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Variational Coupled Loads Analysis using the Hybrid Parametric Variation Method

Time-domain coupled loads analysis (CLA)is used to determine the response of a launch vehicle and payload system to transient forces, such as liftoff, engine ignitions and shutdowns, jettison events, and atmospheric flight loads, such as buffet. CLA, using Hurty/Craig-Bampton (HCB)component models, is the accepted method for the establishment of design-level loads for launch systems. However, uncertainty in the component models flows into uncertainty in predicted system results. Uncertainty in the structural responses during launch is a significant concern because small variations in launch vehicle and payload mode shapes and their interactions can result in significant variations in system loads. Uncertainty quantification (UQ)is used to determine statistical bounds on prediction accuracy based on model uncertainty. In this paper uncertainty is treated at the HCB component-model level. In an effort to account for model uncertainties and statistically bound their effect on CLA predictions, this work combines CLA with UQ in a process termed variational coupled loads analysis (VCLA). The modeling of uncertainty using a parametric approach, in which input parameters are represented by random variables, is common, but its major drawback is the resulting uncertainty is limited to the form of the nominal model. Uncertainty in model form is one of the biggest contributors to uncertainty in complex built-up structures. Model-form uncertainty can be represented using a nonparametric approach based on random matrix theory (RMT). In this work, UQ is performed using the hybrid parametric variation (HPV)method, which combines parametric with nonparametric uncertainty at the HCB component model level. The HPV method requires the selection of dispersion values for the HCB fixed-interface (FI)eigenvalues, and the HCB mass and stiffness matrices. The dispersions are based upon component test-analysis modal correlation results. During VCLA, random component models are assembled into an ensemble of random systems using a Monte Carlo (MC)approach. CLA is applied to each of the ensemble members to produce an ensemble of system-level responses for statistical analysis. The proposed methodology is demonstrated through its application to a buffet loads analysis of NASA’s Space Launch System (SLS)during the transonic regime fifty seconds after liftoff. Core stage (CS)section shears and moments are recovered, and statistics are computed.

Uncertainty Quantification↗
DOE OSTI2026

Machine Learning–Augmented Laser-Induced Breakdown Spectroscopy for Spectral Discrimination of Iron Oxalates

Enhanced characterization and phase identification of post-PUREX Pu Oxalates (PuOXA) are pivotal for nonproliferation and pre-detonation nuclear forensics. Despite significant advances in the characterization of PuO 2 samples, little is known about the impact of both the chemical structure and oxidation states of PuOXA (i.e., Pu(III) and Pu(IV)) have on optical emission signatures. Here, we demonstrate the analytical capabilities of laser-induced breakdown spectroscopy (LIBS) applied to Fe(II) and Fe(III) oxalate samples as surrogates for PuOXA, highlighting the discriminating features in the LIBS emission spectra arising from differences in the oxidation states within mixed FeOXA samples. We report the enhancement of spectral feature selection using Principal Component Analysis (PCA), which enables the analytical superiority of machine learning algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR) over conventional univariate techniques for phase discrimination and chemometric analysis. Cluster analysis revealed how both matrix effects and laser ablation influence cluster separability by introducing spectral artifacts that misdirect the maximization of variance. PCA-selected emission lines were used in the regression models, demonstrating that both univariate and multivariate linear regression models (i.e., PLSR and SVR) can achieve acceptable performance, with machine learning models outperforming conventional calibration regressions. Furthermore, the application of non-linearly activated PCA-selected emission lines illustrates how simplifying the data while retaining captured variance enables the use of less complex and more computationally efficient models. Furthermore, this is particularly evident in the underperformance of RFR, which suffers from increased computational costs and overfitting owing to its high complexity.

Oxalates↗
DOE OSTI2022

Ab initio studies of the double–Gamow-Teller transition and its correlation with neutrinoless double- β decay

Here, we use chiral interactions and several ab initio methods to compute the nuclear matrix elements (NMEs) for ground-state-to-ground-state double Gamow-Teller transitions in a range of isotopes and explore the correlation of these NMEs with those for neutrinoless double beta decay produced by the exchange of a light Majorana neutrino. When all the NMEs of both isospin-conserving and isospin-changing transitions from the ab initio calculations are considered, the correlation is strong. For the experimentally relevant isospin-changing transitions by themselves, however, the correlation is weaker and may not be helpful for reducing the uncertainty in the NMEs for neutrinoless double beta decay.

20 ≤ A ≤ 38↗
DOE OSTI2024

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Source apportionment of soot particles and aqueous-phase processing of black carbon coatings in an urban environment

Abstract. The impacts of soot particles on climate and human health depend on the concentration of black carbon (BC) as well as the thickness and composition of the coating material, i.e., organic and inorganic compounds internally mixed with BC. In this study, the size-resolved chemical composition of BC-containing aerosol was measured using a high-resolution soot particle aerosol mass spectrometer (SP-AMS) during wintertime in Fresno, California, a location influenced by abundant combustion emissions and frequent fog events. Concurrently, particle optical properties were measured to investigate the BC absorption enhancement. Positive matrix factorization (PMF) analysis was performed on the SP-AMS mass spectral measurements to explore the sources of soot particles and the atmospheric processes affecting the properties of BC coatings. The analysis revealed that residential woodburning and traffic are the dominant sources of soot particles. Alongside primary soot particles originating from biomass burning (BBOABC) and vehicles (HOABC) two distinct types of processed BC-containing aerosol were identified: fog-related oxidized organic aerosol (FOOABC) and winter-background OOABC (WOOABC). Both types of OOABC showed evidence of having undergone aqueous processing, albeit with differences. The concentration of FOOABC was substantially elevated during fog events, indicating the formation of aqueous secondary organic aerosol (aqSOA) within fog droplets. On the other hand, WOOABC was present at a relatively consistent concentration throughout the winter and was likely related to the formation of secondary organic aerosol (SOA) in both the gas phase and aerosol liquid water. By comparing the chemical properties and temporal variations in FOOABC and WOOABC, we gain insights into the key aging processes of BC aerosol. It was found that aqueous-phase reactions facilitated by fog droplets had a significant impact on the thickness and chemical composition of BC coatings, thereby affecting the light absorption and hygroscopic properties of soot particles. These findings underscore the important role of chemical reactions occurring within clouds and fogs and influencing the climate forcing of BC aerosol in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Covalent Crosslinking of Carbon Nanotube Materials for Improved Tensile Strength

Carbon nanotubes have attracted much interest in recent years due to their exceptional mechanical properties. Currently, the tensile properties of bulk carbon nanotube-based materials (yarns, sheets, etc.) fall far short of those of the individual nanotube elements. The premature failure in these materials under tensile load has been attributed to inter-tube sliding, which requires far less force than that needed to fracture individual nanotubes.1,2 In order for nanotube materials to achieve their full potential, methods are needed to restrict this tube-tube shear and increase inter-tube forces.Our group is examining covalent crosslinking between the nanotubes as a means to increase the tensile properties of carbon nanotube materials. We are working with multi-walled carbon nanotube (MWCNT) sheet and yarn materials obtained from commercial sources. Several routes to functionalize the nanotubes have been examined including nitrene, aryl diazonium, and epoxide chemistries. The functional nanotubes were crosslinked through small molecule or polymeric bridges. Additionally, electron beam irradiation induced crosslinking of the non-functional and functional nanotube materials was conducted. For example, a nanotube sheet material containing approximately 3.5 mol amine functional groups exhibited a tensile strength of 75 MPa and a tensile modulus of 1.16 GPa, compared to 49 MPa and 0.57 GPa, respectively, for the as-received material. Electron beam irradiation (2.2x 1017 ecm2) of the same amine-functional sheet material further increased the tensile strength to 120 MPa and the modulus to 2.61 GPa. This represents approximately a 150 increase in tensile strength and a 360 increase in tensile modulus over the as-received material with only a 25 increase in material mass. Once we have optimized the nanotube crosslinking methods, the performance of these materials in polymer matrix composites will be evaluated.

polymer matrix composites↗
DOE OSTI2023

SAS4A/SASSYS-1 Commercial Grade Dedication Example Report for a Generic Sodium Pool-Type Fast Reactor Application

In the U.S., a key component of the commercialization of advanced reactors is completion of a license application, which must ultimately be approved by the Nuclear Regulatory Commission (NRC). The approval of the license application by the NRC is contingent on satisfactory demonstration of the design basis and the response of the advanced reactor design to transient and accident scenarios using accepted codes and methods. This report describes the qualification and dedication requirements that the advanced reactor safety analysis system software SAS4A/SASSYS-1 are expected to need to fulfill to be used for sodium-cooled pool-type fast reactor licensing. The qualification and dedication requirements are identified through performance critical characteristics and evaluation model acceptance criteria representative of the advanced reactor design considered for licensing. This document captures, additionally, the verification process developed to demonstrate that the software fulfills the qualification and dedication requirements for a generic sodium-cooled pool-type fast reactor as part of the commercial grade dedication process. Like most software that has primarily existed in the research and development space, the most significant challenge facing SAS4A/SASSYS-1 for use in a licensing framework is the availability of a documentation basis describing the code pedigree. SAS4A/SASSYS-1 has been used for licensing of the fast flux test facility (FFTF) and the JOYO sodium-cooled fast reactor in Japan, as well as the design of the CRBR Plant. However, the historical verification and validation (V&V) activities supporting SAS4A/SASSYS-1 development do not align with modern software quality assurance (SQA) and V&V requirements. Two approaches to use of SAS4A/SASSYS-1 in a commercial licensing framework have been identified: commercial-grade dedication (CGD) and software qualification. The methods and requirements prescribed in the ASME NQA-1-2008/2009 Standard and Regulatory Guide 1.203 on the evaluation model development and assessment process (EMDAP) have been used as guidance to define the CGD and qualification processes, respectively. A qualification and dedication requirements matrix has been developed which utilizes fundamental software verification. In this process, software verification is defined as a software quality process aimed at defining software requirement specifications, developing software design documentation, and performing and documenting acceptance testing of the code against requirements. A key element of software qualification and dedication includes determination of software acceptance with respect to critical characteristics relevant to the functional requirements of the software. To assist with identification of cross-cutting transient phenomena and functional requirements, domestic SFR vendor designs have been reviewed to identify a reference SFR design. For this report, the reference design is defined as a pool-type reactor with metal alloy fuel, a liquid-metal intermediate heat transport system, and passive decay heat rejection systems. Given this reference, a series of high-level cross-cutting phenomena was identified for a general class of single-fault undercooling or reactivity insertion transients that scopes the design basis space, with the goal of assisting with prioritization of documentation development efforts for key transient models in SAS: 1) Reactivity feedback response prior to scram; 2) System-wide thermal inertia; 3) Transition in natural circulation flow regime in heat removal systems; 4) Decay heat generation; 5) Steady-state fuel characterization; 5) Clad/fuel behavior at elevated temperatures; 6) Point kinetics and decay heat; 7) Pump coastdown behavior; 8) Core flow redistribution in loss of forced convection; 9) Pool stratification. As a demonstration of CGD of SAS4A/SASSYS-1 for a sodium pool reactor, a software qualification and dedication gap analysis as it relates to code documentation has been performed. This effort leverages the framework established as part of the SAS4A/SASSYS-1 SQA Program. This CGD demonstration provides a framework that vendors can build upon to demonstrate the applicability of the SAS4A/SASSYS-1 software for licensing a sodium-cooled pool-type fast reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Mapping Thermal Conductivity at the Atomic Scale: A Step toward the Thermal Design of Materials

We describe a spatial decomposition of the thermal conductivity, termed site-projected thermal conductivity, which quantifies the thermal conduction activity at each atomic site—a critical parameter for the thermal design of materials. The method is based on the Green–Kubo formula and the harmonic approximation and requires the force-constant and dynamical matrices, as well as a relaxed structural model. Throughout the study, it uses high quality models previously tested and compared to many experiments. It discusses the method and underlying approximations for amorphous silicon, carries the detailed analysis for amorphous silicon, and then examines an amorphous-crystal silicon interface and representative carbon materials. This study identifies the sites and local structures that reduce heat transport, and quantify these (estimate the spatial range) over which these “thermal defects” are effective. It identifies filamentary structures in the amorphous silicon network which impact heat transport and electronic structure (the Urbach edge) and electronic transport.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Precipitation strengthened high strength, high conductivity Cu-Cr-Nb alloys produced by chill block melt spinning

A series of Cu-based alloys containing 2 to 10 a/o Cr and 1 to 5 a/o Nb were produced by chill block melt spinning (CBMS). The melt spun ribbons were consolidated and hot rolled to sheet to produce a supersaturated Cu-Cr-Nb solid solution from which the high melting point intermetallic compound Cr2Nb could be precipitated to strengthen the Cu matrix. The results show that the materials possess electrical conductivities in excess of 90 percent that of pure Cu at 200 C and above. The strengths of the Cu-Cr-Nb alloys were much greater than Cu, Cu-0.6 Cr, NARloy-A, and NARloy-Z in the as-melt spun condition. The strengths of the consolidated materials were less than Cu-Cr and Cu-Cr-Zr below 500 C and 600 C respectively, but were significantly better above these temperatures. The strengths of the consolidated materials were greater than NARloy-Z, at all temperatures. The GLIDCOP possessed similar strength levels up to 750 C when the strength of the Cu-Cr-Nb alloys begins to degrade. The long term stability of the Cu-Cr-Nb alloys was measured by the microhardness of aged samples and the growth of precipitates. The microhardness measurements indicate that the alloys overage rapidly, but do not suffer much loss in strength between 10 and 100 hours which confirms the results of the electrical resistivity measurements taken during the aging of the alloys at 500 C. The loss in strength from peak strength levels is significant, but the strength remains exceptionally good. Transmission electron microscopy (TEM) of the as-melt spun samples revealed that Cr2Nb precipitates formed in the liquid Cu during the chill block melt spinning, indicating a very strong driving force for the formation of the precipitates. The TEM of the aged and consolidated materials indicates that the precipitates coarsen considerably, but remain in the submicron range.

Ellis, David L.↗
DOE OSTI2022

7.2 kV Three-Port SiC Single-Stage Current-Source Solid-State Transformer With 90 kV Lightning Protection

This article proposes a multiport modular single-stage current-source solid-state transformer (SST) for applications like photovoltaic, energy storage integration, electric vehicle fast charging, data center, etc. The 7.2 kV 50 kVA current-source SST consists of five input-series output-parallel modules, each based on 3.3 kV SiC reverse-blocking MOSFET-plus-diode modules. The proposed SST has some unique features. First, compared to the voltage-source or matrix converter-based SSTs, the current-source SST has a unique advantage of single-stage isolated AC/DC or AC/AC conversion with an inductive DC link, but no medium-voltage (MV) AC experiments have been reported. This article for the first time demonstrates MV AC current-source SST up to 7.5 kV peak. Second, the multiport SST has a buffer port for active power decoupling (APD) or energy storage integration. The double-line-frequency power ripple from single-phase AC grid normally results in a large capacitor size in MV SSTs. The APD scheme is proposed in MV applications for the first time to enable a reduced DC link and the electrolytic capacitor-less SST with high reliability. Third, as a direct grid-connected converter without line-frequency transformer, insulation and protection are critical. A medium-frequency transformer design passes 55 kV basic-insulation level (BIL) and 60 kV high potential dielectrics withstand test with only 0.09% leakage inductance. Importantly, a lightning protection scheme is presented to protect the SST itself from 90 kV BIL impulse. Fourth, the proposed current-source SST topology is a modular soft-switching solid-state transformer (M-S4T) with full-range zero-voltage switching and controlled dv/dt for low electromagnetic interference. Furthermore, these concepts are verified in a three-port M-S4T prototype with forced oil cooling under single-module, stacked-module, steady-state, and dynamic operations.

14 SOLAR ENERGY↗
DOE OSTI2021

Comparing different density-matrix expansions for long-range pion exchange

Empirical energy density functionals (EDFs) are generally successful in describing nuclear properties across the table of nuclides. But their limitations motivate using the density-matrix expansion (DME) to embed long-range pion interactions into a Skyrme functional. Recent results on the impact of the pion were both encouraging and puzzling, necessitating a careful re-examination of the DME implementation. In this study, we take the first steps, focusing on two-body scalar terms in the DME. Exchange energies with long-range one-pion contributions are well approximated by all DME implementations considered, with preference for variants that do not truncate at two derivatives in every EDF term. The use of the DME for chiral pion contributions is therefore supported by this investigation. For scalar-isovector energies it is important to treat neutrons and protons separately. The results are found to apply under broad conditions, although self-consistency is not yet tested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Present Status of Nuclear Shell-Model Calculations of 0 νββ Decay Matrix Elements

Neutrinoless double beta (0νββ) decay searches are currently among the major foci of experimental physics. The observation of such a decay will have important implications in our understanding of the intrinsic nature of neutrinos and shed light on the limitations of the Standard Model. The rate of this process depends on both the unknown neutrino effective mass and the nuclear matrix element (M 0ν ) associated with the given 0νββ transition. The latter can only be provided by theoretical calculations, hence the need of accurate theoretical predictions of M 0ν for the success of the experimental programs. This need drives the theoretical nuclear physics community to provide the most reliable calculations of M 0ν . Among the various computational models adopted to solve the many-body nuclear problem, the shell model is widely considered as the basic framework of the microscopic description of the nucleus. Here, we review the most recent and advanced shell-model calculations of M 0ν considering the light-neutrino-exchange channel for nuclei of experimental interest. We report the sensitivity of the theoretical calculations with respect to variations in the model spaces and the shell-model nuclear Hamiltonians.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Local conformations and heterogeneities in structures and dynamics of isotactic polypropylene adsorbed onto carbon fiber

Carbon fiber (CF) reinforced polymers (CFRPs) have experienced widespread use in various industries. One of the most important parameters that controls the macroscopic property of CFRPs is the interface between a polymer matrix and CF. There is growing evidence to suggest the formation of a bound polymer layer (BPL), i.e., polymer chains that physically adsorb on a filler surface. However, this interface is always in contact with the thicker part of a polymer matrix, rendering its understanding a difficult task. Therein, we use CF-reinforced isotactic polypropylene (iPP) as a rational CFRP. To characterize the BPL on the CF surface, we extracted it from the CFRP using solvent-rinsing with p-xylene. The physical and thermal properties of the BPL were characterized by differential scanning calorimetry and thermogravimetric analysis, while its microscopic structures and dynamics were probed by small-angle neutron scattering and quasi-elastic neutron scattering (QENS) techniques. Subsequently, we employed atomistic molecular dynamics (MD) simulations to complement the QENS results above the bulk melting temperature and reveal details that were experimentally inaccessible. In this work, we observed that the degree of crystallinity of the BPL was quite lower than the bulk, while the melting temperature of the BPL remained the same as the bulks. Within the given length and time scales probed by QENS and MD, we also observed that most of the bound chains were mobile, with the formation of a high-density region (less than 1 nm in thickness) near the CF surface. The segmental dynamics of the bound chains probed by both QENS and MD were also much faster than those of the free chains, possibly due to the presence of a free surface region at the topmost surface of the BPL. Furthermore, the MD results demonstrated that the backbone chains and side groups lie nearly flat on the CF surface, which is the driving force for the flattening process of the iPP BPL to overcome the conformational entropy loss in the total free energy.

36 MATERIALS SCIENCE↗
NASA NTRS2001

A Structural and Molecular Approach for the Study Biomarkers

Investigation of the nucleation and growth of crystals in both abiotic and biotic systems is critical to seemingly diverse disciplines of geology, biology, environmental science, and astrobiology. While there are abundant studies devoted to the determination of the structure and composition of inorganic crystals, as well as to the development of thermodynamic and kinetic models, it is only recently that research efforts have been directed towards understanding mineralization in biological systems (i.e., biomineralization). Biomineralization refers to the processes by which living organisms form inorganic solids. Studies of the processes of biomineralization under low temperature aqueous conditions have focused primarily on magnetite forming bacteria and shell forming marine organisms. Many of the biological building materials consist of inorganic minerals (calcium carbonate, calcium phosphate, silica or iron oxide) intricately combined with organic polymers (like proteins). More recently, efforts have been undertaken to explore the nature of biological activities in ancient rocks. In the absence of well-preserved microorganisms or genetic material required for the polmerase chain reaction (PCR) method in molecular phylogenetic studies, using biominerals as biomarkers offers an alternative approach for the recognition of biogenic activity in both terrestrial and extraterrestrial environments. The primary driving force in biomineralization is the interaction between organic and inorganic phases. Thus, the investigation of the ultrastructure and the nature of reactions at the molecular level occurring at the interface between inorganic and organic phases is essential to understanding the processes leading to the nucleation and growth of crystals. It is recognized that crystal surfaces can serve as the substrate for the organization of organic molecules that lead to the formation of polymers and other complex organic molecules, and in discussions of the origins of life, is referred to as organic synthesis on mineral surfaces. Furthermore, it is suggested that the interaction between mineral surfaces and simple organic molecules resulted in the formation of amino acids, RNA, and perhaps other more complex molecules such as proteins. On the other hand, in natural systems, it is recognized that functional groups on cell walls or membranes of microorganisms serve as sites of nucleation and crystallization. The precise replication of biominerals with controlled structure, morphology, size and texture is not confined to higher organisms as it also occurs in primitive prokaryotic cells such as magnetotactic bacteria and cyanobacteria. This suggests that the principal strategies of biomineralization were established early on in the evolutionary history of organisms. It is critical, therefore, to search for common mechanisms within diverse biological systems. One such common factor is the capability for organization and self-assembly. Organic macromolecules such as proteins and lipids can aggregate and polymerize forming membranes or extracellular matrix. At the organic-inorganic interface, several factors such as lattice geometry, polarity, stereochemistry and topography may act in concert to control nucleation and growth of crystals. Although several models have been proposed that discuss the significance of these factors for biomineralization, no comprehensive experimental data are available. In contrast to crystallization in exclusively inorganic systems, the kinetics of reaction and structural relationships between organic and inorganic phases in biominerals or biomimetic material is poorly understood. For example, it is not clear if the concept of epitactic growth (geometrical matching of unit cells at the interface of a secondary crystal growing on a primary crystal) applies to organic-inorganic systems. In contrast to inorganic templates that often have a smooth and rigid surface that promotes epitactic growth, biological substrates are usually rough and result in a large degree of mismatch. It is apparent that factors controlling the reaction at the crystal-matrix interface are strongly dependent upon the nature of the substrate. Therefore, characterization of the assembled organic surface and surface structure of the inorganic phase is crucial to understanding the processes of biomineralization. The focus of our research is the investigation of the processes leading to the nucleation and growth of crystals on both natural and synthetic systems through an interdisciplinary approach that integrates molecular biology, morphology and mineralogy using advanced preparation and analytical techniques. We have studied run-products, particularly magnetite, siderite and other carbonates, that resulted from extracellular biomineralization by extremophiles isolated from a variety of extreme environments ranging from permafrost to hydrothermal vent systems. The results of this study are critical to recognizing biomarkers in terrestrial and extraterrestrial environments.

Thomas-Keprta, Kathie↗
DOE OSTI2024

Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracy

We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel method and Bayesian linear regression to compute the free energy, atomic forces, and pressure, in conjunction with a linear regression model between the internal and free energies to compute the internal energy, with all training data generated from Kohn–Sham density functional theory (DFT). We verify the accuracy of the formalism by comparing the Hugoniot for carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that Kohn–Sham calculations for the Hugoniot can be accelerated by up to two orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the Hugoniots of 14 materials in the FPEOS database, comprising 9 single elements and 5 compounds, between temperatures of 10 kK and 2 MK. We find good agreement with first principles results in the literature while providing tighter error bars. In addition, we confirm that the inter-element interaction in compounds decreases with temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2009

Integrated High Payoff Rocket Propulsion Technology (IHPRPT) SiC Recession Model

SiC stability and recession rates were modeled in hydrogen/oxygen combustion environments for the Integrated High Payoff Rocket Propulsion Technology (IHPRPT) program. The IHPRPT program is a government and industry program to improve U.S. rocket propulsion systems. Within this program SiC-based ceramic matrix composites are being considered for transpiration cooled injector faceplates or rocket engine thrust chamber liners. Material testing under conditions representative of these environments was conducted at the NASA Glenn Research Center, Cell 22. For the study described herein, SiC degradation was modeled under these Cell 22 test conditions for comparison to actual test results: molar mixture ratio, MR (O2:H2) = 6, material temperatures to 1700 C, combustion gas pressures between 0.34 and 2.10 atm, and gas velocities between 8,000 and 12,000 fps. Recession was calculated assuming rates were controlled by volatility of thermally grown silica limited by gas boundary layer transport. Assumptions for use of this model were explored, including the presence of silica on the SiC surface, laminar gas boundary layer limited volatility, and accuracy of thermochemical data for volatile Si-O-H species. Recession rates were calculated as a function of temperature. It was found that at 1700 C, the highest temperature considered, the calculated recession rates were negligible, about 200 m/h, relative to the expected lifetime of the material. Results compared favorably to testing observations. Other mechanisms contributing to SiC recession are briefly described including consumption of underlying carbon and pitting. A simple expression for liquid flow on the material surface was developed from a one-dimensional treatment of the Navier-Stokes Equation. This relationship is useful to determine under which conditions glassy coatings or thermally grown silica would flow on the material surface, removing protective layers by shear forces. The velocity of liquid flow was found to depend on the gas velocity, the viscosity of gas and liquid, as well as the thickness of the gas boundary layer and the liquid layer. Calculated flow rates of a borosilicate glass coating compared well to flow rates observed for this coating tested on a SiC panel in Cell 22.

Opila, E. J.↗
NASA NTRS2013

The Digital Astronaut Project Computational Bone Remodeling Model (Beta Version) Bone Summit Summary Report

Under the conditions of microgravity, astronauts lose bone mass at a rate of 1% to 2% a month, particularly in the lower extremities such as the proximal femur [1-3]. The most commonly used countermeasure against bone loss in microgravity has been prescribed exercise [4]. However, data has shown that existing exercise countermeasures are not as effective as desired for preventing bone loss in long duration, 4 to 6 months, spaceflight [1,3,5,6]. This spaceflight related bone loss may cause early onset of osteoporosis to place the astronauts at greater risk of fracture later in their lives. Consequently, NASA seeks to have improved understanding of the mechanisms of bone demineralization in microgravity in order to appropriately quantify this risk, and to establish appropriate countermeasures [7]. In this light, NASA's Digital Astronaut Project (DAP) is working with the NASA Bone Discipline Lead to implement well-validated computational models to help predict and assess bone loss during spaceflight, and enhance exercise countermeasure development. More specifically, computational modeling is proposed as a way to augment bone research and exercise countermeasure development to target weight-bearing skeletal sites that are most susceptible to bone loss in microgravity, and thus at higher risk for fracture. Given that hip fractures can be debilitating, the initial model development focused on the femoral neck. Future efforts will focus on including other key load bearing bone sites such as the greater trochanter, lower lumbar, proximal femur and calcaneus. The DAP has currently established an initial model (Beta Version) of bone loss due to skeletal unloading in femoral neck region. The model calculates changes in mineralized volume fraction of bone in this segment and relates it to changes in bone mineral density (vBMD) measured by Quantitative Computed Tomography (QCT). The model is governed by equations describing changes in bone volume fraction (BVF), and rates of changes in bone cell populations that remove and replace bone in packets within the bone region. The DAP bone model is unique in several respects. In particular in takes former models of volume fraction changes one step higher in fidelity and separates BVF into separate equations for mineralized and osteoid volume fractions governed by a mineralization rate. This more closely follows the physiology of the remodeling unit cycles where bone is first resorbed and then followed by the action of osteoblasts to lay down collagen matrix which eventually becomes mineralized. In another respect, the modules allow the functional description of the time rate of change of other parameters and variables in the model during a computational simulation. More detailed description of the model, preliminary validation results, current limitation and caveats, and planned advancements are provided in sections 2 through 5. The DAP bone model is being developed primarily as a research tool, and not as a clinical tool like QCT. Even if it transitions to a clinical tool, it is not intended to replace QCT or any other clinical tool. Moreover, the DAP bone model does not predict bone fracture. Its purpose is to provide valuable additional data via "forward prediction" simulations for during and after spaceflight missions to gain insight on, (1) mechanisms of bone demineralization in microgravity, and (2) the volumetric changes at the various bone sites in response to in-flight and post-flight exercise countermeasures. This data can then be used as input to the Keyak [8] (or equivalent) FE analysis method to gain insight on how bone strength may change during and after flight. This information can also be useful to help optimize exercise countermeasure protocols to minimize changes in bone strength during flight, and improve regain of bone strength post-flight. To achieve this goal, the bone model will be integrated with DAP's exercise countermeasure models to simulate the effect of exercise prescriptions on preserving bone. More specifically, the model will accept loading history due to muscle and joint force on bone and produce quantified remodeling within the bone region under influence of the applied stress. Furthermore, because they tend to respond differently, the bone remodeling model includes both trabecular bone and cortical bone.

Pennline, James↗
NASA NTRS2014

Assessment of the Accuracy of the Conventional Ray-Tracing Technique: Implications in Remote Sensing and Radiative Transfer Involving Ice Clouds.

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).

remote sensing↗