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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Am-241 Nuclear Safety and Environmental Interactions

NASA’s supply of radioisotopes for Radioisotope Heat Units (RHU) and Radioisotope Thermoelectric Generator (RTG) power sources is facing a crisis due to shortages of Pu-238 for future missions. Am-241 is a possible replacement for Pu-238 since its stockpile from the nuclear weapons program has remained relatively intact. The purpose of this project was to assess the safety of Am-241 and the risks associated with it as compared with PU-238. The project has resulted in a journal article, F. De-La-Torre-Aguilar, N. White, M. Prelas, R. V. Tompson, and S. K. Loyalka "Space nuclear power system accidents: Doses from Pu-238 and Am- 241 inhalation," Progress in Nuclear Energy vol.100C (2017), pp.171-182, which showed that the radiation dosage resulting from Am-241 inhalation are about 1/2.5 of the dosage resulting from Pu-238 inhalation per KW of Pu-238 power. Considerable progress was also made on the Direct Simulation Monte Carlo Method (DSMC) for simulation of aerosol evolution during accidents resulting in three publications: 1.I. Saldivar, F. De-La-Torre-Aguilar, M. Boraas, and S. K. Loyalka “Benchmark problems in aerosol evolution: Comparison of some exact and DSMC results” in Annals of Nuclear Energy vol.117 (2018), pp.213-222. 2. I. Saldivar and S. K. Loyalka, “Evolution of Aerosols Coupled to Environments: Verification of Direct Simulation Monte Carlo (DSMC)”, Nuclear Technology 204 (2018), pp.172-183. 3. M. Boraas and S. K. Loyalka, “Mesh Free Simulation of Spatially Inhomogeneous aerosols in Arbitrary Geometries” Nuclear Science and Engineering (2018). Further, we have computations on Am-241/Pu-238 vapor and aerosol interactions, and found that the vapor condensation rate is relatively insensitive to the mass effects, confirming some previous results. We have also completed computations of charge effects on evolution of different species aerosols and a manuscript is in preparation. Additionally, we have compared atmospheric dispersion and deposition of Pu-238 and Am-241 using the HYSPLIT code. We have also used a real lung model and the CFD program FLUENT to compute PuO2 and AmO2 deposition to explore improvements upon the ICPR-66 model. We have found that the deposition efficiencies of PuO2 and AmO2 are similar. These results (four manuscripts) will be submitted for publication in the post project period. We have made progress using framework of Mars 2020 mission nuclear risk assessment model to integrate all results, but our progress has been limited as the improved consequence modeling itself has been quite involved and challenging. We will integrate and complete the more extensive risk modeling computations and publish the results in the post-project period. In addition to the above, the project has resulted in research training of four PhD students

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2008

Effect of the Inhomogeneity of Ice Crystals on Retrieving Ice Cloud Optical Thickness and Effective Particle Size

Spherical or spheroidal air bubbles are generally trapped in the formation of rapidly growing ice crystals. In this study the single-scattering properties of inhomogeneous ice crystals containing air bubbles are investigated. Specifically, a computational model based on an improved geometric-optics method (IGOM) has been developed to simulate the scattering of light by randomly oriented hexagonal ice crystals containing spherical or spheroidal air bubbles. A combination of the ray-tracing technique and the Monte Carlo method is used. The effect of the air bubbles within ice crystals is to smooth the phase functions, diminish the 22deg and 46deg halo peaks, and substantially reduce the backscatter relative to bubble-free particles. These features vary with the number, sizes, locations and shapes of the air bubbles within ice crystals. Moreover, the asymmetry factors of inhomogeneous ice crystals decrease as the volume of air bubbles increases. Cloud reflectance lookup tables were generated at wavelengths 0.65 m and 2.13 m with different air-bubble conditions to examine the impact of the bubbles on retrieving ice cloud optical thickness and effective particle size. The reflectances simulated for inhomogeneous ice crystals are slightly larger than those computed for homogenous ice crystals at a wavelength of 0.65 microns. Thus, the retrieved cloud optical thicknesses are reduced by employing inhomogeneous ice cloud models. At a wavelength of 2.13 microns, including air bubbles in ice cloud models may also increase the reflectance. This effect implies that the retrieved effective particle sizes for inhomogeneous ice crystals are larger than those retrieved for homogeneous ice crystals, particularly, in the case of large air bubbles.

Xie, Yu↗
DOE OSTI2013

A Local Incident Flux Response Expansion Transport Method for Coupling to the Diffusion Method in Cylindrical Geometry

A local incident flux response expansion transport method is developed to generate transport solutions for coupling to diffusion theory codes regardless of their solution method (e.g., fine mesh, nodal, response based, finite element, etc.) for reactor core calculations in both two-dimensional (2-D) and three-dimensional (3-D) cylindrical geometries. In this approach, a Monte Carlo method is first used to precompute the local transport solution (i.e., response function library) for each unique transport coarse node, in which diffusion theory is not valid due to strong transport effects. The response function library is then used to iteratively determine the albedo coefficients on the diffusion-transport interfaces, which are then used as the coupling parameters within the diffusion code. This interface coupling technique allows a seamless integration of the transport and diffusion methods. The new method retains the detailed heterogeneity of the transport nodes and naturally constructs any local solution within them by a simple superposition of local responses to all incoming fluxes from the contiguous coarse nodes. A new technique is also developed for coupling to fine-mesh diffusion methods/codes. The local transport method/module is tested in 2-D and 3-D pebble-bed reactor benchmark problems consisting of an inner reflector, an annular fuel region, and a controlled outer reflector. It is found that the results predicted by the transport module agree very well with the reference fluxes calculated directly by MCNP in both benchmark problems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Integrated microRNA and mRNA signatures in peripheral blood lymphocytes of familial epithelial ovarian cancer

Highlights: • We analyzed the differentially expressed miRNAs along with their target genes in a novel integrated network. • We conducted target gene prediction and the co-expression analysis of miRNAs and mRNAs. • This is the first report that PLS and Monte Carlo methods are combined to construct an integrated network of miRNAs and mRNAs. • Experiments are needed to understand the differentially expressed miRNAs and their effects on predicted targets' expression. • The research provide insights on miRNA-mRNA networks and transcriptional variants studies in familial ovarian cancer. Characterization of the genetic landscapes of familial ovarian cancer through integrated analysis of microRNA and mRNA by partial least squares (PLS) and Monte Carlo technique based on genome-wide association studies (GWAS).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite and analytical models, we train a machine learning algorithm to learn the probability function between cosmological parameters and the possible galaxy cluster observables. The posterior distribution of the cosmological parameters at a given observation is then obtained by sampling the predictions from the trained algorithm. Our results show that the SBI method can successfully recover the truth values of the cosmological parameters within the 2σ limit for this simplified galaxy cluster analysis, and acquires similar posterior constraints obtained with a likelihood-based Markov Chain Monte Carlo method, the current state-of the-art method used in similar cosmological studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1985

Advanced reliability methods for structural evaluation

Fast probability integration (FPI) methods, which can yield approximate solutions to such general structural reliability problems as the computation of the probabilities of complicated functions of random variables, are known to require one-tenth the computer time of Monte Carlo methods for a probability level of 0.001; lower probabilities yield even more dramatic differences. A strategy is presented in which a computer routine is run k times with selected perturbed values of the variables to obtain k solutions for a response variable Y. An approximating polynomial is fit to the k 'data' sets, and FPI methods are employed for this explicit form.

Wirsching, P. H.↗
DOE OSTI2021

25 Siβ + -decay spectroscopy

Background: β-decay spectroscopy provides valuable information on exotic nuclei and a stringent test for nuclear theories beyond the stability line. Purpose: To search for new β-delayed protons and γ rays of 25 Si to investigate the properties of 25 Al excited states. Method: 25 Si β decays were measured by using the Gaseous Detector with Germanium Tagging system at the National Superconducting Cyclotron Laboratory. The protons and γ rays emitted in the decay were detected simultaneously. Here, a Monte Carlo method was used to model the Doppler broadening of 24 Mg γ-ray lines caused by nuclear recoil from proton emission. Shell-model calculations using two newly developed universal sd-shell Hamiltonians were performed. Results: The most precise 25Si half-life to date has been determined. A new proton branch at 724(4) keV and new proton-γ-ray coincidences have been identified. Three 24 Mg γ-ray lines and eight 25 Al γ-ray lines are observed for the first time in 25 Si decay. The first measurement of the 25 Si β-delayed γ-ray intensities through the 25 Al unbound states is reported. All the bound states of 25 Al are observed to be populated in the β decay of 25 Si. Several inconsistencies between the previous measurements have been resolved, and new information on the 25 Al level scheme is provided. An enhanced decay scheme has been constructed and compared to the mirror decay of 25 Na and the shell-model calculations. Conclusions: The measured excitation energies, γ-ray and proton branchings, log $ft$ values, and Gamow-Teller transition strengths for the states of 25 Al populated in the β decay of 25 Si are in good agreement with the shell model calculations, offering gratifyingly consistent insights into the fine nuclear structure of 25 Al.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Uncertainty quantification of mass models using ensemble Bayesian model averaging

Developments in the description of the masses of atomic nuclei have led to various nuclear mass models that provide predictions for masses across the whole chart of nuclides. These mass models play an important role in understanding the synthesis of heavy elements in the rapid neutron capture ( r ) process. However, it is still a challenging task to estimate the size of uncertainty associated with the predictions of each mass model. In this work, a method called ensemble Bayesian model averaging (EBMA) is introduced to quantify the uncertainty of one-neutron separation energies (S 1 n ) which are directly relevant in the calculations of r -process observables. Here, this Bayesian method provides a natural way to perform model averaging, selection, and uncertainty quantification, by combining the mass models as a mixture of normal distributions whose parameters are optimized against the experimental data, employing the Markov chain Monte Carlo method using the no-u-turn sampler. The EBMA model optimized with all the experimental S 1 n from the AME2003 nuclides are shown to provide reliable uncertainty estimates when tested with the new data in the AME2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Neural simulation-based inference of the neutron star equation of state directly from telescope spectra

Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A continuous symmetry breaking measure for finite clusters using Jensen-Shannon divergence

A quantitative measure of symmetry breaking is introduced that allows the quantification of which symmetries are most strongly broken due to the introduction of some kind of defect in a perfect structure. The method uses a statistical approach based on the Jensen-Shannon divergence. The measure is calculated by comparing the transformed atomic density function with its original. Software code is presented that carries the calculations out numerically using Monte Carlo methods. The behavior of this symmetry breaking measure is tested for various cases including finite size crystallites (where the surfaces break the crystallographic symmetry), atomic displacements from high symmetry positions, and collective motions of atoms due to rotations of rigid octahedra. Finally, the approach provides a powerful tool for assessing local symmetry breaking and offers new insights that can help researchers understand how different structural distortions affect different symmetry operations.

atomic & molecular structure↗
DOE OSTI2016

Extreme data compression for the CMB

We apply the Karhunen-Loéve methods to cosmic microwave background (CMB) data sets, and show that we can recover the input cosmology and obtain the marginalized likelihoods in Λ cold dark matter cosmologies in under a minute, much faster than Markov chain Monte Carlo methods. This is achieved by forming a linear combination of the power spectra at each multipole l, and solving a system of simultaneous equations such that the Fisher matrix is locally unchanged. Instead of carrying out a full likelihood evaluation over the whole parameter space, we need evaluate the likelihood only for the parameter of interest, with the data compression effectively marginalizing over all other parameters. The weighting vectors contain insight about the physical effects of the parameters on the CMB anisotropy power spectrum C l . The shape and amplitude of these vectors give an intuitive feel for the physics of the CMB, the sensitivity of the observed spectrum to cosmological parameters, and the relative sensitivity of different experiments to cosmological parameters. We test this method on exact theory C l as well as on a Wilkinson Microwave Anisotropy Probe (WMAP)-like CMB data set generated from a random realization of a fiducial cosmology, comparing the compression results to those from a full likelihood analysis using CosmoMC. Furthermore, after showing that the method works, we apply it to the temperature power spectrum from the WMAP seven-year data release, and discuss the successes and limitations of our method as applied to a real data set.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Monocular Horizon Navigation

The Artemis program advances towards operations on the lunar surface, where precise surface localization is a driving need for safety and science. Using the observable horizon as an image landmark allows for estimating the photographer’s position. This work analyzes the application of Perspective-n-Point (PnP) algorithms to this lunar localization problem. Batch simulations using lunar topography display the accuracy and drawbacks of these methods. Monte Carlo techniques show the pipeline’s solutions as measurements provided to a navigation filter. When filtered, these solutions have position errors of 50 meters or better, which is similar to or better than the performance of other methods of surface localization.

optical navigation↗
DOE OSTI2015

Feasibility of RACT for 3D dose measurement and range verification in a water phantom

Purpose: The objective of this study is to establish the feasibility of using radiation-induced acoustics to measure the range and Bragg peak dose from a pulsed proton beam. Simulation studies implementing a prototype scanner design based on computed tomographic methods were performed to investigate the sensitivity to proton range and integral dose. Methods: Derived from thermodynamic wave equation, the pressure signals generated from the dose deposited from a pulsed proton beam with a 1 cm lateral beam width and a range of 16, 20, and 27 cm in water using Monte Carlo methods were simulated. The resulting dosimetric images were reconstructed implementing a 3D filtered backprojection algorithm and the pressure signals acquired from a 71-transducer array with a cylindrical geometry (30 × 40 cm) rotated over 2π about its central axis. Dependencies on the detector bandwidth and proton beam pulse width were performed, after which, different noise levels were added to the detector signals (using 1 μs pulse width and a 0.5 MHz cutoff frequency/hydrophone) to investigate the statistical and systematic errors in the proton range (at 20 cm) and Bragg peak dose (of 1 cGy). Results: The reconstructed radioacoustic computed tomographic image intensity was shown to be linearly correlated to the dose within the Bragg peak. And, based on noise dependent studies, a detector sensitivity of 38 mPa was necessary to determine the proton range to within 1.0 mm (full-width at half-maximum) (systematic error < 150 μm) for a 1 cGy Bragg peak dose, where the integral dose within the Bragg peak was measured to within 2%. For existing hydrophone detector sensitivities, a Bragg peak dose of 1.6 cGy is possible. Conclusions: This study demonstrates that computed tomographic scanner based on ionizing radiation-induced acoustics can be used to verify dose distribution and proton range with centi-Gray sensitivity. Realizing this technology into the clinic has the potential to significantly impact beam commissioning, treatment verification during particle beam therapy and image guided techniques.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Low Rank Approximation-based Quadrature for Fast Evaluation of Multi-Particle Integrals [Poster]

The objectives of this project are to (1) Develop efficient integration methods for high-dimensional integrals arising in quantum chemistry; (2) Explore the utility of quadrature methods and low-rank tensor approximations for integration efficiency and scalability gains; and (3) Evaluate the integration performance with respect to the number of function evaluations (chemistry computations) compared to the state-of-the-art Monte-Carlo methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗
NASA NTRS1972

A modified Monte Carlo model for the ionospheric heating rates

A Monte Carlo method is adopted as a basis for the derivation of the photoelectron heat input into the ionospheric plasma. This approach is modified in an attempt to minimize the computation time. The heat input distributions are computed for arbitrarily small source elements that are spaced at distances apart corresponding to the photoelectron dissipation range. By means of a nonlinear interpolation procedure their individual heating rate distributions are utilized to produce synthetic ones that fill the gaps between the Monte Carlo generated distributions. By varying these gaps and the corresponding number of Monte Carlo runs the accuracy of the results is tested to verify the validity of this procedure. It is concluded that this model can reduce the computation time by more than a factor of three, thus improving the feasibility of including Monte Carlo calculations in self-consistent ionosphere models.

Mayr, H. G.↗
DOE OSTI2024

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗
NASA NTRS1985

Comments on the measurements of multiple muon phenomena

The extensive air showers in the energy around 10 to the 15th power eV include those initiated by astrophysical primary gamma-rays. The observations need a precise measurement on the directions of primary particles. It is one of the methods to measure the directions of high-energy muons in air showers. The accuracy in measuring the direction, by calculating the cosmic-ray phenomena in the atmosphere at very high energy was investgated. The results calculated by Monte Carlo method suggest that one may determine the direction of primary cosmic-rays within errors of 10/3 rad in observing muons of above 100 GeV at sea level.

Sato, T.↗