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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 811 records · Page 45

Real-Time Reed-Solomon Decoder

Generic Reed-Solomon decoder fast enough to correct errors in real time in practical applications designed to be implemented in fewer and smaller very-large-scale integrated, VLSI, circuit chips. Configured to operate in pipelined manner. One outstanding aspect of decoder design is that Euclid multiplier and divider modules contain Galoisfield multipliers configured as combinational-logic cells. Operates at speeds greater than older multipliers. Cellular configuration highly regular and requires little interconnection area, making it ideal for implementation in extraordinarily dense VLSI circuitry. Flight electronics single chip version of this technology implemented and available.

Maki, Gary K.↗

Simulation of a Real-Time Local Data Integration System over East-Central Florida

The Applied Meteorology Unit (AMU) simulated a real-time configuration of a Local Data Integration System (LDIS) using data from 15-28 February 1999. The objectives were to assess the utility of a simulated real-time LDIS, evaluate and extrapolate system performance to identify the hardware necessary to run a real-time LDIS, and determine the sensitivities of LDIS. The ultimate goal for running LDIS is to generate analysis products that enhance short-range (less than 6 h) weather forecasts issued in support of the 45th Weather Squadron, Spaceflight Meteorology Group, and Melbourne National Weather Service operational requirements. The simulation used the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) software on an IBM RS/6000 workstation with a 67-MHz processor. This configuration ran in real-time, but not sufficiently fast for operational requirements. Thus, the AMU recommends a workstation with a 200-MHz processor and 512 megabytes of memory to run the AMU's configuration of LDIS in real-time. This report presents results from two case studies and several data sensitivity experiments. ADAS demonstrates utility through its ability to depict high-resolution cloud and wind features in a variety of weather situations. The sensitivity experiments illustrate the influence of disparate data on the resulting ADAS analyses.

Case, Jonathan↗

Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information

Here, we study the problem of designing a distributed observer for an LTI system over a time-varying communication graph. The limited existing work on this topic imposes various restrictions either on the observation model or on the sequence of communication graphs. In contrast, we propose a single-time-scale distributed observer that works under mild assumptions. Specifically, our communication model only requires strong-connectivity to be preserved over non-overlapping, contiguous intervals that are even allowed to grow unbounded over time. We show that under suitable conditions that bound the growth of such intervals, joint observability is sufficient to track the state of any discrete-time LTI system exponentially fast, at any desired rate. We also develop a variant of our algorithm that is provably robust to worst-case adversarial attacks, provided the sequence of graphs is sufficiently connected over time. The key to our approach is the notion of a "freshness-index" that keeps track of the age-of-information being diffused across the network. Such indices enable nodes to reject stale estimates of the state, and, in turn, contribute to stability of the error dynamics.

42 ENGINEERING↗

The Effects of Wave Escape on Fast Magnetosonic Wave Turbulence in Solar Flares

One of the leading models for electron acceleration in solar flares is stochastic acceleration by weakly turbulent fast magnetosonic waves ("fast waves"). In this model, large-scale flows triggered by magnetic reconnection excite large-wavelength fast waves, and fast-wave energy then cascades from large wavelengths to small wavelengths. Electron acceleration by large-wavelength fast-waves is weak, and so the model relies on the small-wavelength waves produced by the turbulent cascade. In order for the model to work, the energy cascade time for large-wavelength fast waves must be shorter than the time required for the waves to propagate out of the solar-flare acceleration region. To investigate the effects of wave escape, we solve the wave kinetic equation for fast waves in weak turbulence theory, supplemented with a homogeneous wave-loss term.We find that the amplitude of large-wavelength fast waves must exceed a minimum threshold in order for a significant fraction of the wave energy to cascade to small wavelengths before the waves leave the acceleration region.We evaluate this threshold as a function of the dominant wavelength of the fast waves that are initially excited by reconnection outflows.

Pongkitiwanichakul, Peera↗

Expansion dynamics and chemistry evolution in ultrafast laser filament produced plasmas

Laser ablation in conjunction with optical emission spectroscopy is a potential non-contact, standoff detection method for all elements in the periodic table and certain isotopes such as radionuclides. Currently, significant development efforts are on-going to use ultrafast laser filaments for remote sensing. The application of filaments is of particular interest in extending the range of stand-off capability associated with elemental and isotopic detection via laser-induced breakdown spectroscopy. In this study, we characterize the expansion dynamics and chemical evolution of filament-produced uranium (U) plasmas. Laser filaments are generated in the laboratory by loosely focusing 35 femtosecond (fs), 6 milli Joule (mJ) pulses in air. Two-dimensional spectrally-integrated and time-resolved imaging was performed to study hydrodynamics and evolution of U atomic and UO molecular emission in filament-produced U plasmas. Our results highlight that filament ablation of U plasmas gives a cylindrical plasma plume morphology with an appearance of plume splitting into slow and fast moving components at later times of its evolution. Emission from the slow-moving region shows no distinct spectral features (i.e. broadband-like) and is contributed in part by nanoparticles generated during ultrafast laser ablation. Additionally, we find U atoms and U oxide molecules (i.e. UO, UxOy) co-exist in the filament produced plasma, which can be attributed to the generation of low-temperature plasma conditions during filament ablation

(140.3440) Laser-induced breakdown, (280.5395) Pla↗

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

OpenUniverse2024: a shared, simulated view of the sky for the next generation of cosmological surveys

The OpenUniverse2024 simulation suite is a cross-collaboration effort to produce matched simulated imaging for multiple surveys as they would observe a common simulated sky. Both the simulated data and associated tools used to produce it are intended to uniquely enable a wide range of studies to maximize the science potential of the next generation of cosmological surveys. We have produced simulated imaging for approximately 70 deg 2 of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Wide-Fast-Deep survey and the Nancy Grace Roman Space Telescope High-Latitude Wide-Area Survey, as well as overlapping versions of the ELAIS-S1 Deep-Drilling Field for LSST and the High-Latitude Time-Domain Survey for Roman. OpenUniverse2024 includes (i) an early version of the updated extragalactic model called Diffsky, which substantially improves the realism of optical and infrared photometry of objects, compared to previous versions of these models; (ii) updated transient models that extend through the wavelength range probed by Roman and Rubin; and (iii) improved survey, telescope, and instrument realism based on up-to-date survey plans and known properties of the instruments. It is built on a new and updated suite of simulation tools that improves the ease of consistently simulating multiple observatories viewing the same sky. The approximately 400 TB of synthetic survey imaging and simulated universe catalogs are publicly available, and we preview some scientific uses of the simulations.

large-scale structure of Universe↗

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Decker, Arthur J.↗

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Decker, Arthur J.↗

Ion-rich Acceleration during an Eruptive Flux Rope Event in a Multiple Null-point Configuration

We report on the γ-ray emission above 100 MeV from the GOES M3.3 flare SOL2012-06-03. The hard X-ray (HXR) and microwave emissions have typical time profiles with a fast rise to a well-defined peak followed by a slower decay. The >100 MeV emission during the prompt phase displayed a double-peaked temporal structure with the first peak following the HXR and microwaves, and the second one, about 3 times stronger, occurring 17 ± 2 s later. The time profiles seem to indicate two separate acceleration mechanisms at work, where the second γ-ray peak reveals a potentially pure or at least largely dominant ion acceleration. The Atmospheric Imaging Assembly imaging shows a bright elliptical ribbon and a transient brightening in the northwestern (NW) region. Nonlinear force-free extrapolations at the time of the impulsive peaks show closed field lines connecting the NW region to the southeastern part of the ribbon, and the magnetic topology revealed clusters of nulls. These observations suggest a spine-and-fan geometry, and based on these observations, we interpret the second γ-ray peak as being due to the predominant acceleration of ions in a region with multiple null points. The >100 MeV emission from this flare also exhibits a delayed phase with an exponential decay of roughly 350 s. We find that the delayed emission is consistent with ions being trapped in a closed flux tube with gradual escape via their loss cone to the chromosphere.

Pesce-Rollins, Melissa [Istituto Nazionale di Fisi↗

Decision Support Systems for Launch and Range Operations Using Jess

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Thirumalainambi, Rajkumar↗

Advancing Li-plating detection: Motivating a multi-signal correlation approach

Facilitating fast charging in lithium-ion batteries (LiBs) is often linked to Li-plating, which harms performance, longevity, and safety. Early detection of Li-plating is essential for rapid technological development and for preventing performance deterioration and ensuring safety during operation. Fast and real-time detection, using commonly collected measurements like voltage (V), current (I), temperature (T), and pressure (P), is highly desirable. Existing standalone methods relying on electrochemical and mechanical signatures, using half, smaller, or specially designed cells often operated at lower temperatures, fail to account for real-world fast-charging conditions. These signatures may also have inherent unreliability in aged LiBs, a phenomenon currently not-well understood. All these uncertainties have complicated practical implementation of a robust Li-plating detection technique. This study, through multiple case studies involving real-world fast-charging conditions using automotive-grade 11.6 Ah LiBs, shows that many single signal-based diagnostic techniques may be inadequate to detect Li-plating. Among various signatures, end-of-charge rest pressure, differential pressure-sensing, and end-of-charge rest voltage were identified as particularly useful in detecting Li-plating. Furthermore, A multi-signal-based detection technique is shown to be more robust in detecting Li-plating. Using both fresh and aged cells, the results and analysis highlight how detection capabilities are influenced by various factors, including battery design, size, charging speed, operating temperature, and degradation level. Adopting such a multi-signal Li-plating detection approach may be instrumental in the rapid development of battery technology in laboratories, as well as ensuring the enhanced safety of next-generation LiBs in real-world fast-charging applications.

25 ENERGY STORAGE↗

A New Method to Correct the Electrochemical Concentration Cell (ECC) Ozonesonde Time Response and its Implications for "Background Current" and Pump Efficiency

The electrochemical concentration cell (ECC) ozonesonde has been the main instrument for in situ profiling of ozone worldwide; yet, some details of its operation, which contribute to the ozone uncertainty budget, are not well understood. Here, we investigate the time response of the chemical reactions inside the ECC and how corrections can be used to remove some systematic biases. The analysis is based on the understanding that two reaction pathways involving ozone occur inside the ECC that generate electrical currents on two very different timescales. The main fast-reaction pathway with a time constant of about 20 s is due the conversion of iodide to molecular iodine and the generation of two free electrons per ozone molecule. A secondary slow-reaction pathway involving the buffer generates an excess current of about 2 %–10 % with a time constant of about 25 min. This excess current can be interpreted as what has conventionally been considered the “background current”. This contribution can be calculated and removed from the measured current instead of the background current. Here we provide an algorithm to calculate and remove the contribution of the slow-reaction pathway and to correct for the time lag of the fast-reaction pathway. This processing algorithm has been applied to ozonesonde profiles at Costa Rica and during the Central Equatorial Pacific Experiment (CEPEX) as well as to laboratory experiments evaluating the performance of ECC ozonesondes. At Costa Rica, where a 1 % KI, 1/10th buffer solution is used, there is no change in the derived total ozone column; however, in the upper troposphere and lower stratosphere, average reported ozone concentrations increase by up to 7 % and above 30 km decrease by up to 7 %. During CEPEX, where a 1 % KI, full-buffer solution was used, ozone concentrations are increased mostly in the upper troposphere, with no change near the top of the profile. In the laboratory measurements, the processing algorithms have been applied to measurements using the majority of current sensing solutions and using only the stronger pump efficiency correction reported by Johnson et al. (2002). This improves the accuracy of the ECC sonde ozone profiles, especially for low ozone concentrations or large ozone gradients and removes systematic biases relative to the reference instruments. In the surface layer, operational procedures prior to launch, in particular the use of filters, influence how typical gradients above the surface are detected. The correction algorithm may report gradients that are steeper than originally reported, but their uncertainty is strongly influenced by the prelaunch procedures.

electrochemical concentration cell (ECC) ozonesond↗

Fluorescence lifetime measurements using photon pair correlations generated via spontaneous parametric down conversion (SPDC)

We have used photon pair correlations generated via spontaneous parametric downconversion (SPDC) to measure the fluorescence lifetime of the organic dye rhodamine 6 G, demonstrating that fluorescence lifetime measurements can be achieved using a continuous wave (CW) laser, without pulsed or modulated lasers. Our entangled photon method, quantum fluorescence lifetime (Q-FL) measurements, uses one photon to excite fluorescence and the resulting fluorescence photon is timed and referenced to the arrival time of the other entangled photon. Thus, we can exploit the short timescale of photon pair correlations to conduct experiments that are typically carried out with pulsed lasers and we show that the inherent timing of the photons is fast enough to resolve the nanosecond scale fluorescence lifetime of the sample. This measurement paves the way towards using the time correlations of entangled photons for fluorescence imaging; capitalizing on the presence of fast, sub-100 ps correlations that have not been demonstrated classically.

Eshun, Audrey (ORCID:0000000167697082)↗

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explicit large time-step schemes for the shallow water equations

Modifications to explicit finite difference schemes for solving the shallow water equations for meteorological applications by increasing the time step for the fast gravity waves are analyzed. Terms associated with the gravity waves in the shallow water equations are treated on a coarser grid than those associated with the slow Rossby waves, which contain much more of the available energy and must be treated with higher accuracy, enabling a several-fold increase in time step without degrading the accuracy of the solution. The method is presented in Cartesian and spherical coordinates for a rotating earth, using generalized leapfrog, frozen coefficient, and Fourier filtering finite difference schemes. Computational results verify the numerical stability of the approach.

Turkel, E.↗

A first-order global model of Late Cenozoic climatic change: Orbital forcing as a pacemaker of the ice ages

The development of a theory of the evolution of the climate of the earth over millions of years can be subdivided into three fundamental, nested, problems: (1) to establish by equilibrium climate models (e.g., general circulation models) the diagnostic relations, valid at any time, between the fast-response climate variables (i.e., the 'weather statistics') and both the prescribed external radiative forcing and the prescribed distribution of the slow response variables (e.g., the ice sheets and shelves, the deep ocean state, and the atmospheric CO2 concentration); (2) to construct, by an essentially inductive process, a model of the time-dependent evolution of the slow-response climatic variables over time scales longer than the damping times of these variables but shorter than the time scale of tectonic changes in the boundary conditions (e.g., altered geography and elevation of the continents, slow outgassing, and weathering) and ultra-slow astronomical changes such as in the solar radiative output; and (3) to determine the nature of these ultra-slow processes and their effects on the evolution of the equilibrium state of the climatic system about which the above time-dependent variations occur. All three problems are discussed in the context of the theory of the Quaternary climate, which will be incomplete unless it is embedded in a more general theory for the fuller Cenozoic that can accommodate the onset of the ice-age fluctuations. We construct a simple mathematical model for the Late Cenozoic climatic changes based on the hypothesis that forced and free variations of the concentration of atmospheric greenhouse gases (notably CO2), coupled with changes in the deep ocean state and ice mass, under the additional 'pacemaking' influence of earth-orbital forcing, are primary determinants of the climate state over this period. Our goal is to illustrate how a single model governing both very long term variations and higher frequency oscillatory variations in the Pleistocene can be formulated with relatively few adjustable parameters.

Saltzman, Barry↗