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

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Probing oxygen vacancy concentration and homogeneity in solid-oxide fuel-cell cathode materials on the subunit-cell level

Oxygen vacancy distributions and dynamics directly control the operation of solid-oxide fuel cells and are intrinsically coupled with magnetic, electronic, and transport properties of oxides. For understanding the atomistic mechanisms involved during operation of the cell it is highly desirable to know the distribution of vacancies on the unit cell scale. Here, we develop an approach for direct mapping of oxygen vacancy concentrations based on local lattice parameter measurements by scanning transmission electron microscopy. The concept of chemical expansivity is demonstrated to be applicable on the sub-unit cell level: local stoichiometry variations produce local lattice expansion that can be quantified. The vacancy mapping reveals strong difference in magnetic properties of lanthanum strontium cobaltite model systems induced by different substrate symmetry, opening pathways for structural tuning of the vacancy concentrations and their gradients.

Oxygen Stoichimetry↗
DOE OSTI2018

Prioritized Threshold Allocation for Distributed Frequency Response

Higher penetration of renewable generation will increase the demand for adequate (and cost-effective) controllable resources on the grid that can mitigate and contain the contingencies locally before it can cause a network-wide collapse. However, end-use constraints can potentially lead to load unavailability when an event occurs, leading to unreliable demand response services. Sensors measurements and knowledge of the local load dynamics could be leveraged to improve the performance of load control algorithms. In the context of hierarchical frequency response using ensemble of switching loads, we present a metric to evaluate the fitness of each device in successfully providing the ancillary service. Furthermore a fitness-based assignment of control set-points is formulated which achieves reliable performance under different operating conditions. Monte Carlo simulations of ensembles of electric water heaters and residential air-conditioners are performed to evaluate the proposed control algorithm.

Nandanoori, Sai Pushpak↗
DOE OSTI2023

A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering

The Ensemble Kalman Filters (EnKF) employ a Monte-Carlo approach to represent covariance information, and are affected by sampling errors in operational settings where the number of model realizations is much smaller than the model state dimension. To alleviate the effects of these errors EnKF relies on model-specific heuristics such as covariance localization, which takes advantage of the spatial locality of correlations among the model variables. This work proposes an approach to alleviate sampling errors that utilizes a locally averaged-in-time dynamics of the model, described in terms of a climatological covariance of the dynamical system. We use this covariance as the target matrix in covariance shrinkage methods, and develop a stochastic covariance shrinkage approach where synthetic ensemble members are drawn to enrich both the ensemble subspace and the ensemble transformation. We additionally provide for a way in which this methodology can be localized similar to the state-of-the-art LETKF method, and that for a certain model setup, our methodology significantly outperforms it.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Partnership for Edge Physics Simulation (EPSI)

We propose to develop advanced simulation codes, based upon an extreme parallelism, first principles kinetic approach, to address the challenges associated with the edge region of magnetically confined plasmas. This work is relevant to both existing magnetic fusion facilities and essential for next-generation burning plasma experiments, such as ITER where success is critically dependent upon H-mode operation achieving an edge pedestal of sufficient height for good core plasma performance without producing deleterious large scale edge localized instabilities. The plasma edge presents a well-known set of multi-physics, multi-scale problems involving complex 3D magnetic geometry. Perhaps the greatest computational challenge is the lack of scale separation – temporal scales for drift waves, Alfven waves, ELM dynamics for example have strong overlap. Similar overlap occurs on the spatial scales for the ion poloidal gyro-radius, drift wave and pedestal width. The traditional approach of separating fusion problems into weakly interacting spatial or temporal domains clearly breaks down in the edge. A full kinetic model (full-f model) must be solved to understand and predict the edge physics including non-equilibrium thermodynamic issues arising from the magnetic topology (the open field lines producing a spatially sensitive velocity hole), plasma wall interactions, neutral and atomic physics. The plan here is to model these phenomena within a comprehensive first principles set of equations without the need for the insurmountable multiple-codes coupling issues by building on the XGC1 code developed under the SciDAC Proto-FSP Center for Plasma Edge Simulation (CPES). This proposal includes the critical participants in the XGC1 development. We propose enhancing the capability of XGC1 by including all the important turbulence physics contained in kinetic ion and electron electromagnetic dynamics, by extending the PIC technology to incorporate several positive features found in the Eulerian grid technology, combining the coarse grained XGC0 code into it with a multiscale projective time integration technique to be developed in the project for experimental time scale simulation of the edge multi-physics, and by implementing modern computational technologies to move forward with the extreme scale heterogeneous hardware/software platform development. Ultra-fast edge localized instabilities, involving compressional Alven modes, will be studied using a proper MHD or two-fluid codes employing kinetic closure information from XGC. The proposed research integrates the most important physical processes on overlapping temporal and spatial scales, to study (i) transitions and thresholds for enhanced confinement regimes, (ii) the predictive understanding of the edge pedestal formation, structure and dynamics, (iii) the effect of the edge plasma on the core confinement, (iv) the physics of Edge Localized Modes and their suppression or mitigation via external control techniques, and (v) the heat load on the material wall. Our approach will implement physical models that are valid in their relevant collisionality regimes for current experiments and future burning plasma devices. Comparisons with experimental data will be made at multiple levels including characterization of turbulence dynamics, flux-gradient responses in the energy, particle and momentum channels, and observations of global phenomena such as L-H transitions, momentum generation, ELM dynamics, ELM-free regimes and the tokamak density limit. The proposal team has established strong connections, through joint membership, with other organizations that will be critical for success. These include FASTMath, SUPER and QUEST Institutes respectively for meshing tools and solvers; code performance tuning and uncertainty quantification as well as a proposed Data Management and Visualization Institute.. We will also be teaming with ongoing fusion SciDAC’s: CSWPI for RF-edge plasmas interactions; CEMM for the M3D MHD simulations and with PEPSC for incorporation of energetic particle physics. Finally, the team includes representatives from each of the major U.S. experimental facilities who will coordinate the validation program and the development of synthetic diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1982

Structures and Dynamics Division research and technology plans, FY 1982

Computational devices to improve efficiency for structural calculations are assessed. The potential of large arrays of microprocessors operating in parallel for finite element analysis is defined, and the impact of specialized computer hardware on static, dynamic, thermal analysis in the optimization of structural analysis and design calculations is determined. General aviation aircraft crashworthiness and occupant survivability is also considered. Mechanics technology required for design coefficient, fault tolerant advanced composite aircraft components subject to combined loads, impact, postbuckling effects and local discontinuities are developed.

Bales, K. S.↗
NASA NTRS1985

Overview of Structural Response: Probabilistic Structural Analysis

Advanced analysis methods are required to predict accurately the structural response (static, transient, cyclic, etc.) and accompanying local stresses in space propulsion system components operating in a fatigue environment consisting of complex thermal and mechanical load spectra. The probabilistic approach to structural response consists of the following program elements: (1) composite load spectra, (2) probabilistic structural analysis methods development, (3) probabilitic finite element theory, (4) probabilistic structural analysis application, (5) structural tailoring of turbopump blades, (6) unified theory of dynamic creep buckling/ratcheting, (7) creep buckling/ratcheting analyzer, and (8) nonlinear COBSTRAN development. Research activities on all of these program elements (except the creep buckling/ratcheting analyzer) are under way.

Chamis, C. C.↗
DOE OSTI2016

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

JIGSAW: Preference-directed, co-operative scheduling

Techniques that enable humans and machines to cooperate in the solution of complex scheduling problems have evolved out of work on the daily allocation and scheduling of Tactical Air Force resources. A generalized, formal model of these applied techniques is being developed. It is called JIGSAW by analogy with the multi-agent, constructive process used when solving jigsaw puzzles. JIGSAW begins from this analogy and extends it by propagating local preferences into global statistics that dynamically influence the value and variable ordering decisions. The statistical projections also apply to abstract resources and time periods--allowing more opportunities to find a successful variable ordering by reserving abstract resources and deferring the choice of a specific resource or time period.

Linden, Theodore A.↗
DOE OSTI2020

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

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

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
DOE OSTI2015

Nanomotor dynamics in a chemically oscillating medium

Synthetic nanomotors powered by chemical reactions have potential uses as cargo transport vehicles in both in vivo and in vitro applications. In many situations, motors will have to operate in out-of-equilibrium complex chemically reacting media, which supply fuel to the motors and remove the products they produce. Using molecular simulation and mean-field theory, this paper describes some of the new features that arise when a chemically powered nanomotor, operating through a diffusiophoretic mechanism, moves in an environment that supports an oscillatory chemical reaction network. It is shown how oscillations in the concentrations in chemical species in the environment give rise to oscillatory motor dynamics. More importantly, since the catalytic reactions on the motor that are responsible for its propulsion couple to the bulk phase reaction network, the motor can change its local environment. This process can give rise to distinctive spatiotemporal structures in reaction-diffusion media that occur as a result of active motor motion. Such locally induced nonequilibrium structure will play an important role in applications that involve motor dynamics in complex chemical media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring

In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. Here, to demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Design and Stability of Load-Side Primary Frequency Control in Power Systems

We present a systematic method to design ubiquitous continuous fast-acting distributed load control for primary frequency regulation in power networks, by formulating an optimal load control (OLC) problem where the objective is to minimize the aggregate cost of tracking an operating point subject to power balance over the network. We prove that the swing dynamics and the branch power flows, coupled with frequency-based load control, serve as a distributed primal-dual algorithm to solve OLC. We establish the global asymptotic stability of a multimachine network under such type of load-side primary frequency control. These results imply that the local frequency deviations on each bus convey exactly the right information about the global power imbalance for the loads to make individual decisions that turn out to be globally optimal. Simulations confirm that the proposed algorithm can rebalance power and resynchronize bus frequencies after a disturbance with significantly improved transient performance.

Zhao, CH↗
NASA NTRS1974

Evaluation of localized muscle fatigue using power spectral density analysis of the electromyogram

Surface electromyograms (EMGs) taken from three upper torso muscles during a push-pull task were analyzed by a power spectral density technique to determine the operational feasibility of the technique for identifying changes in the EMGs resulting from muscular fatigue. The EMGs were taken from four subjects under two conditions (1) in shirtsleeves and (2) in a pressurized space suit. This study confirmed that frequency analysis of dynamic muscle activity is capable of providing reliable data for many industrial applications where fatigue may be of practical interest. The results showed significant effects of the pressurized space suit on the pattern of shirtsleeve fatigue responses of the muscles. The data also revealed (1) reliable differences between muscles in fatigue-induced responses to various locations in the reach envelope at which the subjects were required to perform the push-pull exercise and (2) the differential sensitivity of muscles to the various reach positions in terms of fatigue-related shifts in EMG power.

Lafevers, E. V.↗
DOE OSTI2025

Looking at extremal black holes from very far away

Near-extremal black holes are subject to large quantum effects, which modify their low-temperature thermodynamic behavior. Hitherto, these quantum effects were analyzed by separating the geometry into the near-horizon region and its exterior. It is desirable to understand and reproduce such corrections from the full higher-dimensional asymptotically flat or AdS geometry’s perspective. We address this question in this article and fill this gap. Specifically, we find off-shell eigenmodes of the quadratic fluctuation operator of the Euclidean gravitational dynamics, with eigenvalues that vanish linearly with temperature. We illustrate this for BTZ and neutral black holes with hyperbolic horizons in AdS in Einstein-Hilbert theory, and for the charged black holes in Einstein-Maxwell theory. The linear scaling with Matsubara frequency, which is a distinctive feature of the modes, together with the fact that their wavefunctions localize close to the horizon as we approach extremality, identifies them as responsible for the aforementioned quantum effects. We provide a contour prescription to deal with the sign indefiniteness of the Euclidean Einstein-Maxwell action, which we derive to aid our analysis. We also resolve a technical puzzle regarding modes associated with rotational isometries in stationary black hole spacetimes.

AdS-CFT Correspondence↗
DOE OSTI2026

Asynchronous Grid Connections Providing Fast-Frequency Response: System Integration Study

This paper presents an integration study for the recent power electronic-based fast-frequency response technology, "asynchronous grid connection" which operates as an aggregator for behind-the-meter resources and distributed generators. Both technical feasibility and techno-economic viability studies are presented. The fast-frequency response characteristics, validated against Power Hardware-in-the-Loop experiments, are integrated into an IEEE 9- bus system in DigSilent PowerFactory for system-level dynamic analysis. It demonstrates that droop-based control enhancements to local distributed generators allow their aggregation to provide grid-supporting functionalities and participate in the ancillary service markets. To this end, a long-term simulation embedding the system within the ancillary service market framework of PJM has been performed. The fast-frequency response regulation is subsequently used to calculate the potential revenue and project the results on a 15-year investment horizon. Finally, the techno-economic analysis provides recommendations for enhancements to access the full potential of distributed generators on a technical and regulatory level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Serial multiplier arrays for parallel computation

Arrays of systolic serial-parallel multiplier elements are proposed as an alternative to conventional SIMD mesh serial adder arrays for applications that are multiplication intensive and require few stored operands. The design and operation of a number of multiplier and array configurations featuring locality of connection, modularity, and regularity of structure are discussed. A design methodology combining top-down and bottom-up techniques is described to facilitate development of custom high-performance CMOS multiplier element arrays as well as rapid synthesis of simulation models and semicustom prototype CMOS components. Finally, a differential version of NORA dynamic circuits requiring a single-phase uncomplemented clock signal introduced for this application.

Winters, Kel↗
NASA NTRS2019

Quantum Technologies for UAS (QTech)

Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.

Quantum Computing↗