-space coverage - Paper 39

Accurate measurements of soft particle production in hadronic interactions at relativistic energies have long been an experimental challenge, in particular when the measurement is over a large final state phase-space, and when multiple combinations of beam and targets are investigated. Lacking quantitative predictions from the fundamental theory of quantum chromo-dynamics (QCD) in the non-perturbative sector, the study of soft hadronic physics needs to rely on precise, self-consistent, high-statistics data sets with full phase-space coverage and low systematic errors. Phenomenological models of particle production in hadronic collisions need such data to constrain their parameters, and possibly to discriminate among the underlying features of these models. In this article the 'soft' physics refers to production of particles with transverse momenta, pT, below 2 GeV/c, which comprises over 99% of the total production cross-section. It is also known as 'bulk' particle production, or the 'underlying event' in reference to the background of hard processes, particles produced with much larger transverse momentum which are usually described in the framework of perturbative QCD. Improving these models is of interest of the Radiation Protection and Shielding Division (RPSD) community, as well as the availability of accurate data with large phase space coverage. The NA49 collaboration has published new, high precision, and comprehensive sets of inclusive meson and baryon cross sections in p+p and p+C interactions over most of the available phase space with comparisons to past experimental results. The corresponding physics analysis presents a model-independent approach to soft hadronic physics and constitutes a novel approach to exploration of this non-perturbative sector of QCD. The precision study of p+A interactions may allow for differentiation between assumptions underlying different microscopic models of bulk particle production in relativistic hadronic collisions, and thus aid model development. The final data on inclusive particle production including the invariant double differential cross sections, the transversely integrated yields, and the developed interpolations, along with the published papers and other documents relevant to this work are conveniently available. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Biases in southern hemisphere climate trends induced by coarsely specifying the temporal resolution of stratospheric ozone

Abstract Global climate models that do not include interactive middle atmosphere chemistry, such as most of those contributing to the Coupled Model Intercomparison Project Phase 5, typically specify stratospheric ozone using monthly mean, zonal mean values and linearly interpolate to the time resolution of the model. We show that this method leads to significant biases in the simulated climate of the southern hemisphere (SH) over the late twentieth century. Previous studies have attributed similar biases in simulated SH climate change to the effect of the spatial smoothing of the specified ozone, i.e., to using zonal mean concentrations. We here show that the bias in climate trends due to undersampling of the rapid temporal changes in ozone during the seasonal evolution of the Antarctic ozone hole is considerable and reaches all the way into the troposphere. Our results suggest that the bias can be substantially reduced by specifying daily ozone concentrations.

Neely, III, R. R.↗
DOE OSTI2015

Development of fine-resolution analyses and expanded large-scale forcing properties. Part I: Methodology and evaluation

We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Development of fine-resolution analyses and expanded large-scale forcing properties. Part II: Scale-awareness and application to single-column model experiments

Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scales larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

An empirical model of electron and ion fluxes derived from observations at geosynchronous orbit

Knowledge of the plasma fluxes at geosynchronous orbit is important to both scientific and operational investigations. We present a new empirical model of the ion flux and the electron flux at geosynchronous orbit (GEO) in the energy range ~1 eV to ~40 keV. The model is based on a total of 82 satellite-years of observations from the Magnetospheric Plasma Analyzer instruments on Los Alamos National Laboratory satellites at GEO. These data are assigned to a fixed grid of 24 local-times and 40 energies, at all possible values of Kp. Bi-linear interpolation is used between grid points to provide the ion flux and the electron flux values at any energy and local-time, and for given values of geomagnetic activity (proxied by the 3-hour Kp index), and also for given values of solar activity (proxied by the daily F10.7 index). Initial comparison of the electron flux from the model with data from a Compact Environmental Anomaly Sensor II (CEASE-II), also located at geosynchronous orbit, indicate a good match during both quiet and disturbed periods. The model is available for distribution as a FORTRAN code that can be modified to suit user-requirements.

58 GEOSCIENCES↗
DOE OSTI2018

Calibration of the E3SM Land Model Using Surrogate‐Based Global Optimization

Abstract Calibration of the Energy Exascale Earth System Model (E3SM), land model (ELMv0) is challenging because of its model complexity, strong model nonlinearity, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near‐optimal solution within an affordable time. The goal of this study is to calibrate some of the ELMv0 parameters to improve model projection of carbon fluxes. We propose a computationally efficient global optimization procedure using sparse‐grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the ELMv0, and then calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated a sufficiently large number of times in the optimization, which facilitates the global search. We calibrate eight parameters against five years of net ecosystem exchange, total leaf area index, and latent heat flux data from the U.S. Missouri Ozark flux tower. The calibrated model is then used for predicting the three variables in the following 4 years. The results indicate that an accurate surrogate model can be created for the ELMv0 with a relatively small number of SG points, i.e., a few ELMv0 simulations that can be fully parallel. And, the application of the optimized parameters leads to a better model performance and a higher predictive capability than the default parameter values in the ELMv0.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Impact of Three-Phase Relative Permeability and Hysteresis Models on Forecasts of Storage Associated With CO 2 -EOR

Geological CO 2 sequestration in conjunction with enhanced oil recovery (CO 2 -EOR) includes complex multiphase flow processes compared to CO 2 storage in deep saline aquifers. Two of the most critical factors affecting multiphase flow in CO 2 -EOR are three-phase relative permeability and associated hysteresis, both of which are difficult to measure and are usually represented by numerical interpolation models. The purpose of this research is to improve understanding of (1) the relative impacts of different three-phase relative permeability models and hysteresis models on CO 2 trapping mechanisms, and (2) uncertainty associated with these two factors. Four different three-phase relative permeability models and three hysteresis models were applied to simulations of an active CO 2 -EOR site, the SACROC unit located in western Texas. To eliminate potential bias of deterministic parameters, we utilized a sequential Gaussian simulation technique to generate 50 realizations to describe heterogeneity of porosity and permeability, based on data obtained from well logs and seismic survey. Simulation results of forecasted CO 2 storage suggested that (1) the choice of three-phase relative permeability model and hysteresis model led to noticeable impacts on forecasted CO 2 sequestration capacity; (2) impacts of three-phase relative permeability models and hysteresis models on CO 2 trapping are small during the CO 2 -EOR injection period, and increase during the post-EOR CO 2 injection period; (3) the specific choice of hysteresis model is more important relative to the choice of three-phase relative permeability model; and (4) using the recommended three-phase WAG (Water-Alternating-Gas) hysteresis model may increase the impact of three-phase relative permeability models and uncertainty due to heterogeneity.

42 ENGINEERING↗