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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-instanton calculus in $c$ = 1 string theory

We formulate a strategy for computing the complete set of non-perturbative corrections to closed string scattering in c = 1 string theory from the worldsheet per spective. This requires taking into account the effect of multiple ZZ-instantons, including higher instantons constructed from ZZ boundary conditions of type (m, 1), with a careful treatment of the measure and contour in the integration over the instanton moduli space. The only a priori ambiguity in our prescription is a normalization constant $\mathcal{N}_m$ that ap pears in the integration measure for the (m, 1)-type ZZ instanton, at each positive integer m. We investigate leading corrections to the closed string reflection amplitude at the n instanton level, i.e. of order e -n/g s , and find striking agreement with our recent proposal on the non-perturbative completion of the dual matrix quantum mechanics, which in turn fixes $\mathcal{N}_m$ for all m.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

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

Thermal Stability Testing of LANA.75

Savannah River Site has used the metal hydride LaNi 4.25 Al 0.75 (LANA.75) in the Tritium Facilities for over two decades. LANA.75 beds store significant quantities of tritium but have a limited service life due to the radiolytic decay of tritium to 3He within the metal matrix. It has been shown that the isotherm performance of a tritium-aged LANA.75 sample can be restored by heating under vacuum. Additional investigation is needed to ensure there are no unexpected changes to the hydride before this technique is employed in full-scale beds in the Tritium Facilities. In addition, it is necessary to verify the regenerable behavior and thermal stability of LANA.75 on a small scale prior to it being implemented on a large scale. In this work, a non-tritiated bench-scale LANA.75 sample was held at 750°C under vacuum for 200 h to simulate exposure to multiple restoration evolutions. Hydride isotherm performance, chemical composition, crystallinity, and morphology are compared between the pre-restorative and post-restorative testing samples. No significant changes were observed in composition or crystallinity. Comparison of pre-anneal and post-anneal isotherms showed that performance improved rather than deteriorated during the evolution. Scanning electron microscopy analysis showed small growths on the particle surface after exposure to regeneration conditions. Additional testing will be required to determine the cause of these growths.

08 HYDROGEN↗
DOE OSTI2026

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗
NASA NTRSDate not supplied

Multiscale and Multifidelity Modeling of a 3D Woven Composite Thermal Protection System

Complex three-dimensional (3D) woven composites have been considered by multiple NASA projects in recent years as a means of offering improved mechanical and thermal performance over traditional laminated composite systems. Parallel efforts have focused on developing simulation capabilities for these systems, which have traditionally and heavily relied on experimental testing to evaluate composite performance. One system is the Heatshield for Extreme Entry Environment Technology (HEEET), which is being considered for the thermal protection system on reentry spacecraft. Optical microscopy was used to characterize the blended carbon and phenolic fiber tows. A section of HEEET insulation layer was imaged with high-resolution micro-computed tomography (microCT) and segmented to separate individual tows, porous matrix, and voids. These data were used to develop multiscale thermomechanical computational models within the NASA Multiscale Analysis Tool (NASMAT). Two NASMAT modeling approaches were considered to capture the details of the 3D woven architecture: a coarse model appropriate for inclusion in multiscale structural analyses and a high-fidelity model created by downsampling the microCT data. Both elastic and thermal properties were computed and compared. The feasibility and challenges associated with modeling complex, hybrid 3D woven composites were also addressed.

NASMAT↗
DOE OSTI2023

A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data

The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs

Decomposing a matrix $\mathbf {A}$ into a lower matrix $\mathbf {L}$ and an upper matrix $\mathbf {U}$, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matrix, LU decomposition often introduces more nonzero entries in the $\mathbf {L}$ and $\mathbf {U}$ factors than in the original matrix. A symbolic factorization step is needed to identify the nonzero structures of $\mathbf {L}$ and $\mathbf {U}$ matrices. Attracted by the enormous potentials of the Graphics Processing Units (GPUs), an array of efforts have surged to deploy various LU factorization steps except for the symbolic factorization, to the best of our knowledge, on GPUs. This article introduces gSoFa, the first GPU-based symbolic factorization design with the following three optimizations to enable scalable LU symbolic factorization for nonsymmetric pattern sparse matrices on GPUs. First, here we introduce a novel fine-grained parallel symbolic factorization algorithm that is well suited for the Single Instruction Multiple Thread (SIMT) architecture of GPUs. Second, we tailor supernode detection into a SIMT friendly process and strive to balance the workload, minimize the communication and saturate the GPU computing resources during supernode detection. Third, we introduce a three-pronged optimization to reduce the excessive space consumption problem faced by multi-source concurrent symbolic factorization. Taken together, gSoFa achieves up to 31× speedup from 1 to 44 Summit nodes (6 to 264 GPUs) and outperforms the state-of-the-art CPU project, on average, by 5×. Notably, gSoFa also achieves up to 47 percent of the peak memory throughput of a V100 GPU in the Summit Supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

User Role Identification in Software Vulnerability Discussions over Social Networks

Understanding and early awareness of software vulnerabilities is vital for preventing and mitigating potential impacts from cybersecurity events. One step toward early characterization of software vulnerabilities may involve analyzing discussion and spread of information in online social networks. Prior work has used information from such discussions over multiple online forums to develop dynamic networks among users followed by analysis of structure, spread, and information evolution. In this work, we advance the state-of-the-art by focusing on data-driven learning of types, roles, and transition of roles exhibited by users over time. In social networks, users take on particular roles based on their actions and structure of the network. Identifying “meaningful” roles can help separate potential users of interest from the larger community, and identify patterns in a network. We will identify and compare roles found in online forums (e.g., Twitter) using techniques such as feature-based Non-negative Matrix Factorization coupled with topological and influence-based measures of centrality. Since users’ activities change over time, we also analyze role evolution in dynamic networks.

Jones, Rebecca D.↗
NASA NTRS2000

Optical Control of Intersubband Absorption in a Multiple Quantum Well-Embedded Semiconductor Microcravity

Optical intersubband response of a multiple quantum well (MQW)-embedded microcavity driven by a coherent pump field is studied theoretically. The n-type doped MQW structure with three subbands in the conduction band is sandwiched between a semi-infinite medium and a distributed Bragg reflector (DBR). A strong pump field couples the two upper subbands and a weak field probes the two lower subbands. To describe the optical response of the MQW-embedded microcavity, we adopt a semi-classical nonlocal response theory. Taking into account the pump-probe interaction, we derive the probe-induced current density associated with intersubband transitions from the single-particle density-matrix formalism. By incorporating the current density into the Maxwell equation, we solve the probe local field exactly by means of Green's function technique and the transfer-matrix method. We obtain an exact expression for the probe absorption coefficient of the microcavity. For a GaAs/Al(sub x)Ga(sub 1-x)As MQW structure sandwiched between a GaAs/AlAs DBR and vacuum, we performed numerical calculations of the probe absorption spectra for different parameters such as pump intensity, pump detuning, and cavity length. We find that the probe spectrum is strongly dependent on these parameters. In particular, we find that the combination of the cavity effect and the Autler-Townes effect results in a triplet in the optical spectrum of the MQW system. The optical absorption peak value and its location can be feasibly controlled by varying the pump intensity and detuning.

Liu, Ansheng↗
DOE OSTI2021

TUMME: Tsinghua University Minnesota Master Equation program

We report that TUMME is a program for assembling and solving master equations for gas-phase chemical kinetics based on chemically significant eigenmodes. TUMME has interfaces to the Gaussian, Polyrate, and/or MSTor output files that allow the master equation code to obtain the microcanonical flux coefficients needed for the coefficient matrix of the master equation. The flux coefficients for reactions with barriers can be calculated by multi-structural variational transition state theory with small-curvature tunneling (MS-VTST/SCT) or by simpler approximations to this such as conventional transition state theory without tunneling (also called RRKM theory). The flux coefficients for barrierless reactions are provided by a hard-sphere model. TUMME is written in double precision with Python 3; quadruple and octuple precision are also available for some subtasks in C++. The Python code can run in serial or parallel (MP or MPI), and the C++ code can run on a single processor or on multiple processors with OpenMP.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2007

Comparison of Fluka-2006 Monte Carlo Simulation and Flight Data for the ATIC Detector

We have performed a detailed Monte Carlo (MC) simulation for the Advanced Thin Ionization Calorimeter (ATIC) detector using the MC code FLUKA-2006 which is capable of simulating particles up to 10 PeV. The ATIC detector has completed two successful balloon flights from McMurdo, Antarctica lasting a total of more than 35 days. ATIC is designed as a multiple, long duration balloon flight, investigation of the cosmic ray spectra from below 50 GeV to near 100 TeV total energy; using a fully active Bismuth Germanate(BGO) calorimeter. It is equipped with a large mosaic of.silicon detector pixels capable of charge identification, and, for particle tracking, three projective layers of x-y scintillator hodoscopes, located above, in the middle and below a 0.75 nuclear interaction length graphite target. Our simulations are part of an analysis package of both nuclear (A) and energy dependences for different nuclei interacting in the ATIC detector. The MC simulates the response of different components of the detector such as the Si-matrix, the scintillator hodoscopes and the BGO calorimeter to various nuclei. We present comparisons of the FLUKA-2006 MC calculations with GEANT calculations and with the ATIC CERN data and ATIC flight data.

Gunasingha, R.M.↗
NASA NTRS2020

Evidence for Multiple Diagenetic Episodes in Ancient Fluvial‐Lacustrine Sedimentary Rocks in Gale Crater, Mars

The Curiosity rover's exploration of rocks and soils in Gale crater has provided diverse geochemical and mineralogical data sets, underscoring the complex geological history of the region. We report the crystalline, clay mineral, and amorphous phase distributions of four Gale crater rocks from an 80‐m stratigraphic interval. The mineralogy of the four samples is strongly influenced by aqueous alteration processes, including variations in water chemistries, redox, pH, and temperature. Localized hydrothermal events are evidenced by gray hematite and maturation of amorphous SiO 2 to opal‐CT. Low‐temperature diagenetic events are associated with fluctuating lake levels, evaporative events, and ground water infiltration. Among all mudstones analyzed in Gale crater, the diversity in diagenetic processes is primarily captured by the mineralogy and X‐ray amorphous chemistry of the drilled rocks. Variations indicate a transition from magnetite to hematite and an increase in matrix‐associated sulfates suggesting intensifying influence from oxic, diagenetic fluids up section. Furthermore, diagenetic fluid pathways are shown to be strongly affected by unconformities and sedimentary transitions, as evidenced by the intensity of alteration inferred from the mineralogy of sediments sampled adjacent to stratigraphic contacts.

C N Achilles↗
DOE OSTI2022

Mineral Protection and Resource Limitations Combine to Explain Profile-Scale Soil Carbon Persistence

The fate of soil carbon (C) is largely controlled by microbial oxidation of organic matter (OM), which is constrained by a variety of mechanisms. OM association with soil minerals provides pronounced protection against microbial decomposition. However, factors such as climate, occlusion, and resource limitations also contribute to OM preservation. Here, we explore the factors explaining C distribution and age within an upland rainforest soil in Hawai'i, a site with abundant preferential flow paths (PFPs) and high short-range order (SRO) mineral content. We characterized lateral and vertical changes in Δ 14 C, SRO mineral content, C-functional group chemistry, and microbial community composition to elucidate the contributions of multiple protection mechanisms to OM preservation. Consistent with our expectation, SRO mineral content and Δ 14 C were strongly correlated (R 2 = 0.95), indicating strong mineral protection of OM throughout the profile. Surprisingly, distance from PFP was also a significant predictor of Δ 14 C and improved model fit, particularly in the shallow horizons (R 2 = 0.97). Elevated C/N ratios, decreased microbial abundance, and greater SRO mineral content suggest nitrogen limitations and enhanced mineral protection constrain OM turnover with distance from PFPs in deep, subsurface mineral horizons. Steady microbial abundance, increasing putative anaerobe abundance, and changes in C-functional group chemistry indicate oxygen limitations constrain OM turnover in the matrix of shallow mineral horizons. Given that oxygen and nutrient limitations contribute to OM preservation in this high SRO system—an exemplar of mineral protection—resource limitations may play an even more important role in OM preservation in other well-structured soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Convergence Analysis of the Alternating Anderson–Picard Method for Nonlinear Fixed-Point Problems

Anderson acceleration (AA) has been widely used to solve nonlinear fixed-point problems due to its rapid convergence. This work focuses on a variant of AA in which multiple Picard iterations are performed between each AA step, referred to as the Alternating Anderson–Picard (AAP) method. Furthermore, despite introducing more “slow” Picard iterations, this method has been shown to be efficient and even more robust in both linear and nonlinear cases. However, there is a lack of theoretical analysis for AAP in the nonlinear case. In this paper, we address this gap by establishing the equivalence between AAP and a multisecant-GMRES method that uses GMRES to solve a multisecant linear system at each iteration. From this perspective, we show that AAP “converges” to the Newton-GMRES method. Specifically, as the residual approaches zero, the multisecant matrix, the approximate Jacobian inverse, the search direction, and the optimization gain of AAP converge to their counterparts in the Newton-GMRES method. These connections provide insights for analyzing the asymptotic convergence properties of AAP. Consequently, we show that AAP is locally 𝑞-linear convergent and provide an upper bound for the convergence factor of AAP. To validate the theoretical results, numerical examples are provided.

Anderson acceleration↗
NASA NTRS2015

Characterization of Meteorites by Focused Ion Beam Sectioning: Recent Applications to CAIs and Primitive Meteorite Matrices

Focused ion beam (FIB) sectioning has revolutionized preparation of meteorite samples for characterization by analytical transmission electron microscopy (TEM) and other techniques. Although FIB is not "non-destructive" in the purest sense, each extracted section amounts to no more than nanograms (approximately 500 cubic microns) removed intact from locations precisely controlled by SEM imaging and analysis. Physical alteration of surrounding material by ion damage, fracture or sputter contamination effects is localized to within a few micrometers around the lift-out point. This leaves adjacent material intact for coordinate geochemical analysis by SIMS, microdrill extraction/TIMS and other techniques. After lift out, FIB sections can be quantitatively analyzed by electron microprobe prior to final thinning, synchrotron x-ray techniques, and by the full range of state-of-the-art analytical field-emission scanning transmission electron microscope (FE-STEM) techniques once thinning is complete. Multiple meteorite studies supported by FIB/FE-STEM are currently underway at NASA-JSC, including coordinated analysis of refractory phase assemblages in CAIs and fine-grained matrices in carbonaceous chondrites. FIB sectioning of CAIs has uncovered epitaxial and other overgrowth relations between corundum-hibonite-spinel consistent with hibonite preceding corundum and/or spinel in non-equilibrium condensation sequences at combinations of higher gas pressures, dust-gas enrichments or significant nebular transport. For all of these cases, the ability of FIB to allow for coordination with spatially-associated isotopic data by SIMS provides immense value for constraining the formation scenarios of the particular CAI assemblage. For carbonaceous chondrites matrix material, FIB has allowed us to obtain intact continuous sections of the immediate outer surface of Murchison (CM2) after it has been experimentally ion processed to simulate solar wind space weathering. The surface amorphization and loss of OH produced by the irradiation provides important clues regarding space weathering on primitive asteroids such as the OSIRIS-Rex target 101955 Bennu.

Christoffersen, Roy↗
DOE OSTI2025

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Electromagnetic scattering from a class of open-ended waveguide discontinuities

A relatively simple high frequency analysis of electromagnetic scattering from a class of open-ended waveguide discontinuites was developed. The waveguides are composed of perfectly-conducting sections in which the electromagnetic field can be written as the sum of waveguide modes. Junctions are formed at the open end and also within interior regions where different sections are joined. The reflection and transmission properties of each junction are described in terms of a scattering matrix which is determined by combining the modal ray picture with high frequency techniques such as the Geometrical Theory of Diffraction (GTD), the Equivalent Current Method (ECM), and modifications of the Physical Theory of Diffraction (PTD). A new set of equivalent circuits are employed in this ECM analysis which leads to a simple treatment of many types of junction discontinuities. Also, a new procedure is presented to improve the efficiency of the aperture integration at the open end which is required in the PTD procedure for finding the fields radiated from (or coupled to) the open end. Once the scattering matrices are determined, they are then combined using a self-consistent multiple scattering method to obtain the total scattered fields.

Altintas, A.↗