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DSMC Simulation of Etch Pit Formation Through Active Sites in Carbon Fiber Micro-Structures

Erosion of carbon due to oxidation does not occur uniformly but through localized etch pit formation because of active surface sites. In this work we demonstrate a newly developed capability to capture pitting of carbon fiber microstructures such as FiberForm, which is commonly used as the base material for NASA’s spacecraft ablative thermal protection systems (TPS). The simulations are performed at the meso-scale in order to capture the pit formation and growth using direct simulation Monte Carlo (DSMC), specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code. Legacy and latest models both assume uniform reactivity of carbon surface sites with oxygen even at the meso-scale level. However, in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale. The defective nature of these sites enhances their reactivity with atmospheric gases compared to the non-defective sites (2-3 orders of magnitude) and are termed as “active sites”. Thus, these sites tend to be the first to react and eventually get removed through the formation of gases such as CO, CO2, and CN. Their removal results in all the neighboring atoms becoming defective, thus leading to chain reaction of localized carbon removal and formation of etch pits. Capturing the formation of pits during the ablation simulation of carbon micro-structures is critical to predicting their structural failure. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various detailed surface reaction mechanisms. We have implemented the capability of a single surface having multiple site sets with different reactivities within this framework. We have used this feature to model the presence of active sites on carbon surfaces, whose reactivity is orders of magnitude higher than that of the passive sites due to the presence of defects. The active site fraction is a property of surface elements within SPARTA and is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we can capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗
DOE OSTI2019

VEXS, An Open Platform for the Study of Continuous-Energy Cross-Section Lookup Algorithms on GPU’s

A significant bottleneck in continuous-energy neutron transport simulations is the cross-section lookup problem, especially in the case of those occurring in depleted fuel regions. Several algorithms have been developed over the years to solve this problem on more traditional CPU-based platforms, however new computational architectures such as GPUs may not benefit as significantly from these algorithms. As there is increasing interest in using these new computational architectures as a core part of large simulations, the relative efficacy of these algorithms compared to one another is an interesting area of research. Additionally, implementations of these algorithms are sometimes inaccessible to interested scientists outside of the nuclear engineering field given the export-controlled nature of the codes they are implemented in. In this paper, we describe our work to extend an existing open-source platform for cross-section lookup simulation, XSBench, to GPUs. We also describe our adaptation of the original codebase to handle more realistic datasets, and our efforts to accommodate different in-memory data layouts in order to more closely approximate those implementations used in production codes. Finally, we compare our results with those obtained from Shift, a GPU-enabled Monte Carlo transport solver developed for large neutron transport simulations.

Shriver, Forrest↗
DOE OSTI2021

A REDUCED ORDER MODELING APPROACH TO PROBABILISTIC CREEP-DAMAGE PREDICTIONS IN FINITE ELEMENT ANALYSIS

This paper introduces a computationally efficient Reduced Order Modeling (ROM) approach for the probabilistic prediction of creep-damage failure. Component-level probabilistic simulations are needed to assess the reliability and safety of high-temperature components. Full-scale probabilistic creep-damage modeling in finite element (FE) approach is computationally expensive requiring many hundreds of simulations to replicate the uncertainty of component failure. To that end, ROM is proposed to minimize the elevated computational cost while controlling the loss of accuracy. It is proposed that full-scale probabilistic simulations can be completed in 1D at a reduced cost, the extremum conditions extracted, and those conditions applied for lower-cost 2D/3D probabilistic simulations of components that capture the mean and uncertainty of failure. The probabilistic Sine-hyperbolic (Sinh) model is selected which in previous work was calibrated to alloy 304 stainless steel. The Sinh model includes probability density functions (pdfs) for test condition (stress and temperature), initial damage (i.e. microstructure), and material properties uncertainty. The Sinh model is programmed into ANSYS finite element software using the USERCREEP.F material subroutine. First, the Sinh model and FE code are subject to verification and validation to ensure the accuracy of the simulations. Numerous Monte Carlo simulations are executed in a 1D model to generate probabilistic creep deformation, damage, and rupture data. This data is analyzed and the probabilistic parameters corresponding to extreme creep response are extracted. The ROM concept is applied where only the extreme conditions are applied in the 2D probabilistic prediction of a component. The probabilistic predictions between the 1D and 2D geometry is compared to assess ROM for creep. The accuracy of the probabilistic prediction employing the ROM approach will potentially reduce the time and cost of simulating complex engineering systems. Future studies will introduce multi-stage Sinh, stochasticity, and spatial uncertainty for improved prediction.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Parallelization of a Proxy Transport App Using ComputeCPP and SYCL

This document details the attempts to parallelize a multi-group Monte Carlo proxy app using SYCL and the ComputeCPP Community Edition compiler. SYCL is a standard set by the Khronos Group and is described as a, “cross-platform abstraction layer that builds on the underlying concepts, portability and efficiency of OpenCL that enables code for heterogeneous processors to be written in a “single-source” style using completely standard C++.” ComputeCpp Community Edition (CE) is a heterogeneous parallel programming platform that provides a conformant implementation of the SYCL™ 1.2.1 Khronos specification. ComputeCPP provides a compiler and an SDK containing a build system to improve the usability of the compiler. The supported OpenCL 1.2 platforms for ComputeCpp are AMD® and Intel®, with experimental support for PTX which is used on Nvidia graphics cards as well as experimental support for ARM chips. All testing reported in this document was done on the Darwin computer cluster using an Nvidia GTX Titan X graphics card. Since ComputeCPP does not support using this card with OpenCL, ComputeCPP’s experimental PTX64 bit-code generation was used to generate device code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗
NASA NTRS2007

Comparison of Integrated Radiation Transport Models with TEPC Measurements for the Average Quality Factors in Spaceflights

The purpose of this work is to test our theoretical model for the interpretation of radiation data measured in space. During the space missions astronauts are exposed to the complex field of radiation type and kinetic energies from galactic cosmic rays (GCR), trapped protons, and sometimes solar particle events (SPEs). The tissue equivalent proportional counter (TEPC) is a simple time-dependent approach for radiation monitoring for astronauts on board the International Space Station. Another and a newer approach to Microdosimetry is the use of silicon-on-insulator (SOI) technology launched on the MidSTAR-1 mission in low Earth orbit (LEO). In the radiation protection practice, the average quality factor of a radiation field is defined as a function of linear energy transfer (LET), Q(sub ave)(LET). However, TEPC measures the average quality factor as a function of the lineal energy y, Q(sub ave)(y), defined as the average energy deposition in a volume divided by the average chord length of the volume. Lineal energy, y, deviates from LET due to energy straggling, delta-ray escape or entry, and nuclear fragments produced in the detector volume. Monte Carlo track structure simulation was employed to obtain the response of a TEPC irradiated with charged particle for an equivalent site diameter of 1 micron of wall-less counter. The calculated data of the energy absorption in the wall-less counter were compiled for various y values for several ion types at various discrete projectile energy levels. For the simulation of TEPC response from the mixed radiation environments inside a spacecraft, such as, Space Shuttle and International Space Station, the complete microdosimetric TEPC response, f( y, E, Z), were calculated with the Monte Carlo theoretical results by using the first order Lagrangian interpolation for a monovariate function at a given y value (y = 0.1 keV/micron 5000 keV/micron) at any projectile energy level (E = 0.01 MeV/u to 50,000 MeV/u) of each specific radiation type (Z = 1 to 28). Because the anomalous response has been observed at large event sizes in the experiment due to the escape of energy out of sensitive volume by delta-rays and the entry of delta-rays from the high-density wall into the low-density gas-volume cavity, Monte Carlo simulation was also made for the response of a walled-TEPC with wall thickness 2 mm and density 1 g/cm(exp 3). The radius of cavity was set to 6.35 mm and a gas density 7.874 x 10(exp -5) g/cm(exp 3). The response of the walled- and the wall-less counters were compared. The average quality factor Q(sub ave)(y) for trapped protons on STS-89 demonstrated the good agreement between the model calculations and flight TEPC data as shown. Using an integrated space radiation model (this includes the transport codes HZETRN and BRYNTRN, the quantum nuclear interaction model QMSFRG) and the resultant response distribution functions of walled-TEPC from Monte-Carlo track simulations, we compared model calculations with walled-TEPC measurements from NASA missions in LEO and made predictions for the lunar and the Mars missions. The Q(sub ave)(y) values for the trapped or the solar protons ranged from 1.9-2.5. This over-estimates the Qave(LET) values which ranged from 1.4-1.6. Both quantities increase with shield thickness due to nuclear fragmentation. The Q(sub ave)(LET) for the complete GCR spectra was found to be 3.5-4.5, while flight TEPCs measured 2.9-3.4 for Q(sub ave)(y). The GCR values are decreasing with the shield thickness. Our analysis for a proper interpretation of data supports the use of TEPCs for monitoring space radiation environment.

Kim, Myung-Hee Y.↗
DOE OSTI2018

pysrim: Automation, Analysis, and Plotting of SRIM Calculations

The behavior of ions traveling through a material is of great interest to many fields. For instance, radiation damage in nuclear materials and ion beam modification of materials are most concerned with understanding the formation and evolution of defects along the ion path (Was 2016). Some of the important properties that can be gleaned from investigating the initial damage from the ion include: numbers of interstitials and vacancies produced, energy deposited per unit length to electrons and atomic nuclei, track diameter, and implanted ion profile. These properties enable further simulations and allow computing a common unit of radiation damage dose, displacements per atom (dpa), which can be used to compare irradiation experiments with different ions (Backman et al. 2013) (Stoller et al. 2013). Additionally, the ejection of materials near the surface due to incident ions is important to sputtering and ion-beam analysis techniques, such as elastic recoil detection analysis (ERDA) and secondary ion mass spectrometry (SIMS) (Vickerman and Gilmore 2011). The interaction of ions within a material can be broken into two parts: electronic and nuclear stopping. Electronic stopping is the energy lost from the ion due to inelastic collisions with electrons along its path. Nuclear stopping is the energy lost due to elastic collisions between the ion and atomic nuclei within the material. The Stopping and Range of Ions in Matter (SRIM) code is a well known software in the radiation damage and ion-beam communities that allows the simulation, via Monte Carlo, of ions through a material by modeling the energy transfer through electronic and nuclear stopping (J. F. Ziegler, Ziegler, and Biersack 2010). SRIM was originally developed in 1985 and has had numerous updates on the electronic stopping powers since then, with the nuclear stopping well explained by the ZBL potential (J. F. Ziegler 1988). The executable SRIM is free to use for non-commercial use but the source code is not available to the community despite requests. While SRIM is a scientifically accurate code it does not get updated frequently and has many bugs from a usability standpoint.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Monte Carlo Simulation of Proton Upsets in Xilinx Virtex-II FPGA Using a Position Dependent Q(sub crit) with PROPSET

This paper describes new software simulation code for predicting single event upset data from measured heavy ion data, using methods, code, and algorithms already reported in the open literature. The measured data that is used to compare against the results of this new simulation code has also been reported in the open literature (R. Koga, et al). The new code is not provided as part of this paper, only the methodology used in generating the code. This paper presents results of basic research, not design-to information, and is representative of other papers reported in the open literature (see paper references). Therefore, the content of this paper is suitable for being made publicly available at the IEEE conference and the resulting IEEE journal.

O'Neill, Patrick M.↗
DOE OSTI2020

Status, Challenges, and Plans for Consistent Modeling and Evaluation of Fission Data: Nubar, PFNS, and FPY [Slides]

This presentation discusses the importance of consistent evaluations for fission observables. Currently, prompt fission quantities (e.g., neutron multiplicity, neutron energy spectrum, and fission product yields) are evaluated independently of one another, either with separate models or data-only/non-model evaluations (few – if any – shared model inputs) and inconsistencies can arise in evaluated data (e.g. NSE 190, 258 (2018)). They have found that consistent, model-based evaluations lead to more physical constraints on free parameters in the model, more robust predictions for other observables and other isotopes, that there are correlations between the uncertainties on different observables, and that uncertainties can be propagated to unmeasured quantities. They are working on developing models to the point where fission observables are calculated at the quality needed for an evaluation. They are striving to consistently calculate fission observables, such as $\bar{v}$, PFNS, and FPY, to a quality suitable for an evaluation. Current evaluations for fission observables use separate models for each observable (with minimal shared input) or are purely data driven. LANL models, such as the Monte Carlo CGMF and deterministic BeoH, have different strengths; the similar fission fragment initial conditions and decay models leads to consistency between the two codes (FPY can be connected to $\bar{v}$ and PFNS, even when calculated by different codes). Work is underway by Lovell to optimize the models and Neudecker is working to perform detailed uncertainty quantification. The PFNS, in particular, presents a significant challenge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET

The connection between plasma physics and neutronics is crucial for the understanding of the operation and performance of modern and future tokamak devices. Neutrons are one of the primary carriers of information on the plasma state and represent the basis for various plasma diagnostic systems as well as measurements of fusion power, tritium breeding studies, evaluations of tokamak structural embrittlement and the heating of water inside the fusion device's walls. It is therefore important that the birth of neutrons in a plasma and their transport from inside the tokamak vessel to the surrounding structures is well characterized. In this paper a methodology for the modelling of the neutron emission on the tokamak JET is presented. The TRANSP code is used to simulate the total neutron production as well as 2D neutron emission profiles for a JET plasma discharge. The spectra of the fusion neutrons are computed using the DRESS code. Finally, the computational results are analysed in an effort to create a plasma neutron source generator, which is to be used for Monte Carlo neutron transport computations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The Anatomy of an Unusual Edge-on Protoplanetary Disk. I. Dust Settling in a Cold Disk

As the earliest stage of planet formation, massive, optically thick, and gas-rich protoplanetary disks provide key insights into the physics of star and planet formation. When viewed edge-on, high-resolution images offer a unique opportunity to study both the radial and vertical structures of these disks and relate this to vertical settling, radial drift, grain growth, and changes in the midplane temperatures. In this work, we present multi-epoch Hubble Space Telescope and Keck scattered light images, and an Atacama Large Millimeter/submillimeter Array 1.3 mm continuum map for the remarkably flat edge-on protoplanetary disk SSTC2DJ163131.2–242627, a young solar-type star in ρ Ophiuchus. We model the 0.8 μm and 1.3 mm images in separate Markov Chain Monte Carlo (MCMC) runs to investigate the geometry and dust properties of the disk using the MCFOST radiative transfer code. In scattered light, we are sensitive to the smaller dust grains in the surface layers of the disk, while the submillimeter dust continuum observations probe larger grains closer to the disk midplane. An MCMC run combining both data sets using a covariance-based log-likelihood estimation was marginally successful, implying insufficient complexity in our disk model. The disk is well characterized by a flared disk model with an exponentially tapered outer edge viewed nearly edge-on, though some degree of dust settling is required to reproduce the vertically thin profile and lack of apparent flaring. A colder than expected disk midplane, evidence for dust settling, and residual radial substructures all point to a more complex radial density profile to be probed with future, higher-resolution observations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Self-learning kinetic Monte Carlo simulations of diffusion in ferromagnetic α -Fe–Si alloys

Diffusion in α-Fe-Si alloys is studied using AKSOME, an on-lattice self-learning KMC code, in the ferromagnetic state. Si diffusivity in the α-Fe matrix were obtained with and without the magnetic disorder in various temperature ranges. In addition we studied vacancy diffusivity in ferromagnetic α-Fe at various Si concentrations up to 12.5at.% in the temperature range of 350–550 K. The results were compared with available experimental and theoretical values in the literature. Local Si-atom dependent activation energies for vacancy hops were calculated using a broken-model and were stored in a database. The migration barrier and prefactors for Si-diffusivity were found to be in reasonable agreement with available modeling results in the literature. Magnetic disorder has a larger effect on the prefactor than on the migration barrier. Prefactor was approximately an order of magnitude and the migration barrier a tenth of an electron-volt higher with magnetic disorder when compared to a fully ferromagnetic ordered state. In addition, the correlation between various have a larger effect on the Si-diffusivity extracted in various temperature range than the magnetic disorder. In the case of vacancy diffusivity, the migration barrier more or less remained constant while the prefactor decreased with increasing Si concentration in the disordered or A2-phase of Fe-Si alloy. Important vacancy-Si/Fe atom exchange processes and their activation barriers were also identified and discuss the effect of energetics on the formation of ordered phases in Fe-Si alloys.

AKSOME↗
DOE OSTI2021

Rare Event Sampling Improves Mercury Instability Statistics

Due to the chaotic nature of planetary dynamics, there is a non-zero probability that Mercury's orbit will become unstable in the future. Previous efforts have estimated the probability of this happening between 3 and 5 billion years in the future using a large number of direct numerical simulations with an N-body code, but were not able to obtain accurate estimates before 3 billion years in the future because Mercury instability events are too rare. In this paper we use a new rare-event sampling technique, Quantile Diffusion Monte Carlo (QDMC), to estimate that the probability of a Mercury instability event in the next 2 billion years is approximately 10 –4 in the REBOUND N-body code. We show that QDMC provides unbiased probability estimates at a computational cost of up to 100 times less than direct numerical simulation. QDMC is easy to implement and could be applied to many problems in planetary dynamics in which it is necessary to estimate the probability of a rare event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Monte Carlo Second- and Third-Order Many-Body Green’s Function Methods with Frequency-Dependent, Nondiagonal Self-Energy

We fully develop the Monte Carlo many-body Green’s function (MC-GF) method with the following enhancements: (1) The truncation order of the perturbation expansion of the Dyson self-energy is raised from the second order (MC-GF2) to the third order (MC-GF3) with the aid of a computerized procedure to enumerate and transform all 84 third-order Goldstone diagrams into Monte Carlo integrable expressions and then into central processing unit (CPU)/graphical processing unit (GPU)-parallel computer codes. (2) An efficient algorithm is proposed that computes all off-diagonal and diagonal elements of the MC-GF2 and MC-GF3 self-energy matrices by common subexpression elimination. (3) The frequency-independent approximation is lifted by introducing a method that computes frequency derivatives of the MC-GF2 and MC-GF3 self-energies up to any arbitrarily high order at nearly no additional computational cost. (4) The imaginary-time integration in the Laplace-transformed expressions of the self-energy is carried out stochastically (instead of using a quadrature in the previous implementations), resulting in a 50- to 200-fold speedup. (5) The efficiency of the redundant-walker convergence acceleration scheme is analyzed numerically, and the guidelines are established to select an optimal number of walkers for maximal efficiency. When such an optimal number is used, the cost per sample is constant of molecular size on either many CPUs or many GPUs. (6) The computational cost to obtain a binding energy within a given statistical uncertainty is observed to increase as (tentatively) O(n 4 ) and O(n 5 ) of molecular size (n is the number of electrons) with and without the diagonal approximation, respectively, as opposed to O(n 5 ) and O(n 6 ) of the corresponding deterministic algorithms. With this method applied to the electron binding energies of C 60 , we show that the third-order corrections to the self-energies are much greater in electron binding energies than in ground-state energies. As a result, they display a sign of oscillatory convergence toward experimental results, not necessarily improving the agreement with increasing perturbation order, justifying MC-GF3 and motivating even higher-order methods.

Algorithms↗
DOE OSTI2021

Beam modulation and bump-on-tail effects on Alfvén eigenmode stability in DIII-D

Beam modulation effects on Alfvén eigenmode stability have been investigated in a recent DIII-D experiment and show that variations in neutral beam modulation period can have an impact on the beam driven Alfvén eigenmode spectrum and resultant fast ion transport despite similar time-averaged input power. The experiment was carried out during the current ramp phase of L-mode discharges heated with sub-Alfvénic 50–80 kV deuterium neutral beams that drive a variety of Alfvén eigenmodes unstable. The modulation period of two interleaved beams with different tangency radii was varied from shot to shot in order to modify the relative time dependent mix of the beam pitch angle distribution as well as the persistence of a bump-on-tail feature near the injection energy (a feature confirmed by imaging neutral particle analyzer measurements). As the beam modulation period is varied from 7 ms to 30 ms on/off (typical full energy slowing down time of τ slow ≈ 50 ms at mid-radius), toroidicity-induced Alfvén eigenmodes (TAEs) located in the outer periphery of the plasma become intermittent and coincident with the more tangential beam. Core mode activity changes from reversed shear Alfvén eigenmodes (RSAEs) to a mix of RSAE and beta-induced Alfvén eigenmodes. Discharges with 30 ms on/off period do not have a persistent bump-on-tail feature, have the lowest average mode amplitude and least fast ion transport. Furthermore, detailed analysis of an individual TAE using TRANSP kick modeling (Monte Carlo evolution of the distribution function with probabilistic 'kicks' by the AEs) and the resistive MHD code with kinetic fast ions, MEGA, find no strong role of energy gradient drive due to bump-on-tail features. Instead, the observed TAE modulation with interleaved beams is likely a pitch angle dependent result combined with slowing down of the tangential beam between pulses. For the conditions investigated, bump-on-tail contributions to TAE drive were found to be 5% or less of the total drive at any given time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Kernel Density Estimators for SAMPLER Analyses [Slides]

This presentation discusses Sampler, specifically in terms of uncertainty quantification and states that for many simulation tasks nominal input parameters have complicated influence on the uncertainty in the final result. Sampler provides a convenient means to perform stochastic uncertainty quantification, brute force sampling parameter space and tallying changes in outputs, and it can be coupled with any SCALE modules. Perturbed responses can be collected and analyzed with standard statistical measures; however, two problems have been identified. The first problem is that for Monte Carlo simulations the individual response uncertainties are ignored, and the second problem is that features of distributions are easily hidden in histograms. They found that the solution is to add Kernel Density Estimator (KDE) analysis to the Sampler output. In conclusion, Sampler is a unique tool for stochastic uncertainty propagation, and it can be coupled with any module in SCALE. Current functionality is limited to histograms, and it may not adequately account for sample uncertainties and/or not adequately display underlying distribution features. Work is in progress to implement KDE in the Sampler module and no additional flagging is needed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1989

Analytical optical scattering in clouds

An analytical optical model for scattering of light due to lightning by clouds of different geometry is being developed. The self-consistent approach and the equivalent medium concept of Twersky was used to treat the case corresponding to outside illumination. Thus, the resulting multiple scattering problem is transformed with the knowledge of the bulk parameters, into scattering by a single obstacle in isolation. Based on the size parameter of a typical water droplet as compared to the incident wave length, the problem for the single scatterer equivalent to the distribution of cloud particles can be solved either by Mie or Rayleigh scattering theory. The super computing code of Wiscombe can be used immediately to produce results that can be compared to the Monte Carlo computer simulation for outside incidence. A fairly reasonable inverse approach using the solution of the outside illumination case was proposed to model analytically the situation for point sources located inside the thick optical cloud. Its mathematical details are still being investigated. When finished, it will provide scientists an enhanced capability to study more realistic clouds. For testing purposes, the direct approach to the inside illumination of clouds by lightning is under consideration. Presently, an analytical solution for the cubic cloud will soon be obtained. For cylindrical or spherical clouds, preliminary results are needed for scattering by bounded obstacles above or below a penetrable surface interface.

Phanord, Dieudonne D.↗