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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Enhancing Network Visibility and Security through Tensor Analysis

The increasing size, variety, rate of growth and change, and complexity of network data has warranted advanced network analysis and services. Tools that provide automated analysis through traditional or advanced signature-based systems or machine learning classifiers suffer from practical difficulties. These tools fail to provide comprehensive and contextual insights into the network when put to practical use in operational cyber security. In this paper, we present an effective tool for network security and traffic analysis that uses high-performance data analytics based on a class of unsupervised learning algorithms called tensor decompositions. The tool aims to provide a scalable analysis of the network traffic data and also reduce the cognitive load of network analysts and be network-expert-friendly by presenting clear and actionable insights into the network. With this being said, In this paper, we demonstrate the successful use of the tool in two completely diverse operational cyber security environments, namely, (1) security operations center (SOC) for the SCinet network at the SuperComputing (SC) Conference in 2016 and 2017 and (2) Reservoir Labs’ Local Area Network (LAN). In each of these environments, we produce actionable results for cyber security specialists including (but not limited to) (1) finding malicious network traffic involving internal and external attackers using port scans, SSH brute forcing, and NTP amplification attacks, (2) uncovering obfuscated network threats such as data exfiltration using DNS port and using ICMP traffic, and (3) finding network misconfiguration and performance degradation patterns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
NASA NTRS1992

Angularly resolved X-ray photoelectron spectroscopy investigation of PTFE after prolonged space exposure

Monochromatized angularly resolved X-ray photoelectron spectroscopy (ARXPS) was used to study PTFE (Teflon) that had been exposed to an earth orbital environment for approximately six years. The primary interest of the research is on a very reactive component of this environment (atomic oxygen) which, because of the typical orbital velocities of a spacecraft, impinge on exposed surfaces with 5 eV energy. This presentation deals with the method of analysis, the findings as they pertain to a rather complex carbon, oxygen, and fluorine XPS peak analysis, and the character of the valence bands. An improved bias referencing method, based on ARXPS, is also demonstrated for evaluating specimen charging effects. It was found that the polymer molecule tends to resist the atomic oxygen attack by reorienting itself, so that the most electronegative CF3 groups are facing the incoming hyperthermal oxygen atoms. The implications of these findings to ground-based laboratory studies are discussed.

Dalins, I.↗
DOE OSTI2018

ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks

Stochastic simulation and modeling play an important role to elucidate the fundamental mechanisms in complex biochemical networks. The parametric sensitivity analysis of reaction networks becomes a powerful mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, due to overwhelming computational cost, parametric sensitivity analysis is a extremely challenging problem for stochastic models with a high-dimensional parameter space and for which existing approaches are very slow. Here we present an information-theoretic sensitivity analysis in path-space (ISAP) MATLAB package that simulates stochastic processes with various algorithms and most importantly implements a gradient-free approach to quantify the parameter sensitivities of stochastic chemical reaction network dynamics using the pathwise Fisher information matrix (PFIM; Pantazis, Katsoulakis, and Vlachos 2013). The sparse, block-diagonal structure of the PFIM makes its computational complexity scale linearly with the number of model parameters. As a result of the gradientfree and the sparse nature of the PFIM, it is highly suitable for the sensitivity analysis of stochastic reaction networks with a very large number of model parameters, which are typical in the modeling and simulation of complex biochemical phenomena. Finally, the PFIM provides a fast sensitivity screening method (Arampatzis, Katsoulakis, and Pantazis 2015) which allows it to be combined with any existing sensitivity analysis software.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

Unsteady, Transonic Flow Around Delta Wings Undergoing Coupled and Natural Modes Response: A Multidisciplinary Problem

The unsteady, three-dimensional Navier-Stokes equations coupled with the Euler equations of rigid-body dynamics are sequentially solved to simulate and analyze the aerodynamic response of a high angle of attack delta wing undergoing oscillatory motion. The governing equations of fluid flow and dynamics of the multidisciplinary problem are solved using a time-accurate solution of the laminar, unsteady, compressible, full Navier- Stokes equations with the implicit, upwind, Roe flux-difference splitting, finite-volume scheme and a four-stage Runge-Kutta scheme, respectively. The primary model under consideration consists of a 65 deg swept, sharp-edged, cropped delta wing of zero thickness at 20 deg angle of attack. In a freestream of Mach 0.85 and Reynolds number of 3.23 x 10(exp 6), the flow over the upper surface of the wing develops a complex shock system which interacts with the leading-edge primary vortices producing vortex breakdown. The effect of the oscillatory motion of the wing on the vortex breakdown and overall aerodynamic response is detailed to provide insight to the complicated physics associated with unsteady flows and the phenomenon of wing rock. Forced sinusoidal single and coupled mode rolling and pitching motion is presented for the wing in a transonic freestream. The Reynolds number, frequency of oscillation, and the phase angle are varied. Comparison between the single and coupled mode forced rolling and pitching oscillation cases illustrate the effects of coupling the motion. This investigation shows that even when coupled, forced rolling oscillation at a reduced frequency of 2(pi) eliminates the vortex breakdown which results in an increase in lift. The coupling effect for in phase forced oscillations show that the lift coefficient of the pitching-alone case and the rolling-moment coefficient of the rolling-alone case dominate the resulting response. However, with a phase lead in the pitching motion, the coupled motion results in a non-periodic response of the rolling moment. The second class of problems involve releasing the wing in roll to respond to the flowfield. Two models of sharp-edged delta wings, the previous 65 deg swept model and an 80 deg swept, sharp-edged delta wing, are used to observe the aerodynamic response of a wing free to roll in a transonic and subsonic freestream, respectively. These cases demonstrate damped oscillations, self-sustained limit cycle oscillations, and divergent rolling oscillations. Ultimately, an active control model using a mass injection system was applied on the surface of the wing to suppress the self-sustained limit cycle oscillation known as wing rock. Comparisons with experimental investigations complete this study, validating the analysis and illustrating the complex details afforded by computational investigations.

Menzies, Margaret Anne↗
DOE OSTI2019

In-Plane Thorium(IV), Uranium(IV), and Neptunium(IV) Expanded Porphyrin Complexes

In our research, we report a first series of in-plane thorium(IV), uranium(IV), and neptunium(IV) expanded porphyrin complexes. These actinide (An) complexes were synthesized using a hexa-aza porphyrin analogue, termed dipyriamethyrin, and the non-aqueous An(IV) precur-sors: ThCl 4 (DME) 2 , UCl 4 , and NpCl 4 (DME) 2 under conditions of in situ sodium bis(trimethylsilyl)amide deprotonation. The molecu-lar and electronic structure of the ligand, each An(IV) complex, and a corresponding uranyl(VI) complex were characterized using NMR and UV-vis spectroscopies, as well as single crystal X-ray diffraction analysis. Computational analyses of these complexes, coupled with their structural features, provide support for the conclusion that a greater degree of covalency in the ligand-cation orbital interactions arises as the early actinide series is traversed from Th(IV) to U(IV) and Np(IV). The axial ligands in the current An(IV) complexes proved labile, allowing for the electronic features of these complexes to be further modified.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dicopper( i ) complexes of a binucleating, dianionic, naphthyridine bis(amide) ligand

The dinucleating ligand, 1,8-naphthyridine-2,7-bis(2,6-diisopropylphenyl)carboxamide (NBDA), was synthesized by palladium-catalyzed aminocarbonylation. This ligand was treated with two equivalents of mesitylcopper(I) in the presence of [nBu4N]X (X = Cl, N3) to give the anionic complexes [nBu4N][Cu2(NBDA)(μ-Cl)] and [nBu4N][Cu2(NBDA)(μ-N3)]. Treatment of H2NBDA with mesitylcopper(I) and two equivalents of xylyl isocyanide led to the formation of a charge-neutral dicopper(I) complex, [Cu2(NBDA)(CNXyl)2], displaying two isocyanide ligands, each terminally bound to one of the copper atoms. The complexes were characterized by NMR and IR spectroscopy, as well as by single-crystal X-ray diffraction analysis. Electrochemical characterization of the complexes using cyclic voltammetry revealed a reversible ligand-based reduction between -1.65 and -2.0 V vs. Fc/Fc+. DFT calculations suggest a more ionic bonding character and weaker Cu-Cu interactions in the NBDA complexes compared to those with other 1,8-naphthyridine-based ligands. This is congruent with intermetallic separations of over 3 Å induced by relatively strong coordination of the copper atoms to the amide nitrogen donor atoms observed in the solid state molecular structures.

Sévery, Laurent↗
DOE OSTI2022

A Simulation-based Method for Correcting Mode Coupling in CMB Angular Power Spectra

Modern cosmic microwave background (CMB) analysis pipelines regularly employ complex time-domain filters, beam models, masking, and other techniques during the production of sky maps and their corresponding angular power spectra. However, these processes can generate couplings between multipoles from the same spectrum and from different spectra, in addition to the typical power attenuation. Within the context of pseudo-C ℓ based, MASTER-style analyses, the net effect of the time-domain filtering is commonly approximated by a multiplicative transfer function, F ℓ , that can fail to capture mode mixing and is dependent on the spectrum of the signal. To address these shortcomings, we have developed a simulation-based spectral correction approach that constructs a two-dimensional transfer matrix, ${J}_{{\ell }{\ell }^{\prime} }$, which contains information about mode mixing in addition to mode attenuation. We demonstrate the application of this approach on data from the first flight of the Spider balloon-borne CMB experiment.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

Multidisciplinary design optimization using response surface analysis

Aerospace conceptual vehicle design is a complex process which involves multidisciplinary studies of configuration and technology options considering many parameters at many values. NASA Langley's Vehicle Analysis Branch (VAB) has detailed computerized analysis capabilities in most of the key disciplines required by advanced vehicle design. Given a configuration, the capability exists to quickly determine its performance and lifecycle cost. The next step in vehicle design is to determine the best settings of design parameters that optimize the performance characteristics. Typical approach to design optimization is experience based, trial and error variation of many parameters one at a time where possible combinations usually number in the thousands. However, this approach can either lead to a very long and expensive design process or to a premature termination of the design process due to budget and/or schedule pressures. Furthermore, one variable at a time approach can not account for the interactions that occur among parts of systems and among disciplines. As a result, vehicle design may be far from optimal. Advanced multidisciplinary design optimization (MDO) methods are needed to direct the search in an efficient and intelligent manner in order to drastically reduce the number of candidate designs to be evaluated. The payoffs in terms of enhanced performance and reduced cost are significant. A literature review yields two such advanced MDO methods used in aerospace design optimization; Taguchi methods and response surface methods. Taguchi methods provide a systematic and efficient method for design optimization for performance and cost. However, response surface method (RSM) leads to a better, more accurate exploration of the parameter space and to estimated optimum conditions with a small expenditure on experimental data. These two methods are described.

Unal, Resit↗
DOE OSTI2022

Revisiting the Bonding Model for Gold(I) Species: The Importance of Pauli Repulsion Revealed in a Gold(I)‐Cyclobutadiene Complex

Abstract Understanding the bonding of gold(I) species has been central to the development of gold(I) catalysis. Herein, we present the synthesis and characterization of the first gold(I)‐cyclobutadiene complex, accompanied with bonding analysis by state‐of‐the‐art energy decomposition analysis methods. Analysis of possible coordination modes for the new species not only confirms established characteristics of gold(I) bonding, but also suggests that Pauli repulsion is a key yet hitherto overlooked element. Additionally, we obtain a new perspective on gold(I)‐bonding by comparison of the gold(I)‐cyclobutadiene to congeners stabilized by p‐, d‐, and f‐block metals. Consequently, we refine the gold(I) bonding model, with a delicate interplay of Pauli repulsion and charge transfer as the key driving force for various coordination motifs. Pauli repulsion is similarly determined as a significant interaction in Au I ‐alkyne species, corroborating this revised understanding of Au I bonding.

Wong, Zeng Rong↗
DOE OSTI2022

Revisiting the Bonding Model for Gold(I) Species: The Importance of Pauli Repulsion Revealed in a Gold(I)–Cyclobutadiene Complex

Understanding the bonding of gold(I) species has been central to the development of gold(I) catalysis. Herein, we present the synthesis and characterization of the first gold(I)-cyclobutadiene complex, accompanied with bonding analysis by state-of-the-art energy decomposition analysis methods. Analysis of possible coordination modes for the new species not only confirms established characteristics of gold(I) bonding, but also suggests that Pauli repulsion is a key yet hitherto overlooked element. Additionally, we obtain a new perspective on gold(I)-bonding by comparison of the gold(I)-cyclobutadiene to congeners stabilized by p-, d-, and f-block metals. Consequently, we refine the gold(I) bonding model, with a delicate interplay of Pauli repulsion and charge transfer as the key driving force for various coordination motifs. Finally, Pauli repulsion is similarly determined as a significant interaction in Au I -alkyne species, corroborating this revised understanding of Au I bonding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Co(II) Substitution Enhances the Esterase Activity of a de Novo Designed Zn(II) Carbonic Anhydrase

Abstract Carbonic Anhydrases (CAs) have been a target forde novoprotein designers due to the simplicity of the active site and rapid rate of the reaction. The first reported mimic contained a Zn(II) bound to three histidine imidazole nitrogens and an exogenous water molecule, hence closely mimicking the native enzymes’ first coordination sphere. Co(II) has served as an alternative metal to interrogate CAs due to its d 7 electronic configuration for more detailed solution characterization. We present here the Co(II) substituted [Co(II)(H 2 O/OH − )] N (TRIL2WL23H) 3 n+ that behaves similarly to native Co(II) substituted human‐CAs. Like the Zn(II) analogue, the cobalt‐derivative at slightly basic pH is incapable of hydrolyzing p‐nitrophenylacetate (pNPA); however, as the pH is increased a significant activity develops, which at pH values above 10 eventually yields a catalytic efficiency that exceeds that of the [Zn(II)(OH − )] N (TRIL2WL23H) 3 + peptide complex. X‐ray absorption analysis is consistent with an octahedral species at pH 7.5 that converts to a 5‐coordinate species by pH 11. UV‐vis spectroscopy can monitor this transition, giving a pK a for the conversion of 10.3. We assign this conversion to the formation of a 5‐coordinate Co(II)(N imid ) 3 (OH)(H 2 O) species. The pH dependent kinetic analysis indicates the maximal rate (k cat ), and thus the catalytic efficiency (k cat /K m ), follow the same pH profile as the spectroscopic conversion to the pentacoordinate species. This correlation suggests that the chemically irreversible ester hydrolysis corresponds to the rate determining process.

Chemistry↗
DOE OSTI2023

Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform

Abstract Industrial microbes and bio-derived products have emerged as an integral component of the bioeconomy, with an array of agricultural, bioenergy, and biomedical applications. However, the rapid development of microbial biotechnology raises concerns related to environmental escape of laboratory microbes, detection and tracking thereof, and resultant impact upon native ecosystems. Indeed, though wild-type and genetically modified microbes are actively deployed in industrial bioprocesses, an understanding of microbial interactivity and impact upon the environment is severely lacking. In particular, the persistence and sustained ecosystem impact of industrial microbes following laboratory release or unintentional laboratory escape remains largely unexplored. Herein, we investigate the applicability of soil-sorghum mesocosms for the ecological risk assessment of the industrial microbe, Saccharomyces cerevisiae . We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a terrestrial ecosystem perturbation event over a 30-day time course. The platform enables reproducible, high-sensitivity tracking of S. cerevisiae in a complex soil microbiome and analysis of the impact upon abiotic soil characteristics and soil microbiome population dynamics and diversity. The resultant data indicate that even though S. cerevisiae is relatively short-lived in the soil, a single perturbation event can have sustained impact upon mesocosm soil composition and underlying microbial populations in our system, underscoring the necessity for more comprehensive risk assessment and development of mitigation and biocontainment strategies in industrial bioprocesses.

09 BIOMASS FUELS↗
DOE OSTI2024

Reinforcement learning for block decomposition of planar CAD models

Abstract The problem of hexahedral mesh generation of general CAD models has vexed researchers for over 3 decades and analysts often spend more than 50% of the design-analysis cycle time decomposing complex models into simpler blocks meshable by existing techniques. The decomposed blocks are required for generating good quality meshes (tilings of quadrilaterals or hexahedra) suitable for numerical simulations of physical systems governed by conservation laws. We present a novel AI-assisted method for decomposing (segmenting) planar CAD (computer-aided design) models into well shaped rectangular blocks. Even though the simple examples presented here can also be meshed using many conventional methods, we believe this work is proof-of-principle of a AI-based decomposition method that can eventually be generalized to complex 2D and 3D CAD models. Our method uses reinforcement learning to train an agent to perform a series of optimal cuts on the CAD model that result in a good quality block decomposition. We show that the agent quickly learns an effective strategy for picking the location and direction of the cuts and maximizing its rewards. This paper is the first successful demonstration of an agent autonomously learning how to perform this block decomposition task effectively, thereby holding the promise of a viable method to automate this challenging process for more complex cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Regularized Variance-Reduced Modified Extragradient Method for Stochastic Hierarchical Games

We consider an N -player hierarchical game in which the i th player’s objective comprises of an expectation-valued term, parametrized by rival decisions, and a hierarchical term. Such a framework allows for capturing a broad range of stochastic hierarchical optimization problems, Stackelberg equilibrium problems, and leader-follower games. We develop an iteratively regularized and smoothed variance-reduced modified extragradient framework for iteratively approaching hierarchical equilibria in a stochastic setting. We equip our analysis with rate statements, complexity guarantees, and almost-sure convergence results. We then extend these statements to settings where the lower-level problem is solved inexactly and provide the corresponding rate and complexity statements. Our model framework encompasses many game theoretic equilibrium problems studied in the context of power markets. We present a realistic application to the study of virtual power plants, emphasizing the role of hierarchical decision making and regularization. Preliminary numerics suggest that empirical behavior compares well with theoretical guarantees.

Tikhonov regularization↗
DOE OSTI2025

Radiochronometric discordance in cast uranium metal: a multi-laboratory intercomparison exercise

Here, the model age of a nuclear material is crucial in nuclear forensic analysis. Uranium metals with complex production histories often exhibit discordant model ages from the 230 Th– 234 U and 231 Pa– 235 U chronometers. Recent studies involving targeted uranium metal castings have enhanced our understanding of decay product behavior during casting, aiding nuclear forensic interpretation. Building on this prior work, forensics laboratories at Atomic Weapons Establishment (AWE), Lawrence Livermore National Laboratory (LLNL), and Los Alamos National Laboratory (LANL) conducted an interlaboratory comparison to investigate spatial heterogeneity in uranium metal cast under controlled conditions. Each laboratory measured samples of a mixed feedstock and its corresponding cast product. This work furthers our understanding of discordant model ages and the use of discordance as a signature to enhance confidence in interpretations of radiochronometric data for nuclear forensics.

230Th/234U↗
DOE OSTI2019

Effect of Tool Offset and Rotational Speed in Dissimilar Friction Stir Welding of AISI 304 Stainless Steel and Mild Steel

In the present study, dissimilar friction stir welding was carried out between stainless steel (UNS S30400) and mild steel (UNS G10080) plates of 4 mm thickness using a tungsten carbide tool. The influence of tool rotational speeds (600, 875 rpm) and tool offsets (0.6, 1.2 mm) on mechanical properties, i.e., hardness, tensile strength, and impact toughness of welded joints was investigated. Maximum tensile strength of the joint was about 107.6% of the mild steel under rotational speed of 875 rpm and tool offset of 1.2 mm. The maximum hardness reached in the stir zone was about 281 HV{sub 0.5} due to the phase transformations and grain refinement. Charpy’s notch toughness of the welded joints was observed lower than the base materials. The microstructural characterizations were carried by using an optical microscope, and FESEM–EDS analysis which revealed the complex material mixing and material movement during the welding. Tungsten-rich bands were observed in the weld micrograph especially toward the advancing side. During this study, various wear mechanisms like oxidation wear, abrasive wear, and adhesion wear were responsible for the degradation of tungsten carbide tool.

36 MATERIALS SCIENCE↗