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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

A Monte-Carlo Model for the Formation of Radiation-induced Chromosomal Aberrations

Purpose: To simulate radiation-induced chromosome aberrations in mammalian cells (e.g., rings, translocations, and dicentrics) and to calculate their frequency distributions following exposure to DNA double strand breaks (DSBs) produced by high-LET ions. Methods: The interphase genome was assumed to be comprised of a collection of 2 kbp rigid-block monomers following the random-walk geometry. Additional details for the modeling of chromosomal structure, such as chromosomal domains and chromosomal loops, were included. A radial energy profile for heavy ion tracks was used to simulate the high-LET pattern of induced DSBs. The induced DSB pattern depended on the ion charge and kinetic energy, but always corresponded to the DSB yield of 25 DSBs/cell/Gy. The sum of all energy contributions from Poisson-distributed particle tracks was taken to account for all possible one-track and multi-track effects. The relevant output of the model was DNA fragments produced by DSBs. The DSBs, or breakpoints, were defined by (x, y, z, l) positions, where x, y, z were the Euclidian coordinates of a DSB, and where l was the relative position along the genome. Results: The code was used to carry out Monte Carlo simulations for DSB rejoinings at low doses. The resulting fragments were analyzed to estimate the frequencies of specific types of chromosomal aberrations. Histograms for relative frequencies of chromosomal aberrations and P.D.F.s (probability density functions) of a given aberration type were produced. The relative frequency of dicentrics to rings was compared to empirical data to calibrate rejoining probabilities. Of particular interest was the predicted distribution of ring sizes, irrespective of their frequencies relative to other aberrations. Simulated ring sizes were . 4 kbp, which are far too small to be observed experimentally (i.e., by microscopy) but which, nevertheless, are conjectured to exist. Other aberrations, for example, inversions, translocations, as well as multi-centrics were also recorded. Conclusion: High-LET DNA damage affects the frequencies of chromosomal aberrations. The ratio of rings to dicentrics is correct for the genomic size cut-offs corresponding to available experimental data. The present work predicts a relative abundance of small rings following irradiation by heavy ions.

Ponomarev, Artem L.↗
NASA NTRS1978

A theoretical investigation of the aerodynamics of low-aspect-ratio wings with partial leading-edge separation

A numerical method is developed to predict distributed and total aerodynamic characteristics for low aspect-ratio wings with partial leading-edge separation. The flow is assumed to be steady and inviscid. The wing boundary condition is formulated by the quasi-vortex-lattice method. The leading-edge separated vortices are represented by discrete free vortex elements which are aligned with the local velocity vector at mid-points to satisfy the force free condition. The wake behind the trailing-edge is also force free. The flow tangency boundary condition is satisfied on the wing, including the leading- and trailing-edges. Comparison of the predicted results with complete leading-edge separation has shown reasonably good agreement. For cases with partial leading-edge separation, the lift is found to be highly nonlinear with angle of attack.

Mehrotra, S. C.↗
DOE OSTI2016

Molecular dynamics investigation of hexagonal boron nitride sputtering and sputtered particle characteristics

The sputtering of hexagonal boron nitride (h-BN) by impacts of energetic xenon ions is investigated using a molecular dynamics (MD) model. The model is implemented within an open-source MD framework that utilizes graphics processing units to accelerate its calculations, allowing the sputtering process to be studied in much greater detail than has been feasible in the past. Integrated sputter yields are computed over a range of ion energies from 20 eV to 300 eV, and incidence angles from 0° to 75°. Sputtering of boron is shown to occur at energies as low as 40 eV at normal incidence, and sputtering of nitrogen at as low as 30 eV at normal incidence, suggesting a threshold energy between 20 eV and 40 eV. The sputter yields at 0° incidence are compared to existing experimental data and are shown to agree well over the range of ion energies investigated. The semi-empirical Bohdansky curve and an empirical exponential function are fit to the data at normal incidence, and the threshold energy for sputtering is calculated from the Bohdansky curve fit as 35 ± 2 eV. These results are shown to compare well with experimental observations that the threshold energy lies between 20 eV and 40 eV. It is demonstrated that h-BN sputters predominantly as atomic boron and diatomic nitrogen, and the velocity distribution function (VDF) of sputtered boron atoms is investigated. The calculated VDFs are found to reproduce the Sigmund-Thompson distribution predicted by Sigmund's linear cascade theory of sputtering. The average surface binding energy computed from Sigmund-Thompson curve fits is found to be 4.5 eV for ion energies of 100 eV and greater. This compares well to the value of 4.8 eV determined from independent experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Conservative Estimation of Tail Probabilities from Limited Sample Data

Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10 -5 to 10 -1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

The constitution of the atmospheric layers and the extreme ultraviolet spectrum of hot hydrogen-rich white dwarfs

An analysis is presented of the atmospheric properties of hot, H-rich, DA white dwarfs that is based on optical, UV, and X-ray observations aimed at predicting detailed spectral properties of these stars in the range 80-800 A. The divergences between observations from a sample of 15 hot DA white dwarfs emitting in the EUV/soft X-ray range and pure H synthetic spectra calculated from a grid of model atmospheres characterized by Teff and g are examined. Seven out of 15 DA stars are found to consistently exhibit pure hydrogen atmospheres, the remaining seven stars showing inconsistency between FUV and EUV/soft X-ray data that can be explained by the presence of trace EUV/soft X-ray absorbers. Synthetic data are computed assuming two other possible chemical structures: photospheric traces of radiatively levitated heavy elements and a stratified hydrogen/helium distribution. Predictions about forthcoming medium-resolution observations of the EUV spectrum of selected hot H-rich white dwarfs are made.

Vennes, Stephane↗
DOE OSTI2014

Anisotropic Azimuthal Power and Temperature distribution on FuelRod: Impact on Hydride Distribution

The degradation of the zirconium cladding may limit nuclear fuel performance. In the high temperature environment of a reactor, the zirconium in the cladding corrodes, releasing hydrogen in the process. Some of this hydrogen is absorbed by the cladding in a highly inhomogeneous manner. The distribution of the absorbed hydrogen is extremely sensitive to temperature and stress concentration gradients. The absorbed hydrogen tends to concentrate near lower temperatures. This hydrogen absorption and hydride formation can cause cladding failure. This project set out to improve the hydrogen distribution prediction capabilities of the BISON fuel performance code. The project was split into two primary sections, first was the use of a high fidelity multi-physics coupling to accurately predict temperature gradients as a function of r, θ , and z, and the second was to use experimental data to create an analytical hydrogen precipitation model. The Penn State version of thermal hydraulics code COBRA-TF (CTF) was successfully coupled to the DeCART neutronics code. This coupled system was verified by testing and validated by comparison to FRAPCON data. The hydrogen diffusion and precipitation experiments successfully calculated the heat of transport and precipitation rate constant values to be used within the hydrogen model in BISON. These values can only be determined experimentally. These values were successfully implemented in precipitation, diffusion and dissolution kernels that were implemented in the BISON code. The coupled output was fed into BISON models and the hydrogen and hydride distributions behaved as expected. Simulations were conducted in the radial, axial and azimuthal directions to showcase the full capabilities of the hydrogen model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Bayesian calibration of bubble size dynamics applied to CO 2 gas fermenters

To accelerate the scale-up of gaseous CO 2 fermentation reactors, computational models need to predict gas-to-liquid mass transfer which requires capturing the bubble size dynamics, i.e. bubble breakup and coalescence. However, the applicability of existing models beyond air–water mixtures remains to be established. Here, an inverse modeling approach, accelerated with a neural network surrogate, calibrates the breakup and coalescence closure models, that are used in class methods for population balance modeling (PBM). The calibration is performed based on experimental results obtained in a CO 2 -air–water-coflowing bubble column reactor. Bayesian inference is used to account for noise in the experimental dataset and bias in the simulation results. To accurately capture gas holdup and interphase mass transfer, the results show that the breakage rate needs to be increased by one order of magnitude. In conclusion, the inferred model parameters are then used on a separate configuration and shown to also improve bubble size distribution predictions.

09 BIOMASS FUELS↗
DOE OSTI2023

SCALE 6.2 Lattice Physics Performance Assessment

The US Nuclear Regulatory Commission relies on the lattice physics analysis capabilities of the SCALE code system to perform confirmatory licensing analyses. Either SCALE lattice physics code—TRITON/NEWT or Polaris—can be used to generate cross section data used by the PARCS nodal core simulator for full-core neutronics calculations. This report presents an assessment of the accuracy of SCALE lattice physics codes for preparation of lattice physics data that are used to support simulator codes such as the NRC’s PARCS, for UO 2 -mixed oxide (MOX)/Zr fueled light water reactor (LWR) analyses. Due to the nature of lattice physics calculations, critical reactor experiment benchmarks cannot be modeled in explicit detail in a lattice physics code. However, this limitation does not mean that these measurement data are not usable for lattice physics studies. Therefore, either geometry approximations or axial buckling must be implemented to determine the critical water height. These modeling limitations have led to development of a three-phase assessment strategy. In the first phase, selected critical experiment benchmarks are modeled using the SCALE 3D continuous-energy (CE) Monte Carlo (MC) code KENO, which is the most rigorous neutron transport method available in SCALE, with no approximations in the spatial, angle, or energy treatments. Biases and statistical uncertainties in quantities of interest such as k eff and pin power distributions are determined by comparing CE KENO results to experimental data. This first phase in the accuracy assessment is to demonstrate and establish the use of CE KENO as a reference solution for the second phase. In the second phase, 14 numerical test suites are used to compare SCALE lattice physics calculations with CE KENO as a reference solution. In the third phase, SCALE lattice physics depletion calculations are performed, and the spent fuel isotopic results are compared with available radiochemical assay measurements. Isotopic measurement comparisons provide quantitative assessment of isotopic density distribution predictions with the depletion models in SCALE lattice physics codes. This report documents results for all test suites. The assessment was performed using standard production techniques unless otherwise noted. Both TRITON/NEWT and Polaris exhibited acceptable accuracy for most test cases. For the few test cases in which acceptable accuracy criteria were not met, further code and data development are planned. The computer codes used in this assessment are as follows: SCALE 6.2 rev19189 (pre-release of 6.2.1) was used for CE KENO, TRITON/NEWT and Polaris (PWR only) calculations; SCALE 6.2.2 was used for Polaris calculations to address several updates in support of support boiling water reactor (BWR) lattice geometries. For this work, there is no difference between SCALE 6.2.1 and SCALE 6.2.2 beyond the inclusion of the Polaris BWR analysis capability; The ENDF/B-VII.1 continuous energy and 252 group libraries deployed in SCALE 6.2 were generated with AMPX 6.2 that is distributed with SCALE.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

General-Surrogate Adaptive Sampling Using Interquartile Range for Design Space Exploration

Abstract A surrogate model is a common tool to approximate system response at untested points for design space exploration. Adaptive sampling has been studied for improving the accuracy of surrogates iteratively by introducing additional samples (simulations and experiments). New samples are often selected based on the estimated uncertainty in the design space. While some surrogates such as kriging have readily available uncertainty models for their predictions, other surrogates do not. Consequently, there have been studies of using the process of leaving-samples-out (LSO) used in cross-validation tools to estimate prediction uncertainty, such as the universal prediction distribution (UPD). In this paper, an adaptive sampling scheme for general surrogates is proposed based on LSO, similar to cross-validation and interquartile range (IQR). Multiple submodels are first developed from LSO. The uncertainty is then estimated from the IQR of these surrogates at a given point. New samples are added iteratively at the point with maximum IQR for design space exploration. The proposed scheme is illustrated using kriging, radial basis function, and neural network surrogates. The proposed scheme is evaluated using four algebraic test functions. Multiple sets of initial samples were produced to account for randomness. For these test functions, the proposed scheme was found to be more accurate and robust than kriging with its own uncertainty model. The proposed scheme was more accurate than the UPD for three out of the four test functions. For a fixed number of samples, the IQR-based adaptive sampling also proved to be more accurate than all-at-once sampling in most cases even when the estimated uncertainty was only mildly correlated with prediction errors.

Engineering↗
DOE OSTI2021

BrazilClim : The overcoming of limitations of pre‐existing bioclimate data

Abstract Species distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate‐based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on‐field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge‐calibrated the best performing surfaces using machine‐learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predicted distributions and more actual pictures of the species' ecological requirements for megadiverse Brazil, an approach replicable elsewhere. All primary and bioclimatic surfaces generated for this study may be freely downloaded.

Ramoni‐Perazzi, Paolo↗
DOE OSTI2021

Seabird distribution is better predicted by abundance of prey than oceanography. A case study in the Gulf of Cadiz (SW, Iberian Peninsula)

Abstract Quantifying factors that influence marine predator distributions is essential to understanding the current and future change in marine biodiversity. Here, we test whether marine predator distribution relates to prey, or is better predicted by other specific habitat features. We examine the correlation between spatial distribution of three seabird species and their prey, as well as environmental proxies (oceanographic characteristics) in the Gulf of Cadiz, NE Atlantic. We modeled the at-sea distribution of Cory's shearwater, Balearic shearwater and Northern gannet, based on: (i) pelagic fish abundance according to acoustic surveys, and (ii) a forecast-model of remotely sensed environmental variables (productivity, sea surface temperature, and salinity). In general, seabird distributions were better predicted by abundance of fish than by environmental variables at the habitat scale. We obtained consistent correlations between seabird presence and the abundance of medium-sized (10–20 cm) sardines, anchovies and Mediterranean horse mackerel, providing information on their preferred prey. Additionally, oceanographic productivity variables moderately contributed to seabird distribution models, with better predictive value for the critically endangered Balearic shearwater and Northern gannet in the summer, whilst the model for Cory's shearwater's produced poorer predictions. Predator–prey combined studies may represent essential tools for an efficient ecosystem-based management of marine environments.

de la Cruz, Andrés (ORCID:0000000203632498)↗
DOE OSTI2015

Monte Carlo modeling of ultrasound probes for image guided radiotherapy

Purpose: To build Monte Carlo (MC) models of two ultrasound (US) probes and to quantify the effect of beam attenuation due to the US probes for radiation therapy delivered under real-time US image guidance. Methods: MC models of two Philips US probes, an X6-1 matrix-array transducer and a C5-2 curved-array transducer, were built based on their megavoltage (MV) CT images acquired in a Tomotherapy machine with a 3.5 MV beam in the EGSnrc, BEAMnrc, and DOSXYZnrc codes. Mass densities in the probes were assigned based on an electron density calibration phantom consisting of cylinders with mass densities between 0.2 and 8.0 g/cm{sup 3}. Beam attenuation due to the US probes in horizontal (for both probes) and vertical (for the X6-1 probe) orientation was measured in a solid water phantom for 6 and 15 MV (15 × 15) cm{sup 2} beams with a 2D ionization chamber array and radiographic films at 5 cm depth. The MC models of the US probes were validated by comparison of the measured dose distributions and dose distributions predicted by MC. Attenuation of depth dose in the (15 × 15) cm{sup 2} beams and small circular beams due to the presence of the probes was assessed by means of MC simulations. Results: The 3.5 MV CT number to mass density calibration curve was found to be linear with R{sup 2} > 0.99. The maximum mass densities in the X6-1 and C5-2 probes were found to be 4.8 and 5.2 g/cm{sup 3}, respectively. Dose profile differences between MC simulations and measurements of less than 3% for US probes in horizontal orientation were found, with the exception of the penumbra region. The largest 6% dose difference was observed in dose profiles of the X6-1 probe placed in vertical orientation, which was attributed to inadequate modeling of the probe cable. Gamma analysis of the simulated and measured doses showed that over 96% of measurement points passed the 3%/3 mm criteria for both probes placed in horizontal orientation and for the X6-1 probe in vertical orientation. The X6-1 probe in vertical orientation caused the highest attenuation of the 6 and 15 MV beams, which at 10 cm depth accounted for 33% and 43% decrease compared to the respective (15 × 15) cm{sup 2} open fields. The C5-2 probe in horizontal orientation, on the other hand, caused a dose increase of 10% and 53% for the 6 and 15 MV beams, respectively, in the buildup region at 0.5 cm depth. For the X6-1 probe in vertical orientation, the dose at 5 cm depth for the 3-cm diameter 6 MV and 5-cm diameter 15 MV beams was attenuated compared to the corresponding open fields to a greater degree by 65% and 43%, respectively. Conclusions: MC models of two US probes used for real-time image guidance during radiotherapy have been built. Due to the high beam attenuation of the US probes, the authors generally recommend avoiding delivery of treatment beams that intersect the probe. However, the presented MC models can be effectively integrated into US-guided radiotherapy treatment planning in cases for which beam avoidance is not practical due to anatomy geometry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Consistent spatial expansion functions on hexagonal surfaces for use in radiation transport methods

Some of the radiation transport solvers that are based on expansion function methods in hexagonal geometry generally use projection techniques that transform the spatial dependence of the angular flux in hexagonal geometry to Cartesian geometry by mapping and then expanding in terms of expansion functions (e.g., Legendre polynomials). However, this approach usually requires a relatively higherorder expansion in space for accurate representation of the spatial distribution of the flux. To overcome this limitation, a set of consistent spatial expansion functions have been developed in hexagonal geometry in this paper. These functions satisfy the orthogonality condition on hexagonal surfaces and guarantee the conservation of currents after expansion regardless of the truncation order. The latter is an important property for preservation of neutron balance. The new spatial expansion method has been implemented into the coarse mesh radiation transport (COMET) code and tested in both the single assembly and the full core Advanced High Temperature Reactor (AHTR) benchmark problems. The eigenvalues and assembly-averaged and stripe-wise fission density distributions predicted by the new method with 2nd order spatial expansion functions were found to exhibit similar accuracy as those computed by the current mapping method with 4th order spatial expansion functions. This indicates that the angular fluxes in AHTRs can be predominantly represented by a low order expansion if the new spatial expansion functions are used. As a result, to maintain the same accuracy, the computational efficiency of COMET is improved significantly (2–5 times) by using the new spatial expansion method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Two-step neutronics calculations with Shift and Griffin for advanced reactor systems

This research develops the initial coupling of the Shift Monte Carlo (MC) code and the Griffin reactor physics code for reactor analysis of non–light-water reactor systems. The novelty of this work is twofold. It is the first application of Shift to produce the multigroup cross sections needed for Griffin as applied to a non–light-water reactor system; and, the first investigation and analysis of characteristics of the Empire microreactor benchmark that should be considered for steady state and transient reactor physics calculations. This application uses the previously developed two-step neutronics analysis workflow to demonstrate this initial coupling. Here, we outline the two-step neutronics analysis workflow in which the Shift MC code is used to generate the multigroup cross sections and fluxes needed by the Griffin deterministic solver. Details on how these multigroup cross sections are generated using MC tallies are given, as well as the practicalities and limitations of the two-step neutronics workflow. The Empire microreactor benchmark was used to investigate and validate this coupling. Results using this benchmark show good agreement between Griffin calculations using Serpent-generated cross sections and Shift-generated cross sections. Analysis of the characteristics of this Empire benchmark show larger eigenvalue differences between heterogeneous and pin–homogenized solutions compared to those of traditional light-water reactor (LWR) designs, thus requiring super homogenization factor corrections for accurate eigenvalue and power distribution predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

High–Resolution Maps of Near–Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter–scale maps of near–surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near–surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k–fold cross validation, and the modeled extents of near–surface permafrost were compared to the observed extents at each site. At–a–site near–surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at–a–site prediction (70%–83%), yet they had greater accuracy when transferred to the non–training site (62%–78%). These models demonstrate the potential for integrating high–resolution spatial data and machine learning models to develop maps of near–surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Reverse Mössbauer effect as a possible source of “hot” molecules absorbed in crystalline solids at low temperature

As an attempt to explain some of the many anomalies and unresolved problems which have been reported about the dynamic behavior of particles and molecules absorbed in crystalline solids, the “reverse Mössbauer effect” (RME) is proposed. RME theory posits that a particle in non-equilibrium state with respect to a crystal (colliding with the crystal or absorbed in it, but set out of thermal equilibrium by some external cause) is scattered by the whole crystal with a momentum proportional to a vector representing a reciprocal lattice point. The scattering is expected to occur with a well-defined probability and the momentum transferable to the particle is expected to follow a predictable distribution. The RME theory, in practice, is an extension of the Bragg–von Laue scattering law to high-energy colliding particles, in general, and can be applied to any particle or molecule colliding with the surface of a crystalline solid or absorbed in it, but not in thermal equilibrium with the crystal lattice. We verified the RME theory by considering a well-defined unresolved problem. In an experimental study about methane adsorbed in the zeolite Na-ZSM-5 [H. Jobic, Chem. Phys. Lett. 170, 217 (1990)] reporting neutron inelastic-scattering spectra (recoiled bands) at 10 K, the translational kinetic energy of methane resulted to be much higher than equilibrium expected value, namely, about 85 K (or 7.3 meV). The author concluded that “the interpretation of this unusual behavior has yet to be found.” In the present study, on the basis of the RME, an explanation of this behavior is put forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

PROSPECTS FOR CHARACTERIZING HOST STARS OF THE PLANETARY SYSTEM DETECTIONS PREDICTED FOR THE KOREAN MICROLENSING TELESCOPE NETWORK

I investigate the possibility of constraining the flux of the lens (i.e., host star) for the types of planetary systems the Korean Microlensing Telescope Network is predicted to find. I examine the potential to obtain lens flux measurements by (1) imaging the lens once it is spatially resolved from the source, (2) measuring the elongation of the point-spread function of the microlensing target (lens+source) when the lens and source are still unresolved, and (3) taking prompt follow-up photometry. In each case I simulate the observing programs for a representative example of current ground-based adaptive optics (AO) facilities (specifically NACO on the Very Large Telescope), future ground-based AO facilities (GMTIFS on the Giant Magellan Telescope, GMT), and future space telescopes (NIRCAM on the James Webb Space Telescope, JWST). Given the predicted distribution of relative lens-source proper motions, I find that the lens flux could be measured to a precision of σ{sub H{sub ℓ}}≤0.1 for ≳60% of planet detections ≥5 yr after each microlensing event for a simulated observing program using GMT, which images resolved lenses. NIRCAM on JWST would be able to carry out equivalently high-precision measurements for ∼28% of events Δt = 10 yr after each event by imaging resolved lenses. I also explore the effects various blend components would have on the mass derived from prompt follow-up photometry, including companions to the lens, companions to the source, and unassociated interloping stars. I find that undetected blend stars would cause catastrophic failures (i.e., >50% fractional uncertainty in the inferred lens mass) for ≲ (16 · f {sub bin})% of planet detections, where f {sub bin} is the binary fraction, with the majority of these failures occurring for host stars with mass ≲0.3 M {sub ☉}.

79 ASTRONOMY AND ASTROPHYSICS↗