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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 703 records · Page 39

Using Stage Level Microseismic Analysis to Gain Insight into Fracture Efficiency and Completion Effectiveness

Microseismic event density heat maps at sequential time intervals during the treatment of individual completion stages have been developed to better understand fracture behavior on a stage level. Animating these heat maps through time on a single stage provides fascinating visual insights into the dynamic sequencing of populations of events, event timing and their likely genesis, providing a new way of visualizing and interpreting microseismic data sets. This technique leverages heat-map benefits from URTEC 2674376, excluding microseismic event clusters that may obscure or skew statistical analysis of the event densities, thus allowing for more accurate assessment of geologic features, stimulated rock volume, near-field concentration of events due to varying cluster spacing, fracture efficiency and stress shadowing. Far-field microseismic events prior to ramp up of treatment pressure are clearly indicated from this technique that cannot be observed with standard heat maps with certain completion designs. Unambiguous changes in microseismic event character from these far-field pre-ramp up events to those near-field events occurring at the onset of pressure are also observed. Applying a stage by stage approach on packages of wells and different locations provides robust statistical conclusions pertaining to reservoir behavior during well completion.

Wang, Iris↗

Ulysses observations of magnetic waves due to newborn interstellar pickup ions. I. New observations and linear analysis

We have examined Ulysses magnetic field data using dynamic spectrogram techniques that compute wave amplitude, polarization, and direction of propagation over a broad range of frequencies and time. Events were identified that showed a strong polarization signature and an enhancement of power above the local proton gyrofrequency. We perform a statistical study of 502 wave events in an effort to determine when, where, and why they are observed. Most notably, we find that waves arising from newborn interstellar pickup ions are relatively rare and difficult to find. The quantities normally employed in theories of wave growth are neutral atom density and quantities related to their ionization and the subsequent dynamics such as wind speed, solar wind flux, and magnetic field orientation. We find the observations of waves to be largely uncorrelated to these quantities except for mean field direction where quasi-radial magnetic fields are favored and solar wind proton flux where wave observations appear to be favored by low flux conditions which runs contrary to theoretical expectations of wave generation. It would appear that an explanation based on source physics and instability growth rates alone is not adequate to account for the times when these waves are seen.

79 ASTRONOMY AND ASTROPHYSICS↗

Memory Analysis Tool

This tool traces all memory accesses to stack (static allocation) and heap (dynamic allocation) on a trace run in a particular hardware and then estimates execution time on given arbitrary hardware configurations for hardware design space exploration. It can also compute memory access statistics, such as reuse distance.

Sato, Kento↗

Mammalian complex III heme dynamics studied with pump-probe spectroscopy and red light illuminations

The electronic or molecular mechanisms which initiate photobiomodulation (PBM) in cells are not yet fully understood. Porcine complex III (C-III) of the electron transport chain was characterized with transient absorption spectroscopy (TAS). Then we applied our recently developed continuous wave laser coupled TAS procedure (CW-TAS) to investigate the effect of red light irradiances on the heme dynamics of C-III in its c 1 reduced state. The time constants associated with the axial ligand photodissociation were found to be 3.3 ± 0.3 ps for the oxidized state and 4.9 ± 0.4 ps for the c 1 reduced state. The analysis of the CW-TAS procedure yielded no significant changes in the C-III heme dynamics. We rule out the possibility of 635 nm CW light at 4.7 mW/cm 2 inducing a PBM effect on the heme dynamic of C-III, specifically with the photodissociation of its axial ligand.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Feed Injection Strategies on Fluidization Dynamics for Biomass Thermochemical Conversion

To better understand some of the key parameters that control biomass conversion processes in dense granular beds, an efficient computational framework for large-scale simulations of dense, reactive particulate flows using a Lagrange-Euler approach has been developed. This framework is applied here to the investigation of feed injection in a hot fluidized bed reactor, and how it may impact the biomass conversion dynamics. A simple, pseudo-two dimensional configuration is adopted to facilitate the parametric study. Chemical processes are modeled using global kinetics that accurately reproduce particle mass loss and gas release. A posteriori analysis of particle heating rate, mixing and segregation, along with products distribution and residence time inside the reactor is performed for different injection strategies, and compared to non-reactive cases. Results highlight some non-trivial coupling between chemistry and flow dynamics.

09 BIOMASS FUELS↗

A Quantitative Analysis of Aqueous Nanofilm Rupture by Molecular Dynamic Simulation

In this study, we used molecular dynamic (MD) simulations of the rupture process for a water film to define and determine the critical rupture time (CRT). This new approach could be an important method for authentically defining and determining the rupture point of a water film and associated phenomena. We were able to generically predict the CRT and the critical thickness of the water film. Then, we studied the effect of ions on the film rupture process. Our results showed that addition of sodium chloride did not significantly affect on the stability of the water film. Results from MD simulations, when compared with results from experimental measurements, can provide insights into the film rupture process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DAGSENS: Directed Acyclic Graph Based Direct and Adjoint Transient Sensitivity Analysis for Event-Driven Objective Functions

We present DAGSENS, a new theory for parametric transient sensitivity analysis of Differential Algebraic Equation systems (DAEs), such as SPICE-level circuits. The key ideas behind DAGSENS are, (1) to represent the entire sequence of computations, starting from DAE parameters, all the way up to the objective function whose sensitivity is needed, as a Directed Acyclic Graph (DAG) called the "sensitivity DAG", and (2) to compute the required sensitivities efficiently (with time complexity linear in the size of the sensitivity DAG) by leveraging dynamic programming techniques to traverse the DAG. DAGSENS is simple, elegant, and easy-to-understand compared to existing sensitivity analysis approaches; for example, in DAGSENS, one can switch between direct and adjoint transient sensitivities just by changing the direction of DAG traversal (i.e., topological order vs. reverse topological order). Also, DAGSENS is significantly more powerful than existing sensitivity analysis approaches because it allows one to compute the sensitivities of a much more general class of objective functions, including those defined based on "events" that occur during a transient simulation (e.g., a node voltage crossing a particular threshold, a phase-locked loop (PLL) achieving lock, a signal reaching its maximum/minimum value during a transient run, etc.). In this paper, we apply DAGSENS to compute the sensitivities of important event-driven performance metrics in several real-world electronic and biological applications, including high-speed communication (featuring sub-systems such as I/0 links and PLLs), statistical cell library characterization, and gene expression in Drosophila embryos.

42 ENGINEERING↗

Fuel Cycle System Analysis Implications of Sodium-Cooled Metal-Fueled Fast Reactor Transuranic Conversion Ratio

If advanced fuel cycles are to include a large number of fast reactors (FRs), what should be the transuranic (TRU) conversion ratio (CR)? The nuclear energy era started with the assumption that they should be breeder reactors (CR > 1), but the full range of possible CRs eventually received attention. For example, during the recent U.S. Global Nuclear Energy Partnership program, the proposal was burner reactors (CR < 1). Yet, more recently, Massachusetts Institute of Technology's "Future of the Nuclear Fuel Cycle" proposed CR [approximately] 1. Meanwhile, the French company EDF remains focused on breeders. At least one of the reasons for the differences of approach is different fuel cycle objectives. To clarify matters, this paper analyzes the impact of TRU CR on many parameters relevant to fuel cycle systems and therefore spans a broad range of topic areas. The analyses are based on a FR physics parameter scan of TRU CR from 0 to [approximately]1.8 in a sodium-cooled metal-fueled FR (SMFR), in which the fuel from uranium-oxide-fueled light water reactors (LWRs) is recycled directly to FRs and FRs displace LWRs in the fleet. In this instance, the FRs are sodium cooled and metal fueled. Generally, it is assumed that all TRU elements are recycled, which maximizes uranium ore utilization for a given TRU CR and waste radiotoxicity reduction and is consistent with the assumption of used metal fuel separated by electrochemical means. In these analyses, the fuel burnup was constrained by imposing a neutron fluence limit to fuel cladding to the same constant value. This paper first presents static, time-independent measures of performance for the LWR [right arrow] FR fuel cycle, including mass, heat, gamma emission, radiotoxicity, and the two figures of merit for materials for weapon attractiveness developed by C. Bathke et al. No new fuel cycle will achieve a static equilibrium in the foreseeable future. Therefore, additional analyses are shown with dynamic, time-dependent measures of performance including uranium usage, TRU inventory, and radiotoxicity to evaluate the complex impacts of transition from the current uranium-fueled LWR system, and other more realistic impacts that may not be intuited from the time-independent steady-state conditions of the end-state fuel cycle. These analyses were performed using the Verifiable Fuel Cycle Simulation Model VISION. Compared with static calculations, dynamic results paint a different picture of option space and the urgency of starting a FR fleet. For example, in a static analysis, there is a sharp increase in uranium utilization as CR exceeds 1.0 (burner versus breeder). However, in dynamic analyses that examine uranium use over the next 1 to 2 centuries, behavior as CR crosses the 1.0 threshold is smooth, and other parameters such as the time required outside of reactors to recycle fuel become important. Overall, we find that there is no unambiguously superior value of TRU CR; preferences depend on the relative importance of different fuel cycle system objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

3D Motion of DNA-Au Nanoconjugates in Graphene Liquid Cell Electron Microscopy

Liquid-phase transmission electron microscopy (TEM) can probe and visualize dynamic events with structural or functional details at the nanoscale in a liquid medium. Prior efforts have focused on the growth and transformation kinetics of hard material systems, relying on their stability under electron beam. Our recently developed graphene liquid cell technique pushed the spatial resolution of such imaging to the atomic scale but still focused on growth trajectories of metallic nanocrystals. Here, we adopt this technique to imaging three-dimensional (3D) dynamics of soft materials instead, double strand (dsDNA) connecting Au nanocrystals as one example, at nanometer resolution. We show first that a graphene liquid cell can seal an aqueous sample solution of a lower vapor pressure than previously investigated well against the high vacuum in TEM. Then, from quantitative analysis of real time nanocrystal trajectories, we show that the status and configuration of dsDNA dictate the motions of linked nanocrystals throughout the imaging time of minutes. This sustained connecting ability of dsDNA enables this unprecedented continuous imaging of its dynamics via TEM. Moreover, the inert graphene surface minimizes sample-substrate interaction and allows the whole nanostructure to rotate freely in the liquid environment; we thus develop and implement the reconstruction of 3D configuration and motions of the nanostructure from the series of 2D projected TEM images captured while it rotates. In addition to further proving the nanoconjugate structural stability, this reconstruction demonstrates 3D dynamic imaging by TEM beyond its conventional use in seeing a flattened and dry sample. Altogether, we foresee the new and exciting use of graphene liquid cell TEM in imaging 3D biomolecular transformations or interaction dynamics at nanometer resolution.

3D motion↗

Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers

We report the first congruent integration of HPC, AI, and multiscale modeling (MSM) for solving a mainstream biomechanical problem of thrombogenesis involving 6 million particles at record molecular-scale resolutions in space and at simulation rates of milliseconds per day. The two supercomputers, the IBM Summit-like AiMOS and our University’s SeaWulf, are used for scalability analysis of, and production runs with, the LAMMPS with our customization and AI augmentation and they attained optimal simulation speeds of 3,077 µs/day and 266 µs/day respectively. The long-time and large scales simulations enable the first study of the integrated platelet flowing, flipping, aggregating dynamics in one dynamically-coupled production run. The platelets’ angular and translational speeds, membrane particles’ speeds, and the membrane stress distributions are presented for the analysis of platelets’ aggregations.

Zhu, Yicong↗

In-Situ Blade Strain Measurements and Fatigue Analysis of a Cross-Flow Turbine Operating in a Tidal Flow

Cross-flow turbines (CFTs) are inherently unsteady devices with regards to operating principle and loading. By improving our understanding of the dynamic loading on these turbines, we hope to better inform CFT design, improve survivability, and reduce overall costs. The University of New Hampshire (UNH) and the National Renewable Energy Laboratory (NREL) collaborated on a project to instrument and test a four-bladed New Energy Corp. vertical axis cross-flow turbine in a real tidal flow. One blade from the 3.2 m diameter x 1.7 m height turbine was instrumented with eight full-bridge strain gauges along the span of the blade. The turbine was then deployed at the UNH-Atlantic Marine Energy Center (AMEC) Tidal Energy Test Site in Portsmouth, NH. Time-synchronized measurements of blade strain, inflow, thrust, rotational speed, and electrical output were obtained to characterize blade loading under various conditions. The blade strain was examined to assess the dynamic loading and conduct a fatigue analysis on the device.

blade strain↗

Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local and long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.

97 MATHEMATICS AND COMPUTING↗

Temporal Expression-based Analysis of Metabolism

Metabolic flux is frequently rerouted through cellular metabolism in response to dynamic changes in the intra- and extra-cellular environment. Capturing the mechanisms underlying these metabolic transitions in quantitative and predictive models is a prominent challenge in systems biology. Progress in this regard has been made by integrating high-throughput gene expression data into genome-scale stoichiometric models of metabolism. Here, we extend previous approaches to perform a Temporal Expression-based Analysis of Metabolism (TEAM). We apply TEAM to understanding the complex metabolic dynamics of the respiratorily versatile bacterium Shewanella oneidensis grown under aerobic, lactate-limited conditions. TEAM predicts temporal metabolic flux distributions using time-series gene expression data. Increased predictive power is achieved by supplementing these data with a large reference compendium of gene expression, which allows us to take into account the unique character of the distribution of expression of each individual gene. We further propose a straightforward method for studying the sensitivity of TEAM to changes in its fundamental free threshold parameter θ, and reveal that discrete zones of distinct metabolic behavior arise as this parameter is changed. By comparing the qualitative characteristics of these zones to additional experimental data, we are able to constrain the range of θ to a small, well-defined interval. In parallel, the sensitivity analysis reveals the inherently difficult nature of dynamic metabolic flux modeling: small errors early in the simulation propagate to relatively large changes later in the simulation. We expect that handling such “history-dependent” sensitivities will be a major challenge in the future development of dynamic metabolic-modeling techniques.

59 BASIC BIOLOGICAL SCIENCES↗

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchical conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Delamination-Assisted Ultrafast Wrinkle Formation in a Freestanding Film

Freestanding films provide a versatile platform for materials engineering thanks to additional structural motifs not found in films with a substrate. A ubiquitous example is wrinkles, yet little is known about how they can develop over as fast as a few picoseconds due to a lack of experimental probes to visualize their dynamics in real time on the nanoscopic scale. Here, we use time-resolved electron diffraction to directly observe light-activated wrinkling formation in freestanding La 2/3 Ca 1/3 MnO 3 films. Via a “lock-in” analysis of oscillations in the diffraction peak position, intensity, and width, we quantitatively reconstructed how wrinkles develop on the time scale of lattice vibration. Contrary to the common assumption of fixed boundary conditions, we found that wrinkle development is associated with ultrafast delamination at the film boundaries. Finally, our work provides a generic protocol to quantify wrinkling dynamics in freestanding films and highlights the importance of the film–substrate interaction in determining the properties of freestanding structures.

36 MATERIALS SCIENCE↗

Time-Dependent Reliability Analysis of Nuclear Hybrid Energy Systems

This paper focuses on developing a framework for comprehensive time-dependent reliability analysis of a nuclear hybrid energy system (NHES) design. Subsystem interactions of this complex integrated system under stochastic electricity demand and load-following operation capabilities requires dynamic reliability assessment of the NHES in component, subsystem and system level. In order to capture the dynamic operational behavior of critical systems and components, a detailed thermal hydraulic model of the NHES is generated using Modelica and tested under different electricity demand histories generated using RAVEN. The physical data (e.g., valve position, flow rates, inlet outlet water temperatures) gathered from Modelica used to calculate time-dependent failure rates through fitting data into the piecewise Weibull distribution. Optimum maintenance interval is calculated, and maintenance cost estimates based on the calculated reliability metric is presented for the selected component. Component time-dependent failure rates fed into the subsystem reliability model built with non-Markovian Stochastic Petri Nets. The component and subsystem failure rates are calculated and updated in every hour to characterize the system behavior appropriately and to understand operational reliability of the NHES design in a given time.

Guler Yigitoglu, Askin↗

An Idealized Test of the Response of the Community Atmosphere Model to Near‐Grid‐Scale Forcing Across Hydrostatic Resolutions

Abstract A set of idealized experiments are developed using the Community Atmosphere Model (CAM) to understand the vertical velocity response to reductions in forcing scale that is known to occur when the horizontal resolution of the model is increased. The test consists of a set of rising bubble experiments, in which the horizontal radius of the bubble and the model grid spacing are simultaneously reduced. The test is performed with moisture, through incorporating moist physics routines of varying complexity, although convection schemes are not considered. Results confirm that the vertical velocity in CAM is to first‐order, proportional to the inverse of the horizontal forcing scale, which is consistent with a scale analysis of the dry equations of motion. In contrast, experiments in which the coupling time step between the moist physics routines and the dynamical core (i.e., the “physics” time step) are relaxed back to more conventional values results in severely damped vertical motion at high resolution, degrading the scaling. A set of aqua‐planet simulations using different physics time steps are found to be consistent with the results of the idealized experiments.

54 ENVIRONMENTAL SCIENCES↗